From b21ed35021b5530fe857ffd020e302170011a0c7 Mon Sep 17 00:00:00 2001 From: justin-ven <43171764+justin-ven@users.noreply.github.com> Date: Mon, 17 Nov 2025 12:04:53 +0100 Subject: [PATCH 1/5] merging of changes suggested by Andy Baxter in #223 --- input/InitialPopulations/compile/00_master.do | 16 +++--- .../compile/02_create_UKHLS_variables.do | 49 +++++++++++++++++- input/reg_health_mental.xlsx | Bin 44586 -> 51647 bytes .../simpaths/data/ManagerRegressions.java | 18 +++---- src/main/java/simpaths/data/Parameters.java | 24 ++++----- .../java/simpaths/data/RegressionName.java | 6 +-- src/main/java/simpaths/model/Person.java | 39 +++++++------- 7 files changed, 98 insertions(+), 54 deletions(-) diff --git a/input/InitialPopulations/compile/00_master.do b/input/InitialPopulations/compile/00_master.do index 794d13c9a..f35f2aae5 100644 --- a/input/InitialPopulations/compile/00_master.do +++ b/input/InitialPopulations/compile/00_master.do @@ -36,13 +36,11 @@ set matsize 1000 *************************************************************************************/ * Working directory -*global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations" -*global dir_work "C:\Users\Patryk\Documents\SP_prep_pop" -global dir_work "D:\Dasha\ESSEX\ESPON 2024\UK\initial_populations" +global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations" +*global dir_work "D:\Dasha\ESSEX\ESPON 2024\UK\initial_populations" * Directory which contains do files global dir_do "${dir_work}/do" -*global dir_do "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations\compile" * Directory which contains data files global dir_data "${dir_work}/data" @@ -51,14 +49,12 @@ global dir_data "${dir_work}/data" global dir_log "${dir_work}/log" * Directory which contains UKHLS data -*global dir_ukhls_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\ukhls" -global dir_ukhls_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\ukhls" -*global dir_ukhls_data "C:\Users\Patryk\Documents\SP_prep_pop\ukhls\UKDA-6614-stata\stata\stata13_se\ukhls" +global dir_ukhls_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\ukhls" +*global dir_ukhls_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\ukhls" * Directory which contains WAS data -*global dir_was_data "J:\01 DATA\UK\was\wave8\stata\stata13_se" -global dir_was_data "D:\Dasha\UK-original-data\WAS\UKDA-7215-stata\stata\stata13_se" -*global dir_was_data "C:\Users\Patryk\Documents\WAS\UKDA-7215-stata\stata\stata13_se" +global dir_was_data "J:\01 DATA\UK\was\wave8\stata\stata13_se" +*global dir_was_data "D:\Dasha\UK-original-data\WAS\UKDA-7215-stata\stata\stata13_se" * Directory which contains original initial popultions global dir_ipop_orig "${dir_work}/original_initial_populations" diff --git a/input/InitialPopulations/compile/02_create_UKHLS_variables.do b/input/InitialPopulations/compile/02_create_UKHLS_variables.do index 0a1ad1183..1a3d178ae 100644 --- a/input/InitialPopulations/compile/02_create_UKHLS_variables.do +++ b/input/InitialPopulations/compile/02_create_UKHLS_variables.do @@ -331,6 +331,53 @@ lab values dhesp dhe replace dhesp=-9 if missing(dhesp) & idpartner>0 + +/**************************Subjective well-being: GHQ 0-12 score *****************************/ +/*dhm_ghq scghq2_dv "DEMOGRAPHIC: Subjective wellbeing (GHQ): rescaled to 0-12, assumed to be continuous" +This measure converts valid answers to 12 questions of the General Health Questionnaire (GHQ) to a +single scale by recoding the values of individual variables of 1 and 2 to 0, and values of 3 and 4 to 1 before summing them. +This produces a scale that ranges from 0 (indicating the least amount of distress) to 12 (indicating the greatest amount of distress). +*/ +gen dhm_ghq = scghq2_dv +replace dhm_ghq = . if scghq2_dv <0 +la var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): 0-12 score" +* fre dhm_ghq if dag>0 & dag<=18 +* fre dhm_ghq if dag>0 & dag<16 +gen scghq2_dv_miss_flag = (scghq2_dv == .) + +*Imputation for all: +* fre dag if missing(dhm_ghq) + +* fre scghq2_dv +recode scghq2_dv (-9/-1 . = .) +preserve +drop if dgn < 0 | dag<0 | dhe<0 +* eststo predict_dhm_ghq: reg dhm_ghq c.dag i.dgn i.swv i.dhe, vce(robust) // Physical health has a big impact, so included as covariate. +zinb dhm_ghq c.dag i.dgn i.swv i.dhe, inflate(dhm_ghq c.dag i.dgn i.swv i.dhe) vce(robust) // Physical health has a big impact, so included as covariate. +restore + +scalar lnalpha = _b[/lnalpha] +scalar theta = 1/exp(lnalpha) + +predict mu_hat, n // Count component mean (μ) +predict pi_hat, pr // Zero-inflation probability (π) + +gen u = runiform() +gen pred_score = . +replace pred_score = 0 if u < pi_hat // Structural zeros +replace pred_score = rnbinomial(theta, theta/(theta + mu_hat)) if u >= pi_hat // NB samples +replace pred_score = 12 if pred_score > 12 +replace pred_score = 0 if pred_score < 0 + + +cap gen dhm_ghq = 0 +replace dhm_ghq = scghq2_dv +lab var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): Caseness" + +gen dhm_ghq_flag = missing(dhm_ghq) +replace dhm_ghq = round(pred_score) if missing(dhm_ghq) + +/* Alternative method of GHQ caseness - binary cutoff at scghq2_dv <4 /*****************************Subjective well-being ***************************/ /*dhm scghq1_dv "DEMOGRAPHIC: Subjective wellbeing (GHQ): Likert Scale from 0 to 36, assumed to be continuous in the simulation." This measure converts valid answers to 12 questions of the General Health Questionnaire (GHQ) to a single scale by recoding so that @@ -390,7 +437,7 @@ replace dhm_ghq = 0 if scghq2_dv>=0 & scghq2_dv<4 replace dhm_ghq = 1 if scghq2_dv>=4 lab var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): Caseness" //fre dhm_ghq - +*/ /****************************Self-rated health health - mental and physical component summary scores SF12 ***************************/ /*SF-12 Mental Component Summary (MCS). 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8712 -> 8472 bytes .../training/population_initial_UK_2019.csv | 74388 ++++++++-------- 4 files changed, 37087 insertions(+), 37415 deletions(-) diff --git a/.gitignore b/.gitignore index 533686f79..2d83b7bf6 100644 --- a/.gitignore +++ b/.gitignore @@ -227,121 +227,15 @@ analysis/test_base_noalign.dta analysis/test_naive_noalign.dta analysis/test1.dta analysis/test2.dta -input/InitialPopulations/base/population_initial_UK_2010.csv -input/InitialPopulations/base/population_initial_UK_2011.csv -input/InitialPopulations/base/population_initial_UK_2012.csv -input/InitialPopulations/base/population_initial_UK_2013.csv -input/InitialPopulations/base/population_initial_UK_2014.csv -input/InitialPopulations/base/population_initial_UK_2015.csv -input/InitialPopulations/base/population_initial_UK_2016.csv -input/InitialPopulations/base/population_initial_UK_2017.csv -input/InitialPopulations/base/population_initial_UK_2018.csv -input/InitialPopulations/base/population_initial_UK_2019.csv 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zi$Idc6s`VS^eCRW+M2&c8)yg!(p;EW88O(l3b-K4d@c7aKLAJ~cC3RBA_44P3jXa2 z0SaOC{xb^D3Zuz`c#JL&Ixwer0Kw{s?3|PTO$fBYYGQXX>MYUy$q)c=f&qXC@cko! zg;+GNybX)uQw9IP%JV`#SrmkW1Z8Apc(ML=EG`A=OQBVMkhk6b7X>>dy>03Ay#TQP j`|iMLut-)(c1ObZ Date: Tue, 18 Nov 2025 10:27:50 +0100 Subject: [PATCH 4/5] new edits from daria --- input/InitialPopulations/compile/00_master.do | 6 +- .../compile/02_create_UKHLS_variables.do | 112 ++++++++++++++---- .../compile/08_wealth_to_ukhls.do | 4 +- .../compile/RegressionEstimates/master.do | 13 +- .../RegressionEstimates/reg_fertility.do | 4 +- .../reg_leaveParentalHome.do | 4 +- input/reg_fertility.xlsx | Bin 19179 -> 19183 bytes input/reg_labourSupplyUtility.xlsx | Bin 200692 -> 193878 bytes input/reg_leaveParentalHome.xlsx | Bin 13233 -> 13873 bytes 9 files changed, 103 insertions(+), 40 deletions(-) diff --git a/input/InitialPopulations/compile/00_master.do b/input/InitialPopulations/compile/00_master.do index daef7a650..3bce2c866 100644 --- a/input/InitialPopulations/compile/00_master.do +++ b/input/InitialPopulations/compile/00_master.do @@ -37,7 +37,7 @@ set matsize 1000 * Working directory global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations" -*global dir_work "D:\Dasha\ESSEX\ESPON 2024\UK\initial_populations" +*global dir_work "D:\Dasha\ESSEX\_SimPaths\_SimPaths_UK\initial_populations" * Directory containing do files global dir_do "${dir_work}/do" @@ -51,11 +51,11 @@ global dir_log "${dir_work}/log" * Directory containing UKHLS data global dir_ukhls_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\ukhls" -*global dir_ukhls_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\ukhls" +*global dir_ukhls_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\ukhls" //original_data * Directory containing BHPS data global dir_bhps_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\bhps" -*global dir_bhps_data "D:\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\bhps" +*global dir_bhps_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\bhps" //original_data_bhps * Directory containing WAS data global dir_was_data "J:\01 DATA\UK\was\wave8\stata\stata13_se" diff --git a/input/InitialPopulations/compile/02_create_UKHLS_variables.do b/input/InitialPopulations/compile/02_create_UKHLS_variables.do index c4f8b876e..9af78b69e 100644 --- a/input/InitialPopulations/compile/02_create_UKHLS_variables.do +++ b/input/InitialPopulations/compile/02_create_UKHLS_variables.do @@ -970,20 +970,58 @@ drop _merge - is at least 15 years younger than either of their parents - neither of their parents is of the state retirement age in that particular year & neither is retired */ +/* gen adultchildflag = (!missing(dagmother) | !missing(dagfather)) & dag >= $age_become_responsible & idpartner <= 0 replace adultchildflag = 0 if dag >= dagfather-15 & dag >= dagmother-15 //was previously or ==> replaced with & //fre adultchildflag replace adultchildflag = 0 if (dagpnsmother==1 | les_c4mother==4) & (dagpnsfather ==1 | les_c4father==4) +replace adultchildflag = 0 if (dagpnsmother==1 | les_c4mother==4) & missing(dagfather) +replace adultchildflag = 0 if (dagpnsfather==1 | les_c4father==4) & missing(dagmother) tab2 adultchildflag swv , row +* check +sum idmother +sum idfather +sum idpartner +fre dagmother +fre dagfather +fre dagpnsmother +fre dagpnsfather +fre les_c4mother +fre les_c4father +*/ + +cap gen adultchildflag = 0 + +replace adultchildflag = 1 if (idmother > 0 | idfather > 0) /// + & dag >= 17 & dag<=75 & idpartner <= 0 /*added upper age filter as the one used in LS model */ + +/* Exclude if both parents retired or at statutory retirement age */ +replace adultchildflag = 0 if dagpnsmother == 1 & dagpnsfather == . +replace adultchildflag = 0 if dagpnsmother == . & dagpnsfather == 1 +replace adultchildflag = 0 if dagpnsmother == 1 & dagpnsfather == 1 + +replace adultchildflag = 0 if les_c4mother == 4 & les_c4father == . +replace adultchildflag = 0 if les_c4mother == . & les_c4father == 4 +replace adultchildflag = 0 if les_c4mother == 4 & les_c4father == 4 + +replace adultchildflag = 0 if les_c4mother == 4 & dagpnsfather == 1 +replace adultchildflag = 0 if les_c4father == 4 & dagpnsmother == 1 + +/* Exclude if both parents < 15 years older than child */ +replace adultchildflag = 0 if (dagfather-dag)<=15 & dagmother == . +replace adultchildflag = 0 if dagfather == . & (dagmother-dag) <= 15 +replace adultchildflag = 0 if (dagfather-dag) <= 15 & (dagmother-dag)<= 15 + +//fre adultchildflag + /*Account for cases missing information replace adultchildflag = -9 if idmother>0 & /// - (dagmother==. | dagmother<0 | les_c4mother==. | les_c4mother<0) & dag >= 17 + (dagmother==. | dagmother<0 | les_c4mother==. | les_c4mother<0) & dag >= 17 & dag<=75 replace adultchildflag = -9 if idfather>0 & /// - (dagfather==. | dagfather<0 | les_c4father==. | les_c4father<0) & dag >= 17 -fre adultchildflag -2.7% have missing info on one of their parents, not sure if it is worth dropping them? -*/ + (dagfather==. | dagfather<0 | les_c4father==. | les_c4father<0) & dag >= 17 & dag<=75 +fre adultchildflag*/ +//2.7% have missing info on one of their parents, not sure if it is worth dropping them? /************************Household composition*********************************/ @@ -1169,6 +1207,7 @@ replace dukfr=49.8 if stm>=2023 lab var dukfr "UK General fertility rate (ONS)" fre dukfr +save "$dir_data\ukhls_pooled_all_obs_02.dta", replace /************************Number of newborn*************************/ /*NOTE: The approach below was not entirely correct for identifying newborns. @@ -1182,31 +1221,30 @@ fre dukfr cap gen child0 = 0 replace child0=1 if dag<=1 -cap drop dchpd -bysort idmother swv: egen dchpd= total(child0) if idmother>0 -fre dchpd +cap drop dchpd_old +bysort idmother swv: egen dchpd_old= total(child0) if idmother>0 +fre dchpd_old preserve -keep swv idmother dchpd +keep swv idmother dchpd_old rename idmother idperson -rename dchpd mother_dchpd +rename dchpd_old mother_dchpd_old drop if idperson<0 -collapse (max) mother_dchpd, by(idperson swv) -fre mother_dchpd +collapse (max) mother_dchpd_old, by(idperson swv) +fre mother_dchpd_old duplicates report idperson swv -save "$dir_data/mother_dchpd", replace +save "$dir_data/mother_dchpd_old", replace restore -merge 1:1 swv idperson using "$dir_data/mother_dchpd" , keepusing (mother_dchpd) +merge 1:1 swv idperson using "$dir_data/mother_dchpd_old" , keepusing (mother_dchpd_old) keep if _merge == 1 | _merge == 3 drop _merge -replace mother_dchpd=0 if dgn==1 -drop dchpd -rename mother_dchpd dchpd -lab var dchpd "Women's number of newborn children" +replace mother_dchpd_old=0 if dgn==1 +drop dchpd_old +rename mother_dchpd_old dchpd_old +lab var dchpd_old "Women's number of newborn children" */ - -save "$dir_data\ukhls_pooled_all_obs_02.dta", replace + ************************************************************************ * Number of newborn from "newborn" datasets ************************************************************************ @@ -1299,7 +1337,7 @@ rename pidp idperson save "${dir_data}/temp_parent_dchpd.dta", replace * Merge into main person-wave dataset -use "$dir_data\ukhls_pooled_all_obs_02.dta", clear +use "{$dir_data}\ukhls_pooled_all_obs_02.dta", clear merge 1:1 idperson swv using "${dir_data}/temp_parent_dchpd.dta" keep if _merge ==1 | _merge==3 drop _merge @@ -1328,14 +1366,36 @@ tab both_parents restore */ -* Note that for the estimates we will only keep newborns who are reported by mothers, but here we keep all reported newborns for each respondent +/* Note that for the estimates we will only keep newborns who are reported by mothers, but here we keep all reported newborns for each respondent tab2 swv dchpd if dgn==1, m row tab2 swv dchpd if dgn==0 & sprfm==1, m row tab2 swv dchpd if dgn==0 & sprfm==0, m row - +*/ +/*-------------------------------------------------------------* + | Compare dchpd_old vs dchpd across waves | + *------------------------------------------------------------- + +* Recode missing values to 0 in both variables +recode dchpd_old (.=0) +recode dchpd (.=0) + +gen dchpd_comp = . +replace dchpd_comp = 1 if dchpd_old > 0 & dchpd > 0 /* both show a birth */ +replace dchpd_comp = 2 if dchpd_old == 0 & dchpd > 0 /* only new shows a birth */ +replace dchpd_comp = 3 if dchpd_old > 0 & dchpd == 0 /* only old shows a birth */ +replace dchpd_comp = 4 if dchpd_old == 0 & dchpd == 0 /* both zero */ + +cap label define dchpd_comp_lbl 1 "Both>0" /// + 2 "New only>0" /// + 3 "Old only>0" /// + 4 "Both zero" +label values dchpd_comp dchpd_comp_lbl + +tab swv dchpd_comp if sprfm==1 +*/ /*****************************In educational age range*************************/ -gen sedag = 1 if dvage >= 16 & dvage <= 29 +cap gen sedag = 1 if dvage >= 16 & dvage <= 29 replace sedag = 0 if missing(sedag) la val sedag dummy la var sedag "Educ age range" @@ -1824,8 +1884,8 @@ replace l1_potential_earnings_hourly = 0 if missing(l1_potential_earnings_hourly * initialise wealth to missing gen liquid_wealth = -9 -gen tot_pen = -9 -gen nvmhome = -9 +//gen tot_pen = -9 +//gen nvmhome = -9 gen smp = -9 gen rnk = -9 gen mtc = -9 diff --git a/input/InitialPopulations/compile/08_wealth_to_ukhls.do b/input/InitialPopulations/compile/08_wealth_to_ukhls.do index 9ec9e7edd..f7c8e07ce 100644 --- a/input/InitialPopulations/compile/08_wealth_to_ukhls.do +++ b/input/InitialPopulations/compile/08_wealth_to_ukhls.do @@ -393,7 +393,9 @@ sum liquid_wealth [fweight=dwt2], detail * clean data and save *********************************************************************/ use ukhls_wealthtemp3, clear -drop dvage17 year gor gor2 sex nk na dhe2 dhesp2 grad gradsp emp empsp inci inc nk04i nk04 idnk04 dhe2grad dhe2ngrad dlltsdgrad dlltsdngrad empage single_woman single_man couple single ee ee2 was bu couple_ref pct dwt2 treat case person_id p_healths dlltsdsp healths wealth bu_rp tt dhe3 dhe4 dvage07 nk2 nk3 gor3 gor4 pct2 wealthi +drop dvage17 year gor gor2 sex nk na dhe2 dhesp2 grad gradsp emp empsp inci inc nk04i nk04 idnk04 dhe2grad dhe2ngrad /// +dlltsdgrad dlltsdngrad empage single_woman single_man couple single ee ee2 was bu couple_ref pct dwt2 treat case person_id /// +p_healths dlltsdsp healths wealth bu_rp tt dhe3 dhe4 dvage07 nk2 nk3 gor3 gor4 pct2 wealthi recode rnk smp mtc (missing = -9) label var rnk "matching level: 1 = most fine, 2, 3 = most coarse, 4=no match" label var smp "matching sample - number of matched candidates to choose from" diff --git a/input/InitialPopulations/compile/RegressionEstimates/master.do b/input/InitialPopulations/compile/RegressionEstimates/master.do index 4e4337a13..385db09a9 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/master.do +++ b/input/InitialPopulations/compile/RegressionEstimates/master.do @@ -88,11 +88,12 @@ global countyy "UK" /******************************************************************************* * ESTIMATION FILES *******************************************************************************/ - +/* do "${dir_do}/reg_education.do" +*/ do "${dir_do}/reg_leaveParentalHome.do" - +/* do "${dir_do}/reg_partnership.do" do "${dir_do}/reg_fertility.do" @@ -106,16 +107,16 @@ do "${dir_do}/reg_retirement.do" do "${dir_do}/reg_wages.do" do "${dir_do}/reg_income.do" - +*/ ******************************************************************************* * INTERNAL VALIDATION FILES ****************************************************************************** - +/* do "$dir_do_validation/int_val_education.do" - +*/ do "$dir_do_validation/int_val_leave_parental_home.do" - +/* do "$dir_do_validation/int_val_partnership.do" do "$dir_do_validation/int_val_fertility.do" diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do b/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do index c40bd79b5..645f32be7 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do @@ -143,7 +143,7 @@ mata: end * Export into Excel -putexcel set "$dir_results/reg_fertility", sheet("F1a") modify +putexcel set "$dir_results/reg_fertility", sheet("UK_F1a") modify putexcel B2 = matrix(b_trimmed) putexcel C2 = matrix(V_trimmed) @@ -296,7 +296,7 @@ mata: end * Export into Excel -putexcel set "$dir_results/reg_fertility", sheet("F1b") modify +putexcel set "$dir_results/reg_fertility", sheet("UK_F1b") modify putexcel B2 = matrix(b_trimmed) putexcel C2 = matrix(V_trimmed) diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do b/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do index 9c37f0f22..74653889a 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do @@ -37,7 +37,7 @@ xtset idperson swv * Info sheet -putexcel set "$dir_work/reg_leaveParentalHome", sheet("Info") replace +putexcel set "$dir_results/reg_leaveParentalHome", sheet("Info") replace putexcel A1 = "Description:" putexcel B1 = "Model parameters governing leaving parental home" putexcel A2 = "Authors: Patryk Bronka, Justin van de Ven, Daria Popova" @@ -52,7 +52,7 @@ putexcel A10 = "Notes:", bold putexcel B10 = "Added: ethnicity-4 cat (dot); covid dummies (y2020 y2021)" putexcel B11 = "DV is synchronised with the adult child definition" -putexcel set "$dir_work/reg_leaveParentalHome", sheet("Gof") modify +putexcel set "$dir_results/reg_leaveParentalHome", sheet("Gof") modify putexcel A1 = "Goodness of fit", bold diff --git a/input/reg_fertility.xlsx b/input/reg_fertility.xlsx index 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.../compile/07_was_wealth_data.do | 12 +- .../compile/08_wealth_to_ukhls.do | 49 +- .../compile/09_finalise_input_data.do | 45 +- .../compile/10_check_yearly_data.do | 88 +- .../compile/99_training_data.do | 15 +- .../RegressionEstimates/reg_education 2.do | 185 - .../RegressionEstimates/reg_fertility 2.do | 127 - .../RegressionEstimates/reg_health 2.do | 165 - .../reg_home_ownership 2.do | 101 - .../RegressionEstimates/reg_income 2.do | 416 - .../reg_leaveParentalHome 2.do | 112 - .../RegressionEstimates/reg_partnership 2.do | 155 - .../RegressionEstimates/reg_retirement 2.do | 117 - .../RegressionEstimates/reg_socialcare1 2.do | 194 - .../RegressionEstimates/reg_socialcare1.do | 9 +- .../RegressionEstimates/reg_socialcare2 2.do | 413 - .../RegressionEstimates/reg_socialcare2.do | 9 +- .../RegressionEstimates/reg_socialcare3 2.do | 414 - .../RegressionEstimates/reg_socialcare3.do | 3 +- .../RegressionEstimates/reg_wages 2.do | 512 - .../training/population_initial_UK_2019.csv | 74788 ++++++++-------- input/reg_education.xlsx | Bin 44718 -> 44778 bytes input/reg_health.xlsx | Bin 205466 -> 228264 bytes input/reg_labourSupplyUtility.xlsx | Bin 193878 -> 188810 bytes input/reg_socialcare.xlsx | Bin 336123 -> 339064 bytes input/reg_unemployment.xlsx | Bin 180736 -> 180057 bytes src/main/java/simpaths/data/Parameters.java | 61 +- .../simpaths/data/startingpop/DataParser.java | 14 +- src/main/java/simpaths/model/BenefitUnit.java | 876 +- .../java/simpaths/model/LabourMarket.java | 3 + src/main/java/simpaths/model/Person.java | 28 +- .../java/simpaths/model/decisions/States.java | 2 +- .../java/simpaths/model/enums/Labour.java | 11 +- .../expected/EmploymentStatistics1.csv | 16 +- .../expected/HealthStatistics1.csv | 48 +- .../integrationtest/expected/Statistics1.csv | 16 +- .../integrationtest/expected/Statistics21.csv | 16 +- .../integrationtest/expected/Statistics31.csv | 16 +- 41 files changed, 38563 insertions(+), 40486 deletions(-) delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_education 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_fertility 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_health 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_income 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_partnership 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_retirement 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2 2.do delete mode 100644 input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3 2.do 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-1337,7 +1337,7 @@ rename pidp idperson save "${dir_data}/temp_parent_dchpd.dta", replace * Merge into main person-wave dataset -use "{$dir_data}\ukhls_pooled_all_obs_02.dta", clear +use "${dir_data}\ukhls_pooled_all_obs_02.dta", clear merge 1:1 idperson swv using "${dir_data}/temp_parent_dchpd.dta" keep if _merge ==1 | _merge==3 drop _merge @@ -1883,12 +1883,17 @@ replace potential_earnings_hourly = 0 if missing(potential_earnings_hourly) replace l1_potential_earnings_hourly = 0 if missing(l1_potential_earnings_hourly) * initialise wealth to missing -gen liquid_wealth = -9 -//gen tot_pen = -9 -//gen nvmhome = -9 +gen total_wealth = -9 +gen total_pensions = -9 +gen housing_wealth = -9 +gen mortgage_debt = -9 gen smp = -9 gen rnk = -9 gen mtc = -9 +label var total_wealth "total wealth net of liabilities of benefit unit including housing, business and private (personal and occupational) pensions" +label var total_pensions "value of all private (personal and occupational) pensions of benefit unit" +label var housing_wealth "value of main home gross of mortgage debt of benefit unit" +label var mortgage_debt "total mortgage debt owed on main home of benefit unit" *check for duplicates in the pooled dataset duplicates tag idperson idhh swv, gen(dup) diff --git a/input/InitialPopulations/compile/07_was_wealth_data.do b/input/InitialPopulations/compile/07_was_wealth_data.do index 42b9e024d..b7796ab43 100644 --- a/input/InitialPopulations/compile/07_was_wealth_data.do +++ b/input/InitialPopulations/compile/07_was_wealth_data.do @@ -9,6 +9,14 @@ * NOTE: file currently compiles data to merge from 2016 * this could be extended to at least 2011 * +* Approach involves identifying total net wealth (wealth), +* total private pension wealth (personal and occupational), gross +* value of main home (dvhvalue) and value of assocaited mortgage +* debt (main_mort) at the benefit unit level. Total net wealth includes +* pension and housing wealth in addition to "other" wealth variously +* defined. File 08_wealth_to_ukls.do uses matching methods for reference +* people from each benefit unit to merge in these data to the UKHLS data. +* /**************************************************************/ /* @@ -473,7 +481,9 @@ foreach file in "$dir_was_data\was_round_5_person_eul_oct_2020.dta" /// drop pct1 // save control data - keep case person_id bu bu_rp year sex grad gradsp dvage17 na nk* single_man single_woman couple couple_ref gor2 dhe2 healths p_healths dlltsd dlltsdsp idnk04 pct emp empsp wealth inc was dwt + keep case person_id bu bu_rp year sex grad gradsp dvage17 na nk* single_man /// + single_woman couple couple_ref gor2 dhe2 healths p_healths dlltsd dlltsdsp /// + idnk04 pct emp empsp tot_pen dvhvalue main_mort wealth inc was dwt if (`ww' > `ww0') { append using "$dir_data\was_wealthdata.dta" } diff --git a/input/InitialPopulations/compile/08_wealth_to_ukhls.do b/input/InitialPopulations/compile/08_wealth_to_ukhls.do index f7c8e07ce..154506edd 100644 --- a/input/InitialPopulations/compile/08_wealth_to_ukhls.do +++ b/input/InitialPopulations/compile/08_wealth_to_ukhls.do @@ -30,7 +30,7 @@ global seedAdjust = 0 *********************************************************************/ use "population_initial_fs_UK_$yearWealth", clear sort idperson -drop liquid_wealth smp rnk mtc +drop total_wealth total_pensions housing_wealth mortgage_debt smp rnk mtc /********************************************************************** @@ -285,6 +285,9 @@ gen smp = 0 gen rnk = 0 gen mtc = 0 gen wealthi = -9 +gen tot_peni = -9 +gen housingi = -9 +gen mortgagei = -9 qui { sum treat, mean local nn = r(mean) * r(N) @@ -354,9 +357,15 @@ forval kk = 1/`nn' { } local mtc = bu[1] local ww = wealth[1] + local pw = tot_pen[1] + local hw = dvhvalue[1] + local mm = main_mort[1] restore replace mtc=`mtc' if (_n==`kk') replace wealthi = `ww' if (_n==`kk') + replace tot_peni = `pw' if (_n==`kk') + replace housingi = `hw' if (_n==`kk') + replace mortgagei = `mm' if (_n==`kk') } replace rnk=`rnk' if (_n==`kk') drop chk @@ -372,20 +381,33 @@ keep if (treat) append using "ukhls_wealthtemp2.dta" sort bu recode wealthi (mis=0) -by bu: egen liquid_wealth = sum(wealthi) -recode liquid_wealth (-9=0) +recode tot_peni (mis=0) +recode housingi (mis=0) +recode mortgagei (mis=0) +by bu: egen total_wealth = sum(wealthi) +by bu: egen total_pensions = sum(tot_peni) +by bu: egen housing_wealth = sum(housingi) +by bu: egen mortgage_debt = sum(mortgagei) +recode total_wealth (-9=0) +recode total_pensions (-9=0) +recode housing_wealth (-9=0) +recode mortgage_debt (-9=0) +label var total_wealth "total wealth net of liabilities of benefit unit including housing, business and private (personal and occupational) pensions" +label var total_pensions "value of all private (personal and occupational) pensions of benefit unit" +label var housing_wealth "value of main home gross of mortgage debt of benefit unit" +label var mortgage_debt "total mortgage debt owed on main home of benefit unit" save ukhls_wealthtemp3, replace /* -sum liquid_wealth [fweight=dwt2] if (single_woman & rnk<4), detail -sum liquid_wealth [fweight=dwt2] if (single_man & rnk<4), detail -sum liquid_wealth [fweight=dwt2] if (couple_ref & rnk<4), detail -sum liquid_wealth [fweight=dwt2] if (rnk<4), detail - -sum liquid_wealth [fweight=dwt2] if (single_woman), detail -sum liquid_wealth [fweight=dwt2] if (single_man), detail -sum liquid_wealth [fweight=dwt2] if (couple_ref), detail -sum liquid_wealth [fweight=dwt2], detail +sum total_wealth [fweight=dwt2] if (single_woman & rnk<4), detail +sum total_wealth [fweight=dwt2] if (single_man & rnk<4), detail +sum total_wealth [fweight=dwt2] if (couple_ref & rnk<4), detail +sum total_wealth [fweight=dwt2] if (rnk<4), detail + +sum total_wealth [fweight=dwt2] if (single_woman), detail +sum total_wealth [fweight=dwt2] if (single_man), detail +sum total_wealth [fweight=dwt2] if (couple_ref), detail +sum total_wealth [fweight=dwt2], detail */ @@ -395,12 +417,11 @@ sum liquid_wealth [fweight=dwt2], detail use ukhls_wealthtemp3, clear drop dvage17 year gor gor2 sex nk na dhe2 dhesp2 grad gradsp emp empsp inci inc nk04i nk04 idnk04 dhe2grad dhe2ngrad /// dlltsdgrad dlltsdngrad empage single_woman single_man couple single ee ee2 was bu couple_ref pct dwt2 treat case person_id /// -p_healths dlltsdsp healths wealth bu_rp tt dhe3 dhe4 dvage07 nk2 nk3 gor3 gor4 pct2 wealthi +p_healths dlltsdsp healths wealth bu_rp tt dhe3 dhe4 dvage07 nk2 nk3 gor3 gor4 pct2 wealthi tot_peni housingi mortgagei recode rnk smp mtc (missing = -9) label var rnk "matching level: 1 = most fine, 2, 3 = most coarse, 4=no match" label var smp "matching sample - number of matched candidates to choose from" label var mtc "benefit unit id (bu) of matched observation" -label var liquid_wealth "total wealth including housing, business and private (personal and occupational) pensions" save "population_initial_fs_UK_$yearWealth", replace diff --git a/input/InitialPopulations/compile/09_finalise_input_data.do b/input/InitialPopulations/compile/09_finalise_input_data.do index 1b58c8b1f..accf24fbd 100644 --- a/input/InitialPopulations/compile/09_finalise_input_data.do +++ b/input/InitialPopulations/compile/09_finalise_input_data.do @@ -179,36 +179,43 @@ forvalues yy = $firstSimYear/$lastSimYear { cap gen one =1 sum one [w=dwt] + * limit employment history to integer years + replace liwwh = round(liwwh) + *evaluate disposable income at household level gsort idhh idbenefitunit idperson by idhh idbenefitunit: egen disp_inc = sum(ydisp) *limit saved variables - keep idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// - yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// - stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// - l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// - formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// - dhe_pcssp dls dot dot01 unemp financial_distress liwwh + keep idhh idbenefitunit idperson idpartner idmother idfather swv dgn dag dnc02 dnc ded deh_c3 sedex dlltsd01 dhe ydses_c5 /// + yplgrs_dv ypnbihs_dv yptciihs_dv dcpyy dcpagdf ynbcpdf_dv der dehm_c3 dehf_c3 stm dhm scghq2_dv dhh_owned lhw /// + l1_lhw drgn1 les_c4 dhm_ghq adultchildflag dwt potential_earnings_hourly l1_potential_earnings_hourly total_wealth /// + total_pensions housing_wealth mortgage_debt need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs /// + son_socare_hrs other_socare_hrs formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc /// + econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp /// + financial_distress liwwh - order idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// - yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// - stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// - l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// - formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// - dhe_pcssp dls dot dot01 unemp financial_distress liwwh + order idhh idbenefitunit idperson idpartner idmother idfather swv dgn dag dnc02 dnc ded deh_c3 sedex dlltsd01 dhe ydses_c5 /// + yplgrs_dv ypnbihs_dv yptciihs_dv dcpyy dcpagdf ynbcpdf_dv der dehm_c3 dehf_c3 stm dhm scghq2_dv dhh_owned lhw /// + l1_lhw drgn1 les_c4 dhm_ghq adultchildflag dwt potential_earnings_hourly l1_potential_earnings_hourly total_wealth /// + total_pensions housing_wealth mortgage_debt need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs /// + son_socare_hrs other_socare_hrs formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc /// + econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp /// + financial_distress liwwh - recode idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// - yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// - stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// - l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// - carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc formal_socare_cost disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// - dhe_pcssp dls dot dot01 unemp financial_distress liwwh (missing=-9) + recode idhh idbenefitunit idperson idpartner idmother idfather swv dgn dag dnc02 dnc ded deh_c3 sedex dlltsd01 dhe ydses_c5 /// + yplgrs_dv ypnbihs_dv yptciihs_dv dcpyy dcpagdf ynbcpdf_dv der dehm_c3 dehf_c3 stm dhm scghq2_dv dhh_owned lhw /// + l1_lhw drgn1 les_c4 dhm_ghq adultchildflag dwt potential_earnings_hourly l1_potential_earnings_hourly total_wealth /// + total_pensions housing_wealth mortgage_debt need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs /// + son_socare_hrs other_socare_hrs formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc /// + econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp /// + financial_distress liwwh (missing=-9) gsort idhh idbenefitunit idperson save "$dir_data/population_initial_UK_$year.dta", replace - recode dgn liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs carewho (-9=0) + recode dgn total_wealth total_pensions housing_wealth mortgage_debt need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs /// + other_socare_hrs formal_socare_cost aidhrs carewho (-9=0) export delimited using "$dir_data/population_initial_UK_$year.csv", nolabel replace } diff --git a/input/InitialPopulations/compile/10_check_yearly_data.do b/input/InitialPopulations/compile/10_check_yearly_data.do index b589923b9..853dad71e 100644 --- a/input/InitialPopulations/compile/10_check_yearly_data.do +++ b/input/InitialPopulations/compile/10_check_yearly_data.do @@ -22,64 +22,45 @@ local varlist idhh idbenefitunit idperson -idpartner idmother idfather -pno swv dgn dag -dcpst dnc02 dnc ded deh_c3 sedex -les_c3 -dlltsd dlltsd01 dhe ydses_c5 yplgrs_dv ypnbihs_dv yptciihs_dv -dhhtp_c4 -ssscp -dcpen dcpyy -dcpex dcpagdf ynbcpdf_dv der -sedag -sprfm -dchpd -dagsp -dehsp_c3 -dhesp -lessp_c3 dehm_c3 dehf_c3 stm -lesdf_c4 -ppno dhm scghq2_dv dhh_owned scghq2_dv_miss_flag lhw drgn1 -dct -dwt_sampling les_c4 dhm_ghq -lessp_c4 adultchildflag -multiplier dwt potential_earnings_hourly l1_potential_earnings_hourly -liquid_wealth +total_wealth +total_pensions +housing_wealth +mortgage_debt need_socare formal_socare_hrs partner_socare_hrs @@ -104,20 +85,12 @@ liwwh *varlist for categorical variables #delimit ; local varlist_cat -dcpst deh_c3 -les_c3 dhe ydses_c5 -dhhtp_c4 -dehsp_c3 -dhesp -lessp_c3 dehm_c3 dehf_c3 -lesdf_c4 les_c4 -lessp_c4 drgn1 dot dot01 @@ -131,10 +104,8 @@ local varlist2 idhh idbenefitunit idperson -idpartner idmother idfather -pno swv dgn dag @@ -142,41 +113,25 @@ dnc02 dnc ded sedex -dlltsd dlltsd01 ypncp ypnoab yplgrs_dv ypnbihs_dv yptciihs_dv -ssscp -dcpen dcpyy -dcpex dcpagdf ynbcpdf_dv der -sedag -sprfm -dchpd -dagsp stm dhm lhw -dct -dwt_sampling dhm_ghq adultchildflag -multiplier dwt -dcpst_1 -dcpst_2 deh_c3_1 deh_c3_2 deh_c3_3 -les_c3_1 -les_c3_2 -les_c3_3 dhe_1 dhe_2 dhe_3 @@ -187,39 +142,16 @@ ydses_c5_2 ydses_c5_3 ydses_c5_4 ydses_c5_5 -dhhtp_c4_1 -dhhtp_c4_2 -dhhtp_c4_3 -dhhtp_c4_4 -dehsp_c3_1 -dehsp_c3_2 -dehsp_c3_3 -dhesp_1 -dhesp_2 -dhesp_3 -dhesp_4 -dhesp_5 -lessp_c3_1 -lessp_c3_2 -lessp_c3_3 dehm_c3_1 dehm_c3_2 dehm_c3_3 dehf_c3_1 dehf_c3_2 dehf_c3_3 -lesdf_c4_1 -lesdf_c4_2 -lesdf_c4_3 -lesdf_c4_4 les_c4_1 les_c4_2 les_c4_3 les_c4_4 -lessp_c4_1 -lessp_c4_2 -lessp_c4_3 -lessp_c4_4 drgn1_1 drgn1_2 drgn1_3 @@ -241,7 +173,10 @@ daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost -liquid_wealth +total_wealth +total_pensions +housing_wealth +mortgage_debt dhemcs dhepcs dot_1 @@ -293,7 +228,8 @@ foreach var of local varlist2 { recode `var' (-9=.) } -foreach var in need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost liquid_wealth carehoursprovidedweekly { +foreach var in need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// +formal_socare_cost total_wealth total_pensions housing_wealth mortgage_debt carehoursprovidedweekly { recode `var' (.=0) } @@ -312,10 +248,8 @@ forvalues year=2010/2023 { use "$dir_data/population_initial_fs_UK_`year'.dta", clear rename careHoursProvidedWeekly carehoursprovidedweekly -cap gen dwt_sampling =0 cap gen uk_pop=0 cap gen surv_pop=0 -cap gen multiplier=0 cap gen adult = dag>=$age_become_responsible cap gen child = 1 - adult @@ -336,7 +270,7 @@ recode `var' (-9=.) foreach var in need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost /// -liquid_wealth carehoursprovidedweekly { +total_wealth total_pensions housing_wealth mortgage_debt carehoursprovidedweekly { recode `var' (.=0) } diff --git a/input/InitialPopulations/compile/99_training_data.do b/input/InitialPopulations/compile/99_training_data.do index 9620248a7..9581a83e9 100644 --- a/input/InitialPopulations/compile/99_training_data.do +++ b/input/InitialPopulations/compile/99_training_data.do @@ -3,7 +3,7 @@ * FILE TO OBTAIN TRAINING DATA FOR SIMPATHS * * AUTH: Justin van de Ven (JV) -* LAST EDIT: 30/05/2024 (JV) +* LAST EDIT: 19/11/2025 (JV) * *******************************************************************************/ @@ -175,7 +175,6 @@ rename stmb stm save "$dir_data/temp9", replace // adjust weights -drop dwt_sampling multiplier gen ldwt = ln(dwt) sum ldwt gen dwt2 = round(exp(r(mean) + r(sd) * rnormal())) @@ -185,7 +184,8 @@ rename dwt2 dwt save "$dir_data/temp10", replace // adjust continuous variables -foreach vv of varlist yplgrs_dv ypnbihs_dv yptciihs_dv ynbcpdf_dv liquid_wealth tot_pen nvmhome disp_inc ypncp ypnoab formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs { +foreach vv of varlist yplgrs_dv ypnbihs_dv yptciihs_dv ynbcpdf_dv total_wealth total_pensions housing_wealth mortgage_debt /// +disp_inc ypncp ypnoab formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs { gen tmp = `vv' order tmp, a(`vv') recode tmp (0=.) @@ -195,7 +195,8 @@ foreach vv of varlist yplgrs_dv ypnbihs_dv yptciihs_dv ynbcpdf_dv liquid_wealth drop `vv' rename tmp `vv' } -foreach vv of varlist yplgrs_dv ypnbihs_dv yptciihs_dv tot_pen ypncp ypnoab formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs { +foreach vv of varlist yplgrs_dv ypnbihs_dv yptciihs_dv ypncp ypnoab formal_socare_hrs partner_socare_hrs daughter_socare_hrs /// +son_socare_hrs other_socare_hrs formal_socare_cost aidhrs { replace `vv' = 0 if (`vv'<0.0) } gen tmp = ln(potential_earnings_hourly) @@ -212,7 +213,7 @@ save "$dir_data/temp11", replace // set benefit unit level variables use "$dir_data/temp11", clear -foreach vv of varlist drgn1 ydses_c5 dhh_owned dwt liquid_wealth tot_pen nvmhome disp_inc { +foreach vv of varlist drgn1 ydses_c5 dhh_owned dwt total_wealth total_pensions housing_wealth mortgage_debt disp_inc { rename `vv' `vv'i bys idbenefitunit: egen `vv' = mean(`vv'i) @@ -223,7 +224,8 @@ foreach vv of varlist drgn1 ydses_c5 dhh_owned dwt liquid_wealth tot_pen nvmhome /************************************************************************************** * export training data *************************************************************************************/ -recode dgn liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs carewho (-9=0) +recode dgn total_wealth total_pensions housing_wealth mortgage_debt need_socare formal_socare_hrs partner_socare_hrs /// +daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost aidhrs carewho (-9=0) export delimited using "$dir_data/training_population_initial_UK_$wealthEndYear.csv", nolabel replace @@ -235,5 +237,6 @@ forvalues yy = $wealthStartYear/$wealthEndYear { rm "$dir_data/temp_`yy'.dta" } forvalues ii = 0/11 { + rm "$dir_data/temp`ii'.dta" } diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_education 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_education 2.do deleted file mode 100644 index f5485e6e2..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_education 2.do +++ /dev/null @@ -1,185 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Education -* OBJECT: Final Probit Models - Weighted -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_education.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable deh_c3 "Educational Attainment: 3 Category" -/* -label variable dehm_c3 "Mother's Educational Attainment: 3 Category" -label variable dehf_c3 "Father's Educational Attainment: 3 Category" -*/ -label variable dehmf_c3 "Highest Parental Educational Attainment: 3 Category" -label variable dhhtp_c4 "Household Type: 4 Category" -label variable dnc "Number of Children in Household" -label variable dnc02 "Number of Children aged 0-2 in Household" - -label value dgn gdr -label value drgn1 rgna -label value les_c3 jbf -label value deh_c3 dehmf_c3 /*dehm_c3 dehf_c3*/ edd -label value ded yn -label value dhhtp_c4 hht - -drop if dag < 16 - -replace stm = stm - 2000 -fre stm - -/*check if all covariates are available in the data*/ -recode ded dgn dag dagsq dehmf_c3 drgn1 stm deh_c3 les_c3 (-9=.) - - -xtset idperson swv - - -********************************** -*Probability of Being a Student * -********************************** -*Process E1a: Probability of being in education. Sample: Individuals aged 16-29 in continuous education. -*or probability of remaining in education for those who have always been in education without interruptions. - -*sample: Individuals aged 16-29 in continuous education. -fre ded if (dag>=16 & dag<=29 & l.ded==1) /*was in continious education in the previous wave */ - -probit ded i.dgn dag dagsq ib1.dehmf_c3 /*ib1.dehm_c3 ib1.dehf_c3*/ ib8.drgn1 stm if (dag>=16 & dag<=29 & l.ded==1) [pweight=dimxwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/education", sheet("Process E1a") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/E1a.doc", replace /// -title("Process E1a: Probability of remaining in continuous education - individuals aged 16-29 in continuous education.") /// - ctitle(Continuing student) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -**************************************** -*Probability of Returning to education * -**************************************** -*Process E1b: Probability of being in education. Sample: Individuals aged 16-35 not in continuous education. -*Or probability of returning to education for those who had left school. - -*sample: Individuals aged 16-35 not in continuous education. -fre der if (dag>=16 & dag<=35 & ded==0) - -probit der i.dgn dag dagsq lib1.deh_c3 li.les_c3 l.dnc l.dnc02 ib1.dehmf_c3 /*ib1.dehm_c3 ib1.dehf_c3*/ ib8.drgn1 stm if (dag>=16 & dag<=35 & ded==0) [pweight=dimlwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/education", sheet("Process E1b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/E1b.doc", replace /// -title("Process E1b: Probability of returning to education - individuals aged 16-35 not in continuous education.") /// - ctitle(Returning student) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -******************************************** -*Educational level after leaving education * -******************************************** -*Process E2: Educational attainment. Sample: Respondents from Process 1a who have left education. -*Or Level of education for those leaving education. - -*sample: Individuals aged 16-29 who were in continuous education and left it. -fre deh_c3 if (dag>=16 & dag<=29) & l.ded==1 & ded==0 - -/* -mprobit deh_c3 i.dgn dag dagsq ib1.dehm_c3 ib1.dehf_c3 ib8.drgn1 stm if sedcsmpl==1 [pweight=dimxwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/education.xlsx", sheet("Process E2 - Education Level") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -mprobit deh_c3 i.dgn dag dagsq ib1.dehm_c3 ib1.dehf_c3 ib8.drgn1 stm if sedcsmpl==1 [pweight=dimxwt], vce(robust) -matrix e2=get(VCE) -matrix list e2 -putexcel set "$dir_data/edu_vcm.xlsx", sheet("Process E2 - Education Level") modify -putexcel A1 = matrix(e2), names - -//capture log close -*/ - - -/******************************************************************************* -* Ordered probit model to replace multinomial probit E2a -*******************************************************************************/ - -*1. Recode education level (outcome variable) so 1 = Low education, 2 = Medium education, 3 = High education -recode deh_c3 /// - (1 = 3) /// - (3 = 1) /// - , gen(deh_c3_recoded) - -la def deh_c3_recoded 1 "Low" 2 "Medium" 3 "High" -la val deh_c3_recoded deh_c3_recoded - -//oprobit deh_c3_recoded i.dgn dag dagsq ib1.dehm_c3 ib1.dehf_c3 ib8.drgn1 stm if (dag>=16 & ded == 0) [pweight=dimxwt], vce(robust) -oprobit deh_c3_recoded i.dgn dag dagsq ib1.dehmf_c3 /*ib1.dehm_c3 ib1.dehf_c3*/ ib8.drgn1 stm if (dag>=16 & dag<=29 & l.ded==1 & ded==0) [pweight=dimxwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/education", sheet("Process E2a") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/E2a.doc", replace /// -title("Process E2a: Ordered probit for educational attainment - individuals aged 16-29 exiting education.") /// - ctitle(Education attainment) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_fertility 2.do deleted file mode 100644 index 9ae5d272d..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility 2.do +++ /dev/null @@ -1,127 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Fertility -* OBJECT: Final Probit Models -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_fertility.log", replace -******************************************************************* -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable dhhtp_c4 "Household Type: 4 Category" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable dhe "Self-rated Health" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable dnc "Number of Children in Household" -label variable dnc02 "Number of Children aged 0-2 in Household" -label variable ydses_c5 "Annual Household Income Quintile" -label variable dukfr "UK Fertility Rate" - -label value dgn gdr -label value drgn1 rgna -label value dhhtp_c4 hht -label value les_c3 jbf -label value deh_c3 edd -label value ded yn - -drop if dag < 16 -replace stm = stm - 2000 - -/*check if all covariates are available in the data*/ -recode dhe dnc dnc02 deh_c3 les_c3 ydses_c5 dcpst drgn1 sprfm scedsmpl dukfr (-9=. ) -recode dchpd (-9=0) - -xtset idperson swv - - -********************************************************************** -*Proces F1a - Probability of Having a Child - In continuous education -********************************************************************** -*Sample: Women aged 18-44 not in continuous education. -probit dchpd dag l.dnc il.dnc02 ib1.dcpst if (sprfm==1 & scedsmpl==1) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/Fertility_w", sheet("Process F1a - In education") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/F1a.doc", replace /// -title("Process F1a: Probability of giving birth to a child. Sample: Women aged 18-44 in continuous education.") /// - ctitle(Giving birth) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -************************************************************************ -*Proces F1b Probability of Having a Child - Not in continuous education -************************************************************************* -*Sample: Women aged 18-44 not in continuous education. -gen ddnc02 = (dnc02 > 0) -probit dchpd dag dagsq l.dnc l.ddnc02 ib1.dhe ib1.dcpst dukfr li.les_c3 ib8.drgn1 if (sprfm==1 & scedsmpl==0) [pweight=disclwt], vce(robust) - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/Fertility_w", sheet("Process F1b - Not in education") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) - -outreg2 stats(coef se pval) using "$dir_data/F1b.doc", replace /// -title("Process F1b: Probability of giving birth to a child. Sample: Women aged 18-44 not in continuous education.") /// - ctitle(Giving birth) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - - -capture log close - - - - diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_health 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_health 2.do deleted file mode 100644 index 7da6ae616..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_health 2.do +++ /dev/null @@ -1,165 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Health -* OBJECT: Final Probit and Linear Regression Models - Weighted -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_health.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable dhhtp_c4 "Household Type: 4 Category" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable dhe "Self-rated Health" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable ydses_c5 "Annual Household Income Quintile" -label variable dlltsd "Long-term Sick or Disabled" - -label value dgn gdr -label value drgn1 rgna -label value dhhtp_c4 hht -label value les_c3 jbf -label value deh_c3 edd -label value ded yn - - -drop if dag < 16 -replace stm = stm - 2000 - -/*check if all covariates are available in the data*/ -recode dhe deh_c3 les_c3 ydses_c5 dhhtp_c4 drgn1 stm (0= .) (-9=. ) -recode dgn dag dagsq (-9=.) - -xtset idperson swv - - -********************************** -*Process 1a: Those in education * -********************************** -* -*Self-rated health status for those in continuous education. -*sample: 16-29 year olds who have always been in education without a break -fre dhe if (dag>=16 & dag<=29 & ded==1 ) - -/* -regress dhe i.dgn dag dagsq li.ydses_c5 l.dhe ib8.drgn1 stm if scedsmpl==1 [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/health.xlsx", sheet("Process H1a - Self-rated Health") replace -putexcel A1 = matrix(results), names nformat(number_d2) -putexcel A1 = matrix(results), names nformat(number_d2) -*/ - -* Ordered probit models to replace linear regression -oprobit dhe i.dgn dag dagsq li.ydses_c5 ilb5.dhe ib8.drgn1 stm if (dag>=16 & dag<=29 & ded==1) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/health", sheet("Process H1a") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/H1a.doc", replace /// -title("Process H1a: Ordered probit regression estimates of self reported health status - individuals aged 16-29 in continuous education") /// - ctitle(health status) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -**************************************** -*Process 1b: Those in not in education * -**************************************** -* -*Self-rated health status for those not in continuous education (out of education or returned having left education in the past). -*sample: 16 or older who are not in continuous education -fre dhe if (dag>=16 & ded==0 ) -/* -regress dhe i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 l.dhe lib1.dhhtp_c4 ib8.drgn1 stm if scedsmpl==0 [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set health, sheet("Process H1b - Not in education") modify -putexcel A1 = matrix(results), names nformat(number_d2) -*/ - -* Ordered probit models to replace linear regression -oprobit dhe i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 ilb5.dhe lib1.dhhtp_c4 ib8.drgn1 stm if (dag>=16 & ded==0) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/health", sheet("Process H1b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/H1b.doc", replace /// -title("Process H1b: Ordered probit regression estimates of self reported health status - individuals aged 16+ not in continuous education") /// - ctitle(health status) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -********************************************************************************************** -*Process 2b: Probability of being long-term sick or disabled amongst those not in education * -********************************************************************************************** -* -*Probability of becoming long-term sick or disabled for those not in continuous education. -*sample: 16 or older who are not in continuous education -fre dhe if (dag>=16 & ded==0 ) - -probit dlltsd i.dgn dag dagsq ib1.deh_c3 li.ydses_c5 ib5.dhe ilb5.dhe l.dlltsd lib1.dhhtp_c4 ib8.drgn1 stm if (dag>=16 & ded==0 & dag<56) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/health", sheet("Process H2b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/H2b.doc", replace /// -title("Process H2b: Probit regression estimates for being long-term sick or disabled - people aged 16+ not in continuous education") /// - ctitle(long-term sick or disabled) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - - -capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership 2.do deleted file mode 100644 index 52df228ae..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership 2.do +++ /dev/null @@ -1,101 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Home ownership -* OBJECT: Final Regresion Models - Weighted -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_home_ownership.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable stm "Year" -label variable les_c3 "Employment Status: 5 Category" -label variable dhe "Self-rated Health" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable dhhtp_c4 "Household Type: 4 Category" - -label value dgn gdr -label value drgn1 rgna -label value les_c3 lessp_c3 jbf -label value deh_c3 dehsp_c3 edd -label value dcpen dcpex dlrtrd yn -label value dhhtp_c4 hht - -drop if dag < 16 -replace stm = stm - 2000 - - -*check if all covariates are available and recode missing values -recode dhh_owned dgn dag dagsq les_c3 deh_c3 dhe yptciihs_dv ydses_c5 drgn1 dhhtp_c4 lessp_c3 stm (-9=.) - -xtset idperson swv - - -************************************************* -*Process HO1: Probability of being a homeowner. * -************************************************* -*Sample: Individuals aged 16 and above. - -probit dhh_owned dgn dag dagsq il.dhhtp_c4 il.les_c3 il.lessp_c3 i.deh_c3 il.dhe il.ydses_c5 l.yptciihs_dv ib8.drgn1 stm if dag>=16 [pweight=disclwt], vce(cluster idperson) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/homeownership", sheet("Process HO1a") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/U1a.doc", replace /// -title("Process HO1a: Probability of being a home owner - people aged 16+") /// - ctitle(home owner) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_income 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_income 2.do deleted file mode 100644 index 138e19009..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_income 2.do +++ /dev/null @@ -1,416 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Non-employment/non-benefit income -* OBJECT: Final Regresion Models - Weighted -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_income.log", replace -******************************************************************* - - -import excel "$dir_data/time_series_factor.xlsx", sheet("UK_wage_growth") firstrow clear // Import real growth index -rename Year stm -rename Value growth -gen base_val = growth if stm == 2015 -sum base_val -replace base_val = r(mean) -replace growth= growth/base_val -drop base_val -replace stm = stm - 2000 -save "$dir_data\growth_rates", replace - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable dhhtp_c4 "Household Type: 4 Category" -label variable dnc "Number of Children in Household" -label variable dnc02 "Number of Children aged 0-2 in Household" -label variable dhe "Self-rated Health" -label variable ydses_c5 "Annual Household Income Quintile" -label variable dlltsd "Long-term Sick or Disabled" -label variable dcpen "Entered a new Partnership" -label variable dcpex "Partnership dissolution" -label variable lesdf_c4 "Differntial Employment Status" -label variable ypnbihs_dv "Personal Non-benefit Gross Income" - -gen ypnbihs_dv_sq =ypnbihs_dv^2 - -label variable ypnbihs_dv_sq "Personal Non-benefit Gross Income Squared" -label variable ynbcpdf_dv "Differential Personal Non-Benefit Gross Income" - -label value dgn gdr -label value drgn1 rgna -label value les_c3 jbf -label value deh_c3 edd -label value dcpen dcpex yn -label value lesdf_c4 dces -label value ded dlltsd yn -label value dhhtp_c4 hht - -drop if dag < 16 -//replace stm = stm - 2000 -sort stm -merge m:1 stm using "$dir_data/growth_rates", keep(3) nogen keepusing(growth) - - -/********************************************************************** -CLEAN UP VARIABLES FOR REGRESSIONS -***********************************************************************/ -recode dgn dag dagsq dhe drgn1 stm scedsmpl deh_c3 les_c3 dhhtp_c4 dhe (-9=.) -sum yplgrs_dv ypncp ypnoab pred_hourly_wage - -xtset idperson swv -/* -***************************************************************** -*Process I1a: Non-employment income - In continuous education * -***************************************************************** -regress yptciihs_dv i.dgn dag dagsq l.dhe l.yptciihs_dv ib8.drgn1 stm if scedsmpl==1 [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/Income_mdls", sheet("Income - In education") replace -putexcel A1 = matrix(results), names nformat(number_d2) -*predict fittedice -*histogram fittedice -*histogram yptciihs_dv - -*Getting Variance Covariance Matrix -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/income_vcm", sheet("Process I1a - In education") replace -putexcel A1 = matrix(i1a), names - -******************************************************************* -*Process I1b: Non-employment income - Not in continuous education * -******************************************************************* -regress yptciihs_dv i.dgn dag dagsq ib1.deh_c3 i.dlrtrd li.les_c3 lib1.dhhtp_c4 l.dhe l.yplgrs_dv l.yptciihs_dv /// -l2.yplgrs_dv l2.yptciihs_dv l3.yplgrs_dv l3.yptciihs_dv ib8.drgn1 stm if scedsmpl==0 [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/Income_mdls", sheet("Income - Not in education") modify -putexcel A1 = matrix(results), names nformat(number_d2) -*predict fittednice -*histogram fittednice -*histogram yptciihs_dv - -*Getting Variance Covariance Matrix -matrix i1b=get(VCE) -matrix list i1b -putexcel set "$dir_data/income_vcm", sheet("Process I1b - Not in education") modify -putexcel A1 = matrix(i1b), names -*/ - - -/******************************************************************************* - -New models for split income variable -The goal is to split the current non-labour non-benefit income variable into 3 components -(capital returns, occupational pension, public pension) and estimate each of them separately, -using (if possible) current set of controls. We have decided to abstain from estimating transfers at the moment. - -*******************************************************************************/ -bys swv idhh: gen nwa = _N -*Replace l.dhe with dhe if aged 16 -gsort +idperson -stm -bys idperson: carryforward dhe if dag <= 16, replace - -//For those who are 16, L1 of the variables below is missing as they were 15 at the time. Use current value to keep them in the sample. -sort idperson swv -bys idperson: gen dhe_L1 = l.dhe -replace dhe_L1 = dhe if missing(dhe_L1) //For those who have L1.dhe missing, use current dhe - -bys idperson: gen yplgrs_L1 = l.yplgrs_dv -replace yplgrs_L1 = yplgrs_dv if missing(yplgrs_L1) - -bys idperson: gen ypncp_L1 = l.ypncp -replace ypncp_L1 = ypncp if missing(ypncp_L1) - -bys idperson: gen yplgrs_L2 = l2.yplgrs_dv -replace yplgrs_L2 = yplgrs_dv if missing(yplgrs_L2) - -bys idperson: gen ypncp_L2 = l2.ypncp -replace ypncp_L2 = ypncp if missing(ypncp_L2) - -bys idperson: gen dhhtp_c4_L1 = l.dhhtp_c4 -replace dhhtp_c4_L1 = dhhtp_c4 if missing(dhhtp_c4_L1) - -bys idperson: gen les_c3_L1 = l.les_c3 -replace les_c3_L1 = les_c3 if missing(les_c3_L1) - - -/********************************************************************** -SELECTION MODELS FOR CAPITAL INCOME -***********************************************************************/ - -***************************************************************** -*Process I3a selection: Probability of receiving capital income. -***************************************************************** -*Sample: Individuals aged 16 - 29 who are in continuous education. -gen receives_ypncp = (ypncp > 0 & !missing(ypncp)) -logit receives_ypncp i.dgn dag dagsq l.dhe l.yplgrs_dv l.ypncp ib8.drgn1 stm if scedsmpl==1 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I3a_selection E") replace -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I3a_selection VCE") replace -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I3a_sel.doc", replace /// -title("Process I3a selection: Probability of receiving capital income. Sample: Individuals aged 16 - 29 who are in continuous education.") /// -ctitle(Probability of capital income) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -******************************************************************** -*Process I3b selection: Probability of receiving capital income. -******************************************************************** -*Sample: Individuals aged 16+ who are not in continuous education. - -logit receives_ypncp i.dgn dag dagsq ib1.deh_c3 li.les_c3 lib1.dhhtp_c4 l.dhe l.yplgrs_dv l.ypncp l2.yplgrs_dv /// -l2.ypncp ib8.drgn1 stm if scedsmpl==0 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I3b_selection E") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I3b_selection VCE") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I3b_sel.doc", replace /// -title("Process I3b selection: Probability of receiving capital income. Sample: Individuals aged 16+ who are not in continuous education.") /// -ctitle(Probability of capital income) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - -/**********************************************************************/ -******************************************** -*Process I3a: Amount of capital income. -******************************************** -*Sample: Individuals aged 16 - 29 who are in continuous education and receive capital income. -*Using same controls as Cara - use of lags means those observed for the first time are not taken into account - -regress ypncp i.dgn dag dagsq l.dhe l.yplgrs_dv l.ypncp ib8.drgn1 stm if scedsmpl==1 & receives_ypncp == 1 [pweight=dimxwt], /// -vce(cluster idperson) base -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I3a CapIn E") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I3a CapIn E VCE") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I3a.doc", replace /// -title("Process I3a: Amount of capital income. Sample: Individuals aged 16 - 29 who are in continuous education and receive capital income.") /// - ctitle(Amount of capital income) label side dec(2) noparen addstat(R2, e(r2), RMSE, e(rmse)) - -******************************************* -*Process I3b: Amount of capital income. -******************************************* -*Sample: Individuals aged 16+ who are not in continuous education and receive capital income. -*Using same controls as Cara -regress ypncp i.dgn dag dagsq ib1.deh_c3 li.les_c3 lib1.dhhtp_c4 l.dhe l.yplgrs_dv l.ypncp l2.yplgrs_dv l2.ypncp ib8.drgn1 stm /// - if scedsmpl==0 & receives_ypncp == 1 [pweight=dimxwt], vce(cluster idperson) base -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I3b CapIn NiE") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I3b CapIn NiE VCE") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I3b.doc", replace /// -title("Process I3b: Amount of capital income. Sample: Individuals aged 16+ who are not in continuous education and receive capital income.") /// -ctitle(Amount of capital income) label side dec(2) noparen addstat(R2, e(r2), RMSE, e(rmse)) - -replace les_c3 = 4 if dlrtrd == 1 - -label define jbf 4 "Retired", add - -/********************************************************************** -PRIVATE PENSION INCOME -***********************************************************************/ -*************************************************** -*Process I4b: Amount of pension income. -*************************************************** -*Sample: Retired individuals who were retired in the previous year. -gen state_pension_age = (dag >= 68) -gen receives_ypnoab = (ypnoab_lvl > 0 & !missing(ypnoab_lvl)) - -regress ypnoab dag dagsq ib1.deh_c3 lib1.dhhtp_c4 l.dhe l.ypnoab l2.ypnoab ib8.drgn1 c.growth stm /// -if dag >= 50 & les_c3 == 4 & l.les_c3 == 4 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I4b Pension Next") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I4b Pension Next VCE") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/14b.doc", /// -replace title("Process I4b: Amount of pension income. Sample: Retired individuals who were retired in the previous year.") /// -ctitle(Retired) label side dec(2) noparen addstat(R2, e(r2), RMSE, e(rmse)) - - - -/********************************************************************** -PRIVATE PENSION INCOME VERSION 2: - -selection equation for recipiency of private pension income - -followed by level of private pension income using linear model -***********************************************************************/ -************************************************************************** -*Process I5a: Probability of receiving private pension income. -************************************************************************** -*Sample: Retired individuals who were not retired in the previous year. -/* -Estimated on a sample of individuals retired at time t, who were not retired at t-1. -I.e. this is probability of receiving private pension income upon retirement. -*/ - -logit receives_ypnoab i.dgn i.state_pension_age ib1.deh_c3 lib4.les_c3 lib1.dhhtp_c4 l.dhe l.pred_hourly_wage ib8.drgn1 c.growth stm /// -if scedsmpl==0 & dag >= 50 & dlrtrd == 1 & l.les_c3 != 2 & l.les_c3 != 4 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I5a Select") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I5a Select") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I5a.doc", replace /// -title("Process I5a: Probability of receiving private pension income. Sample: Retired individuals who were not retired in the previous year.") /// -ctitle(Probability of private pension income) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - -**************************************************** -*Process I5b: Amount of private pension income. -**************************************************** -*Sample: Retired individuals who were not retired in the previous year and receive private pension income. -regress ypnoab_lvl i.dgn i.state_pension_age ib1.deh_c3 lib4.les_c3 lib1.dhhtp_c4 l.dhe l.pred_hourly_wage ib8.drgn1 c.growth stm /// -if scedsmpl==0 & dag >= 50 & dlrtrd == 1 & l.les_c3 != 2 & l.les_c3 != 4 & receives_ypnoab [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I5b Amount") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I5b Amount") modify -putexcel A1 = matrix(i1a), names - -outreg2 stats(coef se pval) using "$dir_data/I5b.doc", replace /// -title("Process I5b: Amount of private pension income. Sample: Retired individuals who were not retired in the previous year and receive private pension income.") /// -ctitle(Amount of private pension income) label side dec(2) noparen addstat(R2, e(r2), RMSE, e(rmse)) - -capture log close - -/* -******************** -*I6a: selection -******************** -/* - -Processes I6a and I6b are used to estimate private pension income among those continue retirement (retired at t and at t-1), -*and have not received private pension income in the previous year - -Estimated on a sample of individuals retired at time t -I.e. this is probability of receiving private pension in retirement, if not received private pension income in the initial population data -*/ - -logit receives_ypnoab i.dgn i.state_pension_age ib1.deh_c3 lib4.les_c3 lib1.dhhtp_c4 cl.ypncp l.dhe ib8.drgn1 c.growth stm /// -if dag >= 50 & les_c3 == 4 & l.les_c3 == 4 & l.receives_ypnoab == 0 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I6a Select") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I6a Select") modify -putexcel A1 = matrix(i1a), names - -*********************************************************************************** -*I6b: amount of private pension income for those receiving private pension income -*********************************************************************************** - -regress ypnoab_lvl i.dgn i.state_pension_age ib1.deh_c3 lib1.dhhtp_c4 l.dhe ib8.drgn1 cl.ypncp c.growth stm /// -if dag >= 50 & les_c3 == 4 & l.les_c3 == 4 & l.receives_ypnoab == 0 & receives_ypnoab == 1 [pweight=dimxwt], vce(cluster idperson) base - -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/uk_income_split", sheet("Process I6b Amount") modify -putexcel A1 = matrix(results), names nformat(number_d2) - -matrix i1a=get(VCE) -matrix list i1a -putexcel set "$dir_data/uk_income_split_vcm", sheet("Process I6b Amount") modify -putexcel A1 = matrix(i1a), names - -*/ - - diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome 2.do deleted file mode 100644 index 6bbabdde1..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome 2.do +++ /dev/null @@ -1,112 +0,0 @@ -******************************************************************************** -* PROJECT: INAPP -* SECTION: Leaving Parental Home -* OBJECT: Final Probit and Linear Regression Models - Weighted -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_leaveParentalHome.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -/*DP: note that the categories in les_c4 used by Cara are different from the ones currently used -so the categories in the corresponsing Excel file were updated */ - -*Labeling and formating variables - -label define jbg 1 "Employed" 2 "Student" 3 "Not employed" 4 "Retired" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable dhhtp_c4 "Household Type: 4 Category" -label variable stm "Year" -label variable les_c4 "Employment Status: 4 Category" -label variable dhe "Self-rated Health" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable ydses_c5 "Annual Household Income Quintile" -label variable dlltsd "Long-term Sick or Disabled" - -label value dgn gdr -label value drgn1 rgna -label value dhhtp_c4 hht -label value les_c4 jbg -label value deh_c3 edd -label value ded yn - - -drop if dag < 16 -replace stm = stm - 2000 - - -/*check if all covariates are available in the data*/ -recode dlftphm dgn dag dagsq deh_c3 les_c4 les_c3 ydses_c5 drgn1 stm (-9=.) - -xtset idperson swv - - -************************************ -*Process LPH1: Leave Parental Home * -************************************ -*Process P1a: Probability of leaving the parental home. Sample: All non-student respondents living with a parent. -*Or Probability of leaving the parental home for those who have left education. (Students stay in the parental home). - -*sample: All non-student respondents aged 18+ who lived with a parent at t-1 -fre dlftphm if (ded==0 & dag>=18 & l.dlftphm==0) - -probit dlftphm i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 ib8.drgn1 stm if (ded==0 & dag>=18 & l.dlftphm==0) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/leave_parent_home", sheet("Process P1a male grads") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/P1a.doc", replace /// -title("Process P1a: Probability of leaving the parental home. Sample: All non-student respondents living with a parent.") /// - ctitle(Leave parental home) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_partnership 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_partnership 2.do deleted file mode 100644 index 55b7dbece..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_partnership 2.do +++ /dev/null @@ -1,155 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Unions -* OBJECT: Final Probit Models -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_partnership.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -cap gen ypnbihs_dv_sq = ypnbihs_dv^2 - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label define dces 1 "Both Employed" 2 "Employed, Spouse Not Employed" 3 "Not Employed, Spouse Employed" 4 "Both Not Employed" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable dhe "Self-rated Health" -label variable dcpen "Entered a new Partnership" -label variable dcpex "Partnership dissolution" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable dnc "Number of Children in Household" -label variable dnc02 "Number of Children aged 0-2 in Household" -label variable ydses_c5 "Gross Annual Household Income Quintile" -label variable lesdf_c4 "Differential Employment Status" -label variable ypnbihs_dv "Personal Non-benefit Gross Income" -label variable ypnbihs_dv_sq "Personal Non-benefit Gross Income Squared" -label variable ynbcpdf_dv "Differential Personal Non-Benefit Gross Income" -label variable dhhtp_c4 "Household Type: 4 Category" - -label value dgn gdr -label value drgn1 rgna -label value les_c3 lessp_c3 jbf -label value deh_c3 dehsp_c3 edd -label value dcpen dcpex yn -label value lesdf_c4 dces -label value dhhtp_c4 hht - -drop if dag < 16 -replace stm = stm - 2000 - -/*check if all covariates are available in the data*/ -recode dcpen dgn dag dagsq ydses_c5 dnc dnc02 dhe deh_c3 dehsp_c3 les_c3 /// -ypnbihs_dv ypnbihs_dv_sq dnc dnc02 dhe dhesp ynbcpdf_dv dcpyy dcpagdf dhhtp_c4 lesdf_c4 /// -drgn1 stm (-9=. ) - -xtset idperson swv - - -*************************************************************** -*Process U1a: Entering a partnership - In continuous education * -*************************************************************** -*Probability of entering a partnership. -*Sample: All single respondents aged 18 and older, in continuous education. -fre dcpen if (dag>=18 & ded==1 & ssscp!=1) //exclude same sex couples - -probit dcpen i.dgn dag dagsq li.ydses_c5 l.dnc l.dnc02 i.dhe ib8.drgn1 stm if (dag>=16 & ded==1 & ssscp!=1) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/union", sheet("Process U1a") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/U1a.doc", replace /// -title("Process U1a: Probit regression estimates for entering a partnership - single respondents aged 16+ in continuous education") /// - ctitle(enter partnership) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -******************************************************************** -*Process U1b: Entering a partnership - Not in continuous education * -******************************************************************** -*Probability of entering a partnership. -*Sample: All respondents aged 18+ who were not in a parthership at t-1 and were not in continuous education -fre dcpen if (dag>=18 & ded==0 & ssscp!=1) //exclude same sex couples - -probit dcpen i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 l.dnc l.dnc02 i.dhe ib8.drgn1 stm if (dag>=18 & ded==0 & ssscp!=1) [pweight=disclwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/union", sheet("Process U1b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/U1b.doc", replace /// -title("Process U1b: Probit regression estimates for entering a partnership - single respondents aged 18+ not in continuous education") /// - ctitle(enter partnership) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -****************************************************************** -*Process 2b: Exiting a partnership - Not in continuous education * -****************************************************************** -*Probability of partnership break-up. -*Sample: Female member of a couple aged 18+ who were in a partnership at t-1 and not in a partnership at t and were not in continuous education -fre dcpex if (dgn==0 & dag>=18 & ded==0 & ssscp!=1) //exclude same sex couples - -probit dcpex dag dagsq lib1.deh_c3 lib1.dehsp_c3 li.dhe li.dhesp l.dcpyy l.dcpagdf l.dnc l.dnc02 lib1.dhhtp_c4 lib1.lesdf_c4 /// -l.ypnbihs_dv l.ynbcpdf_dv ib8.drgn1 stm if (dgn==0 & dag>=18 & ded==0 & ssscp!=1) [pweight=dhhwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/union", sheet("Process U2b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/U2b.doc", replace /// -title("Process U2b: Probit regression estimates for exiting a partnership - cohabiting women aged 18+ not in continuous education") /// - ctitle(enter partnership) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_retirement 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_retirement 2.do deleted file mode 100644 index d0cdecf27..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_retirement 2.do +++ /dev/null @@ -1,117 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Retirement -* OBJECT: Final Regresion Models -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_retirement.log", replace -******************************************************************* - -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -*Labeling and formating variables -label define jbf 1 "Employed" 2 "Student" 3 "Not Employed" - -label define edd 1 "Degree" 2 "Other Higher/A-level/GCSE" 3 "Other/No Qualification" - -label define gdr 1 "Male" 0 "Female" - -label define rgna 1 "North East" 2 "North West" 4 "Yorkshire and the Humber" 5 "East Midlands" /// -6 "West Midlands" 7 "East of England" 8 "London" 9 "South East" 10 "South West" 11 "Wales" /// -12 "Scotland" 13 "Northern Ireland" - -label define yn 1 "Yes" 0 "No" - -label define hht 1 "Couples with No Children" 2 "Couples with Children" /// - 3 "Single with No Children" 4 "Single with Children" - -label variable dgn "Gender" -label variable dag "Age" -label variable dagsq "Age Squared" -label variable drgn1 "Region" -label variable stm "Year" -label variable les_c3 "Employment Status: 3 Category" -label variable dhe "Self-rated Health" -label variable deh_c3 "Educational Attainment: 3 Category" -label variable dhhtp_c4 "Household Type: 4 Category" - -label value dgn gdr -label value drgn1 rgna -label value les_c3 lessp_c3 jbf -label value deh_c3 dehsp_c3 edd -label value dcpen dcpex dlrtrd dagpns dagpns_sp yn -label value dhhtp_c4 hht - -drop if dag < 16 -replace stm = stm - 2000 - -*check if all covariates are available and recode missing values -recode dgn dag dagsq deh_c3 dagpns lesnr_c2 ydses_c5 dlltsd drgn1 stm dcpst drtren dagpns_sp lessp_c3 dlltsd_sp dcpst (-9=.) - -xtset idperson swv - - -******************************************* -*Process R1a: Enter Retirement - Single * -******************************************* -*Sample: Non-partnered individuals aged 50+ who are not yet retired. -probit drtren i.dgn dag dagsq ib1.deh_c3 i.dagpns li.lesnr_c2 li.ydses_c5 li.dlltsd ib8.drgn1 stm /// -if ((dcpst==2 | dcpst==3) & dag>=50) [pweight=dimlwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/retire", sheet("Process R1a") replace -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/R1a.doc", replace /// -title("Process R1a: Probit regression estimates for retiring - single individuals aged 50+ not yet retired") /// - ctitle(retiring) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -********************************************* -*Process R1b: Enter Retirement - Partnered * -********************************************* -*Sample: Partnered individuals aged 50+ who are not yet retired. -probit drtren i.dgn dag dagsq ib1.deh_c3 i.dagpns li.lesnr_c2 i.dagpns#li.lesnr_c2 li.ydses_c5 li.dlltsd i.dagpns_sp li.lessp_c3 li.dlltsd_sp /// -ib8.drgn1 stm if (ssscp!=1 & dcpst==1 & dag>=50) [pweight=dimlwt], vce(robust) -matrix results = r(table) -matrix results = results[1..6,1...]' -putexcel set "$dir_data/retire", sheet("Process R1b") modify -putexcel A3 = matrix(results), names nformat(number_d2) -putexcel J4 = matrix(e(V)) -outreg2 stats(coef se pval) using "$dir_data/R1b.doc", replace /// -title("Process R1b: Probit regression estimates for retiring - cohabiting individuals aged 50+ not yet retired") /// - ctitle(retiring) label side dec(2) noparen addstat(R2, e(r2_p), Chi2, e(chi2), Log-likelihood, e(ll)) - - -capture log close - diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1 2.do deleted file mode 100644 index 606d6a46b..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1 2.do +++ /dev/null @@ -1,194 +0,0 @@ -/************************************************************************************** -* -* PROGRAM TO EVALUATE SOCIAL CARE FROM FRS DATA -* Last version: Justin van de Ven, 28 Aug 2023 -* First version: Justin van de Ven, 05 Jun 2024 -* -* -**************************************************************************************/ - - -/************************************************************************************** -* -* DATA SET-UP -* -**************************************************************************************/ -clear all -global outdir = "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates\data\" -cd "$outdir" - - -/************************************************************************************** -* compile data -**************************************************************************************/ -global yy = 2015 -foreach datadir in "C:\MyFiles\01 DATA\UK\frs2015-2016\stata\stata11_se" /// - "C:\MyFiles\01 DATA\UK\frs2016-2017\stata" /// - "C:\MyFiles\01 DATA\UK\frs2017-2018\stata" /// - "C:\MyFiles\01 DATA\UK\frs2018-2019\stata" /// - "C:\MyFiles\01 DATA\UK\frs2019-2020\stata\stata13_se" /// - "C:\MyFiles\01 DATA\UK\frs2021-2022\stata\stata13_se" { - - if ($yy == 2020) global yy = $yy + 1 - use "`datadir'/care.dta", clear - drop if (NEEDPER > 14) - rename NEEDPER PERSON - if ($yy == 2018) { - sort sernum BENUNIT PERSON - drop month - merge 1:1 sernum BENUNIT PERSON using "`datadir'/adult.dta" - } - else { - sort SERNUM BENUNIT PERSON - drop MONTH - merge 1:1 SERNUM BENUNIT PERSON using "`datadir'/adult.dta" - } - if ($yy < 2018) { - - drop _merge - merge m:1 SERNUM using "`datadir'/househol.dta" - } - rename *, l - drop if (_merge==1) - drop if (dvhiqual<0) - gen dhe_c3 = 0 - gen male = (sex == 1) - replace dhe_c3 = 3 if (dvhiqual>0 & dvhiqual<4) - replace dhe_c3 = 2 if (dvhiqual>3 & dvhiqual<40) - replace dhe_c3 = 1 if (dvhiqual>39) - gen year = $yy - keep sernum benunit person hourcare hour17 hour18 hour19 hour20 empstati gross4 age80 dhe_c3 male gvtregno year - save "frs_$yy.dta", replace - global yy = $yy + 1 -} - -clear all -append using "frs_2015.dta" "frs_2016.dta" "frs_2017.dta" "frs_2018.dta" "frs_2019.dta" "frs_2021.dta" -save "frs_pooled_raw.dta", replace - - -/************************************************************************************** -* generate variables -**************************************************************************************/ -use "frs_pooled_raw.dta", clear -gen recCare = (hourcare > 0.1) -gen hourFormCare = 0 -foreach vv of varlist hour17 hour18 hour19 hour20 { - replace hourFormCare = hourFormCare + 2.5 if (`vv'==1) - replace hourFormCare = hourFormCare + 7.5 if (`vv'==2) - replace hourFormCare = hourFormCare + 15 if (`vv'==3) - replace hourFormCare = hourFormCare + 27.5 if (`vv'==4) - replace hourFormCare = hourFormCare + 42.5 if (`vv'==5) - replace hourFormCare = hourFormCare + 75 if (`vv'==6) - replace hourFormCare = hourFormCare + 150 if (`vv'==7) - replace hourFormCare = hourFormCare + 10 if (`vv'==8) - replace hourFormCare = hourFormCare + 27.5 if (`vv'==9) - replace hourFormCare = hourFormCare + 95 if (`vv'==10) -} -gen hourInfCare = hourcare*(hourcare>0) - hourFormCare -gen recFormCare = (hourFormCare>0) -gen recInfCare = (hourInfCare>0) -replace hourcare = 0 if (hourcare<0) - -gen ltsd = (empstati==9) -save "frs_pooled.dta", replace - - -/************************************************************************************** -* basic statistical analysis -**************************************************************************************/ -/* -use "frs_pooled.dta", clear -tab dhe_c3 year [fweight=gross4] -tab ltsd recCare [fweight=gross4] if (age80>19 & age80<40) -tab ltsd recCare [fweight=gross4] if (age80>39 & age80<50) -tab ltsd recCare [fweight=gross4] if (age80>49 & age80<60) -tab ltsd recCare [fweight=gross4] if (age80>59 & age80<65) - -matrix store = J(7,7,.) -forval ii = 1/7{ - sum recCare [fweight=gross4] if (age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',1] = r(mean) - sum recInfCare [fweight=gross4] if (age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',2] = r(mean) - sum recFormCare [fweight=gross4] if (age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',3] = r(mean) - sum hourInfCare [fweight=gross4] if (recInfCare==1 & age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',4] = r(mean) - sum hourFormCare [fweight=gross4] if (recFormCare==1 & age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',5] = r(mean) - sum hourInfCare [fweight=gross4] if (recInfCare==1 & recFormCare==1 & age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',6] = r(mean) - sum hourFormCare [fweight=gross4] if (recInfCare==1 & recFormCare==1 & age80>19+10*(`ii'-1) & age80<30+10*(`ii'-1)) - matrix store[`ii',7] = r(mean) -} -matlist store - -matrix store = J(14,7,.) -forval ii = 1/14{ - qui{ - sum recCare [fweight=gross4] if (age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',1] = r(mean) - sum recInfCare [fweight=gross4] if (age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',2] = r(mean) - sum recFormCare [fweight=gross4] if (age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',3] = r(mean) - sum hourInfCare [fweight=gross4] if (recInfCare==1 & age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',4] = r(mean) - sum hourFormCare [fweight=gross4] if (recFormCare==1 & age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',5] = r(mean) - sum hourInfCare [fweight=gross4] if (recInfCare==1 & recFormCare==1 & age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',6] = r(mean) - sum hourFormCare [fweight=gross4] if (recInfCare==1 & recFormCare==1 & age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) - matrix store[`ii',7] = r(mean) - } -} -matlist store -*/ - -/************************************************************************************** -* regression analysis -**************************************************************************************/ -use "frs_pooled.dta", clear -/* -gen ageg5 = 0 -forval ii = 1/10 { - replace ageg5 = `ii' if (age80>14+5*(`ii'-1) & age80<20+5*(`ii'-1)) -} -probit recInfCare i.dhe_c3 i.male i.ageg5 ib8.gvtregno i.year if (ltsd==1 & age80<65) [fweight=gross4] -regress hourInfCare i.dhe_c3 i.male i.ageg5 ib8.gvtregno i.year if (ltsd==1 & age80<65 & recInfCare==1) [fweight=gross4] - -gen agega = 0 -replace agega = 1 if (age80<18) -replace agega = 2 if (age80>17 & age80<20) -replace agega = 3 if (age80>19 & age80<22) -replace agega = 4 if (age80>21 & age80<24) -replace agega = 5 if (age80>23 & age80<26) -replace agega = 6 if (age80>25 & age80<28) -replace agega = 7 if (age80>27 & age80<30) -replace agega = 8 if (age80>29 & age80<32) -replace agega = 9 if (age80>31 & age80<34) -replace agega = 10 if (age80>33 & age80<36) -replace agega = 11 if (age80>35 & age80<38) -replace agega = 12 if (age80>37 & age80<40) -replace agega = 13 if (age80>39 & age80<42) -replace agega = 14 if (age80>41 & age80<44) -replace agega = 15 if (age80>43 & age80<46) -probit recInfCare i.dhe_c3 i.male i.agega ib8.gvtregno if (ltsd==1 & age80<65) [fweight=gross4] -regress hourInfCare i.dhe_c3 i.male i.agega ib8.gvtregno if (ltsd==1 & age80<65 & recInfCare==1) [fweight=gross4] -*/ - -// Process S1a -gen aged = (age80<25) -probit recInfCare i.dhe_c3 male aged ib8.gvtregno if (ltsd==1 & age80<65) [fweight=gross4], vce(r) -putexcel set "$outdir/probitCareUnder65", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// Process S1b -gen agee = (age80<25) + 2*(age80>24)*(age80<40) + 3*(age80>39) -gen lhourInfCare = ln(hourInfCare) if (recInfCare==1) -regress lhourInfCare i.dhe_c3 i.male i.agee ib8.gvtregno if (ltsd==1 & age80<65 & recInfCare==1) [fweight=gross4], vce(r) -putexcel set "$outdir/linearCareUnder65", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1.do index 606d6a46b..f5d500314 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare1.do @@ -1,8 +1,8 @@ /************************************************************************************** * * PROGRAM TO EVALUATE SOCIAL CARE FROM FRS DATA -* Last version: Justin van de Ven, 28 Aug 2023 -* First version: Justin van de Ven, 05 Jun 2024 +* First version: Justin van de Ven, 28 Aug 2023 +* Last version: Justin van de Ven, 19 Nov 2025 * * **************************************************************************************/ @@ -180,7 +180,8 @@ regress hourInfCare i.dhe_c3 i.male i.agega ib8.gvtregno if (ltsd==1 & age80<65 // Process S1a gen aged = (age80<25) -probit recInfCare i.dhe_c3 male aged ib8.gvtregno if (ltsd==1 & age80<65) [fweight=gross4], vce(r) +gen covid = (year==2021) +probit recInfCare i.dhe_c3 male aged ib8.gvtregno covid if (ltsd==1 & age80<65) [fweight=gross4], vce(r) putexcel set "$outdir/probitCareUnder65", modify putexcel A1 = matrix(e(b)) putexcel A2 = matrix(e(V)) @@ -188,7 +189,7 @@ putexcel A2 = matrix(e(V)) // Process S1b gen agee = (age80<25) + 2*(age80>24)*(age80<40) + 3*(age80>39) gen lhourInfCare = ln(hourInfCare) if (recInfCare==1) -regress lhourInfCare i.dhe_c3 i.male i.agee ib8.gvtregno if (ltsd==1 & age80<65 & recInfCare==1) [fweight=gross4], vce(r) +regress lhourInfCare i.dhe_c3 i.male i.agee ib8.gvtregno covid if (ltsd==1 & age80<65 & recInfCare==1) [fweight=gross4], vce(r) putexcel set "$outdir/linearCareUnder65", modify putexcel A1 = matrix(e(b)) putexcel A2 = matrix(e(V)) diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2 2.do deleted file mode 100644 index 9025b6373..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2 2.do +++ /dev/null @@ -1,413 +0,0 @@ -/************************************************************************************** -* -* PROGRAM TO EVALUATE SOCIAL CARE RECEIPT FROM UKHLS DATA -* ANALYSIS BASED ON THE SOCIAL CARE MODULE OF UKHLS -* First version: Justin van de Ven, 28 Aug 2023 -* Last version: Justin van de Ven, 05 Jun 2024 -* -**************************************************************************************/ - - -/************************************************************************************** -* -* DATA SET-UP -* -**************************************************************************************/ -clear all -global datadir = "C:\MyFiles\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" -global outdir = "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates\data\" -cd "$outdir" - - -/************************************************************************************** -* load data -**************************************************************************************/ -// pooled data -local ww = 1 -foreach waveid in "g" "i" "k" { - - use "$datadir/`waveid'_indresp.dta", clear - rename *, l - rename `waveid'_* * - - gen year = intdaty_dv - if (`ww' < 3) { - gen helphours9 = -1 - gen helphoursb9 = -1 - gen helpcode9 = -1 - } - gen wave = `ww' - gen male = (sex==1) - gen partner = (ppid>0) - gen emp = (jbstat==1 | jbstat==2) - rename gor_dv drgn - - keep pidp hidp pno year wave male partner drgn hiqual_dv dvage scsf1 adl* hlpinf* hlpform* helphours* helpcode* emp indinui_xw - save "ukhls_`waveid'.dta", replace - local ww = `ww' + 1 -} - -clear all -append using "ukhls_g.dta" "ukhls_i.dta" "ukhls_k.dta" -save "ukhls_pooled_raw.dta", replace - - -/************************************************************************************** -* generate variables -**************************************************************************************/ -use "ukhls_pooled_raw.dta", clear -gen needCare1 = 0 // any help -gen needCare2 = 0 // not possible to do -foreach vv of varlist adla adlb adlc adld adle adlf adlg adlh adli adlj adlk adll adlm adln { - - replace needCare1 = needCare1 + 0.5 if (`vv'>1) - replace needCare2 = 1 if (`vv'==3) -} -replace needCare1 = 1 if (needCare1>1) -replace needCare1 = 0 if (needCare1<0.9) -gen recInfCareb = 0 -forval ii = 1/10 { - - replace recInfCareb = 1 if (hlpinfa`ii' == 1) - replace recInfCareb = 1 if (hlpinfb`ii' == 1) -} -gen recFormCareb = 0 -forval ii = 1/7 { - - replace recFormCareb = 1 if (hlpforma`ii' == 1) - replace recFormCareb = 1 if (hlpformb`ii' == 1) -} -replace recFormCareb = 1 if (hlpforma97==1) -replace recFormCareb = 1 if (hlpformb97==1) -gen recCareb = max(recFormCareb, recInfCareb) - -gen hourFormCare = 0 -gen hourInfCare = 0 -gen hourPartner = 0 -gen hourDaughter = 0 -gen hourSon = 0 -gen hourParent = 0 -gen numbFormCare = 0 -gen numbInfCare = 0 -forval ii = 1/9 { - - gen hrs = 0 - replace hrs = 2.5 if (helphours`ii' == 3) - replace hrs = 7.0 if (helphours`ii' == 4) - replace hrs = 14.5 if (helphours`ii' == 5) - replace hrs = 27.0 if (helphours`ii' == 6) - replace hrs = 42.0 if (helphours`ii' == 7) - replace hrs = 74.5 if (helphours`ii' == 8) - replace hrs = 125.0 if (helphours`ii' == 9) - gen cc = 0 - replace cc = 1 if (helphours`ii' > 2) - if (helphours`ii' < 2) { - replace hrs = 14.5 if (helphoursb`ii' == 1) - replace hrs = 27.0 if (helphoursb`ii' == 2) - replace hrs = 100.0 if (helphoursb`ii' == 3) - replace cc = 1 if (helphoursb`ii' > 0) - } - replace hourPartner = hourPartner + hrs if (helpcode`ii'==1 & hrs>0) - replace hourSon = hourSon + hrs if (helpcode`ii'==2 & hrs>0) - replace hourDaughter = hourDaughter + hrs if (helpcode`ii'==3 & hrs>0) - replace hourParent = hourParent + hrs if (helpcode`ii'==7 & hrs>0) - replace hourInfCare = hourInfCare + hrs if (helpcode`ii'>=1 & helpcode`ii'<=10 & hrs>0) - replace hourFormCare = hourFormCare + hrs if (helpcode`ii'>=11 & hrs>0) - - replace numbFormCare = numbFormCare + cc if (helpcode`ii'>=11) - replace numbInfCare = numbInfCare + cc if (helpcode`ii'>=1 & helpcode`ii'<=10) - - drop hrs cc -} -gen hourOtherCare = hourInfCare - hourPartner - hourSon - hourDaughter -gen recInfCare = (hourInfCare > 0) -gen recFormCare = (hourFormCare > 0) -gen recCare = (hourInfCare + hourFormCare > 0) -gen recDaughter = (hourDaughter>0) -gen recSon = (hourSon>0) -gen recPartner = (hourPartner>0) -gen recOther = (hourOther>0) -save "ukhls_pooled.dta", replace - - -/************************************************************************************** -* basic statistical analysis -**************************************************************************************/ -/* -use "ukhls_pooled.dta", clear -keep if year < 2020 -tab numbInfCare numbFormCare [aweight=indinui_xw] if (recCare > 0) -matrix store = J(4,7,.) -matrix store2 = J(4,3,.) -forval ii = 11/14{ - qui { - if (`ii'==14) { - local maxAge = 150 - } - else { - local maxAge = 20+5*(`ii'-1) - } - - sum needCare1 [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store2[`ii'-10,1] = r(mean) - sum needCare2 [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store2[`ii'-10,2] = r(mean) - sum recCareb [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store2[`ii'-10,3] = r(mean) - - sum recCare [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,1] = r(mean) - sum recInfCare [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,2] = r(mean) - sum recFormCare [aweight=indinui_xw] if (dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,3] = r(mean) - sum hourInfCare [aweight=indinui_xw] if (recInfCare==1 & dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,4] = r(mean) - sum hourFormCare [aweight=indinui_xw] if (recFormCare==1 & dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,5] = r(mean) - sum hourInfCare [aweight=indinui_xw] if (recInfCare==1 & recFormCare==1 & dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,6] = r(mean) - sum hourFormCare [aweight=indinui_xw] if (recInfCare==1 & recFormCare==1 & dvage>14+5*(`ii'-1) & dvage<`maxAge') - matrix store[`ii'-10,7] = r(mean) - } -} -matlist store -matlist store2 - - -matrix store3 = J(5,4,.) -local jj = 0 -foreach vv of varlist recPartner recDaughter recSon recOther { - - qui { - local jj = `jj' + 1 - local ii = 1 - sum `vv' [aweight=indinui_xw] if (recCare==1) - matrix store3[`ii',`jj'] = r(mean) - foreach ww of varlist recPartner recDaughter recSon recOther { - - local ii = `ii' + 1 - sum `ww' [aweight=indinui_xw] if (`vv'==1) - matrix store3[`ii',`jj'] = r(mean) - } - } -} -matlist store3 -*/ - -/************************************************************************************** -* prepare time-series data for regression analysis -**************************************************************************************/ -clear all -forval ii = 1/3 { - use "ukhls_pooled.dta", clear - keep if (wave == `ii') - save "ukhlst_`ii'.dta", replace -} -forval ii = 1/2 { - use "ukhlst_`ii'.dta", clear - rename * *_l - rename pidp_l pidp - local jj = `ii' + 1 - merge 1:1 pidp using "ukhlst_`jj'.dta" - save "ukhlstml_`jj'.dta", replace -} - -clear all -append using "ukhlstml_2.dta" "ukhlstml_3.dta" -save "ukhlstml_pooled.dta", replace - - -/************************************************************************************** -* regression variables -**************************************************************************************/ -clear all -use "ukhlstml_pooled.dta", clear -keep if (_merge==3 & dvage>64) -replace drgn = . if (drgn<0) -replace scsf1 = . if (scsf1<0) -gen deh_c3 = . -replace deh_c3 = 1 if (hiqual_dv == 1) -replace deh_c3 = 2 if (hiqual_dv>1 & hiqual_dv<5) -replace deh_c3 = 3 if (hiqual_dv>4) -gen dage1 = 0 -forval ii = 1/10 { - replace dage1 = `ii' if (dvage>=65+2*(`ii'-1) & dvage<=67+2*(`ii'-1)) -} -replace dage1 = 11 if (dvage>85) -gen dage2 = 0 -replace dage2 = 1 if (dvage>=85 & dvage<=89) -replace dage2 = 2 if (dvage>89) -gen dage3 = (dvage>=85) - -gen careMarket = . -replace careMarket = 0 if (recInfCare==0 & recFormCare==0) -replace careMarket = 1 if (recInfCare==1 & recFormCare==0) -replace careMarket = 2 if (recInfCare==1 & recFormCare==1) -replace careMarket = 3 if (recInfCare==0 & recFormCare==1) -gen careMarket_l = . -replace careMarket_l = 0 if (recInfCare_l==0 & recFormCare_l==0) -replace careMarket_l = 1 if (recInfCare_l==1 & recFormCare_l==0) -replace careMarket_l = 2 if (recInfCare_l==1 & recFormCare_l==1) -replace careMarket_l = 3 if (recInfCare_l==0 & recFormCare_l==1) - -gen whoCares = . -replace whoCares = 0 if (recPartner==1) -replace whoCares = 3 if (recOther==1) -replace whoCares = 2 if (recSon==1) -replace whoCares = 1 if (recDaughter==1) -gen whoCares_l = . -replace whoCares_l = 0 if (recPartner_l==1) -replace whoCares_l = 3 if (recOther_l==1) -replace whoCares_l = 2 if (recSon_l==1) -replace whoCares_l = 1 if (recDaughter_l==1) - -gen whoCares2 = . -replace whoCares2 = 0 if (recDaughter==0 & recSon==0 & recOther==0) -replace whoCares2 = 1 if (recDaughter==1 & recSon==0 & recOther==0) -replace whoCares2 = 2 if (recDaughter==1 & recSon==1 & recOther==0) -replace whoCares2 = 3 if (recDaughter==1 & recSon==0 & recOther==1) -replace whoCares2 = 4 if (recDaughter==0 & recSon==1 & recOther==0) -replace whoCares2 = 5 if (recDaughter==0 & recSon==1 & recOther==1) -replace whoCares2 = 6 if (recDaughter==0 & recSon==0 & recOther==1) -gen whoCares2_l = . -replace whoCares2_l = 0 if (recDaughter_l==0 & recSon_l==0 & recOther_l==0) -replace whoCares2_l = 1 if (recDaughter_l==1 & recSon_l==0 & recOther_l==0) -replace whoCares2_l = 2 if (recDaughter_l==1 & recSon_l==1 & recOther_l==0) -replace whoCares2_l = 3 if (recDaughter_l==1 & recSon_l==0 & recOther_l==1) -replace whoCares2_l = 4 if (recDaughter_l==0 & recSon_l==1 & recOther_l==0) -replace whoCares2_l = 5 if (recDaughter_l==0 & recSon_l==1 & recOther_l==1) -replace whoCares2_l = 6 if (recDaughter_l==0 & recSon_l==0 & recOther_l==1) - -gen poorHealth = (scsf1==5) -save "ukhlstmlb_pooled.dta", replace - - -/************************************************************************************** -* adjust estimated sample to control for data observed every second year -* -* any observation that does not change its status between observations is assumed to remain -* invariant for intervening year -* any observation that changes status between observations is replicated twice for intervening -* year - once to take previous value another to take altered value, with survey weights of -* each observation halved. -* -**************************************************************************************/ -// start by selecting only population that alters status between observations -// this is the replicated sample -use "ukhlstmlb_pooled.dta", clear -gen wgt = indinui_xw -replace wgt = wgt / 2 if (needCare1!=needCare1_l | recCare!=recCare_l | careMarket!=careMarket_l | recPartner!=recPartner_l | whoCares!=whoCares_l | whoCares2!=whoCares2_l) -save "ukhlstmc_pooled.dta", replace -keep if (needCare1!=needCare1_l | recCare!=recCare_l | careMarket!=careMarket_l | recPartner!=recPartner_l | whoCares!=whoCares_l | whoCares2!=whoCares2_l) -replace indinui_xw = . -gen needCare1_l1 = needCare1 -gen recCare_l1 = recCare -gen careMarket_l1 = careMarket -gen recPartner_l1 = recPartner -gen whoCares_l1 = whoCares -gen whoCares2_l1 = whoCares2 -save "ukhlstmd_pooled.dta", replace -use "ukhlstmc_pooled.dta", clear -gen needCare1_l1 = needCare1_l -gen recCare_l1 = recCare_l -gen careMarket_l1 = careMarket_l -gen recPartner_l1 = recPartner_l -gen whoCares_l1 = whoCares_l -gen whoCares2_l1 = whoCares2_l -append using "ukhlstmd_pooled.dta" -save "ukhlstme_pooled.dta", replace - - -/************************************************************************************** -* evaluate regressions -**************************************************************************************/ -use "ukhlstme_pooled.dta", clear - -// london is drgn=7 -// probit for need care (2a) -//probit needCare1 male i.deh_c3 partner needCare1_l i.scsf1 i.dage1 ib7.drgn [pweight=indinui_xw], vce(r) -probit needCare1 male i.deh_c3 partner needCare1_l1 i.scsf1 i.dage1 ib7.drgn [pweight=wgt], vce(r) -putexcel set "$outdir/probitNeedCareOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// probit for receive care (2b) -//probit recCare male i.deh_c3 partner recCare_l i.scsf1 i.dage1 ib7.drgn [pweight=indinui_xw], vce(r) -probit recCare male i.deh_c3 partner recCare_l1 i.scsf1 i.dage1 ib7.drgn [pweight=wgt], vce(r) -putexcel set "$outdir/probitRecCareOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// mlogit for formal/informal care (2c) -//mlogit careMarket i.deh_c3 partner i.careMarket_l dage3 ib7.drgn if (recCare==1) [pweight=indinui_xw], vce(r) -mlogit careMarket i.deh_c3 partner i.careMarket_l1 dage3 ib7.drgn if (recCare==1) [pweight=wgt], vce(r) -putexcel set "$outdir/mlogitCareMarketOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// probit of partner care (2d) -//probit recPartner male recPartner_l dage3 ib7.drgn [pweight=indinui_xw] if (recCare==1 & partner==1), vce(r) -probit recPartner male recPartner_l1 recFormCare dage3 ib7.drgn [pweight=wgt] if (recInfCare==1 & partner==1), vce(r) -putexcel set "$outdir/probitParnerCareOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// mlogit of other carers for people who have partners caring for them (2e - allowing for formal care not significant) -//mlogit whoCares i.whoCares_l if (recPartner==1) [pweight=indinui_xw], vce(r) -mlogit whoCares i.whoCares_l1 recPartner_l1 if (recPartner==1) [pweight=wgt], vce(r) -putexcel set "$outdir/mlogitPartnerOthCareOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// mlogit of other carers for people who have partners caring for them (2f - lag partner and formal care dummies not significant) -//mlogit whoCares2 i.whoCares2_l if (recPartner==0) [pweight=indinui_xw], vce(r) -mlogit whoCares2 i.whoCares2_l1 if (recPartner==0 & recInfCare==1) [pweight=wgt], vce(r) -putexcel set "$outdir/mlogitNoPartnerOthCareOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// linear regression for partner hours (2g) -gen lhourPartner = ln(hourPartner) if (recPartner==1) -//regress hourPartner male i.deh_c3 recDaughter recSon recOther recFormCare i.scsf1 i.dage1 ib7.drgn if (recPartner==1) [pweight=indinui_xw], vce(r) -//regress hourPartner male i.deh_c3 recDaughter recSon recOther recFormCare i.scsf1 if (recPartner==1) [pweight=indinui_xw], vce(r) -//regress hourPartner male i.deh_c3 recDaughter recSon recOther recFormCare poorHealth ib7.drgn if (recPartner==1) [pweight=indinui_xw], vce(r) -regress lhourPartner male i.deh_c3 recDaughter recSon recOther recFormCare poorHealth ib7.drgn if (recPartner==1) [pweight=indinui_xw], vce(r) -putexcel set "$outdir/linearPartnerHoursOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// linear regression for daughter hours (2h) -gen lhourDaughter = ln(hourDaughter) if (recDaughter==1) -//regress hourDaughter male i.deh_c3 recPartner recSon recOther recFormCare poorHealth ib7.drgn if (recDaughter==1) [pweight=indinui_xw], vce(r) -regress lhourDaughter male i.deh_c3 recPartner recSon recOther recFormCare poorHealth ib7.drgn if (recDaughter==1) [pweight=indinui_xw], vce(r) -putexcel set "$outdir/linearDaughterHoursOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// linear regression for son hours (2i) -gen lhourSon = ln(hourSon) if (recSon==1) -//regress hourSon male i.deh_c3 recPartner recDaughter recOther recFormCare poorHealth ib7.drgn if (recSon==1) [pweight=indinui_xw], vce(r) -regress lhourSon male i.deh_c3 recPartner recDaughter recOther recFormCare poorHealth ib7.drgn if (recSon==1) [pweight=indinui_xw], vce(r) -putexcel set "$outdir/linearSonHoursOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// linear regression for other hours (2j) -gen lhourOther = ln(hourOtherCare) if (recOther==1) -//regress hourOtherCare male i.deh_c3 recPartner recDaughter recSon recFormCare poorHealth ib7.drgn if (recOther==1) [pweight=indinui_xw], vce(r) -regress lhourOther male i.deh_c3 recPartner recDaughter recSon recFormCare poorHealth ib7.drgn if (recOther==1) [pweight=indinui_xw], vce(r) -putexcel set "$outdir/linearOtherHoursOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// linear regression for formal hours (2k) -gen lhourFormal = ln(hourFormCare) if (recFormCare==1) -//regress hourFormCare male i.deh_c3 recPartner recDaughter recSon recOther poorHealth ib7.drgn if (recFormCare==1) [pweight=indinui_xw], vce(r) -//regress lhourFormal male i.deh_c3 recPartner recDaughter recSon recOther poorHealth ib7.drgn if (recFormCare==1) [pweight=indinui_xw], vce(r) -regress lhourFormal male i.deh_c3 recInfCare poorHealth ib7.drgn if (recFormCare==1) [pweight=indinui_xw], vce(r) -putexcel set "$outdir/linearFormalHoursOver64", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - - diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2.do index 9025b6373..8cd50c11f 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare2.do @@ -3,7 +3,7 @@ * PROGRAM TO EVALUATE SOCIAL CARE RECEIPT FROM UKHLS DATA * ANALYSIS BASED ON THE SOCIAL CARE MODULE OF UKHLS * First version: Justin van de Ven, 28 Aug 2023 -* Last version: Justin van de Ven, 05 Jun 2024 +* Last version: Justin van de Ven, 19 Nov 2025 * **************************************************************************************/ @@ -14,7 +14,7 @@ * **************************************************************************************/ clear all -global datadir = "C:\MyFiles\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" +global datadir = "J:\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" global outdir = "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates\data\" cd "$outdir" @@ -323,18 +323,19 @@ save "ukhlstme_pooled.dta", replace * evaluate regressions **************************************************************************************/ use "ukhlstme_pooled.dta", clear +gen covid = (year>2019) * (year<2023) // london is drgn=7 // probit for need care (2a) //probit needCare1 male i.deh_c3 partner needCare1_l i.scsf1 i.dage1 ib7.drgn [pweight=indinui_xw], vce(r) -probit needCare1 male i.deh_c3 partner needCare1_l1 i.scsf1 i.dage1 ib7.drgn [pweight=wgt], vce(r) +probit needCare1 male i.deh_c3 partner needCare1_l1 i.scsf1 i.dage1 ib7.drgn covid [pweight=wgt], vce(r) putexcel set "$outdir/probitNeedCareOver64", modify putexcel A1 = matrix(e(b)) putexcel A2 = matrix(e(V)) // probit for receive care (2b) //probit recCare male i.deh_c3 partner recCare_l i.scsf1 i.dage1 ib7.drgn [pweight=indinui_xw], vce(r) -probit recCare male i.deh_c3 partner recCare_l1 i.scsf1 i.dage1 ib7.drgn [pweight=wgt], vce(r) +probit recCare male i.deh_c3 partner recCare_l1 i.scsf1 i.dage1 ib7.drgn covid [pweight=wgt], vce(r) putexcel set "$outdir/probitRecCareOver64", modify putexcel A1 = matrix(e(b)) putexcel A2 = matrix(e(V)) diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3 2.do deleted file mode 100644 index d4229ebc2..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3 2.do +++ /dev/null @@ -1,414 +0,0 @@ -/************************************************************************************** -* -* PROGRAM TO EVALUATE SOCIAL CARE SUPPLY FROM UKHLS DATA -* ANALYSIS BASED ON THE CARE MODULE OF UKHLS -* First version: Justin van de Ven, 16 Oct 2023 -* Last version: Justin van de Ven, 05 Jun 2024 -* -**************************************************************************************/ - - -/************************************************************************************** -* -* DATA SET-UP -* -**************************************************************************************/ -clear all -global datadir = "C:\MyFiles\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" -global outdir = "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates\data\" -cd "$outdir" -global UKHLSWaves "f g h i j k l" - - -/************************************************************************************** -* load data -**************************************************************************************/ -// pooled data -foreach waveid in $UKHLSWaves { - - local waveno=strpos("abcdefghijklmnopqrstuvwxyz","`waveid'") - - use "$datadir/`waveid'_indresp.dta", clear - rename *, l - rename `waveid'_* * - gen wave = `waveno' - keep pidp hidp pno intdaty_dv wave sex dvage ppid gor_dv hiqual_dv jbstat aidhh aidxhh aidhrs aidhu* aideft scsf1 indinui_xw naidxhh - save "$outdir/int_temp.dta", replace - - use "$datadir/`waveid'_egoalt.dta", clear - rename *, l - rename `waveid'_* * - sort pidp apno - forval ii = 1/16 { - gen rindiv_here = 0 - replace rindiv_here = relationship_dv if (apno == `ii') - by pidp: egen rindiv`ii' = max(rindiv_here) - drop rindiv_here - } - gen chk = 0 - replace chk = 1 if (pidp == pidp[_n-1]) - drop if (chk==1) - drop chk - merge 1:1 pidp using "$outdir/int_temp.dta", keep(2 3) nogen - keep pidp hidp pno intdaty_dv wave sex dvage ppid gor_dv hiqual_dv jbstat aidhh aidxhh aidhrs aidhu* aideft scsf1 indinui_xw naidxhh rindiv* - save "$outdir/ukhls_supply_`waveid'.dta", replace -} -clear all -foreach waveid in $UKHLSWaves { - if ("`waveid'" == "f") { - use "$outdir/ukhls_supply_`waveid'.dta", clear - } - else { - append using "$outdir/ukhls_supply_`waveid'.dta" - } -} -save "$outdir/ukhls_supply_pooled0.dta", replace - - -/************************************************************************************** -* process variables -**************************************************************************************/ -use "ukhls_supply_pooled0.dta", clear - -rename intdaty_dv year -rename gor_dv drgn - -gen male = (sex==1) -gen partner = (ppid>0) -gen emp = (jbstat==1 | jbstat==2) - -// deh_c3 = 1 (degree), 2 (GCSE to other higher degree), 3 (other/no qualification) -gen deh_c3 = . -replace deh_c3 = 1 if (hiqual_dv==1) -replace deh_c3 = 2 if (hiqual_dv>1 & hiqual_dv<5) -replace deh_c3 = 3 if (hiqual_dv>4) - -// provision of care -gen provCare = (aidhh==1) | (aidxhh==1) -gen naidhh = 0 -forval ii = 1/16 { - replace naidhh = naidhh + 1 if (aidhua`ii' > 0) -} -gen nAidTot = naidhh + naidxhh * (naidxhh>0) -forval ii = 1/16 { - replace rindiv`ii' = 0 if (missing(rindiv`ii')) -} - -// relationship to care recipient in household -gen care_partner = 0 -gen care_parent = 0 -gen care_child = 0 -gen care_sibling = 0 -gen care_grandchild = 0 -gen care_grandparent = 0 -gen care_otherfamily = 0 -gen care_other = 0 -forval ii = 1/16 { - // loop over each individual - - replace care_partner = 1 if (aidhua`ii'>0 & rindiv`ii' > 0 & rindiv`ii' < 4) - replace care_parent = 1 if (aidhua`ii'>0 & rindiv`ii' > 3 & rindiv`ii' < 9) - replace care_child = 1 if (aidhua`ii'>0 & rindiv`ii' > 8 & rindiv`ii' < 14) - replace care_sibling = 1 if (aidhua`ii'>0 & rindiv`ii' > 13 & rindiv`ii' < 20) - replace care_grandchild = 1 if (aidhua`ii'>0 & rindiv`ii' == 20) - replace care_grandparent = 1 if (aidhua`ii'>0 & rindiv`ii' == 21) - replace care_otherfamily = 1 if (aidhua`ii'>0 & rindiv`ii' > 21 & rindiv`ii' < 26) - replace care_other = 1 if (aidhua`ii'>0 & rindiv`ii' > 25) -} -replace care_parent = 1 if (aidhu1 == 1 | aidhu2 == 1) -replace care_grandparent = 1 if (aidhu1 == 2 | aidhu2 == 2) -replace care_otherfamily = 1 if (aidhu1 == 3 | aidhu2 == 3) -replace care_otherfamily = 1 if (aidhu1 == 4 | aidhu2 == 4) -replace care_other = 1 if (aidhu1 > 4 | aidhu2 > 4) -gen care_others = care_sibling + care_grandchild + care_grandparent + care_otherfamily + care_other - -gen aidhrs_adj = 0 -replace aidhrs_adj = 2 if (aidhrs==1) -replace aidhrs_adj = 7 if (aidhrs==2) -replace aidhrs_adj = 14.5 if (aidhrs==3) -replace aidhrs_adj = 27.5 if (aidhrs==4) -replace aidhrs_adj = 42 if (aidhrs==5) -replace aidhrs_adj = 74.5 if (aidhrs==6) -replace aidhrs_adj = 120 if (aidhrs==7) -replace aidhrs_adj = 5.48 if (aidhrs==8) //weighted average of 1 to 3 -replace aidhrs_adj = 71.5 if (aidhrs==9) //weighted average of 4 to 7 - -replace drgn = . if (drgn<0) -replace scsf1 = . if (scsf1<0) -gen dage1 = 0 -forval ii = 1/14 { - replace dage1 = `ii' if (dvage>=15+5*(`ii'-1) & dvage<=19+5*(`ii'-1)) -} -replace dage1 = 15 if (dvage>=85) - -gen poorHealth = (scsf1==5) - -gen care_nonpartner = (care_parent + care_child + care_others > 0) -gen careWho = 0 -replace careWho = 1 if (care_partner==1 & care_nonpartner==0) -replace careWho = 2 if (care_partner==1 & care_nonpartner==1) -replace careWho = 3 if (care_partner==0 & care_nonpartner==1) - -save "ukhls_supply_pooled.dta", replace - - -/************************************************************************************** -* basic statistical analysis -**************************************************************************************/ -/* -use "ukhls_supply_pooled.dta", clear -keep if (year<2021 & year>2014) -matrix store = J(14,4,.) -forval ii = 1/14{ - qui { - if (`ii'==14) { - local maxAge = 150 - } - else { - local maxAge = 20+5*(`ii'-1) - } - sum provCare [aweight=indinui_xw] if (dvage>15+5*(`ii'-1) & dvage<`maxAge' & male==1) - matrix store[`ii',1] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (dvage>15+5*(`ii'-1) & dvage<`maxAge' & provCare>0 & male==1) - matrix store[`ii',2] = r(mean) - sum provCare [aweight=indinui_xw] if (dvage>15+5*(`ii'-1) & dvage<`maxAge' & male==0) - matrix store[`ii',3] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (dvage>15+5*(`ii'-1) & dvage<`maxAge' & provCare>0 & male==0) - matrix store[`ii',4] = r(mean) - } -} -matlist store - -matrix store1 = J(5,4,.) -forval ii = 1/5{ - qui { - sum provCare [aweight=indinui_xw] if (scsf1==`ii' & male==1) - matrix store1[`ii',1] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (scsf1==`ii' & provCare>0 & male==1) - matrix store1[`ii',2] = r(mean) - sum provCare [aweight=indinui_xw] if (scsf1==`ii' & male==0) - matrix store1[`ii',3] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (scsf1==`ii' & provCare>0 & male==0) - matrix store1[`ii',4] = r(mean) - } -} -matlist store1 - -matrix store2 = J(4,4,.) -forval ii = 1/3{ - qui { - sum provCare [aweight=indinui_xw] if (deh_c3==`ii' & male==1) - matrix store2[`ii',1] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (deh_c3==`ii' & provCare>0 & male==1) - matrix store2[`ii',2] = r(mean) - sum provCare [aweight=indinui_xw] if (deh_c3==`ii' & male==0) - matrix store2[`ii',3] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (deh_c3==`ii' & provCare>0 & male==0) - matrix store2[`ii',4] = r(mean) - } -} -qui { - sum provCare [aweight=indinui_xw] if (male==1) - matrix store2[4,1] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (provCare>0 & male==1) - matrix store2[4,2] = r(mean) - sum provCare [aweight=indinui_xw] if (male==0) - matrix store2[4,3] = r(mean) - sum aidhrs_adj [aweight=indinui_xw] if (provCare>0 & male==0) - matrix store2[4,4] = r(mean) -} -matlist store2 - -matrix store3 = J(4,3,.) -forval ii = 1/4 { - qui { - if (`ii'<4) { - gen chk = (nAidTot == `ii') - } - else { - gen chk = (nAidTot > 3) - } - sum chk [aweight=indinui_xw] if (nAidTot>0 & male==1) - matrix store3[`ii',1] = r(mean) - sum chk [aweight=indinui_xw] if (nAidTot>0 & male==0) - matrix store3[`ii',2] = r(mean) - sum chk [aweight=indinui_xw] if (nAidTot>0) - matrix store3[`ii',3] = r(mean) - drop chk - } -} -matlist store3 - -matrix store4 = J(8,3,.) -local ii = 1 -foreach vv of varlist care_partner care_parent care_child care_sibling care_grandchild care_grandparent care_otherfamily care_other { - qui { - sum `vv' [aweight=indinui_xw] if (provCare>0 & male==1) - matrix store4[`ii',1] = r(mean) - sum `vv' [aweight=indinui_xw] if (provCare>0 & male==0) - matrix store4[`ii',2] = r(mean) - sum `vv' [aweight=indinui_xw] if (provCare>0) - matrix store4[`ii',3] = r(mean) - local ii = `ii' + 1 - } -} -matlist store4 - -matrix store5 = J(7,6,.) -gen chk2 = (jbstat==1 | jbstat==2) -gen chk3 = (jbstat==3) -gen chk4 = (aideft==1) -gen chk5 = (aideft==2) -gen chk6 = (aideft==3 | jbstat==6) -forval ii = 1/6 { - - if (`ii' == 1) { - gen chk1 = (aidhrs_adj<5) - } - else if (`ii' == 2) { - gen chk1 = (aidhrs_adj>4) * (aidhrs_adj<10) - } - else if (`ii' == 3) { - gen chk1 = (aidhrs_adj>9) * (aidhrs_adj<20) - } - else if (`ii' == 4) { - gen chk1 = (aidhrs_adj>19) * (aidhrs_adj<40) - } - else if (`ii' == 5) { - gen chk1 = (aidhrs_adj>39) * (aidhrs_adj<80) - } - else if (`ii' == 6) { - gen chk1 = (aidhrs_adj>79) - } - sum chk1 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) - matrix store5[`ii',1] = r(mean) - sum chk2 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8 & chk1==1) - matrix store5[`ii',2] = r(mean) - sum chk3 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8 & chk1==1) - matrix store5[`ii',3] = r(mean) - sum chk4 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8 & chk1==1) - matrix store5[`ii',4] = r(mean) - sum chk5 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8 & chk1==1) - matrix store5[`ii',5] = r(mean) - sum chk6 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8 & chk1==1) - matrix store5[`ii',6] = r(mean) - drop chk1 -} -matrix store5[7,1] = 1 -sum chk2 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) -matrix store5[7,2] = r(mean) -sum chk3 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) -matrix store5[7,3] = r(mean) -sum chk4 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) -matrix store5[7,4] = r(mean) -sum chk5 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) -matrix store5[7,5] = r(mean) -sum chk6 [aweight=indinui_xw] if (provCare>0 & dvage>19 & dvage<60 & jbstat!=4 & jbstat!=8) -matrix store5[7,6] = r(mean) -matlist store5 -*/ - - -/************************************************************************************** -* prepare time-series data for regression analysis -**************************************************************************************/ -clear all -forval ii = 6/12 { - use "ukhls_supply_pooled.dta", clear - keep if (wave == `ii') - save "ukhlst_supply_`ii'.dta", replace -} -forval ii = 6/11 { - use "ukhlst_supply_`ii'.dta", clear - rename * *_l - rename pidp_l pidp - local jj = `ii' + 1 - merge 1:1 pidp using "ukhlst_supply_`jj'.dta" - save "ukhlstml_supply_`jj'.dta", replace -} - -clear all -append using "ukhlstml_supply_7.dta" "ukhlstml_supply_8.dta" "ukhlstml_supply_9.dta" "ukhlstml_supply_10.dta" "ukhlstml_supply_11.dta" "ukhlstml_supply_12.dta" -save "ukhlstml_supply_pooled.dta", replace - - -/************************************************************************************** -* evaluate regressions -**************************************************************************************/ -use "ukhlstml_supply_pooled.dta", clear - -// probit regression for people providing care to partners (3a) -probit care_nonpartner male i.deh_c3 i.scsf1 i.careWho_l ib1.dage1 ib7.drgn [pweight=indinui_xw] if (care_partner==1 & dvage>17), vce(r) -putexcel set "$outdir/probitCareWithPartner", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// probit regression for people not providing care to partners (3b) -probit care_nonpartner male i.deh_c3 i.scsf1 i.careWho_l partner ib1.dage1 ib7.drgn [pweight=indinui_xw] if (care_partner==0 & dvage>17), vce(r) -putexcel set "$outdir/probitCareWithoutPartner", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// probit for single people (cannot provide care to partners) - needed because pooled mlogit doesn't converge (3c) -probit careWho male i.deh_c3 i.scsf1 i.careWho_l ib1.dage1 ib7.drgn [pweight=indinui_xw] if (partner==0 & dvage>17), vce(r) -putexcel set "$outdir/probitCareNoPartner", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// multinomial logit regression for social care provision of people with partners (3d) -gen dage2 = 0 -replace dage2 = 1 if (dvage<35) -replace dage2 = 2 if (dvage>34 & dvage<45) -replace dage2 = 3 if (dvage>44 & dvage<55) -replace dage2 = 4 if (dvage>54 & dvage<65) -replace dage2 = 5 if (dvage>64) -mlogit careWho male i.deh_c3 i.scsf1 i.careWho_l ib1.dage2 ib7.drgn [pweight=indinui_xw] if (dvage>17 & partner==1), vce(r) -putexcel set "$outdir/mlogitCareWho", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -// hours regression (3e) -gen lhourCare = ln(aidhrs_adj) if (aidhrs_adj>0) -regress lhourCare male i.deh_c3 i.scsf1 i.careWho partner ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17 & careWho>0), vce(r) -putexcel set "$outdir/linearHoursCareAnyone", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - - -/***************************************************************** -* working variants -*****************************************************************/ - -// london is drgn=7 -probit care_partner male i.deh_c3 partner care_partner_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (partner==1 & dvage>17), vce(r) -putexcel set "$outdir/probitCarePartner", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -probit care_parent male i.deh_c3 partner care_parent_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17), vce(r) -putexcel set "$outdir/probitCareParent", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -probit care_child male i.deh_c3 partner care_child_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17), vce(r) -putexcel set "$outdir/probitCareChild", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -probit care_others male i.deh_c3 partner care_others_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17), vce(r) -putexcel set "$outdir/probitCareOther", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -probit provCare male i.deh_c3 partner provCare_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17), vce(r) -putexcel set "$outdir/probitCareAny", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - -gen lhourCare = ln(aidhrs_adj) if (aidhrs_adj>0) -regress lhourCare male i.deh_c3 partner provCare_l i.scsf1 ib1.dage1 ib7.drgn [pweight=indinui_xw] if (dvage>17), vce(r) -putexcel set "$outdir/linearHoursCareAnyone", modify -putexcel A1 = matrix(e(b)) -putexcel A2 = matrix(e(V)) - - diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3.do b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3.do index d4229ebc2..c37a3fbb5 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_socialcare3.do @@ -14,7 +14,7 @@ * **************************************************************************************/ clear all -global datadir = "C:\MyFiles\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" +global datadir = "J:\01 DATA\UK\ukhls\wave13\stata\stata13_se\ukhls\" global outdir = "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates\data\" cd "$outdir" global UKHLSWaves "f g h i j k l" @@ -336,6 +336,7 @@ save "ukhlstml_supply_pooled.dta", replace * evaluate regressions **************************************************************************************/ use "ukhlstml_supply_pooled.dta", clear +gen covid = (year>2019) * (year<2023) // probit regression for people providing care to partners (3a) probit care_nonpartner male i.deh_c3 i.scsf1 i.careWho_l ib1.dage1 ib7.drgn [pweight=indinui_xw] if (care_partner==1 & dvage>17), vce(r) diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_wages 2.do b/input/InitialPopulations/compile/RegressionEstimates/reg_wages 2.do deleted file mode 100644 index 64f1787d5..000000000 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_wages 2.do +++ /dev/null @@ -1,512 +0,0 @@ -******************************************************************************** -* PROJECT: ESPON -* SECTION: Wage regression -* OBJECT: Heckman regressions -* AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 21/04/2024 (JV) -******************************************************************************** -clear all -set more off -set mem 200m -set type double -//set maxvar 120000 -set maxvar 30000 - - -/******************************************************************************* -* DEFINE DIRECTORIES -*******************************************************************************/ -* Working directory -global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\regression_estimates" - -* Directory which contains do files -global dir_do "${dir_work}/do" - -* Directory which contains data files -global dir_data "${dir_work}/data" - -* Directory which contains log files -global dir_log "${dir_work}/log" - -* Directory which contains pooled UKHLS dataset -global dir_ukhls_data "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations\data" - - -******************************************************************* -cap log close -log using "${dir_log}/reg_wages.log", replace -******************************************************************* - -global min_age = 17 -global max_age = 64 - - -/**************************************************************/ -* -* Fit (programs) -* -/**************************************************************/ -capture program drop computePredicted -program computePredicted - - local model = "`1'" - local filter = "`2'" - - capture drop hat - capture drop epsilon - capture drop u - - if ("`model'" == "heckman") { - predict hat if `filter' - scalar sigma = e(sigma) - } - else if ("`model'" == "fe") { - predict hat if `filter', xbu - scalar sigma = e(sigma_u) - predict u if `filter', u - hist u, xtitle (estimated individual effect) name(u, replace) - } - else display "model not identified correctly (choose between 'fe' and 'heckman')" - - replace lwage_hour_hat = hat if `filter' - gen epsilon = rnormal()*sigma - sum epsilon - replace wage_hour_hat = exp(lwage_hour_hat + epsilon) if `filter' - -end - -capture program drop analyseFit -program analyseFit - - local filter = "`1'" - - sum lwage_hour lwage_hour_hat wage_hour wage_hour_hat if `filter' - if ("`2'" != "nocorr") { - corr wage_hour L1.wage_hour if `filter' & previouslyWorking - corr wage_hour_hat L1.wage_hour_hat if `filter' & previouslyWorking - } - - twoway (hist lwage_hour if `filter', lcolor(gs12) fcolor(gs12)) /// - (hist lwage_hour_hat if `filter', fcolor(none) lcolor(red)), xtitle (log gross hourly wages (GBP)) legend(lab(1 "observed") lab( 2 "predicted")) name(log, replace) - - twoway (hist wage_hour if `filter' & wage_hour < 150, lcolor(gs12) fcolor(gs12)) /// - (hist wage_hour_hat if `filter' & wage_hour_hat < 150, fcolor(none) lcolor(red)), xtitle (gross hourly wages (GBP)) legend(lab(1 "observed") lab( 2 "predicted")) name(levels, replace) - -end - -capture program drop analyseFit2 -program analyseFit2 - - local filter = "`1'" - - sum lwage_hour lwage_hour_hat wage_hour wage_hour_hat if `filter' - if ("`2'" != "nocorr") { - corr wage_hour L1.wage_hour if `filter' & previouslyWorking - corr wage_hour_hat L1.wage_hour_hat if `filter' & previouslyWorking - } - - twoway (hist lwage_hour if `filter', lcolor(gs12) fcolor(gs12)) /// - (hist lwage_hour_hat if `filter', fcolor(none) lcolor(red)), xtitle (log gross hourly wages (GBP)) legend(lab(1 "observed") lab( 2 "predicted")) name(log, replace) title("`3'") - graph export "${dir_graphs}/log_`4'", replace - - twoway (hist wage_hour if `filter' & wage_hour < 150, lcolor(gs12) fcolor(gs12)) /// - (hist wage_hour_hat if `filter' & wage_hour_hat < 150, fcolor(none) lcolor(red)), xtitle (gross hourly wages (GBP)) legend(lab(1 "observed") lab( 2 "predicted")) name(levels, replace) title("`3'") - graph export "${dir_graphs}/level_`4'", replace - -end - -capture program drop outputResults -program outputResults - - local outputFile = "`1'" - - matrix results = r(table) - matrix results = results[1..6,1...]' //extract the first six rows of results, and then transpose results - putexcel set "$dir_data/`outputFile'.xlsx", sheet("Estimates") replace - - putexcel A3 = matrix(results), names nformat(number_d2) - - matrix results = e(V) - putexcel set "$dir_data/`outputFile'.xlsx", sheet("Varcov") modify - putexcel A3 = matrix(results), names nformat(number_d2) - -end - - -/**************************************************************/ -* -* prepare data on real growth of wages -* based on uprating factors from microsimulation's input folder -* note: values are kept as in scenario_uprating_factor file to be consistent with the simulation which rebases indices to a specified BASE_PRICE_YEAR (2015) -* -/**************************************************************/ -/* -import excel "$microsim_input_dir/scenario_uprating_factor.xlsx", sheet("UK_wage_growth") firstrow clear // Import nominal wage growth rates -rename Year stm -rename Value wage_growth -replace stm = stm - 2000 -save "$work_dir/growth_rates", replace - -import excel "$microsim_input_dir/scenario_uprating_factor.xlsx", sheet("UK_inflation") firstrow clear // Import inflation rates -rename Year stm -rename Value inflation -replace stm = stm - 2000 -save "$work_dir/inflation", replace - -use "$work_dir/growth_rates", clear -merge 1:1 stm using "$work_dir/inflation", keep(3) nogen - -// Step 1: rebase wage growth index to 2015 -sum wage_growth if stm == 15 -gen base = r(mean) -replace wage_growth = wage_growth / base // Note: switching from 100 base to 1 base as that's what happens in the simulation when rebasing indices -drop base - -// Step 2: generate real wage growth index, rebased to 2015 and adjusted to 2015 price level -replace inflation = inflation/100 -gen real_wage_growth = wage_growth/inflation - -save "$work_dir/growth_rates", replace -*/ - -// Note: use code above if calculating real wage growth inside of the simulation, but if loading from excel use values from excel in Stata too. -//They *should* be the same but it is more consistent to have one source of values. -import excel "$dir_data/time_series_factor.xlsx", sheet("UK_wage_growth") firstrow clear // Import real wage growth rates -rename Year stm -rename Value real_wage_growth -replace stm = stm - 2000 -sum real_wage_growth if stm == 15 -gen base = r(mean) -replace real_wage_growth = real_wage_growth / base // Note: switching from 100 base to 1 base as that's what happens in the simulation when rebasing indices -drop base -save "$dir_data/growth_rates", replace - - -/**************************************************************/ -* -* open and format data for analysis -* -/**************************************************************/ -use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear - -drop if dag < $min_age -* screen data to ensure that idperson and swv uniquely identify observations -sort idperson swv -gen chk = 0 -replace chk = 1 if (idperson == idperson[_n-1] & swv == swv[_n-1]) -drop if chk == 1 - -* Fill in missing information on year (stm) based on wave (swv) -/* -replace stm = 2009 if swv == 1 & missing(stm) -replace stm = 2010 if swv == 2 & missing(stm) -replace stm = 2011 if swv == 3 & missing(stm) -replace stm = 2012 if swv == 4 & missing(stm) -replace stm = 2013 if swv == 5 & missing(stm) -replace stm = 2014 if swv == 6 & missing(stm) -replace stm = 2015 if swv == 7 & missing(stm) -replace stm = 2016 if swv == 8 & missing(stm) -replace stm = 2017 if swv == 9 & missing(stm) -replace stm = 2018 if swv == 10 & missing(stm) -replace stm = 2019 if swv == 11 & missing(stm) -replace stm = 2020 if swv == 12 & missing(stm) -replace stm = 2021 if swv == 13 & missing(stm) -*/ - -replace stm = stm - 2000 - - -/**************************************************************/ -* -* merge in real growth index from microsimulation's input folder -* -/**************************************************************/ -merge m:1 stm using "$dir_data/growth_rates", keep(3) nogen keepusing(real_wage_growth) - -//rename drgnl drgn1 // Rename region variable to drgn1 (one, not "l") - -*Variable stm identifies time periods. Need to ensure that combining idperson and stm ensures uniqueness. -duplicates tag idperson stm, gen(dup) -sort idperson stm -//DP: no such cases // - -*However, this affects many variables: idhh, dag, ddt, dpd, ddt01, potentially idpartner. Might be best to move entire household. -*Furthermore, the duplicated observation can occur in a year for which y-1 and y+1 have been observed. -*This might require moving the y-1 or y+1 observation to y-2 or y+2. Alternatively, in such cases the duplicated observation for y can be dropped. - -*However, moving observations can be problematic because idhh can change. -*Moving just the observation will result in mismatch between variables and idhh, -*moving whole household will introduce longitudinal inconsistency for other household members. -*=> Only move those observations for which the whole household can be moved - -*Generate a variable indicating which year the observation should belong to to maintain longitudinal consistency: - -*Can only move if: 1) there is a gap on either side of the duplicate, 2) the whole household is duplicated -*Note: idhh is not longitudinal identifier - -*Check if there is a gap: -by idperson: egen min_observed_year = min(stm) -gen count_year = stm - min_observed_year -sort idperson stm swv // Sort interview date in ascending order - earliest interview will be the one with the gap_prev set to 1 -by idperson: gen gap_prev = (((count_year - count_year[_n-1]) > 1) & count_year>0) // There is a gap in year -1 -by idperson: replace gap_prev = 1 if _n == 1 & dup == 1 & stm > 2009 -//DP: 0 cases - -gsort +idperson -stm -swv // Sort years in reverse order. Sort int date in descending order - later interview will be the one with gap_next set to 1 -by idperson: gen gap_next = (((count_year - count_year[_n-1]) < -1) & stm != 2018) // There is a gap in year +1 -sort idperson stm swv -by idperson: replace gap_next = 1 if _n == _N & dup == 1 -//DP: 1,547 real changes made -by idperson: replace gap_prev = 0 if gap_next[_n-1] == 1 & dup[_n-1] == 1 // If previous observation already has flag set to move to next period, can't move another one to the same period -//DP: 3,193 real changes made - -*Check if whole household is duplicated -bys idhh swv: egen min_dup = min(dup) // If == 1, then every observation for that household is duplicated -// 18480 cases - -*Check if whole household can be moved either back or forward: -bys idhh stm: egen hh_gap_prev = min(gap_prev) -bys idhh stm: egen hh_gap_next = min(gap_next) - -*Generate identifier for the whole household which should be moved: move the observation from the wave which is closer to the gap -gen move = 1 if dup == 1 & (hh_gap_prev == 1 | hh_gap_next == 1) & min_dup == 1 -//DP: 6548 cases - -*Move observations: -replace stm = stm-1 if move == 1 & hh_gap_prev == 1 /*3,425 real changes made*/ -replace stm = stm+1 if move == 1 & hh_gap_next == 1 /*3,123 real changes made*/ - -*Drop households with duplicated observations, keeping observations from more recent waves if duplicated years: -sort stm idperson swv -drop dup -duplicates tag idperson stm, gen(dup) -by stm idperson: egen max_wave = max(swv) // Keep more recent obs -gen drop_idhh = idhh if max_wave == swv & dup == 1 // This identifies idhh which should be dropped -bys idhh stm: egen drop_idhh_max = max(drop_idhh) -drop if !missing(drop_idhh_max) -//DP: 8,119 observations deleted -duplicates drop idperson stm, force // Few duplicates left, drop - - -**************************************** -* Setting STATA to recognize Panel Data -xtset idperson stm -* total hours work per week (average) -gen hours = 0 -replace hours = jbhrs if ((jbhrs > 0) & (jbhrs < .)) -replace hours = hours + jshrs if ((jshrs > 0) & (jshrs < .)) -replace hours = hours + j2hrs / 4.333 if ((j2hrs > 0) & (j2hrs < .)) - -* hour groups -gen hrs1 = (hours > 0) * (hours < 10) -gen hrs2 = (hours >= 10) * (hours < 15) -gen hrs3 = (hours >= 15) * (hours < 20) -gen hrs4 = (hours >= 20) * (hours < 25) -gen hrs5 = (hours >= 25) * (hours < 30) -gen hrs6 = (hours >= 30) * (hours < 35) -gen hrs7 = (hours >= 35) * (hours < 40) - -gen hrs0_m1 = hours[_n-1] == 0 -gen hrs1_m1 = (hours[_n-1] > 0) * (hours[_n-1] <= 29) - -/** -gen hrs1_m1 = (hours[_n-1] > 0) * (hours[_n-1] < 10) -gen hrs2_m1 = (hours[_n-1] >= 10) * (hours[_n-1] < 15) -gen hrs3_m1 = (hours[_n-1] >= 15) * (hours[_n-1] < 20) -gen hrs4_m1 = (hours[_n-1] >= 20) * (hours[_n-1] < 25) -gen hrs5_m1 = (hours[_n-1] >= 25) * (hours[_n-1] < 30) -gen hrs6_m1 = (hours[_n-1] >= 30) * (hours[_n-1] < 35) -gen hrs7_m1 = (hours[_n-1] >= 35) * (hours[_n-1] < 40) -**/ - -* hourly wage -* screens population to individuals working (omits 1.58% of population aged 18+ and working): -* at least 1 hour per week(455 obs between 0 and 1) -* no more than 100 hours per week -* earning at least 50 per month -* earning no more than 83333 per month (1M per year) - -// Based on yplgrs which is derived from fimnlabgrs_dv in UKHLS -// Change to sinh(yplgrs_dv) which provides yplgrs deflated by CPI - -gen yplgrs_dv_level = sinh(yplgrs_dv) - -gen wage_hour = . -replace wage_hour = yplgrs_dv_level / hours / 4.333 if (yplgrs_dv_level >= 50 & yplgrs_dv_level <= 83333 & hours >= 1 & hours <= 100) -sum wage_hour, det -*replace wage_hour = . if wage_hour < 4 | wage_hour > 70 -* relationship status (1=cohabitating) -gen mar = (dcpst==1) -* children -gen any02 = dnc02 > 0 -gen dnc4p = dnc -replace dnc4p = 1 if (dnc>4) -gen dnc2p = dnc -replace dnc2p = 2 if (dnc>2) -cap gen child = (dnc>0) -* individual weights -by idperson: egen wgt = mean(dimlwt) -* - - -/**************************************************************/ -* -* preliminaries -* -/**************************************************************/ -gen lwage_hour = ln(wage_hour) -hist lwage_hour if lwage_hour > 0 & lwage_hour < 4.4 - -gen swage_hour = asinh(wage_hour) -hist swage_hour if (swage_hour > 1 & swage_hour < 5) - -replace lwage_hour = . if (wage_hour<5 | wage_hour>1000) - -replace les_c3 = 3 if lwage_hour == . & les_c3 ! = 2 // PB: employment status is set on the basis of hourly wage not missing, so recode labour market activity status to match this for non-students -replace les_c3 = 1 if lwage_hour != . // PB: as above, if wage present consider as employed - -recode deh_c3 dehm_c3 dehf_c3 drgn1 dhe (-9=.) - - -/**************************************************************/ -* -* pooled cross-sectional regressions -* -/**************************************************************/ -gen pt = (hours > 0) * (hours <= 25) -drop hrs0_m1 hrs1_m1 - -* Strategy: -* 1) Heckman estimated on the sub-sample of individuals who were not observed working in previous period. -* Wage equation does not controls for lagged wage -* 2) Heckman estimated on the sub-sample of individuals who were observed working in previous period. -* Wage equation controls for lagged wage -* Specification of selection equation is the same in the two samples - -* Flag to identify observations to be included in the estimation sample -bys idperson: gen obs_count = _N -gen in_sample = (obs_count > 1 & swv > 1) - -* Flag to distinguish the two samples -capture drop previouslyWorking -gen previouslyWorking = (L1.lwage_hour != .) /* PB 07.02.2023: I think this will set previosuly working to 0 for everyone -who is not observed in the previous period, e.g. all observations at Wave 1. I think the sample should include only individuals -who are observed for at least two periods, and then the first observation should not be used in the estimation. */ - -capture drop lwage_hour_hat wage_hour_hat esample -gen lwage_hour_hat = . -gen wage_hour_hat = . -gen esample = . - -gen L1les_c3 = L1.les_c3 -gen lwage_hour_2 = lwage_hour^2 - -gen pred_hourly_wage = . - -*** 1) Heckman estimated on the sub-sample of individuals who were not observed working in previous period. -**** Wage equation does not control for lagged wage - -* women -global wage_eqn "lwage_hour dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 dlltsd i.dhe ib8.drgn1 pt real_wage_growth" -global seln_eqn "i.L1les_c3 dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 mar child dlltsd i.dhe ib8.drgn1 " -local filter = "dgn==0 & dag>=$min_age & dag<=$max_age & !previouslyWorking" -*heckman $wage_eqn if `filter' [pweight=dimxwt], select($seln_eqn) vce(robust) -heckman $wage_eqn if `filter', select($seln_eqn) twostep -outputResults "Not-working women3" - -outreg2 stats(coef se pval) using "$dir_data/Output_NWW.doc", replace /// -title("Heckman-corrected wage equation estimated on the sample of women who were not in employment last year") /// - ctitle(In education) label side dec(2) noparen - -*xtheckmanfe $wage_eqn if `filter', select($seln_eqn) reps(2) -computePredicted "heckman" `filter' -analyseFit "e(sample)" "nocorr" -replace esample = 1 if e(sample) -replace pred_hourly_wage = wage_hour_hat if e(sample) - - - -* men -global wage_eqn "lwage_hour dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 dlltsd i.dhe ib8.drgn1 pt real_wage_growth" -global seln_eqn "i.L1les_c3 dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 mar child dlltsd i.dhe ib8.drgn1 " -local filter = "dgn==1 & dag>=$min_age & dag<=$max_age & !previouslyWorking" -*heckman $wage_eqn if `filter' [pweight=dimxwt], select($seln_eqn) vce(robust) -heckman $wage_eqn if `filter', select($seln_eqn) twostep -outputResults "Not-working men3" - -outreg2 stats(coef se pval) using "$dir_data/Output_NWM.doc", replace /// -title("Heckman-corrected wage equation estimated on the sample of men who were not in employment in the previous year") /// -ctitle(Wage equation coef.) label side dec(2) noparen - -computePredicted "heckman" `filter' -analyseFit "e(sample)" "nocorr" -replace esample = 1 if e(sample) -replace pred_hourly_wage = wage_hour_hat if e(sample) - -*** 2) Heckman estimated on the sub-sample of individuals who were observed working in previous period. -*** Wage equation controls for lagged wage - -* women -global wage_eqn "lwage_hour L1.lwage_hour dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 dlltsd i.dhe ib8.drgn1 pt real_wage_growth" -global seln_eqn "dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 mar child dlltsd i.dhe ib8.drgn1 " -local filter = "dgn==0 & dag>=$min_age & dag<=$max_age & swv > 1 & previouslyWorking" -*heckman $wage_eqn if `filter' [pweight=dimxwt], select($seln_eqn) vce(robust) -heckman $wage_eqn if `filter', select($seln_eqn) twostep -outputResults "Working women3" - -outreg2 stats(coef se pval) using "$dir_data/Output_WW.doc", replace /// -title("Heckman-corrected wage equation estimated on the sample of women who were in employment in the previous year") /// - ctitle(Wage equation coef.) label side dec(2) noparen - -computePredicted "heckman" `filter' -analyseFit "e(sample)" -replace esample = 1 if e(sample) -replace pred_hourly_wage = wage_hour_hat if e(sample) - -* men -global wage_eqn "lwage_hour L1.lwage_hour dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 dlltsd i.dhe ib8.drgn1 pt real_wage_growth" -global seln_eqn "dag dagsq i.deh_c3 i.deh_c3#c.dag ded i.dehmf_c3 mar child dlltsd i.dhe ib8.drgn1" -local filter = "dgn==1 & dag>=$min_age & dag<=$max_age & swv > 1 & previouslyWorking" -*heckman $wage_eqn if `filter' [pweight=dimxwt], select($seln_eqn) vce(robust) -heckman $wage_eqn if `filter', select($seln_eqn) twostep -outputResults "Working men3" - -outreg2 stats(coef se pval) using "$dir_data/Output_WM.doc", replace /// -title("Heckman-corrected wage equation estimated on the sample of men who were in employment in the previous year") /// - ctitle(Wage equation coef.) label side dec(2) noparen - - -computePredicted "heckman" `filter' -analyseFit "e(sample)" -replace esample = 1 if e(sample) -replace pred_hourly_wage = wage_hour_hat if e(sample) - -* all -analyseFit "esample == 1" -analyseFit "esample == 1 & dgn == 0" // women -analyseFit "esample == 1 & dgn == 1" // men - - -* Analyse fit per year: -forvalues year = 11/23 { - di "Current year: `year'" - analyseFit2 "esample == 1 & stm == `year'" "nocorr" "Year 20`year' all obs prv emp" "all_`year'_graph.png" - analyseFit2 "esample == 1 & dgn == 0 & stm == `year'" "nocorr" "Year 20`year' women prv emp" "women_`year'_graph.png" // women - analyseFit2 "esample == 1 & dgn == 1 & stm == `year'" "nocorr" "Year 20`year' men prv emp" "men_`year'_graph.png" // men - analyseFit2 "esample == 1 & dgn == 1 & deh_c3 == 1 & stm == `year'" "nocorr" "Year 20`year' men prv emp high ed" "men_highed_`year'_graph.png" // men -} - - - -// Note: sigma reported in the estimated regressions is the standard deviation of the residuals (=RMSE, assuming residuals are normally distributed) - -*** Save for use in the do file estimating non-employment income -replace pred_hourly_wage = exp(lwage_hour) if missing(pred_hourly_wage) - -save "$dir_ukhls_data/ukhls_pooled_all_obs.dta", replace - - -*** Calculate the proportion of "true zero" hours of work among those in the "ZERO" weekly hours of labour supply bracket. -*I.e. the share of zero hours among 0-5 hours for those at risk of work. - -capture log close diff --git a/input/InitialPopulations/training/population_initial_UK_2019.csv b/input/InitialPopulations/training/population_initial_UK_2019.csv index ecb472446..9927a375a 100644 --- a/input/InitialPopulations/training/population_initial_UK_2019.csv +++ b/input/InitialPopulations/training/population_initial_UK_2019.csv @@ -1,37083 +1,37705 @@ -idhh,idbenefitunit,idperson,idpartner,idmother,idfather,pno,swv,dgn,dag,dcpst,dnc02,dnc,ded,deh_c3,sedex,jbstat,les_c3,dlltsd,dlltsd01,dhe,yplgrs_dv,ypnbihs_dv,yptciihs_dv,dhhtp_c4,ssscp,dcpen,dcpyy,dcpex,dcpagdf,ynbcpdf_dv,der,sedag,sprfm,dchpd,dagsp,dehsp_c3,dhesp,lessp_c3,dehm_c3,dehf_c3,stm,lesdf_c4,ppno,dhm,scghq2_dv,lhw,l1_lhw,dct,les_c4,dhm_ghq,lessp_c4,adultchildflag,potential_earnings_hourly,l1_potential_earnings_hourly,need_socare,formal_socare_hrs,partner_socare_hrs,daughter_socare_hrs,son_socare_hrs,other_socare_hrs,formal_socare_cost,carehoursprovidedweekly,econ_benefits,econ_benefits_nonuc,econ_benefits_uc,ypncp,ypnoab,aidhrs,carewho,dhe_mcs,dhe_pcs,dhe_mcssp,dhe_pcssp,dls,dot,dot01,unemp,financial_distress,liwwh,drgn1,ydses_c5,dhh_owned,dwt,liquid_wealth,tot_pen,nvmhome,disp_inc 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-911,1069,1980,-9,1981,1979,3,1,1,2,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-897.1190873234682,-9,0,0,0,-9,-9,-9,-9,1,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,4,4,1,1406.333333333333,57246.7279026375,0,0,1851.00073896124 -911,1069,1981,1979,-9,-9,2,1,0,43,1,1,1,0,1,-9,2,1,0,0,4,8.302233315932176,8.426342544852982,0,2,0,-9,7,0,-6,-25.32649819657001,-9,0,1,0,49,3,2,1,-9,-9,2019,1,1,10,1,40,0,15,1,0,1,0,12.27071643300371,12.27071643300371,0,0,0,0,0,0,0,0,0,0,0,.0213284613772113,0,0,0,50,55,50.54,33.6,6,1,1,0,0,1,4,4,1,1406.333333333333,57246.7279026375,0,0,1851.00073896124 -912,1070,1982,1983,-9,-9,1,1,1,70,1,0,0,0,2,-9,4,3,0,0,3,0,7.303924662234448,7.103213183187515,1,0,-9,9,0,2,147.4267201934066,0,0,0,0,68,2,4,3,-9,-9,2019,4,2,10,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.331641236368554,7.43359847359343,0,0,40.59,58.72,57.16,56.15,5,1,1,0,0,2,9,2,1,1055.5,1013889.619298877,0,0,1543.849448623865 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-914,1072,1986,1987,-9,-9,1,1,0,64,1,0,0,0,3,-9,6,3,0,1,2,0,0,0,1,0,-9,33,0,-7,0,0,0,0,0,71,3,1,3,3,3,2019,4,2,15,4,0,0,15,3,1,4,0,0,0,1,0,9.674408417541013,0,0,0,0,42,1,1,0,0,0,36.7990059510782,1,37.02,37.37,30.62,22.93,4,1,1,0,0,0,2,1,0,732,233273.3963133908,0,0,1695.705285374649 -914,1072,1987,1986,-9,-9,2,1,1,71,1,0,0,0,3,-9,4,3,0,1,1,0,0,0,1,0,-9,33,0,7,0,0,0,0,0,64,3,2,3,-9,-9,2019,4,1,17,5,0,0,15,4,1,3,0,0,0,1,0,20.78324852487465,0,0,0,0,0,1,1,0,0,0,0,0,30.62,22.93,37.02,37.37,2,1,1,0,0,0,2,1,0,732,233273.3963133908,0,0,1695.705285374649 -915,1073,1988,1989,-9,-9,1,1,0,82,1,0,0,0,2,-9,4,3,0,0,4,0,0,0,1,0,-9,52,0,-2,147.8852459995892,0,0,0,0,84,3,4,3,2,1,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1.290512257066518,0,0,0,54.2,57.49,57.16,56.15,6,1,1,0,0,0,11,3,1,709.5,465413.7199815816,0,0,2823.464515997958 -915,1073,1989,1988,-9,-9,2,1,1,84,1,0,0,0,3,-9,4,3,0,0,4,0,7.747175994421229,7.902473761077532,1,0,-9,52,0,2,48.58627557912128,0,0,0,0,82,2,4,3,2,2,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,7.84923876230469,7.66816521806568,0,0,57.16,56.15,54.2,57.49,6,1,1,0,0,0,11,3,1,709.5,465413.7199815816,0,0,2823.464515997958 -916,1074,1990,1991,-9,-9,2,1,1,91,1,0,0,0,1,-9,4,3,0,1,3,0,8.516945209190554,8.602904798663031,1,0,-9,18,0,22,79.0090569301987,0,0,0,0,69,1,4,3,2,2,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,1,0,125.3646856426531,0,0,0,0,0,1,1,0,6.791792152714979,8.569417722191687,0,0,62.57,19.44,57.16,56.15,6,1,1,0,0,0,10,4,1,1332.5,1919014.285280907,0,0,5136.906904697517 -916,1074,1991,1990,-9,-9,1,1,0,69,1,0,0,0,1,-9,4,3,0,0,4,0,8.031282889625247,7.333186147889165,1,0,-9,18,0,-22,111.6186449047408,0,0,0,0,91,1,3,3,3,2,2019,4,2,10,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,74.5,1,1,0,5.403057447835064,7.533402879032809,65.71677307474079,1,57.16,56.15,62.57,19.44,6,1,1,0,0,0,10,4,1,1332.5,1919014.285280907,0,0,5136.906904697517 -917,1075,1992,-9,-9,-9,1,1,1,76,2,0,0,0,2,-9,1,1,0,0,3,6.424718683791934,6.353302638037676,0,3,0,0,0,-9,0,-881.1970591357227,0,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,6,0,0,14,15,1,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.5755730280281498,0,0,0,59.32,46.98,-9,-9,7,1,1,0,0,5.916666666666667,4,2,1,392,249769.462414772,0,0,1694.354127744565 -918,1076,1993,-9,-9,-9,1,1,0,49,2,0,0,0,2,-9,8,3,1,1,2,0,0,0,3,0,0,0,-9,0,-945.4715420739257,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,16,4,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,36.31,41.6,-9,-9,3,1,1,0,0,8.25,12,1,0,173,26477.11315872113,0,0,2217.477055600647 -919,1077,1994,1995,-9,-9,2,1,0,59,1,0,0,0,2,-9,2,1,0,0,4,8.043988742247269,7.982637230114931,7.100662319311493,1,0,-9,37,0,0,105.9452274231069,0,0,0,0,59,2,4,1,2,2,2019,1,1,9,0,28,30,15,1,0,1,0,12.45504502787893,12.45504502787893,0,0,0,0,0,0,0,0,0,0,0,7.629522826207912,7.633923000879054,0,0,54.2,57.49,57.16,56.15,6,1,1,0,0,12.83333333333333,4,4,1,417.5,611979.976622522,0,0,3248.495356552945 -919,1077,1995,1994,-9,-9,1,1,1,59,1,0,0,0,2,-9,2,1,0,0,4,6.631365222865199,6.85151139572361,0,1,0,-9,37,0,0,-96.29919692984885,0,0,0,0,59,2,4,1,3,2,2019,1,2,6,0,25,24,15,1,0,1,0,3.24148900235334,3.24148900235334,0,0,0,0,0,0,0,0,0,0,0,7.070080530060701,0,0,0,57.16,56.15,54.2,57.49,6,1,1,0,0,9.166666666666666,4,4,1,417.5,611979.976622522,0,0,3248.495356552945 -920,1078,1996,1997,-9,-9,1,1,1,72,1,0,0,0,2,-9,4,3,0,0,4,0,0,0,1,0,-9,9,0,3,36.06120020263187,0,0,0,0,69,2,4,3,3,2,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.808425550543013,0,0,0,60.12,54.8,63.46,23.18,7,1,1,0,0,5.25,6,2,1,136,271763.2611769686,0,0,1664.862599970824 -920,1078,1997,1996,-9,-9,2,1,0,69,1,0,0,0,2,-9,4,3,0,0,4,0,5.703119629213765,5.590884830113219,1,0,-9,9,0,-3,-146.8715062151366,0,0,0,0,72,2,4,3,2,-9,2019,4,1,12,2,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.091884683519346,0,0,63.46,23.18,60.12,54.8,7,1,1,0,0,1,6,2,1,136,271763.2611769686,0,0,1664.862599970824 -921,1079,1998,1999,-9,-9,1,1,0,62,1,0,0,0,3,-9,6,3,0,0,3,0,0,0,1,0,-9,16,0,-11,-81.43512737575969,0,0,0,0,73,3,2,1,3,3,2019,3,2,15,3,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,7,1,1,0,0,0,2.17748208232834,3,39.9,49.39,53.18,38.14,5,1,1,0,0,2.333333333333333,6,3,1,547.5,1010557.687368008,0,0,2295.938992701461 -921,1079,1999,1998,-9,-9,2,1,1,73,1,0,0,0,3,-9,2,1,0,0,2,8.020815417780277,8.015416930161896,0,1,0,-9,8,0,11,-17.95388675292307,-9,0,0,0,62,3,3,3,-9,-9,2019,2,1,10,0,36,0,15,1,0,3,0,9.532917462202573,9.532917462202573,1,0,1.214618676793539,0,0,0,0,2,1,1,0,0,0,6.461321973308967,3,53.18,38.14,39.9,49.39,6,1,1,0,0,3.916666666666667,6,3,1,547.5,1010557.687368008,0,0,2295.938992701461 -922,1080,2000,-9,-9,-9,1,1,0,80,2,0,0,0,2,-9,4,3,0,0,5,0,6.793270305051422,7.150935269945029,3,0,0,0,-9,0,-1014.959534442493,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,2.528329172632698,7.078215108585008,0,0,44.41,58,-9,-9,7,1,1,0,0,0,5,2,1,245,240065.27684234,0,0,1899.542329265081 -923,1081,2001,-9,-9,-9,1,1,1,45,2,0,0,0,1,-9,2,1,0,0,4,9.196393855608434,9.143423006145822,0,3,0,0,0,-9,0,-1096.88001452354,0,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,10,1,40,50,15,1,0,-9,0,33.85910302798746,33.85910302798746,0,0,0,0,0,0,0,0,1,1,0,4.410948141986179,0,0,0,49.35,59.64,-9,-9,6,1,1,0,0,10.33333333333333,8,5,1,395,1503070.478117473,0,0,2666.652523290245 -924,1082,2002,-9,-9,-9,1,1,0,57,2,0,0,0,3,-9,8,3,1,1,2,0,0,0,3,0,0,0,-9,0,-1022.255372239181,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.92,34.09,-9,-9,5,1,1,0,0,0,11,1,0,379,110304.5351880883,0,0,1496.846462874461 -924,1083,2003,-9,2002,-9,2,1,1,28,2,0,0,0,3,-9,3,3,0,0,4,0,0,0,3,0,0,0,-9,0,-1172.997062619076,0,1,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,10,1,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49,58,-9,-9,5,1,1,1,0,0,11,1,0,422,-137669.372353304,0,0,-190.6066366109182 -924,1084,2004,-9,2002,-9,3,1,1,27,2,0,0,0,2,-9,3,3,0,0,4,0,0,0,3,0,0,0,-9,0,-938.4632721621155,0,1,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,10,1,0,40,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49,58,-9,-9,5,1,1,1,0,0,11,1,0,628,0,0,0,594.5412151445444 -925,1085,2005,2006,-9,-9,1,1,0,49,1,0,2,0,2,-9,8,3,1,1,1,0,0,0,2,0,-9,6,0,1,100.7831926508161,0,0,0,0,48,1,4,1,2,2,2019,3,2,10,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,58.66,7.17,49.86,55.31,6,1,1,0,0,0,5,4,1,1232,251427.802008123,0,0,4747.19117407299 -925,1085,2006,2005,-9,-9,2,1,1,48,1,0,2,0,1,-9,2,1,0,0,4,8.882034415568762,9.1083763982304,0,2,0,-9,6,0,-1,83.54121722480548,0,0,0,0,49,2,1,3,-9,-9,2019,2,1,11,0,50,45,15,1,0,3,0,17.96701214720473,17.96701214720473,0,0,0,0,0,0,0,0,1,1,0,1.281120117847073,0,0,0,49.86,55.31,58.66,7.17,5,1,1,0,0,8.833333333333334,5,4,1,1232,251427.802008123,0,0,4747.19117407299 -926,1086,2007,2008,-9,-9,1,1,0,49,1,0,0,0,3,-9,2,1,0,0,3,8.227515961857952,7.992505585456686,0,1,0,-9,25,0,0,35.45392404478591,0,0,0,0,49,2,3,1,2,2,2019,1,2,9,0,40,38,15,1,0,1,0,9.45353302451355,9.45353302451355,0,0,0,0,0,0,0,0,0,0,0,6.548199765186648,0,0,0,52.99,36.14,54.96,53.17,6,1,1,0,0,11.08333333333333,10,3,1,327.5,85909.9246775739,0,0,1635.275131314698 -926,1086,2008,2007,-9,-9,2,1,1,49,1,0,0,0,2,-9,1,1,0,0,3,0,0,0,1,0,-9,2,0,0,72.76476706609634,0,0,0,0,49,3,3,1,-9,-9,2019,1,1,6,0,60,60,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.96,53.17,52.99,36.14,6,1,1,0,0,11.91666666666667,10,3,1,327.5,85909.9246775739,0,0,1635.275131314698 -926,1087,2009,-9,2007,2008,3,1,1,25,2,0,0,0,2,-9,2,1,0,0,5,7.863719242218896,7.959646534974318,0,3,0,0,0,-9,0,-1029.341448119169,0,1,0,0,-9,-9,-9,-9,3,2,2019,-9,0,6,0,40,45,15,1,0,-9,1,8.333192552269885,8.333192552269885,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.39,56.71,-9,-9,6,1,1,0,0,5.833333333333333,10,4,1,401,76297.26219649687,0,0,1031.887115497304 -926,1088,2010,-9,2007,2008,4,1,1,24,2,0,0,0,2,-9,2,1,0,0,5,8.2042440300545,8.157042706150211,0,3,0,0,0,-9,0,-1014.229204406142,0,1,0,0,-9,-9,-9,-9,3,2,2019,-9,0,6,0,45,45,15,1,0,-9,1,12.34257133891002,12.34257133891002,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.39,56.71,-9,-9,7,1,1,0,0,4.5,10,4,1,1852,176433.339902197,0,0,2169.014415366372 -927,1089,2011,-9,-9,-9,1,1,0,64,2,0,0,0,1,-9,2,1,0,0,3,7.227932621781247,8.144340681272865,7.027784904604731,3,0,0,0,-9,0,-970.0445015815252,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,8,0,20,0,15,1,0,-9,0,11.81638900209941,11.81638900209941,0,0,0,0,0,0,0,0,1,1,0,1.933260047005912,7.233290189714772,0,0,59.31,49.81,-9,-9,5,1,1,0,0,6.416666666666667,12,4,1,2399,253882.5378307401,0,0,988.282113947673 -928,1090,2012,2013,-9,-9,1,1,0,64,1,0,0,0,2,-9,6,3,0,1,2,0,0,0,1,0,-9,17,0,1,54.1071166270719,0,0,0,0,63,3,1,3,3,3,2019,4,2,7,0,0,0,15,3,0,3,0,0,0,0,0,0,0,0,0,0,42,1,1,0,0,0,44.74288083510822,1,61.52,42.41,42.81,15.98,6,1,1,0,0,5.916666666666667,10,2,1,385.5,391803.9836060486,0,0,824.0732742830166 -928,1090,2013,2012,-9,-9,2,1,1,63,1,0,0,0,3,-9,8,3,1,1,1,0,6.544042293676942,6.407395859408467,1,0,-9,10,0,-1,-61.9317069653677,0,0,0,0,64,2,2,3,-9,-9,2019,4,1,10,0,0,0,15,3,0,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.328274751063092,0,0,42.81,15.98,61.52,42.41,4,1,1,0,0,3.166666666666667,10,2,1,385.5,391803.9836060486,0,0,824.0732742830166 -929,1091,2014,-9,-9,-9,1,1,0,35,2,0,0,0,2,-9,5,1,0,0,4,7.545185624157075,7.574433663162779,0,3,0,0,0,-9,0,-976.7870180021088,0,0,1,0,-9,-9,-9,-9,2,2,2019,-9,0,8,0,22,30,15,1,0,-9,0,13.0189846399467,13.0189846399467,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.33,43.06,-9,-9,6,1,1,0,0,7.416666666666667,9,3,1,182,59341.70390812129,0,0,911.3061410442045 -929,1092,2015,-9,2014,-9,2,1,0,20,2,0,0,0,2,-9,2,1,0,0,3,7.577096977703462,7.269317097588978,0,3,0,0,0,-9,0,-987.1444643860306,0,1,1,0,-9,-9,-9,-9,3,3,2019,-9,0,12,2,30,0,15,1,0,-9,1,6.227465205179432,6.227465205179432,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41.01,41.97,-9,-9,3,1,1,0,0,2.166666666666667,9,3,1,263,93572.61526604016,0,0,565.0391631589448 -930,1093,2016,-9,-9,-9,1,1,0,77,2,0,0,0,3,-9,4,3,0,0,3,0,0,0,3,0,0,0,-9,0,-1044.71717230596,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,55.53,51.55,-9,-9,6,1,1,0,0,0,4,1,1,459,-6167.687603603247,0,0,994.9671059458575 -931,1094,2017,2018,-9,-9,1,1,0,73,1,0,0,0,2,-9,4,3,0,0,3,0,8.040812492600109,8.572873123126598,1,0,-9,47,0,-6,-75.01572454446827,0,0,0,0,79,3,4,3,2,2,2019,4,2,15,4,0,0,15,4,1,4,0,0,0,0,0,0,0,0,0,0,27.5,1,1,0,4.303739574898846,7.973535913731873,31.04412460014466,3,47.37,46.26,48.65,37.21,6,1,1,0,0,0,8,4,1,488,1344104.906397176,0,0,3959.558801008805 -931,1094,2018,2017,-9,-9,2,1,1,79,1,0,0,0,3,-9,4,3,0,0,4,0,7.676085644265224,7.404412898738394,1,0,-9,50,0,6,-88.09568346022608,0,0,0,0,73,2,3,3,3,2,2019,4,1,14,3,0,0,15,4,0,4,0,0,0,1,0,22.22330780463932,0,0,0,0,0,1,1,0,2.213949515215398,7.994967038333959,0,0,48.65,37.21,47.37,46.26,5,1,1,0,0,0,8,4,1,488,1344104.906397176,0,0,3959.558801008805 -932,1095,2019,2020,-9,-9,1,1,0,76,1,0,0,0,2,-9,4,3,0,0,2,0,0,0,1,0,-9,8,0,0,18.79962756985858,0,0,0,0,76,2,3,3,2,2,2019,4,2,19,6,0,0,15,4,1,4,0,0,0,1,0,9.004665814622493,0,1.107853479265209,0,0,0,1,1,0,1.779276861162272,0,0,0,29.82,32.56,42.7,46.47,5,1,1,0,0,0,6,3,1,577.5,1024019.155009255,0,0,2788.061605922388 -932,1095,2020,2019,-9,-9,2,1,1,76,1,0,0,0,2,-9,4,3,0,0,3,0,8.113031742319285,8.353203576974561,1,0,-9,8,0,0,68.22921846362527,0,0,0,0,76,2,2,3,2,2,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,1,0,0,0,3.128942617541272,0,0,0,1,1,0,4.987581088929273,8.185995904812682,0,0,42.7,46.47,29.82,32.56,4,1,1,0,0,0,6,3,1,577.5,1024019.155009255,0,0,2788.061605922388 -932,1096,2021,-9,2019,2020,3,1,1,45,2,0,0,0,2,-9,2,1,0,0,2,8.432462006223284,8.338773093890165,0,3,0,0,0,-9,0,-986.4748870160163,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,6,0,42,44,15,1,0,-9,0,12.5551398621406,12.5551398621406,0,0,0,0,0,0,0,2,1,1,0,2.655377326573717,0,0,3,52.24,50.75,-9,-9,6,1,1,0,0,9.333333333333334,6,4,1,1057,248069.2433902489,0,0,1706.056150414859 -933,1097,2022,2023,-9,-9,1,1,0,53,1,0,2,0,2,-9,2,1,0,0,2,8.071832422733554,7.600943011457691,0,2,0,1,10,-9,-1,-60.34298948163543,0,0,0,0,54,2,3,1,-9,-9,2019,1,4,11,2,40,38,15,1,0,1,0,8.583425352044806,8.583425352044806,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.77,50.89,22.12,42.4,5,3,4,0,0,9.75,4,4,0,2866.333333333333,605153.2762276164,0,0,2776.933892401069 -933,1097,2023,2022,-9,-9,4,1,1,54,1,0,2,0,2,-9,2,1,0,0,3,8.401578866174459,8.356127028024355,0,2,0,-9,10,-9,1,-90.80001187872065,-9,0,0,0,53,2,2,1,2,2,2019,1,1,21,9,49,0,15,1,1,1,0,8.232745321429949,8.232745321429949,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,22.12,42.4,48.77,50.89,6,3,4,0,0,7.583333333333333,4,4,0,2866.333333333333,605153.2762276164,0,0,2776.933892401069 -933,1097,2024,-9,2022,2023,3,1,0,11,2,0,2,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1044.884050625334,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,62,-9,-9,5,1,1,0,0,0,4,4,0,2866.333333333333,605153.2762276164,0,0,2776.933892401069 -933,1098,2025,-9,2022,2023,2,1,1,18,2,0,2,1,2,0,7,2,0,0,3,6.654358355090753,6.459942978459802,0,3,0,0,0,-9,0,-1036.987361702698,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,5,0,10,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.98,50.59,-9,-9,5,3,4,0,0,1.083333333333333,4,4,0,243,-105864.6891507149,0,0,561.8394250802912 -934,1099,2026,-9,-9,-9,1,1,0,68,2,0,0,0,2,-9,2,1,0,0,3,6.328688752276417,7.443599586361765,7.008428188777144,3,0,0,0,-9,0,-1111.088441827636,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,13,2,12,0,15,1,0,-9,0,7.690829426660762,7.690829426660762,0,0,0,0,0,0,0,2,1,1,0,0,6.69493861270155,0,3,39.25,52.26,-9,-9,6,1,1,0,0,9.333333333333334,10,3,1,871,319496.5289691215,0,0,1209.387660108519 -935,1100,2027,-9,-9,-9,1,1,0,70,2,0,0,0,3,-9,2,1,0,0,4,7.156938495725516,7.219736960977073,0,3,0,0,0,-9,0,-1155.92936612284,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,5,0,15,32,15,1,0,-9,0,8.428444091406362,8.428444091406362,0,0,0,0,0,0,0,71.5,1,1,0,0,0,69.47204287436601,3,57.16,56.15,-9,-9,7,1,1,0,0,10.75,9,2,1,793,466659.5594191969,0,0,1078.788906818482 -936,1101,2028,-9,-9,-9,1,1,0,47,2,0,0,0,3,-9,3,3,0,1,1,0,0,0,3,0,0,0,-9,0,-1043.707827316636,0,0,0,0,-9,-9,-9,-9,-9,3,2019,-9,0,27,10,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,24.68,21.22,-9,-9,1,1,1,1,1,0,8,1,0,291,-102507.4217259353,0,0,958.0132634546911 -936,1102,2029,-9,2028,-9,2,1,0,19,2,0,0,0,2,-9,2,1,0,0,5,7.382340172029645,7.481223622386356,0,3,0,0,0,-9,0,-910.252492596292,0,1,1,0,-9,-9,-9,-9,3,-9,2019,-9,0,6,0,40,40,15,1,0,-9,1,4.201924493090928,4.201924493090928,0,0,0,0,0,0,0,7,1,1,0,0,0,2.968634297723331,3,59.43,58.05,-9,-9,6,1,1,0,0,9.333333333333334,8,3,0,526,9734.963686830552,0,0,643.6586402937248 -937,1103,2030,-9,-9,-9,1,1,0,96,2,0,0,0,2,-9,4,3,0,0,4,0,7.624475364338145,7.458263479851398,3,0,0,0,-9,0,-1054.866250744942,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,7.525845245636828,0,0,60.33,43.7,-9,-9,7,1,1,0,0,0,12,3,1,246,245665.2837399505,0,0,1485.887180652842 -938,1104,2031,-9,-9,-9,1,1,0,73,2,0,0,0,3,-9,4,3,0,0,5,0,0,0,3,0,0,0,-9,0,-978.7275361259327,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.39,46.45,-9,-9,6,3,4,0,0,0,8,1,0,88,-66276.28643484283,0,0,1379.177883319177 -939,1105,2032,-9,2033,-9,1,1,0,60,2,0,0,0,3,-9,3,3,0,1,4,0,0,0,3,0,-9,0,-9,0,-1119.568049570524,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,120,1,1,0,4.773218984464954,0,124.5646290950122,3,49.94,58.01,-9,-9,6,1,1,1,0,6.583333333333333,13,1,1,1588,-54153.6191492774,0,0,383.0487183168757 -939,1106,2033,-9,-9,-9,2,1,0,85,2,0,0,0,3,-9,4,3,0,0,3,0,4.687937822259027,4.593759840898407,3,0,-9,0,-9,0,-983.7408079726172,-9,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,1,0,0,15,4,0,-9,0,0,0,1,5.493344503069516,0,126.6160035448804,0,0,50.70177726276479,0,1,1,0,0,4.873308415758681,0,0,53,44,-9,-9,6,1,1,0,0,0,13,2,1,359,290038.8864161032,0,0,1328.810792406118 -939,1107,2034,-9,2032,-9,3,1,1,28,2,0,0,0,2,-9,1,1,0,0,4,7.589544135644987,7.377700544622048,0,3,0,-9,0,-9,0,-981.8812102132615,-9,1,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,6,0,30,0,15,1,0,-9,1,6.002249355935081,6.002249355935081,0,0,0,0,0,0,0,14.5,1,1,0,0,0,7.044345027261836,3,62.49,55.09,-9,-9,1,1,1,0,0,3.333333333333333,13,3,1,1041,-117534.6971803678,0,0,1474.235941675042 -940,1108,2035,2036,-9,-9,2,1,0,65,1,0,0,0,1,-9,4,3,0,0,5,0,7.922424593824975,8.32381611678866,1,0,-9,9,0,-6,-23.53758129777209,0,0,0,0,71,2,5,3,3,2,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,8.05166882607622,0,0,62.39,56.71,57.06,57.76,7,1,1,0,0,5.916666666666667,12,4,1,326,1875679.284133542,0,0,3784.502517099218 -940,1108,2036,2035,-9,-9,1,1,1,71,1,0,0,0,2,-9,4,3,0,0,5,0,7.920995217208431,7.848863753081013,1,0,-9,9,0,6,49.96712950217046,0,0,0,0,65,1,5,3,3,3,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,7,1,1,0,4.866640131230802,7.892316803058333,11.35011049726194,3,57.06,57.76,62.39,56.71,6,1,1,0,0,5.833333333333333,12,4,1,326,1875679.284133542,0,0,3784.502517099218 -941,1109,2037,-9,2039,2040,4,1,0,7,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1033.524637559686,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,10,3,1,732,354069.4121067656,0,0,2582.899386191326 -941,1109,2038,-9,2039,2040,3,1,0,10,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1034.099555431957,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,14,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41,55,-9,-9,5,1,1,0,0,0,10,3,1,732,354069.4121067656,0,0,2582.899386191326 -941,1109,2039,2040,-9,-9,1,1,0,48,1,0,2,0,1,-9,6,3,0,0,3,7.446428263524234,7.655544379989023,5.983228951593119,2,0,-9,5,0,-3,49.69122388388705,0,0,0,0,51,1,4,1,1,1,2019,3,2,7,1,10,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.905803196067824,0,0,0,43.99,50.34,49.46,56.91,6,1,1,0,0,4.083333333333333,10,3,1,732,354069.4121067656,0,0,2582.899386191326 -941,1109,2040,2039,-9,-9,2,1,1,51,1,0,2,0,1,-9,1,1,0,0,4,7.971940208331595,8.190705133253584,0,2,0,-9,5,0,3,101.1239305393868,0,0,0,0,48,1,3,3,2,2,2019,2,1,6,0,38,38,15,1,0,3,0,9.147399582086354,9.147399582086354,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.46,56.91,43.99,50.34,6,1,1,0,0,8.083333333333334,10,3,1,732,354069.4121067656,0,0,2582.899386191326 -942,1110,2041,-9,-9,-9,1,1,0,46,2,0,1,0,1,-9,1,1,0,0,5,9.109302653391262,8.873241707471035,0,4,0,0,0,-9,0,-1042.593030135755,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,12,2,35,40,15,1,0,-9,0,22.90060137529235,22.90060137529235,0,0,0,0,0,0,0,0,1,1,0,7.26172785639659,0,0,0,40.95,63.66,-9,-9,6,1,1,0,0,10.58333333333333,8,5,1,720,273515.7419368765,0,0,4475.423056183728 -942,1110,2042,-9,2041,-9,2,1,0,9,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1024.336767327091,-9,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,4,2,0,0,0,8,5,1,720,273515.7419368765,0,0,4475.423056183728 -943,1111,2043,-9,2045,-9,3,1,0,6,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-912.2202848382266,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,61,-9,-9,5,1,1,0,0,0,9,2,0,842.6666666666666,103823.3573025977,0,0,2374.81365027709 -943,1111,2044,-9,2045,-9,2,1,1,10,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,4,0,0,0,-9,0,-1041.215982175996,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,56,-9,-9,5,4,2,0,0,0,9,2,0,842.6666666666666,103823.3573025977,0,0,2374.81365027709 -943,1111,2045,-9,-9,-9,1,1,0,46,2,0,2,0,2,-9,2,1,0,0,1,7.458009719649604,7.675596092629379,4.029277455312974,4,0,0,0,-9,0,-968.1852827178375,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,24,11,24,26,15,1,1,-9,0,10.06214044424864,10.06214044424864,0,0,0,0,0,0,0,0,1,1,0,4.333088011597683,0,0,0,35.47,38.09,-9,-9,2,1,1,0,0,9.25,9,2,0,842.6666666666666,103823.3573025977,0,0,2374.81365027709 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-967,1137,2111,-9,2107,2108,4,1,1,6,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1204.231143514076,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,5,3,0,573,28180.38533641577,0,0,3820.34558130291 -968,1138,2112,2113,-9,-9,2,1,0,51,1,0,0,0,2,-9,6,3,0,0,3,0,0,0,1,0,-9,6,0,6,10.0331265192593,0,0,0,0,45,2,2,1,-9,-9,2019,3,1,9,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,61.04,39.41,47.43,25.79,5,1,1,0,0,1.5,9,5,0,661,452735.690199526,0,0,3898.734260593065 -968,1138,2113,2112,-9,-9,1,1,1,45,1,0,0,0,2,-9,1,1,0,1,2,8.959792430982565,9.110094982210923,0,1,0,-9,4,0,-6,42.16730113708162,0,0,0,0,51,2,3,3,-9,-9,2019,2,2,19,7,30,60,15,1,1,3,0,28.91986840592776,28.91986840592776,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47.43,25.79,61.04,39.41,3,1,1,0,0,8.333333333333334,9,5,0,661,452735.690199526,0,0,3898.734260593065 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-971,1142,2123,-9,2124,2120,6,1,0,0,2,1,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1066.108177412267,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,7,2,0,1027.2,-39219.14885940511,0,0,3073.056236858005 -971,1142,2124,2120,-9,-9,2,1,0,39,1,1,3,0,2,-9,6,3,0,0,4,0,0,0,2,0,-9,6,0,12,-58.14785727294952,0,0,1,1,27,2,4,1,-9,-9,2019,3,1,13,3,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.96,50.73,58.15,52.91,6,1,1,0,0,2.583333333333333,7,2,0,1027.2,-39219.14885940511,0,0,3073.056236858005 -972,1143,2125,2126,-9,-9,2,1,0,49,1,0,0,0,1,-9,2,1,0,0,3,8.273284629186328,8.179724169262808,0,1,0,-9,9,0,-15,63.4756451227839,0,0,0,0,64,1,3,1,-9,-9,2019,1,1,12,0,38,52,15,1,0,1,0,12.91368571054157,12.91368571054157,0,0,0,0,0,0,0,0,0,0,0,3.51077681511504,0,0,0,51.41,56.15,51,49,3,1,1,0,0,12.66666666666667,2,4,0,939.5,1136984.145594073,0,0,3246.262448328413 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-1291,1543,2841,2840,-9,-9,1,1,0,42,1,0,1,0,2,-9,2,1,0,0,2,7.511809218637224,7.666738895880163,0,2,0,-9,20,0,-10,-110.3779229762164,0,0,1,0,52,2,3,1,2,2,2019,1,2,20,8,80,40,15,1,1,1,0,3.035148956077011,3.035148956077011,0,0,0,0,0,0,0,0,1,1,0,3.227469317133776,0,0,0,40.5,46.83,42.22,52.03,3,1,1,0,0,9.5,11,3,1,1059,388378.122118053,0,0,2178.494359487904 -1292,1544,2842,2845,-9,-9,1,1,1,21,1,2,2,0,1,-9,2,1,0,0,5,8.655840140611373,8.252676191975379,0,2,0,-9,3,0,2,6.190541243247445,0,1,0,0,19,3,4,3,-9,-9,2019,2,2,0,0,30,20,15,1,0,3,0,18.36067072516786,18.36067072516786,0,0,0,0,0,0,0,7,1,1,0,0,0,9.252823612661915,2,32.72,43.47,46,59,5,1,1,0,0,3,12,3,0,859.5,159352.2170478281,0,0,2293.024243568192 -1292,1544,2843,-9,2845,2842,3,1,0,2,2,2,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-934.4002386078976,-9,0,0,0,-9,-9,-9,-9,3,1,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,12,3,0,859.5,159352.2170478281,0,0,2293.024243568192 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-1372,1640,3037,-9,3040,3038,4,1,1,13,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1076.648370171391,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,4,2,1,589,17158.12669423666,0,0,1438.736620495515 -1372,1640,3038,3040,-9,-9,1,1,1,52,1,0,2,0,3,-9,1,1,0,0,4,7.882426113637506,7.860123194921365,0,2,0,-9,15,0,-2,-70.75927194714225,0,0,0,0,54,3,4,3,2,-9,2019,2,2,9,1,0,56,15,1,0,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53,54,49.11,52.88,6,1,1,0,0,1,4,2,1,589,17158.12669423666,0,0,1438.736620495515 -1372,1640,3039,-9,3040,3038,3,1,0,14,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-999.9055399738317,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,1,1,0,0,0,4,2,1,589,17158.12669423666,0,0,1438.736620495515 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-1374,1642,3043,3044,-9,-9,2,1,1,53,1,0,0,0,2,-9,3,3,0,0,4,0,0,0,1,0,-9,6,0,-3,39.78275705764003,0,0,0,0,56,1,3,1,3,3,2019,3,1,9,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54,54,52,54.51,6,1,1,1,0,0,9,4,1,468.5,142559.2612573366,0,0,1666.659432434456 -1374,1642,3044,3043,-9,-9,1,1,0,56,1,0,0,0,1,-9,2,1,0,0,3,8.391426229607609,8.595178065983573,0,1,0,-9,10,0,3,58.61726571512678,0,0,0,0,53,2,4,3,-9,-9,2019,2,2,7,0,26,24,15,1,0,3,0,27.6796517510819,27.6796517510819,0,0,0,0,0,0,0,2,0,0,0,2.693797230082576,0,.7387886544806326,3,52,54.51,54,54,6,1,1,0,0,8.416666666666666,9,4,1,468.5,142559.2612573366,0,0,1666.659432434456 -1375,1643,3045,3046,-9,-9,2,1,1,64,1,0,0,0,2,-9,1,1,0,0,4,7.517351245023849,7.490760970432063,0,1,0,-9,6,0,0,96.04280754230004,0,0,0,0,64,3,3,3,3,3,2019,2,1,7,0,37,35,15,1,0,4,0,6.110735866602593,6.110735866602593,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,54.96,53.17,6,1,1,0,0,8.166666666666666,12,2,1,1927,521008.4429824,0,0,1868.576889749631 -1375,1643,3046,3045,-9,-9,1,1,0,64,1,0,0,0,3,-9,4,3,0,0,3,0,0,0,1,0,-9,45,0,0,70.62070416477714,0,0,0,0,64,2,4,1,-9,-9,2019,3,2,6,0,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.96,53.17,57.16,56.15,6,1,1,0,0,0,12,2,1,1927,521008.4429824,0,0,1868.576889749631 -1376,1644,3047,3048,-9,-9,1,1,1,50,1,0,0,0,2,-9,2,1,0,0,2,8.281927854598376,8.039026975617498,0,1,0,-9,30,0,5,-74.79088564121295,0,0,0,0,45,2,4,1,3,2,2019,1,2,12,0,39,43,15,1,0,1,0,9.188536874360272,9.188536874360272,0,0,0,0,0,0,0,0,0,0,0,3.077697290739305,0,0,0,46.32,53.44,52.82,53.97,5,1,1,0,0,9.583333333333334,10,5,1,335,669220.1430016932,0,0,3097.14082259832 -1376,1644,3048,3047,-9,-9,2,1,0,45,1,0,0,0,2,-9,2,1,0,0,4,8.489077299593561,8.209189536703803,0,1,0,-9,30,0,-5,-160.2758768530423,0,0,0,0,50,2,2,1,1,1,2019,1,1,9,0,45,49,15,1,0,1,0,9.98130779532503,9.98130779532503,0,0,0,0,0,0,0,0,0,0,0,2.436410502200894,0,0,0,52.82,53.97,46.32,53.44,6,1,1,0,0,9.583333333333334,10,5,1,335,669220.1430016932,0,0,3097.14082259832 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-1378,1646,3051,3050,-9,-9,1,1,0,75,1,0,0,0,1,-9,4,3,0,0,3,0,7.836647674114681,7.786841963864823,1,0,-9,55,0,1,-78.85539674820862,0,0,0,0,74,1,4,3,3,-9,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.559579206918043,0,0,64.75,30.9,57.16,56.15,6,1,1,0,0,0,4,4,1,1503.5,3603400.052934438,0,0,3277.496686307712 -1379,1647,3052,3053,-9,-9,1,1,0,58,1,0,0,0,2,-9,2,1,0,0,3,7.646874474591118,7.52659152303218,0,1,0,-9,9,0,3,41.3713747777999,0,0,0,0,55,1,2,1,3,3,2019,1,2,22,9,16,16,15,1,1,1,0,12.30969317531485,12.30969317531485,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28.48,49.07,37.01,42.9,6,1,1,0,0,10.08333333333333,5,4,1,913,431935.0502329151,0,0,2545.443091518214 -1379,1647,3053,3052,-9,-9,2,1,1,55,1,0,0,0,1,-9,2,1,0,0,2,8.005661403110107,8.34341457788746,0,1,0,-9,9,0,-3,-43.714811275231,0,0,0,0,58,2,3,1,-9,-9,2019,1,1,18,6,0,30,15,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.01,42.9,28.48,49.07,3,1,1,0,0,8.416666666666666,5,4,1,913,431935.0502329151,0,0,2545.443091518214 -1380,1648,3054,3055,-9,-9,2,1,0,86,1,0,0,0,3,-9,4,3,0,0,2,0,4.985640943373274,5.049403997504118,1,0,-9,46,0,9,-24.46333247886599,0,0,0,0,77,2,2,3,3,3,2019,4,1,14,2,0,0,15,4,0,4,0,0,0,1,0,5.290242262591663,0,0,0,0,0,1,1,0,0,5.292911008095272,0,0,51.42,49.68,46.55,44.15,7,1,1,0,0,0,10,2,1,284.5,740387.7614197033,0,0,2543.224637724476 -1380,1648,3055,3054,-9,-9,1,1,1,77,1,0,0,0,2,-9,4,3,0,0,2,0,7.548924430586381,7.027077344239999,1,0,-9,46,0,0,-35.29204131984226,0,0,0,0,86,3,2,3,3,3,2019,4,2,12,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.245428827289754,7.50199279072698,0,0,46.55,44.15,51.42,49.68,5,1,1,0,0,0,10,2,1,284.5,740387.7614197033,0,0,2543.224637724476 -1381,1649,3056,3057,-9,-9,2,1,0,77,1,0,0,0,2,-9,4,3,0,0,3,0,4.502695935374033,4.747211288394065,1,0,-9,4,0,4,54.24840146107893,0,0,0,0,73,1,2,3,-9,-9,2019,4,1,9,0,0,0,15,4,0,4,0,0,0,1,2.281732247247045,3.86478800760509,0,0,0,0,0,1,1,0,4.921669986104711,4.747762696959626,0,0,55.52,35.3,59.57,29.57,4,1,1,0,0,0,10,2,1,604.5,1375924.628733581,0,0,1368.085172152839 -1381,1649,3057,3056,-9,-9,1,1,1,73,1,0,0,0,1,-9,4,3,0,0,2,0,6.791296903322573,7.181330126022719,1,0,-9,4,0,-4,-28.23968481546703,0,0,0,0,77,2,3,3,3,3,2019,4,2,11,0,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,2,1,1,0,5.679079385786177,6.497966127823936,4.79429501605679,1,59.57,29.57,55.52,35.3,5,1,1,0,0,0,10,2,1,604.5,1375924.628733581,0,0,1368.085172152839 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-1656,1996,3685,-9,3684,3686,3,1,0,7,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-974.154172783745,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,6,3,1,1193,106946.0092783198,0,0,3330.526923016861 -1656,1996,3686,3684,-9,-9,2,1,1,35,1,0,4,0,1,-9,2,1,0,0,3,8.057383489061394,7.993076742741805,0,2,0,-9,10,0,-6,-70.15307487397614,0,0,0,0,41,2,3,1,1,2,2019,1,1,10,0,38,37,15,1,0,1,0,8.649421019171278,8.649421019171278,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.67,55.57,49.44,54.26,4,1,1,0,1,8.916666666666666,6,3,1,1193,106946.0092783198,0,0,3330.526923016861 -1656,1996,3687,-9,3684,3686,4,1,1,6,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1005.693329849754,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,6,3,1,1193,106946.0092783198,0,0,3330.526923016861 -1657,1997,3688,-9,-9,-9,1,1,1,72,2,0,0,0,3,-9,4,3,0,0,2,0,6.956004109438868,6.473539879125585,3,0,0,0,-9,0,-962.1314275109537,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,9,2,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.645758259268257,6.066798875941974,0,0,57.5,37.38,-9,-9,6,1,1,0,0,0,6,2,1,1082,145087.0568887169,0,0,1432.157775508834 -1658,1998,3689,-9,3690,3692,3,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-956.7548497094563,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,13,4,1,750.5,41315.22467372804,0,0,3062.032644030298 -1658,1998,3690,3692,-9,-9,1,1,0,36,1,0,2,0,1,-9,8,3,1,1,2,0,0,0,2,0,-9,9,0,-1,-163.2309880415483,0,0,1,0,37,2,4,1,3,3,2019,3,2,12,1,0,22,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43.4,31.71,57.16,56.15,6,1,1,0,0,10.08333333333333,13,4,1,750.5,41315.22467372804,0,0,3062.032644030298 -1658,1998,3691,-9,3690,3692,4,1,0,7,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-968.2080882373272,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,60,-9,-9,5,1,1,0,0,0,13,4,1,750.5,41315.22467372804,0,0,3062.032644030298 -1658,1998,3692,3690,-9,-9,2,1,1,37,1,0,2,0,2,-9,2,1,0,0,4,9.038843378699523,8.964067647716227,0,2,0,-9,9,0,1,78.40715183223972,0,0,0,0,36,1,2,3,-9,-9,2019,2,1,6,0,47,52,15,1,0,3,0,18.4256556216845,18.4256556216845,0,0,0,0,0,0,0,0,1,1,0,3.749157853022501,0,0,0,57.16,56.15,43.4,31.71,6,1,1,0,0,10.41666666666667,13,4,1,750.5,41315.22467372804,0,0,3062.032644030298 -1659,1999,3693,-9,-9,-9,1,1,0,54,2,0,0,0,2,-9,4,3,0,1,1,0,6.29233396108727,6.244449814254293,3,0,0,0,-9,0,-1069.585386534384,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,15,3,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,120,1,1,0,0,5.888953843288892,112.415402185413,3,40.55,21,-9,-9,2,1,1,0,0,0,11,2,0,719,82023.35491577721,0,0,-247.6641942535929 -1659,2000,3694,-9,3693,-9,2,1,1,34,2,0,0,0,2,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-1145.229436128439,0,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,13,1,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,30.12,36.2,-9,-9,2,1,1,0,1,0,11,1,0,445,-3511.945258812745,0,0,1375.755506343009 -1660,2001,3695,3696,-9,-9,2,1,1,56,1,0,0,0,2,-9,2,1,0,0,5,8.49260118406089,8.309345035701673,0,1,0,-9,8,0,3,-98.67698591627384,0,0,0,0,53,2,3,1,-9,-9,2019,1,1,8,0,39,39,15,1,0,1,0,19.66152753092331,19.66152753092331,0,0,0,0,0,0,0,0,0,0,0,2.178268378254857,0,0,0,54.1,59.11,54.1,49.39,7,1,1,0,0,9.333333333333334,9,5,1,889.5,592963.323430879,0,0,2991.944742195978 -1660,2001,3696,3695,-9,-9,1,1,0,53,1,0,0,0,2,-9,2,1,0,0,3,7.679634334337284,7.832736324245769,0,1,0,-9,37,0,-3,-45.29017238441791,0,0,0,0,56,2,5,1,3,3,2019,1,2,12,0,25,25,15,1,0,1,0,11.77718368477972,11.77718368477972,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.1,49.39,54.1,59.11,6,1,1,0,0,9.333333333333334,9,5,1,889.5,592963.323430879,0,0,2991.944742195978 -1660,2002,3697,-9,3696,3695,3,1,0,27,2,0,0,0,2,-9,2,1,0,0,3,7.627849000732839,7.751765701494488,0,3,0,0,0,-9,0,-912.055640958947,0,1,1,0,-9,-9,-9,-9,2,2,2019,-9,0,15,5,40,36,15,1,1,-9,1,5.196271451299551,5.196271451299551,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47.19,53.98,-9,-9,3,1,1,0,0,9.333333333333334,9,3,1,658,-69922.53820425025,0,0,868.249161700429 -1661,2003,3698,3699,-9,-9,2,1,1,67,1,0,0,0,2,-9,4,3,0,0,3,0,7.083731925331546,6.52399697579959,1,0,-9,9,0,3,-90.5337833555692,0,0,0,0,64,3,3,3,3,3,2019,4,1,9,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.865304885646504,7.112046764186995,0,0,60.86,50.49,56.85,37.23,6,1,1,0,0,0,4,2,1,424,382134.7415065505,0,0,1656.565803603964 -1661,2003,3699,3698,-9,-9,1,1,0,64,1,0,0,0,3,-9,4,3,0,0,3,0,5.518006852473035,5.601856178460294,1,0,-9,48,0,-3,44.66833777210956,0,0,0,0,67,2,3,3,3,3,2019,4,2,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,4.932105823991266,0,0,56.85,37.23,60.86,50.49,6,1,1,0,0,0,4,2,1,424,382134.7415065505,0,0,1656.565803603964 -1662,2004,3700,3701,-9,-9,1,1,0,72,1,0,0,0,2,-9,4,3,0,0,4,0,7.057923921917827,6.814277304029349,1,0,-9,10,0,0,-69.41803165010117,0,0,0,0,72,2,4,3,3,2,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.401312171677001,0,0,61.27,46.03,45.52,52.01,6,1,1,0,0,3.75,9,4,1,343.5,824666.8861252908,0,0,4377.536204937567 -1662,2004,3701,3700,-9,-9,2,1,1,72,1,0,0,0,2,-9,4,3,0,0,4,0,8.503536599627973,8.921565700100146,1,0,-9,10,0,0,-59.37045570154363,0,0,0,0,72,2,4,3,3,2,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.160128097691739,8.747552156022319,0,0,45.52,52.01,61.27,46.03,6,1,1,0,0,3.416666666666667,9,4,1,343.5,824666.8861252908,0,0,4377.536204937567 -1663,2005,3702,-9,-9,-9,1,1,1,76,2,0,0,0,3,-9,4,3,0,0,2,0,6.823833093443577,6.764244958095056,3,0,0,0,-9,0,-975.143773462258,0,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.712499986664137,0,0,56.1,39.4,-9,-9,4,1,1,0,0,0,7,2,1,887,333805.1000852118,0,0,1390.350573392639 -1664,2006,3703,3704,-9,-9,2,1,0,35,1,1,1,0,1,-9,2,1,0,0,4,8.716604560263075,8.878492554237379,0,2,0,-9,2,0,-7,0,-9,0,1,0,42,2,5,1,-9,-9,2019,1,1,6,0,37,0,15,1,0,1,0,20.52079695188164,20.52079695188164,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.24,58.84,57.06,57.76,7,1,1,0,0,9.166666666666666,12,5,1,1253,139145.1881812413,0,0,4552.105216547018 -1664,2006,3704,3703,-9,-9,1,1,1,42,1,1,1,0,2,-9,2,1,0,0,5,8.930954053739178,8.711161969231233,0,2,0,-9,2,0,7,0,0,0,0,1,35,1,4,1,2,1,2019,1,2,8,0,40,40,15,1,0,1,0,19.98688951906874,19.98688951906874,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.06,57.76,51.24,58.84,6,1,1,0,0,9.583333333333334,12,5,1,1253,139145.1881812413,0,0,4552.105216547018 -1664,2006,3705,-9,3703,3704,3,1,1,1,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1024.556134997326,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,12,5,1,1253,139145.1881812413,0,0,4552.105216547018 -1665,2007,3706,-9,3707,-9,2,1,0,8,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1057.478574183666,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,60,-9,-9,5,1,1,0,0,0,9,2,0,86,76625.45802397146,0,0,2675.141783410244 -1665,2007,3707,-9,-9,-9,1,1,0,29,2,0,1,0,2,-9,2,1,0,0,1,7.03751190965706,7.198803901341881,5.506675154675054,4,0,0,0,-9,0,-1072.544463308403,0,1,1,0,-9,-9,-9,-9,-9,2,2019,-9,0,26,10,15,15,15,1,1,-9,0,8.328876944458006,8.328876944458006,0,0,0,0,0,0,0,0,1,1,0,5.515978180412671,0,0,0,21.87,37.7,-9,-9,4,1,1,0,1,6.083333333333333,9,2,0,86,76625.45802397146,0,0,2675.141783410244 -1666,2008,3708,-9,-9,-9,1,1,0,96,2,0,0,0,2,-9,4,3,0,0,1,0,4.472061650531925,4.230992859115422,3,0,0,0,-9,0,-985.2399247920315,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,22,6,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.14593936881776,4.758921685808208,0,0,26.73,24.82,-9,-9,2,1,1,0,0,0,11,1,1,2318,-21409.30980004312,0,0,134.4172001058015 -1667,2009,3709,-9,-9,-9,1,1,1,73,2,0,0,0,2,-9,4,3,0,0,4,0,7.587353456417768,7.736280643387201,3,0,0,0,-9,0,-946.1234481245615,0,0,0,0,-9,-9,-9,-9,3,1,2019,-9,0,7,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.30166680871079,7.71697805022478,0,0,66.36,32.68,-9,-9,6,1,1,0,0,0,9,3,1,1666,1544901.916264822,0,0,1330.271514528779 -1668,2010,3710,-9,-9,-9,1,1,1,53,2,0,0,0,2,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-826.4587138608315,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,16,5,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,26.95,30.1,-9,-9,2,1,1,0,0,0,13,1,0,475,-181075.6120204146,0,0,1223.801765967998 -1669,2011,3711,-9,-9,-9,1,1,0,42,2,0,2,0,1,-9,2,1,0,0,3,7.887365503382874,7.951379292631759,0,4,0,0,0,-9,0,-1119.089591437832,0,0,1,0,-9,-9,-9,-9,3,2,2019,-9,0,10,0,33,40,15,1,0,-9,0,7.254313941229577,7.254313941229577,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.29,54.59,-9,-9,6,1,1,0,0,6.083333333333333,10,3,0,379,118304.0888213882,0,0,1662.81081912595 -1670,2012,3712,-9,-9,-9,1,1,0,66,2,0,0,0,3,-9,4,3,0,0,5,0,0,0,3,0,0,0,-9,0,-771.7610657399289,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,56,54,-9,-9,7,1,1,0,0,0,4,1,0,461,-149518.0869263824,0,0,1059.284556558462 -1671,2013,3713,-9,3716,3715,4,1,1,3,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-922.4372880069154,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,9,4,1,458.5,211074.9057808644,0,0,3681.369730248914 -1671,2013,3714,-9,3716,3715,3,1,0,5,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-999.6098208420893,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,9,4,1,458.5,211074.9057808644,0,0,3681.369730248914 -1671,2013,3715,3716,-9,-9,2,1,1,38,1,0,2,0,2,-9,2,1,0,0,2,8.805730295809212,8.951892523407352,0,2,0,-9,8,0,8,-182.0074237026299,0,0,0,0,30,2,3,3,2,2,2019,2,1,16,5,38,38,15,1,1,3,0,21.74643072439819,21.74643072439819,0,0,0,0,0,0,0,0,1,1,0,.1008361963028919,0,0,0,24.07,47.67,30.75,61.56,6,1,1,0,0,8.75,9,4,1,458.5,211074.9057808644,0,0,3681.369730248914 -1671,2013,3716,3715,-9,-9,1,1,0,30,1,0,2,0,2,-9,6,3,0,0,3,0,0,0,2,0,-9,9,0,-8,-35.48355241900669,0,0,1,0,38,2,2,1,2,2,2019,3,2,13,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,30.75,61.56,24.07,47.67,6,1,1,0,0,4.916666666666667,9,4,1,458.5,211074.9057808644,0,0,3681.369730248914 -1672,2014,3717,3718,-9,-9,2,1,0,54,1,0,0,0,1,-9,1,1,0,0,4,9.289717396458563,9.343486823458456,0,1,0,-9,6,0,-2,8.013913620350195,0,0,0,0,56,1,3,1,1,1,2019,1,1,10,0,7,4,15,1,0,1,0,283.9694680397894,283.9694680397894,0,0,0,0,0,0,0,0,0,0,0,6.763152100327897,0,0,0,56.27,41.65,55.02,46.73,6,2,3,0,0,8.166666666666666,8,5,1,523,3058489.953341245,0,0,6595.393666974812 -1672,2014,3718,3717,-9,-9,1,1,1,56,1,0,0,0,1,-9,2,1,0,0,3,9.055187912304632,8.737613154607729,0,1,0,-9,33,0,2,46.91316880892426,0,0,0,0,54,1,4,1,2,1,2019,1,2,7,0,48,55,15,1,0,1,0,25.16002517196379,25.16002517196379,0,0,0,0,0,0,0,2,0,0,0,3.621863256489204,0,0,3,55.02,46.73,56.27,41.65,2,2,3,0,0,8.166666666666666,8,5,1,523,3058489.953341245,0,0,6595.393666974812 -1672,2015,3719,-9,3717,3718,3,1,1,24,2,0,0,1,2,0,7,2,0,0,5,0,0,0,3,0,0,0,-9,0,-1057.796248469884,-9,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,1,0,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,3.623791186879299,3,60.02,56.42,-9,-9,6,2,3,0,0,0,8,1,1,201,10108.5190364096,0,0,267.4748004685863 -1673,2016,3720,-9,-9,-9,1,1,0,23,2,0,0,0,2,-9,7,2,0,0,4,6.114890270842426,5.890526189533075,0,3,0,0,0,-9,0,-974.4607695376844,1,1,1,0,-9,-9,-9,-9,1,1,2019,-9,0,18,5,12,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.39,66.76000000000001,-9,-9,2,3,4,0,1,1.333333333333333,4,2,0,385,78874.97620237604,0,0,1364.297722524777 -1674,2017,3721,-9,-9,-9,1,1,0,20,2,0,0,0,2,0,7,2,0,0,3,6.827160148692915,6.864679483604162,0,3,0,0,0,-9,0,-1091.988894541201,-9,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,13,1,15,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.88,59.72,-9,-9,6,1,1,0,0,3.416666666666667,12,2,0,230,-23149.75223789372,0,0,-455.1322960252393 -1675,2018,3722,3723,-9,-9,1,1,1,73,1,0,0,0,2,-9,4,3,0,0,2,0,7.006536087873338,7.180374091588646,1,0,-9,8,0,2,29.38789318673901,0,0,0,0,71,2,4,3,3,3,2019,4,2,11,2,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.100340771268203,6.7231679164436,0,0,55.51,24.77,59.74,45.34,4,1,1,0,0,0,2,3,1,335,1104648.709339853,0,0,2921.384595149152 -1675,2018,3723,3722,-9,-9,2,1,0,71,1,0,0,0,2,-9,4,3,0,0,4,0,7.618656125062818,7.262489531416921,1,0,-9,8,0,-2,-11.26212728884073,0,0,0,0,73,2,2,3,2,2,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,8.3736387897701,7.44298664262477,0,0,59.74,45.34,55.51,24.77,6,1,1,0,0,0,2,3,1,335,1104648.709339853,0,0,2921.384595149152 -1676,2019,3724,3725,-9,-9,2,1,1,53,1,0,0,0,2,-9,2,1,0,0,2,8.83885826053765,8.920250018457773,0,1,0,-9,9,0,-5,-143.6448864105038,0,0,0,0,58,2,1,3,3,3,2019,2,1,15,4,55,50,15,1,1,3,0,14.47315698630283,14.47315698630283,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,12.12,57.09,19.01,22.64,3,1,1,0,0,9.5,2,5,1,315,-215619.9199728344,0,0,2193.106666787952 -1676,2019,3725,3724,-9,-9,1,1,0,58,1,0,0,0,2,-9,8,3,1,1,1,0,0,0,1,0,-9,9,0,5,53.9026918516296,0,0,0,0,53,2,2,1,3,3,2019,3,2,34,12,0,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,19.01,22.64,12.12,57.09,4,1,1,0,0,0,2,5,1,315,-215619.9199728344,0,0,2193.106666787952 -1677,2020,3726,-9,-9,-9,1,1,0,45,2,0,0,0,1,-9,2,1,0,0,3,8.093936238282231,8.243256321603663,0,3,0,0,0,-9,0,-971.833975860975,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,6,0,38,40,15,1,0,-9,0,13.63185605102018,13.63185605102018,0,0,0,0,0,0,0,0,1,1,0,3.155623248192668,0,0,0,54.96,53.17,-9,-9,6,1,1,0,0,9.083333333333334,5,4,1,1369,-224194.9975137888,0,0,1925.447905587619 -1678,2021,3727,-9,-9,-9,1,1,0,69,2,0,0,0,1,-9,4,3,0,1,1,0,0,0,3,0,0,0,-9,0,-961.1474595726032,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,1,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,56.19,5.98,-9,-9,6,1,1,0,0,0,4,1,1,533,407964.7666395297,0,0,1202.742162642866 -1679,2022,3728,3729,-9,-9,2,1,0,78,1,0,0,0,3,-9,4,3,0,0,2,0,0,0,1,0,-9,57,0,-4,62.54483417533572,0,0,0,0,82,3,3,3,3,3,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.47,32.69,47.17,46.96,5,1,1,0,0,6.75,11,3,1,617,506044.1854354431,0,0,1659.270446595868 -1679,2022,3729,3728,-9,-9,1,1,1,82,1,0,0,0,3,-9,4,3,0,0,3,0,7.490197333624343,7.856104171558875,1,0,-9,57,0,4,84.50461889186593,0,0,0,0,78,3,2,3,3,3,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,2.971008348011227,7.626313851322482,0,0,47.17,46.96,53.47,32.69,6,1,1,0,0,0,11,3,1,617,506044.1854354431,0,0,1659.270446595868 -1680,2023,3730,-9,-9,-9,1,1,1,70,2,0,0,0,3,-9,4,3,0,0,2,0,0,0,3,0,0,0,-9,0,-827.6111256420455,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,13,2,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.43,28.6,-9,-9,4,1,1,0,0,0,5,1,0,154,-67548.18035905338,0,0,1645.91814216297 -1681,2024,3731,3732,-9,-9,2,1,0,50,1,0,3,0,3,-9,6,3,0,0,5,0,0,0,2,0,-9,19,0,0,-26.24419349788176,0,0,0,0,50,3,4,1,3,3,2019,3,1,10,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.08,55.11,52,55,6,4,5,0,0,0,8,2,0,596.8,1725264.197488616,0,0,1656.061584611534 -1681,2024,3732,3731,-9,-9,1,1,1,50,1,0,3,0,3,-9,1,1,0,0,4,6.589161916536982,6.522649559803388,0,2,0,-9,19,0,0,-58.66070659130885,0,0,0,0,50,3,5,3,3,3,2019,2,2,9,1,8,40,15,1,0,3,0,11.91909663391811,11.91909663391811,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,55,51.08,55.11,6,4,5,0,0,1,8,2,0,596.8,1725264.197488616,0,0,1656.061584611534 -1681,2024,3733,-9,3731,3732,5,1,1,12,2,0,3,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-999.012923194979,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48,62,-9,-9,5,4,5,0,0,0,8,2,0,596.8,1725264.197488616,0,0,1656.061584611534 -1681,2024,3734,-9,3731,3732,4,1,0,15,2,0,3,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1103.629090435208,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,14,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41,54,-9,-9,5,4,5,0,0,0,8,2,0,596.8,1725264.197488616,0,0,1656.061584611534 -1681,2024,3735,-9,3731,3732,3,1,1,17,2,0,3,1,2,0,7,2,0,0,4,0,0,0,2,0,0,0,-9,0,-974.7842255957935,-9,1,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.73,54.53,-9,-9,6,4,5,0,0,0,8,2,0,596.8,1725264.197488616,0,0,1656.061584611534 -1682,2025,3736,-9,-9,-9,1,1,0,67,2,0,0,0,3,-9,4,3,0,0,3,0,6.771251981244867,7.184213401337496,3,0,0,0,-9,0,-1048.629105171964,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.18689009699765,6.493629944486119,0,0,54.14,42.51,-9,-9,6,1,1,0,0,0,7,2,0,354,192554.5592302331,0,0,1333.52322917075 -1683,2026,3737,-9,-9,-9,1,1,1,54,2,0,0,0,2,-9,2,1,0,0,3,8.797667893099332,8.60763125791599,0,3,0,0,0,-9,0,-986.907134231638,0,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,7,0,50,63,15,1,0,-9,0,17.00397583849644,17.00397583849644,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,55.96,49.93,-9,-9,6,3,4,0,0,8.583333333333334,6,5,1,520,345811.1490143492,0,0,2466.176190020102 -1684,2027,3738,3739,-9,-9,1,1,1,46,1,0,2,0,2,-9,2,1,0,0,4,8.436317596309033,8.079273913351427,0,2,0,-9,19,0,-1,-170.0913031153648,0,0,0,0,47,2,3,1,2,3,2019,1,2,9,0,37,37,15,1,0,1,0,19.37680705438754,19.37680705438754,0,0,0,0,0,0,0,0,1,1,0,2.064956852839993,0,0,0,54.2,57.49,52.79,51.64,6,1,1,0,0,10.16666666666667,13,4,1,605.75,290043.7493903844,0,0,3252.45421589534 -1684,2027,3739,3738,-9,-9,2,1,0,47,1,0,2,0,2,-9,2,1,0,0,3,8.308418795312605,8.529166584036787,0,2,0,-9,9,0,1,-81.48978390585965,0,0,0,0,46,2,4,1,-9,-9,2019,1,1,9,0,42,20,15,1,0,1,0,9.475994789167375,9.475994789167375,0,0,0,0,0,0,0,0,1,1,0,1.438965493475258,0,0,0,52.79,51.64,54.2,57.49,6,1,1,0,0,10.16666666666667,13,4,1,605.75,290043.7493903844,0,0,3252.45421589534 -1684,2027,3740,-9,3739,3738,3,1,0,13,2,0,2,1,3,-9,-9,2,0,0,2,0,0,0,2,0,0,0,-9,0,-970.6501067751736,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,16,4,0,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,37,44,-9,-9,4,1,1,0,0,0,13,4,1,605.75,290043.7493903844,0,0,3252.45421589534 -1684,2027,3741,-9,3739,3738,4,1,1,10,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1019.646954315046,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,56,-9,-9,5,1,1,0,0,0,13,4,1,605.75,290043.7493903844,0,0,3252.45421589534 -1685,2028,3742,3743,-9,-9,1,1,1,53,1,0,0,0,2,-9,1,1,0,0,3,6.828928467745747,6.982482115216476,0,1,0,-9,33,0,2,104.5647719818853,0,0,0,0,51,3,3,1,3,3,2019,1,2,9,0,40,0,15,1,0,1,0,1.991218979427799,1.991218979427799,0,0,0,0,0,0,0,0,0,0,0,2.555043904707237,0,0,0,52.65,51.64,57.92,51.82,4,1,1,0,0,5.916666666666667,9,3,1,399,144605.1273383928,0,0,1607.041994510817 -1685,2028,3743,3742,-9,-9,2,1,0,51,1,0,0,0,3,-9,2,1,0,0,3,7.154934926355174,7.816760881231803,6.972161660641647,1,0,-9,33,0,-2,70.26800916278169,0,0,0,0,53,2,3,1,-9,-9,2019,1,1,13,1,16,0,15,1,0,1,0,9.150936690105581,9.150936690105581,0,0,0,0,0,0,0,0,0,0,0,0,6.946597194222867,0,0,57.92,51.82,52.65,51.64,1,1,1,0,0,8.083333333333334,9,3,1,399,144605.1273383928,0,0,1607.041994510817 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-1962,2368,4380,-9,4382,4384,4,1,1,12,2,0,3,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1013.644632906463,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,55,-9,-9,5,1,1,0,0,0,6,4,1,444.6,459435.3410877323,0,0,4644.857789161671 -1962,2368,4381,-9,4382,4384,3,1,1,14,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1063.417375912265,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,6,4,1,444.6,459435.3410877323,0,0,4644.857789161671 -1962,2368,4382,4384,-9,-9,2,1,0,39,1,0,3,0,2,-9,2,1,0,0,4,8.538316576202572,8.657860663901882,0,2,0,-9,7,0,0,-179.4703952549099,0,0,1,0,48,2,3,1,3,1,2019,1,1,10,1,53,53,15,1,0,1,0,9.961297562262352,9.961297562262352,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.83,57.2,49.19,53.68,5,1,1,0,0,4.833333333333333,6,4,1,444.6,459435.3410877323,0,0,4644.857789161671 -1962,2368,4383,-9,4382,4384,5,1,0,10,2,0,3,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-961.9226195992915,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,14,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41,55,-9,-9,5,1,1,0,0,0,6,4,1,444.6,459435.3410877323,0,0,4644.857789161671 -1962,2368,4384,4382,-9,-9,1,1,1,48,1,0,3,0,2,-9,2,1,0,0,3,8.939200790512242,8.922017233455355,0,2,0,-9,7,0,9,6.338525942736628,0,0,0,0,39,2,4,1,-9,-9,2019,1,2,8,0,65,65,15,1,0,1,0,10.25683749831008,10.25683749831008,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.19,53.68,51.83,57.2,6,1,1,0,0,7.5,6,4,1,444.6,459435.3410877323,0,0,4644.857789161671 -1963,2369,4385,-9,-9,-9,1,1,0,51,2,0,0,0,1,-9,2,1,0,0,4,8.853494792737026,8.823693775045925,0,1,0,-9,10,0,6,-16.01730382476894,0,0,0,0,-9,-9,-9,-9,3,2,2019,1,2,11,0,32,30,15,1,0,-9,0,20.67900603566697,20.67900603566697,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.91,59.89,45.82,54.57,5,1,1,0,0,11.66666666666667,2,5,1,281,886095.5521194442,0,0,2483.18542231629 -1963,2370,4386,-9,-9,-9,2,1,0,45,2,0,0,0,1,-9,2,1,0,0,4,8.318303376154754,8.16319054471232,0,1,0,-9,10,0,-6,16.0011763209029,0,0,0,0,-9,-9,-9,-9,2,3,2019,1,1,13,2,38,32,15,1,0,-9,0,11.82343497556405,11.82343497556405,0,0,0,0,0,0,0,0,0,0,0,2.137393720260981,0,0,0,45.82,54.57,45.91,59.89,6,1,1,0,0,11.66666666666667,2,5,1,484,217055.7152552202,0,0,1382.681168375251 -1964,2371,4387,4388,-9,-9,2,1,1,36,1,0,0,0,1,-9,2,1,0,0,4,8.876113306313892,8.801324448314118,0,1,0,-9,13,0,0,-52.48155456505071,0,0,0,0,36,1,4,1,1,1,2019,1,1,10,0,38,50,15,1,0,1,0,14.40705395695417,14.40705395695417,0,0,0,0,0,0,0,0,0,0,0,.8613039670795986,0,0,0,45.91,59.89,37.31,57.36,5,1,1,0,0,7.5,6,5,1,507,258482.9378696822,0,0,4612.97366094371 -1964,2371,4388,4387,-9,-9,1,1,0,36,1,0,0,0,1,-9,2,1,0,0,4,8.746830424908573,8.835743082338297,0,1,0,-9,13,0,0,-45.67152412633268,0,0,1,0,36,1,4,1,2,2,2019,1,2,20,8,48,50,15,1,1,1,0,14.95994864782588,14.95994864782588,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.31,57.36,45.91,59.89,5,1,1,0,0,8.166666666666666,6,5,1,507,258482.9378696822,0,0,4612.97366094371 -1965,2372,4389,4390,-9,-9,2,1,0,67,1,0,0,0,2,-9,4,3,0,0,2,0,5.902927150418184,5.987743882684037,1,0,-9,22,0,8,72.77033094091651,0,0,0,0,59,1,4,1,3,2,2019,3,1,12,1,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.190296809692046,6.042117493544458,0,0,41.65,36.47,24.85,67.03,5,1,1,0,0,10.5,7,4,1,261,1478447.893308204,0,0,2506.245678763753 -1965,2372,4390,4389,-9,-9,1,1,1,59,1,0,0,0,1,-9,2,1,0,0,4,8.641654712715237,8.41939719102759,0,1,0,-9,22,0,-8,-115.6567167622727,0,0,0,0,67,2,2,3,2,-9,2019,2,2,22,11,34,36,15,1,1,4,0,16.04132794962511,16.04132794962511,0,0,0,0,0,0,0,0,1,1,0,4.167033293290046,0,0,0,24.85,67.03,41.65,36.47,2,1,1,0,0,12.75,7,4,1,261,1478447.893308204,0,0,2506.245678763753 -1966,2373,4391,4392,-9,-9,2,1,0,30,1,1,2,0,2,-9,2,1,0,0,4,7.563557594413931,7.662571824205007,0,2,0,-9,5,0,-2,110.186088488411,0,0,1,0,32,2,3,1,-9,-9,2019,1,1,8,0,33,36,15,1,0,1,0,7.276230608054575,7.276230608054575,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,61.12,51.57,39.54,49.64,5,1,1,0,0,12.58333333333333,13,4,1,522,107350.4294440316,0,0,3049.833952509045 -1966,2373,4392,4391,-9,-9,1,1,1,32,1,1,2,0,2,-9,2,1,0,0,3,8.22539642558313,8.290767783639224,0,2,0,-9,5,0,2,-61.05763969540356,0,0,0,0,30,2,4,1,2,2,2019,1,2,11,0,47,47,15,1,0,1,0,8.62797883752987,8.62797883752987,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,39.54,49.64,61.12,51.57,4,1,1,0,0,10.33333333333333,13,4,1,522,107350.4294440316,0,0,3049.833952509045 -1966,2373,4393,-9,4391,4392,4,1,0,2,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1182.517046407018,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,62,-9,-9,5,1,1,0,0,0,13,4,1,522,107350.4294440316,0,0,3049.833952509045 -1966,2373,4394,-9,4391,4392,3,1,1,4,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1036.79947121871,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,62,-9,-9,5,1,1,0,0,0,13,4,1,522,107350.4294440316,0,0,3049.833952509045 -1967,2374,4395,-9,-9,-9,1,1,0,69,2,0,0,0,3,-9,2,1,0,0,4,6.582316716658307,6.950629185144504,0,3,0,0,0,-9,0,-1027.616704362088,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,6,0,20,20,15,1,0,-9,0,6.977780161298327,6.977780161298327,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,60.72,47.63,-9,-9,6,1,1,0,0,7.083333333333333,13,2,1,432,23516.1257460287,0,0,1104.891373422581 -1968,2375,4396,-9,-9,-9,1,1,1,53,2,0,0,0,2,-9,2,1,0,0,3,8.638463282216771,8.622496282368886,0,3,0,0,0,-9,0,-944.5638464633877,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,0,40,42,15,1,0,-9,0,16.73321290102355,16.73321290102355,0,0,0,0,0,0,0,2,1,1,0,0,0,3.834364408538463,3,55.1,39.62,-9,-9,6,1,1,0,0,9.75,12,5,1,596,1148664.853830102,0,0,1558.327236862604 -1969,2376,4397,4398,-9,-9,1,1,0,74,1,0,0,0,3,-9,4,3,0,0,3,0,0,0,1,0,-9,23,0,17,-21.05884013609924,0,0,0,0,57,2,3,1,-9,-9,2019,3,2,9,0,0,0,15,4,0,1,0,0,0,1,0,19.00693961452085,0,0,0,0,0,1,1,0,0,0,0,0,43.43,44.84,60.86,50.49,6,1,1,0,0,0,10,2,0,282,1889899.42308775,0,0,2042.995746877186 -1969,2376,4398,4397,-9,-9,2,1,1,57,1,0,0,0,2,-9,1,1,0,0,3,7.149728710944534,6.956362172637234,0,1,0,-9,7,0,-17,82.54882830144197,0,0,0,0,74,3,3,3,-9,-9,2019,2,1,9,0,16,16,15,1,0,4,0,7.317045113277418,7.317045113277418,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,60.86,50.49,43.43,44.84,7,1,1,0,0,9.916666666666666,10,2,0,282,1889899.42308775,0,0,2042.995746877186 -1970,2377,4399,-9,-9,-9,1,1,1,38,2,0,0,0,2,-9,2,1,0,0,3,8.114658356891715,8.084613978195765,0,3,0,0,0,-9,0,-951.3428414097915,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,18,6,45,36,15,1,1,-9,0,9.255171934056168,9.255171934056168,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20.27,55.75,-9,-9,2,1,1,0,0,8.583333333333334,8,4,0,1414,-41736.84496656294,0,0,1434.256781637381 -1971,2378,4400,-9,-9,-9,1,1,0,22,2,0,0,1,1,0,7,2,0,0,4,0,7.103515575451513,7.486067839424463,3,0,0,0,-9,0,-1042.565518324591,-9,1,1,0,-9,-9,-9,-9,1,1,2019,-9,0,15,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.326636383157462,0,0,0,40.71,62.41,-9,-9,6,1,1,0,0,0,1,2,0,527,-22857.16286273348,0,0,981.8359692310473 -1972,2379,4401,4402,-9,-9,2,1,1,47,1,0,1,0,1,-9,2,1,0,0,3,9.169142526525606,9.221187724742686,0,2,0,-9,1,-9,1,31.33294873640332,-9,0,0,0,46,2,3,1,-9,-9,2019,1,1,8,0,40,0,15,1,0,1,0,33.34851554369642,33.34851554369642,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.33,55.93,55.36,51.57,5,1,1,0,0,10.08333333333333,4,5,1,630.6666666666666,469084.3706001033,0,0,4295.839546720706 -1972,2379,4402,4401,-9,-9,1,1,0,46,1,0,1,0,2,-9,1,1,0,0,3,7.370427436286151,7.306141773153159,0,2,0,-9,18,-9,-1,-29.0043574348779,-9,0,0,0,47,1,3,1,2,2,2019,1,2,9,1,2,0,15,1,0,1,0,79.44711715065047,79.44711715065047,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,55.36,51.57,46.33,55.93,6,1,1,0,0,10.41666666666667,4,5,1,630.6666666666666,469084.3706001033,0,0,4295.839546720706 -1972,2379,4403,-9,4402,4401,3,1,1,16,2,0,1,0,2,-9,2,2,0,0,4,6.547305098901587,6.495111782805489,0,2,0,-9,0,-9,0,-1036.973470462788,-9,1,0,0,-9,-9,-9,-9,2,1,2019,-9,0,7,0,15,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.12,57.28,-9,-9,2,1,1,0,0,.5833333333333334,4,5,1,630.6666666666666,469084.3706001033,0,0,4295.839546720706 -1973,2380,4404,-9,4405,4406,3,1,0,11,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1016.727576416423,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,1,1,0,0,0,13,5,1,340.25,572350.0021303985,0,0,4299.555255681992 -1973,2380,4405,4406,-9,-9,1,1,0,38,1,0,2,0,1,-9,2,1,0,0,3,8.85211860802802,8.845875892940127,0,2,0,-9,16,0,-8,142.1561612628662,0,0,1,0,46,1,5,1,1,2,2019,1,2,5,0,32,28,15,1,0,1,0,23.20240387758356,23.20240387758356,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.37,54.8,54.69,57.47,6,1,1,0,0,7.666666666666667,13,5,1,340.25,572350.0021303985,0,0,4299.555255681992 -1973,2380,4406,4405,-9,-9,2,1,1,46,1,0,2,0,1,-9,2,1,0,0,5,8.453572536552768,8.367962493433192,0,2,0,-9,7,0,8,98.27420091305659,0,0,0,0,38,1,3,1,-9,-9,2019,1,1,7,0,48,94,15,1,0,1,0,12.51636234448782,12.51636234448782,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.69,57.47,54.37,54.8,5,1,1,0,0,8.25,13,5,1,340.25,572350.0021303985,0,0,4299.555255681992 -1973,2380,4407,-9,4405,4406,4,1,1,10,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1140.208467866169,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,13,5,1,340.25,572350.0021303985,0,0,4299.555255681992 -1974,2381,4408,4409,-9,-9,2,1,1,49,1,0,0,0,3,-9,8,3,1,1,2,0,0,0,1,0,-9,8,0,5,0,0,0,0,0,44,2,2,3,-9,-9,2019,4,1,16,4,0,0,15,3,1,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,31.44,38.78,42,40,3,1,1,0,0,0,12,1,1,701.5,-103448.7250869916,0,0,934.7500105230113 -1974,2381,4409,4408,-9,-9,1,1,0,44,1,0,0,0,2,-9,8,3,1,1,2,0,0,0,1,0,-9,8,0,-5,0,0,0,1,0,49,3,2,3,2,2,2019,4,2,32,11,0,0,15,3,1,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,40,31.44,38.78,1,1,1,0,1,1.333333333333333,12,1,1,701.5,-103448.7250869916,0,0,934.7500105230113 -1975,2382,4410,-9,-9,-9,1,1,0,87,2,0,0,0,3,-9,4,3,0,1,2,0,0,0,3,0,0,0,-9,0,-1106.101224291766,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,16,4,0,0,15,4,1,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.13,18.97,-9,-9,2,1,1,0,0,0,10,1,0,249,-26681.26100585608,0,0,2866.529504529051 -1976,2383,4411,4413,-9,-9,1,1,0,35,1,1,1,0,1,-9,2,1,0,0,4,8.218270778163172,8.565506447702909,0,2,0,-9,10,0,-3,78.67157986761505,0,0,1,0,38,1,3,1,2,2,2019,1,2,6,0,17,16,15,1,0,1,0,29.41217076962642,29.41217076962642,0,0,0,0,0,0,0,0,1,1,0,1.003531958655759,0,0,0,48.74,51.67,46.73,54.33,6,1,1,0,0,11.5,5,5,1,213,446935.4575595233,0,0,5127.246014512425 -1976,2383,4412,-9,4411,4413,3,1,0,2,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-920.391293837234,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,61,-9,-9,5,1,1,0,0,0,5,5,1,213,446935.4575595233,0,0,5127.246014512425 -1976,2383,4413,4411,-9,-9,2,1,1,38,1,1,1,0,1,-9,2,1,0,0,3,9.177316687455122,8.892386638750281,0,2,0,-9,10,0,3,-52.52267004196469,0,0,0,0,35,1,4,1,2,2,2019,1,1,15,4,70,60,15,1,1,1,0,17.96782999525535,17.96782999525535,0,0,0,0,0,0,0,0,1,1,0,.9621111436886424,0,0,0,46.73,54.33,48.74,51.67,5,1,1,0,0,9.916666666666666,5,5,1,213,446935.4575595233,0,0,5127.246014512425 -1977,2384,4414,-9,-9,-9,1,1,1,59,2,0,0,0,3,-9,1,1,0,0,4,7.390189530645378,7.406161007171865,0,3,0,0,0,-9,0,-1064.535414114453,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,0,30,30,15,1,0,-9,0,6.089371288749939,6.089371288749939,0,0,0,0,0,0,0,0,1,1,0,.2076817383213613,0,0,0,49.12,57.28,-9,-9,4,1,1,0,0,9.25,2,3,0,784,97319.86796082191,0,0,440.6802433846878 -1978,2385,4415,4416,-9,-9,2,1,1,48,1,0,2,0,2,-9,6,3,0,1,4,0,0,0,2,0,-9,10,-9,6,117.4156594665063,-9,0,0,0,42,1,2,1,2,2,2019,3,1,9,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,74.5,1,1,0,0,0,75.4029931368205,3,57.98,47.73,50.51,32.45,6,1,1,0,0,4.416666666666667,11,4,1,1878.75,228861.8507650051,0,0,3386.088785221921 -1978,2385,4416,4415,-9,-9,1,1,0,42,1,0,2,0,1,-9,2,1,0,0,2,9.045237889619932,9.442875315696151,0,2,0,-9,10,-9,-6,-12.24657422888876,-9,0,1,0,48,2,4,3,3,2,2019,2,2,11,2,39,0,15,1,0,3,0,22.80763330647796,22.80763330647796,0,0,0,0,0,0,0,0,1,1,0,6.450154678008529,0,0,0,50.51,32.45,57.98,47.73,5,1,1,0,0,12.41666666666667,11,4,1,1878.75,228861.8507650051,0,0,3386.088785221921 -1978,2385,4417,-9,4416,4415,4,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-869.2719915437839,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,11,4,1,1878.75,228861.8507650051,0,0,3386.088785221921 -1978,2385,4418,-9,4416,4415,3,1,1,11,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-953.8442701602996,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,11,4,1,1878.75,228861.8507650051,0,0,3386.088785221921 -1979,2386,4419,-9,-9,-9,1,1,0,26,2,0,0,0,1,-9,2,1,0,0,4,8.264803831039995,8.478110003323168,0,3,0,0,0,-9,0,-1117.504722387852,0,1,1,0,-9,-9,-9,-9,1,1,2019,-9,0,8,0,20,55,15,1,0,-9,0,24.11651516652281,24.11651516652281,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,-9,-9,6,1,1,0,0,4.833333333333333,8,4,0,360,1646.955853401398,0,0,1541.476039541792 -1980,2387,4420,4421,-9,-9,1,1,0,61,1,0,0,0,2,-9,2,1,0,0,2,8.085080821462306,8.042959930211763,0,1,0,-9,7,0,12,-82.34757142239513,0,0,0,0,49,2,1,1,3,-9,2019,1,2,16,4,40,38,15,1,1,1,0,11.61169475540235,11.61169475540235,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,36.6,48.26,49.61,41.04,6,1,1,0,0,9.25,4,4,1,1135.5,442916.0352503828,0,0,3002.505980843112 -1980,2387,4421,4420,-9,-9,2,1,1,49,1,0,0,0,2,-9,2,1,0,0,1,8.238393689643141,8.374664087908615,0,1,0,-9,7,0,-12,-4.95960055161581,0,0,0,0,61,2,2,1,2,3,2019,1,1,11,2,36,36,15,1,0,1,0,12.5039411502879,12.5039411502879,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.61,41.04,36.6,48.26,4,1,1,0,0,7.166666666666667,4,4,1,1135.5,442916.0352503828,0,0,3002.505980843112 -1981,2388,4422,4423,-9,-9,1,1,0,31,1,0,0,0,2,-9,2,1,0,0,3,7.955648248379655,8.027290752603424,0,1,0,-9,5,0,-4,6.734654100196781,0,0,1,0,35,1,3,1,2,2,2019,1,2,9,0,46,48,15,1,0,1,0,7.846844323035908,7.846844323035908,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,35.07,59.68,32.03,59.32,6,1,1,0,0,9.416666666666666,12,5,1,2066.5,-91132.8659496583,0,0,3477.409390457325 -1981,2388,4423,4422,-9,-9,2,1,1,35,1,0,0,0,1,-9,2,1,0,0,3,8.491290883521394,8.176172728172489,0,1,0,-9,5,0,4,52.94112771335972,0,0,0,0,31,2,3,1,-9,-9,2019,1,1,17,5,37,43,15,1,1,1,0,17.94073161594516,17.94073161594516,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,32.03,59.32,35.07,59.68,3,1,1,0,0,3.75,12,5,1,2066.5,-91132.8659496583,0,0,3477.409390457325 -1982,2389,4424,-9,-9,-9,1,1,1,55,2,0,0,0,2,-9,2,1,0,0,3,9.747839945085497,9.577028156137651,0,3,0,0,0,-9,0,-1016.068940140743,0,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,7,0,45,57,15,1,0,-9,0,36.04807778081068,36.04807778081068,0,0,0,0,0,0,0,7,0,0,0,6.653532978593266,0,6.713021125716622,3,41.89,50.72,-9,-9,5,1,1,0,0,9.666666666666666,9,5,1,777,734977.6051565242,0,0,7568.749083977095 -1983,2390,4425,4426,-9,-9,1,1,1,68,1,0,0,0,2,-9,4,3,0,0,5,0,6.398041481359798,5.993635310540373,1,0,-9,44,0,1,64.11952686622737,0,0,0,0,67,3,4,1,2,3,2019,3,2,6,0,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.601341893266534,6.226981088626614,0,0,62.39,56.71,55.34,46.23,7,1,1,0,0,5.416666666666667,5,2,1,626.5,23161.62834234413,0,0,2496.473409081079 -1983,2390,4426,4425,-9,-9,2,1,0,67,1,0,0,0,3,-9,2,1,0,0,4,7.411368727482262,7.485114727867405,0,1,0,-9,44,0,-1,-39.00117271264955,0,0,0,0,68,2,5,3,3,3,2019,2,1,8,0,23,0,15,1,0,4,0,6.91095567533778,6.91095567533778,0,0,0,0,0,0,0,0,1,1,0,4.271326790172219,0,0,0,55.34,46.23,62.39,56.71,6,1,1,0,0,3,5,2,1,626.5,23161.62834234413,0,0,2496.473409081079 -1984,2391,4427,-9,4428,4431,6,1,1,5,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1063.822025828712,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46,61,-9,-9,5,3,4,0,0,0,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1984,2391,4428,4431,-9,-9,2,1,0,42,1,0,4,0,1,-9,2,1,0,0,4,8.296944549423104,8.403988367008999,0,2,0,-9,23,0,-11,.9561250508719725,0,0,1,0,53,1,4,1,2,2,2019,1,1,9,0,25,20,15,1,0,1,0,23.05356314677143,23.05356314677143,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.24,58.84,57.16,56.15,6,3,4,0,0,6.833333333333333,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1984,2391,4429,-9,4428,4431,5,1,0,10,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-944.9847867106961,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45,60,-9,-9,5,3,4,0,0,0,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1984,2391,4430,-9,4428,4431,3,1,0,15,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-909.192205500904,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45,59,-9,-9,5,3,4,0,0,0,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1984,2391,4431,4428,-9,-9,1,1,1,53,1,0,4,0,1,-9,2,1,0,0,4,9.887761581795145,9.74761652488254,0,2,0,-9,21,0,11,-1.383007856687264,0,0,0,0,42,1,4,1,3,3,2019,1,2,8,0,60,60,15,1,0,1,0,27.78156841114137,27.78156841114137,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,51.24,58.84,6,3,4,0,0,7.166666666666667,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1984,2391,4432,-9,4428,4431,4,1,1,13,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1167.003052308567,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47,60,-9,-9,5,3,4,0,0,0,9,5,1,415.5,2770336.857127396,0,0,6305.425560651289 -1985,2392,4433,-9,-9,-9,1,1,1,50,2,0,0,0,1,-9,1,1,0,0,3,9.69253507740337,9.6810462989939,0,3,0,0,0,-9,0,-917.6975595891772,0,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,7,0,50,50,15,1,0,-9,0,39.7339176495997,39.7339176495997,0,0,0,0,0,0,0,0,1,1,0,5.433765456821336,0,0,0,57.9,51.84,-9,-9,6,1,1,0,0,6.833333333333333,10,5,1,1631,823368.4843727314,0,0,8520.752112242695 -1986,2393,4434,-9,-9,-9,1,1,1,76,2,0,0,0,2,-9,4,3,0,0,3,0,6.682134680182044,6.672511168788025,3,0,0,0,-9,0,-1009.951563048696,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.724739035906175,6.587625370606151,0,0,48.24,35.69,-9,-9,4,1,1,0,0,0,2,2,1,814,136767.9049100204,0,0,752.9063335180057 -1987,2394,4435,4436,-9,-9,2,1,0,41,1,0,2,0,1,-9,2,1,0,0,4,8.652988410855317,8.609914498764317,0,2,0,-9,2,0,-2,-27.87936510557662,0,0,1,0,43,1,4,1,1,1,2019,1,1,12,0,30,30,15,1,0,1,0,20.02556076514832,20.02556076514832,0,0,0,0,0,0,0,0,1,1,0,2.495474572183732,0,0,0,41.59,61.77,46.9,56.66,6,1,1,0,0,11.91666666666667,7,5,1,724.75,1096843.646798641,0,0,3942.917822783034 -1987,2394,4436,4435,-9,-9,1,1,1,43,1,0,2,0,1,-9,2,1,0,0,4,8.615020386551205,8.873971717957394,0,2,0,-9,2,0,2,74.33865189619526,0,0,0,0,41,1,4,1,2,3,2019,1,2,19,7,40,40,15,1,1,1,0,18.54605215156927,18.54605215156927,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.9,56.66,41.59,61.77,4,1,1,0,0,11.91666666666667,7,5,1,724.75,1096843.646798641,0,0,3942.917822783034 -1987,2394,4437,-9,4435,4436,4,1,0,5,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1032.556290852557,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,61,-9,-9,5,1,1,0,0,0,7,5,1,724.75,1096843.646798641,0,0,3942.917822783034 -1987,2394,4438,-9,4435,4436,3,1,1,8,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1030.556324887914,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,7,5,1,724.75,1096843.646798641,0,0,3942.917822783034 -1988,2395,4439,4440,-9,-9,3,1,0,24,1,0,0,0,2,-9,2,1,0,0,4,7.945179962209234,8.119708934907944,0,1,0,1,1,-9,3,90.48796201307329,-9,1,1,0,21,2,4,2,2,2,2019,2,6,8,1,38,0,15,1,0,2,0,10.08354459506945,10.08354459506945,0,0,0,0,0,0,0,0,0,0,0,.7378809336921782,0,0,0,46.98,59.35,48,58,6,4,2,0,0,8,8,3,0,275.5,201100.8696345942,0,0,1534.76596106694 -1988,2395,4440,4439,-9,-9,6,1,1,21,1,0,0,1,2,-9,7,2,0,0,4,0,0,0,1,0,-9,1,-9,-3,-46.41671510540118,-9,1,0,0,24,2,4,1,-9,-9,2019,3,3,11,2,0,0,15,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48,58,46.98,59.35,5,1,1,0,0,0,8,3,0,275.5,201100.8696345942,0,0,1534.76596106694 -1989,2396,4441,-9,4442,-9,3,1,1,9,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-938.7477110078702,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,60,-9,-9,5,1,1,0,0,0,2,1,0,481.5,-121856.9326434228,0,0,2574.112287449405 -1989,2396,4442,-9,-9,-9,1,1,0,42,2,0,3,0,3,-9,8,3,1,1,1,0,0,0,4,0,-9,0,-9,0,-898.6355304298158,-9,0,1,0,-9,-9,-9,-9,3,2,2019,-9,0,22,6,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,38.89,16.13,-9,-9,4,1,1,0,1,0,2,1,0,481.5,-121856.9326434228,0,0,2574.112287449405 -1989,2396,4443,-9,4442,-9,2,1,1,16,2,0,3,1,2,-9,7,2,0,0,3,0,0,0,4,0,-9,0,-9,0,-856.1603918730641,-9,1,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,10,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,0,0,0,3,55.51,51.57,-9,-9,7,1,1,0,0,0,2,1,0,481.5,-121856.9326434228,0,0,2574.112287449405 -1989,2396,4444,-9,4442,-9,4,1,1,14,2,0,3,1,3,-9,-9,2,0,0,3,0,0,0,4,0,-9,0,-9,0,-1024.566898545497,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,55,-9,-9,5,1,1,0,0,0,2,1,0,481.5,-121856.9326434228,0,0,2574.112287449405 -1990,2397,4445,-9,-9,-9,1,1,0,55,2,0,0,0,2,-9,2,1,0,0,5,8.133676403940751,8.154155961996315,0,3,0,-9,0,-9,0,-945.1352662551712,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,7,0,37,0,15,1,0,-9,0,8.645170531944855,8.645170531944855,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.63,56.14,-9,-9,5,1,1,0,0,5.583333333333333,10,4,0,202,791790.7792042171,0,0,1843.664715990349 -1991,2398,4446,-9,-9,-9,1,1,1,81,2,0,0,0,3,-9,4,3,0,0,3,0,5.136506785031977,5.106377936121231,3,0,0,0,-9,0,-1071.491771293814,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,5.437004867118202,0,0,45.72,34.28,-9,-9,6,1,1,0,0,0,2,2,0,708,247778.1303522297,0,0,311.6478001749774 -1992,2399,4447,-9,4448,-9,3,1,0,3,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-974.5785969367718,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,11,2,0,763,23769.46573568117,0,0,1251.752401449412 -1992,2399,4448,-9,-9,-9,1,1,0,34,2,0,2,0,2,-9,2,1,0,0,4,5.916398899024567,5.861982971335521,0,4,0,0,0,-9,0,-954.4664746351382,0,0,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,11,0,12,0,15,1,0,-9,0,4.23235044810729,4.23235044810729,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.88,53.01,-9,-9,4,1,1,0,0,4.666666666666667,11,2,0,763,23769.46573568117,0,0,1251.752401449412 -1992,2399,4449,-9,4448,-9,2,1,1,8,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1027.947853172629,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,11,2,0,763,23769.46573568117,0,0,1251.752401449412 -1993,2400,4450,-9,4451,4452,4,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-987.8034495376344,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,9,4,1,566,538421.1047297956,0,0,3438.771277944742 -1993,2400,4451,4452,-9,-9,2,1,0,45,1,0,2,0,2,-9,6,3,0,0,4,0,0,0,2,0,-9,16,0,2,-82.38847574475683,0,0,0,0,43,1,3,1,2,2,2019,3,1,9,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1.721997691620796,0,0,0,48.87,58.55,35.32,58.41,5,1,1,0,0,0,9,4,1,566,538421.1047297956,0,0,3438.771277944742 -1993,2400,4452,4451,-9,-9,1,1,1,43,1,0,2,0,1,-9,2,1,0,0,3,9.014521675953251,9.093017362961275,0,2,0,-9,15,0,-2,53.42630952489866,0,0,0,0,45,2,4,3,3,3,2019,2,2,12,1,43,42,15,1,0,3,0,19.75999434231628,19.75999434231628,0,0,0,0,0,0,0,0,1,1,0,3.940942882342314,0,0,0,35.32,58.41,48.87,58.55,5,1,1,0,0,11.5,9,4,1,566,538421.1047297956,0,0,3438.771277944742 -1993,2400,4453,-9,4451,4452,3,1,0,12,2,0,2,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1053.149377721013,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,62,-9,-9,5,1,1,0,0,0,9,4,1,566,538421.1047297956,0,0,3438.771277944742 -1994,2401,4454,4456,-9,-9,1,1,0,42,1,0,1,0,1,-9,2,1,0,0,4,8.610979936925057,8.877740115250694,0,2,0,-9,5,0,1,-33.49130480310566,0,0,1,0,41,1,4,1,1,2,2019,1,2,12,0,38,37,15,1,0,1,0,24.09971573996721,24.09971573996721,0,0,0,0,0,0,0,0,0,0,0,1.612520392777643,0,0,0,53.81,53.56,51.83,57.2,6,1,1,0,0,12.75,6,5,1,442,368270.2853719132,0,0,6095.353319395207 -1994,2401,4455,-9,-9,4456,3,1,0,10,2,0,1,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-977.2098452539346,-9,0,0,0,-9,-9,-9,-9,-9,1,2019,-9,0,14,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41,55,-9,-9,5,1,1,0,0,0,6,5,1,442,368270.2853719132,0,0,6095.353319395207 -1994,2401,4456,4454,-9,-9,2,1,1,41,1,0,1,0,1,-9,2,1,0,0,4,9.543807227671698,9.610559054007565,0,2,0,-9,5,0,-1,51.81648610703901,0,0,0,0,42,1,4,1,-9,-9,2019,1,1,9,2,52,52,15,1,0,1,0,30.51109030622851,30.51109030622851,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.83,57.2,53.81,53.56,6,1,1,0,0,5.25,6,5,1,442,368270.2853719132,0,0,6095.353319395207 -1995,2402,4457,4458,-9,-9,2,1,1,82,1,0,0,0,3,-9,4,3,0,1,2,0,4.75675690047715,4.34097517929462,1,0,-9,44,0,15,-78.10131206228047,0,0,0,0,67,2,2,3,-9,-9,2019,4,1,11,1,0,0,15,4,0,4,0,0,0,1,0,72.51486759466951,0,0,0,0,0,1,1,0,4.322188723148886,4.645274852249309,0,0,46.3,29.03,62.81,30.81,3,4,2,0,0,9.25,9,3,1,687.5,703752.2497916413,0,0,2662.958122224051 -1995,2402,4458,4457,-9,-9,1,1,0,67,1,0,0,0,2,-9,4,3,0,0,2,0,7.919482025853298,7.764126448732619,1,0,-9,44,0,-15,135.2245854115827,0,0,0,0,82,3,2,3,-9,-9,2019,4,2,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.788972207757454,0,1,62.81,30.81,46.3,29.03,6,3,4,0,0,6.333333333333333,9,3,1,687.5,703752.2497916413,0,0,2662.958122224051 -1996,2403,4459,-9,4460,-9,2,1,1,7,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-870.2327123448608,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,1,2,0,690.6666666666666,19415.39373361284,0,0,1925.888869309852 -1996,2403,4460,-9,-9,-9,1,1,0,29,2,1,2,0,2,-9,2,1,0,0,4,7.156333530249599,7.270212397866243,5.000109438463945,4,0,0,0,-9,0,-1011.26709845649,0,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,11,2,16,16,15,1,0,-9,0,8.651307194660006,8.651307194660006,0,0,0,0,0,0,0,0,1,1,0,4.402973408350592,0,0,0,49.92,46.05,-9,-9,6,1,1,0,0,10.83333333333333,1,2,0,690.6666666666666,19415.39373361284,0,0,1925.888869309852 -1996,2403,4461,-9,4460,-9,3,1,0,1,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1037.826857743038,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,1,2,0,690.6666666666666,19415.39373361284,0,0,1925.888869309852 -1997,2404,4462,-9,-9,-9,1,1,0,40,2,0,1,0,2,-9,3,3,0,0,2,0,5.357792324439608,5.276093660546663,4,0,0,0,-9,0,-1064.337692243859,0,0,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,31,12,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.181611652165213,0,0,0,23.34,32.7,-9,-9,1,3,4,1,1,1.416666666666667,2,2,0,1033.5,59193.01427230432,0,0,1432.450689065901 -1997,2404,4463,-9,4462,-9,2,1,1,13,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-976.4379527096984,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,3,4,0,0,0,2,2,0,1033.5,59193.01427230432,0,0,1432.450689065901 -1998,2405,4464,-9,-9,-9,1,1,0,79,2,0,0,0,3,-9,4,3,0,0,2,0,7.138989738951579,7.254351610468927,3,0,-9,0,1,0,-1068.165543765505,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,2,0,0,15,4,0,-9,0,0,0,1,3.469259431928748,0,0,0,0,0,0,1,1,0,7.841282657519975,6.860413076269509,0,0,49.8,35.57,-9,-9,6,1,1,0,0,0,7,3,1,497,-163750.1192407511,0,0,1063.109328223306 -1999,2406,4465,-9,-9,-9,1,1,0,79,2,0,0,0,3,-9,4,3,0,1,2,0,2.843897209240538,2.9969693400226,3,0,0,0,-9,0,-1041.373092006594,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,14,2,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.379142622155462,2.959392993678291,0,0,37.26,26.17,-9,-9,5,1,1,0,0,0,5,1,1,358,-83056.9870475225,0,0,1727.77263135565 -2000,2407,4466,-9,-9,-9,1,1,0,50,2,0,0,0,2,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-1130.660741664622,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,23,9,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,26.98,27.16,-9,-9,4,1,1,0,1,0,13,1,0,208,-64842.89749289765,0,0,319.1686328921527 -2000,2408,4467,-9,4466,-9,2,1,1,23,2,0,0,0,2,-9,3,3,0,0,3,0,0,0,3,0,0,0,-9,0,-911.2082873234043,0,1,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,13,1,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47.46,52.7,-9,-9,3,1,1,1,1,.5,13,1,0,276,173974.8726391614,0,0,0 -2001,2409,4468,-9,-9,-9,1,1,1,25,2,0,0,0,1,-9,2,1,0,0,4,7.615800818426463,7.710488929091341,0,3,0,0,0,-9,0,-971.9326838556811,0,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,0,28,30,15,1,0,-9,0,6.802326582572944,6.802326582572944,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.76,52.64,-9,-9,6,1,1,0,0,7.5,6,3,0,321,-147248.8302873544,0,0,1494.231704028013 -2002,2410,4469,-9,-9,-9,1,1,0,50,2,0,0,0,2,-9,8,3,1,1,2,0,0,0,3,0,0,0,-9,0,-898.4597565240795,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.66,29.1,-9,-9,4,1,1,0,0,0,13,1,1,1116,148968.2069186595,0,0,1340.895579093803 -2003,2411,4470,-9,-9,-9,1,1,0,50,2,0,0,0,1,-9,2,1,0,0,4,9.701602118941617,9.613340759971841,0,3,0,0,0,-9,0,-905.579136681594,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,7,0,16,35,15,1,0,-9,0,112.8744920467364,112.8744920467364,0,0,0,0,0,0,0,0,0,0,0,3.74030542310811,0,0,0,52.31,58.29,-9,-9,6,1,1,0,0,10.08333333333333,7,5,1,122,1827293.240966614,0,0,6016.202455796767 -2004,2412,4471,4472,-9,-9,2,1,0,49,1,0,0,0,1,-9,1,1,0,0,3,8.038014427652866,8.183049198544074,0,1,0,-9,27,0,-2,17.28651226407966,0,0,0,0,51,1,4,1,3,3,2019,1,1,6,0,30,28,15,1,0,1,0,13.18047420850541,13.18047420850541,0,0,0,0,0,0,0,2,0,0,0,0,0,0,3,61.88,39,57.16,56.15,6,1,1,0,0,10.91666666666667,10,5,1,280.5,851686.1979104653,0,0,5660.332105412128 -2004,2412,4472,4471,-9,-9,1,1,1,51,1,0,0,0,1,-9,2,1,0,0,4,9.957995957345339,9.997096127177242,0,1,0,-9,27,0,2,61.35152118395413,0,0,0,0,49,1,3,1,2,2,2019,1,2,11,3,55,50,15,1,0,1,0,32.7254077202205,32.7254077202205,0,0,0,0,0,0,0,0,0,0,0,.852590457668979,0,0,0,57.16,56.15,61.88,39,6,1,1,0,0,10.91666666666667,10,5,1,280.5,851686.1979104653,0,0,5660.332105412128 -2005,2413,4473,4474,-9,-9,1,1,0,38,1,0,0,0,1,-9,2,1,0,0,3,8.728630202277168,8.389928819006366,0,1,0,-9,2,0,-4,130.7018349310614,0,0,1,0,42,1,4,1,2,2,2019,1,2,5,1,40,39,15,1,0,1,0,13.08901482965601,13.08901482965601,0,0,0,0,0,0,0,0,0,0,0,.8489876646238252,0,0,0,41.2,52.67,47.83,54.78,7,1,1,0,0,10.25,11,5,1,665,367205.9467387556,0,0,3265.810097952017 -2005,2413,4474,4473,-9,-9,2,1,1,42,1,0,0,0,1,-9,2,1,0,0,4,8.019558995864347,8.01527173020011,0,1,0,-9,2,0,4,99.33308439992115,0,0,0,0,38,1,3,1,-9,-9,2019,1,1,11,1,40,39,15,1,0,1,0,11.36556589809462,11.36556589809462,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47.83,54.78,41.2,52.67,5,1,1,0,0,5.166666666666667,11,5,1,665,367205.9467387556,0,0,3265.810097952017 -2006,2414,4475,-9,4476,-9,4,1,0,4,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-970.1578780976156,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,3,4,0,0,0,6,1,0,1324,-96864.46663091995,0,0,1632.504932427443 -2006,2414,4476,-9,-9,-9,1,1,0,33,2,1,4,0,3,-9,6,3,0,0,4,0,0,0,4,0,0,0,-9,0,-1055.015776191525,0,0,1,1,-9,-9,-9,-9,-9,-9,2019,-9,0,11,2,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48,56,-9,-9,5,3,4,0,0,0,6,1,0,1324,-96864.46663091995,0,0,1632.504932427443 -2006,2414,4477,-9,4476,-9,5,1,1,0,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1083.360386871767,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,3,4,0,0,0,6,1,0,1324,-96864.46663091995,0,0,1632.504932427443 -2006,2414,4478,-9,4476,-9,3,1,0,9,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1087.359121905157,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,3,4,0,0,0,6,1,0,1324,-96864.46663091995,0,0,1632.504932427443 -2007,2415,4479,-9,-9,-9,1,1,1,46,2,0,0,0,3,-9,1,1,0,0,4,7.3243532530611,7.264322964675964,0,3,0,0,0,-9,0,-1011.692473154861,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,4,1,40,30,15,1,0,-9,0,4.306117797020354,4.306117797020354,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,-9,-9,6,3,4,0,1,3,8,3,0,513,0,0,0,1014.628797222199 -2008,2416,4480,4481,-9,-9,2,1,0,68,1,0,0,0,3,-9,4,3,0,0,5,0,4.388082375043018,4.481991074049484,1,0,-9,51,0,-2,35.22702360944157,0,0,0,0,70,3,4,3,-9,-9,2019,4,1,9,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.547985097975004,4.24650766184711,0,0,46.13,57.2,58.15,52.91,7,1,1,0,0,0,1,2,1,494.5,1785357.484832858,0,0,2013.328678507514 -2008,2416,4481,4480,-9,-9,1,1,1,70,1,0,0,0,3,-9,4,3,0,0,4,0,7.436728733471822,7.561872781160745,1,0,-9,51,0,2,63.04916754029256,0,0,0,0,68,3,5,3,3,3,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.443051669807669,7.43580833180192,0,0,58.15,52.91,46.13,57.2,6,1,1,0,0,4.5,1,2,1,494.5,1785357.484832858,0,0,2013.328678507514 -2009,2417,4482,4483,-9,-9,1,1,0,84,1,0,0,0,2,-9,4,3,0,1,1,0,6.755249467267005,6.55297240681491,1,0,-9,63,0,0,19.31320346139194,0,0,0,0,84,3,2,3,-9,-9,2019,4,2,15,3,0,0,15,4,0,4,0,0,0,1,0,28.06619502744778,0,4.228452375814683,0,0,0,1,1,0,0,6.647319855387812,0,0,24.93,19.95,43.03,26.89,4,1,1,0,0,0,9,2,1,748.5,538757.0590735485,0,0,1998.437900635896 -2009,2417,4483,4482,-9,-9,2,1,1,84,1,0,0,0,3,-9,4,3,0,0,2,0,4.097919271169173,3.90137926878725,1,0,-9,8,0,0,24.96739539046511,0,0,0,0,84,2,1,3,-9,-9,2019,4,1,13,2,0,0,15,4,0,4,0,0,0,1,0,17.08534980498159,1.035426425793087,.6967109737825163,0,0,120,1,1,0,4.121069086878713,3.985762332828865,124.8043771072764,1,43.03,26.89,24.93,19.95,4,1,1,0,0,0,9,2,1,748.5,538757.0590735485,0,0,1998.437900635896 -2010,2418,4484,4485,-9,-9,1,1,1,43,1,0,0,0,1,-9,2,1,0,0,4,8.268983181497749,8.591477309068248,0,1,0,-9,10,0,-3,144.1380695254313,0,0,0,0,46,1,2,1,3,2,2019,1,2,8,0,37,77,15,1,0,1,0,15.12145039674132,15.12145039674132,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,33.93,33.3,6,1,1,0,0,9.75,10,5,1,505.5,-40327.98578321976,0,0,4830.377764372952 -2010,2418,4485,4484,-9,-9,2,1,0,46,1,0,0,0,1,-9,2,1,0,0,2,8.376498472356904,8.696638625593424,5.925577631923163,1,0,-9,10,0,3,-16.66770038079466,0,0,0,0,43,1,4,1,3,2,2019,1,1,22,8,40,35,15,1,1,1,0,17.0895375863592,17.0895375863592,0,0,0,0,0,0,0,2,0,0,0,6.499098697495679,0,3.995009679971867,3,33.93,33.3,57.16,56.15,4,1,1,0,0,11.16666666666667,10,5,1,505.5,-40327.98578321976,0,0,4830.377764372952 -2011,2419,4486,-9,-9,-9,1,1,1,78,2,0,0,0,3,-9,4,3,0,0,4,0,7.072055838205787,6.836837226327595,3,0,0,0,-9,0,-924.7819087613221,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.190329055947747,0,0,54.79,55.86,-9,-9,6,1,1,0,0,7.083333333333333,1,2,0,361,-24755.01093661285,0,0,1364.901265796218 -2012,2420,4487,-9,-9,-9,1,1,0,81,2,0,0,0,2,-9,4,3,0,0,3,0,7.835273190438647,7.622063898608646,3,0,0,0,-9,0,-889.2326463757348,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,4,0,-9,0,0,0,1,0,0,0,2.862260092447389,0,0,0,1,1,0,1.057676396014576,8.124040008822636,0,0,46.54,40.46,-9,-9,4,1,1,0,0,0,8,3,1,2819,869410.0423354394,0,0,1627.280404955099 -2013,2421,4488,-9,-9,-9,1,1,0,41,2,0,1,0,2,-9,2,1,0,0,4,8.3795613777115,8.774179897653688,0,4,0,0,0,-9,0,-1032.567054285805,0,0,1,0,-9,-9,-9,-9,3,3,2019,-9,0,7,0,50,48,15,1,0,-9,0,9.042567397094626,9.042567397094626,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,60.12,54.8,-9,-9,5,3,4,0,0,8.333333333333334,7,4,0,621,38731.74356003928,0,0,2244.850286441241 -2014,2422,4489,4491,-9,-9,1,1,1,48,1,0,2,0,2,-9,2,1,0,0,5,9.563998199254961,9.61083897157301,0,2,0,-9,17,0,0,91.45673978315394,0,0,0,0,48,2,5,1,2,2,2019,1,4,14,2,50,50,15,1,0,1,0,29.98475464458924,29.98475464458924,0,0,0,0,0,0,0,0,0,0,0,.6896176243484029,0,0,0,48.18,61.8,43.44,61.22,4,1,1,0,1,9.083333333333334,8,5,0,266.75,344656.6728455926,0,0,6277.107990819508 -2014,2422,4490,-9,4491,4489,3,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1098.015656506432,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44,60,-9,-9,5,4,2,0,0,0,8,5,0,266.75,344656.6728455926,0,0,6277.107990819508 -2014,2422,4491,4489,-9,-9,4,1,0,48,1,0,2,0,2,-9,2,1,0,0,5,8.488382236197141,8.456713769444349,0,2,0,-9,17,0,0,32.1324497512919,0,0,0,0,48,2,5,1,2,2,2019,1,1,16,5,38,37,15,1,1,1,0,13.64292631721111,13.64292631721111,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,43.44,61.22,48.18,61.8,5,2,3,0,0,3,8,5,0,266.75,344656.6728455926,0,0,6277.107990819508 -2014,2422,4492,-9,4491,4489,2,1,1,14,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1050.444052857597,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44,55,-9,-9,5,4,2,0,0,0,8,5,0,266.75,344656.6728455926,0,0,6277.107990819508 -2015,2423,4493,4494,-9,-9,2,1,0,68,1,0,0,0,3,-9,4,3,0,0,4,0,7.161474181065192,7.162983463206505,1,0,-9,51,0,-3,-157.6251372063188,0,0,0,0,71,2,1,3,3,2,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,2,1,1,0,2.573497050069063,7.007660875961827,0,1,54.2,57.49,58.25,22.01,6,1,1,0,0,3.333333333333333,8,4,1,657.5,1572584.060551663,0,0,3076.019604284716 -2015,2423,4494,4493,-9,-9,1,1,1,71,1,0,0,0,2,-9,4,3,0,0,1,0,8.14957080559466,8.006485888243951,1,0,-9,51,0,3,6.612369452324854,0,0,0,0,68,3,4,3,3,3,2019,4,2,10,0,0,0,15,4,0,4,0,0,0,1,124.3466229669124,129.5458604733482,0,0,0,1168.317620636699,0,1,1,0,1.784745870767579,7.852048629669958,0,0,58.25,22.01,54.2,57.49,3,1,1,0,0,0,8,4,1,657.5,1572584.060551663,0,0,3076.019604284716 -2016,2424,4495,-9,4497,4496,4,1,1,13,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-955.763979137704,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,60,-9,-9,5,1,1,0,0,0,2,3,1,547,119866.9580187394,0,0,3205.812949578173 -2016,2424,4496,4497,-9,-9,2,1,1,50,1,0,2,0,2,-9,1,1,0,0,3,7.998602397060862,7.651927860556495,0,2,0,-9,8,0,7,-109.5150056025148,0,0,0,0,43,2,3,1,-9,-9,2019,1,1,9,0,30,50,15,1,0,1,0,7.845499054793282,7.845499054793282,0,0,0,0,0,0,0,0,1,1,0,6.942129033306191,0,0,0,48.14,53.42,51.94,55.88,4,1,1,0,0,11.33333333333333,2,3,1,547,119866.9580187394,0,0,3205.812949578173 -2016,2424,4497,4496,-9,-9,1,1,0,43,1,0,2,0,2,-9,2,1,0,0,3,7.825225869434071,7.564149966374266,0,2,0,-9,18,0,-7,-23.60644255632904,0,0,1,0,50,2,3,1,-9,-9,2019,1,2,8,0,32,33,15,1,0,1,0,8.223893077908487,8.223893077908487,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.94,55.88,48.14,53.42,5,1,1,0,0,12.25,2,3,1,547,119866.9580187394,0,0,3205.812949578173 -2016,2424,4498,-9,4497,4496,3,1,1,16,2,0,2,1,3,-9,7,2,0,0,4,5.509539241004665,5.29355442908734,0,2,0,0,0,-9,0,-1145.812400472213,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,0,4,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,6,1,1,0,0,.5833333333333334,2,3,1,547,119866.9580187394,0,0,3205.812949578173 -2017,2425,4499,-9,-9,-9,1,1,0,48,2,0,0,0,3,-9,2,1,0,0,4,7.627596583291673,7.567631543274353,0,3,0,0,0,-9,0,-961.9356530523606,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,32,33,15,1,0,-9,0,8.178856016428687,8.178856016428687,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.49,55.09,-9,-9,7,1,1,0,0,6.25,13,3,0,435,185965.1824531551,0,0,614.8960471061453 -2018,2426,4500,4501,-9,-9,1,1,1,59,1,0,0,0,1,-9,4,3,0,0,2,0,0,0,1,0,-9,9,0,-11,0,0,0,0,0,70,1,2,3,-9,-9,2019,4,2,13,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,34.54,31.77,40.99,54.49,2,1,1,0,0,0,10,1,0,1009.5,901827.6586886662,0,0,1318.148903307453 -2018,2426,4501,4500,-9,-9,2,1,0,70,1,0,0,0,1,-9,4,3,0,0,2,0,0,0,1,0,-9,9,0,11,0,0,0,0,0,59,1,2,3,3,2,2019,4,1,11,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.99,54.49,34.54,31.77,4,1,1,0,0,0,10,1,0,1009.5,901827.6586886662,0,0,1318.148903307453 -2019,2427,4502,-9,4503,-9,3,1,0,0,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-989.6030950373956,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,61,-9,-9,5,1,1,0,0,0,13,2,0,931.3333333333334,-45667.26668311484,0,0,2003.63177951438 -2019,2427,4503,-9,-9,-9,1,1,0,27,2,1,2,0,2,-9,2,1,0,0,4,6.673013539308592,7.226918833739043,0,4,0,0,0,-9,0,-1023.540491527768,0,1,1,1,-9,-9,-9,-9,-9,-9,2019,-9,0,7,0,16,16,15,1,0,-9,0,8.117739212182375,8.117739212182375,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,58.47,47.36,-9,-9,7,1,1,0,0,8.833333333333334,13,2,0,931.3333333333334,-45667.26668311484,0,0,2003.63177951438 -2019,2427,4504,-9,4503,-9,2,1,0,6,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1055.634518260416,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,13,2,0,931.3333333333334,-45667.26668311484,0,0,2003.63177951438 -2020,2428,4505,4506,-9,-9,2,1,1,76,1,0,0,0,3,-9,4,3,0,0,3,0,6.171313897589355,6.08831680263541,1,0,-9,57,0,2,-34.78330700359597,0,0,0,0,74,3,3,3,3,3,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,6.269810735906912,0,0,60.29,52.11,63.83,43.62,7,1,1,0,0,0,4,2,1,546,412481.8246344342,0,0,645.5352010820739 -2020,2428,4506,4505,-9,-9,1,1,0,74,1,0,0,0,3,-9,4,3,0,0,3,0,5.273666358851638,5.538920375093996,1,0,-9,57,0,-2,-80.01656018780093,0,0,0,0,76,3,3,3,3,-9,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,1,0,8.49216962720056,0,0,0,0,0,1,1,0,0,5.130632176724175,0,0,63.83,43.62,60.29,52.11,7,1,1,0,0,0,4,2,1,546,412481.8246344342,0,0,645.5352010820739 -2021,2429,4507,-9,-9,-9,1,1,1,63,2,0,0,0,2,-9,2,1,0,0,4,8.950981414239754,9.345143631493169,7.172912118424529,3,0,0,0,-9,0,-1208.157522390465,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,7,0,40,40,15,1,0,-9,0,23.6697710523166,23.6697710523166,0,0,0,0,0,0,0,0,0,0,0,6.295641185782566,7.900776941073102,0,0,58.15,52.91,-9,-9,6,1,1,0,0,7.833333333333333,7,5,0,776,805239.9702197441,0,0,3313.172010744298 -2022,2430,4508,4509,-9,-9,2,1,0,58,1,0,0,0,1,-9,10,3,0,1,2,0,0,0,1,0,-9,8,0,-7,-39.67159457398206,0,0,0,0,65,2,3,1,-9,-9,2019,3,1,16,4,0,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,7,1,1,0,4.887624538727543,0,6.926604048849947,3,31.68,51.99,57.33,53.46,4,1,1,0,0,5.083333333333333,4,3,0,460,91574.48021996187,0,0,2139.716916106192 -2022,2430,4509,4508,-9,-9,1,1,1,65,1,0,0,0,2,-9,1,1,0,0,3,7.694957351471057,7.708236809787971,0,1,0,-9,8,0,7,137.4381759358942,0,0,0,0,58,1,2,3,3,3,2019,2,2,6,0,25,30,15,1,0,3,0,10.30768624883957,10.30768624883957,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.33,53.46,31.68,51.99,2,1,1,0,0,9.583333333333334,4,3,0,460,91574.48021996187,0,0,2139.716916106192 -2023,2431,4510,4512,-9,-9,1,1,0,44,1,0,2,0,1,-9,2,1,0,0,5,8.930804429736083,8.921059605309765,0,2,0,-9,19,0,0,-53.1516441669492,0,0,1,0,44,2,5,1,2,3,2019,1,2,9,0,32,30,15,1,0,1,0,26.6416519869681,26.6416519869681,0,0,0,0,0,0,0,0,1,1,0,2.644151020295227,0,0,0,51.14,60.45,46.06,60.24,7,1,1,0,0,11.5,9,5,1,795.5,351283.1767814848,0,0,4449.559090840381 -2023,2431,4511,-9,4510,4512,3,1,1,14,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-919.4981094489655,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,9,5,1,795.5,351283.1767814848,0,0,4449.559090840381 -2023,2431,4512,4510,-9,-9,2,1,1,44,1,0,2,0,2,-9,2,1,0,0,5,8.798436919726777,8.836966425515092,0,2,0,-9,19,0,0,205.8059265156351,0,0,0,0,44,1,5,1,2,2,2019,1,1,12,3,44,42,15,1,0,1,0,25.81411423217733,25.81411423217733,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.06,60.24,51.14,60.45,6,1,1,0,0,11.5,9,5,1,795.5,351283.1767814848,0,0,4449.559090840381 -2023,2431,4513,-9,4510,4512,4,1,0,11,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-997.0355698144631,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,9,5,1,795.5,351283.1767814848,0,0,4449.559090840381 -2024,2432,4514,4517,-9,-9,1,1,1,35,1,1,2,0,2,0,7,2,0,0,2,0,0,0,2,0,-9,6,0,0,-61.83294208929325,-9,0,0,0,35,1,3,1,2,2,2019,3,2,9,2,0,0,15,2,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.63,43.7,33.02,58.91,5,1,1,0,0,1.25,2,4,1,1647.5,71747.948436126,0,0,4216.048081931534 -2024,2432,4515,-9,4517,4514,4,1,1,2,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1173.969344837615,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,2,4,1,1647.5,71747.948436126,0,0,4216.048081931534 -2024,2432,4516,-9,4517,4514,3,1,1,6,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-932.6688822535282,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,2,4,1,1647.5,71747.948436126,0,0,4216.048081931534 -2024,2432,4517,4514,-9,-9,2,1,0,35,1,1,2,0,1,-9,2,1,0,0,3,9.09722133142631,9.160272408864641,0,2,0,-9,6,0,0,5.580021774334893,0,0,1,0,35,2,2,2,2,2,2019,2,1,14,3,40,0,15,1,0,2,0,24.87447757237596,24.87447757237596,0,0,0,0,0,0,0,0,1,1,0,7.31975329742656,0,0,0,33.02,58.91,49.63,43.7,4,1,1,0,0,6.333333333333333,2,4,1,1647.5,71747.948436126,0,0,4216.048081931534 -2025,2433,4518,-9,-9,-9,1,1,0,73,2,0,0,0,2,-9,4,3,0,0,4,0,7.035773062389194,7.043686273256142,3,0,0,0,-9,0,-1039.007129360911,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.482105144571235,6.756455604120246,0,0,54.2,57.49,-9,-9,6,1,1,0,0,7.75,12,2,1,801,104570.9093502005,0,0,1517.302159686093 -2026,2434,4519,4520,-9,-9,2,1,1,35,1,0,0,0,1,-9,2,1,0,0,5,8.984731181680305,9.033889442281961,0,1,0,-9,1,-9,4,38.98909831097149,-9,0,0,0,31,1,4,1,-9,-9,2019,1,1,11,0,40,0,15,1,0,1,0,28.00300681854132,28.00300681854132,0,0,0,0,0,0,0,0,1,1,0,3.877300647848351,0,0,0,57.06,57.76,56.16,35.1,6,1,1,0,0,3,10,5,1,1415.5,336589.4815977472,0,0,4364.106620201616 -2026,2434,4520,4519,-9,-9,1,1,0,31,1,0,0,0,1,-9,5,1,0,0,4,0,0,0,1,0,-9,1,-9,-4,-21.64105780345846,-9,0,1,0,35,1,5,1,2,1,2019,1,2,5,1,0,0,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,56.16,35.1,57.06,57.76,7,1,1,0,0,7.25,10,5,1,1415.5,336589.4815977472,0,0,4364.106620201616 -2027,2435,4521,4523,-9,-9,2,1,1,46,1,1,1,0,2,-9,2,1,0,0,4,8.056414361897621,8.165037371018274,0,2,0,-9,10,0,10,-177.5459695619062,-9,0,0,1,36,3,3,1,-9,-9,2019,1,1,9,0,36,0,15,1,0,1,0,10.18261921154379,10.18261921154379,0,0,0,0,0,0,0,0,1,1,0,1.644073888469339,0,0,0,48.87,58.55,42.61,49.31,6,1,1,0,0,10.58333333333333,7,3,0,732.3333333333334,244125.6204582924,0,0,1964.293139062634 -2027,2435,4522,-9,4523,4521,3,1,0,2,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-943.5941175693398,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,62,-9,-9,5,1,1,0,0,0,7,3,0,732.3333333333334,244125.6204582924,0,0,1964.293139062634 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-3560,4308,7987,-9,7985,7986,6,1,1,16,2,0,2,1,3,-9,7,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1037.068481459256,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,48.7,56.22,-9,-9,6,1,1,0,1,0,13,2,0,533.25,873897.9801789157,0,0,2073.950553350092 -3560,4309,7988,-9,7985,-9,3,1,1,24,2,0,2,0,2,-9,2,1,0,0,4,7.695404428954796,7.797924104439912,0,3,0,0,0,-9,0,-1211.081990462573,0,1,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,37,40,15,1,0,-9,1,7.974081883487859,7.974081883487859,0,0,0,0,0,0,0,0,1,0,1,1.065443864143742,0,0,0,48,59,-9,-9,5,1,1,0,0,1,13,4,0,1721,-162991.1449653979,0,0,2248.920418601097 -3560,4310,7989,-9,7985,-9,4,1,1,22,2,0,2,0,2,-9,3,3,0,0,2,0,0,0,3,0,0,0,-9,0,-1043.686978807716,0,1,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,0,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,33.55,58.17,-9,-9,5,1,1,1,1,0,13,1,0,1498,-124068.5876852242,0,0,-191.4320460982898 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-4081,4947,9068,-9,9069,-9,2,1,0,12,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1125.637319299532,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,1,1,0,0,0,2,2,0,776.5,-73311.846848805,0,0,1095.455115827961 -4081,4947,9069,-9,-9,-9,1,1,0,37,2,0,1,0,2,-9,2,1,0,0,4,6.739583699657904,6.746132829914184,0,4,0,-9,0,-9,0,-934.2025906152737,-9,0,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,9,1,17,0,15,1,0,-9,0,5.683483942081026,5.683483942081026,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41.06,62.04,-9,-9,7,1,1,0,0,2.833333333333333,2,2,0,776.5,-73311.846848805,0,0,1095.455115827961 -4082,4948,9070,9071,-9,-9,2,1,0,73,1,0,0,0,3,-9,4,3,0,1,2,0,0,0,1,0,-9,10,0,4,-89.19702695424388,-9,0,0,0,69,3,3,1,3,3,2019,3,1,18,5,0,0,15,4,1,1,0,0,0,1,18.41881885557369,47.64539658003163,5.438887896733817,0,5.052835798742159,111.1010467551163,0,1,1,0,0,0,0,0,42.75,23.98,35.72,56.81,6,1,1,0,0,0,13,3,1,1522.5,471085.2325909931,0,0,2670.688276646125 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-4086,4953,9080,-9,9081,9079,3,1,0,2,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-935.2477235434859,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,2,3,0,0,0,6,3,1,1782.333333333333,488746.9849904536,0,0,1728.629299105464 -4086,4953,9081,9079,-9,-9,2,1,0,27,1,1,1,0,3,-9,6,3,0,0,4,0,0,0,2,0,-9,4,0,0,60.71843362527299,-9,1,1,0,36,2,4,1,-9,-9,2019,3,1,11,2,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,57,36.1,63.29,5,2,3,0,0,0,6,3,1,1782.333333333333,488746.9849904536,0,0,1728.629299105464 -4087,4954,9082,9083,-9,-9,2,1,1,37,1,0,0,0,2,-9,2,1,0,0,4,8.283017260166854,8.16865786974823,0,1,0,-9,4,0,10,86.67067633120209,0,0,0,0,27,2,1,1,-9,-9,2019,1,1,9,0,48,42,15,1,0,1,0,8.123234670914746,8.123234670914746,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,43.78,53.93,32.5,32.86,5,1,1,0,1,12.83333333333333,6,4,1,623,83467.81346897208,0,0,2712.16596575559 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-4103,4972,9125,-9,9123,9124,3,1,0,6,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1001.604102227601,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,5,5,1,854.6666666666666,142489.799231193,0,0,4914.399392824606 -4104,4973,9126,9127,-9,-9,2,1,0,90,1,0,0,0,3,-9,4,3,0,0,4,0,0,0,1,0,-9,61,0,4,62.93287828468728,0,0,0,0,86,2,3,3,-9,-9,2019,4,1,8,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,7.36718647243228,0,0,0,57.16,56.15,45.45,47.75,7,1,1,0,0,0,2,3,1,1765,858916.0878576351,0,0,2974.915844035656 -4104,4973,9127,9126,-9,-9,1,1,1,86,1,0,0,0,2,-9,4,3,0,0,3,0,7.617536298440566,7.669869968121145,1,0,-9,61,0,-4,71.84915719631883,0,0,0,0,90,3,4,3,-9,-9,2019,4,2,10,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,8.209466149366182,7.673071525236499,0,0,45.45,47.75,57.16,56.15,6,1,1,0,0,0,2,3,1,1765,858916.0878576351,0,0,2974.915844035656 -4105,4974,9128,9129,-9,-9,2,1,0,81,1,0,0,0,3,-9,4,3,0,0,3,0,6.296733826873433,6.147173125736209,1,0,-9,9,0,-2,13.46238493948013,0,0,0,0,83,1,4,3,3,3,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,1,0,2.696809798411226,0,0,0,0,0,1,1,0,6.269748399069785,5.892950953996457,0,0,58.85,33.57,59.74,45.34,6,1,1,0,0,0,10,3,1,505,317175.6817210214,0,0,2933.893417968764 -4105,4974,9129,9128,-9,-9,1,1,1,83,1,0,0,0,1,-9,4,3,0,0,4,0,7.122770634708008,7.337077893674077,1,0,-9,9,0,2,-34.08248345749504,0,0,0,0,81,3,3,3,3,3,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,0,1,1,0,6.825124443761355,7.841703220983359,0,0,59.74,45.34,58.85,33.57,6,1,1,0,0,0,10,3,1,505,317175.6817210214,0,0,2933.893417968764 -4106,4975,9130,-9,9132,9131,3,1,0,14,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-857.4633052909475,-9,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,59,-9,-9,5,1,1,0,0,0,7,4,1,718.6666666666666,995034.5641580401,0,0,2905.7160329252 -4106,4975,9131,9132,-9,-9,2,1,1,55,1,0,1,0,3,-9,2,1,0,0,3,8.198026523612471,8.476170735677641,0,2,0,-9,30,0,5,-46.38971917422055,0,0,0,0,50,2,4,1,-9,-9,2019,1,1,12,2,38,39,15,1,0,1,0,12.03996133098938,12.03996133098938,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.45,46.21,52.4,55.58,6,1,1,0,0,12.5,7,4,1,718.6666666666666,995034.5641580401,0,0,2905.7160329252 -4106,4975,9132,9131,-9,-9,1,1,0,50,1,0,1,0,2,-9,2,1,0,0,4,8.256645557352931,8.019079273008748,0,2,0,-9,30,0,-5,4.879333835559492,-9,0,0,0,55,3,3,1,3,2,2019,1,2,10,2,40,0,15,1,0,1,0,14.30729348748338,14.30729348748338,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52.4,55.58,46.45,46.21,6,1,1,0,0,12.91666666666667,7,4,1,718.6666666666666,995034.5641580401,0,0,2905.7160329252 -4107,4976,9133,-9,-9,-9,1,1,0,52,2,0,0,0,3,-9,2,1,0,0,2,6.760913758920567,7.008478449092532,0,3,0,0,0,-9,0,-939.4791133186427,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,14,3,4,16,15,1,0,-9,0,31.8080217336468,31.8080217336468,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.29,43.73,-9,-9,5,1,1,0,0,1.416666666666667,2,2,1,158,214377.7157778623,0,0,259.0549590963799 -4108,4977,9134,-9,-9,-9,1,1,1,73,2,0,0,0,3,-9,4,3,0,0,3,0,7.470393372332541,7.364270780153594,3,0,0,0,-9,0,-1118.880155989307,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,1,0,64.00736409956022,0,0,0,0,0,1,1,0,6.162641185987092,6.675047208597623,0,0,58.14,26.29,-9,-9,6,1,1,0,0,0,13,2,1,403,654548.6036670121,0,0,482.3813822354355 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-4110,4979,9137,-9,-9,-9,1,1,1,30,2,0,0,0,2,-9,1,1,0,0,4,7.820092892927192,7.438423638105093,0,3,0,0,0,-9,0,-1013.095609725753,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,0,60,45,15,1,0,-9,0,4.751917196328771,4.751917196328771,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,38.4,60.75,-9,-9,3,1,1,0,0,9.25,1,3,1,804,41272.63339533674,0,0,899.6347805689031 -4111,4980,9138,-9,-9,-9,1,1,1,66,2,0,0,0,2,-9,4,3,0,0,4,0,5.879818843630523,5.994124924893885,3,0,0,0,-9,0,-830.6156145774366,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,13,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,9.5885150392019,6.182175551611351,0,0,51.19,52.17,-9,-9,6,4,2,0,0,9.166666666666666,8,2,1,2903,236675.1962998874,0,0,7519.305289803408 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-4535,5483,10060,-9,10059,10061,5,1,1,13,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1189.742128527099,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46,60,-9,-9,5,1,1,0,0,0,12,5,1,359,331653.4542467686,0,0,2059.401530367023 -4535,5483,10061,10059,-9,-9,4,1,1,47,1,0,1,0,2,-9,2,1,0,0,2,9.525897602229877,9.356222498183264,0,2,0,-9,9,0,-2,39.1142573425217,-9,0,0,0,49,2,5,1,-9,-9,2019,1,1,12,1,94,0,15,1,0,1,0,19.14156299994633,19.14156299994633,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.63,35.79,51.67,60.18,4,1,1,0,0,9.833333333333334,12,5,1,359,331653.4542467686,0,0,2059.401530367023 -4535,5484,10062,-9,10059,10061,2,1,1,25,2,0,1,0,2,-9,2,1,0,0,4,8.38315118084102,8.128106386851648,0,3,0,0,0,-9,0,-1023.441053743647,0,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,0,45,45,15,1,0,-9,1,8.636020521130625,8.636020521130625,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.91,58.02,-9,-9,5,1,1,0,0,8.583333333333334,12,4,1,1911,160489.7489413705,0,0,1550.80790673091 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-5381,6530,12021,12020,-9,-9,1,1,0,52,1,0,1,0,1,-9,2,1,0,0,3,8.069078900778639,7.924386531382564,0,2,0,-9,30,0,-7,122.8777619429638,0,0,0,0,59,2,4,1,2,2,2019,1,2,19,7,20,18,15,1,1,1,0,16.02196005296087,16.02196005296087,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43.03,53.23,57.91,46.15,6,1,1,0,0,5,4,4,1,418,251831.5255877347,0,0,3201.659004697249 -5382,6531,12022,12023,-9,-9,1,1,0,39,1,0,0,0,1,-9,3,3,0,0,4,0,0,0,1,0,-9,3,0,-4,19.14576943973674,0,0,1,0,43,1,4,1,2,2,2019,3,2,19,7,0,40,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,.086296172774768,0,0,0,24.62,64.67,44.26,59.43,3,1,1,1,0,11.25,11,3,1,1574,2221002.155056032,0,0,1365.7526500666 -5382,6531,12023,12022,-9,-9,2,1,1,43,1,0,0,0,1,-9,2,1,0,0,4,7.81519803945237,8.141745256838002,0,1,0,-9,3,0,4,108.980623301387,0,0,0,0,39,1,4,3,-9,-9,2019,2,1,13,1,39,40,15,1,0,3,0,11.08170426123934,11.08170426123934,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.26,59.43,24.62,64.67,5,1,1,0,0,6.166666666666667,11,3,1,1574,2221002.155056032,0,0,1365.7526500666 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-5383,6532,12027,-9,12028,12024,4,1,1,14,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-952.0176395610976,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,11,4,1,944.2,587124.1189967077,0,0,5502.844323557196 -5383,6532,12028,12024,-9,-9,2,1,0,34,1,0,2,0,2,-9,2,1,0,0,5,8.250681887428904,8.156352469818994,0,2,0,-9,7,0,-4,126.1173771411928,0,0,1,0,38,2,2,1,2,3,2019,1,1,8,0,40,40,15,1,0,1,0,7.966808009512593,7.966808009512593,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42.02,63.11,44.05,40.95,6,1,1,0,0,9.75,11,4,1,944.2,587124.1189967077,0,0,5502.844323557196 -5384,6533,12029,-9,-9,-9,1,1,1,64,2,0,0,0,1,-9,2,1,0,0,3,8.250694885853536,8.512698239401779,0,3,0,0,0,-9,0,-999.710782593712,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,0,37,39,15,1,0,-9,0,11.5163577124972,11.5163577124972,0,0,0,0,0,0,0,7,0,0,0,.5542594214420822,0,3.251993730779426,3,53.53,51,-9,-9,5,1,1,0,0,12.83333333333333,7,4,1,631,1676124.975535449,0,0,1642.384337851611 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-7378,9013,16491,-9,16490,16492,5,1,0,10,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1198.656135006252,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,1,1,0,0,0,9,5,1,534.8,1277412.046500654,0,0,4460.909765084008 -7378,9013,16492,16490,-9,-9,2,1,1,46,1,0,2,0,2,-9,2,1,0,0,4,8.762015535668347,8.904957147371759,0,2,0,-9,7,0,6,-19.74709312819589,0,0,0,0,40,2,3,1,2,2,2019,1,1,8,0,41,41,15,1,0,1,0,28.41691773719442,28.41691773719442,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,47.43,54.04,6,1,1,0,1,8,9,5,1,534.8,1277412.046500654,0,0,4460.909765084008 -7379,9014,16493,16494,-9,-9,2,1,1,41,1,0,1,0,1,-9,2,1,0,0,4,8.743673303494676,8.815042252591683,0,2,0,-9,7,0,-1,-31.99723183062554,0,0,0,0,42,2,2,3,-9,-9,2019,2,1,8,0,42,45,15,1,0,3,0,18.67861157551127,18.67861157551127,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.87,58.55,42.79,33.24,5,1,1,0,0,11.08333333333333,2,4,1,1307.666666666667,174087.0828902223,0,0,2306.88693658384 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-7381,9017,16500,16499,-9,-9,2,1,1,25,1,0,0,0,2,-9,2,1,0,0,5,8.058037868771711,8.524933288345808,0,1,0,-9,5,0,0,-77.3668474228657,0,1,0,0,25,1,3,1,-9,-9,2019,1,1,6,0,42,38,15,1,0,1,0,11.40810401171771,11.40810401171771,0,0,0,0,0,0,0,0,0,0,0,.5318753534729946,0,0,0,43.63,61.31,36.33,59.23,6,1,1,0,0,4.916666666666667,10,4,0,850.5,119340.5126837014,0,0,1553.500704874553 -7382,9018,16501,16502,-9,-9,1,1,1,52,1,0,0,0,2,-9,8,3,1,1,1,0,6.562017355201138,6.336627705256311,1,0,-9,6,0,-3,-42.64804119216865,0,0,0,0,55,1,3,1,3,3,2019,3,2,12,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.544720735756218,6.692640458383441,0,0,37.81,25.04,50.71,52.35,2,1,1,0,0,1.916666666666667,1,3,0,428,184390.6718864326,0,0,2857.805591338597 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-7383,9019,16505,-9,16506,16503,4,1,1,4,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-930.6290711436023,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,2,3,0,0,0,5,5,1,719.75,304657.7300354268,0,0,5189.146817877801 -7383,9019,16506,16503,-9,-9,1,1,0,38,1,0,2,0,1,-9,2,1,0,0,4,8.786036126159587,8.734823464824546,0,2,0,-9,8,0,1,-56.38709657956277,0,0,1,0,37,1,4,1,2,2,2019,1,2,6,0,39,39,15,1,0,1,0,26.67379035038326,26.67379035038326,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,50,57,6,2,3,0,0,7.583333333333333,5,5,1,719.75,304657.7300354268,0,0,5189.146817877801 -7384,9020,16507,-9,-9,-9,1,1,0,47,2,0,1,0,2,-9,2,1,0,0,2,7.550399517933485,7.357827083123219,0,4,0,0,0,-9,0,-995.5658408244119,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,17,5,23,21,15,1,1,-9,0,6.688483819633181,6.688483819633181,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,29.48,47.73,-9,-9,2,1,1,0,1,7.083333333333333,10,2,0,324,37091.56976081331,0,0,1894.545026977167 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-7457,9106,16671,-9,16667,16668,3,1,1,17,2,0,3,1,2,0,7,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1006.083996341536,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,48,59,-9,-9,5,1,1,0,0,3.5,5,2,1,803.4,35742.98750837102,0,0,2938.026276276114 -7458,9107,16672,16674,-9,-9,2,1,1,38,1,0,1,0,2,-9,2,1,0,0,3,8.342807113504998,8.294842499525537,0,2,0,-9,6,0,-1,-73.31175992984876,0,0,0,0,39,1,4,1,-9,-9,2019,1,1,20,6,43,43,15,1,1,1,0,12.51718112538048,12.51718112538048,0,0,0,0,0,0,0,0,1,1,0,1.990115325636351,0,0,0,35.3,62.04,42.95,61.24,3,1,1,0,0,8.25,10,4,1,604,180452.1282887761,0,0,2367.30951646683 -7458,9107,16673,-9,16674,16672,3,1,1,3,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-959.0956895751701,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,10,4,1,604,180452.1282887761,0,0,2367.30951646683 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-7557,9236,16923,16919,-9,-9,1,1,1,54,1,0,3,0,3,-9,2,1,0,0,3,7.043095900842674,7.045223315202056,0,2,0,-9,26,0,3,60.30684956472396,0,0,0,0,51,2,2,3,3,3,2019,2,2,9,0,24,24,15,1,0,3,0,7.19555376032069,7.19555376032069,0,0,0,0,0,0,0,0,1,1,0,.5527283718268241,0,0,0,46.89,50.36,46.44,39.76,5,2,3,0,0,1.083333333333333,6,2,1,688.6,94217.58095994072,0,0,1846.35047088805 -7558,9237,16924,-9,-9,-9,1,1,0,54,2,0,0,0,2,-9,6,3,0,1,2,0,0,0,3,0,0,0,-9,0,-1008.323399680428,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,24,12,0,36,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,27.5,1,1,0,0,0,28.76316036676313,3,27.39,34.55,-9,-9,4,1,1,0,1,7.916666666666667,12,1,0,294,-104212.1726022295,0,0,712.2827078213334 -7559,9238,16925,16926,-9,-9,2,1,1,55,1,0,1,0,1,-9,1,1,0,0,3,0,0,0,2,0,-9,28,0,0,-142.0931415414452,0,0,0,0,55,2,2,3,2,2,2019,2,1,10,1,0,0,15,1,0,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49.28,50.19,39.16,35.3,3,1,1,0,1,7.083333333333333,2,1,0,515,32131.50100857185,0,0,2495.12867273728 -7559,9238,16926,16925,-9,-9,1,1,0,55,1,0,1,0,2,-9,8,3,1,1,2,0,4.08094101373355,4.231644528165461,2,0,-9,27,0,0,-39.76435565267057,0,0,0,0,55,1,3,1,1,1,2019,3,2,17,5,0,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.107649698149394,0,0,0,39.16,35.3,49.28,50.19,2,1,1,0,1,3.583333333333333,2,1,0,515,32131.50100857185,0,0,2495.12867273728 -7559,9238,16927,-9,16926,16925,3,1,0,15,2,0,1,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1046.787007728519,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,54,-9,-9,5,1,1,0,0,0,2,1,0,515,32131.50100857185,0,0,2495.12867273728 -7560,9239,16928,-9,-9,-9,1,1,1,37,2,0,0,0,1,-9,2,1,0,0,5,8.572753978315362,8.444974896374619,0,1,0,-9,5,0,6,76.0745290873739,0,0,0,0,-9,-9,-9,-9,3,3,2019,1,2,5,0,7,15,15,1,0,-9,0,85.28328628851224,85.28328628851224,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.39,56.71,51.77,58.57,6,1,1,0,0,11,2,5,1,178,39825.72585339922,0,0,1323.698356487194 -7560,9240,16929,-9,-9,-9,2,1,1,31,2,0,0,0,1,-9,2,1,0,0,4,8.032866166655188,8.455214006221714,0,1,0,-9,5,0,-6,-56.54815906921321,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,1,1,13,3,37,37,15,1,0,-9,0,14.72881474441971,14.72881474441971,0,0,0,0,0,0,0,0,0,0,0,3.33779336833333,0,0,0,51.77,58.57,62.39,56.71,6,1,1,0,0,12.75,2,5,1,398,197958.1892789904,0,0,2165.794014204292 -7561,9241,16930,-9,-9,-9,1,1,1,73,2,0,0,0,2,-9,4,3,0,0,2,0,7.833659862203097,7.978684787148667,3,0,0,0,-9,0,-1022.491348937563,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,13,2,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.229089941164099,7.871562416070141,0,0,59.14,23.37,-9,-9,4,1,1,0,0,0,12,3,1,1412,714512.7951485241,0,0,2424.663042548918 -7562,9242,16931,-9,-9,-9,1,1,1,74,2,0,0,0,3,-9,4,3,0,0,3,0,0,0,3,0,0,0,-9,0,-924.281401713252,0,0,0,0,-9,-9,-9,-9,-9,2,2019,-9,0,9,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53,46,-9,-9,6,1,1,0,0,0,7,1,0,464,0,0,0,1073.209307292065 -7563,9243,16932,16933,-9,-9,2,1,1,57,1,0,0,0,2,-9,2,1,0,0,5,9.105852741533088,8.943631822230714,0,1,0,-9,3,0,-4,-32.65576925506434,0,0,0,0,61,1,4,1,-9,-9,2019,1,1,6,0,40,40,15,1,0,1,0,21.7544479717247,21.7544479717247,0,0,0,0,0,0,0,14.5,0,0,0,7.181564843704836,0,15.6659320333633,3,52.32,57.18,57.16,56.15,6,1,1,0,0,1.25,5,5,1,1357.5,614833.6620399989,0,0,4791.555246120216 -7563,9243,16933,16932,-9,-9,1,1,0,61,1,0,0,0,1,-9,2,1,0,0,4,8.650837211447071,8.921567000323805,0,1,0,-9,3,0,4,-56.03731501059652,0,0,0,0,57,2,5,1,2,2,2019,1,2,6,0,33,48,15,1,0,1,0,23.93290362486821,23.93290362486821,0,0,0,0,0,0,0,0,0,0,0,2.53658334090753,0,0,0,57.16,56.15,52.32,57.18,7,1,1,0,0,9.416666666666666,5,5,1,1357.5,614833.6620399989,0,0,4791.555246120216 -7564,9244,16934,16935,-9,-9,1,1,0,47,1,0,0,0,3,-9,6,3,0,0,4,0,0,0,1,0,-9,7,0,-14,-27.31521599461784,0,0,0,0,61,3,3,1,3,3,2019,3,2,10,1,0,12,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50,55,51,48,6,1,1,0,0,6.166666666666667,11,3,0,446.5,475722.8867272365,0,0,713.6762840521685 -7564,9244,16935,16934,-9,-9,2,1,1,61,1,0,0,0,3,-9,2,1,0,0,3,7.710320224475242,7.419982713995537,0,1,0,-9,7,0,14,-49.09414523410506,0,0,0,0,47,3,4,3,-9,-9,2019,2,1,10,1,32,31,15,1,0,3,0,8.806131988112492,8.806131988112492,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,48,50,55,5,1,1,0,0,4.75,11,3,0,446.5,475722.8867272365,0,0,713.6762840521685 -7565,9245,16936,-9,-9,-9,1,1,0,56,2,0,0,0,3,-9,8,3,1,1,2,0,0,0,3,0,0,0,-9,0,-969.2415888205084,0,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,12,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47.05,47.73,-9,-9,6,1,1,0,0,.5833333333333334,5,1,0,625,-157026.572530334,0,0,715.5779656251223 -7566,9246,16937,16938,-9,-9,2,1,0,53,1,0,0,0,2,-9,2,1,0,0,5,8.413728201725439,8.3083034521584,0,1,0,-9,6,0,0,157.938089760973,0,0,0,0,53,2,4,1,3,-9,2019,1,1,6,0,30,30,15,1,0,1,0,13.55726884192694,13.55726884192694,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.1,59.11,53,54,7,1,1,0,0,7.083333333333333,11,5,1,584,1741440.605565232,0,0,4187.141470500376 -7566,9246,16938,16937,-9,-9,1,1,1,53,1,0,0,0,2,-9,2,1,0,0,4,8.571203427638805,8.556275377707374,0,1,0,-9,6,0,0,34.45921696350667,0,0,0,0,53,2,5,1,-9,-9,2019,1,2,9,1,40,44,15,1,0,1,0,16.48528780541705,16.48528780541705,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53,54,54.1,59.11,6,1,1,0,0,1,11,5,1,584,1741440.605565232,0,0,4187.141470500376 -7567,9247,16939,16940,-9,-9,2,1,1,38,1,0,0,0,1,-9,2,1,0,0,3,8.447467804202022,8.601777212195071,0,1,0,-9,10,0,-1,-39.82132862616534,0,0,0,0,39,1,4,1,1,2,2019,1,1,9,0,39,0,15,1,0,1,0,19.08127880921338,19.08127880921338,0,0,0,0,0,0,0,0,0,0,0,3.125424606951436,0,0,0,33.06,63.21,31.77,61.1,3,4,5,0,0,9.333333333333334,8,4,1,753.5,327455.9148690671,0,0,3046.791431701609 -7567,9247,16940,16939,-9,-9,1,1,0,39,1,0,0,0,1,-9,2,1,0,0,4,6.768375386941056,6.337036784417747,0,1,0,-9,10,0,1,-91.26557668679946,0,0,1,0,38,1,3,1,1,1,2019,1,2,12,5,30,30,15,1,1,1,0,3.028194646617117,3.028194646617117,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,31.77,61.1,33.06,63.21,5,4,5,0,0,11.16666666666667,8,4,1,753.5,327455.9148690671,0,0,3046.791431701609 -7568,9248,16941,16942,-9,-9,1,1,1,67,1,0,0,0,1,-9,1,1,0,0,4,9.84059219701258,10.15947560676897,9.477522867903073,1,0,-9,45,0,2,-85.39040642877364,0,0,0,0,65,1,4,1,2,2,2019,1,2,6,0,20,10,15,1,0,1,0,101.5598951008938,101.5598951008938,0,0,0,0,0,0,0,0,1,1,0,7.633850363306612,9.56296441831824,0,0,57.16,56.15,63.48,51.85,6,1,1,0,0,9.333333333333334,10,5,1,423,5181852.710460333,0,0,13186.09448900573 -7568,9248,16942,16941,-9,-9,2,1,0,65,1,0,0,0,1,-9,1,1,0,0,4,4.637139842921671,7.655291126447557,7.971314440845182,1,0,-9,9,0,-2,-74.89960519260332,0,0,0,0,67,1,4,1,-9,-9,2019,1,1,7,0,10,8,15,1,0,1,0,1.243123694587092,1.243123694587092,0,0,0,0,0,0,0,0,1,1,0,5.547102168093659,7.70025446765405,0,0,63.48,51.85,57.16,56.15,7,1,1,0,0,9.833333333333334,10,5,1,423,5181852.710460333,0,0,13186.09448900573 -7569,9249,16943,-9,-9,-9,1,1,1,68,2,0,0,0,2,-9,4,3,0,0,5,0,8.221749473438493,8.236589369718638,3,0,0,0,-9,0,-1000.612414223103,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.519409515124059,8.091086143860283,0,0,57.06,57.76,-9,-9,7,1,1,0,0,0,9,4,1,2001,1649141.498872063,0,0,2387.866868666646 -7570,9250,16944,16945,-9,-9,3,1,1,54,1,0,0,0,2,-9,2,1,0,0,3,8.271594907413075,8.18805621908013,0,1,0,-9,1,-9,2,0,-9,0,0,0,52,2,4,1,-9,-9,2019,1,1,7,0,39,0,15,1,0,1,0,8.265778069579671,8.265778069579671,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.33,53.46,49.11,52.88,6,1,1,0,0,12.66666666666667,9,5,1,1340,482776.0895846876,0,0,3230.495989722814 -7570,9250,16945,16944,-9,-9,1,1,0,52,1,0,0,0,2,-9,2,1,0,0,4,8.011833506841471,8.160872443118867,0,1,0,-9,1,-9,-2,0,-9,0,0,0,54,2,3,1,2,2,2019,1,3,9,0,37,0,15,1,0,1,0,10.9332468370547,10.9332468370547,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.11,52.88,57.33,53.46,6,1,1,0,0,12.66666666666667,9,5,1,1340,482776.0895846876,0,0,3230.495989722814 -7571,9251,16946,16947,-9,-9,2,1,1,82,1,0,0,0,2,-9,4,3,0,0,3,0,7.92008485894422,7.852399215541747,1,0,-9,9,0,2,23.40792154232834,0,0,0,0,80,2,3,3,-9,-9,2019,4,1,9,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.190725356926845,7.538819227024104,0,0,54,46,58.08,40.76,6,1,1,0,0,0,4,3,1,1174,1078176.963740213,0,0,3737.753911330247 -7571,9251,16947,16946,-9,-9,1,1,0,80,1,0,0,0,2,-9,4,3,0,0,3,0,7.096065262141495,7.129262163956388,1,0,-9,58,0,-2,-120.6252662033927,0,0,0,0,82,2,3,3,3,2,2019,4,2,11,2,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.9363839375954741,7.105926500181473,0,0,58.08,40.76,54,46,6,1,1,0,0,0,4,3,1,1174,1078176.963740213,0,0,3737.753911330247 -7572,9252,16948,16949,-9,-9,1,1,0,56,1,0,0,0,2,-9,2,1,0,0,4,8.510602631974399,8.855568633560218,0,1,0,-9,10,0,12,-33.4971944958267,0,0,0,0,44,2,4,1,-9,-9,2019,1,2,6,0,35,38,15,1,0,1,0,21.72572319017099,21.72572319017099,0,0,0,0,0,0,0,14.5,0,0,0,0,0,23.56877483105799,3,51.24,58.84,57.16,56.15,6,1,1,0,0,12.5,12,5,1,693.5,85733.65634060933,0,0,3002.211314738837 -7572,9252,16949,16948,-9,-9,2,1,1,44,1,0,0,0,2,-9,2,1,0,0,4,8.482997416412383,8.231543915417975,0,1,0,-9,10,0,-12,35.59166437213308,0,0,0,0,56,2,4,1,2,-9,2019,1,1,8,0,37,37,15,1,0,1,0,10.03439959886975,10.03439959886975,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,51.24,58.84,5,1,1,0,0,12.41666666666667,12,5,1,693.5,85733.65634060933,0,0,3002.211314738837 -7573,9253,16950,16951,-9,-9,2,1,0,61,1,0,0,0,1,-9,2,1,0,0,4,9.023975176265099,8.989490311599166,0,1,0,-9,9,0,3,-115.2465759855609,0,0,0,0,58,2,5,3,-9,-9,2019,2,1,10,0,45,46,15,1,0,4,0,17.97090025623903,17.97090025623903,0,0,0,0,0,0,0,0,0,0,0,5.122001413838016,0,0,0,51.24,58.84,59.33,51.29,6,1,1,0,0,12.5,10,5,1,1751,1442013.657994851,0,0,4121.563773951591 -7573,9253,16951,16950,-9,-9,1,1,1,58,1,0,0,0,2,-9,4,3,0,0,5,0,7.691030101706615,7.807783026617768,1,0,-9,24,0,-3,-24.99196281120786,0,0,0,0,61,1,4,1,3,3,2019,3,2,7,1,0,45,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.702975860166516,7.639704274997419,0,0,59.33,51.29,51.24,58.84,6,1,1,0,0,12.41666666666667,10,5,1,1751,1442013.657994851,0,0,4121.563773951591 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-7579,9259,16964,-9,-9,-9,1,1,1,40,2,0,0,0,2,-9,2,1,0,0,4,7.753177563257753,8.544796265490067,5.823868581373542,3,0,0,0,-9,0,-1114.94987054738,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,7,0,50,0,15,1,0,-9,0,6.050419268847078,6.050419268847078,0,0,0,0,0,0,0,0,0,0,0,6.167805036310933,0,0,0,49.35,59.64,-9,-9,5,1,1,0,0,4,9,4,1,384,0,0,0,1047.303904431135 -7580,9260,16965,-9,-9,-9,1,1,1,29,2,0,0,0,2,-9,2,1,0,0,4,7.782288028645096,7.806742735403287,0,3,0,0,0,-9,0,-1056.430363151781,0,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,21,6,65,0,15,1,1,-9,0,5.137494954910953,5.137494954910953,0,0,0,0,0,0,0,0,0,0,0,.9673845985701488,0,0,0,32.13,54.99,-9,-9,4,1,1,0,0,9.833333333333334,7,3,0,7606,88025.39764106102,0,0,1906.886400467873 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-8243,10078,18413,-9,18412,18411,3,1,1,18,2,0,0,0,2,1,2,1,0,0,4,7.679843620092014,7.454564325311742,0,3,0,0,0,-9,0,-958.0531402556476,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,30,0,15,1,0,-9,1,7.333709918550987,7.333709918550987,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,34.04,54.63,-9,-9,5,1,1,0,1,3.333333333333333,10,3,1,866,-123158.6218040039,0,0,740.7123863264716 -8244,10079,18414,18415,-9,-9,1,1,1,64,1,0,0,0,2,-9,4,3,0,0,4,0,7.321742868085955,7.091470806487557,1,0,-9,45,0,1,-81.25987178316151,0,0,0,0,63,2,4,1,3,3,2019,3,2,4,0,0,37,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.461217021459706,7.358325325636343,0,0,57.16,56.15,57.16,56.15,7,1,1,0,0,11.91666666666667,7,4,1,309,1324407.770347537,0,0,3111.113833266655 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-8668,10608,19363,-9,19364,19365,4,1,1,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1094.572027426971,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,60,-9,-9,5,1,1,0,0,0,4,3,1,496.75,505169.5855897253,0,0,2787.361206913985 -8668,10608,19364,19365,-9,-9,1,1,0,41,1,0,2,0,2,-9,2,1,0,0,5,8.326164296457804,8.229941682108201,0,2,0,-9,16,0,-1,36.16691580203341,0,0,1,0,42,2,3,1,2,2,2019,1,2,12,0,32,35,15,1,0,1,0,15.44252768780095,15.44252768780095,0,0,0,0,0,0,0,0,1,1,0,7.312888496191087,0,0,0,54.1,59.11,55.53,51.55,6,1,1,0,0,6.166666666666667,4,3,1,496.75,505169.5855897253,0,0,2787.361206913985 -8668,10608,19365,19364,-9,-9,2,1,1,42,1,0,2,0,2,-9,1,1,0,0,3,7.274436524931816,7.379644312602125,0,2,0,-9,18,0,1,-78.27874004487801,0,0,0,0,41,2,5,1,2,2,2019,1,1,9,0,40,40,15,1,0,1,0,4.105199538831259,4.105199538831259,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,55.53,51.55,54.1,59.11,6,1,1,0,0,9.666666666666666,4,3,1,496.75,505169.5855897253,0,0,2787.361206913985 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-8770,10737,19586,-9,19584,-9,3,1,1,22,2,0,0,0,2,-9,2,1,0,0,4,8.036084479933292,8.175820155472909,0,3,0,0,0,-9,0,-1113.298775414223,0,1,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,9,0,38,35,15,1,0,-9,1,7.34794858568792,7.34794858568792,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,52.23,55.6,-9,-9,5,1,1,0,0,8.583333333333334,12,3,1,136,-169934.9496770107,0,0,951.4209077630892 -8771,10738,19587,-9,-9,-9,1,1,0,89,2,0,0,0,1,-9,4,3,0,0,2,0,7.815372132578992,7.880369842991688,3,0,0,0,-9,0,-922.026910325819,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,17,7,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,5.482403433915875,8.099791974700343,2.416842653539897,3,39.83,30.82,-9,-9,4,1,1,0,0,0,9,3,1,330,949284.2216644598,0,0,2089.914664296622 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-8923,10927,19954,-9,-9,-9,1,1,0,26,2,0,0,0,1,-9,2,1,0,0,5,8.137875620459033,8.3617193756319,0,3,0,0,0,-9,0,-1087.034125579861,0,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,13,3,35,35,15,1,0,-9,0,11.29115657465038,11.29115657465038,0,0,0,0,0,0,0,0,0,0,0,2.106871115024963,0,0,0,46.88,60.96,-9,-9,5,1,1,0,0,5.416666666666667,4,4,0,255,138311.5352066085,0,0,2012.70500079765 -8924,10928,19955,19956,-9,-9,2,1,1,57,1,0,0,0,2,-9,2,1,0,0,3,7.651424742492035,8.715218129126201,8.008329761676226,1,0,-9,10,0,0,-182.0326155268476,0,0,0,0,57,3,4,3,3,3,2019,2,1,7,0,19,19,15,1,0,3,0,15.19724829391032,15.19724829391032,0,0,0,0,0,0,0,2,0,0,0,3.997248095251776,8.282551547104902,0,3,44.57,52.34,57.16,56.15,2,1,1,0,0,10.5,9,4,1,243,2694580.925503522,0,0,2381.140247269931 -8924,10928,19956,19955,-9,-9,1,1,0,57,1,0,0,0,3,-9,6,3,0,0,4,0,0,0,1,0,-9,10,0,0,-24.07028434894717,0,0,0,0,57,2,3,1,3,3,2019,3,2,11,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,7,0,0,0,3.994806764891778,0,13.91026227136932,3,57.16,56.15,44.57,52.34,6,1,1,0,0,7,9,4,1,243,2694580.925503522,0,0,2381.140247269931 -8925,10929,19957,19958,-9,-9,2,1,0,34,1,0,0,0,2,-9,2,1,0,0,3,7.702164436028191,7.745938668791487,5.802638609575099,1,0,-9,2,0,9,37.93600713555649,0,0,1,0,25,2,5,1,-9,-9,2019,1,1,23,8,32,21,15,1,1,1,0,6.859416490138726,6.859416490138726,0,0,0,0,0,0,0,0,1,1,0,5.73836749058115,0,0,0,25.37,63.98,57.06,57.76,6,1,1,0,0,1.083333333333333,9,5,1,544,81240.85133038397,0,0,4189.81309562707 -8925,10929,19958,19957,-9,-9,1,1,1,25,1,0,0,0,2,-9,2,1,0,0,5,8.530848312764622,8.641621505047389,0,1,0,-9,2,0,0,-82.65196513141049,0,1,0,0,34,2,3,1,2,2,2019,1,2,6,0,40,36,15,1,0,1,0,17.19137821571602,17.19137821571602,0,0,0,0,0,0,0,0,1,1,0,1.407812988063128,0,0,0,57.06,57.76,25.37,63.98,6,1,1,0,0,9.75,9,5,1,544,81240.85133038397,0,0,4189.81309562707 -8926,10930,19959,-9,19964,19963,4,1,0,5,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-919.9855564282858,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,2,3,0,0,0,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8926,10930,19960,-9,19964,19963,6,1,1,1,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-968.4137175537609,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,62,-9,-9,5,2,3,0,0,0,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8926,10930,19961,-9,19964,19963,3,1,1,15,2,1,4,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1029.672826308502,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,55,-9,-9,5,2,3,0,0,0,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8926,10930,19962,-9,19964,19963,5,1,1,4,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-972.2806020762491,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,2,3,0,0,0,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8926,10930,19963,19964,-9,-9,1,1,1,35,1,1,4,0,2,-9,2,1,0,0,4,7.979945030949001,8.160169358968913,0,2,0,-9,13,0,-1,37.69537529143253,0,0,0,1,36,3,4,3,2,2,2019,2,2,8,0,40,35,15,1,0,3,0,7.251431364050431,7.251431364050431,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41.35,37.74,37.57,39.48,1,2,3,0,0,7.666666666666667,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8926,10930,19964,19963,-9,-9,2,1,0,36,1,1,4,0,3,-9,6,3,0,0,4,0,0,0,2,0,-9,13,0,1,-17.8354377968076,0,0,1,1,35,2,4,1,-9,-9,2019,3,1,15,4,0,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,37.57,39.48,41.35,37.74,3,2,3,0,0,0,4,2,0,836.6666666666666,200596.9640179247,0,0,2747.670190796807 -8927,10931,19965,-9,-9,-9,1,1,0,67,2,0,0,0,2,-9,4,3,0,0,3,0,4.000659977508342,4.226683609680038,3,0,0,0,-9,0,-979.745556102331,0,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,2,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,71.5,1,1,0,0,4.492878972126173,61.51545521824758,3,63.85,40.9,-9,-9,1,1,1,0,0,2,9,2,0,917,-8494.02734951982,0,0,1659.11062551339 -8927,10932,19966,-9,-9,-9,2,1,0,60,2,0,0,0,2,-9,3,3,0,1,2,0,0,0,3,0,0,0,-9,0,-930.8994038193695,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.98,37.01,-9,-9,3,1,1,1,0,3.333333333333333,9,1,0,254,-120659.830897894,0,0,1158.783768773328 -8928,10933,19967,19968,-9,-9,2,1,0,77,1,0,0,0,2,-9,4,3,0,0,3,0,7.211636549247347,6.820391346914271,1,0,-9,58,0,-2,61.05915371361509,0,0,0,0,79,1,2,3,3,2,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.150814751110222,0,0,50.77,50.99,54,33.92,2,1,1,0,0,0,9,3,1,100,1259108.194985609,0,0,2489.716511540108 -8928,10933,19968,19967,-9,-9,1,1,1,79,1,0,0,0,1,-9,4,3,0,0,2,0,7.550377917293269,7.4146926371386,1,0,-9,58,0,2,-53.23772558585393,0,0,0,0,77,2,3,3,3,-9,2019,4,2,12,2,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,7.566714656144511,0,0,54,33.92,50.77,50.99,5,1,1,0,0,0,9,3,1,100,1259108.194985609,0,0,2489.716511540108 -8929,10934,19969,-9,-9,-9,1,1,1,79,2,0,0,0,2,-9,4,3,0,0,2,0,7.236591993281002,7.181963148281141,3,0,0,0,-9,0,-1062.305586488148,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,11,2,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.311311265801304,0,0,51.34,37.58,-9,-9,6,1,1,0,0,0,4,3,1,390,36140.30548354413,0,0,721.8359999011952 -8930,10935,19970,-9,-9,-9,1,1,1,67,2,0,0,0,2,-9,4,3,0,0,1,0,7.18407062966487,7.10881378866667,3,0,0,0,-9,0,-972.0164600176752,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,13,2,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,7.885057691177169,7.011616658460053,0,0,51.02,22.74,-9,-9,6,1,1,0,0,5.75,10,2,1,277,532887.8904537375,0,0,1792.153185317962 -8931,10936,19971,19972,-9,-9,1,1,1,89,1,0,0,0,2,-9,4,3,0,0,3,0,6.266445946642743,5.895828954627658,1,0,-9,7,0,8,-4.109725725784775,0,0,0,0,81,2,3,3,2,2,2019,4,2,6,0,0,0,15,4,0,4,0,0,0,1,0,25.06524852358934,0,0,0,0,0,1,1,0,2.003192101754419,6.059840739449808,0,0,54.31,28.8,47.17,47.5,7,1,1,0,0,0,12,2,1,424,5521.029090634656,0,0,1480.577424813317 -8931,10936,19972,19971,-9,-9,2,1,0,81,1,0,0,0,2,-9,4,3,0,0,3,0,0,0,1,0,-9,7,0,-8,-53.28023771731738,0,0,0,0,89,2,3,3,1,2,2019,4,1,10,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.62338385511767,0,0,0,47.17,47.5,54.31,28.8,6,1,1,0,0,0,12,2,1,424,5521.029090634656,0,0,1480.577424813317 -8932,10937,19973,19974,-9,-9,2,1,1,64,1,1,1,0,2,-9,8,3,1,1,1,0,0,0,2,0,-9,37,0,-2,-112.1641727728044,0,0,0,0,66,3,1,3,-9,-9,2019,4,1,26,12,0,0,15,3,1,4,0,0,0,0,0,0,0,0,0,0,71.5,1,1,0,0,0,75.21867340184419,1,32.97,18.82,29.48,36.9,4,1,1,0,1,9.666666666666666,2,2,0,1717,70510.71537257871,0,0,2826.628106808149 -8932,10937,19974,19973,-9,-9,1,1,0,66,1,1,1,0,3,-9,4,3,0,0,1,0,4.54528467628363,4.714460342484975,2,0,-9,37,0,2,-55.05794289765829,0,0,0,0,64,2,1,3,-9,-9,2019,4,2,21,7,0,0,15,4,1,3,0,0,0,1,0,15.13068088942926,2.764221682923643,0,0,0,71.5,1,1,0,0,4.522500156651716,71.93765888063935,1,29.48,36.9,32.97,18.82,2,1,1,0,0,0,2,2,0,1717,70510.71537257871,0,0,2826.628106808149 -8932,10938,19975,-9,-9,-9,3,1,0,24,2,1,1,0,2,-9,5,1,0,0,4,8.354814889934403,8.15494637817819,0,4,0,0,0,-9,0,-1019.013393669974,0,1,1,1,-9,-9,-9,-9,-9,-9,2019,-9,0,10,0,39,51,15,1,0,-9,0,10.23710785674511,10.23710785674511,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.87,58.55,-9,-9,7,1,1,0,0,4.5,2,4,0,1124.5,-1992.298267584043,0,0,2542.682952739409 -8932,10938,19976,-9,19975,-9,4,1,1,0,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1024.082077507074,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,62,-9,-9,5,1,1,0,0,0,2,4,0,1124.5,-1992.298267584043,0,0,2542.682952739409 -8933,10939,19977,-9,-9,-9,1,1,0,59,2,0,0,0,1,-9,4,3,0,0,3,0,7.935376141180116,8.118519130193279,3,0,0,0,-9,0,-938.9002346002139,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.271137647573827,0,0,59.22,34.69,-9,-9,6,1,1,0,0,6.916666666666667,10,4,1,347,354660.7668779697,0,0,2455.78639426048 -8934,10940,19978,19979,-9,-9,1,1,1,25,1,0,0,0,2,-9,2,1,0,0,1,8.078021635749595,8.063829383320376,0,1,0,-9,7,0,3,1.566359383516056,0,1,0,0,22,2,3,1,-9,-9,2019,1,2,18,6,40,40,15,1,1,1,0,8.251368563587221,8.251368563587221,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,39.32,28.21,45.98,56.3,5,1,1,0,0,6.916666666666667,9,4,0,659.5,-41470.14045489847,0,0,2021.424258932621 -8934,10940,19979,19978,-9,-9,2,1,0,22,1,0,0,0,2,-9,2,1,0,0,3,7.769871518913972,7.808692143123394,0,1,0,-9,7,0,-3,83.54143189638567,0,1,1,0,25,2,1,1,-9,-9,2019,1,1,12,0,0,44,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.98,56.3,39.32,28.21,4,1,1,0,0,6.25,9,4,0,659.5,-41470.14045489847,0,0,2021.424258932621 -8935,10941,19980,-9,-9,-9,1,1,0,78,2,0,0,0,2,-9,4,3,0,0,4,0,0,0,3,0,0,0,-9,0,-904.5248773321945,0,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,10,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52.34,56.95,-9,-9,7,1,1,0,0,0,11,1,1,751,101581.4812167289,0,0,1237.732077616095 -8936,10942,19981,19982,-9,-9,1,1,0,63,1,0,0,0,3,-9,1,1,0,0,3,7.53703262195295,7.474728848478862,0,1,0,-9,45,0,-5,6.288686326538047,0,0,0,0,68,2,2,1,3,3,2019,1,2,11,2,0,25,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,50,47,40.54,53.95,5,1,1,0,0,8.916666666666666,1,4,1,291,404228.0888093757,0,0,4369.022438735839 -8936,10942,19982,19981,-9,-9,2,1,1,68,1,0,0,0,2,-9,1,1,0,0,2,8.426073156056782,8.196397299688122,5.85598658954416,1,0,-9,47,0,5,-71.86511357121843,0,0,0,0,63,3,3,1,3,2,2019,1,1,12,0,20,15,15,1,0,1,0,21.9256691430211,21.9256691430211,0,0,0,0,0,0,0,0,1,1,0,7.893428623933177,6.167210116841108,0,0,40.54,53.95,50,47,6,1,1,0,0,8.916666666666666,1,4,1,291,404228.0888093757,0,0,4369.022438735839 -8937,10943,19983,-9,-9,-9,1,1,1,19,2,0,0,1,2,0,7,2,0,0,3,0,0,0,3,0,0,0,-9,0,-956.7930228088003,-9,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.497427195612174,0,0,0,57.33,53.46,-9,-9,7,1,1,0,0,1.583333333333333,10,1,1,405,-98733.59328828387,0,0,1739.306655929708 -8938,10944,19984,19985,-9,-9,1,1,0,45,1,0,0,0,2,-9,2,1,0,0,4,7.1322682280606,6.897105440924304,0,1,0,-9,26,0,-2,-20.96216900395202,0,0,0,0,47,2,3,1,2,2,2019,1,2,6,0,15,15,15,1,0,1,0,8.865341204475209,8.865341204475209,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.79,55.86,51.41,56.15,6,2,3,0,0,8.916666666666666,4,2,1,2054.5,43104.71667301076,0,0,739.5226073209495 -8938,10944,19985,19984,-9,-9,2,1,1,47,1,0,0,0,2,-9,1,1,0,0,3,6.009541625859382,6.236134652587686,0,1,0,-9,6,0,2,17.1889067569872,0,0,0,0,45,2,4,1,-9,-9,2019,1,1,6,0,40,45,15,1,0,1,0,1.431486839494738,1.431486839494738,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.41,56.15,54.79,55.86,6,2,3,0,0,8.916666666666666,4,2,1,2054.5,43104.71667301076,0,0,739.5226073209495 -8938,10945,19986,-9,19984,19985,3,1,0,18,2,0,0,0,2,1,2,1,0,0,4,6.895553006745974,6.763648382291364,0,3,0,0,0,-9,0,-983.2294883351495,-9,1,1,0,-9,-9,-9,-9,2,2,2019,-9,0,9,0,12,0,15,1,0,-9,1,12.90797806488345,12.90797806488345,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.77,58.57,-9,-9,7,2,3,0,0,1.166666666666667,4,2,1,871,-141503.6532567833,0,0,1671.349437367018 -8938,10946,19987,-9,19984,19985,4,1,1,20,2,0,0,0,2,1,2,1,0,0,5,6.216684980393492,6.52396486424598,0,3,0,0,0,-9,0,-995.19575084134,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,8,2,18,0,15,1,0,-9,1,5.310578323088111,5.310578323088111,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51,60,-9,-9,4,2,3,0,0,6.083333333333333,4,2,1,253,-51006.15170335449,0,0,3.19093666352012 -8939,10947,19988,-9,-9,-9,1,1,1,71,2,0,0,0,2,-9,4,3,0,0,4,0,7.847062484588867,8.31450483132998,3,0,0,0,-9,0,-1039.753702588544,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,8.3673651188428,8.252742392276637,0,0,62.91,42.54,-9,-9,7,1,1,0,0,0,9,4,1,150,1288573.117917853,0,0,4370.643885907434 -8940,10948,19989,-9,-9,-9,1,1,0,34,2,0,2,0,2,1,3,3,0,1,4,0,0,0,4,0,0,0,-9,0,-1095.617989692469,-9,0,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,5,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47.51,59.08,-9,-9,6,4,2,1,1,0,8,1,0,3244,35227.44059430823,0,0,775.4565146025351 -8941,10949,19990,19991,-9,-9,2,1,0,58,1,0,0,0,3,-9,6,3,0,0,3,0,0,0,1,0,-9,42,0,-4,-67.70724768773658,0,0,0,0,62,3,3,1,3,3,2019,3,1,11,2,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.154515786666019,0,0,0,49,48,51,48,5,2,3,0,0,0,4,3,1,346.5,794538.077484217,0,0,1649.643603973683 -8941,10949,19991,19990,-9,-9,1,1,1,62,1,0,0,0,3,-9,2,1,0,0,3,8.325324604788392,7.967355985405798,0,1,0,-9,43,0,4,-13.07816354063572,0,0,0,0,58,3,3,3,3,3,2019,2,2,10,1,39,57,15,1,0,3,0,9.505184573578857,9.505184573578857,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51,48,49,48,5,2,3,0,0,10.5,4,3,1,346.5,794538.077484217,0,0,1649.643603973683 -8942,10950,19992,19993,-9,-9,2,1,0,53,1,0,0,0,2,-9,4,3,0,0,2,0,0,0,1,0,-9,9,0,0,-106.1453685482618,0,0,0,0,53,2,3,1,3,-9,2019,3,1,8,0,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,58.74,40.91,51.5,45.28,7,2,3,0,0,7.916666666666667,7,4,1,1252.5,1656844.990859191,0,0,1825.650085747213 -8942,10950,19993,19992,-9,-9,1,1,1,53,1,0,0,0,2,-9,2,1,0,0,3,8.446269414253232,8.306951697811844,0,1,0,-9,9,0,0,75.51782898034799,0,0,0,0,53,2,2,3,2,2,2019,2,2,12,0,38,37,15,1,0,4,0,17.39447913368873,17.39447913368873,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,51.5,45.28,58.74,40.91,6,1,1,0,0,10.16666666666667,7,4,1,1252.5,1656844.990859191,0,0,1825.650085747213 -8942,10951,19994,-9,19992,19993,3,1,1,20,2,0,0,0,2,-9,2,1,0,0,3,0,0,0,3,0,0,0,-9,0,-1024.199489757133,0,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,0,0,0,15,1,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,48.7,56.22,-9,-9,4,2,3,0,0,2.833333333333333,7,1,1,1303,-111712.440845826,0,0,-336.2242665540996 -8942,10952,19995,-9,19992,19993,4,1,0,32,2,0,0,0,3,-9,2,1,0,0,3,7.71346984715555,7.811497726080108,0,3,0,0,0,-9,0,-940.5354456346876,0,0,1,0,-9,-9,-9,-9,2,2,2019,-9,0,12,0,45,50,15,1,0,-9,1,6.216946456770554,6.216946456770554,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,49.04,55.86,-9,-9,6,2,3,0,0,10.16666666666667,7,3,1,782,33802.94950541889,0,0,1340.987433172585 -8943,10953,19996,19998,-9,-9,2,1,1,52,1,0,2,0,2,-9,1,1,0,0,3,8.75727011668504,9.073195507911363,0,2,0,-9,5,0,19,-17.7586838666136,0,0,0,0,33,2,4,1,2,2,2019,1,1,20,8,60,60,15,1,1,1,0,10.32518701580785,10.32518701580785,0,0,0,0,0,0,0,0,1,1,0,6.449386859756234,0,0,0,41.87,56.48,48,56,1,1,1,0,0,8.083333333333334,8,4,1,1053,193052.9061597089,0,0,4768.675911008469 -8943,10953,19997,-9,19998,19996,4,1,0,5,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1043.258624058772,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,8,4,1,1053,193052.9061597089,0,0,4768.675911008469 -8943,10953,19998,19996,-9,-9,1,1,0,33,1,0,2,0,2,-9,2,1,0,0,4,7.991647322360127,7.924677825861115,0,2,0,-9,5,0,-19,76.54989880962191,0,0,1,0,52,2,3,1,1,-9,2019,1,2,11,2,26,18,15,1,0,1,0,10.63986576816595,10.63986576816595,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48,56,41.87,56.48,5,1,1,0,0,1,8,4,1,1053,193052.9061597089,0,0,4768.675911008469 -8944,10954,19999,-9,-9,-9,1,1,0,69,2,0,0,0,1,-9,97,3,0,1,1,0,8.803518568264359,8.53552594750062,3,0,0,0,-9,0,-934.9070639345405,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,21,9,0,0,15,3,1,-9,0,0,0,1,9.628664421177461,0,0,0,0,77.32685204805961,2,1,1,0,0,8.81377311287306,11.17252930275414,3,51.32,24.19,-9,-9,6,1,1,0,0,1.166666666666667,10,5,1,587,1752152.282536368,0,0,3051.064204786573 -8945,10955,20000,20001,-9,-9,1,1,0,37,1,0,0,0,2,-9,2,1,0,0,4,8.026024642835411,8.032963112904696,0,1,0,-9,7,0,-2,-55.25750970201452,0,0,1,0,39,2,5,1,2,2,2019,1,2,8,0,40,43,15,1,0,1,0,12.03442380073575,12.03442380073575,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.49,47.77,57.06,57.76,6,1,1,0,0,5.75,2,4,1,883.5,108551.6570592965,0,0,2872.756554918767 -8945,10955,20001,20000,-9,-9,2,1,1,39,1,0,0,0,2,-9,1,1,0,0,5,7.474002616024236,7.791093302504221,0,1,0,-9,7,0,2,74.65471968945539,0,0,0,0,37,2,4,1,2,2,2019,1,1,8,1,35,35,15,1,0,1,0,6.218443970496315,6.218443970496315,0,0,0,0,0,0,0,0,0,0,0,6.424214989423803,0,0,0,57.06,57.76,57.49,47.77,2,1,1,0,0,9.166666666666666,2,4,1,883.5,108551.6570592965,0,0,2872.756554918767 -8946,10956,20002,20003,-9,-9,2,1,1,60,1,0,0,0,2,-9,1,1,0,0,3,8.583834708354511,8.624268298419416,5.493612517575346,1,0,-9,31,0,6,19.28216269319471,0,0,0,0,54,2,4,1,-9,-9,2019,1,1,9,0,55,55,15,1,0,1,0,10.9122092323616,10.9122092323616,0,0,0,0,0,0,0,0,0,0,0,5.781950834482865,5.574200380548166,0,0,64.55,36.47,49.74,55.34,4,1,1,0,0,12.83333333333333,7,5,1,370,1564313.345449999,0,0,3143.232610279357 -8946,10956,20003,20002,-9,-9,1,1,0,54,1,0,0,0,2,-9,2,1,0,0,4,7.832931748116932,8.060718125809041,0,1,0,-9,31,0,-6,-8.039241265935532,0,0,0,0,60,2,3,1,-9,-9,2019,1,2,15,5,0,36,15,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49.74,55.34,64.55,36.47,5,1,1,0,0,11.08333333333333,7,5,1,370,1564313.345449999,0,0,3143.232610279357 -8946,10957,20004,-9,20003,20002,3,1,0,25,2,0,0,0,1,-9,2,1,0,0,4,7.866685173441544,7.967141810385194,0,3,0,0,0,-9,0,-1074.752859171243,-9,1,1,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,42,0,15,1,0,-9,1,6.997113334955103,6.997113334955103,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46,58,-9,-9,5,1,1,0,0,5.166666666666667,7,3,1,450,-295526.7607124601,0,0,855.1006119460176 -8946,10958,20005,-9,20003,20002,4,1,1,21,2,0,0,0,2,-9,2,1,0,0,4,7.808159335426622,7.993001346159653,0,3,0,0,0,-9,0,-946.7906531232503,0,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,0,38,35,15,1,0,-9,1,9.458742389378097,9.458742389378097,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.42,50.46,-9,-9,4,1,1,0,0,5.333333333333333,7,4,1,387,-87919.19434456456,0,0,833.6933428988966 -8947,10959,20006,-9,-9,-9,1,1,1,45,2,0,0,0,2,-9,2,1,0,0,4,8.76609742443263,9.149183868833887,0,3,0,-9,0,1,0,-1066.035220545285,0,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,13,2,40,40,15,1,0,-9,0,24.8463391295355,24.8463391295355,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.72,63.16,-9,-9,6,1,1,0,0,9.083333333333334,8,5,1,310,-29469.22167387596,0,0,3399.654117773713 -8948,10960,20007,-9,-9,-9,1,1,0,63,2,0,0,0,3,-9,4,3,0,0,1,0,7.434308877309754,6.976769953576552,3,0,0,0,-9,0,-964.7062607747293,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,16,4,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.194737670784008,0,0,30.82,26.77,-9,-9,3,1,1,0,1,3,5,3,1,1230,155970.1880474649,0,0,1204.826797328471 -8949,10961,20008,-9,-9,-9,1,1,1,86,2,0,0,0,3,-9,4,3,0,0,3,0,6.18456592145417,5.7677684702579,3,0,0,0,-9,0,-1021.072418751077,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.2897366353402155,5.55049516075178,0,0,45.15,49.59,-9,-9,4,1,1,0,0,0,11,2,1,356,366471.0518494908,0,0,-34.7606182054601 -8950,10962,20009,-9,-9,-9,1,1,1,74,2,0,0,0,3,-9,4,3,0,0,3,0,6.773677652998842,6.516499570057151,3,0,0,0,-9,0,-971.1090260000326,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,14,4,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.42922066707885,0,0,26.8,53.71,-9,-9,5,1,1,0,0,0,1,2,0,650,192954.5125875786,0,0,928.4138207418814 -8951,10963,20010,20011,-9,-9,1,1,1,57,1,0,0,0,3,-9,1,1,0,0,4,8.883482267572756,8.541814632686483,0,1,0,-9,6,0,2,42.75766856532035,0,0,0,0,55,3,4,3,3,3,2019,2,2,6,0,30,30,15,1,0,3,0,21.22502539562668,21.22502539562668,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,57.16,56.15,6,2,3,0,0,8.666666666666666,4,4,1,625.5,967633.1187054927,0,0,2222.42731401081 -8951,10963,20011,20010,-9,-9,2,1,0,55,1,0,0,0,3,-9,6,3,0,0,4,0,0,0,1,0,-9,6,0,-2,-82.22165055899144,0,0,0,0,57,3,4,1,-9,-9,2019,3,1,6,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,27.5,1,1,0,0,0,30.42225812137928,3,57.16,56.15,57.16,56.15,6,2,3,0,0,0,4,4,1,625.5,967633.1187054927,0,0,2222.42731401081 -8951,10964,20012,-9,20011,20010,4,1,0,25,2,0,0,0,2,-9,3,3,0,0,2,0,0,0,3,0,0,0,-9,0,-997.8162342923047,0,1,1,0,-9,-9,-9,-9,3,3,2019,-9,0,17,6,0,20,15,3,1,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,38.05,51.86,-9,-9,2,2,3,1,0,0,4,1,1,2702,0,0,0,0 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-8970,10989,20050,-9,20051,20052,4,1,1,1,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1131.909254524109,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,2,3,0,0,0,2,3,1,447.5,87319.04361452709,0,0,2690.869596870626 -8970,10989,20051,20052,-9,-9,2,1,0,31,1,1,2,0,2,-9,2,1,0,0,4,7.03896042192074,6.727729734238898,0,2,0,-9,11,0,1,-60.94088451453795,0,0,1,0,30,2,4,1,3,2,2019,1,1,13,1,14,22,15,1,0,1,0,7.880191365083456,7.880191365083456,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.77,61.04,51.49,57.57,5,2,3,0,0,3.416666666666667,2,3,1,447.5,87319.04361452709,0,0,2690.869596870626 -8970,10989,20052,20051,-9,-9,1,1,1,30,1,1,2,0,2,-9,2,1,0,0,4,8.008155114582582,8.234569504296356,0,2,0,-9,11,0,-1,25.56043692491517,0,0,0,0,31,2,4,1,3,2,2019,1,2,8,1,70,66,15,1,0,1,0,4.755946856213756,4.755946856213756,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.49,57.57,40.77,61.04,4,2,3,0,0,6.583333333333333,2,3,1,447.5,87319.04361452709,0,0,2690.869596870626 -8971,10990,20053,-9,-9,-9,1,1,0,67,2,0,0,0,2,-9,4,3,0,0,2,0,5.500834804174791,5.752273633984561,3,0,0,0,-9,0,-1094.410948756255,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,6.081086120778964,0,0,53.94,45.89,-9,-9,5,1,1,0,0,5.583333333333333,2,2,1,959,76237.55806792575,0,0,577.5152890243528 -8972,10991,20054,-9,-9,-9,1,1,0,39,2,1,1,0,1,-9,2,1,0,0,4,8.822117987198222,8.696551889539206,0,4,0,0,0,-9,0,-949.6603697354753,0,0,1,0,-9,-9,-9,-9,1,1,2019,-9,0,9,0,40,24,15,1,0,-9,0,17.26315215863824,17.26315215863824,0,0,0,0,0,0,0,0,1,1,0,1.717555676392628,0,0,0,48.87,58.55,-9,-9,6,1,1,0,0,7.75,12,4,1,465.5,73414.11210285631,0,0,2669.475184614814 -8972,10991,20055,-9,20054,-9,2,1,1,2,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1044.968971951505,-9,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,12,4,1,465.5,73414.11210285631,0,0,2669.475184614814 -8973,10992,20056,-9,-9,-9,1,1,1,37,2,0,0,0,1,-9,2,1,0,1,2,8.827445963508511,8.537142128873482,0,3,0,0,0,-9,0,-974.0865479846868,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,0,40,37,15,1,0,-9,0,14.88420268882226,14.88420268882226,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.79,30.76,-9,-9,6,1,1,0,0,7.416666666666667,12,5,1,497,-82900.9218879221,0,0,2247.259495580573 -8974,10993,20057,-9,20059,20061,4,1,1,10,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-954.8502901646885,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,11,2,1,917,337792.443917975,0,0,743.7777773139858 -8974,10993,20058,-9,20059,20061,5,1,0,7,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1054.205605848516,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,11,2,1,917,337792.443917975,0,0,743.7777773139858 -8974,10993,20059,20061,-9,-9,1,1,0,45,1,0,3,0,2,-9,2,1,0,0,4,7.203249603413624,7.435007009300966,0,2,0,-9,13,0,-12,60.17806892419757,0,0,0,0,57,2,1,3,3,-9,2019,2,2,7,0,24,44,15,1,0,3,0,7.326511654204753,7.326511654204753,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.83,57.2,19.98,32.97,6,1,1,0,0,7,11,2,1,917,337792.443917975,0,0,743.7777773139858 -8974,10993,20060,-9,20059,20061,3,1,1,14,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-920.996238994064,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,11,2,1,917,337792.443917975,0,0,743.7777773139858 -8974,10993,20061,20059,-9,-9,2,1,1,57,1,0,3,0,2,-9,3,3,0,0,1,0,0,0,2,0,-9,7,0,12,-61.82698258986483,0,0,0,0,45,2,4,1,-9,-9,2019,3,1,31,12,0,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,19.98,32.97,51.83,57.2,3,1,1,1,0,7.833333333333333,11,2,1,917,337792.443917975,0,0,743.7777773139858 -8975,10994,20062,20063,-9,-9,1,1,1,30,1,0,0,0,2,-9,2,1,0,0,3,8.794493982501967,8.636874336507393,0,1,0,-9,2,0,5,-59.33902772187068,0,0,0,0,25,2,4,1,2,2,2019,1,2,20,8,45,40,15,1,1,1,0,18.19616355690194,18.19616355690194,0,0,0,0,0,0,0,0,0,0,0,6.940435695374109,0,0,0,20,62.76,48.87,58.55,6,1,1,0,0,8.333333333333334,9,5,1,778,445512.2507349909,0,0,4553.03937417625 -8975,10994,20063,20062,-9,-9,2,1,0,25,1,0,0,0,2,-9,2,1,0,0,4,8.302107175367329,8.195945211930674,0,1,0,-9,2,0,-5,-131.7604687201614,0,1,1,0,30,2,3,1,-9,-9,2019,1,1,8,0,45,40,15,1,0,1,0,12.73549385256901,12.73549385256901,0,0,0,0,0,0,0,0,0,0,0,8.018234621108142,0,0,0,48.87,58.55,20,62.76,2,1,1,0,0,3.916666666666667,9,5,1,778,445512.2507349909,0,0,4553.03937417625 -8976,10995,20064,20065,-9,-9,2,1,1,50,1,0,0,0,1,-9,2,1,0,0,2,8.751468617678835,8.603427520773696,0,1,0,-9,9,0,4,53.32476299724674,0,0,0,0,46,2,4,1,-9,-9,2019,1,1,11,0,37,37,15,1,0,1,0,19.73672371086936,19.73672371086936,0,0,0,0,0,0,0,0,0,0,0,2.345960540864313,0,0,0,37.03,52.5,55.3,55.6,3,1,1,0,0,7.916666666666667,1,5,1,571.5,297330.7647206641,0,0,2346.616593281649 -8976,10995,20065,20064,-9,-9,1,1,0,46,1,0,0,0,2,-9,2,1,0,0,4,7.496073110888857,7.477737690689822,0,1,0,-9,27,0,-4,68.14123520121245,0,0,0,0,50,1,2,1,3,-9,2019,1,2,7,0,28,18,15,1,0,1,0,8.385080916783219,8.385080916783219,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.3,55.6,37.03,52.5,7,1,1,0,0,11.91666666666667,1,5,1,571.5,297330.7647206641,0,0,2346.616593281649 -8977,10996,20066,-9,-9,-9,1,1,1,43,2,0,0,0,1,-9,2,1,0,0,5,8.655150066168419,8.690275970704032,0,3,0,-9,0,-9,0,-1016.140207258129,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,0,50,0,15,1,0,-9,0,17.58424640942943,17.58424640942943,0,0,0,0,0,0,0,0,0,0,0,5.406255950167881,0,0,0,48.18,61.8,-9,-9,6,1,1,0,0,8.916666666666666,1,5,0,624,618709.2312082743,0,0,2718.663102187893 -8978,10997,20067,-9,-9,-9,1,1,1,71,2,0,0,0,3,-9,4,3,0,0,4,0,0,0,3,0,0,0,-9,0,-1018.326753907158,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.11,56.11,-9,-9,7,1,1,0,0,4.833333333333333,12,1,0,513,221202.2548469373,0,0,1240.960371252869 -8979,10998,20068,20069,-9,-9,2,1,0,29,1,0,0,0,1,-9,3,3,0,0,5,8.493678900433023,8.62467134571278,0,1,0,-9,4,0,0,-78.33379025507664,0,1,1,0,29,2,4,1,-9,-9,2019,3,1,13,3,40,39,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,.5715827090643424,0,0,0,43.38,62.58,40.58,60.95,5,1,1,1,0,7.083333333333333,4,5,1,266,58711.21108019623,0,0,4067.022683069483 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-9026,11060,20186,-9,20185,20184,3,1,1,7,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-978.4490790652167,-9,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,10,1,0,842.6666666666666,83611.58911793427,0,0,1736.871104786994 -9027,11061,20187,20189,-9,-9,1,1,1,43,1,0,2,0,2,-9,1,1,0,0,2,7.47301680861688,8.101634830441927,0,2,0,-9,21,0,5,-1.651164746631033,0,0,0,0,38,3,5,1,2,2,2019,1,2,9,0,55,55,15,1,0,1,0,4.033765632194747,4.033765632194747,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.97,40.34,62.39,56.71,6,2,3,0,0,7.5,8,3,0,805.75,80905.13114216892,0,0,2600.754958453632 -9027,11061,20188,-9,20189,20187,3,1,1,17,2,0,2,1,2,0,7,2,0,0,4,0,0,0,2,0,0,0,-9,0,-955.9679490818231,-9,1,0,0,-9,-9,-9,-9,3,2,2019,-9,0,7,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,-9,-9,6,2,3,0,0,0,8,3,0,805.75,80905.13114216892,0,0,2600.754958453632 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-9029,11063,20192,20195,-9,-9,2,1,0,33,1,1,2,0,1,-9,5,1,0,0,4,8.340530708905947,8.268418671739301,0,2,0,-9,3,0,0,42.62472973351653,0,0,1,1,33,1,4,1,-9,-9,2019,1,1,7,0,40,40,15,1,0,1,0,14.7236506138137,14.7236506138137,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,62.49,55.09,46.98,59.35,6,3,4,0,0,2.416666666666667,6,4,1,830.5,158779.5887039685,0,0,3430.449090494618 -9029,11063,20193,-9,20192,20195,3,1,1,3,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1062.267214434768,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,3,4,0,0,0,6,4,1,830.5,158779.5887039685,0,0,3430.449090494618 -9029,11063,20194,-9,20192,20195,4,1,0,0,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-923.8979602721886,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,3,4,0,0,0,6,4,1,830.5,158779.5887039685,0,0,3430.449090494618 -9029,11063,20195,20192,-9,-9,1,1,1,33,1,1,2,0,1,-9,2,1,0,0,4,8.487286746770431,8.100235808318994,0,2,0,-9,3,0,0,27.24629605670527,0,0,0,1,33,1,4,1,2,1,2019,1,2,9,0,38,40,15,1,0,1,0,10.96593196003577,10.96593196003577,0,0,0,0,0,0,0,0,1,1,0,1.452408117701404,0,0,0,46.98,59.35,62.49,55.09,6,3,4,0,0,6.083333333333333,6,4,1,830.5,158779.5887039685,0,0,3430.449090494618 -9030,11064,20196,-9,-9,-9,1,1,0,62,2,0,0,0,2,-9,4,3,0,1,1,0,6.89230954007984,6.699434858047632,3,0,0,0,-9,0,-1124.896359069829,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,18,6,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.561701402404116,6.795289996586185,0,0,47.27,11.36,-9,-9,3,1,1,0,0,0,9,2,1,3864,111824.7320545849,0,0,1494.759792329943 -9031,11065,20197,-9,20199,-9,3,1,1,13,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1003.929419267504,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,59,-9,-9,5,1,1,0,0,0,2,3,0,359,326164.0540719889,0,0,2068.78560230322 -9031,11065,20198,-9,20199,-9,2,1,0,16,2,0,2,1,3,-9,7,2,0,0,2,0,0,0,4,0,0,0,-9,0,-885.675646412481,-9,1,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,8,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,42.53,-9,-9,6,1,1,0,0,0,2,3,0,359,326164.0540719889,0,0,2068.78560230322 -9031,11065,20199,-9,-9,-9,1,1,0,46,2,0,2,0,3,-9,1,1,0,0,5,7.566377553129886,7.934630852450647,6.688368287869899,4,0,0,0,-9,0,-1041.118258683082,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,0,30,30,15,1,0,-9,0,7.604977901165757,7.604977901165757,0,0,0,0,0,0,0,0,1,1,0,6.500221593249718,0,0,0,38.8,57.71,-9,-9,6,1,1,0,0,8.083333333333334,2,3,0,359,326164.0540719889,0,0,2068.78560230322 -9032,11066,20200,-9,-9,-9,1,1,0,40,2,0,3,0,2,-9,2,1,0,1,4,6.342787246541564,6.79935767999191,0,4,0,0,0,-9,0,-1064.19481671495,0,0,1,0,-9,-9,-9,-9,2,3,2019,-9,0,9,1,12,12,15,1,0,-9,0,6.421104982622715,6.421104982622715,0,0,0,0,0,0,0,114,1,1,0,0,0,124.0774640123406,3,59.47,44.13,-9,-9,5,1,1,0,0,8.333333333333334,13,2,0,2183,97052.47313341062,0,0,1692.909995601919 -9032,11066,20201,-9,20200,-9,4,1,1,5,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1129.4130739327,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,13,2,0,2183,97052.47313341062,0,0,1692.909995601919 -9033,11067,20202,20206,-9,-9,1,1,1,32,1,0,4,0,2,-9,2,1,0,0,3,8.11681058137134,8.207632964393301,0,2,0,-9,10,0,1,86.24615775909648,0,0,0,0,31,2,3,1,3,-9,2019,1,2,24,10,0,55,15,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43.19,44.86,46.08,57.2,6,1,1,0,0,8.5,7,3,0,486.4,234353.9238808057,0,0,3782.520771474837 -9033,11067,20203,-9,20206,20202,4,1,0,7,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1018.820588602263,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,60,-9,-9,5,1,1,0,0,0,7,3,0,486.4,234353.9238808057,0,0,3782.520771474837 -9033,11067,20204,-9,20206,20202,5,1,1,5,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1057.012408695468,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,7,3,0,486.4,234353.9238808057,0,0,3782.520771474837 -9033,11067,20205,-9,20206,20202,6,1,0,3,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-931.2775038584645,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,7,3,0,486.4,234353.9238808057,0,0,3782.520771474837 -9033,11067,20206,20202,-9,-9,2,1,0,31,1,0,4,0,2,-9,2,1,0,0,3,7.593488450805358,7.451903091247334,0,2,0,-9,10,0,-1,141.2095466313929,0,0,1,0,32,2,3,1,2,3,2019,1,1,15,3,25,25,15,1,0,1,0,8.347056459201157,8.347056459201157,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.08,57.2,43.19,44.86,6,1,1,0,0,6.166666666666667,7,3,0,486.4,234353.9238808057,0,0,3782.520771474837 -9034,11068,20207,-9,-9,-9,1,1,0,50,2,0,0,0,2,-9,2,1,0,0,3,7.741029775420023,7.688938643891807,0,3,0,-9,0,1,0,-973.034360890076,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,13,2,30,16,15,1,0,-9,0,8.1009059240609,8.1009059240609,0,0,0,0,0,0,0,0,0,0,0,3.399087532948999,0,0,0,42.63,54.83,-9,-9,5,1,1,0,0,10.5,9,3,1,1610,251832.4237507914,0,0,1021.083616429014 -9034,11069,20208,-9,20207,-9,2,1,0,19,2,0,0,0,2,-9,2,1,0,0,5,7.610710351374638,7.397989438492062,0,3,0,0,0,-9,0,-1053.475148907414,0,1,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,18,6,34,38,15,1,1,-9,1,5.77858372593424,5.77858372593424,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,31.3,62.97,-9,-9,4,1,1,0,0,3.583333333333333,9,3,1,479,-84178.65910405619,0,0,334.1259807671282 -9035,11070,20209,-9,-9,-9,1,1,0,22,2,0,0,0,2,-9,3,3,0,0,3,0,0,0,3,0,-9,0,-9,0,-881.2748649757802,-9,1,1,1,-9,-9,-9,-9,-9,-9,2019,-9,0,6,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,64.64,48.76,-9,-9,7,1,1,1,0,0,6,1,0,606,66290.61240679417,0,0,1170.224048347401 -9035,11071,20210,-9,-9,-9,3,1,0,45,2,0,0,0,3,-9,8,3,1,1,1,0,0,0,3,0,-9,0,-9,0,-953.1596627253776,-9,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,26,10,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,20.2,28.78,-9,-9,1,1,1,0,1,0,6,1,0,420,-178594.7468777916,0,0,794.6088594967056 -9035,11072,20211,-9,20210,-9,4,1,0,21,2,0,0,0,2,-9,3,3,0,0,3,0,0,0,3,0,-9,0,-9,0,-865.1861100549469,-9,1,1,0,-9,-9,-9,-9,3,-9,2019,-9,0,25,9,0,0,15,3,1,-9,1,0,0,0,0,0,0,0,0,0,27.5,1,1,0,0,0,20.93675900451362,3,42,54,-9,-9,3,1,1,1,1,0,6,1,0,685,0,0,0,1075.593010531558 -9035,11073,20212,-9,20210,-9,5,1,0,19,2,0,0,0,2,-9,2,1,0,0,4,6.870823120691744,6.780060767776475,0,3,0,-9,0,-9,0,-951.5427218470386,-9,1,1,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,1,14,0,15,1,0,-9,1,6.913884312703225,6.913884312703225,0,0,0,0,0,0,0,7,1,1,0,0,0,10.09350945866547,3,44.47,57.73,-9,-9,4,4,2,0,0,2.166666666666667,6,2,0,246,-18271.05210110835,0,0,-759.2852974939234 -9035,11074,20213,-9,20210,-9,6,1,0,23,2,0,0,0,2,-9,3,3,0,1,1,0,0,0,3,0,-9,0,-9,0,-1022.199892664995,-9,1,1,0,-9,-9,-9,-9,3,-9,2019,-9,0,33,12,0,0,15,3,1,-9,1,0,0,0,0,0,0,0,0,0,71.5,1,1,0,0,0,76.20933140483274,3,14.81,31.2,-9,-9,1,1,1,1,1,0,6,1,0,1135,-201517.4315559814,0,0,2180.788411354882 -9035,11075,20214,-9,20210,-9,2,1,1,25,2,0,0,0,3,-9,1,1,0,0,2,0,0,0,3,0,-9,0,-9,0,-967.9867484851826,-9,1,0,1,-9,-9,-9,-9,3,-9,2019,-9,0,25,10,0,0,15,1,1,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43.18,42.37,-9,-9,3,1,1,0,0,3.416666666666667,6,1,0,812,0,0,0,0 -9036,11076,20215,-9,20217,20216,4,1,0,7,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1047.086537363535,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,2,3,0,0,0,8,2,0,527.25,64794.76126713975,0,0,2070.443668514893 -9036,11076,20216,20217,-9,-9,2,1,1,41,1,0,2,0,3,-9,2,1,0,0,4,7.223529497621984,7.001042646608496,0,2,0,-9,12,0,1,-53.77198019167108,0,0,0,0,40,3,3,3,2,2,2019,2,1,9,1,24,24,15,1,0,3,0,6.377468178073924,6.377468178073924,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,55,49.51,41.82,5,2,3,0,1,3.25,8,2,0,527.25,64794.76126713975,0,0,2070.443668514893 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-9065,11111,20275,20274,-9,-9,1,1,1,49,1,0,0,0,2,-9,2,1,0,0,3,8.855798365275449,8.545052996079304,0,1,0,-9,26,0,1,167.4544183095876,0,0,0,0,48,2,2,1,2,3,2019,1,2,7,0,54,54,15,1,0,1,0,10.17938160748111,10.17938160748111,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.29,52.11,35.78,44.58,6,1,1,0,0,11.58333333333333,5,5,1,232,-39502.43053122961,0,0,3901.768529625784 -9065,11112,20276,-9,20274,20275,3,1,1,20,2,0,0,0,2,1,2,1,0,0,5,7.956585848898508,7.853109828219917,0,3,0,0,0,-9,0,-1132.796090975743,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,9,3,44,0,15,1,0,-9,1,6.635474551057149,6.635474551057149,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.69,57.47,-9,-9,1,1,1,0,0,1.083333333333333,5,4,1,306,-61872.53121327005,0,0,1150.403410109727 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-9066,11114,20279,-9,20278,20277,3,1,1,22,2,0,0,0,1,-9,2,1,0,0,5,7.934538154165693,8.435228550000785,0,3,0,0,0,-9,0,-992.0128061171209,0,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,6,0,50,41,15,1,0,-9,1,6.488918621206514,6.488918621206514,0,0,0,0,0,0,0,0,0,0,0,.1581528205973481,0,0,0,48.77,60.16,-9,-9,6,1,1,0,0,1.666666666666667,10,4,1,933,-46.04064650338842,0,0,1729.62219104672 -9066,11115,20280,-9,20278,20277,4,1,1,19,2,0,0,1,2,0,7,2,0,0,4,0,0,0,3,0,0,0,-9,0,-921.3473639325496,-9,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48,59,-9,-9,5,1,1,0,0,0,10,1,1,1319,66991.69892899583,0,0,680.823751393437 -9067,11116,20281,20282,-9,-9,1,1,1,30,1,0,0,0,2,-9,2,1,0,0,4,0,0,0,1,0,-9,3,0,-1,-56.46317615052315,0,0,0,0,31,2,3,1,-9,-9,2019,1,2,9,0,0,60,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.36153340310389,0,0,0,44.81,57.83,44,52,6,1,1,0,0,7.25,10,5,1,2104,-231552.8996280273,0,0,2822.306783507102 -9067,11116,20282,20281,-9,-9,2,1,0,31,1,0,0,0,2,-9,2,1,0,0,3,8.792224702838107,9.078290586809542,0,1,0,-9,3,0,1,42.7065084882521,-9,0,1,0,30,2,4,1,-9,-9,2019,1,1,9,1,40,0,15,1,0,1,0,26.18117867867479,26.18117867867479,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,52,44.81,57.83,2,1,1,0,0,2.666666666666667,10,5,1,2104,-231552.8996280273,0,0,2822.306783507102 -9068,11117,20283,20284,-9,-9,1,1,1,44,1,0,0,0,3,-9,2,1,0,0,5,8.791074125383599,8.766775256464664,0,1,0,-9,5,0,0,-95.52206896743404,0,0,0,0,44,2,3,1,2,3,2019,1,2,8,0,50,52,15,1,0,1,0,13.50753072672079,13.50753072672079,0,0,0,0,0,0,0,0,0,0,0,7.590920174338324,0,0,0,54.1,59.11,51.66,49.35,5,1,1,0,0,6.416666666666667,11,5,1,293.5,2534090.708534294,0,0,5154.598705156994 -9068,11117,20284,20283,-9,-9,2,1,0,44,1,0,0,0,2,-9,2,1,0,0,3,8.288798037765421,8.375788057452612,0,1,0,-9,5,0,0,-47.97564989770832,0,0,1,0,44,3,5,1,2,3,2019,1,1,12,0,47,45,15,1,0,1,0,11.93499383392956,11.93499383392956,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.66,49.35,54.1,59.11,6,1,1,0,0,6.416666666666667,11,5,1,293.5,2534090.708534294,0,0,5154.598705156994 -9068,11118,20285,-9,20284,20283,3,1,0,21,2,0,0,0,2,-9,2,1,0,0,4,7.621144413325008,7.807395778002521,0,3,0,0,0,-9,0,-974.5924089242682,0,1,1,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,36,48,15,1,0,-9,1,6.159090328610277,6.159090328610277,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47,58,-9,-9,5,1,1,0,0,1,11,3,1,843,-233356.7114230537,0,0,852.625258161892 -9069,11119,20286,20287,-9,-9,2,1,1,57,1,0,0,0,2,-9,2,1,0,0,4,8.712406094193957,8.868230832699995,0,1,0,-9,29,0,0,-30.97584027359412,0,0,0,0,57,2,4,3,-9,-9,2019,2,1,6,0,45,43,15,1,0,3,0,15.52525975399838,15.52525975399838,0,0,0,0,0,0,0,0,0,0,0,4.651118155319714,0,0,0,57.16,56.15,39.99,62.58,6,1,1,0,0,8.333333333333334,10,4,1,389.5,229393.2077964921,0,0,2460.580557394969 -9069,11119,20287,20286,-9,-9,1,1,0,57,1,0,0,0,2,-9,6,3,0,0,4,0,0,0,1,0,-9,29,0,0,55.28272762679588,0,0,0,0,57,2,4,1,3,2,2019,3,2,11,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5.542596300234607,0,0,0,39.99,62.58,57.16,56.15,4,1,1,0,0,0,10,4,1,389.5,229393.2077964921,0,0,2460.580557394969 -9070,11120,20288,20289,-9,-9,1,1,1,62,1,0,0,0,3,-9,2,1,0,0,2,0,6.764804715025555,6.647758237371687,1,0,-9,9,0,1,63.56292773981365,0,0,0,0,61,2,4,2,3,3,2019,2,2,18,6,0,35,15,1,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.950294095610807,0,0,28.78,45.18,46.63,59.72,3,1,1,0,0,9.75,11,2,1,443.5,188740.8579898929,0,0,1757.584538723495 -9070,11120,20289,20288,-9,-9,2,1,0,61,1,0,0,0,2,-9,7,2,0,0,4,0,0,0,1,0,-9,9,0,-1,-4.414527789827872,1,0,0,0,62,3,2,1,3,3,2019,3,1,13,2,0,35,15,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46.63,59.72,28.78,45.18,6,1,1,0,0,9.083333333333334,11,2,1,443.5,188740.8579898929,0,0,1757.584538723495 -9071,11121,20290,-9,-9,-9,1,1,0,85,2,0,0,0,3,-9,4,3,0,0,3,0,6.698315840385612,6.629607176557564,3,0,0,0,-9,0,-959.8023519338448,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,10,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.653583029269363,0,0,52,45,-9,-9,6,1,1,0,0,0,2,2,1,186,505005.5556793542,0,0,820.9326379276336 -9072,11122,20291,20292,-9,-9,2,1,1,49,1,0,2,0,2,-9,2,1,0,0,4,8.591712120375275,8.851445836950198,0,2,0,-9,22,0,8,-55.41496247884984,-9,0,0,0,41,2,4,3,-9,-9,2019,2,1,9,1,40,0,15,1,0,3,0,20.61897045103139,20.61897045103139,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,55,40.39,60.98,6,2,3,0,0,1,2,5,1,942.6666666666666,885939.7772747477,0,0,5788.024735365063 -9072,11122,20292,20291,-9,-9,1,1,0,41,1,0,2,0,2,-9,6,3,0,0,4,9.134374099240702,9.129563728966994,0,2,0,-9,23,0,-8,-.2937178718658274,0,0,1,0,49,2,4,1,3,3,2019,3,2,15,4,10,0,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.39,60.98,52,55,4,2,3,0,0,4.833333333333333,2,5,1,942.6666666666666,885939.7772747477,0,0,5788.024735365063 -9072,11122,20293,-9,20292,20291,4,1,0,15,2,0,2,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-943.3922556078645,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48,61,-9,-9,6,2,3,0,0,0,2,5,1,942.6666666666666,885939.7772747477,0,0,5788.024735365063 -9073,11123,20294,-9,-9,-9,1,1,0,41,2,0,0,0,3,-9,2,1,0,0,3,7.875034229269926,7.935742841152266,0,3,0,0,0,-9,0,-906.0399572739659,0,0,1,0,-9,-9,-9,-9,3,2,2019,-9,0,4,0,42,28,15,1,0,-9,0,9.878020218550168,9.878020218550168,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.92,51.82,-9,-9,6,3,4,0,0,9.083333333333334,8,4,0,981,25099.03604053947,0,0,1988.922887304916 -9074,11124,20295,20296,-9,-9,2,1,0,75,1,0,0,0,2,-9,4,3,0,0,4,0,5.777190903132232,5.614699183166101,1,0,-9,10,0,-7,32.94548389464396,0,0,0,0,82,3,2,1,2,3,2019,3,1,7,0,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.127071886548691,5.943533150657965,0,0,52.43,55.57,58.91,35.36,6,1,1,0,0,0,13,3,1,810,547087.2402850342,0,0,2710.769878757618 -9074,11124,20296,20295,-9,-9,1,1,1,82,1,0,0,0,3,-9,1,1,0,0,2,7.5487326805703,7.338691580079082,0,1,0,-9,10,0,7,-33.20114385873973,0,0,0,0,75,2,4,3,3,3,2019,2,2,7,0,60,60,15,1,0,4,0,4.01808409907143,4.01808409907143,1,0,2.364558957443402,0,0,0,0,0,1,1,0,0,0,0,0,58.91,35.36,52.43,55.57,6,1,1,0,0,12.66666666666667,13,3,1,810,547087.2402850342,0,0,2710.769878757618 -9075,11125,20297,20298,-9,-9,2,1,1,37,1,0,0,0,2,-9,2,1,0,0,4,8.866070144755833,9.054687655815947,0,1,0,-9,1,-9,5,45.68254345861276,-9,0,0,0,32,1,2,1,-9,-9,2019,1,1,11,1,52,0,15,1,0,1,0,16.17722667496511,16.17722667496511,0,0,0,0,0,0,0,0,0,0,0,5.167261648314033,0,0,0,50.91,44.05,55.84,31.4,5,1,1,0,0,5.5,9,5,1,1560,462824.517999392,0,0,4074.773865313424 -9075,11125,20298,20297,-9,-9,1,1,0,32,1,0,0,0,1,-9,2,1,0,0,2,8.190495987756675,8.305724665395273,0,1,0,1,1,-9,-5,74.76290947062775,0,0,1,0,37,2,4,1,2,-9,2019,1,2,10,2,42,44,15,1,0,1,0,10.71109674612774,10.71109674612774,0,0,0,0,0,0,0,0,0,0,0,1.175130162579535,0,0,0,55.84,31.4,50.91,44.05,6,1,1,0,0,9.083333333333334,9,5,1,1560,462824.517999392,0,0,4074.773865313424 -9076,11126,20299,20300,-9,-9,2,1,0,73,1,0,0,0,2,-9,4,3,0,0,4,0,0,0,1,0,-9,45,0,-8,29.02636079353946,0,0,0,0,81,2,1,3,2,-9,2019,4,1,8,1,0,0,15,4,0,4,0,0,0,1,0,1.731283964725549,0,0,0,39.69536968601152,74.5,1,1,0,3.190730480777528,0,71.19452880794951,1,61.27,46.03,58.35,15.54,6,1,1,0,0,0,9,3,1,605.5,1077885.200030509,0,0,2643.849657054726 -9076,11126,20300,20299,-9,-9,1,1,1,81,1,0,0,0,2,-9,4,3,0,0,1,0,8.194631339216544,7.759078628876488,1,0,-9,45,0,8,136.9115829644022,0,0,0,0,73,2,4,3,2,3,2019,4,2,8,1,0,0,15,4,0,4,0,0,0,1,0,3.09675601242231,0,8.053664791565033,3.679319241566342,0,0,1,1,0,2.166154844239832,7.855998004788001,0,0,58.35,15.54,61.27,46.03,6,1,1,0,0,0,9,3,1,605.5,1077885.200030509,0,0,2643.849657054726 -9077,11127,20301,-9,-9,-9,1,1,1,21,2,0,0,0,2,-9,7,2,0,0,3,6.840144967956173,6.767208699085225,0,1,0,1,1,-9,-17,86.13536079110315,1,1,0,0,-9,-9,-9,-9,2,2,2019,3,2,20,8,16,56,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,34.26,58.61,44.26,59.43,6,1,1,0,0,2.166666666666667,9,4,0,306,1728.233062400474,0,0,1224.69409592343 -9077,11128,20302,-9,-9,-9,2,1,1,38,2,0,0,0,1,-9,2,1,0,0,4,8.466990380251175,8.88540177218181,0,1,0,-9,1,-9,17,11.52170976180867,-9,0,0,0,-9,-9,-9,-9,-9,-9,2019,2,1,16,6,37,0,15,1,1,-9,0,22.64240714678066,22.64240714678066,0,0,0,0,0,0,0,0,0,0,0,7.418727180237787,0,0,0,44.26,59.43,34.26,58.61,6,1,1,0,0,.1666666666666667,9,4,0,478,461753.6529413026,0,0,2497.519694641447 -9078,11129,20303,-9,-9,-9,1,1,0,60,2,0,0,0,1,-9,2,1,0,0,4,9.067201286503657,8.813838042566575,4.630312394705891,3,0,0,0,-9,0,-972.3165766690998,0,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,7,0,50,55,15,1,0,-9,0,17.59113699772172,17.59113699772172,0,0,0,0,0,0,0,0,1,1,0,0,4.888777213989518,0,0,57.16,56.15,-9,-9,7,1,1,0,0,9.083333333333334,12,5,0,278,1325632.761231041,0,0,2779.0080156105 -9079,11130,20304,-9,-9,-9,1,1,0,59,2,0,0,0,2,-9,4,3,0,0,3,0,6.953082606525423,6.932423948655106,3,0,0,0,-9,0,-1126.423153706946,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.508688609898535,0,0,0,52.33,44.67,-9,-9,6,1,1,0,0,0,12,2,1,1929,284302.5316387479,0,0,1384.480571476848 -9080,11131,20305,20310,-9,-9,2,1,0,36,1,0,4,0,3,-9,6,3,0,0,4,0,0,0,2,0,-9,15,0,-3,2.700109677261103,-9,0,1,0,39,2,4,1,3,3,2019,3,1,11,2,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49,56,51,56,5,2,3,0,0,0,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9080,11131,20306,-9,20305,20310,5,1,1,11,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-962.4825668409712,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,2,3,0,0,0,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9080,11131,20307,-9,20305,20310,3,1,1,16,2,0,4,1,3,-9,7,2,0,0,5,0,0,0,2,0,0,0,-9,0,-963.2030178883189,-9,1,0,0,-9,-9,-9,-9,3,2,2019,-9,0,6,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,70.29000000000001,42.14,-9,-9,7,2,3,0,0,0,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9080,11131,20308,-9,20305,20310,6,1,0,5,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1011.557301313253,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,2,3,0,0,0,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9080,11131,20309,-9,20305,20310,4,1,1,13,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-958.0046293766312,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,2,3,0,0,0,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9080,11131,20310,20305,-9,-9,1,1,1,39,1,0,4,0,2,-9,2,1,0,0,4,7.645779480748869,7.899541190063998,0,2,0,-9,15,0,3,-8.815494584929422,0,0,0,0,36,3,4,3,-9,-9,2019,2,2,9,1,45,32,15,1,0,3,0,5.32519266846013,5.32519266846013,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51,56,49,56,6,2,3,0,0,7.916666666666667,8,2,0,368.5,14362.31846909859,0,0,2499.167813259225 -9081,11132,20311,-9,20312,20313,4,1,0,16,2,0,2,1,2,0,7,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1108.844496752305,-9,1,0,0,-9,-9,-9,-9,1,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,59,-9,-9,5,2,3,0,0,0,8,2,1,438.75,340444.8045889691,0,0,2404.739558935256 -9081,11132,20312,20313,-9,-9,1,1,0,46,1,0,2,0,1,-9,2,1,0,0,4,8.153171433660654,8.128987904923951,0,2,0,-9,25,0,-7,80.022919846523,0,0,0,0,53,3,4,3,-9,-9,2019,2,2,11,0,17,17,15,1,0,3,0,23.7207145163025,23.7207145163025,0,0,0,0,0,0,0,14.5,1,1,0,0,0,15.02607857691266,3,51.49,57.57,53,54,6,2,3,0,0,9.5,8,2,1,438.75,340444.8045889691,0,0,2404.739558935256 -9081,11132,20313,20312,-9,20316,2,1,1,53,1,0,2,0,3,-9,3,3,0,0,4,0,0,0,2,0,-9,5,0,7,-11.98799445774562,0,0,0,0,46,1,4,1,-9,3,2019,3,1,9,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,3,53,54,51.49,57.57,6,2,3,1,0,0,8,2,1,438.75,340444.8045889691,0,0,2404.739558935256 -9081,11132,20314,-9,20312,20313,6,1,1,11,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1077.234814986551,-9,0,0,0,-9,-9,-9,-9,1,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,2,3,0,0,0,8,2,1,438.75,340444.8045889691,0,0,2404.739558935256 -9081,11133,20315,-9,20312,20313,3,1,0,21,2,0,2,0,2,-9,3,3,0,0,3,0,0,0,3,0,0,0,-9,0,-1017.451825149961,0,1,1,0,-9,-9,-9,-9,1,3,2019,-9,0,14,5,0,0,15,3,1,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,61.19,39.41,-9,-9,6,2,3,1,0,0,8,1,1,202,-207918.4547165795,0,0,0 -9081,11134,20316,-9,-9,-9,5,1,1,84,2,0,2,0,3,-9,4,3,0,0,3,0,7.817940537075613,7.351694050194995,4,0,0,0,-9,0,-1001.240250277473,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.6438175308784497,7.814111562248897,0,0,55,45,-9,-9,6,2,3,0,0,0,8,2,1,165,252890.5719900001,0,0,2407.766362442015 -9082,11135,20317,-9,-9,-9,1,1,0,77,2,0,0,0,3,-9,4,3,0,0,2,0,0,0,3,0,0,0,-9,0,-898.9150807019208,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,15,3,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,14.5,1,1,0,0,0,19.54334000265078,3,35.97,32.23,-9,-9,5,2,3,0,0,0,9,1,1,862,65064.21042805586,0,0,1241.565233704812 -9082,11136,20318,20319,-9,-9,3,1,1,58,1,0,0,0,2,-9,2,1,0,0,3,8.079530628811002,7.743774242285929,0,1,0,-9,4,0,0,-15.6668592185105,0,0,0,0,58,3,3,1,-9,-9,2019,1,2,8,0,38,38,15,1,0,1,0,9.700654415606115,9.700654415606115,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.33,53.46,39.15,41.42,6,2,3,0,0,8.25,9,4,1,478.5,260188.0080034169,0,0,2164.980982461266 -9082,11136,20319,20318,20317,-9,2,1,0,58,1,0,0,0,3,-9,2,1,0,0,3,7.718614740357292,8.045479320591266,0,1,0,-9,4,0,0,-52.84287927182709,0,0,0,0,58,2,3,1,3,2,2019,1,3,12,0,38,38,15,1,0,1,0,9.879788879672546,9.879788879672546,0,0,0,0,0,0,0,5.48,1,1,0,0,0,11.26851853704638,3,39.15,41.42,57.33,53.46,4,2,3,0,0,10.08333333333333,9,4,1,478.5,260188.0080034169,0,0,2164.980982461266 -9083,11137,20320,-9,20323,20322,4,1,0,1,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-943.6757592237433,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,61,-9,-9,5,1,1,0,0,0,11,4,1,476.5,75307.49231889707,0,0,4015.097909449879 -9083,11137,20321,-9,20323,20322,3,1,1,3,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-996.8087926206172,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,62,-9,-9,5,1,1,0,0,0,11,4,1,476.5,75307.49231889707,0,0,4015.097909449879 -9083,11137,20322,20323,-9,-9,1,1,1,30,1,1,2,0,2,-9,2,1,0,0,3,8.138106063307358,8.826885505961783,7.817832935606068,2,0,-9,6,0,0,-22.87437739193636,0,0,0,0,30,2,2,1,-9,-9,2019,1,2,21,9,40,37,15,1,1,1,0,8.89460501715665,8.89460501715665,0,0,0,0,0,0,0,0,1,1,0,7.506767596850336,0,0,0,25.05,50.56,54.56,44.37,3,1,1,0,0,5,11,4,1,476.5,75307.49231889707,0,0,4015.097909449879 -9083,11137,20323,20322,-9,-9,2,1,0,30,1,1,2,0,2,-9,2,1,0,0,2,7.180308374525119,7.440894424266965,0,2,0,-9,6,0,0,-.5912294537483133,0,0,1,0,30,2,3,1,-9,-9,2019,1,1,8,0,16,24,15,1,0,1,0,9.648173691519213,9.648173691519213,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.56,44.37,25.05,50.56,7,1,1,0,1,11.08333333333333,11,4,1,476.5,75307.49231889707,0,0,4015.097909449879 -9084,11138,20324,-9,20328,20325,5,1,0,7,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1068.424000653072,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,9,3,1,379,239720.2658365995,0,0,2545.898008999821 -9084,11138,20325,20328,-9,-9,1,1,1,42,1,0,3,0,1,-9,2,1,0,0,4,0,0,0,2,0,-9,7,0,0,14.16605851876859,0,0,0,0,42,1,4,1,2,2,2019,1,2,13,2,0,45,15,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.9,52.09,38.63,63.11,5,1,1,0,0,7.583333333333333,9,3,1,379,239720.2658365995,0,0,2545.898008999821 -9084,11138,20326,-9,20328,20325,3,1,0,13,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-993.2820022213549,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,1,1,0,0,0,9,3,1,379,239720.2658365995,0,0,2545.898008999821 -9084,11138,20327,-9,20328,20325,4,1,1,10,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1107.801776150192,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,4,2,0,0,0,9,3,1,379,239720.2658365995,0,0,2545.898008999821 -9084,11138,20328,20325,-9,-9,2,1,0,42,1,0,3,0,1,-9,2,1,0,0,4,8.332440768054413,8.581553021988112,0,2,0,-9,7,0,0,25.01924034424941,0,0,1,0,42,1,4,1,2,2,2019,1,1,22,10,24,0,15,1,1,1,0,17.20054082087681,17.20054082087681,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,38.63,63.11,53.9,52.09,5,1,1,0,0,1.083333333333333,9,3,1,379,239720.2658365995,0,0,2545.898008999821 -9085,11139,20329,-9,-9,-9,1,1,0,73,2,0,0,0,2,-9,4,3,0,0,2,0,6.130175071846431,6.322530534062199,3,0,0,0,-9,0,-969.3948887002073,0,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,19,7,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,6.209500670518489,5.020998969769778,7.135962927600668,3,39.41,37.64,-9,-9,3,1,1,0,0,0,10,2,1,485,602838.022888171,0,0,1538.130763976253 -9086,11140,20330,-9,20332,20331,3,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-983.1455637603763,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,2,3,0,0,0,8,2,0,612.25,45461.34057571436,0,0,1206.660906272722 -9086,11140,20331,20332,-9,-9,2,1,1,42,1,0,2,0,2,-9,1,1,0,0,4,6.275164689764867,6.371029795795312,0,2,0,-9,14,0,0,67.51701938376856,0,0,0,0,42,2,4,1,2,1,2019,1,1,11,0,28,0,15,1,0,1,0,2.365648484057382,2.365648484057382,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.76,53.24,45.62,54.94,5,2,3,0,1,11.41666666666667,8,2,0,612.25,45461.34057571436,0,0,1206.660906272722 -9086,11140,20332,20331,-9,-9,1,1,0,42,1,0,2,0,2,-9,2,1,0,0,4,6.958787462047227,6.910330929045911,0,2,0,-9,14,0,0,-17.52647047209612,0,0,1,0,42,2,4,1,3,2,2019,1,2,9,0,16,0,15,1,0,1,0,6.476872799618764,6.476872799618764,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45.62,54.94,48.76,53.24,4,2,3,0,0,12.58333333333333,8,2,0,612.25,45461.34057571436,0,0,1206.660906272722 -9086,11140,20333,-9,20332,20331,4,1,0,3,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1032.710707373669,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,61,-9,-9,5,2,3,0,0,0,8,2,0,612.25,45461.34057571436,0,0,1206.660906272722 -9087,11141,20334,-9,-9,-9,1,1,0,28,2,1,2,0,2,-9,3,3,0,0,5,0,0,0,4,0,0,0,-9,0,-924.7181767648798,0,1,1,1,-9,-9,-9,-9,2,2,2019,-9,0,6,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,7,1,1,0,0,0,1.42616355386268,3,60.02,56.42,-9,-9,7,1,1,1,0,2.166666666666667,9,1,0,515.3333333333334,85327.09551313086,0,0,1302.188832709192 -9087,11141,20335,-9,20334,-9,3,1,1,0,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-970.0196204639627,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,9,1,0,515.3333333333334,85327.09551313086,0,0,1302.188832709192 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-9178,11251,20537,-9,-9,-9,1,1,0,52,2,0,0,0,1,-9,2,1,0,0,5,9.248896295574159,8.945556706194539,0,3,0,0,0,-9,0,-1075.395669951057,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,8,0,35,40,15,1,0,-9,0,31.97272527465957,31.97272527465957,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.06,57.76,-9,-9,6,1,1,0,0,9.916666666666666,12,5,1,781,157671.6582780764,0,0,2738.935850072316 -9179,11252,20538,20539,-9,-9,2,1,1,56,1,0,4,0,3,-9,2,1,0,0,3,7.837457775548999,7.578984332248899,0,2,0,-9,15,0,13,46.09334657434112,-9,0,0,0,43,3,3,3,-9,-9,2019,2,1,14,2,34,0,15,1,0,3,0,7.508442917809545,7.508442917809545,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.66,40.56,36.95,46.32,5,2,3,0,0,8.333333333333334,5,2,1,1565,564569.6383250498,0,0,1419.421217757697 -9179,11252,20539,20538,-9,-9,1,1,0,43,1,0,4,0,3,-9,6,3,0,0,3,0,0,0,2,0,-9,15,0,-13,-131.8341146961687,0,0,1,0,56,3,3,1,3,3,2019,3,2,12,3,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,36.95,46.32,46.66,40.56,5,2,3,0,0,0,5,2,1,1565,564569.6383250498,0,0,1419.421217757697 -9179,11252,20540,-9,20539,20538,6,1,1,7,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-969.6249209986183,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,2,3,0,0,0,5,2,1,1565,564569.6383250498,0,0,1419.421217757697 -9179,11252,20541,-9,20539,20538,5,1,0,9,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-795.8713801564934,-9,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,2,3,0,0,0,5,2,1,1565,564569.6383250498,0,0,1419.421217757697 -9180,11253,20542,-9,-9,-9,1,1,0,24,2,0,0,0,1,-9,2,1,0,0,4,8.174494753470244,8.091237912520439,0,3,0,0,0,-9,0,-1033.201207704482,0,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,5,0,41,40,15,1,0,-9,0,10.26358588301635,10.26358588301635,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,52.91,55.33,-9,-9,6,1,1,0,0,8.166666666666666,2,4,0,880,66782.98694636227,0,0,777.4254089121271 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-9229,11314,20667,20665,-9,-9,3,1,0,32,1,0,2,0,3,-9,6,3,0,1,3,0,0,0,2,0,-9,4,0,-1,17.41197156268185,0,0,1,0,33,2,4,1,-9,-9,2019,3,2,9,1,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,54.51,50,57,6,2,3,0,0,0,2,3,1,969.75,28894.84992579371,0,0,2938.993904255844 -9230,11315,20668,-9,-9,-9,1,1,0,45,2,0,1,0,2,-9,2,1,0,0,2,7.891957617371466,7.912156075020595,0,4,0,0,0,-9,0,-873.241145875371,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,2,52,48,15,1,0,-9,0,5.761820055421906,5.761820055421906,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,30.35,47.56,-9,-9,6,3,4,0,0,2.333333333333333,2,3,0,384.5,194776.0138948948,0,0,2405.786439498589 -9230,11315,20669,-9,20668,-9,2,1,1,13,2,0,1,1,3,-9,-9,2,0,0,5,0,0,0,4,0,0,0,-9,0,-1016.78641580563,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,10,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49,62,-9,-9,5,1,1,0,0,0,2,3,0,384.5,194776.0138948948,0,0,2405.786439498589 -9231,11316,20670,20671,-9,-9,1,1,0,32,1,1,3,0,2,-9,2,1,0,0,4,7.741403885118011,8.098432913528908,5.734468018657031,2,0,-9,2,0,-6,-6.942667636989733,0,0,1,0,38,2,4,1,2,2,2019,1,2,9,1,20,20,15,1,0,1,0,15.43986238168907,15.43986238168907,0,0,0,0,0,0,0,0,1,1,0,6.018248749823323,0,0,0,57.22,41.02,51,56,6,1,1,0,0,9.083333333333334,11,4,1,910,-20984.92904589442,0,0,3231.891831141682 -9231,11316,20671,20670,-9,-9,2,1,1,38,1,1,3,0,2,-9,2,1,0,0,4,8.394520319862869,8.541430767085163,0,2,0,-9,2,0,6,-21.93054490641368,0,0,0,0,32,2,4,1,-9,-9,2019,1,1,9,1,38,40,15,1,0,1,0,13.95114275946764,13.95114275946764,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51,56,57.22,41.02,6,1,1,0,0,1,11,4,1,910,-20984.92904589442,0,0,3231.891831141682 -9231,11316,20672,-9,20670,20671,5,1,0,2,2,1,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1042.760522349702,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,11,4,1,910,-20984.92904589442,0,0,3231.891831141682 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-9233,11318,20675,-9,-9,-9,1,1,1,36,2,0,0,0,2,-9,2,1,0,0,5,8.798030068165231,8.677092230769906,0,3,0,0,0,-9,0,-1177.375037148624,0,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,6,0,35,20,15,1,0,-9,0,16.94777392830078,16.94777392830078,0,0,0,0,0,0,0,0,1,1,0,3.313459495685121,0,0,0,57.06,57.76,-9,-9,6,1,1,0,0,6.833333333333333,5,5,1,261,-14139.73987767457,0,0,1624.993455525206 -9234,11319,20676,-9,-9,-9,1,1,1,67,2,0,0,0,3,-9,4,3,0,1,3,0,0,0,3,0,0,0,-9,0,-1027.910865033938,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.479732425454396,0,0,0,38.6,51.05,-9,-9,5,1,1,0,0,0,12,1,0,2169,105223.3144253834,0,0,2000.152494732032 -9235,11320,20677,20678,-9,-9,1,1,0,50,1,0,0,0,2,-9,1,1,0,0,3,7.113765787712315,7.357509967215559,0,1,0,-9,2,0,-8,-118.5758484792001,0,0,0,0,58,2,3,3,2,-9,2019,2,2,12,2,37,40,15,1,0,4,0,3.191774973893647,3.191774973893647,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.19,52.45,51,49,4,1,1,0,0,9.166666666666666,4,3,1,1371.5,283732.6325548696,0,0,1585.349758066253 -9235,11320,20678,20677,-9,-9,2,1,1,58,1,0,0,0,2,-9,4,3,0,0,3,0,7.887589457037741,7.679501642985372,1,0,-9,2,0,8,2.099509230359973,0,0,0,0,50,2,3,1,-9,-9,2019,3,1,10,1,0,40,15,4,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5.046150678882236,7.615212652264069,0,0,51,49,33.19,52.45,5,4,1,0,0,0,4,3,1,1371.5,283732.6325548696,0,0,1585.349758066253 -9236,11321,20679,20680,-9,-9,2,1,0,23,1,0,0,0,1,-9,2,1,0,0,4,8.05200862648104,8.159422699748468,0,1,0,-9,2,0,-5,-88.82299451956625,0,1,1,0,28,1,4,1,-9,-9,2019,1,1,11,0,38,35,15,1,0,1,0,9.384614169604301,9.384614169604301,0,0,0,0,0,0,0,0,0,0,0,.1189825264017845,0,0,0,45.91,59.89,54.79,55.86,6,1,1,0,0,1,12,5,1,598,80569.76497637863,0,0,3911.642808139971 -9236,11321,20680,20679,-9,-9,1,1,1,28,1,0,0,0,1,-9,2,1,0,0,4,8.834696157607803,8.952531636610846,0,1,0,-9,2,0,5,-33.28673752393389,0,1,0,0,23,1,4,1,-9,-9,2019,1,2,6,1,40,45,15,1,0,1,0,18.82396219412688,18.82396219412688,0,0,0,0,0,0,0,0,0,0,0,.510082103175537,0,0,0,54.79,55.86,45.91,59.89,6,1,1,0,0,9.833333333333334,12,5,1,598,80569.76497637863,0,0,3911.642808139971 -9237,11322,20681,20682,-9,-9,2,1,1,64,1,0,0,0,3,-9,4,3,0,0,3,0,7.34145593564684,7.507130277824675,1,0,-9,5,0,2,-79.56446978011269,0,0,0,0,62,2,3,3,-9,-9,2019,4,1,6,0,0,39,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.242170276000873,6.703741496786107,0,0,62.56,45.64,63.65,49.16,7,1,1,0,0,7.583333333333333,6,3,1,1603.5,1339525.321036941,0,0,1784.707520836108 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-9302,11401,20835,-9,20834,20833,3,1,1,11,2,0,2,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1146.68215183961,-9,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,10,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,50,61,-9,-9,5,1,1,0,0,0,2,3,1,994.5,104350.334068891,0,0,2905.540447344282 -9303,11402,20836,20837,-9,-9,1,1,1,64,1,0,0,0,2,-9,4,3,0,0,3,0,7.156767729024494,7.341829932590859,1,0,-9,43,0,2,50.630131389863,0,0,0,0,62,3,3,3,-9,-9,2019,4,2,7,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.479842056071822,0,0,52.6,52.88,49,48,6,1,1,0,0,7.833333333333333,13,2,1,1003.5,491215.2212840044,0,0,603.6889083509175 -9303,11402,20837,20836,-9,-9,2,1,0,62,1,0,0,0,3,-9,4,3,0,0,3,0,0,0,1,0,-9,43,0,-2,103.0543090268252,-9,0,0,0,64,2,3,3,3,3,2019,4,1,11,2,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49,48,52.6,52.88,5,1,1,0,0,0,13,2,1,1003.5,491215.2212840044,0,0,603.6889083509175 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-9821,12042,22002,-9,21999,22000,3,1,0,5,2,1,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-974.504897206746,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,4,5,1,408.5,676834.6837411711,0,0,3149.952772235693 -9822,12043,22003,22004,-9,-9,2,1,0,29,1,1,1,0,2,-9,5,1,0,0,4,7.904760337147684,7.926410883687657,0,2,0,-9,3,0,-4,182.876148562034,0,1,1,1,33,1,4,1,-9,-9,2019,1,1,16,4,25,25,15,1,1,1,0,11.8953950505209,11.8953950505209,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41.17,59.31,57.16,56.15,6,1,1,0,0,2.166666666666667,5,5,1,1519.666666666667,97653.87189812557,0,0,3757.709410669382 -9822,12043,22004,22003,-9,-9,1,1,1,33,1,1,1,0,1,-9,2,1,0,0,4,8.68340587911395,8.610303401230112,0,2,0,-9,3,0,4,22.69363901708559,0,0,0,1,29,2,4,1,2,2,2019,1,2,6,0,41,40,15,1,0,1,0,23.89633212008867,23.89633212008867,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,41.17,59.31,6,1,1,0,0,7.333333333333333,5,5,1,1519.666666666667,97653.87189812557,0,0,3757.709410669382 -9822,12043,22005,-9,22003,22004,3,1,0,0,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1077.991149906972,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,5,5,1,1519.666666666667,97653.87189812557,0,0,3757.709410669382 -9823,12044,22006,-9,-9,-9,1,1,0,38,2,0,1,0,1,-9,2,1,0,0,4,9.366222260398366,9.444428175400681,7.686359354744249,4,0,0,0,-9,0,-908.3342888536046,0,0,1,0,-9,-9,-9,-9,2,2,2019,-9,0,11,0,40,40,15,1,0,-9,0,28.3913653297078,28.3913653297078,0,0,0,0,0,0,0,0,1,1,0,8.840372572542181,0,0,0,30.89,61.61,-9,-9,4,1,1,0,0,7.25,9,5,0,366,96147.16998191776,0,0,4871.851584139646 -9823,12044,22007,-9,22006,-9,2,1,1,10,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1018.592372728484,-9,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,9,5,0,366,96147.16998191776,0,0,4871.851584139646 -9824,12045,22008,-9,-9,-9,1,1,0,78,2,0,0,0,2,-9,4,3,0,0,4,0,8.546765410332506,8.536606304863692,3,0,0,0,-9,0,-967.1288937806959,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,7,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,4.941955478748522,8.679258001675141,0,3,57.16,56.15,-9,-9,7,1,1,0,0,0,4,5,1,315,57935.23615897531,0,0,2743.830154627494 -9825,12046,22009,-9,-9,-9,1,1,0,26,2,0,2,0,3,-9,7,2,0,0,4,0,5.792126225903869,5.666147544237294,4,0,0,0,-9,0,-1058.682001748152,1,1,1,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,14.5,1,1,0,5.769518080581598,0,19.86057591592013,3,54.2,57.49,-9,-9,6,1,1,0,0,0,2,2,0,502,56052.06032287576,0,0,943.5631540064682 -9825,12046,22010,-9,22009,-9,2,1,0,8,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1058.419606097901,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,2,2,0,502,56052.06032287576,0,0,943.5631540064682 -9825,12046,22011,-9,22009,-9,3,1,1,4,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-938.8914535626426,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,2,2,0,502,56052.06032287576,0,0,943.5631540064682 -9826,12047,22012,-9,-9,-9,1,1,0,68,2,0,0,0,2,-9,4,3,0,0,4,0,8.09325162410482,7.720303060750862,3,0,0,0,-9,0,-1074.508725250944,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,7,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.221197784969188,7.735583891856103,0,0,56.77,52.22,-9,-9,7,1,1,0,0,7.166666666666667,4,3,1,416,871579.2781160546,0,0,1331.713035065547 -9827,12048,22013,-9,-9,-9,1,1,0,38,2,1,3,0,1,-9,6,3,0,1,4,0,5.146240176598898,5.222469134750792,4,0,0,0,-9,0,-988.5164792675255,0,0,1,0,-9,-9,-9,-9,3,2,2019,-9,0,19,7,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,5.498178328850552,0,0,0,35.95,61.84,-9,-9,4,1,1,0,0,0,6,2,0,506.6666666666667,-18906.84266533231,0,0,1792.347728055033 -9827,12048,22014,-9,22013,-9,5,1,1,2,2,1,3,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-992.3483322739646,-9,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,62,-9,-9,5,1,1,0,0,0,6,2,0,506.6666666666667,-18906.84266533231,0,0,1792.347728055033 -9827,12048,22015,-9,22013,-9,4,1,1,4,2,1,3,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1047.183320729021,-9,0,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,6,2,0,506.6666666666667,-18906.84266533231,0,0,1792.347728055033 -9827,12049,22016,-9,22013,-9,2,1,1,18,2,1,3,1,2,0,7,2,0,0,3,6.813135757278116,6.92566738283866,0,3,0,0,0,-9,0,-996.8969657278659,-9,1,0,0,-9,-9,-9,-9,1,-9,2019,-9,0,13,3,20,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,35.44,55.47,-9,-9,5,1,1,0,0,1.083333333333333,6,2,0,324,31626.52717808471,0,0,697.5916286777905 -9828,12050,22017,-9,-9,-9,1,1,0,21,2,0,0,1,2,0,7,2,0,0,5,0,0,0,3,0,0,0,-9,0,-1096.598536608444,-9,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,3,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4.994116726512119,0,0,0,40.38,61.66,-9,-9,4,3,4,0,0,0,9,1,0,632,58150.41171451547,0,0,127.1196483243411 -9829,12051,22018,-9,-9,-9,1,1,1,54,2,0,0,0,2,-9,2,1,0,0,4,8.096503757759502,8.413133351043202,0,3,0,0,0,-9,0,-927.3179586635619,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,1,37,40,15,1,0,-9,0,9.38820891642558,9.38820891642558,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,34.38,62.3,-9,-9,5,1,1,0,0,8.666666666666666,8,4,0,1413,397297.0395014535,0,0,1469.630245070959 -9830,12052,22019,-9,-9,-9,1,1,0,77,2,0,0,0,2,-9,4,3,0,1,2,0,6.2111375772185,6.312156885151265,3,0,0,0,-9,0,-1028.54871506072,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,15,5,0,0,15,4,1,-9,0,0,0,1,0,0,31.99958576029575,0,0,0,0,1,1,0,0,6.028202036438754,0,0,30.73,36.36,-9,-9,4,1,1,0,0,0,4,2,1,640,-30472.75500609516,0,0,2078.575250822614 -9831,12053,22020,22021,-9,-9,1,1,0,51,1,0,0,0,3,-9,2,1,0,0,4,7.357903771689,8.059859154869072,0,1,0,-9,7,0,2,15.11328912111259,0,0,0,0,49,2,4,1,3,3,2019,1,2,8,1,40,35,15,1,0,1,0,5.486672921108977,5.486672921108977,0,0,0,0,0,0,0,27.5,0,0,0,0,0,26.62194415722789,3,60.12,54.8,52,55,6,1,1,0,0,7.833333333333333,13,3,1,346,228931.4799168262,0,0,2299.798815129452 -9831,12053,22021,22020,-9,-9,2,1,1,49,1,0,0,0,2,-9,1,1,0,0,4,7.157258345911028,6.90917125051028,0,1,0,-9,7,0,-2,-57.96488732718316,0,0,0,0,51,3,4,1,-9,-9,2019,1,1,9,1,40,40,15,1,0,1,0,3.254887613584224,3.254887613584224,0,0,0,0,0,0,0,0,0,0,0,5.906611391498491,0,0,0,52,55,60.12,54.8,6,1,1,0,0,1,13,3,1,346,228931.4799168262,0,0,2299.798815129452 -9832,12054,22022,-9,-9,-9,1,1,0,71,2,0,0,0,3,-9,4,3,0,0,3,0,4.83548984773266,4.74027469594122,3,0,0,0,-9,0,-1001.100612680996,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,11,1,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,4.453660768199997,0,0,51,46,-9,-9,5,1,1,0,0,0,5,1,0,523,-45946.79698302342,0,0,1216.500234130462 -9833,12055,22023,-9,22027,22026,2,1,0,13,2,0,3,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1014.610335208659,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,10,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48,61,-9,-9,5,2,3,0,0,0,2,2,0,544.4,35933.1463594621,0,0,2913.651290804532 -9833,12055,22024,-9,22027,22026,3,1,1,12,2,0,3,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1025.930249559056,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,9,1,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,50,61,-9,-9,5,2,3,0,0,0,2,2,0,544.4,35933.1463594621,0,0,2913.651290804532 -9833,12055,22025,-9,22027,22026,4,1,1,8,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-939.3871735366564,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,60,-9,-9,5,1,1,0,0,0,2,2,0,544.4,35933.1463594621,0,0,2913.651290804532 -9833,12055,22026,22027,-9,-9,5,1,1,39,1,0,3,0,2,-9,2,1,0,0,4,7.58680503283858,7.785414672198542,0,2,0,-9,3,0,2,42.61842979479344,0,0,0,0,37,3,4,3,-9,-9,2019,2,1,9,1,38,40,15,1,0,3,0,9.425734111219649,9.425734111219649,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,56,54.2,57.49,5,2,3,0,0,1,2,2,0,544.4,35933.1463594621,0,0,2913.651290804532 -9833,12055,22027,22026,-9,-9,1,1,0,37,1,0,3,0,3,-9,6,3,0,0,4,0,0,0,2,0,-9,3,0,-2,-95.91276685671029,0,0,1,0,39,2,4,1,3,2,2019,3,5,8,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.2,57.49,52,56,6,2,3,0,0,0,2,2,0,544.4,35933.1463594621,0,0,2913.651290804532 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-10786,13237,24118,-9,24116,24117,3,1,1,23,2,0,1,0,1,1,2,1,0,0,5,8.128297721666957,8.306903876766686,0,3,0,0,0,-9,0,-1140.213726997472,-9,1,0,0,-9,-9,-9,-9,2,1,2019,-9,0,10,0,37,0,15,1,0,-9,1,12.86419311164791,12.86419311164791,0,0,0,0,0,0,0,0,0,0,0,2.757405631037381,0,0,0,59.04,32.46,-9,-9,4,2,3,0,0,3,5,4,1,3430,-6019.249432648361,0,0,1821.063312594665 -10786,13238,24119,-9,24116,24117,4,1,1,18,2,0,1,0,2,1,3,3,0,0,4,0,0,0,3,0,0,0,-9,0,-962.7238520165914,-9,1,0,0,-9,-9,-9,-9,2,1,2019,-9,0,10,0,0,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47,59,-9,-9,6,2,3,1,0,0,5,4,1,527,-55325.7777576139,0,0,0 -10787,13239,24120,-9,-9,-9,1,1,0,72,2,0,0,0,3,-9,4,3,0,0,3,0,7.016162130191309,6.950169323303873,3,0,0,0,-9,0,-954.2881203612596,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,1,7.38049836874595,0,4.077142611451141,0,0,0,0,1,1,0,4.966229215146269,6.809084811343435,0,0,62.57,35.9,-9,-9,6,1,1,0,0,0,13,2,1,206,375579.7022827208,0,0,903.9925400009776 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-10788,13240,24124,-9,24123,24121,4,1,1,10,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-952.1508362580877,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,56,-9,-9,5,4,2,0,0,0,5,2,0,613.25,-112412.3890977043,0,0,1024.051826587057 -10789,13241,24125,24126,-9,-9,2,1,1,31,1,0,0,0,2,-9,2,1,0,0,4,8.04177638250304,8.115044969631297,0,1,0,-9,3,0,3,-176.494834029693,-9,0,0,0,28,2,3,1,-9,-9,2019,1,1,10,2,47,0,15,1,0,1,0,8.693755268148495,8.693755268148495,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,42.78,45.32,54.94,53.18,6,1,1,0,0,.75,10,4,0,955,163049.401330829,0,0,3255.297168215564 -10789,13241,24126,24125,-9,-9,1,1,0,28,1,0,0,0,2,-9,2,1,0,0,3,7.870271760177789,8.089942982809129,0,1,0,-9,3,0,-3,90.18718607307849,0,1,1,0,31,2,4,1,2,2,2019,1,2,7,0,47,43,15,1,0,1,0,8.008360740449362,8.008360740449362,0,0,0,0,0,0,0,2,0,0,0,6.893984555583569,0,0,3,54.94,53.18,42.78,45.32,6,1,1,0,0,8.916666666666666,10,4,0,955,163049.401330829,0,0,3255.297168215564 -10790,13242,24127,-9,-9,-9,1,1,0,55,2,0,0,0,2,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-1002.303845084976,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,25,11,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,7,1,1,0,0,0,1.880896247344385,3,32.57,22.01,-9,-9,5,1,1,0,0,2.083333333333333,6,1,0,310,68148.79549555707,0,0,1124.530683940036 -10791,13243,24128,-9,-9,-9,1,1,1,79,2,0,0,0,3,-9,4,3,0,0,3,0,0,0,3,0,0,0,-9,0,-903.0698645167274,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,9,1,0,0,15,4,0,-9,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54,46,-9,-9,6,1,1,0,0,6.75,2,1,1,430,147258.0451641072,0,0,464.3095896241842 -10792,13244,24129,24130,-9,-9,2,1,1,50,1,0,0,0,2,-9,2,1,0,0,3,7.832990619774904,8.151741914752515,0,1,0,-9,7,0,0,151.9760666498413,0,0,0,0,50,2,2,1,-9,-9,2019,1,1,12,0,45,0,15,1,0,1,0,9.356682223318625,9.356682223318625,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,54.51,45.74,30.78,5,1,1,0,0,9.416666666666666,12,4,1,352.5,146897.2844034396,0,0,2585.514332607157 -10792,13244,24130,24129,-9,-9,1,1,0,50,1,0,0,0,2,-9,2,1,0,0,2,7.721752833448318,7.92857084671108,0,1,0,-9,7,0,0,68.11474961092462,0,0,0,0,50,2,3,1,3,-9,2019,1,2,19,7,30,29,15,1,1,1,0,8.098099954002896,8.098099954002896,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45.74,30.78,52,54.51,3,1,1,0,0,7.666666666666667,12,4,1,352.5,146897.2844034396,0,0,2585.514332607157 -10793,13245,24131,24132,-9,-9,2,1,0,52,1,0,0,0,1,-9,2,1,0,0,4,8.33149155028258,8.917859567449144,0,1,0,-9,33,0,-1,-108.9856740036593,-9,0,0,0,53,3,4,1,-9,-9,2019,1,1,10,1,40,0,15,1,0,1,0,14.14531786795088,14.14531786795088,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52,53,52.6,50.15,6,1,1,0,0,1,5,5,1,407.5,1453392.978306296,0,0,4219.017985317447 -10793,13245,24132,24131,-9,-9,1,1,1,53,1,0,0,0,3,-9,2,1,0,0,4,8.495405009977864,8.227829746291732,0,1,0,-9,34,0,1,22.99939413531904,0,0,0,0,52,1,4,1,3,3,2019,1,2,13,1,39,40,15,1,0,1,0,13.9148977121392,13.9148977121392,0,0,0,0,0,0,0,7,1,1,0,.6467944101554404,0,7.628758769904185,3,52.6,50.15,52,53,2,1,1,0,0,8.083333333333334,5,5,1,407.5,1453392.978306296,0,0,4219.017985317447 -10794,13246,24133,24134,-9,-9,1,1,1,61,1,0,0,0,2,-9,2,1,0,0,4,7.552389777410002,7.547832750085389,0,1,0,-9,9,0,5,12.70599868063544,0,0,0,0,56,2,4,1,2,2,2019,1,2,9,1,37,33,15,1,0,1,0,7.553187972420862,7.553187972420862,0,0,0,0,0,0,0,14.5,0,0,0,.2783367362041035,0,14.72433934821638,3,51.24,58.84,54.2,57.49,6,1,1,0,0,9.666666666666666,11,4,1,693.5,322966.7957419805,0,0,2291.336766058395 -10794,13246,24134,24133,-9,-9,2,1,0,56,1,0,0,0,2,-9,2,1,0,0,4,7.68184947599386,7.640027500847142,0,1,0,-9,9,0,-5,75.03957821615055,0,0,0,0,61,2,4,1,2,2,2019,1,1,9,0,33,33,15,1,0,1,0,7.344168299056496,7.344168299056496,0,0,0,0,0,0,0,14.5,0,0,0,0,0,17.22309863095038,3,54.2,57.49,51.24,58.84,6,1,1,0,0,9.833333333333334,11,4,1,693.5,322966.7957419805,0,0,2291.336766058395 -10795,13247,24135,24136,-9,-9,2,1,1,62,1,0,0,0,2,-9,2,1,0,0,3,0,5.998873764328074,6.400281619223956,1,0,-9,2,0,-1,56.76759926776697,0,0,0,0,63,2,2,3,-9,-9,2019,2,1,6,0,0,45,15,1,0,3,0,0,0,0,0,0,0,0,0,0,5.48,1,1,0,5.350981873863119,6.154486723920567,7.714571821576831,1,64.23999999999999,44.83,43.69,21.98,5,1,1,0,0,12.66666666666667,12,2,1,503,376497.282999839,0,0,868.4324426061478 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-10915,13393,24379,-9,24377,24378,3,1,1,28,2,0,0,0,2,-9,1,1,0,0,4,6.76538635928318,6.98398138694186,0,3,0,0,0,-9,0,-911.4027146038012,0,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,10,0,60,60,15,1,0,-9,1,1.562054536326568,1.562054536326568,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.98,59.35,-9,-9,5,1,1,0,0,4.083333333333333,4,2,1,1094,-14148.41084643183,0,0,442.8438560441293 -10916,13394,24380,24381,-9,-9,2,1,0,67,1,0,0,0,3,-9,8,3,1,1,2,0,4.290376702098132,4.519691689094826,1,0,-9,50,0,0,-50.2426905163944,0,0,0,0,67,2,4,3,3,3,2019,4,1,27,11,0,0,15,3,1,4,0,0,0,1,0,20.65207881063182,0,0,0,0,0,1,1,0,2.484365479882451,4.458177246171432,0,0,28.53,42.84,42.62,54.02,3,1,1,0,1,0,7,2,1,695,665548.2008060861,0,0,2159.35565238199 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-10921,13399,24392,-9,24397,24395,4,1,0,15,2,0,6,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1097.754558924319,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,54,-9,-9,5,2,3,0,0,0,8,2,0,1361.5,38926.25103983809,0,0,3380.376798252727 -10921,13399,24393,-9,24397,24395,7,1,1,4,2,0,6,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1005.444922948784,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,2,3,0,0,0,8,2,0,1361.5,38926.25103983809,0,0,3380.376798252727 -10921,13399,24394,-9,24397,24395,5,1,0,12,2,0,6,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-954.5384251252012,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,2,3,0,0,0,8,2,0,1361.5,38926.25103983809,0,0,3380.376798252727 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-10922,13400,24398,-9,-9,-9,3,1,1,29,2,0,0,0,2,-9,2,1,0,0,4,7.575565212622595,7.781907617936922,0,3,0,0,0,-9,0,-1162.515603156219,0,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,17,5,40,38,15,1,1,-9,0,5.777318270563671,5.777318270563671,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.57,34.33,-9,-9,6,1,1,0,0,4.25,6,3,1,453,-80117.72965611453,0,0,1310.327460172237 -10922,13401,24399,24400,-9,-9,2,1,1,33,1,0,0,0,1,-9,2,1,0,0,4,8.217408265611487,8.287523677462453,0,1,0,-9,8,0,3,-49.11078902076977,0,0,0,0,30,2,2,1,-9,-9,2019,1,1,12,2,65,72,15,1,0,1,0,5.864470677820263,5.864470677820263,0,0,0,0,0,0,0,0,0,0,0,.9216517830202968,0,0,0,48.87,58.55,55.2,49.4,5,1,1,0,0,6.916666666666667,6,5,1,653,274204.7917941508,0,0,3677.098543712581 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-11156,13701,24910,-9,24909,24912,4,1,0,11,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1083.0678142149,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,45,60,-9,-9,5,2,3,0,0,0,8,2,0,238,68598.81202435902,0,0,1190.913184900184 -11156,13701,24911,-9,24909,24912,3,1,1,15,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1069.849506850072,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,47,60,-9,-9,5,2,3,0,0,0,8,2,0,238,68598.81202435902,0,0,1190.913184900184 -11156,13701,24912,24909,-9,-9,2,1,1,52,1,0,2,0,1,-9,2,1,0,0,4,7.448001962902326,7.456120262997754,0,2,0,-9,8,0,6,115.7177069522836,0,0,0,0,46,2,4,3,-9,-9,2019,2,1,9,1,24,25,15,1,0,3,0,8.281620293364814,8.281620293364814,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,53,54,36.34,56.37,6,2,3,0,0,1,8,2,0,238,68598.81202435902,0,0,1190.913184900184 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-11159,13704,24916,24917,-9,-9,1,1,1,54,1,0,0,0,2,-9,2,1,0,0,4,7.992816233379037,8.011906597730968,0,1,0,-9,7,0,1,28.27047769146631,0,0,0,0,53,2,5,1,1,2,2019,1,2,8,0,32,32,15,1,0,1,0,12.51644681896179,12.51644681896179,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.79,55.86,57.06,57.76,6,1,1,0,0,7.75,11,5,1,1043,711714.1922203942,0,0,3247.47132614059 -11159,13704,24917,24916,-9,-9,2,1,0,53,1,0,0,0,2,-9,2,1,0,0,5,8.531966029676886,8.398680041608531,0,1,0,-9,7,0,-1,-58.91968921012418,0,0,0,0,54,2,4,1,2,2,2019,1,1,8,0,38,37,15,1,0,1,0,13.26422632602709,13.26422632602709,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.06,57.76,54.79,55.86,6,1,1,0,0,7.75,11,5,1,1043,711714.1922203942,0,0,3247.47132614059 -11160,13705,24918,24919,-9,-9,1,1,1,64,1,0,0,0,2,-9,8,3,1,1,2,0,0,0,1,0,-9,44,0,4,-7.314356506450818,0,0,0,0,60,2,3,1,2,-9,2019,3,2,6,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42.88,39.09,60.3,46.58,5,1,1,0,0,0,12,2,0,884.5,432089.2453931146,0,0,795.2961692921101 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-11208,13767,25025,-9,-9,-9,1,1,1,27,2,0,0,0,1,-9,2,1,0,0,5,8.892567909189246,8.924589887000145,0,3,0,0,0,-9,0,-988.679776922632,0,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,8,0,40,38,15,1,0,-9,0,17.71308603258161,17.71308603258161,0,0,0,0,0,0,0,0,0,0,0,6.534652775978957,0,0,0,44.45,62.04,-9,-9,6,1,1,0,0,6.75,7,5,1,656,-165627.3226088871,0,0,2835.021251934419 -11209,13768,25026,25027,-9,-9,2,1,0,69,1,0,0,0,2,-9,4,3,0,0,4,0,4.938427319446799,4.563922891666944,1,0,-9,51,0,-2,-86.39625462686762,0,0,0,0,71,2,2,3,3,3,2019,4,1,9,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,120,1,1,0,5.243150195332293,4.855510788341136,115.2645386776059,1,55.34,54.26,55.03,11.91,6,1,1,0,0,2.833333333333333,5,2,0,729.5,364078.7732095913,0,0,1414.847202510182 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-11371,13967,25395,-9,-9,-9,1,1,1,48,2,0,0,0,2,-9,2,1,0,0,3,7.960131308154001,7.868912860113181,0,3,0,0,0,-9,0,-1041.844609449967,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,2,45,42,15,1,0,-9,0,6.086808161247092,6.086808161247092,0,0,0,0,0,0,0,14.5,1,1,0,0,0,22.34975831770542,3,43.46,51.61,-9,-9,5,1,1,0,0,9.333333333333334,12,3,0,493,176513.5421156505,0,0,1348.260113930397 -11372,13968,25396,25397,-9,-9,1,1,1,61,1,0,0,0,1,-9,4,3,0,0,4,6.467928447711311,8.02006932419234,7.867967147774491,1,0,-9,9,0,0,47.32759072847422,0,0,0,0,61,2,3,3,3,3,2019,4,2,6,0,6,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.34206452346631,7.530854012559185,0,0,62.25,48.33,59.07,43.05,6,1,1,0,0,9.666666666666666,13,4,1,522,1833498.95189188,0,0,2151.106866885748 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-11377,13973,25404,25405,-9,-9,2,1,1,71,1,0,0,0,2,-9,4,3,0,0,3,0,7.236216721720262,7.199217989922801,1,0,-9,8,0,3,-69.31009940624122,0,0,0,0,68,2,4,3,-9,-9,2019,4,1,10,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.223495096409256,7.216832679476037,0,0,53,47,37.03,45.04,5,1,1,0,0,0,2,2,1,296.5,486216.4705051342,0,0,2264.318706007452 -11377,13973,25405,25404,-9,-9,1,1,0,68,1,0,0,0,2,-9,4,3,0,0,4,0,6.193410105255706,6.327687152547491,1,0,-9,42,0,-3,9.082742408817975,0,0,0,0,71,2,3,3,3,3,2019,4,2,23,11,0,0,15,4,1,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,.3089302827604908,6.44413285399155,0,0,37.03,45.04,53,47,5,1,1,0,0,0,2,2,1,296.5,486216.4705051342,0,0,2264.318706007452 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-11748,14439,26249,-9,26248,26247,4,1,1,10,2,0,2,1,3,-9,-9,2,0,0,2,0,0,0,2,0,0,0,-9,0,-1045.954055315793,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,15,4,0,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,39,45,-9,-9,4,1,1,0,0,0,13,2,1,580.6666666666666,260207.6565861687,0,0,2288.452197191321 -11749,14440,26250,26251,-9,-9,1,1,1,60,1,0,0,0,1,-9,1,1,0,0,3,7.968501377691383,8.929222543449248,8.629707509821172,1,0,-9,40,0,1,-89.67896185134146,0,0,0,0,59,2,5,3,-9,-9,2019,2,2,10,0,25,20,15,1,0,4,0,14.91550583000055,14.91550583000055,0,0,0,0,0,0,0,7,0,0,0,0,8.673008251529245,5.538156793551886,3,50.85,40.24,54.1,59.11,6,1,1,0,0,11.08333333333333,7,5,1,479,366237.5326513585,0,0,5162.719488465249 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-11789,14492,26347,-9,26350,26349,4,1,1,9,2,1,5,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1058.606377621003,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,11,2,0,1017.5,180689.8792816623,0,0,2513.387178370782 -11789,14492,26348,-9,26350,26349,6,1,1,6,2,1,5,1,3,-9,-9,2,0,0,4,0,0,0,2,0,-9,0,-9,0,-1081.241045910343,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,11,2,0,1017.5,180689.8792816623,0,0,2513.387178370782 -11789,14492,26349,26350,-9,-9,2,1,1,48,1,1,5,0,2,-9,2,1,0,0,3,7.740011443958588,8.113253105166615,0,2,0,-9,1,-9,16,179.6417473809253,-9,0,0,0,32,2,3,3,2,2,2019,2,1,7,0,40,0,15,1,0,3,0,7.85725013578657,7.85725013578657,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.67,55.57,57.33,53.46,6,1,1,0,0,8.25,11,2,0,1017.5,180689.8792816623,0,0,2513.387178370782 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-11945,14680,26690,-9,26688,26687,4,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-937.7798901071652,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,1,1,0,0,0,8,4,1,728.5,632535.9450143683,0,0,3920.020627981001 -11946,14681,26691,-9,26692,26694,4,1,1,7,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-966.3507658344745,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,6,4,0,313.5,436772.6124454489,0,0,3669.952933908532 -11946,14681,26692,26694,-9,-9,2,1,0,40,1,0,2,0,1,-9,2,1,0,1,2,8.003704050235651,7.633812562378459,0,2,0,-9,9,0,3,-22.11914848421093,0,0,1,0,37,2,2,1,2,2,2019,1,1,12,1,39,37,15,1,0,1,0,9.59737609962761,9.59737609962761,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52.29,23.64,40.15,42.79,6,1,1,0,0,6.583333333333333,6,4,0,313.5,436772.6124454489,0,0,3669.952933908532 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-12605,15516,28173,-9,-9,-9,1,1,0,76,2,0,0,0,3,-9,4,3,0,0,4,0,0,0,3,0,0,0,-9,0,-1004.177645264135,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,3,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,54.79,55.86,-9,-9,7,1,1,0,0,0,2,1,0,1840,243409.7112981664,0,0,913.4019458381604 -12606,15517,28174,28175,-9,-9,1,1,1,25,1,0,0,0,2,-9,2,1,0,0,3,8.623847875246662,8.696280698055885,0,1,0,1,1,-9,0,22.7678954485598,0,1,0,0,25,1,3,1,-9,-9,2019,1,2,6,1,40,42,15,1,0,1,0,13.26019224607889,13.26019224607889,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,47.81,52.33,57.33,53.46,6,1,1,0,0,7.75,7,5,0,266.5,85122.41939966328,0,0,2970.683706528039 -12606,15517,28175,28174,-9,-9,2,1,0,25,1,0,0,0,1,-9,2,1,0,0,3,7.956740952914937,7.698430453423978,0,1,0,-9,1,-9,0,-141.7931898804426,-9,1,1,0,25,2,3,1,-9,-9,2019,1,1,6,0,37,0,15,1,0,1,0,9.516960893837352,9.516960893837352,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.33,53.46,47.81,52.33,6,1,1,0,0,1.5,7,5,0,266.5,85122.41939966328,0,0,2970.683706528039 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-12691,15620,28342,-9,28340,28344,4,1,0,2,2,2,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1082.786330712419,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,2,3,0,0,0,2,1,0,748.2,-37157.26343818504,0,0,2225.640463431924 -12691,15620,28343,-9,28340,28344,5,1,1,1,2,2,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1056.500562211356,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,2,3,0,0,0,2,1,0,748.2,-37157.26343818504,0,0,2225.640463431924 -12691,15620,28344,28340,-9,-9,1,1,1,27,1,2,3,0,2,-9,3,3,0,1,2,0,0,0,2,0,-9,2,0,2,0,0,1,0,0,25,2,2,3,-9,-9,2019,4,2,24,12,0,0,15,3,1,3,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,25.34,47,28.23,51.2,3,2,3,1,0,0,2,1,0,748.2,-37157.26343818504,0,0,2225.640463431924 -12692,15621,28345,28346,-9,-9,2,1,0,39,1,0,1,0,1,-9,2,1,0,0,4,9.119314724747099,9.151416565787995,0,2,0,-9,12,0,-8,0,0,0,1,0,47,2,3,1,2,2,2019,1,1,10,0,45,0,15,1,0,1,0,23.69845294092701,23.69845294092701,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,55.36,51.57,5,1,1,0,0,6.5,2,5,1,791.6666666666666,305760.4517380034,0,0,7522.20327361424 -12692,15621,28346,28345,-9,-9,1,1,1,47,1,0,1,0,2,-9,2,1,0,0,3,9.185277382461269,9.282706125680932,0,2,0,-9,14,0,8,0,0,0,0,0,39,1,4,1,2,2,2019,1,2,6,0,42,0,15,1,0,1,0,20.90581290132766,20.90581290132766,0,0,0,0,0,0,0,0,0,0,0,.0634728650906752,0,0,0,55.36,51.57,57.16,56.15,6,1,1,0,0,6.833333333333333,2,5,1,791.6666666666666,305760.4517380034,0,0,7522.20327361424 -12692,15621,28347,-9,28345,28346,3,1,0,10,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-990.9791709064838,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45,60,-9,-9,5,1,1,0,0,0,2,5,1,791.6666666666666,305760.4517380034,0,0,7522.20327361424 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-12705,15635,28378,28376,-9,-9,2,1,0,45,1,0,2,0,1,-9,6,3,0,0,2,0,0,0,2,0,-9,9,0,-6,-142.365259185922,0,0,0,0,51,2,3,1,2,3,2019,3,1,15,3,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,32.99,49.06,47.66,52.33,4,1,1,0,0,0,12,2,1,891,135299.7563147364,0,0,1466.673239595554 -12706,15636,28379,28380,-9,-9,2,1,1,56,1,0,0,0,2,-9,2,1,0,0,4,8.338637220107984,8.488253429098114,0,1,0,-9,8,0,-1,-104.3136989437586,-9,0,0,0,57,1,4,1,-9,-9,2019,1,1,5,0,28,0,15,1,0,1,0,18.00375816464944,18.00375816464944,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,54.77,55.87,7,1,1,0,0,2.333333333333333,9,5,1,240,590655.5842409595,0,0,3932.42901727753 -12706,15636,28380,28379,-9,-9,1,1,0,57,1,0,0,0,1,-9,2,1,0,0,4,8.659293602928019,8.38803773530182,0,1,0,-9,8,0,1,71.90000841819295,0,0,0,0,56,2,4,1,3,3,2019,1,2,11,0,45,38,15,1,0,1,0,14.39620891219654,14.39620891219654,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.77,55.87,57.16,56.15,6,1,1,0,0,9.166666666666666,9,5,1,240,590655.5842409595,0,0,3932.42901727753 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-13062,16050,29165,-9,29167,29166,5,1,1,10,2,0,3,1,3,-9,-9,2,0,0,1,0,0,0,2,0,0,0,-9,0,-972.6726860726628,-9,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,20,7,0,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,31,34,-9,-9,3,1,1,0,0,0,12,3,0,566.2,94410.91810575739,0,0,2274.367334281042 -13062,16050,29166,29167,-9,-9,3,1,1,38,1,0,3,0,3,-9,2,1,0,0,2,8.506460690787842,8.503065201420256,0,2,0,-9,10,0,-2,-7.336229812330233,0,0,0,0,40,2,4,3,-9,-9,2019,2,1,10,2,42,42,15,1,0,3,0,11.36662578420001,11.36662578420001,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.69,42.63,51.83,57.2,1,1,1,0,1,10.91666666666667,12,3,0,566.2,94410.91810575739,0,0,2274.367334281042 -13062,16050,29167,29166,-9,-9,1,1,0,40,1,0,3,0,2,-9,6,3,0,0,4,0,0,0,2,0,-9,10,0,2,32.71687543472981,0,0,1,0,38,3,2,1,2,3,2019,3,3,10,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.83,57.2,40.69,42.63,5,1,1,0,0,0,12,3,0,566.2,94410.91810575739,0,0,2274.367334281042 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-13731,16863,30654,-9,30656,30657,5,1,1,4,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1093.018750732301,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,5,4,0,642.75,35455.69303736014,0,0,3855.561992566711 -13731,16863,30655,-9,30656,30657,4,1,1,9,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1095.139820811537,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,60,-9,-9,5,1,1,0,0,0,5,4,0,642.75,35455.69303736014,0,0,3855.561992566711 -13731,16863,30656,30657,-9,-9,2,1,0,30,1,0,3,0,2,1,2,1,0,0,3,7.772566014107736,8.105250386689256,0,2,0,-9,5,0,-3,23.25739664372701,-9,0,1,0,33,2,5,1,-9,-9,2019,1,1,7,0,43,0,15,1,0,1,0,9.384974347453172,9.384974347453172,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.09,46.7,60.02,56.42,6,1,1,0,0,2.833333333333333,5,4,0,642.75,35455.69303736014,0,0,3855.561992566711 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-13733,16865,30660,-9,-9,-9,1,1,0,35,2,0,4,0,2,-9,1,1,0,0,4,8.40200663698003,8.322723482794414,0,4,0,0,0,-9,0,-971.3661914451664,0,0,1,0,-9,-9,-9,-9,3,-9,2019,-9,0,16,4,27,42,15,1,1,-9,0,19.3431231777601,19.3431231777601,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,36.66,61.22,-9,-9,5,1,1,0,0,6.916666666666667,5,3,0,987.6666666666666,-47582.96905715757,0,0,1758.796354617958 -13733,16865,30661,-9,30660,-9,5,1,0,5,2,0,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-952.823037063419,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,5,3,0,987.6666666666666,-47582.96905715757,0,0,1758.796354617958 -13734,16866,30662,-9,-9,-9,1,1,0,64,2,0,0,0,2,-9,4,3,0,0,3,0,5.735860463971874,5.727999800409874,3,0,0,0,-9,0,-944.1438042532253,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,25,8,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,5.796149572840018,0,0,17.81,49.93,-9,-9,5,1,1,0,1,0,10,2,0,370,179803.466667949,0,0,1726.345047813922 -13735,16867,30663,-9,-9,-9,1,1,0,52,2,0,0,0,2,-9,2,1,0,0,3,6.57563148263983,6.622046256272544,0,3,0,0,0,-9,0,-1115.841273870061,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,7,0,16,16,15,1,0,-9,0,4.582415698895166,4.582415698895166,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.76,50.23,-9,-9,6,1,1,0,0,5.666666666666667,1,2,0,1799,19297.24021542189,0,0,-154.8158523285736 -13735,16868,30664,-9,30663,-9,2,1,0,18,2,0,0,0,2,1,11,3,0,0,5,6.590171478051286,6.239788985526531,0,3,0,0,0,-9,0,-1022.14977536734,-9,1,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,6,0,30,0,15,3,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,59.43,58.05,-9,-9,6,1,1,0,0,2.083333333333333,1,2,0,276,19717.4578754656,0,0,1047.224581424848 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-13737,16870,30667,-9,-9,-9,1,1,0,74,2,0,0,0,1,-9,4,3,0,0,3,0,6.486529607868937,6.484414760396922,3,0,0,0,-9,0,-905.3864528379185,0,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,9,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.55937514822256,6.256508265523647,0,0,63.41,39.7,-9,-9,6,1,1,0,0,1.666666666666667,9,2,1,479,136698.1421521456,0,0,2011.12815164646 -13738,16871,30668,-9,-9,-9,1,1,0,59,2,0,0,0,2,-9,2,1,0,0,4,8.497372514992225,8.473558306146419,0,3,0,0,0,-9,0,-1022.936124031914,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,0,42,42,15,1,0,-9,0,10.47462126727775,10.47462126727775,0,0,0,0,0,0,0,7,0,0,0,0,0,14.62922283894595,3,52.77,55.33,-9,-9,5,1,1,0,0,10,12,4,0,343,413640.0096001328,0,0,2061.265108786773 -13739,16872,30669,-9,-9,-9,1,1,1,22,2,0,0,1,1,0,7,2,0,0,3,0,5.755551575028452,5.921208682710801,3,0,0,0,-9,0,-938.8439051757899,-9,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,20,8,0,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5.763693558778177,0,0,0,26.09,63.8,-9,-9,3,1,1,0,0,0,4,2,0,271,117077.166484139,0,0,98.93197021173191 -13740,16873,30670,-9,-9,-9,1,1,0,49,2,0,1,0,3,-9,8,3,1,1,1,0,0,0,4,0,0,0,-9,0,-924.0738937888592,0,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,22,7,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,21.36,34,-9,-9,2,1,1,0,0,0,9,1,0,1099.5,43404.7233477019,0,0,1999.836323226524 -13740,16873,30671,-9,30670,-9,2,1,0,14,2,0,1,1,3,-9,-9,2,0,0,2,0,0,0,4,0,0,0,-9,0,-1001.221294848312,-9,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,16,4,0,0,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,38,43,-9,-9,4,1,1,0,0,0,9,1,0,1099.5,43404.7233477019,0,0,1999.836323226524 -13741,16874,30672,-9,-9,-9,1,1,1,70,2,0,0,0,2,-9,4,3,0,0,3,0,6.366078251902904,6.203865638795317,3,0,0,0,-9,0,-902.0607695286233,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,6.03148581119253,6.297159837629512,0,3,56.67,42.78,-9,-9,6,1,1,0,0,7.333333333333333,6,2,0,799,272470.996843136,0,0,1265.104816764136 -13742,16875,30673,-9,30675,-9,1,1,1,46,2,0,0,0,2,-9,2,1,0,0,2,8.020636790600449,7.667445271201469,0,3,0,0,0,-9,0,-996.9502119646107,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,0,45,42,15,1,0,-9,1,8.100548349515844,8.100548349515844,0,0,0,0,0,0,0,2,1,1,0,0,0,5.734254651429309,3,41.21,39.55,-9,-9,3,1,1,0,0,10.75,7,4,0,1743,141449.1414174873,0,0,1016.229848227787 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-13774,16915,30744,30743,-9,-9,1,1,0,37,1,0,2,0,2,-9,2,1,0,0,4,7.547046509916822,7.733918604884285,0,2,0,-9,5,0,-2,46.57010922341272,0,0,1,0,39,2,5,1,2,3,2019,1,2,11,2,24,32,15,1,0,1,0,9.991486267506454,9.991486267506454,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,49,55,52.38,55.95,5,1,1,0,0,1,5,4,1,1263,295454.5530089078,0,0,3046.784469030921 -13775,16916,30745,30746,-9,-9,2,1,1,63,1,0,0,0,2,-9,4,3,0,0,4,0,7.668083309529089,7.824276781031373,1,0,-9,35,0,1,54.94579446024225,0,0,0,0,62,2,5,3,2,1,2019,4,1,9,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5.014154920447165,7.390261785198308,0,0,42.95,61.24,54.1,59.11,6,1,1,0,0,10.25,6,4,1,239,1649306.879149771,0,0,2018.809278151439 -13775,16916,30746,30745,-9,-9,1,1,0,62,1,0,0,0,2,-9,4,3,0,0,5,0,7.57796744479711,7.345170380754627,1,0,-9,35,0,-1,194.2918115581887,0,0,0,0,63,2,4,3,3,3,2019,4,2,10,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8.468184715529464,7.900150987466832,0,0,54.1,59.11,42.95,61.24,7,1,1,0,0,9.416666666666666,6,4,1,239,1649306.879149771,0,0,2018.809278151439 -13776,16917,30747,30748,-9,-9,2,1,1,68,1,0,0,0,1,-9,2,1,0,0,4,7.771432013260886,8.850809243288419,8.013064567918336,1,0,-9,48,0,0,-52.88973541760317,0,0,0,0,68,1,4,3,2,2,2019,2,1,9,1,7,7,15,1,0,4,0,33.24568585161138,33.24568585161138,0,0,0,0,0,0,0,0,1,1,0,8.299304997497048,8.775596423011059,0,0,61.12,51.57,51.24,58.84,6,1,1,0,0,9.75,10,5,1,520,1767670.943955004,0,0,5289.854181946817 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-13778,16920,30751,30752,-9,-9,2,1,1,35,1,0,0,0,1,-9,2,1,0,0,4,7.910267792765176,8.052947796556845,0,1,0,-9,1,-9,6,-57.54031192567053,-9,0,0,0,29,1,4,1,-9,-9,2019,1,1,13,1,44,0,15,1,0,1,0,6.95590037596494,6.95590037596494,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,43.98,58.43,43.67,61.06,3,1,1,0,0,.9166666666666666,13,4,0,390.5,57495.45669225208,0,0,2520.908002765901 -13778,16920,30752,30751,-9,-9,1,1,0,29,1,0,0,0,1,-9,2,1,0,0,4,7.731626085664743,8.094943402417476,0,1,0,1,1,-9,-6,-63.8037069529925,0,1,1,0,35,1,4,1,2,1,2019,1,2,11,0,44,50,15,1,0,1,0,5.941965460598044,5.941965460598044,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,43.67,61.06,43.98,58.43,6,1,1,0,0,6.666666666666667,13,4,0,390.5,57495.45669225208,0,0,2520.908002765901 -13779,16921,30753,30754,-9,-9,2,1,0,29,1,0,0,0,2,-9,2,1,0,0,4,9.233369746836708,9.321872873504121,0,1,0,-9,3,0,-2,89.53191606360832,-9,1,1,0,31,1,4,1,-9,-9,2019,1,1,9,1,42,0,15,1,0,1,0,25.14532913783256,25.14532913783256,0,0,0,0,0,0,0,0,0,0,0,4.480016186408718,0,0,0,48.28,60.18,49.59,58.37,6,1,1,0,0,5.416666666666667,9,5,1,1420,707485.6131009957,0,0,4928.169204488286 -13779,16921,30754,30753,-9,-9,1,1,1,31,1,0,0,0,1,-9,2,1,0,0,4,9.035185520694979,8.906834138004498,0,1,0,-9,3,0,2,-145.9193238348083,0,0,0,0,29,2,4,1,-9,-9,2019,1,2,5,0,43,50,15,1,0,1,0,21.90842707343768,21.90842707343768,0,0,0,0,0,0,0,0,0,0,0,3.050550834415901,0,0,0,49.59,58.37,48.28,60.18,6,1,1,0,0,6.416666666666667,9,5,1,1420,707485.6131009957,0,0,4928.169204488286 -13780,16922,30755,30756,-9,-9,2,1,0,37,1,0,1,0,1,-9,1,1,0,0,1,7.292562059033945,7.332572158503552,0,2,0,-9,6,0,-16,148.4637944424056,0,0,1,0,53,2,1,1,-9,-9,2019,1,1,6,0,35,15,15,1,0,1,0,3.909034631904937,3.909034631904937,0,0,0,0,0,0,0,0,1,1,0,4.706332683278355,0,0,0,41.55,48.36,43.52,52.09,5,1,1,0,0,2.833333333333333,9,4,1,493.6666666666667,1293228.440967606,0,0,3382.750342514835 -13780,16922,30756,30755,-9,-9,1,1,1,53,1,0,1,0,2,-9,2,1,0,0,1,8.943015352033173,8.950098810538236,0,2,0,-9,6,0,16,-64.4980699169883,0,0,0,0,37,1,1,1,3,2,2019,1,2,16,5,48,40,15,1,1,1,0,16.27263614813035,16.27263614813035,0,0,0,0,0,0,0,14.5,1,1,0,0,0,15.93866713525535,1,43.52,52.09,41.55,48.36,6,1,1,0,0,7.166666666666667,9,4,1,493.6666666666667,1293228.440967606,0,0,3382.750342514835 -13780,16922,30757,-9,30755,30756,3,1,1,5,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-925.7839440387839,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,9,4,1,493.6666666666667,1293228.440967606,0,0,3382.750342514835 -13781,16923,30758,30759,-9,-9,1,1,0,74,1,0,0,0,3,-9,4,3,0,0,4,0,6.491265808778658,6.438972267564719,1,0,-9,43,0,-1,-36.28916118452606,0,0,0,0,75,2,3,3,3,2,2019,4,2,9,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.418229652271549,0,0,57.16,56.15,51.15,51.18,6,1,1,0,0,0,1,2,1,469.5,30145.96833164923,0,0,1797.425333601246 -13781,16923,30759,30758,-9,-9,2,1,1,75,1,0,0,0,2,-9,4,3,0,0,3,0,3.819532938106884,3.777166939186055,1,0,-9,43,0,1,102.5635139716939,0,0,0,0,74,3,4,3,3,3,2019,4,1,8,0,0,0,15,4,0,4,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,3.733965836914058,0,0,51.15,51.18,57.16,56.15,6,1,1,0,0,2.416666666666667,1,2,1,469.5,30145.96833164923,0,0,1797.425333601246 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-13957,17142,31179,31178,-9,-9,2,1,0,51,1,0,0,0,3,-9,2,1,0,0,4,7.498568948589164,7.294296086460069,0,1,0,-9,33,0,0,-4.171180296575798,0,0,0,0,51,2,4,1,2,3,2019,1,1,11,2,45,23,15,1,0,1,0,3.861115576921671,3.861115576921671,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,34.71,55.7,43.96,62.06,6,1,1,0,0,10.83333333333333,13,5,1,3543,918348.8345475002,0,0,3112.048678462018 -13957,17143,31180,-9,31179,31178,3,1,1,27,2,0,0,0,1,-9,2,1,0,0,3,8.283293639947685,8.387428343695918,0,3,0,0,0,-9,0,-942.7388584584004,0,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,0,43,38,15,1,0,-9,1,10.90594453733422,10.90594453733422,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,30.94,61.65,-9,-9,4,1,1,0,0,9.333333333333334,13,5,1,430,-4827.814467100852,0,0,1768.909938075137 -13958,17144,31181,-9,31182,31183,4,1,1,9,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-959.349707016417,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,4,2,0,0,0,12,4,0,907.3333333333334,129330.5252614719,0,0,2354.773322776631 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-14332,17596,32005,-9,-9,-9,1,1,0,41,2,0,1,0,2,-9,2,1,0,0,4,7.61105065212506,7.543620989109203,0,4,0,0,0,-9,0,-1042.196518956185,0,0,1,0,-9,-9,-9,-9,2,2,2019,-9,0,6,0,37,37,15,1,0,-9,0,8.385359043629549,8.385359043629549,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.16,56.15,-9,-9,6,1,1,0,0,10.66666666666667,13,3,0,1255,105311.9384613463,0,0,2603.820569437181 -14332,17597,32006,-9,32005,-9,2,1,0,18,2,0,1,0,3,0,7,2,0,0,4,7.102397069240347,6.706720983222032,0,3,0,0,0,-9,0,-1134.044147724634,-9,1,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,6,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,59,-9,-9,5,1,1,0,0,0,13,3,0,1535,-108779.4176123905,0,0,880.9529606149365 -14333,17598,32007,32008,-9,-9,2,1,0,70,1,0,0,0,2,-9,4,3,0,0,4,0,7.159213477443702,7.475493146264736,1,0,-9,6,0,6,29.09541019915752,0,0,0,0,64,1,3,1,2,1,2019,3,1,10,0,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,2,1,1,0,3.278605359722785,7.268946303232186,3.778606703669755,3,51.83,57.2,54.96,53.17,6,1,1,0,0,0,10,4,1,364,1814209.797244282,0,0,3131.122945049883 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-14510,17823,32390,-9,-9,-9,1,1,0,56,2,0,0,0,2,-9,2,1,0,0,3,7.751217328834977,7.951616505337952,0,3,0,0,0,-9,0,-1012.878508571332,0,0,0,0,-9,-9,-9,-9,3,-9,2019,-9,0,17,4,37,37,15,1,1,-9,0,7.844792693020826,7.844792693020826,0,0,0,0,0,0,0,0,0,0,0,4.362053551957219,0,0,0,43.95,51.24,-9,-9,4,1,1,0,0,7.25,4,3,1,432,-32115.24430716189,0,0,1196.669482367645 -14511,17824,32391,-9,-9,-9,1,1,0,53,2,0,0,0,2,-9,8,3,1,1,3,0,0,0,3,0,0,0,-9,0,-1150.920196501133,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,49,-9,-9,5,1,1,0,1,4.75,13,1,1,1291,127711.9001535085,0,0,0 -14511,17825,32392,-9,32391,-9,2,1,0,25,2,0,0,0,1,-9,2,1,0,0,3,7.594675021582182,7.548494735176109,0,3,0,0,0,-9,0,-858.4089080703384,0,1,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,1,20,26,15,1,0,-9,1,12.87451734293293,12.87451734293293,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.33,53.46,-9,-9,6,1,1,0,0,4.166666666666667,13,3,1,953,147631.3033126997,0,0,1422.907106559247 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-14513,17827,32395,32396,-9,-9,1,1,1,70,1,0,0,0,2,-9,4,3,0,0,4,0,7.739554793542352,7.972222992890871,1,0,-9,45,0,3,-127.8351143544232,0,0,0,0,67,1,3,3,-9,-9,2019,4,2,7,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.697437031772876,7.975791301788676,0,0,54.2,57.49,55.36,51.57,6,1,1,0,0,3.666666666666667,7,3,1,196.5,1156155.570496121,0,0,3770.425081957896 -14513,17827,32396,32395,-9,-9,2,1,0,67,1,0,0,0,1,-9,4,3,0,0,3,0,7.561117101779133,7.207939136324075,1,0,-9,45,0,-3,39.19796480147362,0,0,0,0,70,2,4,3,-9,-9,2019,4,1,10,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,2.523986575859321,7.143839221915222,0,0,55.36,51.57,54.2,57.49,6,1,1,0,0,0,7,3,1,196.5,1156155.570496121,0,0,3770.425081957896 -14514,17828,32397,-9,-9,-9,1,1,1,39,2,0,0,0,3,-9,8,3,1,1,2,0,0,0,3,0,-9,0,-9,0,-968.9289750642655,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,31,12,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,15.88,50.09,-9,-9,1,1,1,0,0,1.5,10,1,0,741,-54908.09414204995,0,0,1428.252052302847 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-14516,17831,32401,-9,32399,32400,3,1,1,30,2,0,0,0,2,-9,2,1,0,0,4,7.714780301519223,8.090850891206138,0,3,0,0,0,-9,0,-1060.76217347261,0,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,10,1,37,38,15,1,0,-9,1,8.18070556438132,8.18070556438132,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,50,57,-9,-9,5,1,1,0,0,1,12,3,0,350,112248.9553410878,0,0,902.4831438242636 -14517,17832,32402,32403,-9,-9,1,1,1,55,1,0,0,0,2,-9,2,1,0,0,4,8.770669083332075,9.160408330313924,7.516316170261804,1,0,-9,37,0,1,35.61200980318227,0,0,0,0,54,3,1,1,3,2,2019,1,2,6,0,50,45,15,1,0,1,0,13.19902886835664,13.19902886835664,0,0,0,0,0,0,0,0,0,0,0,7.308588994484972,0,0,0,57.16,56.15,51.67,26.53,6,1,1,0,0,10.08333333333333,12,5,1,482.5,260107.8065963338,0,0,4100.726974575526 -14517,17832,32403,32402,-9,-9,2,1,0,54,1,0,0,0,3,-9,2,1,0,0,1,6.717935422356161,6.778902273036906,0,1,0,-9,37,0,-1,146.2369535929919,0,0,0,0,55,2,4,1,3,-9,2019,1,1,16,4,16,21,15,1,1,1,0,5.975381988685198,5.975381988685198,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.67,26.53,57.16,56.15,5,1,1,0,0,10.08333333333333,12,5,1,482.5,260107.8065963338,0,0,4100.726974575526 -14518,17833,32404,32405,-9,-9,2,1,1,76,1,0,0,0,3,-9,4,3,0,0,3,0,7.009257367696534,7.210666765622894,1,0,-9,7,0,2,32.42097151004926,0,0,0,0,74,2,2,3,-9,-9,2019,4,1,9,1,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,7.073502083645354,0,0,54,46,55.31,24.55,6,1,1,0,0,0,6,2,1,641,738663.5918100056,0,0,2073.724210053779 -14518,17833,32405,32404,-9,-9,1,1,0,74,1,0,0,0,2,-9,4,3,0,0,2,0,6.059064708879019,6.269594723253102,1,0,-9,53,0,-2,10.94340610669239,0,0,0,0,76,3,3,3,3,3,2019,4,2,12,2,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.245960869780527,6.344049360688361,0,0,55.31,24.55,54,46,6,1,1,0,0,0,6,2,1,641,738663.5918100056,0,0,2073.724210053779 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-14532,17851,32435,32434,-9,-9,2,1,0,62,1,0,0,0,1,-9,4,3,0,0,4,0,6.421586708722122,6.755636739783787,1,0,-9,26,0,0,-24.57461949470583,0,0,0,0,62,2,2,1,-9,-9,2019,3,1,8,1,0,0,15,4,0,1,0,0,0,0,0,0,0,0,0,0,14.5,1,1,0,0,6.880870367129432,17.93293758437126,3,57.57,41.31,33.32,44.29,6,2,3,0,0,3.083333333333333,5,4,1,394.5,496160.1865531503,0,0,1702.388830886223 -14533,17852,32436,-9,-9,-9,1,1,0,76,2,0,0,0,2,-9,4,3,0,0,3,0,8.328563918279908,8.07374400662173,3,0,0,0,-9,0,-837.3926049961105,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,20,8,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,2,1,1,0,8.293679676886393,7.851121346647866,0,3,32.48,46.08,-9,-9,5,1,1,0,0,1.166666666666667,2,4,1,77,916936.2241333297,0,0,4182.185779997689 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-14726,18077,32834,32833,-9,-9,2,1,0,27,1,0,1,0,3,-9,6,3,0,0,4,0,0,0,2,0,-9,6,0,-3,-18.18748596842665,0,1,1,0,30,2,4,1,-9,-9,2019,3,1,11,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,41.17,59.31,44.15,49.61,5,2,3,0,0,0,8,4,0,700.6666666666666,-201685.8364463068,0,0,2256.32666090561 -14726,18077,32835,-9,32834,32833,3,1,0,4,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1001.012847352104,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,61,-9,-9,5,2,3,0,0,0,8,4,0,700.6666666666666,-201685.8364463068,0,0,2256.32666090561 -14727,18078,32836,32837,-9,-9,1,1,1,66,1,0,0,0,2,-9,2,1,0,0,4,8.161075105266697,8.205836883943485,0,1,0,-9,5,0,1,13.89536149178152,0,0,0,0,65,2,3,3,3,2,2019,2,2,5,0,40,40,15,1,0,3,0,9.536201562970543,9.536201562970543,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45.66,43.86,36.93,41.13,4,2,3,0,0,4.583333333333333,4,3,1,1061.5,809878.928937947,0,0,1521.496601356644 -14727,18078,32837,32836,-9,-9,2,1,0,65,1,0,0,0,2,-9,6,3,0,0,3,6.421155063948581,6.482045815005123,0,1,0,-9,5,0,-1,-115.3673592613781,0,0,0,0,66,2,4,1,3,2,2019,3,1,15,3,10,11,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,36.93,41.13,45.66,43.86,5,2,3,0,0,7,4,3,1,1061.5,809878.928937947,0,0,1521.496601356644 -14728,18079,32838,-9,32839,-9,2,1,1,3,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1024.047598052775,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,11,3,1,443,14949.6033884943,0,0,1042.563127490143 -14728,18079,32839,-9,-9,-9,1,1,0,38,2,0,1,0,2,-9,2,1,0,0,5,7.558206101925212,7.405129104582508,0,4,0,0,0,-9,0,-898.1549806913647,0,0,1,0,-9,-9,-9,-9,2,2,2019,-9,0,9,0,22,22,15,1,0,-9,0,10.44988694631869,10.44988694631869,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,62.39,56.71,-9,-9,7,1,1,0,0,7.583333333333333,11,3,1,443,14949.6033884943,0,0,1042.563127490143 -14729,18080,32840,32841,-9,-9,2,1,0,51,1,0,1,0,2,-9,2,1,0,0,5,6.852026817373225,6.419245212205805,0,2,0,-9,28,0,-7,-70.16405325727166,0,0,0,0,58,2,5,1,2,2,2019,1,1,8,0,12,13,15,1,0,1,0,7.300510007407289,7.300510007407289,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.06,57.76,62.39,56.71,7,1,1,0,0,8.5,6,4,1,4445.5,162909.7017938124,0,0,2734.373264539279 -14729,18080,32841,32840,-9,-9,1,1,1,58,1,0,1,0,2,-9,1,1,0,0,5,8.363439057381006,8.296644548959661,6.950052189158933,2,0,-9,9,0,7,-134.908485591356,0,0,0,0,51,2,5,1,-9,-9,2019,1,2,6,0,40,40,15,1,0,1,0,12.0240750234001,12.0240750234001,0,0,0,0,0,0,0,0,1,1,0,4.307768366209752,7.228738988305102,0,0,62.39,56.71,57.06,57.76,7,1,1,0,0,10.66666666666667,6,4,1,4445.5,162909.7017938124,0,0,2734.373264539279 -14729,18081,32842,-9,32840,32841,5,1,1,18,2,0,1,1,2,0,7,2,0,0,4,0,0,0,3,0,0,0,-9,0,-1085.619756134319,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,4,0,0,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,1,1,0,2.277413254275001,0,0,0,54.79,55.86,-9,-9,6,1,1,0,0,1.583333333333333,6,4,1,896,77105.14255937289,0,0,-355.6934449829477 -14730,18082,32843,-9,32847,-9,2,1,0,11,2,1,4,1,3,-9,-9,2,0,0,5,0,0,0,4,0,-9,0,-9,0,-1098.931868357283,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,47,61,-9,-9,5,3,4,0,0,0,8,1,0,1227.4,37299.80749074445,0,0,2478.48765619121 -14730,18082,32844,-9,32847,-9,5,1,0,1,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1020.10522628773,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,3,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,3,4,0,0,0,8,1,0,1227.4,37299.80749074445,0,0,2478.48765619121 -14730,18082,32845,-9,32847,-9,4,1,0,5,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1039.90415956483,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,3,4,0,0,0,8,1,0,1227.4,37299.80749074445,0,0,2478.48765619121 -14730,18082,32846,-9,32847,-9,3,1,0,10,2,1,4,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-1046.94510940106,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,3,4,0,0,0,8,1,0,1227.4,37299.80749074445,0,0,2478.48765619121 -14730,18082,32847,-9,-9,-9,1,1,0,33,2,1,4,0,2,-9,8,3,1,1,1,0,0,0,4,0,-9,0,-9,0,-993.9448054674605,-9,0,1,1,-9,-9,-9,-9,2,2,2019,-9,0,32,11,0,0,15,3,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,16.04,23.99,-9,-9,1,3,4,0,1,0,8,1,0,1227.4,37299.80749074445,0,0,2478.48765619121 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-14732,18084,32850,-9,-9,-9,3,1,1,24,2,0,0,0,2,-9,2,1,0,0,3,8.609093430273624,8.347762910103619,0,3,0,0,0,-9,0,-1068.784371785093,-9,1,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,45,0,15,1,0,-9,1,11.0007820159118,11.0007820159118,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46.08,57.2,-9,-9,5,1,1,0,0,10.25,7,5,1,836,-153311.1436093477,0,0,1791.854076675666 -14733,18085,32851,-9,-9,-9,1,1,1,73,2,0,0,0,2,-9,4,3,0,0,2,0,4.351955216145742,4.435022399835983,3,0,0,0,-9,0,-999.0989733581002,0,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,27,11,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,4.360252766658493,4.455498664711802,0,0,22.98,43.88,-9,-9,2,1,1,0,0,3.833333333333333,11,2,1,934,158639.2038313531,0,0,50.33225786318314 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-14881,18260,33162,-9,33163,33161,3,1,0,11,2,0,1,1,3,-9,-9,2,0,0,5,0,0,0,2,0,0,0,-9,0,-1034.059059171195,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,62,-9,-9,5,1,1,0,0,0,2,4,1,1139.666666666667,462295.9794261379,0,0,3767.806772299307 -14881,18260,33163,33161,-9,-9,2,1,0,46,1,0,1,0,2,-9,2,1,0,0,4,7.498198778954776,7.485351066163505,0,2,0,-9,9,0,-8,17.7679894774626,0,0,0,0,54,2,3,1,-9,-9,2019,1,1,11,0,20,20,15,1,0,1,0,8.631193242932522,8.631193242932522,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52.43,55.57,50.63,50.99,6,1,1,0,0,11.25,2,4,1,1139.666666666667,462295.9794261379,0,0,3767.806772299307 -14882,18261,33164,-9,-9,-9,1,1,1,31,2,0,0,0,3,-9,2,1,0,0,3,7.95763351080203,8.067006471716899,0,3,0,0,0,-9,0,-1066.123056856122,0,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,10,0,40,0,15,1,0,-9,0,10.8830018709955,10.8830018709955,0,0,0,0,0,0,0,0,0,0,0,3.542131682563861,0,0,0,61.01,36.73,-9,-9,2,1,1,0,0,10.25,12,4,1,122,22805.99211574066,0,0,1883.865365413132 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-14942,18333,33292,33291,-9,-9,1,1,1,31,1,0,0,0,1,-9,2,1,0,0,4,8.864763749305553,8.906902500054455,0,1,0,-9,4,0,-1,-25.92125475958973,0,0,0,0,32,1,5,1,-9,-9,2019,1,2,8,0,58,57,15,1,0,1,0,14.10553072884848,14.10553072884848,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,59.43,58.05,6,1,1,0,0,5.25,8,5,1,353.5,50002.83428157506,0,0,5321.891479463675 -14943,18334,33293,-9,33295,33294,3,1,0,9,2,0,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-978.7189490624039,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,2,4,1,772.6666666666666,773693.8799793046,0,0,3709.805046225072 -14943,18334,33294,33295,-9,-9,1,1,1,52,1,0,1,0,2,-9,2,1,0,0,3,8.635624597575408,8.831892861153392,0,2,0,-9,7,0,8,87.06863869466093,0,0,0,0,44,2,4,1,-9,-9,2019,1,2,10,0,60,65,15,1,0,1,0,10.65752459704387,10.65752459704387,0,0,0,0,0,0,0,0,1,1,0,3.192176054303219,0,0,0,50.78,45.45,33.61,61.54,6,1,1,0,0,9.25,2,4,1,772.6666666666666,773693.8799793046,0,0,3709.805046225072 -14943,18334,33295,33294,-9,-9,2,1,0,44,1,0,1,0,2,-9,2,1,0,0,4,7.560856555590436,7.509289010392678,0,2,0,-9,7,0,-8,14.5336302300693,0,0,1,0,52,2,3,1,-9,-9,2019,1,1,9,0,20,20,15,1,0,1,0,12.84978974755703,12.84978974755703,0,0,0,0,0,0,0,0,1,1,0,1.565403359406205,0,0,0,33.61,61.54,50.78,45.45,5,1,1,0,0,9.25,2,4,1,772.6666666666666,773693.8799793046,0,0,3709.805046225072 -14944,18335,33296,-9,-9,-9,1,1,0,71,2,0,0,0,1,-9,4,3,0,0,2,0,7.400748097029616,7.89381165826721,3,0,0,0,-9,0,-992.0550170338059,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,12,0,0,0,15,4,0,-9,0,0,0,1,0,0,1.282215732224214,0,0,0,0,1,1,0,0,7.684037021806541,0,0,56.57,37.79,-9,-9,7,1,1,0,0,0,9,3,0,165,628378.4980327447,0,0,2855.329822652913 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-14953,18345,33309,-9,-9,-9,1,1,0,75,2,0,0,0,3,-9,4,3,0,0,3,0,7.485475514888729,7.368754342263997,3,0,0,0,-9,0,-1102.643894397761,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,11,0,0,0,15,4,0,-9,0,0,0,1,0,0,14.60882573726779,2.446916411866711,0,0,0,1,1,0,5.850237312692509,7.407991469311528,0,0,61.83,36.54,-9,-9,6,2,3,0,0,0,8,3,1,968,9861.685968064412,0,0,925.9542333065141 -14953,18346,33310,33311,33309,-9,2,1,1,51,1,0,0,0,2,-9,2,1,0,0,4,8.450247541619367,8.575499060121006,3.998490059107432,1,0,-9,3,0,20,-80.53827415536335,0,0,0,0,31,2,4,1,3,-9,2019,1,3,11,0,40,40,15,1,0,1,0,16.14752140021332,16.14752140021332,0,0,0,0,0,0,0,0,1,1,0,9.022802680020071,3.986261493292924,0,0,56.33,51.02,58.15,52.91,5,2,3,0,0,6.416666666666667,8,5,1,794.5,466747.9007109831,0,0,7783.165119140324 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-16141,19808,35995,-9,35994,35993,6,1,0,11,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1006.298428019324,-9,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,2,3,0,0,0,6,2,0,585.6,147090.9115352088,0,0,2733.21702678055 -16141,19809,35996,35997,-9,-9,7,1,0,24,1,0,3,0,1,-9,2,1,0,0,4,8.272615711165061,7.963164855621078,0,2,0,-9,1,-9,2,-46.31083204304183,-9,1,1,0,22,2,4,1,-9,-9,2019,1,3,8,0,38,0,15,1,0,1,0,13.50300029574665,13.50300029574665,0,0,0,0,0,0,0,0,1,1,0,2.518846727587675,0,0,0,51.83,57.2,40.46,51.25,6,2,3,0,0,2.583333333333333,6,3,0,677,182600.793184937,0,0,2547.61644794615 -16141,19809,35997,35996,35994,35993,3,1,1,22,1,0,3,0,2,-9,2,1,0,0,4,7.089793854740428,6.871654761707696,0,2,0,1,1,-9,-2,-28.68879491318612,0,1,0,0,24,1,4,1,2,2,2019,1,7,15,2,18,24,15,1,0,1,0,11.90611686412221,11.90611686412221,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,40.46,51.25,51.83,57.2,4,2,3,0,0,6,6,3,0,677,182600.793184937,0,0,2547.61644794615 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-16179,19856,36089,36088,-9,-9,2,1,1,48,1,0,2,0,2,-9,2,1,0,0,4,8.257601343937617,8.007523946288618,0,2,0,-9,9,0,7,-181.3450132939003,0,0,0,0,41,2,4,1,-9,-9,2019,1,1,7,0,37,37,15,1,0,1,0,13.96231582182306,13.96231582182306,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46.98,59.35,32.67,63.54,5,1,1,0,0,10.5,1,4,1,1269.75,778911.2414098815,0,0,3751.102926487474 -16179,19856,36090,-9,36088,36089,4,1,0,6,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1106.161099973994,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,61,-9,-9,5,1,1,0,0,0,1,4,1,1269.75,778911.2414098815,0,0,3751.102926487474 -16180,19857,36091,-9,-9,-9,1,1,1,64,2,0,0,0,3,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-1084.586077070186,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,52.24,10.56,-9,-9,6,1,1,0,0,0,13,1,0,310,113058.6406571396,0,0,1235.171832036555 -16181,19858,36092,-9,-9,-9,1,1,0,73,2,0,0,0,1,-9,4,3,0,0,3,6.140623722472706,7.096971426681593,6.452962921836734,3,0,0,0,-9,0,-1047.857173532777,0,0,0,0,-9,-9,-9,-9,3,1,2019,-9,0,9,0,2,0,15,4,0,-9,0,0,0,1,4.239892561925487,0,0,0,0,21.3956996419938,0,1,1,0,4.629604704982082,7.126973548157775,0,0,51.41,56.15,-9,-9,6,1,1,0,0,7.25,6,2,0,445,524548.9493357455,0,0,785.8158728400182 -16182,19859,36093,36094,-9,-9,2,1,1,67,1,0,0,0,2,-9,1,1,0,0,3,8.237983523363587,7.934504079529033,0,1,0,-9,6,0,1,-53.77451206841162,0,0,0,0,66,2,4,1,-9,-9,2019,1,1,9,0,30,32,15,1,0,1,0,13.71791942682789,13.71791942682789,0,0,0,0,0,0,0,0,1,1,0,3.304734189786072,0,0,0,54.37,54.8,59.14,52.5,5,1,1,0,0,8.333333333333334,10,4,1,247.5,734287.1728534385,0,0,3879.491441290195 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-16188,19867,36103,-9,-9,-9,1,1,0,75,2,0,0,0,3,-9,2,1,0,0,3,7.53215893048994,7.132315884301059,5.00836113324774,3,0,0,0,-9,0,-1115.058163835071,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,6,0,28,28,15,1,0,-9,0,5.891547098977375,5.891547098977375,0,0,0,0,0,0,0,0,1,1,0,6.740490499799954,0,0,0,56.63,49.66,-9,-9,6,1,1,0,0,9.333333333333334,13,3,1,2038,250319.7335220847,0,0,1810.737322486827 -16189,19868,36104,-9,-9,-9,1,1,0,24,2,0,0,0,2,-9,7,2,0,0,4,7.390455502228937,7.255045992613914,0,3,0,0,0,-9,0,-1050.660772000657,1,1,1,0,-9,-9,-9,-9,2,2,2019,-9,0,23,8,22,33,15,2,1,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,24.02,61.9,-9,-9,2,4,2,0,1,5.583333333333333,12,3,0,2476,95575.27283696082,0,0,1342.152371548485 -16190,19869,36105,-9,-9,-9,1,1,0,50,2,0,0,0,2,-9,2,1,0,0,2,8.41689283407492,8.448085817808423,0,3,0,0,0,-9,0,-1033.271529259983,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,9,0,46,48,15,1,0,-9,0,12.26679733624453,12.26679733624453,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53.05,26.08,-9,-9,6,1,1,0,0,8.333333333333334,2,5,1,205,33356.27121895372,0,0,2014.16008837732 -16190,19870,36106,-9,36105,-9,2,1,0,21,2,0,0,0,2,-9,2,1,0,0,1,7.997794890263224,7.921495500750029,0,3,0,0,0,-9,0,-1078.222940886406,0,1,1,0,-9,-9,-9,-9,2,-9,2019,-9,0,32,11,39,40,15,1,1,-9,1,7.690063467034242,7.690063467034242,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.3,47.96,-9,-9,3,1,1,0,0,3.916666666666667,2,4,1,2411,112355.5700218741,0,0,349.877810845986 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-16250,19953,36244,-9,36243,36242,3,1,1,20,2,0,0,1,2,0,7,2,0,0,3,0,0,0,3,0,0,0,-9,0,-1034.871175853487,-9,1,0,0,-9,-9,-9,-9,1,1,2019,-9,0,17,5,0,0,15,2,1,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1.336133095173925,0,0,0,33.12,61.85,-9,-9,5,4,2,0,0,1.583333333333333,9,1,1,170,0,0,0,-138.6227026265464 -16251,19954,36245,-9,-9,-9,1,1,1,69,2,0,0,0,3,-9,4,3,0,1,1,0,0,0,3,0,0,0,-9,0,-916.0882238334437,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,28,11,0,0,15,4,1,-9,0,0,0,1,8.112248412335578,0,0,0,0,50.84125332204304,0,1,1,0,0,0,0,0,23.92,31.55,-9,-9,1,1,1,0,0,0,10,1,0,327,24510.25013467512,0,0,854.9957146004001 -16252,19955,36246,36248,-9,-9,1,1,1,38,1,1,2,0,2,-9,2,1,0,0,3,7.856681841797214,7.826056887686984,0,2,0,-9,7,0,11,-20.57509787028643,0,0,0,0,27,2,3,1,-9,-9,2019,1,2,12,0,49,53,15,1,0,1,0,7.408108042685441,7.408108042685441,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,50.99,49.74,30.94,61.65,5,1,1,0,0,2.833333333333333,5,3,1,887.75,-99378.78512059126,0,0,2859.293893088492 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-16323,20044,36406,36405,-9,-9,1,1,0,56,1,0,0,0,2,-9,2,1,0,0,3,7.592497483895756,7.861991416837347,5.888947450545833,1,0,-9,8,0,5,-42.1613981270012,0,0,0,0,51,2,4,1,3,2,2019,1,2,18,6,24,30,15,1,1,1,0,8.597585694887359,8.597585694887359,0,0,0,0,0,0,0,2,0,0,0,5.836615669240329,0,.7966988905533687,3,46.57,44.73,54.77,55.87,6,1,1,0,0,9.583333333333334,10,5,1,699.5,1128782.154481907,0,0,10885.76359099117 -16324,20045,36407,-9,-9,-9,1,1,1,48,2,0,0,0,2,-9,2,1,0,0,1,6.878654894027752,7.184153257520018,0,3,0,0,0,-9,0,-1007.6991484454,0,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,23,10,40,0,15,1,1,-9,0,2.502225046783584,2.502225046783584,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.76,27.9,-9,-9,2,3,4,0,1,1.25,6,2,0,961,-22493.54035307705,0,0,924.4871326778564 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-16330,20054,36421,-9,36420,36419,5,1,1,7,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1024.128381948463,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,5,3,0,680.6,38700.35451145073,0,0,2871.887423223183 -16330,20054,36422,-9,36420,36419,3,1,1,12,2,0,3,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-981.6197887763876,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,13,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,55,-9,-9,5,1,1,0,0,0,5,3,0,680.6,38700.35451145073,0,0,2871.887423223183 -16331,20055,36423,36425,-9,-9,1,1,0,39,1,0,3,0,1,-9,2,1,0,0,5,8.381088019094323,8.462491598447498,0,2,0,-9,15,0,5,49.48473441212582,0,0,1,0,34,2,4,1,2,2,2019,1,4,3,0,36,32,15,1,0,1,0,14.17178880738607,14.17178880738607,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51.67,60.18,50,57,6,3,4,0,0,9.416666666666666,8,4,0,2203,372046.9652676113,0,0,3470.380180457656 -16331,20055,36424,-9,36423,36425,5,1,0,3,2,0,3,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-962.4699079451058,-9,0,0,0,-9,-9,-9,-9,1,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,3,4,0,0,0,8,4,0,2203,372046.9652676113,0,0,3470.380180457656 -16331,20055,36425,36423,-9,-9,4,1,1,34,1,0,3,0,2,-9,1,1,0,0,4,7.846254956521012,8.418162021225044,0,2,0,-9,8,0,-5,-40.35383939673106,-9,0,0,0,39,1,5,1,-9,-9,2019,1,1,10,1,35,0,15,1,0,1,0,11.94387785741781,11.94387785741781,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,50,57,51.67,60.18,5,3,4,0,0,1,8,4,0,2203,372046.9652676113,0,0,3470.380180457656 -16332,20056,36426,-9,-9,-9,1,1,1,74,2,0,0,0,1,-9,4,3,0,0,5,9.660734247564497,9.722204312622676,0,3,0,-9,0,1,0,-1040.087598326585,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,10,0,10,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.73,58.82,-9,-9,6,1,1,0,0,8,2,5,1,93,6004948.215206128,0,0,5802.600722492833 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-16336,20062,36434,-9,36431,36432,4,1,1,18,2,0,1,1,2,0,7,2,0,0,5,0,0,0,3,0,0,0,-9,0,-1083.575066352073,-9,1,0,0,-9,-9,-9,-9,2,3,2019,-9,0,8,0,0,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,2.75042658554336,0,0,0,62.39,56.71,-9,-9,7,1,1,0,0,0,7,5,1,735,-91130.90540496957,0,0,545.5511858046541 -16337,20063,36435,36436,-9,-9,2,1,0,29,1,0,0,0,1,-9,2,1,0,0,3,7.908239257436545,8.118547542552141,0,1,0,-9,6,0,2,-67.9660892299167,0,1,1,0,27,1,3,1,-9,-9,2019,1,1,15,2,38,38,15,1,0,1,0,7.745241872671609,7.745241872671609,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,39.28,53.83,33.86,52.31,4,1,1,0,0,5.666666666666667,1,3,1,821,-46686.93901867903,0,0,692.4227065299431 -16337,20063,36436,36435,-9,-9,1,1,1,27,1,0,0,0,1,-9,1,1,0,0,3,0,0,0,1,0,-9,6,0,-2,-42.89263472109489,0,1,0,0,29,1,3,1,1,1,2019,1,2,28,10,0,0,15,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,.9648346998477205,0,0,0,33.86,52.31,39.28,53.83,4,1,1,0,1,5.25,1,3,1,821,-46686.93901867903,0,0,692.4227065299431 -16338,20064,36437,-9,-9,-9,1,1,1,22,2,0,0,0,1,0,7,2,0,0,4,4.178068437513052,7.78675521089948,7.580821847721359,3,0,0,0,-9,0,-1142.434496860919,-9,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,15,3,2,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.687269843970923,0,0,0,39.41,61.57,-9,-9,6,1,1,0,0,2.166666666666667,8,3,0,3978,117361.6345840066,0,0,2338.13442787038 -16338,20065,36438,-9,-9,-9,2,1,1,21,2,0,0,1,2,-9,7,2,0,0,3,5.852140760864605,7.604488824552718,7.598109221524641,3,0,-9,0,-9,0,-1069.615649572832,-9,1,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,3,0,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.673431273244208,0,0,0,51.41,56.15,-9,-9,5,1,1,0,0,0,8,3,0,488,-101884.4222900175,0,0,624.3926823678494 -16339,20066,36439,36440,-9,-9,2,1,0,63,1,0,0,0,2,-9,4,3,0,1,2,0,0,0,1,0,-9,7,0,-3,193.4287127638674,0,0,0,0,66,2,2,3,-9,-9,2019,4,1,11,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.867264409687635,0,0,0,42.16,37.92,51.66,38.82,6,1,1,0,0,0,5,3,1,488.5,1339844.984543129,0,0,2107.288449198355 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-16343,20072,36447,-9,-9,-9,1,1,0,52,2,0,0,0,3,-9,8,3,1,1,1,0,0,0,3,0,0,0,-9,0,-958.126297953846,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,14,1,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43.11,15.87,-9,-9,2,1,1,0,0,6.333333333333333,10,1,0,1285,-109404.6670913392,0,0,1884.818783598805 -16344,20073,36448,36449,-9,-9,2,1,1,28,1,0,0,0,1,-9,2,1,0,0,4,8.368596977464879,8.576088059881601,0,1,0,-9,4,0,0,104.8938891451174,0,1,0,0,28,1,5,3,-9,-9,2019,2,1,6,0,39,38,15,1,0,3,0,10.92959136724631,10.92959136724631,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.16,56.15,61.16,53.18,6,1,1,0,0,4.333333333333333,6,3,0,234,71671.4423807617,0,0,1576.927615049374 -16344,20073,36449,36448,-9,-9,1,1,0,28,1,0,0,0,1,1,3,3,0,0,5,0,0,0,1,0,-9,4,0,0,-28.65904291460243,-9,1,1,0,28,1,4,1,3,2,2019,3,2,4,0,0,0,15,3,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,61.16,53.18,57.16,56.15,6,1,1,1,0,5.166666666666667,6,3,0,234,71671.4423807617,0,0,1576.927615049374 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-16376,20108,36518,-9,-9,-9,1,1,0,56,2,0,0,0,2,-9,2,1,0,0,3,8.123164942305992,8.183655393880318,0,3,0,0,0,-9,0,-1039.271245799034,0,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,1,47,46,15,1,0,-9,0,7.200973424537726,7.200973424537726,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,37,59.43,-9,-9,7,1,1,0,0,11.41666666666667,1,4,0,1144,-9503.166667358086,0,0,1096.175895146824 -16376,20109,36519,-9,-9,-9,2,1,0,64,2,0,0,0,2,-9,2,1,0,1,3,7.69993839036508,7.936303275293237,2.770174536374626,3,0,0,0,-9,0,-831.5590124785717,0,0,0,0,-9,-9,-9,-9,-9,-9,2019,-9,0,9,0,43,40,15,1,0,-9,0,6.68005768943763,6.68005768943763,0,0,0,0,0,0,0,0,1,1,0,0,2.914543144186136,0,0,60.88,20.66,-9,-9,6,1,1,0,0,11.41666666666667,1,3,0,1355,386646.4686306332,0,0,1994.577248597573 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-16385,20119,36531,-9,-9,-9,1,1,0,72,2,0,0,0,3,-9,4,3,0,0,4,0,0,0,3,0,0,0,-9,0,-1098.339648729517,0,0,0,0,-9,-9,-9,-9,2,3,2019,-9,0,8,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,56.82,56.51,-9,-9,7,1,1,0,0,0,12,1,0,288,-139997.5461208054,0,0,1653.17777687878 -16386,20120,36532,36535,-9,-9,1,1,1,56,1,0,2,0,2,-9,2,1,0,0,4,7.635012269094862,7.527436586817561,0,2,0,-9,6,0,14,14.89136132383802,0,0,0,0,42,2,4,3,2,2,2019,2,2,26,12,70,60,15,1,1,3,0,2.75231709251192,2.75231709251192,0,0,0,0,0,0,0,0,1,1,0,6.361630762161623,0,0,0,37.02,61.3,25.84,63.8,2,1,1,0,0,8.416666666666666,12,2,1,306.5,40909.8108689784,0,0,1936.065213210864 -16386,20120,36533,-9,36535,36532,4,1,0,9,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1053.386036456776,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,60,-9,-9,5,1,1,0,0,0,12,2,1,306.5,40909.8108689784,0,0,1936.065213210864 -16386,20120,36534,-9,36535,36532,3,1,0,12,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-847.0343943395096,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,59,-9,-9,5,1,1,0,0,0,12,2,1,306.5,40909.8108689784,0,0,1936.065213210864 -16386,20120,36535,36532,-9,-9,2,1,0,42,1,0,2,0,2,-9,3,3,0,0,4,0,0,0,2,0,-9,6,0,-14,-70.7383725898402,0,0,1,0,56,2,4,1,-9,2,2019,3,1,25,11,0,43,15,3,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,2.593302203832502,0,0,0,25.84,63.8,37.02,61.3,3,1,1,1,0,6.583333333333333,12,2,1,306.5,40909.8108689784,0,0,1936.065213210864 -16387,20121,36536,36537,-9,-9,1,1,1,67,1,0,0,0,2,-9,4,3,0,0,3,0,0,0,1,0,-9,10,0,5,0,0,0,0,0,62,3,3,3,3,3,2019,4,2,9,0,0,0,15,4,0,3,0,0,0,1,0,0,0,0,0,0,27.5,1,1,0,0,0,36.4857020619669,3,59.62,30.39,57.33,53.46,6,1,1,0,0,1.333333333333333,13,1,0,691,130112.2272927879,0,0,1746.453980006414 -16387,20121,36537,36536,-9,-9,2,1,0,62,1,0,0,0,3,-9,6,3,0,0,3,0,0,0,1,0,-9,10,0,-5,0,0,0,0,0,67,2,3,3,3,3,2019,4,1,7,0,0,0,15,3,0,4,0,0,0,0,0,0,0,0,0,0,2,1,1,0,0,0,10.13795408545354,3,57.33,53.46,59.62,30.39,6,1,1,0,0,0,13,1,0,691,130112.2272927879,0,0,1746.453980006414 -16388,20122,36538,36539,-9,-9,1,1,0,67,1,0,0,0,1,-9,4,3,0,0,4,0,6.752882380430136,6.863703840346655,1,0,-9,48,0,-3,-89.76583892847999,0,0,0,0,70,1,4,3,3,2,2019,4,2,8,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,5.48,1,1,0,.8394573693278471,6.649881448460655,0,3,54.2,57.49,59.47,44.13,6,1,1,0,0,7.833333333333333,5,4,1,452.5,2970709.368223534,0,0,4221.109017515099 -16388,20122,36539,36538,-9,-9,2,1,1,70,1,0,0,0,1,-9,4,3,0,0,4,0,8.571894974009529,8.588205533793179,1,0,-9,10,0,3,-49.21227162957832,0,0,0,0,67,1,4,3,-9,-9,2019,4,1,6,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,5.48,1,1,0,3.758340348713905,8.914566760483504,2.981408365648214,3,59.47,44.13,54.2,57.49,6,1,1,0,0,4,5,4,1,452.5,2970709.368223534,0,0,4221.109017515099 -16388,20123,36540,-9,36538,36539,3,1,1,39,2,0,0,0,2,-9,2,1,0,0,4,9.086181804246836,8.710021987214269,0,3,0,0,0,-9,0,-1038.065666814085,0,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,12,0,48,49,15,1,0,-9,0,16.27346393640613,16.27346393640613,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45.97,49.04,-9,-9,6,1,1,0,0,10.25,5,5,1,198,236541.211137481,0,0,2102.935557220076 -16388,20124,36541,-9,36538,36539,5,1,1,34,2,0,0,0,3,-9,97,3,0,0,4,0,0,0,3,0,0,0,-9,0,-882.421342101483,0,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,13,1,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,3.020101872115771,0,0,0,38.24,46.08,-9,-9,4,1,1,0,0,0,5,1,1,154,81839.42354934968,0,0,1528.875760803314 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-16390,20126,36544,-9,-9,-9,1,1,0,26,2,0,2,0,2,-9,6,3,0,0,3,0,0,0,4,0,-9,0,-9,0,-1059.294517700162,-9,1,1,0,-9,-9,-9,-9,-9,-9,2019,-9,0,12,0,0,0,15,3,0,-9,0,0,0,0,0,0,0,0,0,0,14.5,1,1,0,0,0,14.41864219601366,3,43.37,57.28,-9,-9,6,1,1,0,0,0,11,1,0,349.3333333333333,-45585.07845637854,0,0,490.7719787403175 -16390,20126,36545,-9,36544,-9,3,1,1,4,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-951.7798032862958,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,11,1,0,349.3333333333333,-45585.07845637854,0,0,490.7719787403175 -16390,20126,36546,-9,36544,-9,2,1,0,5,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,4,0,-9,0,-9,0,-984.6286963509061,-9,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,11,1,0,349.3333333333333,-45585.07845637854,0,0,490.7719787403175 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-16423,20166,36618,-9,36619,36623,8,1,0,6,2,0,5,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-1119.287815820528,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,5,2,0,397,-27475.98578342904,0,0,3299.041237854498 -16423,20166,36619,-9,-9,-9,1,1,0,38,2,0,5,0,3,-9,4,3,0,1,2,0,5.550153885561284,5.489381003215288,4,0,-9,0,1,0,-1088.281460882853,0,0,1,0,-9,-9,-9,-9,3,3,2019,-9,0,24,11,0,0,15,4,1,-9,0,0,0,0,0,0,0,0,0,0,74.5,1,1,0,5.532828645329384,0,75.46543267298155,3,21.55,51.46,-9,-9,3,1,1,0,0,0,5,2,0,397,-27475.98578342904,0,0,3299.041237854498 -16423,20166,36620,-9,36619,36623,6,1,1,9,2,0,5,1,3,-9,-9,2,0,0,4,0,0,0,4,0,0,0,-9,0,-930.1649134511832,-9,0,0,0,-9,-9,-9,-9,3,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,61,-9,-9,5,1,1,0,0,0,5,2,0,397,-27475.98578342904,0,0,3299.041237854498 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-16432,20179,36638,-9,36639,36637,3,1,1,1,2,1,1,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-975.3697448606661,-9,0,0,0,-9,-9,-9,-9,1,1,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,45,62,-9,-9,5,1,1,0,0,0,5,4,1,1173.666666666667,432574.5604242493,0,0,3521.717834934213 -16432,20179,36639,36637,-9,-9,1,1,0,28,1,1,1,0,1,-9,2,1,0,0,5,8.18674524515291,7.932636072445994,0,2,0,-9,6,0,-3,-84.63792187086551,0,1,1,0,31,1,3,1,3,3,2019,1,2,7,0,32,32,15,1,0,1,0,13.78506084693064,13.78506084693064,0,0,0,0,0,0,0,0,1,1,0,2.764746047912932,0,0,0,57.06,57.76,47.15,56.66,6,1,1,0,0,7,5,4,1,1173.666666666667,432574.5604242493,0,0,3521.717834934213 -16433,20180,36640,-9,-9,-9,1,1,0,62,2,0,0,0,2,-9,2,1,0,0,4,8.112113815687009,8.323441450979455,0,3,0,0,0,-9,0,-1101.195896593289,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,10,0,31,31,15,1,0,-9,0,14.95737499839776,14.95737499839776,0,0,0,0,0,0,0,0,0,0,0,3.081455954585744,0,0,0,43.42,62.33,-9,-9,6,1,1,0,0,10.25,7,4,1,244,860314.9800282446,0,0,1777.532925461756 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-16435,20182,36644,36643,-9,-9,2,1,0,54,1,0,1,0,2,-9,2,1,0,0,2,7.628749815896104,8.025680431672075,0,2,0,-9,6,0,-1,33.36984906263293,0,0,0,0,55,1,5,1,2,1,2019,1,1,18,6,30,35,15,1,1,1,0,10.03784189526046,10.03784189526046,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.82,25.25,54.1,59.11,6,1,1,0,0,6.083333333333333,5,5,1,459,1982882.47701674,0,0,5141.342851709799 -16435,20183,36645,-9,36644,36643,3,1,1,22,2,0,1,0,2,-9,7,2,0,0,4,7.735189302372813,7.540109286768831,0,3,0,0,0,-9,0,-1008.785108543661,1,1,0,0,-9,-9,-9,-9,2,1,2019,-9,0,9,0,20,20,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.19,54.26,-9,-9,6,1,1,0,0,4.75,5,3,1,528,-120736.2781049147,0,0,1704.502187199478 -16435,20184,36646,-9,36644,36643,4,1,1,18,2,0,1,1,2,0,7,2,0,0,5,7.250469074164301,6.981684264915127,0,3,0,0,0,-9,0,-1045.39822055131,-9,1,0,0,-9,-9,-9,-9,2,1,2019,-9,0,5,0,30,0,15,2,0,-9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,63.38,53.47,-9,-9,7,1,1,0,0,2.083333333333333,5,5,1,367,110304.8785910711,0,0,335.7601714748854 -16436,20185,36647,36650,-9,-9,1,1,1,39,1,0,2,0,2,-9,2,1,0,0,4,8.370812593720871,8.004516589487706,0,2,0,-9,8,0,5,26.5817603512961,0,0,0,0,34,2,3,1,2,2,2019,1,2,15,4,41,41,15,1,1,1,0,10.07017496966466,10.07017496966466,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,33.66,60.3,48.45,57.49,5,1,1,0,0,6.583333333333333,2,3,1,753.5,186697.573504691,0,0,2543.995263773016 -16436,20185,36648,-9,36650,36647,4,1,0,5,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-937.814923767694,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,12,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,44,60,-9,-9,5,1,1,0,0,0,2,3,1,753.5,186697.573504691,0,0,2543.995263773016 -16436,20185,36649,-9,36650,36647,3,1,1,7,2,0,2,1,3,-9,-9,2,0,0,4,0,0,0,2,0,0,0,-9,0,-1082.136046081673,-9,0,0,0,-9,-9,-9,-9,2,2,2019,-9,0,11,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,46,61,-9,-9,5,1,1,0,0,0,2,3,1,753.5,186697.573504691,0,0,2543.995263773016 -16436,20185,36650,36647,-9,-9,2,1,0,34,1,0,2,0,2,-9,2,1,0,0,3,7.38607372174299,7.218811871048663,0,2,0,-9,8,0,-5,112.6891129162626,0,0,1,0,39,2,4,1,2,1,2019,1,1,17,4,25,25,15,1,1,1,0,7.597745768550743,7.597745768550743,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,48.45,57.49,33.66,60.3,3,1,1,0,0,8.916666666666666,2,3,1,753.5,186697.573504691,0,0,2543.995263773016 -16437,20186,36651,36652,-9,-9,2,1,0,72,1,0,0,0,2,-9,4,3,0,1,2,0,6.163247856361124,5.951881640022305,1,0,-9,54,0,-1,56.65160044565856,0,0,0,0,73,2,3,3,3,3,2019,4,1,14,4,0,0,15,4,1,4,0,0,0,1,3.488091477435544,2.511241117196578,0,0,0,51.34773568232395,7,1,1,0,2.240647504378243,6.278704152272111,7.085007078722962,3,47.51,36.73,58.89,48.6,5,1,1,0,0,.5833333333333334,6,3,1,608.5,737092.501256492,0,0,3624.599438964216 -16437,20186,36652,36651,-9,-9,1,1,1,73,1,0,0,0,2,-9,4,3,0,0,3,0,7.962182403907176,8.135231008570262,1,0,-9,54,0,1,133.398139119293,0,0,0,0,72,2,2,3,3,3,2019,4,2,8,0,0,0,15,4,0,4,0,0,0,0,0,0,0,0,0,0,71.5,1,1,0,8.144745424283428,8.020593052752648,83.18478118351871,1,58.89,48.6,47.51,36.73,5,1,1,0,0,0,6,3,1,608.5,737092.501256492,0,0,3624.599438964216 -16438,20187,36653,36654,-9,-9,1,1,0,52,1,0,0,0,1,-9,2,1,0,0,4,8.494774783574368,8.234739965101166,0,1,0,-9,29,0,-1,5.284948713342157,0,0,0,0,53,1,4,1,1,1,2019,1,2,15,5,40,37,15,1,1,1,0,11.20716466452397,11.20716466452397,0,0,0,0,0,0,0,0,0,0,0,2.985808030446936,0,0,0,43.67,61.06,40.71,62.41,5,1,1,0,0,11.91666666666667,11,5,1,1054,107294.9532258974,0,0,3417.393834408913 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-16439,20189,36657,36659,-9,-9,2,1,0,45,1,0,2,0,2,-9,2,1,0,0,3,8.140001147956625,8.407571543518651,0,2,0,-9,15,0,-3,68.62056111408209,0,0,0,0,48,1,3,1,2,2,2019,1,1,11,0,38,22,15,1,0,1,0,14.21861687404147,14.21861687404147,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,38.51,59.43,42,52.08,6,2,3,0,0,12.83333333333333,6,4,0,1021,486773.4320035863,0,0,2919.761843070592 -16439,20189,36658,-9,36657,36659,4,1,1,12,2,0,2,1,3,-9,-9,2,0,0,3,0,0,0,2,0,0,0,-9,0,-1032.329656985486,-9,0,0,0,-9,-9,-9,-9,2,1,2019,-9,0,13,2,0,0,15,2,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,55,-9,-9,5,2,3,0,0,0,6,4,0,1021,486773.4320035863,0,0,2919.761843070592 -16439,20189,36659,36657,-9,-9,1,1,1,48,1,0,2,0,1,-9,2,1,0,0,3,7.414870609019281,7.373257783183679,0,2,0,-9,15,0,3,-67.88983666110623,0,0,0,0,45,2,3,1,3,2,2019,1,2,7,0,23,30,15,1,0,1,0,8.870970722367954,8.870970722367954,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,42,52.08,38.51,59.43,7,2,3,0,0,12.75,6,4,0,1021,486773.4320035863,0,0,2919.761843070592 -16440,20190,36660,36661,-9,-9,2,1,0,32,1,0,0,0,1,-9,2,1,0,0,5,8.601108460947893,8.66699462315462,0,1,0,-9,2,0,0,74.20356365001012,0,0,1,0,32,1,5,1,-9,-9,2019,1,1,6,0,37,37,15,1,0,1,0,15.538991545859,15.538991545859,0,0,0,0,0,0,0,0,0,0,0,7.274835178673739,0,0,0,54.69,57.47,51.73,58.82,6,1,1,0,0,4.583333333333333,4,5,1,703,113067.2508082312,0,0,4087.261246689986 -16440,20190,36661,36660,-9,-9,1,1,1,32,1,0,0,0,1,1,2,1,0,0,5,7.967295955414346,7.841342176115283,0,1,0,-9,2,0,0,18.16045135067595,-9,0,0,0,32,1,5,1,-9,-9,2019,1,2,10,0,38,0,15,1,0,1,0,9.684325263374307,9.684325263374307,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.73,58.82,54.69,57.47,6,1,1,0,0,3.916666666666667,4,5,1,703,113067.2508082312,0,0,4087.261246689986 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-16442,20192,36664,36663,-9,-9,2,1,1,41,1,0,0,0,2,-9,2,1,0,0,4,8.038399853070858,8.223738175052716,0,1,0,-9,6,0,3,121.4776442750649,0,0,0,0,38,2,3,1,-9,-9,2019,1,1,8,0,43,61,15,1,0,1,0,10.72161457894946,10.72161457894946,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,39.16,62.84,42.5,53.5,4,1,1,0,0,5.166666666666667,11,5,1,1607.5,54605.6673034104,0,0,3308.416065854891 -16443,20193,36665,-9,-9,-9,1,1,0,71,2,0,0,0,2,-9,4,3,0,0,4,0,7.845260819962205,8.081824408710085,3,0,0,0,-9,0,-979.4182838093622,0,0,0,0,-9,-9,-9,-9,3,3,2019,-9,0,6,0,0,0,15,4,0,-9,0,0,0,0,0,0,0,0,0,0,0,1,1,0,7.872896025987903,5.544761118197106,0,0,55.34,54.26,-9,-9,6,1,1,0,0,0,10,3,1,835,432515.63428848,0,0,2407.44982828972 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-16520,20289,36845,-9,-9,-9,1,1,1,62,2,0,0,0,2,-9,2,1,0,0,3,0,0,0,3,0,0,0,-9,0,-1087.575220893412,0,0,0,0,-9,-9,-9,-9,2,-9,2019,-9,0,7,0,40,38,15,1,0,-9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.0115369389747,0,0,0,68.2,37.54,-9,-9,6,1,1,0,0,6.416666666666667,9,1,0,243,380286.2882842355,0,0,-495.8715429980742 -16521,20290,36846,36847,-9,-9,1,1,0,52,1,0,0,0,2,-9,2,1,0,0,4,9.569350154402883,9.229022948204307,0,1,0,-9,30,0,-1,75.71601867108785,0,0,0,0,53,1,4,1,1,3,2019,1,2,7,0,30,38,15,1,0,1,0,47.53182744256672,47.53182744256672,0,0,0,0,0,0,0,0,1,1,0,3.260485443423613,0,0,0,54.2,57.49,54,54,6,1,1,0,0,8.5,2,5,1,561,2338733.041468623,0,0,8033.839703110787 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+850,1072,1994,-9,-9,-9,1,1,77,0,0,0,3,-9,0,2,0,6.617223201503691,7.259651350260167,0,0,-954.0593476842016,0,3,3,2019,10,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.921478419952268,0,0,59.3,39.29,-9,-9,5,1,1,0,0,0,9,2,1,657,879767.4271166606,161192.8664083745,674030.0667709068,0,1275.144389372664 +851,1073,1995,-9,-9,-9,1,0,52,0,0,0,1,-9,0,4,8.09945660543667,7.97345603786466,0,0,0,-1065.523481936182,0,1,1,2019,5,0,40,40,1,0,0,8.98369724889924,8.98369724889924,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53.18,34.96,-9,-9,7,3,4,0,0,4,4,4,0,325,473183.2284889342,198728.9281797566,88309.80713028394,10248.29843106792,855.3311419636336 +851,1074,1996,-9,1995,-9,1,0,19,0,0,1,2,0,0,4,0,0,0,0,0,-762.5769113512499,-9,1,-9,2019,6,0,0,0,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.12,57.34,-9,-9,5,4,2,0,0,0,4,1,0,192,0,0,0,0,1574.84448288597 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+852,1076,1999,-9,1998,1997,1,1,22,0,0,0,2,-9,0,4,6.981601278104297,7.106717169132629,0,0,0,-892.3862600412592,-9,2,2,2019,11,2,35,0,1,0,1,3.400127623150084,3.400127623150084,0,0,0,0,0,0,0,0,0,0,0,.8838266501668083,0,0,0,49,58,-9,-9,5,1,1,0,0,1,9,2,1,207,225204.0755092959,0,0,0,1.594526470469532 +853,1077,2000,-9,-9,-9,1,0,74,0,0,0,2,-9,0,2,0,0,0,0,0,-1162.532204212288,0,2,2,2019,11,0,0,0,4,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,.7498081501778031,0,0,0,49.91,42.12,-9,-9,6,2,3,0,0,0,9,1,1,4014,100173.7017444912,0,151520.3020904074,0,1120.909013490163 +854,1078,2001,-9,-9,-9,1,0,46,0,0,0,3,-9,0,3,7.512220841615243,7.708618740651223,0,4,15,-43.82691726425884,0,3,3,2019,21,9,35,44,1,1,0,5.904966982242791,5.904966982242791,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,52.66,27.15,39.33,58.88,3,1,1,0,0,10,12,4,1,217,41505.20514650396,72913.66532417561,0,0,1535.216767516701 +854,1079,2002,-9,-9,-9,1,0,31,0,0,0,1,-9,0,4,8.277330359021041,8.571699361418663,0,4,-15,-43.71890656425116,0,3,2,2019,12,0,42,42,1,0,0,11.60460246336884,11.60460246336884,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,39.33,58.88,52.66,27.15,6,1,1,0,1,8,12,4,1,957,57052.71138812667,-3928.226814338268,0,0,1315.468147718943 +855,1080,2003,2004,-9,-9,1,0,26,0,0,0,2,-9,0,4,8.105231124646041,7.855493591584071,0,1,-11,-105.054854262084,-9,-9,-9,2019,8,0,43,0,1,0,0,7.242100246572542,7.242100246572542,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,51.31,46.4,61.11,48.86,6,1,1,0,0,3,7,4,0,1192.5,-82684.39959661828,-31489.76053912225,142445.8505719318,84056.86769216994,3154.470978976145 +855,1080,2004,2003,-9,-9,1,1,37,0,0,0,1,-9,0,4,8.125347552497976,8.080973241560883,0,1,11,-14.54078893502088,0,2,2,2019,8,0,40,42,1,0,0,11.0790996102428,11.0790996102428,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,61.11,48.86,51.31,46.4,5,1,1,0,1,11,7,4,0,1192.5,-82684.39959661828,-31489.76053912225,142445.8505719318,84056.86769216994,3154.470978976145 +856,1081,2005,2006,-9,-9,1,1,36,0,0,0,1,-9,0,3,7.878090308538606,8.037584751799034,0,7,0,67.53308559162382,0,-9,-9,2019,12,3,38,38,1,0,0,6.458444718186032,6.458444718186032,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.98,56.3,37.93,54.93,5,1,1,0,0,4,2,4,0,400.5,182560.4595712337,166221.5895333324,0,0,1980.162711439389 +856,1081,2006,2005,-9,-9,1,0,36,0,0,0,2,-9,0,2,7.632842973997858,7.829737634544792,0,7,0,56.07122254489045,0,3,3,2019,17,4,38,38,1,1,0,7.819494905777576,7.819494905777576,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.93,54.93,45.98,56.3,2,1,1,0,1,6,2,4,0,400.5,182560.4595712337,166221.5895333324,0,0,1980.162711439389 +857,1082,2007,2008,-9,-9,1,0,60,0,0,0,2,-9,0,3,0,5.528287224380623,5.529499039036813,40,-3,-113.8168798851709,0,3,2,2019,9,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4.934637443621374,5.858842757243737,0,0,57.1,41.16,53.83,53.69,6,1,1,0,0,0,5,5,1,588.5,1832059.339036152,1227349.230162734,492227.5833566887,0,7278.07106432506 +857,1082,2008,2007,-9,-9,1,1,63,0,0,0,1,-9,0,5,9.727889033423281,10.20256594268801,8.525636845396582,40,3,50.5704841286107,0,2,3,2019,6,0,20,20,1,0,0,115.0532006765326,115.0532006765326,0,0,0,0,0,0,0,0,0,0,0,9.272145099203803,8.907207891981452,0,0,53.83,53.69,57.1,41.16,6,1,1,0,0,8,5,5,1,588.5,1832059.339036152,1227349.230162734,492227.5833566887,0,7278.07106432506 +858,1083,2009,-9,-9,-9,1,0,80,0,0,0,1,-9,0,4,0,7.196081039301721,7.1601757869176,0,0,-982.1407523762714,0,3,3,2019,7,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,6.312299507524904,7.134411419616329,0,0,57.7,50.34,-9,-9,6,1,1,0,0,0,7,3,1,1035,798988.7618092478,140220.2106842625,482424.2290440097,0,1734.363400349179 +859,1084,2010,2011,-9,-9,1,0,58,0,0,0,2,-9,0,3,0,0,0,30,0,-1.036414708815385,0,3,2,2019,14,2,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.117254742040907,0,0,0,43.71,56.91,56.33,51.02,4,1,1,0,0,0,10,4,1,893.5,1294319.192448855,1074640.866243824,220499.8579061097,0,1803.636463709502 +859,1084,2011,2010,-9,-9,1,1,58,0,0,0,2,-9,0,4,8.461528564349637,8.566254539476141,0,30,0,-22.6767731196599,0,-9,-9,2019,6,0,43,45,1,0,0,16.6549395077841,16.6549395077841,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,56.33,51.02,43.71,56.91,6,1,1,0,0,9,10,4,1,893.5,1294319.192448855,1074640.866243824,220499.8579061097,0,1803.636463709502 +859,1085,2012,-9,2010,2011,1,1,24,0,0,0,2,-9,0,4,8.440560436870973,8.230296655123055,0,0,0,-964.4206065529398,-9,2,2,2019,10,1,40,0,1,0,1,9.710195129092856,9.710195129092856,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,49,58,-9,-9,5,1,1,0,0,1,10,4,1,241,228069.5302697623,0,0,0,252.6314952506386 +860,1086,2013,2014,-9,-9,1,0,70,0,0,0,3,-9,0,3,0,0,0,10,-7,-14.85989562260325,0,3,3,2019,8,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,53.42,43,53,47,6,1,1,0,0,1,13,2,1,528.5,309516.5215644314,146444.7938644884,95633.23960871747,0,1711.437789114696 +860,1086,2014,2013,-9,-9,1,1,77,0,0,0,2,-9,0,3,0,6.306044547280732,6.224797010841993,10,7,18.44466189050024,0,3,3,2019,7,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,6.141122288601717,0,0,53,47,53.42,43,6,1,1,0,0,0,13,2,1,528.5,309516.5215644314,146444.7938644884,95633.23960871747,0,1711.437789114696 +861,1087,2015,-9,-9,-9,1,0,65,0,0,0,2,-9,0,2,0,7.481953584859506,7.872084114097083,0,0,-1050.144926545703,0,1,2,2019,13,2,0,0,4,0,0,0,0,1,0,0,0,0,0,0,14.5,1,1,0,5.574583611179556,8.162467602228439,12.57973017090013,3,51.41,45.62,-9,-9,4,1,1,0,0,5,7,3,1,993,1024776.962696745,524514.6715224404,268799.0187160288,0,1588.056659604563 +862,1088,2016,2017,-9,-9,1,0,64,0,1,0,2,-9,0,3,0,7.864511437686534,7.580984815212357,2,-3,-78.45587721561749,0,3,1,2019,13,1,0,0,4,0,0,0,0,0,0,0,0,0,0,0,14.5,1,1,0,3.314686377095009,7.367219422984043,13.83745127074164,3,42.22,56.11,51,48,2,1,1,0,0,1,5,2,1,485.5,690467.0173051367,257600.1280489038,622531.9364128115,116362.9090934357,1333.801037719654 +862,1088,2017,2016,-9,-9,1,1,67,0,1,0,2,-9,0,3,0,0,0,2,3,143.2013322838019,0,-9,-9,2019,10,1,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,51,48,42.22,56.11,5,1,1,0,0,0,5,2,1,485.5,690467.0173051367,257600.1280489038,622531.9364128115,116362.9090934357,1333.801037719654 +862,1089,2018,-9,2019,-9,1,0,4,0,1,1,3,-9,0,4,0,0,0,0,0,-756.5493986062172,-9,2,-9,2019,13,2,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,43,61,-9,-9,5,1,1,0,0,0,5,4,1,949,317002.2513118608,104069.6423250609,228439.3694375448,125938.6719768764,1807.185337594959 +862,1089,2019,-9,2016,2017,1,0,32,0,1,0,2,-9,0,4,8.224146873693517,7.958686542803316,5.572991514289402,0,0,-1066.123646566836,0,2,2,2019,11,0,43,43,1,0,0,10.76154391369749,10.76154391369749,0,0,0,0,0,0,0,2,1,1,0,6.119956412970674,0,14.04263257057072,3,48.76,53.24,-9,-9,5,1,1,0,0,11,5,4,1,949,317002.2513118608,104069.6423250609,228439.3694375448,125938.6719768764,1807.185337594959 +863,1090,2020,2021,-9,-9,1,0,56,0,0,0,1,-9,0,3,8.1918592156395,7.970019325095133,0,31,-5,35.28098326925673,-9,3,3,2019,11,2,18,0,1,0,0,24.54048593778955,24.54048593778955,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48,48,40.88,41.16,5,3,4,0,0,10,8,3,1,839,1399099.672557321,529133.2595736773,233028.7227373626,0,1979.018863106578 +863,1090,2021,2020,-9,-9,1,1,61,0,0,0,1,-9,0,2,0,0,0,37,5,81.21830343389746,0,2,2,2019,12,0,0,20,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.88,41.16,48,48,5,1,1,0,0,7,8,3,1,839,1399099.672557321,529133.2595736773,233028.7227373626,0,1979.018863106578 +864,1091,2022,2023,-9,-9,1,1,68,0,0,0,3,-9,0,4,6.732327195328312,7.236469410386663,5.909847170582237,27,6,123.5211167637629,0,3,3,2019,6,0,20,26,1,0,0,4.573830076552673,4.573830076552673,0,0,0,0,0,0,0,0,1,1,0,6.242790423837625,6.197470052687905,0,0,57.16,56.15,49.88,59.37,6,1,1,0,0,10,6,5,1,666.5,318649.3730183063,96512.90574534012,119875.0564787656,0,3433.403057277766 +864,1091,2023,2022,-9,-9,1,0,62,0,0,0,2,-9,0,4,8.661330767538161,9.142875331171854,3.829373021175977,28,-6,-78.11017725110275,-9,2,3,2019,9,1,10,0,1,0,0,65.30282428736733,65.30282428736733,0,0,0,0,0,0,0,2,1,1,0,3.792075780538459,3.763255518019414,6.901535093173234,3,49.88,59.37,57.16,56.15,6,1,1,0,0,10,6,5,1,666.5,318649.3730183063,96512.90574534012,119875.0564787656,0,3433.403057277766 +865,1092,2024,2025,-9,-9,1,1,63,0,0,0,2,-9,1,3,0,8.011876438536783,7.898837375479737,42,3,-61.04841842721697,0,-9,2,2019,21,9,0,0,3,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,8.236225384921136,0,0,26.91,41.62,42.62,33.25,2,1,1,0,0,7,2,4,1,292.5,1411008.572852867,64175.72318879656,316661.5027253933,70426.39567426965,3809.099622609726 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+8959,10993,20204,20205,-9,-9,1,0,31,1,2,0,1,-9,0,5,8.325358022167865,8.589583543099312,0,12,-7,-61.31825592145867,0,2,2,2019,8,0,37,35,1,0,0,12.88193125060046,12.88193125060046,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,57.06,57.76,61.58,48.86,6,1,1,0,0,10,12,5,1,794.25,649662.170308746,206600.1674157071,281673.2235738987,30013.63876561361,4092.240063736358 +8959,10993,20205,20204,-9,-9,1,1,38,1,2,0,2,-9,0,5,8.316233785323467,8.608326774946292,0,7,7,-27.81529494433786,0,1,2,2019,6,0,40,36,1,0,0,13.99110502274766,13.99110502274766,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,61.58,48.86,57.06,57.76,6,1,1,0,0,10,12,5,1,794.25,649662.170308746,206600.1674157071,281673.2235738987,30013.63876561361,4092.240063736358 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z{OIVdZDM%S`h)!x+32$}(gK_+Vo8c@XBu%&#*hL`gBx1|B-x(_ydM&7&cxpuacQ;7w9ty30ltQSJh%lVI5|Bnlz8F&F)AuuwedQJaW8FUAuM*iNii>Z zEm0Ef&Ty7MwO-Z6?W%Ncd;9wHX)d=cmsO+yliraYitRV-{%09diMto>h%e6T4|1>8 z5;D2=#FL%h3NZKTCNty=rXZy%lJ9Qcuq+ho2t-+K-Vz)*PnW;MMLw$qM-xF4$XS`O zPjeGwUoH3zo+1ed6#IdM4k=OxCZoSiZqHPV3j!Tt_tJp=U1msQADTgs?sZ@YJsvdH z=;9s-v?ljo)lB|ZHUFa|#zd&_us5%W{D0LR>tBUmk5$V7n@hA<#qd9hQ{=Bw{zol_ zhLj#-TYT|9%3b-dLSWVX-Qj5;_FEv(8P$JV%t5x+gSqH$Zo*uauwaw+zW{88t%eSH z+T4UZ>Ji<4>$-9Js|x>7*Ne>_B%vUXsu>uB zt?pmt!2Pebau)wp0(i)Wjo8S|pDW6b#ehKQkN*{!VgCp!q<142 z!k`WWv$X_*K(yxnWhIQ@Sn@}d$o57sFE|G~@!bf1MF0OIJ8}?+^k1=oKoKQK;U=&s znExx%sR=9v_NhWvHi4PB{&u<8e!&?G0$~sOS5dD9gG?Pv)SMhXU_VB8a56*gH-IVW c|Gy)_rX1P7I0!URgXC)lGvAu4$JPb= 50 - MaleLeisure_FemaleLeisure, //Male leisure interacted with female leisure + Constant, + couple_emp_2ft, + couple_emp_2ne, + couple_emp_2pt, + couple_emp_ftne, + couple_emp_ftpt, + couple_emp_ptne, + Cut1, // ordered probit/logit cut points - ignore these when evaluating score + Cut10, + Cut2, + Cut3, + Cut4, + Cut5, + Cut6, + Cut7, + Cut8, + Cut9, + FemaleEduH_1, + FemaleEduH_10, + FemaleEduH_2, + FemaleEduH_20, + FemaleEduH_3, + FemaleEduH_30, + FemaleEduH_4, + FemaleEduH_40, + FemaleEduM_1, + FemaleEduM_10, + FemaleEduM_2, + FemaleEduM_20, + FemaleEduM_3, + FemaleEduM_30, + FemaleEduM_4, + FemaleEduM_40, + FemaleHoursAbove40, FemaleLeisure, //24*7 - labour supply weekly for Female - FemaleLeisureSq, - FemaleLeisure_IncomeDiv100, + FemaleLeisure_DChildren017, //Male leisure interacted with dummy for presence of children aged 0 - 17 + FemaleLeisure_DChildren1317, //Male leisure interacted with dummy for presence of children aged 13-17 + FemaleLeisure_DChildren2Under, + FemaleLeisure_DChildren36, //Male leisure interacted with dummy for presence of children aged 3 - 6 + FemaleLeisure_DChildren712, //Male leisure interacted with dummy for presence of children aged 7 - 12 + FemaleLeisure_dnc, + FemaleLeisure_dnc02, + FemaleLeisure_FemaleAge50Above, //Female leisure interacted with dummy for age >= 50 FemaleLeisure_FemaleAgeDiv100, //Female Leisure interacted with age of Female FemaleLeisure_FemaleAgeSqDiv10000, - FemaleLeisure_NChildren017, - FemaleLeisure_DChildren2Under, FemaleLeisure_FemaleDeh_c3_Low, FemaleLeisure_FemaleDeh_c3_Medium, + FemaleLeisure_IncomeDiv100, + FemaleLeisure_NChildren017, FemaleLeisure_UKC, FemaleLeisure_UKD, FemaleLeisure_UKE, @@ -1452,44 +1431,69 @@ public enum Regressors { FemaleLeisure_UKL, FemaleLeisure_UKM, FemaleLeisure_UKN, - FemaleLeisure_FemaleAge50Above, //Female leisure interacted with dummy for age >= 50 - FixedCostMale, - FixedCostMale_NorthernRegions, - FixedCostMale_SouthernRegions, + FemaleLeisureSq, + FixedCost_Female, + FixedCost_Male, + FixedCostByHighEducation, FixedCostFemale, + FixedCostFemale_DChildren2Under, + FixedCostFemale_Dlltsdsp, //Fixed cost interacted with dummy for partner being long-term sick or disabled + FixedCostFemale_Lesspc3_Student, //Fixed cost interacted with dummy for partner being a student + FixedCostFemale_NChildren017, FixedCostFemale_NorthernRegions, FixedCostFemale_SouthernRegions, - FixedCostMale_NChildren017, + FixedCostFemaleByDchildren2under, + FixedCostFemaleByNumberChildren, + FixedCostMale, FixedCostMale_DChildren2Under, - FixedCostFemale_NChildren017, - FixedCostFemale_DChildren2Under, - - MaleHoursAbove40, - FemaleHoursAbove40, - - //Additional regressors for single female or single male benefitUnits: - - MaleLeisure_DChildren1317, //Male leisure interacted with dummy for presence of children aged 13-17 - MaleLeisure_DChildren712, //Male leisure interacted with dummy for presence of children aged 7 - 12 - MaleLeisure_DChildren36, //Male leisure interacted with dummy for presence of children aged 3 - 6 - MaleLeisure_DChildren017, //Male leisure interacted with dummy for presence of children aged 0 - 17 FixedCostMale_Dlltsdsp, //Fixed cost interacted with dummy for partner being long-term sick or disabled FixedCostMale_Lesspc3_Student, //Fixed cost interacted with dummy for partner being a student - - FemaleLeisure_DChildren1317, //Male leisure interacted with dummy for presence of children aged 13-17 - FemaleLeisure_DChildren712, //Male leisure interacted with dummy for presence of children aged 7 - 12 - FemaleLeisure_DChildren36, //Male leisure interacted with dummy for presence of children aged 3 - 6 - FemaleLeisure_DChildren017, //Male leisure interacted with dummy for presence of children aged 0 - 17 - FixedCostFemale_Dlltsdsp, //Fixed cost interacted with dummy for partner being long-term sick or disabled - FixedCostFemale_Lesspc3_Student, //Fixed cost interacted with dummy for partner being a student - - // Additional variables for re-estimated LS processes - FixedCost_Male, - FixedCost_Female, - IncomeDiv100_MaleAgeDiv100, - IncomeDiv100_MaleAgeSqDiv10000, + FixedCostMale_NChildren017, + FixedCostMale_NorthernRegions, + FixedCostMale_SouthernRegions, + FixedCostMaleByDchildren2under, + FixedCostMaleByNumberChildren, + Graduate, + Homeownership_D, // Indicator: does the benefit unit own home? + HoursFemale, + HoursFemaleByAgeFemale, + HoursFemaleByAgeFemaleSquared, + HoursFemaleByDchildren13_17, + HoursFemaleByDchildren2under, + HoursFemaleByDchildren3_6, + HoursFemaleByDchildren7_12, + HoursFemaleByDelderly, + HoursFemaleByDregion, + HoursFemaleByIncome, + HoursFemaleSquared, + HoursMale, + HoursMaleByAgeMale, + HoursMaleByAgeMaleSquared, + HoursMaleByDelderly, + HoursMaleByDregion, + HoursMaleByHoursFemale, + HoursMaleByIncome, + HoursMaleByNumberChildren, + HoursMaleSquared, + Hrs_36plus_Female, + Hrs_36plus_Male, + Income, + IncomeByAge, + IncomeByAgeSquared, + IncomeByNumberChildren, + IncomeDiv100, //Disposable monthly income from donor household divided by 100 + IncomeDiv100_DChildren2Under, //Income divided by 100 interacted with dummy for presence of children aged 0-2 in the household IncomeDiv100_dnc, IncomeDiv100_dnc02, + IncomeDiv100_FemaleAgeDiv100, + IncomeDiv100_FemaleAgeSqDiv10000, + IncomeDiv100_MaleAgeDiv100, + IncomeDiv100_MaleAgeSqDiv10000, + IncomeDiv100_MeanPartnersAgeDiv100, //Income divided by 100 interacted with mean age of male and female in the household divided by 100 + IncomeDiv100_MeanPartnersAgeSqDiv10000, //Income divided by 100 interacted with square of mean age of male and female in the household divided by 100 + IncomeDiv100_NChildren017, //Income divided by 100 interacted with the number of children aged 0-17 + IncomeSqDiv10000, //Income squared divided by 10000 + IncomeSquared, L1_lhw_1, L1_lhw_10, L1_lhw_2, @@ -1498,107 +1502,244 @@ public enum Regressors { L1_lhw_30, L1_lhw_4, L1_lhw_40, - L1_lhw_Male_1, L1_lhw_Female_1, - L1_lhw_Male_2, + L1_lhw_Female_10, + L1_lhw_Female_11, + L1_lhw_Female_12, + L1_lhw_Female_13, + L1_lhw_Female_14, L1_lhw_Female_2, - L1_lhw_Male_3, + L1_lhw_Female_20, + L1_lhw_Female_21, + L1_lhw_Female_22, + L1_lhw_Female_23, + L1_lhw_Female_24, L1_lhw_Female_3, - L1_lhw_Male_4, + L1_lhw_Female_30, + L1_lhw_Female_31, + L1_lhw_Female_32, + L1_lhw_Female_33, + L1_lhw_Female_34, L1_lhw_Female_4, + L1_lhw_Female_40, + L1_lhw_Female_41, + L1_lhw_Female_42, + L1_lhw_Female_43, + L1_lhw_Female_44, + L1_lhw_Male_1, L1_lhw_Male_10, - L1_lhw_Female_10, L1_lhw_Male_11, - L1_lhw_Female_11, L1_lhw_Male_12, - L1_lhw_Female_12, L1_lhw_Male_13, - L1_lhw_Female_13, L1_lhw_Male_14, - L1_lhw_Female_14, + L1_lhw_Male_2, L1_lhw_Male_20, - L1_lhw_Female_20, L1_lhw_Male_21, - L1_lhw_Female_21, L1_lhw_Male_22, - L1_lhw_Female_22, L1_lhw_Male_23, - L1_lhw_Female_23, L1_lhw_Male_24, - L1_lhw_Female_24, + L1_lhw_Male_3, L1_lhw_Male_30, - L1_lhw_Female_30, L1_lhw_Male_31, - L1_lhw_Female_31, L1_lhw_Male_32, - L1_lhw_Female_32, L1_lhw_Male_33, - L1_lhw_Female_33, L1_lhw_Male_34, - L1_lhw_Female_34, + L1_lhw_Male_4, L1_lhw_Male_40, - L1_lhw_Female_40, L1_lhw_Male_41, - L1_lhw_Female_41, L1_lhw_Male_42, - L1_lhw_Female_42, L1_lhw_Male_43, - L1_lhw_Female_43, L1_lhw_Male_44, - L1_lhw_Female_44, - MaleEduM_10, + Liwwh_1, + Liwwh_10, + Liwwh_2, + Liwwh_20, + Liwwh_3, + Liwwh_30, + Liwwh_4, + Liwwh_40, + Liwwh_5, + Liwwh_50, + Liwwh_6, + Liwwh_60, + Liwwh_Female_01, + Liwwh_Female_02, + Liwwh_Female_03, + Liwwh_Female_04, + Liwwh_Female_05, + Liwwh_Female_06, + Liwwh_Female_1, + Liwwh_Female_10, + Liwwh_Female_11, + Liwwh_Female_12, + Liwwh_Female_13, + Liwwh_Female_14, + Liwwh_Female_15, + Liwwh_Female_16, + Liwwh_Female_2, + Liwwh_Female_20, + Liwwh_Female_21, + Liwwh_Female_22, + Liwwh_Female_23, + Liwwh_Female_24, + Liwwh_Female_25, + Liwwh_Female_26, + Liwwh_Female_3, + Liwwh_Female_30, + Liwwh_Female_31, + Liwwh_Female_32, + Liwwh_Female_33, + Liwwh_Female_34, + Liwwh_Female_35, + Liwwh_Female_36, + Liwwh_Female_4, + Liwwh_Female_40, + Liwwh_Female_41, + Liwwh_Female_42, + Liwwh_Female_43, + Liwwh_Female_44, + Liwwh_Female_45, + Liwwh_Female_46, + Liwwh_Female_5, + Liwwh_Female_50, + Liwwh_Female_51, + Liwwh_Female_52, + Liwwh_Female_53, + Liwwh_Female_54, + Liwwh_Female_55, + Liwwh_Female_56, + Liwwh_Female_6, + Liwwh_Female_60, + Liwwh_Female_61, + Liwwh_Female_62, + Liwwh_Female_63, + Liwwh_Female_64, + Liwwh_Female_65, + Liwwh_Female_66, + Liwwh_Male_01, + Liwwh_Male_02, + Liwwh_Male_03, + Liwwh_Male_04, + Liwwh_Male_05, + Liwwh_Male_06, + Liwwh_Male_1, + Liwwh_Male_10, + Liwwh_Male_11, + Liwwh_Male_12, + Liwwh_Male_13, + Liwwh_Male_14, + Liwwh_Male_15, + Liwwh_Male_16, + Liwwh_Male_2, + Liwwh_Male_20, + Liwwh_Male_21, + Liwwh_Male_22, + Liwwh_Male_23, + Liwwh_Male_24, + Liwwh_Male_25, + Liwwh_Male_26, + Liwwh_Male_3, + Liwwh_Male_30, + Liwwh_Male_31, + Liwwh_Male_32, + Liwwh_Male_33, + Liwwh_Male_34, + Liwwh_Male_35, + Liwwh_Male_36, + Liwwh_Male_4, + Liwwh_Male_40, + Liwwh_Male_41, + Liwwh_Male_42, + Liwwh_Male_43, + Liwwh_Male_44, + Liwwh_Male_45, + Liwwh_Male_46, + Liwwh_Male_5, + Liwwh_Male_50, + Liwwh_Male_51, + Liwwh_Male_52, + Liwwh_Male_53, + Liwwh_Male_54, + Liwwh_Male_55, + Liwwh_Male_56, + Liwwh_Male_6, + Liwwh_Male_60, + Liwwh_Male_61, + Liwwh_Male_62, + Liwwh_Male_63, + Liwwh_Male_64, + Liwwh_Male_65, + Liwwh_Male_66, + MaleEduH_1, MaleEduH_10, - MaleEduM_20, + MaleEduH_2, MaleEduH_20, - MaleEduM_30, + MaleEduH_3, MaleEduH_30, - MaleEduM_40, + MaleEduH_4, MaleEduH_40, MaleEduM_1, - MaleEduH_1, + MaleEduM_10, MaleEduM_2, - MaleEduH_2, + MaleEduM_20, MaleEduM_3, - MaleEduH_3, + MaleEduM_30, MaleEduM_4, - MaleEduH_4, - FemaleEduM_10, - FemaleEduH_10, - FemaleEduM_20, - FemaleEduH_20, - FemaleEduM_30, - FemaleEduH_30, - FemaleEduM_40, - FemaleEduH_40, - FemaleEduM_1, - FemaleEduH_1, - FemaleEduM_2, - FemaleEduH_2, - FemaleEduM_3, - FemaleEduH_3, - FemaleEduM_4, - FemaleEduH_4, + MaleEduM_40, + MaleHoursAbove40, + MaleLeisure, //24*7 - labour supply weekly for male + MaleLeisure_DChildren017, //Male leisure interacted with dummy for presence of children aged 0 - 17 + MaleLeisure_DChildren1317, //Male leisure interacted with dummy for presence of children aged 13-17 + MaleLeisure_DChildren2Under, + MaleLeisure_DChildren36, //Male leisure interacted with dummy for presence of children aged 3 - 6 + MaleLeisure_DChildren712, //Male leisure interacted with dummy for presence of children aged 7 - 12 MaleLeisure_dnc, - FemaleLeisure_dnc, MaleLeisure_dnc02, - FemaleLeisure_dnc02, - IncomeDiv100_FemaleAgeDiv100, - IncomeDiv100_FemaleAgeSqDiv10000, - //Other - Homeownership_D, // Indicator: does the benefit unit own home? - - //Enums for use with the tax-benefit matching method + MaleLeisure_FemaleLeisure, //Male leisure interacted with female leisure + MaleLeisure_IncomeDiv100, + MaleLeisure_MaleAge50Above, //Male leisure interacted with dummy for age >= 50 + MaleLeisure_MaleAgeDiv100, //Male Leisure interacted with age of male + MaleLeisure_MaleAgeSqDiv10000, + MaleLeisure_MaleDeh_c3_Low, + MaleLeisure_MaleDeh_c3_Medium, + MaleLeisure_NChildren017, + MaleLeisure_UKC, + MaleLeisure_UKD, + MaleLeisure_UKE, + MaleLeisure_UKF, + MaleLeisure_UKG, + MaleLeisure_UKH, + MaleLeisure_UKJ, + MaleLeisure_UKK, + MaleLeisure_UKL, + MaleLeisure_UKM, + MaleLeisure_UKN, + MaleLeisureSq, MaximumAge, // Returns maximum age of responsible individuals in the benefit (tax) unit MinimumAge, // Returns maximum age of all people in benefit unit - NumberMembersOver17, // Return number of members of benefit unit aged over 17 + n_children_0, + n_children_1, + n_children_10, + n_children_11, + n_children_12, + n_children_13, + n_children_14, + n_children_2, + n_children_3, + n_children_4, + n_children_5, + n_children_6, + n_children_7, + n_children_8, + n_children_9, NumberChildren04, // Return number of children aged <0;5) - NumberChildren59, NumberChildren1017, NumberChildren517, // Return number of children aged <5;17> - - // regressors for childcare costs - Constant, - Year_transformed, + NumberChildren59, + NumberMembersOver17, // Return number of members of benefit unit aged over 17 + single_emp_ft, + single_emp_ne, + single_emp_pt, UKC, UKD, UKE, @@ -1611,41 +1752,7 @@ public enum Regressors { UKL, UKM, UKN, - n_children_0, - n_children_1, - n_children_2, - n_children_3, - n_children_4, - n_children_5, - n_children_6, - n_children_7, - n_children_8, - n_children_9, - n_children_10, - n_children_11, - n_children_12, - n_children_13, - n_children_14, - couple_emp_2ft, - couple_emp_ftpt, - couple_emp_2pt, - couple_emp_ftne, - couple_emp_ptne, - couple_emp_2ne, - single_emp_ft, - single_emp_pt, - single_emp_ne, - Graduate, - Cut1, // ordered probit/logit cut points - ignore these when evaluating score - Cut2, - Cut3, - Cut4, - Cut5, - Cut6, - Cut7, - Cut8, - Cut9, - Cut10, + Year_transformed, } @@ -2107,9 +2214,23 @@ public double getDoubleValue(Enum variableID) { case HoursMaleSquared -> { return getMale().getLabourSupplyHoursWeekly() * getMale().getLabourSupplyHoursWeekly(); } + case Hrs_36plus_Male -> { + if (getMale() != null) { + return getMale().getLabourSupplyHoursWeekly() >=36 ? 1.:0.; + } else{ + return 0.; + } + } case HoursFemaleSquared -> { return getFemale().getLabourSupplyHoursWeekly() * getFemale().getLabourSupplyHoursWeekly(); } + case Hrs_36plus_Female -> { + if (getFemale() != null) { + return getFemale().getLabourSupplyHoursWeekly() >=36 ? 1.:0.; + } else{ + return 0.; + } + } case HoursMaleByIncome -> { return getMale().getLabourSupplyHoursWeekly() * getDisposableIncomeMonthlyUpratedToBasePriceYear() * 1.e-3; } @@ -2441,6 +2562,272 @@ public double getDoubleValue(Enum variableID) { case L1_lhw_Female_44 -> { return (getMale() != null && getFemale() != null && getMale().getLabourSupplyWeekly().equals(Labour.FORTY) && getFemale().getLabourSupplyWeekly().equals(Labour.FORTY)) ? getFemale().getL1LabourSupplyHoursWeekly() : 0.; } + case Liwwh_1 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_1 for non-single woman"); + } + } + case Liwwh_10 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_10 for non-single man"); + } + } + case Liwwh_2 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_2 for non-single woman"); + } + } + case Liwwh_20 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_20 for non-single man"); + } + } + case Liwwh_3 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_3 for non-single woman"); + } + } + case Liwwh_30 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_30 for non-single man"); + } + } + case Liwwh_4 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_4 for non-single woman"); + } + } + case Liwwh_40 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_40 for non-single man"); + } + } + case Liwwh_5 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_5 for non-single woman"); + } + } + case Liwwh_50 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_50 for non-single man"); + } + } + case Liwwh_6 -> { + if (Occupancy.Single_Female.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_6 for non-single woman"); + } + } + case Liwwh_60 -> { + if (Occupancy.Single_Male.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_60 for non-single man"); + } + } + case Liwwh_Female_1 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_2 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_3 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_4 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_5 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_6 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getMale().atRiskOfWork()) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Female_10, Liwwh_Female_20, Liwwh_Female_30, Liwwh_Female_40, Liwwh_Female_50, Liwwh_Female_60 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.ZERO)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_01, Liwwh_Female_11, Liwwh_Female_21, Liwwh_Female_31, Liwwh_Female_41, Liwwh_Female_51, Liwwh_Female_61 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_02, Liwwh_Female_12, Liwwh_Female_22, Liwwh_Female_32, Liwwh_Female_42, Liwwh_Female_52, Liwwh_Female_62 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_03, Liwwh_Female_13, Liwwh_Female_23, Liwwh_Female_33, Liwwh_Female_43, Liwwh_Female_53, Liwwh_Female_63 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_04, Liwwh_Female_14, Liwwh_Female_24, Liwwh_Female_34, Liwwh_Female_44, Liwwh_Female_54, Liwwh_Female_64 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_05, Liwwh_Female_15, Liwwh_Female_25, Liwwh_Female_35, Liwwh_Female_45, Liwwh_Female_55, Liwwh_Female_65 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Female_06, Liwwh_Female_16, Liwwh_Female_26, Liwwh_Female_36, Liwwh_Female_46, Liwwh_Female_56, Liwwh_Female_66 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getFemale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getFemale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Female_XY for non-couple"); + } + } + case Liwwh_Male_1 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_2 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_3 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_4 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_5 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_6 -> { + if (Occupancy.Couple.equals(getOccupancy()) && !getFemale().atRiskOfWork()) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + return 0.; + } + } + case Liwwh_Male_01, Liwwh_Male_02, Liwwh_Male_03, Liwwh_Male_04, Liwwh_Male_05, Liwwh_Male_06 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.ZERO)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_10, Liwwh_Male_11, Liwwh_Male_12, Liwwh_Male_13, Liwwh_Male_14, Liwwh_Male_15, Liwwh_Male_16 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TEN)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_20, Liwwh_Male_21, Liwwh_Male_22, Liwwh_Male_23, Liwwh_Male_24, Liwwh_Male_25, Liwwh_Male_26 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.TWENTY)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_30, Liwwh_Male_31, Liwwh_Male_32, Liwwh_Male_33, Liwwh_Male_34, Liwwh_Male_35, Liwwh_Male_36 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_40, Liwwh_Male_41, Liwwh_Male_42, Liwwh_Male_43, Liwwh_Male_44, Liwwh_Male_45, Liwwh_Male_46 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.THIRTY_EIGHT)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_50, Liwwh_Male_51, Liwwh_Male_52, Liwwh_Male_53, Liwwh_Male_54, Liwwh_Male_55, Liwwh_Male_56 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FORTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } + case Liwwh_Male_60, Liwwh_Male_61, Liwwh_Male_62, Liwwh_Male_63, Liwwh_Male_64, Liwwh_Male_65, Liwwh_Male_66 -> { + if (Occupancy.Couple.equals(getOccupancy())) { + return (getMale().getLabourSupplyWeekly().equals(Labour.FIFTY_FIVE)) ? getMale().getLiwwh() : 0.; + } else { + throw new RuntimeException("request for parameter Liwwh_Male_XY for non-couple"); + } + } case MaleEduM_10 -> { return (getMale() != null && getMale().getLabourSupplyWeekly().equals(Labour.TEN) && getMale().getDeh_c3().equals(Education.Medium)) ? 1. : 0.; } @@ -2794,7 +3181,6 @@ protected void homeownership() { if (innovations.getDoubleDraw(6) < prob) { male_homeowner = true; } - male.setDhhOwned(male_homeowner); } if (female!=null) { @@ -2802,7 +3188,6 @@ protected void homeownership() { if (innovations.getDoubleDraw(7) < prob) { female_homeowner = true; } - female.setDhhOwned(female_homeowner); } if (male_homeowner || female_homeowner) { //If neither person in the BU is a homeowner, BU not classified as owning home setDhhOwned(true); @@ -2864,25 +3249,25 @@ public void initialiseLiquidWealth(int age, double donorLiquidWealth, double don wealth += (1.0 - Parameters.getPensionWealthDiscount(age)) * donorPensionWealth; if (!Parameters.projectHousingWealth) wealth += (1.0 - Parameters.getHousingWealthDiscount(age)) * donorHousingWealth; - setLiquidWealth(wealth); + setTotalWealth(wealth); } - public double getLiquidWealth() { + public double getTotalWealth() { return getLiquidWealth(true); } public double getLiquidWealth(boolean throwError) { - if (!Parameters.checkFinite(liquidWealth)) { + if (!Parameters.checkFinite(totalWealth)) { if (throwError) throw new RuntimeException("Call to get benefit unit liquid wealth before it is initialised."); else return 0.0; } - return liquidWealth; + return totalWealth; } - public void setLiquidWealth(Double liquidWealth) { - this.liquidWealth = liquidWealth; + public void setTotalWealth(Double liquidWealth) { + this.totalWealth = liquidWealth; } public double getPensionWealth() { @@ -3350,10 +3735,10 @@ private void updateRetirementPensions() { Person refPerson = getRefPersonForDecisions(); boolean toRetire = refPerson.considerRetirement(); Occupancy occupancy = getOccupancy(); - if (toRetire && getLiquidWealth() > 0.0) { - pensionIncomeAnnual = liquidWealth * Parameters.SHARE_OF_WEALTH_TO_ANNUITISE_AT_RETIREMENT / + if (toRetire && getTotalWealth() > 0.0) { + pensionIncomeAnnual = totalWealth * Parameters.SHARE_OF_WEALTH_TO_ANNUITISE_AT_RETIREMENT / Parameters.annuityRates.getAnnuityRate(occupancy, getYear()-refPerson.getDag(), refPerson.getDag()); - liquidWealth *= (1.0 - Parameters.SHARE_OF_WEALTH_TO_ANNUITISE_AT_RETIREMENT); + totalWealth *= (1.0 - Parameters.SHARE_OF_WEALTH_TO_ANNUITISE_AT_RETIREMENT); // upate person variables double val; @@ -3387,7 +3772,7 @@ public void setInvestmentIncomeAnnual() { Person male = getMale(); Person female = getFemale(); - if (getLiquidWealth() < 0) { + if (getTotalWealth() < 0) { double wageFactor = 0.0; if (male != null) wageFactor += 0.7 * male.getEarningsWeekly(DecisionParams.FULLTIME_HOURS_WEEKLY) * 52.0; @@ -3396,15 +3781,15 @@ public void setInvestmentIncomeAnnual() { if (wageFactor < 0.1) { phi = 1.0; } else { - phi = - liquidWealth / wageFactor; + phi = -totalWealth / wageFactor; } phi = Math.min(phi, 1.0); investmentIncomeAnnual = (Parameters.getTimeSeriesRate(model.getYear(), TimeVaryingRate.RealDebtCostLow)*(1.0-phi) + Parameters.getTimeSeriesRate(model.getYear(), TimeVaryingRate.RealDebtCostHigh)*phi + - Parameters.realInterestRateInnov) * liquidWealth; + Parameters.realInterestRateInnov) * totalWealth; } else { investmentIncomeAnnual = (Parameters.getTimeSeriesRate(model.getYear(), TimeVaryingRate.RealSavingReturns) + - Parameters.realInterestRateInnov) * liquidWealth; + Parameters.realInterestRateInnov) * totalWealth; } if ((investmentIncomeAnnual < -20000000.0) || (investmentIncomeAnnual > 200000000.0)) throw new RuntimeException("odd projection for annual investment income: " + investmentIncomeAnnual); @@ -3447,7 +3832,7 @@ void updateDiscretionaryConsumption() { throw new RuntimeException("Disposable income not defined."); } - double cashOnHand = Math.max(getLiquidWealth(), DecisionParams.getMinWealthByAge(getIntValue(Regressors.MaximumAge))) + double cashOnHand = Math.max(getTotalWealth(), DecisionParams.getMinWealthByAge(getIntValue(Regressors.MaximumAge))) + getDisposableIncomeMonthly()*12.0 + states.getAvailableCredit() - getNonDiscretionaryConsumptionPerYear(); if (!Parameters.checkFinite(cashOnHand)) { throw new RuntimeException("Problem identifying cash on hand"); @@ -3754,24 +4139,24 @@ public void removeMember(Person member) { public static void setBenefitUnitIdCounter(long id) {benefitUnitIdCounter = id;} - /** - * Calculates the labour innovation value for the current period with persistence. - * - * This method implements a persistence mechanism for labour innovations where there's - * a probability that the previous period's innovation will persist into the current period. - * A new innovation is drawn each period, but it's only used with probability (1 - persistenceProbability). - * - * The persistence mechanism works as follows: - * 1. Draw a new potential innovation value - * 2. Draw a random number to determine if we should use the new value or persist with the old one - * 3. If it's the first period or there was a gap in years, use the new innovation - * 4. Otherwise, use the persistence probability to decide between new and old values - * - * @param persistenceProbability The probability (between 0 and 1) that the previous period's - * innovation will persist. A value of 0 means always use new innovations, - * while 1 means always keep the old innovation. - * @return The labour innovation value for this period - */ + /** + * Calculates the labour innovation value for the current period with persistence. + * + * This method implements a persistence mechanism for labour innovations where there's + * a probability that the previous period's innovation will persist into the current period. + * A new innovation is drawn each period, but it's only used with probability (1 - persistenceProbability). + * + * The persistence mechanism works as follows: + * 1. Draw a new potential innovation value + * 2. Draw a random number to determine if we should use the new value or persist with the old one + * 3. If it's the first period or there was a gap in years, use the new innovation + * 4. Otherwise, use the persistence probability to decide between new and old values + * + * @param persistenceProbability The probability (between 0 and 1) that the previous period's + * innovation will persist. A value of 0 means always use new innovations, + * while 1 means always keep the old innovation. + * @return The labour innovation value for this period + */ private double getLabourInnovation(double persistenceProbability) { double newLabourInnovation = innovations.getDoubleDraw(5); @@ -3800,8 +4185,15 @@ private double getLabourInnovation(double persistenceProbability) { lastYear = currentYear; return labourInnov; + } - - + private Person getSingle() { + if (getMale() != null & getFemale() == null) { + return null; + } else if (getMale() != null) { + return getMale(); + } else { + return getFemale(); } + } } diff --git a/src/main/java/simpaths/model/LabourMarket.java b/src/main/java/simpaths/model/LabourMarket.java index 0d74e06bc..b6401b7f9 100644 --- a/src/main/java/simpaths/model/LabourMarket.java +++ b/src/main/java/simpaths/model/LabourMarket.java @@ -241,6 +241,9 @@ Need to model wages and hours of work (as the other labour supply module would d } //Update Labour Supply +// for (BenefitUnit benefitUnit : benefitUnitsAllRegions) { +// benefitUnit.updateLabourSupplyAndIncome(); +// } benefitUnitsAllRegions.parallelStream() .forEach(BenefitUnit::updateLabourSupplyAndIncome); diff --git a/src/main/java/simpaths/model/Person.java b/src/main/java/simpaths/model/Person.java index 1c62b9bc5..ef47b03d5 100644 --- a/src/main/java/simpaths/model/Person.java +++ b/src/main/java/simpaths/model/Person.java @@ -80,7 +80,7 @@ public class Person implements EventListener, IDoubleSource, IIntSource, Weight, @Enumerated(EnumType.STRING) private Les_c7_covid les_c7_covid; //Activity (employment) status used in the Covid-19 models @Transient private Les_c4 les_c4_lag1; //Lag(1) of activity_status @Transient private Les_c7_covid les_c7_covid_lag1; //Lag(1) of 7-category activity status - @Transient private Integer liwwh; //Work history in months (number of months in employment) (Note: this is monthly in EM, but simulation updates annually so increment by 12 months). + @Column(name="liwwh") private Integer liwwh; //Work history in months (number of months in employment) (Note: this is monthly in EM, but simulation updates annually so increment by 12 months). @Enumerated(EnumType.STRING) private Indicator dlltsd; //Long-term sick or disabled if = 1 @Transient private Indicator dlltsd_lag1; //Lag(1) of long-term sick or disabled @Enumerated(EnumType.STRING) @Column(name="need_socare") private Indicator needSocialCare; @@ -99,7 +99,7 @@ public class Person implements EventListener, IDoubleSource, IIntSource, Weight, @Transient private Boolean socialCareFromDaughter; @Transient private Boolean socialCareFromSon; @Transient private Boolean socialCareFromOther; - @Column(name="socare_provided_hrs") private Double careHoursProvidedWeekly; + @Column(name="carehoursprovidedweekly") private Double careHoursProvidedWeekly; @Enumerated(EnumType.STRING) @Column(name="socare_provided_to") private SocialCareProvision socialCareProvision; @Transient private SocialCareProvision socialCareProvision_lag1; @Transient private Indicator needSocialCare_lag1; @@ -147,8 +147,6 @@ public class Person implements EventListener, IDoubleSource, IIntSource, Weight, @Column(name="he_eq5d") private Double he_eq5d; @Column(name="financial_distress") private Boolean financialDistress; - - @Column(name="dhh_owned") private Boolean dhhOwned; // Person is a homeowner, true / false @Transient private Boolean receivesBenefitsFlag_L1; // Lag(1) of whether person receives benefits @Transient private Boolean receivesBenefitsFlag; // Does person receive benefits @Column(name="econ_benefits_uc") private Boolean receivesBenefitsFlagUC; // Person receives UC @@ -310,7 +308,6 @@ public Person(Gender gender, Person mother) { lifetimeIncome = 0.; sIndexYearMap = new LinkedHashMap(); bornInSimulation = true; - dhhOwned = false; receivesBenefitsFlag = false; receivesBenefitsFlagNonUC = false; receivesBenefitsFlagUC = false; @@ -472,8 +469,6 @@ else if (dag > Parameters.MAX_AGE_TO_LEAVE_CONTINUOUS_EDUCATION) dhe = originalPerson.dhe; dhm = originalPerson.dhm; - isHomeOwner_lag1 = originalPerson.dhhOwned; - if (originalPerson.dhe_lag1 != null) { //If original person misses lagged level of health, assign current level of health as lagged value dhe_lag1 = originalPerson.dhe_lag1; } else { @@ -541,7 +536,6 @@ else if (dag > Parameters.MAX_AGE_TO_LEAVE_CONTINUOUS_EDUCATION) yearlyEquivalisedConsumptionSeries = new Series.Double(this, DoublesVariables.EquivalisedConsumptionYearly); yearlyEquivalisedConsumption = originalPerson.yearlyEquivalisedConsumption; sIndexYearMap = new LinkedHashMap(); - dhhOwned = originalPerson.dhhOwned; dot01 = originalPerson.dot01; receivesBenefitsFlag = originalPerson.receivesBenefitsFlag; receivesBenefitsFlag_L1 = originalPerson.receivesBenefitsFlag_L1; @@ -1854,7 +1848,7 @@ public double getLiquidWealth() { if (dag <= Parameters.AGE_TO_BECOME_RESPONSIBLE) { return 0.0; } else if (benefitUnit != null) { - return (Occupancy.Couple.equals(benefitUnit.getOccupancy())) ? benefitUnit.getLiquidWealth() / 2.0 : benefitUnit.getLiquidWealth(); + return (Occupancy.Couple.equals(benefitUnit.getOccupancy())) ? benefitUnit.getTotalWealth() / 2.0 : benefitUnit.getTotalWealth(); } else { throw new RuntimeException("Call to get liquid wealth for person object without benefit unit assigned"); } @@ -2290,6 +2284,7 @@ public enum DoublesVariables { CareToPartnerOnly_L1, Cohort, Constant, // For the constant (intercept) term of the regression + Covid_D, Covid_2020_D, Covid_2021_D, Covid19GrossPayMonthly_L1, @@ -3853,6 +3848,9 @@ else throw new IllegalArgumentException( case D_Home_owner_L1, Dhh_owned_L1 -> { return isHomeOwner_lag1 ? 1. : 0.; } // Evaluated at the level of a benefit unit. If required, can be changed to individual-level homeownership status. + case Covid_D -> { + return (getYear() > 2019 & getYear() < 2023) ? 1. : 0.; + } case Covid_2020_D -> { return (getYear() == 2020) ? 1. : 0.; } @@ -4986,14 +4984,6 @@ public void setCovidModuleGrossLabourIncomeBaseline_Xt5(Quintiles covidModuleGro this.covidModuleGrossLabourIncomeBaseline_Xt5 = covidModuleGrossLabourIncomeBaseline_Xt5; } - public boolean isDhhOwned() { - return dhhOwned; - } - - public void setDhhOwned(boolean dhh_owned) { - this.dhhOwned = dhh_owned; - } - public boolean isReceivesBenefitsFlag() { return receivesBenefitsFlag; } @@ -5651,4 +5641,8 @@ public void updateLtIncome() { } public Individual getLtIncomeDonor() {return ltIncomeDonor;} + + public Integer getLiwwh() { + return liwwh; + } } diff --git a/src/main/java/simpaths/model/decisions/States.java b/src/main/java/simpaths/model/decisions/States.java index 2739c82e6..fd655aab4 100644 --- a/src/main/java/simpaths/model/decisions/States.java +++ b/src/main/java/simpaths/model/decisions/States.java @@ -64,7 +64,7 @@ public States(BenefitUnit benefitUnit, GridScale scale) { // populate wealth double val; - val = Math.min(Math.max(benefitUnit.getLiquidWealth(), DecisionParams.getMinWealthByAge(ageYears)), DecisionParams.getMaxWealthByAge(ageYears)); + val = Math.min(Math.max(benefitUnit.getTotalWealth(), DecisionParams.getMinWealthByAge(ageYears)), DecisionParams.getMaxWealthByAge(ageYears)); val = Math.log(val + DecisionParams.C_LIQUID_WEALTH); populate(Axis.LiquidWealth, val); diff --git a/src/main/java/simpaths/model/enums/Labour.java b/src/main/java/simpaths/model/enums/Labour.java index 420f72177..e37c71d9c 100644 --- a/src/main/java/simpaths/model/enums/Labour.java +++ b/src/main/java/simpaths/model/enums/Labour.java @@ -15,7 +15,10 @@ public enum Labour implements IntegerValuedEnum { TEN(10, 6, 15), TWENTY(20, 16, 25), THIRTY(30, 26, 35), - FORTY(40, 36, Parameters.MAX_LABOUR_HOURS_IN_WEEK); + THIRTY_EIGHT(38, 36, 40), + FORTY(40, 36, Parameters.MAX_LABOUR_HOURS_IN_WEEK), + FORTY_FIVE(45, 41, 49), + FIFTY_FIVE(55, 50, Parameters.MAX_LABOUR_HOURS_IN_WEEK); private final int hours, minBound, maxBound; Labour(int hours, int minBound, int maxBound) { @@ -56,8 +59,12 @@ private static Labour convertHoursToLabourInternal(int hoursWorked) { return Labour.TWENTY; } else if (hoursWorked <= 35) { return Labour.THIRTY; + } else if (hoursWorked <= 40) { + return Labour.THIRTY_EIGHT; + } else if (hoursWorked <= 49) { + return Labour.FORTY_FIVE; } else { - return Labour.FORTY; + return Labour.FIFTY_FIVE; } } diff --git a/src/test/java/simpaths/integrationtest/expected/EmploymentStatistics1.csv b/src/test/java/simpaths/integrationtest/expected/EmploymentStatistics1.csv index 074417009..aeb46bbc9 100644 --- a/src/test/java/simpaths/integrationtest/expected/EmploymentStatistics1.csv +++ b/src/test/java/simpaths/integrationtest/expected/EmploymentStatistics1.csv @@ -1,9 +1,9 @@ run,time,id_EmploymentStatistics1,EmpToNotEmp,NotEmpToEmp,PropEmployed,PropUnemployed, -1,2019.0,1,0.09074711961040503,0.35912531539108494,0.6883149240096338,0.172826177227805, -1,2020.0,1,0.08529902311174649,0.22314814814814815,0.6689643717299227,0.19815629931068848, -1,2021.0,1,0.07200686947988223,0.24427168576104746,0.6649758855812407,0.20031598203891568, -1,2022.0,1,0.05939498278406296,0.23995127892813642,0.6736325035384231,0.19065856298393138, -2,2019.0,1,0.09074711961040503,0.35912531539108494,0.6883149240096338,0.172826177227805, -2,2020.0,1,0.08529902311174649,0.22314814814814815,0.6689643717299227,0.19815629931068848, -2,2021.0,1,0.07200686947988223,0.24427168576104746,0.6649758855812407,0.20031598203891568, -2,2022.0,1,0.05939498278406296,0.23995127892813642,0.6736325035384231,0.19065856298393138, \ No newline at end of file +1,2019.0,1,0.07657975099835565,0.49482312338222606,0.7276956305034059,0.13648446585811597, +1,2020.0,1,0.010929577464788733,0.31957547169811323,0.7674669768214671,0.09869568829442552, +1,2021.0,1,0.011645299145299146,0.21739130434782608,0.7767523073085557,0.09162717219589257, +1,2022.0,1,0.016505466778805718,0.20640569395017794,0.7801081980857262,0.08722430295464004, +2,2019.0,1,0.07657975099835565,0.49482312338222606,0.7276956305034059,0.13648446585811597, +2,2020.0,1,0.010929577464788733,0.31957547169811323,0.7674669768214671,0.09869568829442552, +2,2021.0,1,0.011645299145299146,0.21739130434782608,0.7767523073085557,0.09162717219589257, +2,2022.0,1,0.016505466778805718,0.20640569395017794,0.7801081980857262,0.08722430295464004, \ No newline at end of file diff --git a/src/test/java/simpaths/integrationtest/expected/HealthStatistics1.csv b/src/test/java/simpaths/integrationtest/expected/HealthStatistics1.csv index e3b3b6c12..a8c7f557b 100644 --- a/src/test/java/simpaths/integrationtest/expected/HealthStatistics1.csv +++ b/src/test/java/simpaths/integrationtest/expected/HealthStatistics1.csv @@ -1,25 +1,25 @@ run,time,id_HealthStatistics1,N,dhe_mcs_mean,dhe_mcs_median,dhe_mcs_p_10,dhe_mcs_p_25,dhe_mcs_p_75,dhe_mcs_p_90,dhe_pcs_mean,dhe_pcs_median,dhe_pcs_p_10,dhe_pcs_p_25,dhe_pcs_p_75,dhe_pcs_p_90,dhm_mean,dhm_median,dhm_p_10,dhm_p_25,dhm_p_75,dhm_p_90,dls_mean,dls_median,dls_p_10,dls_p_25,dls_p_75,dls_p_90,gender,qalys,wellbys, -1,2019.0,1,11824,47.5736180649524,49.44,33.45,42.0125,54.96,57.93,51.8826911366716,55.0,38.98,48.98,57.76,59.89,11.464140730717185,10.0,6.0,8.0,13.0,19.0,5.086941813261164,6.0,3.0,4.0,6.0,6.0,Total,9906.052344066891,94518.28571428571, -1,2019.0,1,5817,48.65735258724435,51.0,35.02,43.67,55.79,58.32,52.31592401581564,55.01,40.498,49.81,57.72,59.64,10.909059652741963,10.0,6.0,7.0,12.0,18.0,5.117586384734399,6.0,3.0,5.0,6.0,6.0,Male,4965.820273018077,46779.857142857145, -1,2019.0,1,6007,46.52416181122022,48.45,32.028,40.79,54.37,57.33,51.46316131180291,54.92,37.396,47.94,57.76,59.982,12.001664724488098,11.0,6.0,8.0,14.0,20.0,5.057266522390544,6.0,3.0,4.0,6.0,6.0,Female,4940.23207104888,47738.42857142857, -1,2020.0,1,11811,46.9828317203763,48.21192291876018,38.139179489624965,43.73076483727526,51.57207071785401,53.7132160991283,51.89472384047728,54.223965975401605,42.1216050844597,49.45973025022309,56.746370723429685,58.16824835160589,11.80500826154653,11.488701946577724,4.805864582913094,7.946269988151016,15.354730475209958,19.080519072823943,5.117178901024468,5.0,4.0,5.0,6.0,6.0,Total,9914.700221785752,94975.57142857142, -1,2020.0,1,5817,47.937520371254315,49.21301353520895,39.48041228341415,44.97992462055961,52.226120467594924,54.214410364925534,52.40630893745394,54.481089902035976,43.58297754270954,50.491669218527754,56.85750575025777,58.31187241795759,11.257209188744934,10.929051995783485,4.297229704265973,7.4410056627296335,14.757943096101776,18.502432022806637,5.094206635722881,5.0,4.0,5.0,6.0,6.0,Male,4974.510985950679,46566.142857142855, -1,2020.0,1,5994,46.05633457620566,47.17786832378907,37.1505315717579,42.57278786693074,50.79227186965555,53.09992543669607,51.398245610728225,53.94649107144282,40.76871627021943,48.49638381027012,56.6324545352227,58.053199432170636,12.336631085451547,12.154108299621347,5.377015895069153,8.462664015722995,15.8133677487073,19.57371648280389,5.139472806139473,5.0,4.0,5.0,6.0,6.0,Female,4940.189235835038,48409.42857142857, -1,2021.0,1,11796,46.45866845918023,47.14178110497447,40.297191829625,44.049949959400664,49.64207671732523,51.405308832527965,51.67937242064294,53.27911545108051,43.79191840811212,49.4098842462724,55.755815616746034,57.35244328001342,11.970653246650183,11.928010076605602,4.907966511747718,8.202373674260357,15.63569488833851,18.954731810674268,5.100881654798236,5.0,4.0,5.0,6.0,6.0,Total,9837.08534008081,94552.85714285714, -1,2021.0,1,5813,47.36903995666408,48.08054345347827,41.55759276081639,45.305471117782616,50.415784801778734,52.008952390160445,52.265805120464705,53.71047779580114,45.0810629192304,50.408150655483524,56.08400523971494,57.666745545355695,11.433757695524402,11.43560311474676,4.4080679894773285,7.656136238140753,15.06974076396039,18.497248489850666,5.058489592293136,5.0,4.0,5.0,5.0,6.0,Male,4942.78463782298,46207.857142857145, -1,2021.0,1,5983,45.57416411104796,46.22034281046154,39.58468987747994,43.09833334852991,48.72442266410778,50.601405339897944,51.10960252526229,52.822166558389455,42.63391316017519,48.39926968888706,55.48650348081337,57.02135796023039,12.492293533913157,12.416519644473265,5.583951247388121,8.811320717480012,16.12751978397379,19.36636138663872,5.14206919605549,5.0,4.0,5.0,6.0,6.0,Female,4894.300702257869,48345.0, -1,2022.0,1,11788,46.03583023991024,46.40109747322356,41.224770077021375,43.92603822657883,48.619044569216655,50.27212865538313,51.473869379794735,52.61467808350739,44.72877081219608,49.13329908530466,55.086242755771885,56.8086913893179,12.11192916450608,12.06104013081038,5.119036040371666,8.4110997560532,15.68468816090212,19.07692087264592,5.066168985408891,5.0,4.0,5.0,5.0,6.0,Total,9759.57763949609,93845.71428571429, -1,2022.0,1,5811,46.928135047133125,47.38294455795195,42.03788070209821,45.06562908633818,49.431186486555625,50.89733702374304,52.10077218002101,53.15239507074041,45.82506282882073,50.05381442259219,55.48018513224668,57.175388019188524,11.498182550103945,11.499310126689208,4.542072450998329,7.746667460329107,15.017335148100996,18.418037049381812,5.019273791085872,5.0,4.0,5.0,5.0,6.0,Male,4908.719504473957,45833.857142857145, -1,2022.0,1,5977,45.16830753039534,45.448812079555644,40.645557718602035,43.14535390271415,47.59380245438486,49.33853312664365,50.86437763274552,51.99898281101934,43.750204312466664,48.30351439499377,54.66948635939042,56.351979734688705,12.708630114194985,12.690383639370134,5.865157518871705,9.042827672321135,16.258919284062983,19.59317247914636,5.111761753387987,5.0,4.0,5.0,5.0,6.0,Female,4850.858135022106,48011.857142857145, -2,2019.0,1,11824,47.5736180649524,49.44,33.45,42.0125,54.96,57.93,51.8826911366716,55.0,38.98,48.98,57.76,59.89,11.464140730717185,10.0,6.0,8.0,13.0,19.0,5.086941813261164,6.0,3.0,4.0,6.0,6.0,Total,9906.052344066891,94518.28571428571, -2,2019.0,1,5817,48.65735258724435,51.0,35.02,43.67,55.79,58.32,52.31592401581564,55.01,40.498,49.81,57.72,59.64,10.909059652741963,10.0,6.0,7.0,12.0,18.0,5.117586384734399,6.0,3.0,5.0,6.0,6.0,Male,4965.820273018077,46779.857142857145, -2,2019.0,1,6007,46.52416181122022,48.45,32.028,40.79,54.37,57.33,51.46316131180291,54.92,37.396,47.94,57.76,59.982,12.001664724488098,11.0,6.0,8.0,14.0,20.0,5.057266522390544,6.0,3.0,4.0,6.0,6.0,Female,4940.23207104888,47738.42857142857, -2,2020.0,1,11811,46.9828317203763,48.21192291876018,38.139179489624965,43.73076483727526,51.57207071785401,53.7132160991283,51.89472384047728,54.223965975401605,42.1216050844597,49.45973025022309,56.746370723429685,58.16824835160589,11.80500826154653,11.488701946577724,4.805864582913094,7.946269988151016,15.354730475209958,19.080519072823943,5.117178901024468,5.0,4.0,5.0,6.0,6.0,Total,9914.700221785752,94975.57142857142, -2,2020.0,1,5817,47.937520371254315,49.21301353520895,39.48041228341415,44.97992462055961,52.226120467594924,54.214410364925534,52.40630893745394,54.481089902035976,43.58297754270954,50.491669218527754,56.85750575025777,58.31187241795759,11.257209188744934,10.929051995783485,4.297229704265973,7.4410056627296335,14.757943096101776,18.502432022806637,5.094206635722881,5.0,4.0,5.0,6.0,6.0,Male,4974.510985950679,46566.142857142855, -2,2020.0,1,5994,46.05633457620566,47.17786832378907,37.1505315717579,42.57278786693074,50.79227186965555,53.09992543669607,51.398245610728225,53.94649107144282,40.76871627021943,48.49638381027012,56.6324545352227,58.053199432170636,12.336631085451547,12.154108299621347,5.377015895069153,8.462664015722995,15.8133677487073,19.57371648280389,5.139472806139473,5.0,4.0,5.0,6.0,6.0,Female,4940.189235835038,48409.42857142857, -2,2021.0,1,11796,46.45866845918023,47.14178110497447,40.297191829625,44.049949959400664,49.64207671732523,51.405308832527965,51.67937242064294,53.27911545108051,43.79191840811212,49.4098842462724,55.755815616746034,57.35244328001342,11.970653246650183,11.928010076605602,4.907966511747718,8.202373674260357,15.63569488833851,18.954731810674268,5.100881654798236,5.0,4.0,5.0,6.0,6.0,Total,9837.08534008081,94552.85714285714, -2,2021.0,1,5813,47.36903995666408,48.08054345347827,41.55759276081639,45.305471117782616,50.415784801778734,52.008952390160445,52.265805120464705,53.71047779580114,45.0810629192304,50.408150655483524,56.08400523971494,57.666745545355695,11.433757695524402,11.43560311474676,4.4080679894773285,7.656136238140753,15.06974076396039,18.497248489850666,5.058489592293136,5.0,4.0,5.0,5.0,6.0,Male,4942.78463782298,46207.857142857145, -2,2021.0,1,5983,45.57416411104796,46.22034281046154,39.58468987747994,43.09833334852991,48.72442266410778,50.601405339897944,51.10960252526229,52.822166558389455,42.63391316017519,48.39926968888706,55.48650348081337,57.02135796023039,12.492293533913157,12.416519644473265,5.583951247388121,8.811320717480012,16.12751978397379,19.36636138663872,5.14206919605549,5.0,4.0,5.0,6.0,6.0,Female,4894.300702257869,48345.0, -2,2022.0,1,11788,46.03583023991024,46.40109747322356,41.224770077021375,43.92603822657883,48.619044569216655,50.27212865538313,51.473869379794735,52.61467808350739,44.72877081219608,49.13329908530466,55.086242755771885,56.8086913893179,12.11192916450608,12.06104013081038,5.119036040371666,8.4110997560532,15.68468816090212,19.07692087264592,5.066168985408891,5.0,4.0,5.0,5.0,6.0,Total,9759.57763949609,93845.71428571429, -2,2022.0,1,5811,46.928135047133125,47.38294455795195,42.03788070209821,45.06562908633818,49.431186486555625,50.89733702374304,52.10077218002101,53.15239507074041,45.82506282882073,50.05381442259219,55.48018513224668,57.175388019188524,11.498182550103945,11.499310126689208,4.542072450998329,7.746667460329107,15.017335148100996,18.418037049381812,5.019273791085872,5.0,4.0,5.0,5.0,6.0,Male,4908.719504473957,45833.857142857145, -2,2022.0,1,5977,45.16830753039534,45.448812079555644,40.645557718602035,43.14535390271415,47.59380245438486,49.33853312664365,50.86437763274552,51.99898281101934,43.750204312466664,48.30351439499377,54.66948635939042,56.351979734688705,12.708630114194985,12.690383639370134,5.865157518871705,9.042827672321135,16.258919284062983,19.59317247914636,5.111761753387987,5.0,4.0,5.0,5.0,6.0,Female,4850.858135022106,48011.857142857145, \ No newline at end of file +1,2019.0,1,11824,47.53145382273326,49.52,33.49,41.48,54.94,57.92,51.620701962111106,54.8,37.394999999999996,48.2325,57.76,60.16,11.339648173207037,10.0,6.0,8.0,13.0,19.0,5.081613667117726,6.0,3.0,4.0,6.0,6.0,Total,9863.580224193543,94419.28571428571, +1,2019.0,1,5816,48.750213204951876,51.0,35.317,43.54,55.61,58.209,52.15159559834913,54.81,39.49,49.66,57.76,59.89,10.696011004126547,10.0,6.0,7.0,12.0,17.0,5.1170907840440165,6.0,3.0,4.0,6.0,6.0,Male,4960.864357969549,46767.28571428571, +1,2019.0,1,6008,46.35164280958701,48.305,31.955,40.2,54.2,57.33,51.10677430093201,54.63,35.159,47.2225,57.76,60.31200000000001,11.96271637816245,11.0,6.0,8.0,14.0,20.0,5.047270306258322,6.0,3.0,4.0,6.0,6.0,Female,4902.715866224087,47652.0, +1,2020.0,1,11807,47.10941448373623,48.38591059201562,38.530957748504775,43.72849480252921,51.6796834208416,53.77616226716376,51.778446097231736,54.293119660231184,40.93703266545548,49.206663538692844,56.75013486265197,58.24255404773437,12.101866498882556,11.749470849880943,5.1207581249594645,8.207846631920455,15.597788110086341,19.369832339180604,5.141526213263318,5.0,4.0,5.0,6.0,6.0,Total,9908.885025192694,95395.14285714286, +1,2020.0,1,5812,48.20769996220281,49.59861977121065,39.92751014698549,45.12492424972986,52.29258153825101,54.268294584275466,52.38754419536497,54.578014803066296,43.00808332000675,50.2382551587784,56.78808193586045,58.292567474335975,11.409737701194516,11.11188507341574,4.684473015909666,7.647013239093138,14.808815317387765,18.264878765496725,5.139538885065382,5.0,4.0,5.0,6.0,6.0,Male,4985.226496404391,46940.142857142855, +1,2020.0,1,5995,46.04465465039986,47.31328777119278,37.191641109307774,42.40352972240403,50.86679005944934,53.13597609700303,51.18794098524653,53.89579935242729,39.442432815940734,48.32375216492676,56.68430674832035,58.196421925093084,12.772867761962253,12.374579691125433,5.585569640279202,8.859116398244083,16.34329155668191,20.189828913175486,5.143452877397832,5.0,4.0,5.0,6.0,6.0,Female,4923.658528788254,48455.0, +1,2021.0,1,11797,46.742723558893196,47.531607733750725,40.69354136926197,44.42538238486669,49.888988353206436,51.54530727727393,51.763077789662745,53.506636227813544,43.209096044443925,49.54370191712697,55.90611085886066,57.47689361185802,12.55276026455242,12.369667018693207,5.406709586836046,8.699816635271794,16.157982273224874,19.898848257757567,5.1569042977028055,5.0,4.0,5.0,6.0,6.0,Total,9883.812529623396,95599.42857142857, +1,2021.0,1,5815,47.78433101777409,48.55619746019689,42.18300726704802,45.708261571541364,50.57804865760657,52.18568315080371,52.39502647622476,53.938458394599515,44.971347026749505,50.3859258908235,56.13210634183931,57.676089810168456,11.787618738648383,11.594638386237689,4.7631129647138275,7.983589835560535,15.334535818120202,18.964363178050263,5.141874462596733,5.0,4.0,5.0,6.0,6.0,Male,4977.783935691994,46985.71428571428, +1,2021.0,1,5982,45.730194743548275,46.501163748257824,39.64003054734682,43.214243352448136,48.922701489493306,50.66305268501862,51.148771268038566,53.03736875420955,41.451651716765305,48.59633858422124,55.68980497022974,57.25634420554174,13.29654126975659,13.046112943963163,6.118241697965072,9.41450207345843,16.939524513206845,20.76093926302054,5.1715145436308925,5.0,4.0,5.0,6.0,6.0,Female,4906.028593931412,48613.71428571428, +1,2022.0,1,11789,46.38791157807319,46.84845777608714,41.76098980047244,44.36330161239812,48.890740662378974,50.40362339164728,51.72231537854947,52.947464023105965,44.64952354821375,49.61643166407461,55.39564927937097,57.00414483236732,12.865781274501389,12.719508855512391,5.851427349202874,9.093647361260285,16.441809638490682,20.15453060286348,5.134192891678683,5.0,4.0,5.0,5.0,6.0,Total,9840.776785439459,95113.85714285714, +1,2022.0,1,5814,47.40504454813718,47.76885925146938,43.2092740419604,45.642269944515974,49.698286080133414,51.08486265081363,52.363573439012384,53.46361486991707,46.07404512571718,50.38544557063861,55.731072408373784,57.24389555266204,12.105365732047783,11.920280045534616,5.371015154032802,8.419391272232012,15.61140833859421,19.17873261096259,5.11609907120743,5.0,4.0,5.0,5.0,6.0,Male,4958.470183947376,46742.142857142855, +1,2022.0,1,5975,45.39818587297606,45.84094647011746,40.82474337039838,43.35690960841514,47.870925768156,49.42836191547398,51.09833640557406,52.43912097247147,43.03110053075838,48.74662755096215,55.05860871339304,56.68502893754849,13.605706958823626,13.43860854115701,6.588642085755079,9.806464562899398,17.14752737213547,21.002651241003846,5.151799163179916,5.0,4.0,5.0,6.0,6.0,Female,4882.306601492123,48371.71428571428, +2,2019.0,1,11824,47.53145382273326,49.52,33.49,41.48,54.94,57.92,51.620701962111106,54.8,37.394999999999996,48.2325,57.76,60.16,11.339648173207037,10.0,6.0,8.0,13.0,19.0,5.081613667117726,6.0,3.0,4.0,6.0,6.0,Total,9863.580224193543,94419.28571428571, +2,2019.0,1,5816,48.750213204951876,51.0,35.317,43.54,55.61,58.209,52.15159559834913,54.81,39.49,49.66,57.76,59.89,10.696011004126547,10.0,6.0,7.0,12.0,17.0,5.1170907840440165,6.0,3.0,4.0,6.0,6.0,Male,4960.864357969549,46767.28571428571, +2,2019.0,1,6008,46.35164280958701,48.305,31.955,40.2,54.2,57.33,51.10677430093201,54.63,35.159,47.2225,57.76,60.31200000000001,11.96271637816245,11.0,6.0,8.0,14.0,20.0,5.047270306258322,6.0,3.0,4.0,6.0,6.0,Female,4902.715866224087,47652.0, +2,2020.0,1,11807,47.10941448373623,48.38591059201562,38.530957748504775,43.72849480252921,51.6796834208416,53.77616226716376,51.778446097231736,54.293119660231184,40.93703266545548,49.206663538692844,56.75013486265197,58.24255404773437,12.101866498882556,11.749470849880943,5.1207581249594645,8.207846631920455,15.597788110086341,19.369832339180604,5.141526213263318,5.0,4.0,5.0,6.0,6.0,Total,9908.885025192694,95395.14285714286, +2,2020.0,1,5812,48.20769996220281,49.59861977121065,39.92751014698549,45.12492424972986,52.29258153825101,54.268294584275466,52.38754419536497,54.578014803066296,43.00808332000675,50.2382551587784,56.78808193586045,58.292567474335975,11.409737701194516,11.11188507341574,4.684473015909666,7.647013239093138,14.808815317387765,18.264878765496725,5.139538885065382,5.0,4.0,5.0,6.0,6.0,Male,4985.226496404391,46940.142857142855, +2,2020.0,1,5995,46.04465465039986,47.31328777119278,37.191641109307774,42.40352972240403,50.86679005944934,53.13597609700303,51.18794098524653,53.89579935242729,39.442432815940734,48.32375216492676,56.68430674832035,58.196421925093084,12.772867761962253,12.374579691125433,5.585569640279202,8.859116398244083,16.34329155668191,20.189828913175486,5.143452877397832,5.0,4.0,5.0,6.0,6.0,Female,4923.658528788254,48455.0, +2,2021.0,1,11797,46.742723558893196,47.531607733750725,40.69354136926197,44.42538238486669,49.888988353206436,51.54530727727393,51.763077789662745,53.506636227813544,43.209096044443925,49.54370191712697,55.90611085886066,57.47689361185802,12.55276026455242,12.369667018693207,5.406709586836046,8.699816635271794,16.157982273224874,19.898848257757567,5.1569042977028055,5.0,4.0,5.0,6.0,6.0,Total,9883.812529623396,95599.42857142857, +2,2021.0,1,5815,47.78433101777409,48.55619746019689,42.18300726704802,45.708261571541364,50.57804865760657,52.18568315080371,52.39502647622476,53.938458394599515,44.971347026749505,50.3859258908235,56.13210634183931,57.676089810168456,11.787618738648383,11.594638386237689,4.7631129647138275,7.983589835560535,15.334535818120202,18.964363178050263,5.141874462596733,5.0,4.0,5.0,6.0,6.0,Male,4977.783935691994,46985.71428571428, +2,2021.0,1,5982,45.730194743548275,46.501163748257824,39.64003054734682,43.214243352448136,48.922701489493306,50.66305268501862,51.148771268038566,53.03736875420955,41.451651716765305,48.59633858422124,55.68980497022974,57.25634420554174,13.29654126975659,13.046112943963163,6.118241697965072,9.41450207345843,16.939524513206845,20.76093926302054,5.1715145436308925,5.0,4.0,5.0,6.0,6.0,Female,4906.028593931412,48613.71428571428, +2,2022.0,1,11789,46.38791157807319,46.84845777608714,41.76098980047244,44.36330161239812,48.890740662378974,50.40362339164728,51.72231537854947,52.947464023105965,44.64952354821375,49.61643166407461,55.39564927937097,57.00414483236732,12.865781274501389,12.719508855512391,5.851427349202874,9.093647361260285,16.441809638490682,20.15453060286348,5.134192891678683,5.0,4.0,5.0,5.0,6.0,Total,9840.776785439459,95113.85714285714, +2,2022.0,1,5814,47.40504454813718,47.76885925146938,43.2092740419604,45.642269944515974,49.698286080133414,51.08486265081363,52.363573439012384,53.46361486991707,46.07404512571718,50.38544557063861,55.731072408373784,57.24389555266204,12.105365732047783,11.920280045534616,5.371015154032802,8.419391272232012,15.61140833859421,19.17873261096259,5.11609907120743,5.0,4.0,5.0,5.0,6.0,Male,4958.470183947376,46742.142857142855, +2,2022.0,1,5975,45.39818587297606,45.84094647011746,40.82474337039838,43.35690960841514,47.870925768156,49.42836191547398,51.09833640557406,52.43912097247147,43.03110053075838,48.74662755096215,55.05860871339304,56.68502893754849,13.605706958823626,13.43860854115701,6.588642085755079,9.806464562899398,17.14752737213547,21.002651241003846,5.151799163179916,5.0,4.0,5.0,6.0,6.0,Female,4882.306601492123,48371.71428571428, \ No newline at end of file diff --git a/src/test/java/simpaths/integrationtest/expected/Statistics1.csv b/src/test/java/simpaths/integrationtest/expected/Statistics1.csv index 87d6f027f..e21f58d38 100644 --- a/src/test/java/simpaths/integrationtest/expected/Statistics1.csv +++ b/src/test/java/simpaths/integrationtest/expected/Statistics1.csv @@ -1,9 +1,9 @@ run,time,id_Statistics1,edi_p50,giniEquivalisedHouseholdDisposableIncomeNational,giniMarketIncomeNational,grossLabourIncome_p20,grossLabourIncome_p40,grossLabourIncome_p60,grossLabourIncome_p80,medianEquivalisedHouseholdDisposableIncome,sIndex_p50,ydses_p20,ydses_p40,ydses_p60,ydses_p80, -1,2019.0,1,11757.302709762187,0.0,0.0,683.5225871491517,1315.48384350156,1937.24673210554,2912.6461388214298,11750.452611489904,NaN,0.0,5.115931367978064,7.730281112717949,8.291158851348424, -1,2020.0,1,12024.725900296515,0.0,0.0,548.2818795027198,1280.8738690230748,1986.8316720090172,3038.8698400369094,12024.725900296515,NaN,0.0,0.0,7.692716996498925,8.332092121974863, -1,2021.0,1,11824.704596407068,0.0,0.0,530.3116199269688,1346.0712162595285,2094.0259592091907,3168.282850516031,11824.704596407068,NaN,0.0,0.0,7.710970594492367,8.375714882133623, -1,2022.0,1,11865.185788988649,0.0,0.0,614.6531134486551,1390.2712104917964,2104.4788626265145,3181.5010830738493,11863.531823182017,NaN,0.0,0.0,7.73369628779575,8.372046690671485, -2,2019.0,1,11757.302709762185,0.0,0.0,683.5225871491517,1315.48384350156,1937.24673210554,2912.6461388214298,11750.452611489904,NaN,0.0,5.115931367978064,7.730281112717949,8.291158851348424, -2,2020.0,1,12024.725900296515,0.0,0.0,548.2818795027198,1280.8738690230748,1986.8316720090172,3038.8698400369094,12024.725900296515,NaN,0.0,0.0,7.692716996498925,8.332092121974863, -2,2021.0,1,11824.704596407068,0.0,0.0,530.3116199269688,1346.0712162595285,2094.0259592091907,3168.282850516031,11824.704596407068,NaN,0.0,0.0,7.710970594492367,8.375714882133623, -2,2022.0,1,11865.185788988649,0.0,0.0,614.6531134486551,1390.2712104917964,2104.4788626265145,3181.5010830738493,11863.531823182017,NaN,0.0,0.0,7.73369628779575,8.372046690671485, \ No newline at end of file +1,2019.0,1,13095.307851314308,0.0,0.0,973.4096725036837,1525.932657685651,2158.2741367617946,3228.276924267956,13095.307851314308,NaN,0.0,4.858943553994427,7.849675860587956,8.375850062998584, +1,2020.0,1,15575.722944710858,0.0,0.0,1181.5608933150663,1747.6557506385611,2421.8789326058222,3469.277972897026,15564.82710517697,NaN,0.0,7.074433470218817,8.020759494695893,8.504765831925205, +1,2021.0,1,16113.258882190123,0.0,0.0,1273.1333164859516,1866.7122771619715,2517.1508140543865,3606.7262455727155,16106.24011323231,NaN,0.0,7.277018560662857,8.093902718239285,8.557598702286088, +1,2022.0,1,16090.047149617112,0.0,0.0,1280.1333935903701,1866.018980405856,2531.202527148557,3627.2081348233537,16089.736327524866,NaN,0.0,7.2572637515703775,8.08880530015257,8.577949944032026, +2,2019.0,1,13095.307851314308,0.0,0.0,973.4096725036837,1525.932657685651,2158.2741367617946,3228.276924267956,13095.307851314308,NaN,0.0,4.858943553994427,7.849675860587956,8.375850062998584, +2,2020.0,1,15575.722944710858,0.0,0.0,1181.5608933150663,1747.6557506385611,2421.8789326058222,3469.277972897026,15564.82710517697,NaN,0.0,7.074433470218817,8.020759494695893,8.504765831925205, +2,2021.0,1,16113.258882190123,0.0,0.0,1273.1333164859516,1866.7122771619715,2517.1508140543865,3606.7262455727155,16106.24011323231,NaN,0.0,7.277018560662857,8.093902718239285,8.557598702286088, +2,2022.0,1,16090.047149617112,0.0,0.0,1280.1333935903701,1866.018980405856,2531.202527148557,3627.2081348233537,16089.736327524866,NaN,0.0,7.2572637515703775,8.08880530015257,8.577949944032026, \ No newline at end of file diff --git a/src/test/java/simpaths/integrationtest/expected/Statistics21.csv b/src/test/java/simpaths/integrationtest/expected/Statistics21.csv index b8f7b04ea..fd276948a 100644 --- a/src/test/java/simpaths/integrationtest/expected/Statistics21.csv +++ b/src/test/java/simpaths/integrationtest/expected/Statistics21.csv @@ -1,9 +1,9 @@ run,time,id_Statistics21,aaconsToLeisRatio,aadisposableIncome18to29,aadisposableIncome30to54,aadisposableIncome55to74,aaexpenditure18to29,aaexpenditure18to54,aaexpenditure30to54,aaexpenditure55to74,aaworkNone18to29,aaworkNone18to74,aaworkNone30to54,aaworkNone55to74,avkids18to29,avkids30to54,avkids55to74,aworkFulltime18to29,aworkFulltime30to54,aworkFulltime55to74,aworkParttime18to29,aworkParttime30to54,aworkParttime55to74,dispIncomeGrossOfLosses18to29,dispIncomeGrossOfLosses30to54,dispIncomeGrossOfLosses55to74,health18to29,health30to54,health55to74,investmentIncome18to29,investmentIncome30to54,investmentIncome55to74,investmentLosses18to29,investmentLosses30to54,investmentLosses55to74,labourIncome18to29,labourIncome30to54,labourIncome55to74,pensionIncome18to29,pensionIncome30to54,pensionIncome55to74,population18to29,population30to54,population55to74,prDisabled18to29,prDisabled30to54,prDisabled55to74,prMarried18to29,prMarried30to54,prMarried55to74,wealth18to29,wealth30to54,wealth55to74, -1,2019.0,1,-1.3237521686439095,-73.20797646998699,-436.0223487690191,-881.2646809274731,-720.1695169780969,-1107.8924607013428,-1343.000294074045,-1403.8734750814162,-0.005149673984858938,-0.0033329270384359067,-0.004920269336670835,0.07424024470868018,0.2770130763936683,0.9652690863579474,0.07300832342449465,0.5488644184445974,0.634386733416771,0.24114149821640904,0.11355815554026152,0.16598873591989988,0.08347205707491082,1213.0042449585842,1663.4985699809808,1197.580913715384,3.7250516173434276,3.486232790988736,3.130796670630202,0.0,0.0,0.0,0.0,0.0,0.0,388.21609660671504,545.9129449730592,508.7545280917505,0.0,0.0,0.0,2906.0,6392.0,4205.0,0.04679972470750172,0.08635794743429287,0.1426872770511296,0.25636613902271166,0.688360450563204,0.619500594530321,0.0,0.0,0.0, 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LinearRegression getLinearRegression(RegressionName regression) { case HealthHM2LevelFemales -> { return Parameters.getRegHealthHM2LevelFemales(); } + case HealthHM1Case -> { + return Parameters.getRegHealthHM1Case(); + } + case HealthHM2CaseMales -> { + return Parameters.getRegHealthHM2CaseMales(); + } + case HealthHM2CaseFemales -> { + return Parameters.getRegHealthHM2CaseFemales(); + } case HealthMCS1 -> { return Parameters.getRegHealthMCS1(); } @@ -142,15 +151,6 @@ public static BinomialRegression getBinomialRegression(RegressionName regression case HealthH2b -> { return Parameters.getRegHealthH2b(); } - case HealthHM1Case -> { - return Parameters.getRegHealthHM1Case(); - } - case HealthHM2CaseMales -> { - return Parameters.getRegHealthHM2CaseMales(); - } - case HealthHM2CaseFemales -> { - return Parameters.getRegHealthHM2CaseFemales(); - } case SocialCareS1a -> { return Parameters.getRegReceiveCareS1a(); } diff --git a/src/main/java/simpaths/data/Parameters.java b/src/main/java/simpaths/data/Parameters.java index dce897569..68dc6cae5 100644 --- a/src/main/java/simpaths/data/Parameters.java +++ b/src/main/java/simpaths/data/Parameters.java @@ -742,9 +742,9 @@ else if(numberOfChildren <= 5) { private static LinearRegression regHealthHM2LevelMales; private static LinearRegression regHealthHM2LevelFemales; - private static BinomialRegression regHealthHM1Case; - private static BinomialRegression regHealthHM2CaseMales; - private static BinomialRegression regHealthHM2CaseFemales; + private static LinearRegression regHealthHM1Case; + private static LinearRegression regHealthHM2CaseMales; + private static LinearRegression regHealthHM2CaseFemales; //Health private static LinearRegression regHealthMCS1; @@ -1191,9 +1191,9 @@ else if(country.equals(Country.UK)) { columnsHealthH1a = 31; columnsHealthH1b = 110; columnsHealthH2b = 36; - columnsHealthHM1 = 30; - columnsHealthHM2Males = 15; - columnsHealthHM2Females = 15; + columnsHealthHM1 = 35; + columnsHealthHM2Males = 10; + columnsHealthHM2Females = 10; columnsHealthMCS1 = 30; columnsHealthMCS2Males = 15; columnsHealthMCS2Females = 15; @@ -1648,9 +1648,9 @@ else if (country.equals(Country.IT)) { regHealthHM2LevelMales = new LinearRegression(coeffCovarianceHM2LevelMales); regHealthHM2LevelFemales = new LinearRegression(coeffCovarianceHM2LevelFemales); - regHealthHM1Case = new BinomialRegression(RegressionType.Logit, Indicator.class, coeffCovarianceHM1Case); - regHealthHM2CaseMales = new BinomialRegression(RegressionType.Logit, Indicator.class, coeffCovarianceHM2CaseMales); - regHealthHM2CaseFemales = new BinomialRegression(RegressionType.Logit, Indicator.class, coeffCovarianceHM2CaseFemales); + regHealthHM1Case = new LinearRegression(coeffCovarianceHM1Case); + regHealthHM2CaseMales = new LinearRegression(coeffCovarianceHM2CaseMales); + regHealthHM2CaseFemales = new LinearRegression(coeffCovarianceHM2CaseFemales); //Health regHealthMCS1 = new LinearRegression(coeffCovarianceDHE_MCS1); @@ -2166,9 +2166,9 @@ public static void setEmploymentsFurloughedFlex(MultiKeyCoefficientMap employmen public static LinearRegression getRegHealthHM1Level() { return regHealthHM1Level; } public static LinearRegression getRegHealthHM2LevelMales() { return regHealthHM2LevelMales; } public static LinearRegression getRegHealthHM2LevelFemales() { return regHealthHM2LevelFemales; } - public static BinomialRegression getRegHealthHM1Case() {return regHealthHM1Case;} - public static BinomialRegression getRegHealthHM2CaseMales() {return regHealthHM2CaseMales;} - public static BinomialRegression getRegHealthHM2CaseFemales() {return regHealthHM2CaseFemales;} + public static LinearRegression getRegHealthHM1Case() {return regHealthHM1Case;} + public static LinearRegression getRegHealthHM2CaseMales() {return regHealthHM2CaseMales;} + public static LinearRegression getRegHealthHM2CaseFemales() {return regHealthHM2CaseFemales;} public static LinearRegression getRegHealthMCS1() { return regHealthMCS1; } public static LinearRegression getRegHealthMCS2Males() { return regHealthMCS2Males; } diff --git a/src/main/java/simpaths/data/RegressionName.java b/src/main/java/simpaths/data/RegressionName.java index 80757c7ad..77e659d86 100644 --- a/src/main/java/simpaths/data/RegressionName.java +++ b/src/main/java/simpaths/data/RegressionName.java @@ -25,9 +25,9 @@ public enum RegressionName { HealthHM1Level(RegressionType.Linear), HealthHM2LevelMales(RegressionType.Linear), HealthHM2LevelFemales(RegressionType.Linear), - HealthHM1Case(RegressionType.Logit), - HealthHM2CaseMales(RegressionType.Logit), - HealthHM2CaseFemales(RegressionType.Logit), + HealthHM1Case(RegressionType.Linear), + HealthHM2CaseMales(RegressionType.Linear), + HealthHM2CaseFemales(RegressionType.Linear), HealthMCS1(RegressionType.Linear), HealthMCS2Males(RegressionType.Linear), diff --git a/src/main/java/simpaths/model/Person.java b/src/main/java/simpaths/model/Person.java index c0b7a873c..1c62b9bc5 100644 --- a/src/main/java/simpaths/model/Person.java +++ b/src/main/java/simpaths/model/Person.java @@ -129,8 +129,8 @@ public class Person implements EventListener, IDoubleSource, IIntSource, Weight, @Transient private Boolean hasTestPartner; @Transient private Boolean leavePartner; // Used in partnership alignment process. Indicates that this person has found partner in a test run of union matching. @Column(name="person_weight") private Double weight; - @Column(name="dhm_ghq") private Boolean dhmGhq; //Psychological distress case-based - @Transient private Boolean dhmGhq_lag1; + @Column(name="dhm_ghq") private Double dhmGhq; //Psychological distress GHQ-12 0-12 caseness score + @Transient private Double dhmGhq_lag1; @Transient private Dhe dhe_lag1; @Enumerated(EnumType.STRING) private Dhe dhe; private Double dhm; //Psychological distress GHQ-12 Likert scale @@ -294,7 +294,7 @@ public Person(Gender gender, Person mother) { weight = mother.getWeight(); //Newborn has same weight as mother (the number of newborns will then be aligned in fertility alignment) dhe = Dhe.VeryGood; dhm = 9.; //Set to median for under 18's as a placeholder - dhmGhq = false; + dhmGhq = 0.; deh_c3 = Education.Low; dot01 = mother.getDot01(); les_c4 = Les_c4.Student; //Set lag activity status as Student, i.e. in education from birth @@ -486,7 +486,7 @@ else if (dag > Parameters.MAX_AGE_TO_LEAVE_CONTINUOUS_EDUCATION) dhm_lag1 = originalPerson.dhm; } - dhmGhq = Objects.requireNonNullElse(originalPerson.dhmGhq, false); + dhmGhq = Objects.requireNonNullElse(originalPerson.dhmGhq, 0.); dhmGhq_lag1 = Objects.requireNonNullElse(originalPerson.dhmGhq_lag1, dhmGhq); dls = originalPerson.dls; @@ -1115,7 +1115,7 @@ protected void healthMentalHM1HM2Cases() { if (dag >= 16) { double tmp_step1_score = 0, tmp_step2_score = 0, tmp_total_score = 0, tmp_probability = 0; - boolean tmp_outcome; + Double tmp_outcome; tmp_step1_score = Parameters.getRegHealthHM1Case().getScore(this, Person.DoublesVariables.class); // Obtain score from Step 1 of case-based psychological distress model if (dag >= 25 && dag <= 64) { @@ -1125,19 +1125,20 @@ protected void healthMentalHM1HM2Cases() { tmp_step2_score = Parameters.getRegHealthHM2CaseFemales().getScore(this, Person.DoublesVariables.class); // Obtain score from Step 2 of case-based psychological distress model } else System.out.println("healthMentalHM2 method in Person class: Person has no gender!"); } - - //Put together: get total score, convert to probability, get event, set dummy - // 1. Sum scores from Step 1 and 2. This produces the basic score modified by the effect of transitions modelled in Step 2. - tmp_total_score = tmp_step1_score + tmp_step2_score; - // 2. Convert to probability - tmp_probability = 1.0 / (1.0 + Math.exp(-tmp_total_score)); - // 3. Get event outcome - tmp_outcome = (innovations.getDoubleDraw(2) < tmp_probability); - // 4. Set dhm_ghq dummy + tmp_outcome = constrainDhmGhqEstimate(tmp_step1_score + tmp_step2_score); setDhmGhq(tmp_outcome); } } + protected Double constrainDhmGhqEstimate(Double dhm_ghq) { + if (dhm_ghq < 0.) { + dhm_ghq = 0.; + } else if (dhm_ghq > 12.) { + dhm_ghq = 12.; + } + return dhm_ghq; + } + /* Psychological distress on the GHQ-12 scale has no meaning outside of the original values between 0 and 36, but we model this variable on a continuous scale. If the predicted value is outside of this interval, limit it to fall within these values. */ @@ -2203,7 +2204,7 @@ public int getIntValue(Enum variableID) { return (isToBePartnered())? 1 : 0; case isPsychologicallyDistressed: - return (dhmGhq)? 1 : 0; + return (dhmGhq >= 4)? 1 : 0; case isNeedSocialCare: return (Indicator.True.equals(needSocialCare)) ? 1 : 0; @@ -3129,7 +3130,7 @@ else throw new IllegalArgumentException( } else return 0.; } case Dhmghq_L1 -> { - return (getDhmGhq_lag1()) ? 1. : 0.; + return getDhmGhq_lag1(); } case Dhesp_L1 -> { return (dhesp_lag1 != null) ? (double) dhesp_lag1.getValue() : 0.0; @@ -4586,11 +4587,11 @@ public void setDhm_lag1(Double dhm) { this.dhm_lag1 = dhm; } - public boolean getDhmGhq() { + public Double getDhmGhq() { return dhmGhq; } - public void setDhmGhq(boolean dhm_ghq) { + public void setDhmGhq(Double dhm_ghq) { this.dhmGhq = dhm_ghq; } @@ -5545,7 +5546,7 @@ public void setProcessedId(long id) { public long getSeed() {return (seed!=null) ? seed : 0L;} - private boolean getDhmGhq_lag1() { + private Double getDhmGhq_lag1() { if (dhmGhq_lag1 == null) throw new RuntimeException("attempt to access dhmGhq_lag1 before it has been initialised"); return dhmGhq_lag1; From 94bde8b669ca69d61effe60c707baebfe8469725 Mon Sep 17 00:00:00 2001 From: justin-ven <43171764+justin-ven@users.noreply.github.com> Date: Mon, 17 Nov 2025 20:47:31 +0100 Subject: [PATCH 2/5] merged Daria's changes --- input/InitialPopulations/compile/00_master.do | 42 +- .../compile/01_prepare_UKHLS_pooled_data.do | 4 +- .../compile/02_create_UKHLS_variables.do | 458 +++-- .../compile/06_reweight_and_slice.do | 4 +- .../compile/08_wealth_to_ukhls.do | 4 +- .../compile/09_finalise_input_data.do | 44 +- .../compile/10_check_yearly_data.do | 45 +- .../compile/RegressionEstimates/master.do | 22 +- .../RegressionEstimates/reg_fertility.do | 351 ++-- .../RegressionEstimates/reg_home_ownership.do | 219 +- .../reg_leaveParentalHome.do | 179 +- .../RegressionEstimates/variable_update.do | 46 +- .../compile/calculate_statistics.do | 844 -------- .../compile/calculate_statistics_UK.do | 1822 ----------------- .../compile/do_emphist/00_Master_emphist.do | 69 + .../compile/do_emphist/01_Intdate.do | 60 + .../compile/do_emphist/02_Lwintdat.do | 123 ++ .../compile/do_emphist/03_Bhps_lintdate.do | 98 + .../compile/do_emphist/04_Sp0_1_2a.do | 223 ++ .../compile/do_emphist/05_Newentrant1.do | 191 ++ .../compile/do_emphist/06_Aspells1.do | 160 ++ .../compile/do_emphist/07_Empcal1a.do | 324 +++ input/reg_fertility.xlsx | Bin 29474 -> 19179 bytes input/reg_home_ownership.xlsx | Bin 25177 -> 25312 bytes input/reg_labourSupplyUtility.xlsx | Bin 107873 -> 200692 bytes input/reg_leaveParentalHome.xlsx | Bin 13153 -> 13233 bytes 26 files changed, 2021 insertions(+), 3311 deletions(-) delete mode 100644 input/InitialPopulations/compile/calculate_statistics.do delete mode 100644 input/InitialPopulations/compile/calculate_statistics_UK.do create mode 100644 input/InitialPopulations/compile/do_emphist/00_Master_emphist.do create mode 100644 input/InitialPopulations/compile/do_emphist/01_Intdate.do create mode 100644 input/InitialPopulations/compile/do_emphist/02_Lwintdat.do create mode 100644 input/InitialPopulations/compile/do_emphist/03_Bhps_lintdate.do create mode 100644 input/InitialPopulations/compile/do_emphist/04_Sp0_1_2a.do create mode 100644 input/InitialPopulations/compile/do_emphist/05_Newentrant1.do create mode 100644 input/InitialPopulations/compile/do_emphist/06_Aspells1.do create mode 100644 input/InitialPopulations/compile/do_emphist/07_Empcal1a.do diff --git a/input/InitialPopulations/compile/00_master.do b/input/InitialPopulations/compile/00_master.do index f35f2aae5..daef7a650 100644 --- a/input/InitialPopulations/compile/00_master.do +++ b/input/InitialPopulations/compile/00_master.do @@ -39,25 +39,36 @@ set matsize 1000 global dir_work "C:\MyFiles\99 DEV ENV\JAS-MINE\data work\initial_populations" *global dir_work "D:\Dasha\ESSEX\ESPON 2024\UK\initial_populations" -* Directory which contains do files +* Directory containing do files global dir_do "${dir_work}/do" +*global dir_do "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations\compile" -* Directory which contains data files +* Directory containing processed data global dir_data "${dir_work}/data" -* Directory which contains log files +* Directory containing log files global dir_log "${dir_work}/log" -* Directory which contains UKHLS data +* Directory containing UKHLS data global dir_ukhls_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\ukhls" *global dir_ukhls_data "D:\Dasha\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\ukhls" -* Directory which contains WAS data +* Directory containing BHPS data +global dir_bhps_data "J:\01 DATA\UK\ukhls\wave14\stata\stata13_se\bhps" +*global dir_bhps_data "D:\UK-original-data\USoc\UKDA-6614-stata\stata\stata13_se\bhps" + +* Directory containing WAS data global dir_was_data "J:\01 DATA\UK\was\wave8\stata\stata13_se" *global dir_was_data "D:\Dasha\UK-original-data\WAS\UKDA-7215-stata\stata\stata13_se" -* Directory which contains original initial popultions -global dir_ipop_orig "${dir_work}/original_initial_populations" +* Directory containing processed employment history data +global dir_data_emphist "${dir_data}/emphist" + +* Directory containing employment history do-files +global dir_do_emphist "${dir_do}/do_emphist" + +* Directory containing employment history log files +global dir_log_emphist "${dir_log}/emphist" /************************************************************************************** @@ -85,10 +96,19 @@ wave 13 m 2021-2023 wave 14 n 2022-2024 */ global UKHLSwaves "a b c d e f g h i j k l m n" /*all waves*/ +global UKHLSwaves_numbers "1 2 3 4 5 6 7 8 9 10 11 12 13 14" //ukhls_all_waves_numbers + +global UKHLS_panel_waves "b c d e f g h i j k l m n" +global UKHLS_panel_waves_numbers "2 3 4 5 6 7 8 9 10 11 12 13 14" //ukhls_waves_numbers +global UKHLS_waves_prefixed "b_ c_ d_ e_ f_ g_ h_ i_ j_ k_ l_ m_ n_" +global BHPS_waves "l m n o p q r" + * waves reporting social care module in ukhls - ADL questions added from wave 7 and then every other wave (from 2016) global scRecWaves "g i k m" + * waves reporting social care provided in ukhls (from 2015) -global scProvWaves "f g h i j k l m" +global scProvWaves "f g h i j k l m n" + global firstSimYear = 2010 global lastSimYear = 2023 global wealthStartYear = 2015 @@ -98,9 +118,9 @@ global wealthEndYear = 2019 /************************************************************************************** * ROUTE TO WORKER FILES *************************************************************************************/ -* Prepare simulated and observed data +* prepare simulated and observed data do "${dir_do}/01_prepare_UKHLS_pooled_data.do" -* Process UKHLS data +* process UKHLS data do "${dir_do}/02_create_UKHLS_variables.do" * add social care do "${dir_do}/03_social_care_received.do" @@ -115,7 +135,9 @@ forvalues year = $wealthStartYear / $wealthEndYear { global yearWealth = `year' do "${dir_do}/08_wealth_to_ukhls.do" } +* check data and slice into initial populations do "${dir_do}/09_finalise_input_data.do" +* descriptives for initial populations and full sample do "${dir_do}/10_check_yearly_data.do" diff --git a/input/InitialPopulations/compile/01_prepare_UKHLS_pooled_data.do b/input/InitialPopulations/compile/01_prepare_UKHLS_pooled_data.do index e8f0b2f47..bff821225 100644 --- a/input/InitialPopulations/compile/01_prepare_UKHLS_pooled_data.do +++ b/input/InitialPopulations/compile/01_prepare_UKHLS_pooled_data.do @@ -30,12 +30,12 @@ foreach w of global UKHLSwaves { local waveno=strpos("abcdefghijklmnopqrstuvwxyz","`w'") if (`waveno'<13) { - use pidp `w'_ivfho `w'_ivfio `w'_hhorig `w'_buno_dv `w'_dvage `w'_sex `w'_depchl `w'_hidp `w'_pno `w'_pns1pid `w'_pns2pid `w'_month `w'_intdaty_dv /// + use pidp `w'_ivfho `w'_ivfio `w'_hhorig `w'_memorig `w'_buno_dv `w'_dvage `w'_sex `w'_depchl `w'_hidp `w'_pno `w'_pns1pid `w'_pns2pid `w'_month `w'_intdaty_dv /// `w'_mnspid `w'_fnspid `w'_ppid `w'_ppno `w'_sppid `w'_sex_dv `w'_mastat_dv `w'_gor_dv `w'_age_dv /* `w'_hgbioad1 `w'_hgbioad2 */ /// `w'_intdatd_dv `w'_intdatm_dv `w'_intdaty_dv `w'_ethn_dv using `w'_indall.dta, clear } else { - use pidp `w'_ivfho `w'_ivfio `w'_hhorig `w'_buno_dv `w'_dvage `w'_sex `w'_depchl `w'_hidp `w'_pno `w'_pns1pid `w'_pns2pid `w'_month `w'_intdaty_dv /// + use pidp `w'_ivfho `w'_ivfio `w'_hhorig `w'_memorig `w'_buno_dv `w'_dvage `w'_sex `w'_depchl `w'_hidp `w'_pno `w'_pns1pid `w'_pns2pid `w'_month `w'_intdaty_dv /// `w'_mnspid `w'_fnspid `w'_ppid `w'_ppno `w'_sppid `w'_sex_dv `w'_mastat_dv `w'_gor_dv `w'_age_dv `w'_hgbioad1 `w'_hgbioad2 /// `w'_intdatd_dv `w'_intdatm_dv `w'_intdaty_dv `w'_ethn_dv using `w'_indall.dta, clear } diff --git a/input/InitialPopulations/compile/02_create_UKHLS_variables.do b/input/InitialPopulations/compile/02_create_UKHLS_variables.do index 1a3d178ae..c4f8b876e 100644 --- a/input/InitialPopulations/compile/02_create_UKHLS_variables.do +++ b/input/InitialPopulations/compile/02_create_UKHLS_variables.do @@ -6,7 +6,7 @@ * COUNTRY: UK * DATA: UKHLS EUL version - UKDA-6614-stata [to wave n] * AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 18 July 2025 DP +* LAST UPDATE: 3 Nov 2025 DP * NOTE: Called from 00_master.do - see master file for further details * Use -9 for missing values *************************************************************************************** @@ -331,53 +331,6 @@ lab values dhesp dhe replace dhesp=-9 if missing(dhesp) & idpartner>0 - -/**************************Subjective well-being: GHQ 0-12 score *****************************/ -/*dhm_ghq scghq2_dv "DEMOGRAPHIC: Subjective wellbeing (GHQ): rescaled to 0-12, assumed to be continuous" -This measure converts valid answers to 12 questions of the General Health Questionnaire (GHQ) to a -single scale by recoding the values of individual variables of 1 and 2 to 0, and values of 3 and 4 to 1 before summing them. -This produces a scale that ranges from 0 (indicating the least amount of distress) to 12 (indicating the greatest amount of distress). -*/ -gen dhm_ghq = scghq2_dv -replace dhm_ghq = . if scghq2_dv <0 -la var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): 0-12 score" -* fre dhm_ghq if dag>0 & dag<=18 -* fre dhm_ghq if dag>0 & dag<16 -gen scghq2_dv_miss_flag = (scghq2_dv == .) - -*Imputation for all: -* fre dag if missing(dhm_ghq) - -* fre scghq2_dv -recode scghq2_dv (-9/-1 . = .) -preserve -drop if dgn < 0 | dag<0 | dhe<0 -* eststo predict_dhm_ghq: reg dhm_ghq c.dag i.dgn i.swv i.dhe, vce(robust) // Physical health has a big impact, so included as covariate. -zinb dhm_ghq c.dag i.dgn i.swv i.dhe, inflate(dhm_ghq c.dag i.dgn i.swv i.dhe) vce(robust) // Physical health has a big impact, so included as covariate. -restore - -scalar lnalpha = _b[/lnalpha] -scalar theta = 1/exp(lnalpha) - -predict mu_hat, n // Count component mean (μ) -predict pi_hat, pr // Zero-inflation probability (π) - -gen u = runiform() -gen pred_score = . -replace pred_score = 0 if u < pi_hat // Structural zeros -replace pred_score = rnbinomial(theta, theta/(theta + mu_hat)) if u >= pi_hat // NB samples -replace pred_score = 12 if pred_score > 12 -replace pred_score = 0 if pred_score < 0 - - -cap gen dhm_ghq = 0 -replace dhm_ghq = scghq2_dv -lab var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): Caseness" - -gen dhm_ghq_flag = missing(dhm_ghq) -replace dhm_ghq = round(pred_score) if missing(dhm_ghq) - -/* Alternative method of GHQ caseness - binary cutoff at scghq2_dv <4 /*****************************Subjective well-being ***************************/ /*dhm scghq1_dv "DEMOGRAPHIC: Subjective wellbeing (GHQ): Likert Scale from 0 to 36, assumed to be continuous in the simulation." This measure converts valid answers to 12 questions of the General Health Questionnaire (GHQ) to a single scale by recoding so that @@ -437,7 +390,7 @@ replace dhm_ghq = 0 if scghq2_dv>=0 & scghq2_dv<4 replace dhm_ghq = 1 if scghq2_dv>=4 lab var dhm_ghq "DEMOGRAPHIC: Subjective wellbeing (GHQ): Caseness" //fre dhm_ghq -*/ + /****************************Self-rated health health - mental and physical component summary scores SF12 ***************************/ /*SF-12 Mental Component Summary (MCS). Continuous scale with a range of 0 (low functioning) to 100 (high functioning)*/ @@ -760,28 +713,28 @@ la var der "Return to education" //fre der /*****************************Partnership status*******************************/ -recode mastat_dv (2 3 10 = 1 "Partnered") /// - (0 1 = 2 "Single never married") /// Includes children under 16 - (4 5 6 7 8 9 = 3 "Previously partnered") /// - , into (dcpst) -la var dcpst "Partnership status" -recode dcpst (-8 -2 -1 = -9) - -*If idpartner = 0 (because of household splitting), dcpst should be set to 3 depending on mastat_dv value -replace dcpst = 3 if dcpst == 1 & idpartner <= 0 -replace dcpst = 1 if idpartner > 0 & !missing(idpartner) - -//Children coded as "Never Married" (17 and under chosen as can marry from 18 years onwards) -replace dcpst = 2 if dag <= 17 & idpartner<0 -//fre dcpst +gen dcpst = . +replace dcpst = 1 if idpartner > 0 & !missing(idpartner) //partnered +replace dcpst = 2 if idpartner < 0 | missing(idpartner) +lab var dcpst "Partnership status" +lab def dcpst 1 "partnered" 2 "single" +lab val dcpst dcpst + +recode dcpst (. = -9) +/* +* Children coded as "Never Married" +Can only marry from age 18 onwards in the simulation +*/ +replace dcpst = 2 if dag <= 17 & idpartner < 0 +//fre dcpst /*****************************Enter partnership*******************************/ sort idperson swv cap drop dcpen gen dcpen = -9 -replace dcpen=0 if (l.dcpst==2 | l.dcpst==3) -replace dcpen=1 if dcpst==1 & (l.dcpst==2 | l.dcpst==3) +replace dcpen=0 if (l.dcpst==2) +replace dcpen=1 if dcpst==1 & (l.dcpst==2) la val dcpen dummy la var dcpen "Enter partnership" //fre dcpen @@ -792,7 +745,7 @@ sort idperson swv cap drop dcpex gen dcpex=-9 replace dcpex = 0 if l.dcpst==1 -replace dcpex = 1 if dcpst==3 & l.dcpst==1 +replace dcpex = 1 if dcpst==2 & l.dcpst==1 la val dcpex dummy la var dcpex "Exit partnership" //fre dcpex @@ -804,7 +757,7 @@ la var dcpagdf "Partner's age difference" /*********************************Activity status*****************************/ -recode jbstat (1 2 5 12 13 14 = 1 "Employed or self-employed") /// +recode jbstat (1 2 5 12 13 14 15 = 1 "Employed or self-employed") /// (7 = 2 "Student") /// (3 6 8 10 11 97 9 4 = 3 "Not employed") /// /*includes apprenticeships, unpaid family business, govt training scheme+retired */ , into(les_c3) @@ -814,6 +767,7 @@ la var les "Activity status" replace les_c3 = 2 if dag <= 16 //People below age to leave home are not at risk of work so set activity status to not employed if not a student replace les_c3 = 3 if dag < $age_become_responsible & les_c3 != 2 +//fre les_c3 /***********************Activity status variable adding retirement*************/ @@ -824,7 +778,7 @@ replace les_c4 = 4 if jbstat==4 lab var les_c4 "LABOUR MARKET: Activity status" lab define les_c4 1 "Employed or self-employed" 2 "Student" 3 "Not employed" 4 "Retired" lab val les_c4 les_c4 -//tab2 les_c3 les_c4 +//fre les_c4 /****************************Partner's activity status:***********************/ @@ -918,18 +872,86 @@ bys swv idhh: egen dnc = sum(depChild) la var dnc "Number of dependent children 0 - 18" +/****************************Pension Age***************************************/ +/*cap gen bdt = mdy(1, 15, birthy) /*month of birth is available in special license only*/ +*/ +/*State Retirement Ages for Men in the UK (2009-2023): +2009-2010: 65 +2010-2011: 65 +2011-2012: 65 +2012-2013: 65 +2013-2014: 65 +2014-2015: 65 +2015-2016: 65 +2016-2017: 65 +2017-2018: 65 +2018-2019: 65 +2019-2020: 65 +2020-2021: 66 +2021-2022: 66 +2022-2023: 66 +State Retirement Ages for Women in the UK (2009-2023): +2009-2010: 60 +2010-2011: 60 +2011-2012: 60 +2012-2013: 61 +2013-2014: 61 +2014-2015: 62 +2015-2016: 62 +2016-2017: 63 +2017-2018: 63 +2018-2019: 64 +2019-2020: 65 +2020-2021: 65 +2021-2022: 66 +2022-2023: 66 +*/ +gen dagpns = 0 +//for men +replace dagpns = 1 if dgn==1 & dag>=65 & stm>=2009 & stm<2020 +replace dagpns = 1 if dgn==1 & dag>=66 & stm>=2020 +//for women +replace dagpns = 1 if dgn==0 & dag>=60 & stm>=2009 & stm<2012 +replace dagpns = 1 if dgn==0 & dag>=61 & stm>=2012 & stm<2014 +replace dagpns = 1 if dgn==0 & dag>=62 & stm>=2014 & stm<2016 +replace dagpns = 1 if dgn==0 & dag>=63 & stm>=2016 & stm<2018 +replace dagpns = 1 if dgn==0 & dag>=64 & stm>=2018 & stm<2019 +replace dagpns = 1 if dgn==0 & dag>=65 & stm>=2019 & stm<2021 +replace dagpns = 1 if dgn==0 & dag>=66 & stm>=2021 +//fre dagpns + + +/****************************Pension age of a spouse***************************/ +preserve +keep swv idperson idhh dagpns +rename dagpns dagpns_sp +rename idperson idpartner +save "$dir_data/temp_dagpns", replace +restore +merge m:1 swv idpartner idhh using "$dir_data/temp_dagpns" +keep if _merge == 1 | _merge == 3 +la var dagpns_sp "Pension age - partner" +drop _merge +replace dagpns_sp=-9 if idpartner<0 + + /*******************************Flag for adult children***********************/ +//add parental ages & retirement status preserve keep if dgn == 0 -keep swv idhh idperson dag +keep swv idhh idperson dag dagpns les_c4 rename idperson idmother rename dag dagmother +rename dagpns dagpnsmother +rename les_c4 les_c4mother save "$dir_data/temp_mother_dag", replace restore, preserve keep if dgn == 1 -keep swv idhh idperson dag +keep swv idhh idperson dag dagpns les_c4 rename idperson idfather rename dag dagfather +rename dagpns dagpnsfather +rename les_c4 les_c4father save "$dir_data/temp_father_dag", replace restore @@ -940,20 +962,38 @@ merge m:1 swv idhh idfather using "$dir_data/temp_father_dag" keep if _merge == 1 | _merge == 3 drop _merge -//Adult child is identified on the successful merge with mother / father in the same household and age -gen adultchildflag = (!missing(dagmother) | !missing(dagfather)) & dag >= $age_become_responsible & idpartner <= 0 -*Introduce a condition that (adult) children cannot be older than parents-15 year of age -replace adultchildflag = 0 if dag >= dagfather-15 | dag >= dagmother-15 + +/*Individual is considered as adult child if +- they have at least one parent in the household (i.e. non-missing parental age) +- aged 18+ +- do not have a partner living in the same household +- is at least 15 years younger than either of their parents +- neither of their parents is of the state retirement age in that particular year & neither is retired +*/ +gen adultchildflag = (!missing(dagmother) | !missing(dagfather)) & dag >= $age_become_responsible & idpartner <= 0 +replace adultchildflag = 0 if dag >= dagfather-15 & dag >= dagmother-15 //was previously or ==> replaced with & +//fre adultchildflag +replace adultchildflag = 0 if (dagpnsmother==1 | les_c4mother==4) & (dagpnsfather ==1 | les_c4father==4) +tab2 adultchildflag swv , row + +/*Account for cases missing information +replace adultchildflag = -9 if idmother>0 & /// + (dagmother==. | dagmother<0 | les_c4mother==. | les_c4mother<0) & dag >= 17 +replace adultchildflag = -9 if idfather>0 & /// + (dagfather==. | dagfather<0 | les_c4father==. | les_c4father<0) & dag >= 17 +fre adultchildflag +2.7% have missing info on one of their parents, not sure if it is worth dropping them? +*/ /************************Household composition*********************************/ cap gen dhhtp_c4 = -9 replace dhhtp_c4 = 1 if dcpst == 1 & dnc == 0 //Couple, no children replace dhhtp_c4 = 2 if dcpst == 1 & dnc > 0 & !missing(dnc) //Couple, children -replace dhhtp_c4 = 3 if (dcpst == 2 | dcpst == 3) & (dnc == 0 | dag <= $age_become_responsible | adultchildflag== 1) +replace dhhtp_c4 = 3 if (dcpst == 2) & (dnc == 0 | dag <= $age_become_responsible | adultchildflag== 1) /*Single, no children (Note: adult children and children below age to become responsible should be assigned "no children" category, even if there are some children in the household)*/ -replace dhhtp_c4 = 4 if (dcpst == 2 | dcpst == 3) & dnc > 0 & !missing(dnc) & dhhtp_c4 != 3 //Single, children +replace dhhtp_c4 = 4 if (dcpst == 2) & dnc > 0 & !missing(dnc) & dhhtp_c4 != 3 //Single, children la def dhhtp_c4_lb 1"Couple with no children" 2"Couple with children" 3"Single with no children" 4"Single with children" la values dhhtp_c4 dhhtp_c4_lb @@ -1045,75 +1085,10 @@ la var drtren "DEMOGRAPHIC: Enter retirement" //fre drtren -/****************************Pension Age***************************************/ -/*cap gen bdt = mdy(1, 15, birthy) /*month of birth is available in special license only*/ -*/ -/*State Retirement Ages for Men in the UK (2009-2023): - -2009-2010: 65 -2010-2011: 65 -2011-2012: 65 -2012-2013: 65 -2013-2014: 65 -2014-2015: 65 -2015-2016: 65 -2016-2017: 65 -2017-2018: 65 -2018-2019: 65 -2019-2020: 65 -2020-2021: 66 -2021-2022: 66 -2022-2023: 66 - -State Retirement Ages for Women in the UK (2009-2023): - -2009-2010: 60 -2010-2011: 60 -2011-2012: 60 -2012-2013: 61 -2013-2014: 61 -2014-2015: 62 -2015-2016: 62 -2016-2017: 63 -2017-2018: 63 -2018-2019: 64 -2019-2020: 65 -2020-2021: 65 -2021-2022: 66 -2022-2023: 66 -*/ -gen dagpns = 0 -//for men -replace dagpns = 1 if dgn==1 & dag>=65 & stm>=2009 & stm<2020 -replace dagpns = 1 if dgn==1 & dag>=66 & stm>=2020 -//for women -replace dagpns = 1 if dgn==0 & dag>=60 & stm>=2009 & stm<2012 -replace dagpns = 1 if dgn==0 & dag>=61 & stm>=2012 & stm<2014 -replace dagpns = 1 if dgn==0 & dag>=62 & stm>=2014 & stm<2016 -replace dagpns = 1 if dgn==0 & dag>=63 & stm>=2016 & stm<2018 -replace dagpns = 1 if dgn==0 & dag>=64 & stm>=2018 & stm<2019 -replace dagpns = 1 if dgn==0 & dag>=65 & stm>=2019 & stm<2021 -replace dagpns = 1 if dgn==0 & dag>=66 & stm>=2021 - - -/****************************Pension age of a spouse***************************/ -preserve -keep swv idperson idhh dagpns -rename dagpns dagpns_sp -rename idperson idpartner -save "$dir_data/temp_dagpns", replace -restore -merge m:1 swv idpartner idhh using "$dir_data/temp_dagpns" -keep if _merge == 1 | _merge == 3 -la var dagpns_sp "Pension age - partner" -drop _merge -replace dagpns_sp=-9 if idpartner<0 - - /************************************JBSTAT: Not Retired***********************/ -gen lesnr_c2 = . -replace lesnr_c2 = 1 if (jbstat ==1 | jbstat==2) /*employed*/ -replace lesnr_c2 = 2 if jbstat==3 | jbstat==5 | jbstat==6 | jbstat==8 | jbstat==9 | jbstat==10 | jbstat==11 | jbstat==14 | jbstat==97 +gen lesnr_c2 = -9 +replace lesnr_c2 = 1 if les_c3==1 +replace lesnr_c2 = 2 if les_c3==2 | les_c3==3 lab var lesnr_c2 "Not retired work status" lab define lesnr_c2 1 "in work" 2 "not in work" lab val lesnr_c2 lesnr_c2 @@ -1121,21 +1096,22 @@ lab val lesnr_c2 lesnr_c2 /************************Exited parental home*********************************/ /*Generated from fnspid and/or mnspid. 1 means that individual no longer lives with a parent (fnspid & mnspid is equal to missing) - when in the previous wave they lived with a parent (fnspid or mnspid not equal to missing).*/ -/* -bysort swv: fre mnspid if mnspid<=0 -bysort swv: fre fnspid if fnspid<=0 -bysort swv: fre mnspid if mnspid>=. -bysort swv: fre fnspid if fnspid>=. + when in the previous wave they lived with a parent (fnspid or mnspid not equal to missing). +NOTE: Leaving the parental home was synchronised with the definition of adult child; +an individual can leave the parental home unless they are a "responsible adult" (their both parents retired). */ sort idperson swv -gen dlftphm = -9 if (l.fnspid<0 & l.mnspid<0) //those who did not live with parents in the same hh -replace dlftphm=0 if (l.fnspid>0 | l.mnspid>0) //those who lived with at least one parent -replace dlftphm =1 if (fnspid<0 & mnspid<0) & (l.fnspid>0 | l.mnspid>0) //lived with at least one parent but not anymore -bys idperson: replace dlftphm =-9 if _n==1 //this condition will not be applicable for first year in the panel// -la val dlftphm dummy -la var dlftphm "DEMOGRAPHIC: Exited Parental Home" -//bys swv: fre dlftphm +gen dlftphm = -9 +replace dlftphm = 0 if adultchildflag[_n-1] == 1 & idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +replace dlftphm = 0 if dag == 18 & adultchildflag == 1 +replace dlftphm = 1 if adultchildflag == 0 & adultchildflag[_n-1] == 1 & idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +lab var dlftphm "DEMOGRAPHIC: Exit the Parental Home" +/* +tab dlftphm swv, col +tab dlftphm stm, col +tab dlftphm dun +tab dlftphm adultchildflag +*/ /*********************************Left education*******************************/ @@ -1195,6 +1171,14 @@ fre dukfr /************************Number of newborn*************************/ +/*NOTE: The approach below was not entirely correct for identifying newborns. +* It defines newborns based on child age (dag <= 1), not on actual birth events. +* As a result, it counts all children aged under one at interview, not just those +* born since the previous wave. The same baby can be counted twice across waves, +* and adopted or stepchildren under one may also be included. +* At the BHPS–UKHLS transition, this method overcounts legacy BHPS infants +* who were already born before the merge but still under one year old in wave B. +* reported since the last interview, linked to the reporting parent (usually the mother). cap gen child0 = 0 replace child0=1 if dag<=1 @@ -1220,6 +1204,134 @@ replace mother_dchpd=0 if dgn==1 drop dchpd rename mother_dchpd dchpd lab var dchpd "Women's number of newborn children" +*/ + +save "$dir_data\ukhls_pooled_all_obs_02.dta", replace +************************************************************************ +* Number of newborn from "newborn" datasets +************************************************************************ +/*DP: This code uses the UKHLS newborn module, where each row directly represents a birth event (not inferred from child age). +Each record corresponds to a child newly reported since the last interview. We exclude BHPS "legacy" infants in wave B to prevent overcounting at the merge. +- It is more conceptually exact – counts actual reported births, not inferred ones. +- No double-counting across waves – each newborn appears only once. +- Handles BHPS transition properly – avoids inflating wave B with pre-existing BHPS babies (note that in original Cara's SAS code all BHPS newborns were dropped which I think shoudn't happen, + so Cara's version was underestimating number of newborns. +*/ + +* Combine newborn files (b–n) into one long-format dataset +clear + +local firstwave : word 1 of $UKHLS_panel_waves + +* --- Load the first wave --- +use "${dir_ukhls_data}/`firstwave'_newborn.dta", clear +gen swv = "`firstwave'" + +* Remove wave prefix from variable names +local prefix = "`firstwave'_" +foreach var of varlist `firstwave'_* { + local base = subinstr("`var'", "`prefix'", "", .) + rename `var' `base' +} + +* Save as base file +save "${dir_data}/temp_uknbrn.dta", replace + +* --- Append remaining waves --- +foreach w of global UKHLS_panel_waves { + if "`w'" != "`firstwave'" { + di as text "Appending wave `w'..." + use "${dir_ukhls_data}/`w'_newborn.dta", clear + gen swv = "`w'" + + * Remove wave prefix + local prefix = "`w'_" + capture unab prefixed : `w'_* + if _rc == 0 { + foreach var of local prefixed { + local base = subinstr("`var'", "`prefix'", "", .) + rename `var' `base' + } + } + + * Append to the long dataset + append using "${dir_data}/temp_uknbrn.dta" + save "${dir_data}/temp_uknbrn.dta", replace + } +} +//convert wave number to numeric +gen swv_num = . +local i = 1 +foreach w of global UKHLS_panel_waves { + local num : word `i' of $UKHLS_panel_waves_numbers + replace swv_num = `num' if swv == "`w'" + local ++i +} +drop swv +rename swv_num swv +save "${dir_data}/temp_uknbrn.dta", replace + +* Count all genuine newborns (UKHLS + BHPS), excludes BHPS legacy infants in wave B +use "${dir_data}/temp_uknbrn.dta", clear + +keep pidp swv memorig lchlv +keep if lchlv == 1 + +* Define newborn indicator +gen byte nbrn = 0 +* UKHLS-origin respondents (memorig = 1, 2, 7, 8): +* Always count their newborns. These are all part of the original or ethnic minority boost samples. +replace nbrn = 1 if inlist(memorig, 1, 2, 7, 8) +* BHPS-origin respondents (memorig = 3, 4, 5, 6): +* The BHPS sample was integrated into UKHLS starting from wave B (2010–2012). +* Infants recorded at that point include "legacy" BHPS babies already born before +* the merge — not genuine new births within the UKHLS observation window. +** To avoid overcounting these legacy infants, we exclude BHPS-origin newborns +* only in their first UKHLS wave (wave B). From wave C onward, BHPS households +* are fully integrated, so new births are genuine new births and should be counted. +replace nbrn = 1 if inlist(memorig, 3, 4, 5, 6) & swv != 2 + +* Collapse to parent-wave level ==> both parents may report the same child of they are in the same hh +bys pidp swv: egen dchpd = total(nbrn) +label var dchpd "Number of newborn children (UKHLS + BHPS, excl. BHPS legacy infants in wave B)" +bys pidp swv: keep if _n == 1 //(376 observations deleted) +rename pidp idperson +save "${dir_data}/temp_parent_dchpd.dta", replace + +* Merge into main person-wave dataset +use "$dir_data\ukhls_pooled_all_obs_02.dta", clear +merge 1:1 idperson swv using "${dir_data}/temp_parent_dchpd.dta" +keep if _merge ==1 | _merge==3 +drop _merge + +* After merging: fill missing with 0 +replace dchpd = 0 if missing(dchpd) +label var dchpd "Number of newborn children (UKHLS + BHPS, excl. BHPS legacy infants in wave B)" + +/*check how many hh reported same newborn twice because both parents are respondents +preserve +* Keep only cases with at least one newborn +keep if dchpd > 0 +* Keep only core identifiers and gender +keep idperson idhh swv dgn dchpd +* Count households with both male and female respondents reporting newborns +bysort idhh swv: egen hh_births = total(dchpd>0) +bysort idhh swv: egen men_births = total(dchpd>0 & dgn==1) +bysort idhh swv: egen women_births = total(dchpd>0 & dgn==0) +* Mark households where both genders reported at least one newborn +gen both_parents = (men_births>0 & women_births>0) +* Summarise how common these are +tab men_births +tab women_births +tab both_parents +*No such cases, new births are reported by women only +restore +*/ + +* Note that for the estimates we will only keep newborns who are reported by mothers, but here we keep all reported newborns for each respondent +tab2 swv dchpd if dgn==1, m row +tab2 swv dchpd if dgn==0 & sprfm==1, m row +tab2 swv dchpd if dgn==0 & sprfm==0, m row /*****************************In educational age range*************************/ @@ -1695,9 +1807,6 @@ foreach var in idhh idperson idpartner idfather idmother dct drgn1 dwt dnc02 dnc qui recode `var' (-9/-1=-9) (.=-9) } - - - *recode missings in weights to zero. foreach var in dimlwt disclwt dimxwt dhhwt { qui recode `var' (.=0) (-9/-1=0) @@ -1733,6 +1842,31 @@ isid idperson idhh swv * save the whole pooled dataset that will be used for regression estimates *******************************************************************************/ save "$dir_data\ukhls_pooled_all_obs_02.dta", replace + + +/*********************** Run employment history do-files to produce liwwh *******************************/ +* 01_Intdate.do: set up cross-wave file of interview dates +* ==> needed to link previous wave interview date to each respondent*/ +do "${dir_do_emphist}/00_Master_emphist.do" + +use "$dir_data\ukhls_pooled_all_obs_02.dta", clear + +merge 1:1 idperson swv using "${dir_data_emphist}/temp_liwwh", keepusing (liwwh) +//This is done analogous to UKMOD input data +drop if _merge==2 +replace liwwh=12 if _merge==1 +replace liwwh=0 if _merge==1 & les_c3 !=1 //assume zero months if not in employment +replace liwwh=-9 if swv==1 + +replace liwwh = liwwh/12 +label var liwwh "Total years in employment since Jan 2007" + +bys swv: fre liwwh if dag<16 +bys swv: fre liwwh if dag>=16 + +drop _merge +save "$dir_data\ukhls_pooled_all_obs_02.dta", replace + cap log close @@ -1742,7 +1876,6 @@ cap log close #delimit ; local files_to_drop father_edu.dta - mother_dchpd.dta mother_edu.dta temp.dta temp_age.dta @@ -1758,7 +1891,8 @@ local files_to_drop temp_ypnb.dta tmp_partnershipDuration.dta temp_dot01.dta - + temp_uknbrn.dta + temp_parent_dchpd.dta ; #delimit cr // cr stands for carriage return diff --git a/input/InitialPopulations/compile/06_reweight_and_slice.do b/input/InitialPopulations/compile/06_reweight_and_slice.do index d94be7bd9..f3e0aa8f6 100644 --- a/input/InitialPopulations/compile/06_reweight_and_slice.do +++ b/input/InitialPopulations/compile/06_reweight_and_slice.do @@ -3,7 +3,7 @@ * WEIGHT ADJUSTMENT TO ACCOUNT FOR USING HOUSEHOLDS WITHOUT MISSING VALUES * * AUTH: Patryk Bronka, Daria Popova, Justin van de Ven -* LAST EDIT: 18 July 2025 DP +* LAST EDIT: 21 Oct 2025 DP * *********************************************************************/ ******************************************************************************** @@ -60,7 +60,7 @@ recode hh_size (1=1) (2=2) (3=3) (4/max=4) , gen(hhsize_cat2) /*Household-level probit. Model probabiltiy of being a complete household conditional on presence of people of certain education age gender combination, marital status and region.*/ -probit complete_hh _Ideh* dcpstcat* ib8.drgn1 i.stm , vce(robust) iterate(20) //i.hhsize_cat2 DP: dropped as otherwise does not converge +probit complete_hh _Ideh* dcpstcat* ib8.drgn1 i.stm , vce(robust) iterate(20) //i.hhsize_cat2, dropped as otherwise does not converge *Predict probability of being a complete household predict pr_comphh diff --git a/input/InitialPopulations/compile/08_wealth_to_ukhls.do b/input/InitialPopulations/compile/08_wealth_to_ukhls.do index 40be09823..9ec9e7edd 100644 --- a/input/InitialPopulations/compile/08_wealth_to_ukhls.do +++ b/input/InitialPopulations/compile/08_wealth_to_ukhls.do @@ -404,7 +404,7 @@ save "population_initial_fs_UK_$yearWealth", replace /************************************************************************************** * clean-up and exit -*************************************************************************************/ +************************************************************************************* #delimit ; local files_to_drop ukhls_wealthtemp.dta @@ -418,7 +418,7 @@ foreach file of local files_to_drop { erase "$dir_data/`file'" } - +*/ /************************************************************************************** * fin **************************************************************************************/ diff --git a/input/InitialPopulations/compile/09_finalise_input_data.do b/input/InitialPopulations/compile/09_finalise_input_data.do index d261d5db3..1b58c8b1f 100644 --- a/input/InitialPopulations/compile/09_finalise_input_data.do +++ b/input/InitialPopulations/compile/09_finalise_input_data.do @@ -6,7 +6,7 @@ * COUNTRY: UK * DATA: UKHLS EUL version - UKDA-6614-stata [to wave n] * AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 18 July 2025 +* LAST UPDATE: 3 Nov 2025 * NOTE: Called from 00_master.do - see master file for further details *************************************************************************************** @@ -185,23 +185,25 @@ forvalues yy = $firstSimYear/$lastSimYear { *limit saved variables keep idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// - yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// - stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt /// - potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost carehoursprovidedweekly /// - econ_benefits econ_benefits_nonuc econ_benefits_uc /// - disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp financial_distress + yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// + stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// + l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// + formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// + dhe_pcssp dls dot dot01 unemp financial_distress liwwh - order idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen /// - dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag /// - multiplier dwt potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost carehoursprovidedweekly /// - econ_benefits econ_benefits_nonuc econ_benefits_uc /// - disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp financial_distress + order idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// + yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// + stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// + l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// + formal_socare_cost carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// + dhe_pcssp dls dot dot01 unemp financial_distress liwwh - recode idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp /// - dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 /// - adultchildflag multiplier dwt potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs carehoursprovidedweekly /// - econ_benefits econ_benefits_nonuc econ_benefits_uc /// - formal_socare_cost disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dls dot dot01 unemp financial_distress (missing=-9) + recode idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// + yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dchpd dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// + stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw l1_lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt potential_earnings_hourly /// + l1_potential_earnings_hourly liquid_wealth tot_pen nvmhome need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// + carehoursprovidedweekly econ_benefits econ_benefits_nonuc econ_benefits_uc formal_socare_cost disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp /// + dhe_pcssp dls dot dot01 unemp financial_distress liwwh (missing=-9) gsort idhh idbenefitunit idperson save "$dir_data/population_initial_UK_$year.dta", replace @@ -211,11 +213,17 @@ forvalues yy = $firstSimYear/$lastSimYear { } cap log close -/**************************************************************************************** + + +*************************************************************************************** * finalise *************************************************************************************** #delimit ; local files_to_drop + ukhls_wealthtemp.dta + ukhls_wealthtemp1.dta + ukhls_wealthtemp2.dta + ukhls_wealthtemp3.dta was_wealthdata.dta ; #delimit cr // cr stands for carriage return @@ -223,7 +231,7 @@ local files_to_drop foreach file of local files_to_drop { erase "$dir_data/`file'" } -*/ + *************************************************************************************** * end diff --git a/input/InitialPopulations/compile/10_check_yearly_data.do b/input/InitialPopulations/compile/10_check_yearly_data.do index e73de386d..b589923b9 100644 --- a/input/InitialPopulations/compile/10_check_yearly_data.do +++ b/input/InitialPopulations/compile/10_check_yearly_data.do @@ -6,7 +6,7 @@ * COUNTRY: UK * DATA: UKHLS EUL version - UKDA-6614-stata [to wave n] * AUTHORS: Daria Popova -* LAST UPDATE: 18 July 2025 DP +* LAST UPDATE: 3 Nov 2025 DP * NOTE: Called from 00_master.do - see master file for further details ***************************************************************************************/* set matsize 11000, permanently @@ -52,7 +52,8 @@ dcpagdf ynbcpdf_dv der sedag -sprfm +sprfm +dchpd dagsp dehsp_c3 dhesp @@ -86,7 +87,6 @@ daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost -disp_inc ypncp ypnoab dhe_mcs @@ -97,6 +97,7 @@ unemp dls financial_distress carehoursprovidedweekly +liwwh ; #delimit cr // cr stands for carriage return @@ -137,14 +138,12 @@ pno swv dgn dag -dcpst dnc02 dnc ded sedex dlltsd dlltsd01 -disp_inc ypncp ypnoab yplgrs_dv @@ -159,6 +158,7 @@ ynbcpdf_dv der sedag sprfm +dchpd dagsp stm dhm @@ -171,7 +171,6 @@ multiplier dwt dcpst_1 dcpst_2 -dcpst_3 deh_c3_1 deh_c3_2 deh_c3_3 @@ -259,6 +258,7 @@ unemp dls financial_distress carehoursprovidedweekly +liwwh ; #delimit cr // cr stands for carriage return @@ -304,7 +304,7 @@ qui sum `varlist2' , de outreg2 using "$dir_data/population_initial_UK_sumstats.xls" if stm==`year', sum(log) append cttop(`year') keep (`varlist2') } -/* + ********************************************************************** *output summary stats for new initial populations before dropping hhs* ********************************************************************** @@ -348,40 +348,9 @@ qui sum `varlist2' , de outreg2 using "$dir_data/population_initial_fs_UK_sumstats.xls" if stm==`year', sum(log) append cttop(`year') keep (`varlist2') } -*/ cap erase "$dir_data/population_initial_UK_sumstats.txt" cap erase "$dir_data/population_initial_fs_UK_sumstats.txt" cap log close - -/* -************************************************************* -*clean up new initial populations - keep only required vars * -************************************************************* -forvalues year=2010/2023 { -insheet using "$dir_data/population_initial_UK_`year'.csv", clear - - *limit saved variables - keep idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 /// - yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 /// - stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag multiplier dwt /// - potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost /// - disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dot dot01 unemp dhe_mcssp dhe_pcssp - - order idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp dcpen /// - dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 adultchildflag /// - multiplier dwt potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs formal_socare_cost /// - disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dot dot01 unemp - - recode idhh idbenefitunit idperson idpartner idmother idfather pno swv dgn dag dcpst dnc02 dnc ded deh_c3 sedex jbstat les_c3 dlltsd dlltsd01 dhe ydses_c5 yplgrs_dv ypnbihs_dv yptciihs_dv dhhtp_c4 ssscp /// - dcpen dcpyy dcpex dcpagdf ynbcpdf_dv der sedag sprfm dagsp dehsp_c3 dhesp lessp_c3 dehm_c3 dehf_c3 stm lesdf_c4 ppno dhm scghq2_dv dhh_owned lhw drgn1 dct dwt_sampling les_c4 dhm_ghq lessp_c4 /// - adultchildflag multiplier dwt potential_earnings_hourly l1_potential_earnings_hourly liquid_wealth need_socare formal_socare_hrs partner_socare_hrs daughter_socare_hrs son_socare_hrs other_socare_hrs /// - formal_socare_cost disp_inc ypncp ypnoab aidhrs carewho dhe_mcs dhe_pcs dhe_mcssp dhe_pcssp dot dot01 unemp (missing=-9) - - gsort idhh idbenefitunit idperson - save "$dir_data/population_initial_UK_`year'.dta", replace - export delimited using "$dir_data/population_initial_UK_`year'.csv", nolabel replace -} -*/ diff --git a/input/InitialPopulations/compile/RegressionEstimates/master.do b/input/InitialPopulations/compile/RegressionEstimates/master.do index 373b7f3f8..4e4337a13 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/master.do +++ b/input/InitialPopulations/compile/RegressionEstimates/master.do @@ -8,7 +8,7 @@ * DATA: UKHLS EUL version - UKDA-6614-stata [to wave n] * * AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 1 July 2025 DP +* LAST UPDATE: 5 Nov 2025 DP *************************************************************************************** *************************************************************************************** @@ -47,7 +47,7 @@ set matsize 1000 **************************************************************************************/ * Working directory -global dir_work "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates" +global dir_work "D:\Dasha\ESSEX\_SimPaths\_SimPaths_UK\regression_estimates" * Directory which contains do files global dir_do "${dir_work}/do" @@ -62,26 +62,26 @@ global dir_raw_results "${dir_work}/raw_results" global dir_results "${dir_work}/results" * Directory which contains pooled dataset for estimates -global dir_ukhls_data "D:\Dasha\ESSEX\ESPON 2024\UK\initial_populations\data" +global dir_ukhls_data "D:\Dasha\ESSEX\_SimPaths\_SimPaths_UK\initial_populations\data" * Directory containing external input data global dir_external_data "$dir_work/external_data" * Directory containing results of comparison of various weights -global weight_checks "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates\weight_checks" +global weight_checks "${dir_work}/weight_checks" *********************Internal validation**************************************** * Directory to save data for internal validation -global dir_validation_data "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates\internal_validation\data" +global dir_validation_data "${dir_work}/internal_validation/data" * Directory for internal validation do-files -global dir_do_validation "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates\internal_validation\do_files" +global dir_do_validation "${dir_work}/internal_validation/do_files" * Directory for internal validation do-files -global dir_do_validation "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates\internal_validation\do_files" +global dir_do_validation "${dir_work}/internal_validation/do_files" * Directory for internal validation do-files -global dir_validation_graphs "D:\Dasha\ESSEX\ESPON 2024\UK\regression_estimates\internal_validation\graphs" +global dir_validation_graphs "${dir_work}/internal_validation/graphs" global countyy "UK" @@ -108,9 +108,7 @@ do "${dir_do}/reg_wages.do" do "${dir_do}/reg_income.do" - - -/******************************************************************************* +******************************************************************************* * INTERNAL VALIDATION FILES ****************************************************************************** @@ -131,7 +129,7 @@ do "$dir_do_validation/int_val_retirement.do" do "$dir_do_validation/int_val_wages.do" do "$dir_do_validation/int_val_income.do" -*/ + /************************************************************************************** * END OF FILE **************************************************************************************/ diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do b/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do index 95ed15194..c40bd79b5 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_fertility.do @@ -1,9 +1,9 @@ -******************************************************************************** +********************************************************************************* * PROJECT: ESPON * SECTION: Fertility * OBJECT: Final Probit Models * AUTHORS: Daria Popova, Justin van de Ven -* LAST UPDATE: 26 Aug 2025 DP +* LAST UPDATE: 21 Oct 2025 DP * COUNTRY: UK * * NOTES: Simplified the fertility process for those in this initial @@ -37,7 +37,7 @@ putexcel set "$dir_results/reg_fertility", sheet("Info") replace putexcel A1 = "Description:" putexcel B1 = "Model parameters governing projection of fertility" putexcel A2 = "Authors: Patryk Bronka, Justin van de Ven, Daria Popova" -putexcel A3 = "Last edit: 1 July 2025 DP" +putexcel A3 = "Last edit: 3 Nov 2025 DP" putexcel A4 = "Process:", bold putexcel B4 = "Description:", bold @@ -49,7 +49,7 @@ putexcel B6 = "Probit regression estimates of probability of having a child for putexcel A10 = "Notes:", bold putexcel B10 = "All processes: replaced dhe with dhe_pcs and dhe_mcs, added ethnicity-4 cat (dot), covid dummies (y2020 y2021)" putexcel B11 = "F1a: only 24 obs having a child when in initial education spell, therefore have to take away some covariates to obtain estimate" - +putexcel B12 = "All processes: replaced dcpst with a dummy version (1=partnered 2=single)" putexcel set "$dir_results/reg_fertility", sheet("Gof") modify putexcel A1 = "Goodness of fit", bold @@ -63,9 +63,11 @@ xtset idperson swv * Process F1a: Probabiltiy of having a child * Sample: Women aged 18-44, in initial education spell education. * DV: New born child dummy (note that in the estimation sample dchpd contains the number of newborn children, which could be >1) - +tab sprfm dgn replace dchpd=1 if dchpd>1 & dchpd<. -// only 69 ppl meet the condition in total +replace dchpd = 0 if dchpd==-9 +tab2 swv dchpd, row + tab dchpd if (sprfm == 1 & ded == 1) /*///////////////////////////////////////////////////////////////////////////////////////////////// @@ -86,10 +88,9 @@ erase "${weight_checks}/weight_comparison_F1a.txt" //////////////////////////////////////////////////////////////////////////////////////////////////// */ -probit dchpd dag /*dhe dhe_mcs dhe_pcs*/ ib1.dcpst stm /*y2020 y2021*/ i.dot if /// +probit dchpd Dag /*dhe dhe_mcs dhe_pcs li.Dcpst_Single*/ Year_transformed /*y2020 y2021*/ Ethn_Asian Ethn_Black Ethn_Other if /// sprfm == 1 & ded == 1 [pweight=dimxwt], vce(robust) - * raw results matrix results = r(table) matrix results = results[1..6,1...]' @@ -112,95 +113,77 @@ scalar N = e(N) scalar chi2 = e(chi2) scalar ll = e(ll) +* Store results in Excel -* Results -* Note: Zeros eliminated - +* Store estimates matrix b = e(b) matrix V = e(V) +mata: + // Call matrices into mata + V = st_matrix("V") + b = st_matrix("b") -* Store variance-covariance matrix - -preserve - -putexcel set "$dir_raw_results/fertility/var_cov", sheet("var_cov") replace -putexcel A1 = matrix(V) - -import excel "$dir_raw_results/fertility/var_cov", sheet("var_cov") clear - -describe -local no_vars = `r(k)' + // Find which coefficients are nonzero + keep = (b :!= 0) -forvalues i = 1/2 { - egen row_sum = rowtotal(*) - drop if row_sum == 0 - drop row_sum - xpose, clear -} + // Eliminate zeros + b_trimmed = select(b, keep) + V_trimmed = select(V, keep) + V_trimmed = select(V_trimmed', keep)' + + // Inspection + b_trimmed + V_trimmed -mkmat v*, matrix(var) -putexcel set "$dir_results/reg_fertility", sheet("UK_F1a") modify -putexcel C2 = matrix(var) - -restore + // Return to Stata + st_matrix("b_trimmed", b_trimmed') + st_matrix("V_trimmed", V_trimmed) + st_matrix("nonzero_b_flag", keep) +end +* Export into Excel +putexcel set "$dir_results/reg_fertility", sheet("F1a") modify +putexcel B2 = matrix(b_trimmed) +putexcel C2 = matrix(V_trimmed) -* Store estimated coefficients -// Initialize a counter for non-zero coefficients -local non_zero_count = 0 -//local names : colnames b - -// Loop through each element in `b` to count non-zero coefficients -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - local non_zero_count = `non_zero_count' + 1 - } -} - -// Create a new row vector to hold only non-zero coefficients -matrix nonzero_b = J(1, `non_zero_count', .) - -// Populate nonzero_b with non-zero coefficients from b -local index = 1 -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - matrix nonzero_b[1, `index'] = b[1, `i'] - local index = `index' + 1 - } -} - -putexcel set "$dir_results/reg_fertility", sheet("UK_F1a") modify -putexcel A1 = matrix(nonzero_b'), names nformat(number_d2) +* Labelling +// Need to variable label when add new variable to model. Order matters. +local var_list Dag Year_transformed Ethn_Asian Ethn_Black Ethn_Other Constant + +putexcel A1 = "REGRESSOR" +putexcel B1 = "COEFFICIENT" +local i = 1 +foreach var in `var_list' { + local ++i + putexcel A`i' = "`var'" -* Labelling +} -putexcel A1 = "REGRESSOR" -putexcel A2 = "Dag" -putexcel A3 = "Dcpst_Single" -putexcel A4 = "Year_transformed" -putexcel A5 = "Ethn_Black" -putexcel A6 = "Ethn_Other" -putexcel A7 = "Constant" +local i = 2 +foreach var in `var_list' { + local ++i -putexcel B1 = "COEFFICIENT" -putexcel C1 = "Dag" -putexcel D1 = "Dcpst_Single" -putexcel E1 = "Year_transformed" -putexcel F1 = "Ethn_Black" -putexcel G1 = "Ethn_Other" -putexcel H1 = "Constant" + if `i' <= 26 { + local letter = char(64 + `i') // Convert 1=A, 2=B, ..., 26=Z + putexcel `letter'1 = "`var'" + } + else { + local first = char(64 + int((`i' - 1) / 26)) // First letter: A-Z + local second = char(65 + mod((`i' - 1), 26)) // Second letter: A-Z + putexcel `first'`second'1 = "`var'" // Correctly places AA-ZZ + } +} - -* Goodness of fit +* Export model fit statistics putexcel set "$dir_results/reg_fertility", sheet("Gof") modify -putexcel A3 = "F1a - Fertility in initial education spell", bold +putexcel A9 = "F1a - Fertility, in initial education spell", bold putexcel A5 = "Pseudo R-squared" putexcel B5 = r2_p @@ -212,7 +195,10 @@ putexcel E6 = "Log likelihood" putexcel F6 = ll drop in_sample p -scalar drop r2_p N chi2 ll +scalar drop r2_p N chi2 ll + + + ************************************************ * F1b - Having a child, left initial edu spell * @@ -245,9 +231,17 @@ erase "${weight_checks}/weight_comparison_F1b.txt" //////////////////////////////////////////////////////////////////////////////////////////////////// */ -probit dchpd dag dagsq li.ydses_c5 l.dnc l.dnc02 /*ib1.dhe*/ dhe_pcs dhe_mcs /*ib1.dcpst*/ /// - lib1.dcpst ib1.deh_c3 dukfr li.les_c3 ib8.drgn1 stm y2020 y2021 i.dot if /// - (sprfm == 1 & ded == 0) [pweight=dimxwt], vce(robust) +probit dchpd Dag Dag_sq Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + Dnc_L1 Dnc02_L1 /// + Dhe_pcs Dhe_mcs /// + Dcpst_Single_L1 /// + Deh_c3_Medium Deh_c3_Low /// + FertilityRate /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other /// +if (sprfm == 1 & ded == 0) [pweight = dimxwt], vce(robust) + * raw results matrix results = r(table) @@ -271,151 +265,84 @@ scalar N = e(N) scalar chi2 = e(chi2) scalar ll = e(ll) - -* Results -* Note: Zeros eliminated - -matrix b = e(b) -matrix V = e(V) - -* Store variance-covariance matrix +* Store results in Excel -preserve - -putexcel set "$dir_raw_results/fertility/var_cov", sheet("var_cov") replace -putexcel A1 = matrix(V) +* Store estimates +matrix b = e(b) +matrix V = e(V) -import excel "$dir_raw_results/fertility/var_cov", sheet("var_cov") clear +mata: + // Call matrices into mata + V = st_matrix("V") + b = st_matrix("b") -describe -local no_vars = `r(k)' + // Find which coefficients are nonzero + keep = (b :!= 0) -forvalues i = 1/2 { - egen row_sum = rowtotal(*) - drop if row_sum == 0 - drop row_sum - xpose, clear -} + // Eliminate zeros + b_trimmed = select(b, keep) + V_trimmed = select(V, keep) + V_trimmed = select(V_trimmed', keep)' + + // Inspection + b_trimmed + V_trimmed -mkmat v*, matrix(var) -putexcel set "$dir_results/reg_fertility", sheet("UK_F1b") modify -putexcel C2 = matrix(var) - -restore + // Return to Stata + st_matrix("b_trimmed", b_trimmed') + st_matrix("V_trimmed", V_trimmed) + st_matrix("nonzero_b_flag", keep) +end +* Export into Excel +putexcel set "$dir_results/reg_fertility", sheet("F1b") modify +putexcel B2 = matrix(b_trimmed) +putexcel C2 = matrix(V_trimmed) -* Store estimated coefficients +* Labelling +// Need to variable label when add new variable to model. Order matters. +local var_list Dag Dag_sq Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + Dnc_L1 Dnc02_L1 /// + Dhe_pcs Dhe_mcs /// + Dcpst_Single_L1 /// + Deh_c3_Medium Deh_c3_Low /// + FertilityRate /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other Constant + + +putexcel A1 = "REGRESSOR" +putexcel B1 = "COEFFICIENT" + +local i = 1 +foreach var in `var_list' { + local ++i + + putexcel A`i' = "`var'" + +} -// Initialize a counter for non-zero coefficients -local non_zero_count = 0 -//local names : colnames b +local i = 2 +foreach var in `var_list' { + local ++i -// Loop through each element in `b` to count non-zero coefficients -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - local non_zero_count = `non_zero_count' + 1 + if `i' <= 26 { + local letter = char(64 + `i') // Convert 1=A, 2=B, ..., 26=Z + putexcel `letter'1 = "`var'" } -} - -// Create a new row vector to hold only non-zero coefficients -matrix nonzero_b = J(1, `non_zero_count', .) - -// Populate nonzero_b with non-zero coefficients from b -local index = 1 -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - matrix nonzero_b[1, `index'] = b[1, `i'] - local index = `index' + 1 + else { + local first = char(64 + int((`i' - 1) / 26)) // First letter: A-Z + local second = char(65 + mod((`i' - 1), 26)) // Second letter: A-Z + putexcel `first'`second'1 = "`var'" // Correctly places AA-ZZ } } -putexcel set "$dir_results/reg_fertility", sheet("UK_F1b") modify -putexcel A1 = matrix(nonzero_b'), names nformat(number_d2) - - -* Labelling - -putexcel A1 = "REGRESSOR" -putexcel A2 = "Dag" -putexcel A3 = "Dag_sq" -putexcel A4 = "Ydses_c5_Q2_L1" -putexcel A5 = "Ydses_c5_Q3_L1" -putexcel A6 = "Ydses_c5_Q4_L1" -putexcel A7 = "Ydses_c5_Q5_L1" -putexcel A8 = "Dnc_L1" -putexcel A9 = "Dnc02_L1" -putexcel A10 = "Dhe_pcs" -putexcel A11 = "Dhe_mcs" -putexcel A12 = "Dcpst_Single_L1" -putexcel A13 = "Dcpst_PreviouslyPartnered_L1" -putexcel A14 = "Deh_c3_Medium" -putexcel A15 = "Deh_c3_Low" -putexcel A16 = "FertilityRate" -putexcel A17 = "Les_c3_Student_L1" -putexcel A18 = "Les_c3_NotEmployed_L1" -putexcel A19 = "UKC" -putexcel A20 = "UKD" -putexcel A21 = "UKE" -putexcel A22 = "UKF" -putexcel A23 = "UKG" -putexcel A24 = "UKH" -putexcel A25 = "UKJ" -putexcel A26 = "UKK" -putexcel A27 = "UKL" -putexcel A28 = "UKM" -putexcel A29 = "UKN" -putexcel A30 = "Year_transformed" -putexcel A31 = "Y2020" -putexcel A32 = "Y2021" -putexcel A33 = "Ethn_Asian" -putexcel A34 = "Ethn_Black" -putexcel A35 = "Ethn_Other" -putexcel A36 = "Constant" - -putexcel B1 = "COEFFICIENT" -putexcel C1 = "Dag" -putexcel D1 = "Dag_sq" -putexcel E1 = "Ydses_c5_Q2_L1" -putexcel F1 = "Ydses_c5_Q3_L1" -putexcel G1 = "Ydses_c5_Q4_L1" -putexcel H1 = "Ydses_c5_Q5_L1" -putexcel I1 = "Dnc_L1" -putexcel J1 = "Dnc02_L1" -putexcel K1 = "Dhe_pcs" -putexcel L1 = "Dhe_mcs" -putexcel M1 = "Dcpst_Single_L1" -putexcel N1 = "Dcpst_PreviouslyPartnered_L1" -putexcel O1 = "Deh_c3_Medium" -putexcel P1 = "Deh_c3_Low" -putexcel Q1 = "FertilityRate" -putexcel R1 = "Les_c3_Student_L1" -putexcel S1 = "Les_c3_NotEmployed_L1" -putexcel T1 = "UKC" -putexcel U1 = "UKD" -putexcel V1 = "UKE" -putexcel W1 = "UKF" -putexcel X1 = "UKG" -putexcel Y1 = "UKH" -putexcel Z1 = "UKJ" -putexcel AA1 = "UKK" -putexcel AB1 = "UKL" -putexcel AC1 = "UKM" -putexcel AD1 = "UKN" -putexcel AE1 = "Year_transformed" -putexcel AF1 = "Y2020" -putexcel AG1 = "Y2021" -putexcel AH1 = "Ethn_Asian" -putexcel AI1 = "Ethn_Black" -putexcel AJ1 = "Ethn_Other" -putexcel AK1 = "Constant" - - -* Goodness of fit - +* Export model fit statistics putexcel set "$dir_results/reg_fertility", sheet("Gof") modify -putexcel A9 = "F1b - Fertility left initial education spell", bold +putexcel A9 = "F1b - Fertility, left initial education spell", bold putexcel A11 = "Pseudo R-squared" putexcel B11 = r2_p @@ -428,7 +355,7 @@ putexcel F12 = ll drop in_sample p scalar drop r2_p N chi2 ll - - + + capture log close diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership.do b/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership.do index 427c70485..d75449cd7 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_home_ownership.do @@ -26,12 +26,11 @@ use "$dir_ukhls_data/ukhls_pooled_all_obs_09.dta", clear do "$dir_do/variable_update" -*sample selection +/*sample selection drop if dag < 16 - xtset idperson swv - +*/ * Set Excel file @@ -41,7 +40,7 @@ putexcel set "$dir_results/reg_home_ownership", sheet("Info") replace putexcel A1 = "Description:" putexcel B1 = "Model parameters governing projection of home ownership" putexcel A2 = "Authors: Patryk Bronka, Justin van de Ven, Daria Popova" -putexcel A3 = "Last edit: 1 July 2025 DP" +putexcel A3 = "Last edit: 4 Nov 2025 DP" putexcel A4 = "Process:", bold putexcel B4 = "Description:", bold @@ -51,6 +50,7 @@ putexcel B5 = "Probit regression estimates of the probability of being a home ow putexcel A10 = "Notes:", bold putexcel B10 = "Have combined dhhtp_c4 and lessp_c3 into a single variable with 8 categories, dhhtp_c8" putexcel B11 = "Added lagged home ownership, replaced dhe with dhe_pcs and dhe_mcs, added ethnicity (dot) and covid dummies (y2020 2021)" +putexcel B12 = "Re-estimated process at benefit unit level to be consistent with SimPaths" putexcel set "$dir_results/reg_home_ownership", sheet("Gof") modify putexcel A1 = "Goodness of fit", bold @@ -61,12 +61,13 @@ putexcel A1 = "Goodness of fit", bold ************************ * Process HO1a: Probability of being a home owner -* Sample: Individuals aged 18+ +* Sample: Individuals aged 18+ who are benefit unit heads * DV: Home ownerhip dummy +/* fre dhh_owned if dag >= 18 -/*///////////////////////////////////////////////////////////////////////////////////////////////// +///////////////////////////////////////////////////////////////////////////////////////////////// //check weights ////////////////////////////////////////////////////////////////////////////////// probit dhh_owned dgn dag dagsq il.dhhtp_c8 il.les_c3 /// i.deh_c3 /*il.dhe*/ l.dhe_mcs l.dhe_pcs il.ydses_c5 l.yptciihs_dv l.dhh_owned ib8.drgn1 stm y2020 y2021 i.dot if /// @@ -85,12 +86,97 @@ outreg2 using "${weight_checks}/weight_comparison_HO1a.xls", alpha(0.001, 0.01, erase "${weight_checks}/weight_comparison_HO1a.txt" //////////////////////////////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////////////////////////////// -*/ + probit dhh_owned dgn dag dagsq il.dhhtp_c8 il.les_c3 /// i.deh_c3 /*il.dhe*/ l.dhe_mcs l.dhe_pcs il.ydses_c5 l.yptciihs_dv l.dhh_owned ib8.drgn1 stm y2020 y2021 i.dot if /// dag>=18 [pweight=dimxwt], vce(cluster idperson) +*/ + +* DEFINE BENEFIT UNIT HEAD (AGED 18+) + +* Keep adults (18+) +keep if dag >= 18 + + +* Count unique benefit-unit–wave combinations BEFORE head selection +egen tag_bu_wave = tag(idbenefitunit swv) +count if tag_bu_wave +local n_bu_before = r(N) +display "Number of benefit unit–wave combinations BEFORE selecting head: `n_bu_before'" + + +* Sort benefit unit members within each wave: +* 1. Highest non-benefit income (ypnbihs_dv) +* 2. Highest age (dag) +* 3. Lowest idperson (idperson) +gsort idbenefitunit swv -ypnbihs_dv -dag idperson + +* Tag the first person (the "head") per benefit unit and wave +bysort idbenefitunit swv: gen benunit_head = (_n == 1) + +* Keep only benefit unit heads +keep if benunit_head == 1 + +* Count unique benefit-unit–wave combinations AFTER head selection +drop tag_bu_wave +egen tag_bu_wave = tag(idbenefitunit swv) +count if tag_bu_wave +local n_bu_after = r(N) +display "Number of benefit unit–wave combinations AFTER selecting head: `n_bu_after'" + +* Ensure benefit unit–wave counts match before and after head selection +assert `n_bu_before' == `n_bu_after' + +* Verify only one head per benefit unit per wave +by idbenefitunit swv, sort: gen n=_N +assert n==1 + +* Declare panel +xtset idperson swv + + +******************************************************************************** +* SET EXCEL OUTPUT FILES +******************************************************************************** + +* Info sheet +putexcel set "$dir_results/reg_home_ownership", sheet("Info") replace +putexcel A1 = "Description:" +putexcel B1 = "Model parameters governing projection of home ownership" +putexcel A2 = "Authors: Patryk Bronka, Justin van de Ven, Daria Popova" +putexcel A3 = "Last edit: 4 Nov 2025 DP" +putexcel A4 = "Process:", bold +putexcel B4 = "Description:", bold +putexcel A5 = "HO1a" +putexcel B5 = "Probit regression estimates of the probability of being a home owner, benefit unit heads aged 18+" + +putexcel A10 = "Notes:", bold +putexcel B10 = "Have combined dhhtp_c4 and lessp_c3 into a single variable with 8 categories, dhhtp_c8" +putexcel B11 = "Added lagged home ownership, replaced dhe with dhe_pcs and dhe_mcs, added ethnicity (dot) and covid dummies (y2020, y2021)" +putexcel B12 = "Re-estimated process at benefit unit level using heads defined by highest personal non-benefit income, or age, or lowest idperson" + +putexcel set "$dir_results/reg_home_ownership", sheet("Gof") modify +putexcel A1 = "Goodness of fit", bold + + +******************************************************************************** +* HO1a: Home ownership +******************************************************************************** + +probit dhh_owned Dgn Dag Dag_sq /// + Dhhtp_c8_2_L1 Dhhtp_c8_3_L1 Dhhtp_c8_4_L1 Dhhtp_c8_5_L1 Dhhtp_c8_6_L1 Dhhtp_c8_7_L1 Dhhtp_c8_8_L1 /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + Deh_c3_Medium Deh_c3_Low /// + Dhe_mcs_L1 Dhe_pcs_L1 /// + Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + Yptciihs_dv_L1 /// + Dhh_owned_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other /// + [pweight = dimxwt], vce(cluster idperson) + * raw results matrix results = r(table) @@ -177,90 +263,45 @@ putexcel A1 = matrix(nonzero_b'), names nformat(number_d2) * Labelling - +// Need to variable label when add new variable to model. Order matters. +local var_list Dgn Dag Dag_sq /// + Dhhtp_c8_2_L1 Dhhtp_c8_3_L1 Dhhtp_c8_4_L1 Dhhtp_c8_5_L1 Dhhtp_c8_6_L1 Dhhtp_c8_7_L1 Dhhtp_c8_8_L1 /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + Deh_c3_Medium Deh_c3_Low /// + Dhe_mcs_L1 Dhe_pcs_L1 /// + Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + Yptciihs_dv_L1 /// + Dhh_owned_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other /// + Constant + + putexcel A1 = "REGRESSOR" -putexcel A2 = "Dgn" -putexcel A3 = "Dag" -putexcel A4 = "Dag_sq" -putexcel A5 = "Dhhtp_c8_2_L1" -putexcel A6 = "Dhhtp_c8_3_L1" -putexcel A7 = "Dhhtp_c8_4_L1" -putexcel A8 = "Dhhtp_c8_5_L1" -putexcel A9 = "Dhhtp_c8_6_L1" -putexcel A10 = "Dhhtp_c8_7_L1" -putexcel A11 = "Dhhtp_c8_8_L1" -putexcel A12 = "Les_c3_Student_L1" -putexcel A13 = "Les_c3_NotEmployed_L1" -putexcel A14 = "Deh_c3_Medium" -putexcel A15 = "Deh_c3_Low" -putexcel A16 = "Dhe_mcs" -putexcel A17 = "Dhe_pcs" -putexcel A18 = "Ydses_c5_Q2_L1" -putexcel A19 = "Ydses_c5_Q3_L1" -putexcel A20 = "Ydses_c5_Q4_L1" -putexcel A21 = "Ydses_c5_Q5_L1" -putexcel A22 = "Yptciihs_dv_L1" -putexcel A23 = "Dhh_owned_L1" -putexcel A24 = "UKC" -putexcel A25 = "UKD" -putexcel A26 = "UKE" -putexcel A27 = "UKF" -putexcel A28 = "UKG" -putexcel A29 = "UKH" -putexcel A30 = "UKJ" -putexcel A31 = "UKK" -putexcel A32 = "UKL" -putexcel A33 = "UKM" -putexcel A34 = "UKN" -putexcel A35 = "Year_transformed" -putexcel A36 = "Y2020" -putexcel A37 = "Y2021" -putexcel A38 = "Ethn_Asian" -putexcel A39 = "Ethn_Black" -putexcel A40 = "Ethn_Other" -putexcel A41 = "Constant" - putexcel B1 = "COEFFICIENT" -putexcel C1 = "Dgn" -putexcel D1 = "Dag" -putexcel E1 = "Dag_sq" -putexcel F1 = "Dhhtp_c8_2_L1" -putexcel G1 = "Dhhtp_c8_3_L1" -putexcel H1 = "Dhhtp_c8_4_L1" -putexcel I1 = "Dhhtp_c8_5_L1" -putexcel J1 = "Dhhtp_c8_6_L1" -putexcel K1 = "Dhhtp_c8_7_L1" -putexcel L1 = "Dhhtp_c8_8_L1" -putexcel M1 = "Les_c3_Student_L1" -putexcel N1 = "Les_c3_NotEmployed_L1" -putexcel O1 = "Deh_c3_Medium" -putexcel P1 = "Deh_c3_Low" -putexcel Q1 = "Dhe_mcs" -putexcel R1 = "Dhe_pcs" -putexcel S1 = "Ydses_c5_Q2_L1" -putexcel T1 = "Ydses_c5_Q3_L1" -putexcel U1 = "Ydses_c5_Q4_L1" -putexcel V1 = "Ydses_c5_Q5_L1" -putexcel W1 = "Yptciihs_dv_L1" -putexcel X1 = "Dhh_owned_L1" -putexcel Y1 = "UKC" -putexcel Z1 = "UKD" -putexcel AA1 = "UKE" -putexcel AB1 = "UKF" -putexcel AC1 = "UKG" -putexcel AD1 = "UKH" -putexcel AE1 = "UKJ" -putexcel AF1 = "UKK" -putexcel AG1 = "UKL" -putexcel AH1 = "UKM" -putexcel AI1 = "UKN" -putexcel AJ1 = "Year_transformed" -putexcel AK1 = "Y2020" -putexcel AL1 = "Y2021" -putexcel AM1 = "Ethn_Asian" -putexcel AN1 = "Ethn_Black" -putexcel AO1 = "Ethn_Other" -putexcel AP1 = "Constant" + +local i = 1 +foreach var in `var_list' { + local ++i + + putexcel A`i' = "`var'" + +} + +local i = 2 +foreach var in `var_list' { + local ++i + + if `i' <= 26 { + local letter = char(64 + `i') // Convert 1=A, 2=B, ..., 26=Z + putexcel `letter'1 = "`var'" + } + else { + local first = char(64 + int((`i' - 1) / 26)) // First letter: A-Z + local second = char(65 + mod((`i' - 1), 26)) // Second letter: A-Z + putexcel `first'`second'1 = "`var'" // Correctly places AA-ZZ + } +} * Goodness of fit diff --git a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do b/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do index 9a852ab65..9c37f0f22 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do +++ b/input/InitialPopulations/compile/RegressionEstimates/reg_leaveParentalHome.do @@ -41,7 +41,7 @@ putexcel set "$dir_work/reg_leaveParentalHome", sheet("Info") replace putexcel A1 = "Description:" putexcel B1 = "Model parameters governing leaving parental home" putexcel A2 = "Authors: Patryk Bronka, Justin van de Ven, Daria Popova" -putexcel A3 = "Last edit: 1 July 2025 DP" +putexcel A3 = "Last edit: 4 Nov 2025 DP" putexcel A4 = "Process:", bold putexcel B4 = "Description:", bold @@ -49,23 +49,26 @@ putexcel A5 = "P1a" putexcel B5 = "Probit regression estimates for leaving the parental home - 18+, not in intitial education spell, living with parents in t-1" putexcel A10 = "Notes:", bold -putexcel B10 = "Added: ethnicity-4 cat (dot); covid dummies (y2020 y2021); not partnered condition (dcpst != 1) to be consistent with the simulation" +putexcel B10 = "Added: ethnicity-4 cat (dot); covid dummies (y2020 y2021)" +putexcel B11 = "DV is synchronised with the adult child definition" putexcel set "$dir_work/reg_leaveParentalHome", sheet("Gof") modify putexcel A1 = "Goodness of fit", bold -************************************ -* Process P1a: Leave Parental Home * -************************************ - +******************************************************************************** +* Process P1a: Leave Parental Home +******************************************************************************** * Process P1a: Probability of leaving the parental home. -* Sample: All respondents living with a parent in t-1, aged 18+, not in initial +* Sample: All respondents adult child in t-1 and not currently in initial * education spell -* DV: Left parental home dummy of those who lived with parents in t-1 -* Note: Added not partnered condition as well to be consistent with the simulation -fre dlftphm if (ded == 0 & dag >= 18 & dcpst != 1) //3.65% - +* DV: Observed transitioning from adult child to non-adult child + +xtset idperson swv +//fre dlftphm if (ded == 0 & dag >= 18 & dcpst != 1) //3.65% +fre dlftphm if (ded == 0 & dag >= 18 ) +tab2 stm dlftphm if (ded == 0 & dag >= 18), r + /*///////////////////////////////////////////////////////////////////////////////////////////////// //check weights ////////////////////////////////////////////////////////////////////////////////// probit dlftphm i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 ib8.drgn1 stm y2020 y2021 i.dot /// @@ -84,9 +87,13 @@ erase "${weight_checks}/weight_comparison_P1a.txt" //////////////////////////////////////////////////////////////////////////////////////////////////// */ -probit dlftphm i.dgn dag dagsq ib1.deh_c3 li.les_c3 li.ydses_c5 ib8.drgn1 stm y2020 y2021 i.dot /// - if (ded==0 & dag>=18 & l.dlftphm==0 & dcpst != 1) [pweight=dimxwt], vce(robust) - +probit dlftphm Dgn Dag Dag_sq Deh_c3_Medium Deh_c3_Low /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other /// + if (ded == 0 & dag >= 18 /*& dagpns!=1 & les_c4!=4*/ ) [pw = dimxwt], vce(robust) + * save raw results matrix results = r(table) @@ -145,98 +152,76 @@ putexcel C2 = matrix(var) restore -* Store estimated coefficients +* Store results in Excel -// Initialize a counter for non-zero coefficients -local non_zero_count = 0 -//local names : colnames b - -// Loop through each element in `b` to count non-zero coefficients -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - local non_zero_count = `non_zero_count' + 1 - } -} +* Store estimates +matrix b = e(b) +matrix V = e(V) -// Create a new row vector to hold only non-zero coefficients -matrix nonzero_b = J(1, `non_zero_count', .) +mata: + // Call matrices into mata + V = st_matrix("V") + b = st_matrix("b") -// Populate nonzero_b with non-zero coefficients from b -local index = 1 -forvalues i = 1/`no_vars' { - if (b[1, `i'] != 0) { - matrix nonzero_b[1, `index'] = b[1, `i'] - local index = `index' + 1 - } -} + // Find which coefficients are nonzero + keep = (b :!= 0) + + // Eliminate zeros + b_trimmed = select(b, keep) + V_trimmed = select(V, keep) + V_trimmed = select(V_trimmed', keep)' + + // Inspection + b_trimmed + V_trimmed + + // Return to Stata + st_matrix("b_trimmed", b_trimmed') + st_matrix("V_trimmed", V_trimmed) + st_matrix("nonzero_b_flag", keep) +end +* Export into Excel putexcel set "$dir_results/reg_leaveParentalHome", sheet("UK_P1a") modify -putexcel A1 = matrix(nonzero_b'), names //nformat(number_d2) +putexcel B2 = matrix(b_trimmed) +putexcel C2 = matrix(V_trimmed) + +* Labelling +// Need to variable label when add new variable to model. Order matters. +local var_list Dgn Dag Dag_sq /// + Deh_c3_Medium Deh_c3_Low /// + Les_c3_Student_L1 Les_c3_NotEmployed_L1 /// + Ydses_c5_Q2_L1 Ydses_c5_Q3_L1 Ydses_c5_Q4_L1 Ydses_c5_Q5_L1 /// + UKC UKD UKE UKF UKG UKH UKJ UKK UKL UKM UKN /// + Year_transformed Y2020 Y2021 Ethn_Asian Ethn_Black Ethn_Other /// + Constant -* Labeling - putexcel A1 = "REGRESSOR" -putexcel A2 = "Dgn" -putexcel A3 = "Dag" -putexcel A4 = "Dag_sq" -putexcel A5 = "Deh_c3_Medium" -putexcel A6 = "Deh_c3_Low" -putexcel A7 = "Les_c3_Student_L1" -putexcel A8 = "Les_c3_NotEmployed_L1" -putexcel A9 = "Ydses_c5_Q2_L1" -putexcel A10 = "Ydses_c5_Q3_L1" -putexcel A11 = "Ydses_c5_Q4_L1" -putexcel A12 = "Ydses_c5_Q5_L1" -putexcel A13 = "UKC" -putexcel A14 = "UKD" -putexcel A15 = "UKE" -putexcel A16 = "UKF" -putexcel A17 = "UKG" -putexcel A18 = "UKH" -putexcel A19 = "UKJ" -putexcel A20 = "UKK" -putexcel A21 = "UKL" -putexcel A22 = "UKM" -putexcel A23 = "UKN" -putexcel A24 = "Year_transformed" -putexcel A25 = "Y2020" -putexcel A26 = "Y2021" -putexcel A27 = "Ethn_Asian" -putexcel A28 = "Ethn_Black" -putexcel A29 = "Ethn_Other" -putexcel A30 = "Constant" - putexcel B1 = "COEFFICIENT" -putexcel C1 = "Dgn" -putexcel D1 = "Dag" -putexcel E1 = "Dag_sq" -putexcel F1 = "Deh_c3_Medium" -putexcel G1 = "Deh_c3_Low" -putexcel H1 = "Les_c3_Student_L1" -putexcel I1 = "Les_c3_NotEmployed_L1" -putexcel J1 = "Ydses_c5_Q2_L1" -putexcel K1 = "Ydses_c5_Q3_L1" -putexcel L1 = "Ydses_c5_Q4_L1" -putexcel M1 = "Ydses_c5_Q5_L1" -putexcel N1 = "UKC" -putexcel O1 = "UKD" -putexcel P1 = "UKE" -putexcel Q1 = "UKF" -putexcel R1 = "UKG" -putexcel S1 = "UKH" -putexcel T1 = "UKJ" -putexcel U1 = "UKK" -putexcel V1 = "UKL" -putexcel W1 = "UKM" -putexcel X1 = "UKN" -putexcel Y1 = "Year_transformed" -putexcel Z1 = "Y2020" -putexcel AA1 = "Y2021" -putexcel AB1 = "Ethn_Asian" -putexcel AC1 = "Ethn_Black" -putexcel AD1 = "Ethn_Other" -putexcel AE1 = "Constant" + +local i = 1 +foreach var in `var_list' { + local ++i + + putexcel A`i' = "`var'" + +} + +local i = 2 +foreach var in `var_list' { + local ++i + + if `i' <= 26 { + local letter = char(64 + `i') // Convert 1=A, 2=B, ..., 26=Z + putexcel `letter'1 = "`var'" + } + else { + local first = char(64 + int((`i' - 1) / 26)) // First letter: A-Z + local second = char(65 + mod((`i' - 1), 26)) // Second letter: A-Z + putexcel `first'`second'1 = "`var'" // Correctly places AA-ZZ + } +} * Goodness of fit diff --git a/input/InitialPopulations/compile/RegressionEstimates/variable_update.do b/input/InitialPopulations/compile/RegressionEstimates/variable_update.do index 84ceb66f4..e10372b10 100644 --- a/input/InitialPopulations/compile/RegressionEstimates/variable_update.do +++ b/input/InitialPopulations/compile/RegressionEstimates/variable_update.do @@ -49,9 +49,18 @@ replace dhhtp_c8 = 5 if dhhtp_c4 == 2 & lessp_c3 == 2 replace dhhtp_c8 = 6 if dhhtp_c4 == 2 & lessp_c3 == 3 replace dhhtp_c8 = 7 if dhhtp_c4 == 3 replace dhhtp_c8 = 8 if dhhtp_c4 == 4 -cap label define dhhtp_c8 1 "Couple with no children, spouse employed" 2 "Couple with no children, spouse student" 3 "Couple with no children, spouse not employed" 4 "Couple with children, spouse employed" 5 "Couple with children, spouse student" 6 "Couple with children, spouse not employed" 7 "Single with no children" 8 "Single with children" +cap label define dhhtp_c8 1 "Couple with no children, spouse employed" /// +2 "Couple with no children, spouse student" /// +3 "Couple with no children, spouse not employed" /// +4 "Couple with children, spouse employed" /// +5 "Couple with children, spouse student" /// +6 "Couple with children, spouse not employed" /// +7 "Single with no children" /// +8 "Single with children" label values dhhtp_c8 dhhtp_c8 +tab dhhtp_c8, gen(Dhhtp_c8_) + // Squared income variable cap cap gen ypnbihs_dv_sq = ypnbihs_dv^2 label variable ypnbihs_dv_sq "Personal Non-benefit Gross Income Squared" @@ -89,6 +98,13 @@ cap gen l_dhe_pcs = dhe_pcs[_n-1] if idperson == idperson[_n-1] & swv == swv[_n- cap gen l_dhe_mcs = dhe_mcs[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 cap gen l_dlltsd = dlltsd[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 cap gen l_dlltsd01 = dlltsd01[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_dnc = dnc[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_dnc02 = dnc02[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_dcpst = dcpst[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_dhhtp_c8 = dhhtp_c8[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_dhh_owned = dhh_owned[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 +cap gen l_yptciihs_dv = yptciihs_dv[_n-1] if idperson == idperson[_n-1] & swv == swv[_n-1] + 1 + // Fill in missing lags using current values at age 16 gsort +idperson -stm @@ -291,12 +307,25 @@ rename L_Dhhtp_c4_2 Dhhtp_c4_CoupleChildren_L1 rename L_Dhhtp_c4_3 Dhhtp_c4_SingleNoChildren_L1 rename L_Dhhtp_c4_4 Dhhtp_c4_SingleChildren_L1 +tab l_dhhtp_c8, gen(L_Dhhtp_c8_) +forvalues i=1/8 { +rename L_Dhhtp_c8_`i' Dhhtp_c8_`i'_L1 +} + tab dot, gen(dot_) rename dot_1 Ethn_White rename dot_2 Ethn_Asian rename dot_3 Ethn_Black rename dot_4 Ethn_Other +tab dcpst, gen(Dcpst_) +rename Dcpst_1 Dcpst_Partnered +rename Dcpst_2 Dcpst_Single + +tab l_dcpst, gen(L_Dcpst_) +rename L_Dcpst_1 Dcpst_Partnered_L1 +rename L_Dcpst_2 Dcpst_Single_L1 + cap gen Year_transformed = stm @@ -321,5 +350,20 @@ cap gen Dlltsd01 = dlltsd01 cap gen Dlltsd_L1 = l_dlltsd cap gen Dlltsd01_L1 = l_dlltsd01 +cap gen FertilityRate = dukfr + +cap gen Dnc = dnc + +cap gen Dnc02 = dnc02 + +rename l_dnc Dnc_L1 + +rename l_dnc02 Dnc02_L1 + +gen Ypnbihs_dv = ypnbihs_dv +gen Yptciihs_dv = yptciihs_dv +gen Yptciihs_dv_L1 = l_yptciihs_dv +gen Dhh_owned = dhh_owned +gen Dhh_owned_L1 = l_dhh_owned diff --git a/input/InitialPopulations/compile/calculate_statistics.do b/input/InitialPopulations/compile/calculate_statistics.do deleted file mode 100644 index 485b376ee..000000000 --- a/input/InitialPopulations/compile/calculate_statistics.do +++ /dev/null @@ -1,844 +0,0 @@ -/**********************************************************************/ - -cd "C:\Users\Patryk\Dropbox\EUROMODFiles\JAS-mine\LABSim\Validation" - -tempfile temp - -******************************************************************************** -*Students by Age -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 14 -replace ageGroup = 1 if dag >= 15 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 24 -replace ageGroup = 3 if dag >= 25 & dag <= 29 -replace ageGroup = 4 if dag >= 30 & dag <= 34 -replace ageGroup = 5 if dag >= 35 & dag <= 39 -replace ageGroup = 6 if dag >= 40 & dag <= 59 -replace ageGroup = 7 if dag >= 60 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_14" /// - 1 "ageGroup_15_19" /// - 2 "ageGroup_20_24" /// - 3 "ageGroup_25_29" /// - 4 "ageGroup_30_34" /// - 5 "ageGroup_35_39" /// - 6 "ageGroup_40_59" /// - 7 "ageGroup_60_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen student = (les_c3 == 2) -cap drop _* - -preserve -collapse (mean) mean=student [aweight=dwt], by(stm) -rename mean ageGroup_All -save `temp', replace -restore - -collapse (mean) mean=student [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide mean, i(stm) j(ageGroup) - -rename mean0 ageGroup_0_14 -rename mean1 ageGroup_15_19 -rename mean2 ageGroup_20_24 -rename mean3 ageGroup_25_29 -rename mean4 ageGroup_30_34 -rename mean5 ageGroup_35_39 -rename mean6 ageGroup_40_59 -rename mean7 ageGroup_60_79 -rename mean8 ageGroup_80_100 - -merge 1:1 stm using `temp', nogen - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_studentsByAge") firstrow(variables) replace - -******************************************************************************** -*Students by Region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -*Define regions -*Regions defined in the drgn1 variable: -* ITC("Nord Ovest", 1), //Nord Ovest 1 -* ITF("Sud", 4), //Sud 4 -* ITG("Isole", 5), //Isole 5 -* ITH("Nord Est", 2), //Nord Est (formerly ITD) 2 -* ITI("Centro", 3), //Centro (formerly ITE) 3 - - -la def drgn1_lb /// - 1 "region_ITC" /// - 2 "region_ITH" /// - 3 "region_ITI" /// - 4 "region_ITF" /// - 5 "region_ITG" /// - -la val drgn1 drgn1_lb - -gen student = (les_c3 == 2) -cap drop _* - -preserve -collapse (mean) mean=student [aweight=dwt], by(stm) -rename mean region_All -save `temp', replace -restore - -collapse (mean) mean=student [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide mean, i(stm) j(drgn1) - -rename mean1 region_ITC -rename mean2 region_ITH -rename mean3 region_ITI -rename mean4 region_ITF -rename mean5 region_ITG - -merge 1:1 stm using `temp', nogen - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_studentsByRegion", replace) firstrow(variables) - -******************************************************************************** -*Education level over 17 years old (excluding students) -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - - - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c3 == 2) -cap drop _* - -drop if student == 1 -drop if dag < 18 - - -collapse (mean) mean1=educ_high mean2=educ_med mean3=educ_low [aweight=dwt], by(stm) - -rename mean1 educ_high -rename mean2 educ_med -rename mean3 educ_low - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_educationLevel", replace) firstrow(variables) - -******************************************************************************** -*Activity status -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - - -la def les_c4_lb /// - 1 "Employed" /// - 2 "Student" /// - 3 "Not employed" /// - 4 "Retired" - - -la val les_c4 les_c4_lb - -gen as_employed = (les_c4 == 1) -gen as_student = (les_c4 == 2) -gen as_notemployedretired = (les_c4 == 3 | les_c4 == 4) -*gen as_retired = (les_c4 == 4) - -cap drop _* - -collapse (mean) as_* [aweight=dwt], by(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_activityStatus", replace) firstrow(variables) - -******************************************************************************** -*Education level by age group -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c3 == 2) -cap drop _* - -drop if student == 1 -drop if dag < 18 - - -collapse (mean) educ_high = educ_high educ_med=educ_med educ_low=educ_low [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide educ*, i(stm) j(ageGroup) - -foreach var in educ_high educ_med educ_low { -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_educationLevelByAge", replace) firstrow(variables) - -******************************************************************************** -*Education level by region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def drgn1_lb /// - 1 "region_ITC" /// - 2 "region_ITH" /// - 3 "region_ITI" /// - 4 "region_ITF" /// - 5 "region_ITG" /// - -la val drgn1 drgn1_lb - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c4 == 2) -cap drop _* - -*drop if student == 1 -*drop if dag < 18 - - -collapse (mean) educ_high = educ_high educ_med=educ_med educ_low=educ_low [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide educ*, i(stm) j(drgn1) - -foreach var in educ_high educ_med educ_low { -rename `var'1 `var'_ITC -rename `var'2 `var'_ITH -rename `var'3 `var'_ITI -rename `var'4 `var'_ITF -rename `var'5 `var'_ITG -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_educationLevelByRegion", replace) firstrow(variables) - -******************************************************************************** -*BenefitUnit couple occupancy by region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def drgn1_lb /// - 1 "region_ITC" /// - 2 "region_ITH" /// - 3 "region_ITI" /// - 4 "region_ITF" /// - 5 "region_ITG" /// - -la val drgn1 drgn1_lb - -recode dhhtp_c4 (1/2 = 1) (3/4 = 0), gen(partnered) - -duplicates drop stm idbenefitunit partnered, force - -preserve -collapse (mean) partnered [aweight=dwt], by(stm) -rename partnered partnered_All -save `temp', replace -restore - -collapse (mean) partnered [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide partnered, i(stm) j(drgn1) - -foreach var in partnered { -rename `var'1 `var'_ITC -rename `var'2 `var'_ITH -rename `var'3 `var'_ITI -rename `var'4 `var'_ITF -rename `var'5 `var'_ITG -} - -merge 1:1 stm using `temp', nogen -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_partneredBUShareByRegion", replace) firstrow(variables) - -******************************************************************************** -*Disability by gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - - -collapse (mean) dlltsd [aweight=dwt], by(dgn stm) -drop if missing(dgn) -reshape wide dlltsd*, i(stm) j(dgn) - -foreach var in dlltsd { -rename `var'0 `var'_female -rename `var'1 `var'_male -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_disabledByGender", replace) firstrow(variables) - -******************************************************************************** -*Disability by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 49 -replace ageGroup = 1 if dag >= 50 & dag <= 74 -replace ageGroup = 2 if dag >= 75 & dag <= 100 - -la def ageGrouplb /// - 0 "ageGroup_0_49" /// - 1 "ageGroup_50_74" /// - 2 "ageGroup_75_100" - -la val ageGroup ageGrouplb - -gen disabled_female = (dlltsd == 1) if dgn == 0 -gen disabled_male = (dlltsd == 1) if dgn == 1 - -collapse (mean) disabled_female disabled_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide disabled*, i(stm) j(ageGroup) - -foreach var in disabled_female disabled_male { -rename `var'0 `var'_0_49 -rename `var'1 `var'_50_74 -rename `var'2 `var'_75_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_disabledByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Health by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 49 -replace ageGroup = 1 if dag >= 50 & dag <= 74 -replace ageGroup = 2 if dag >= 75 & dag <= 100 - -la def ageGrouplb /// - 0 "ageGroup_0_49" /// - 1 "ageGroup_50_74" /// - 2 "ageGroup_75_100" - -la val ageGroup ageGrouplb - -gen health_female = dhe if dgn == 0 -gen health_male = dhe if dgn == 1 - -collapse (mean) health_female health_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide health*, i(stm) j(ageGroup) - -foreach var in health_female health_male { -rename `var'0 `var'_0_49 -rename `var'1 `var'_50_74 -rename `var'2 `var'_75_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_healthByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Employment rate by gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -keep if dag >= 18 & dag <= 64 - -*TODO: students in the denominator? Remove if so and check with simulation. Retired? - -*Employed: les_c4 == 1 == EmployedOrSelfEmployed -gen employed = (les_c4 == 1) -*replace employed = 1 if yplgrs_dv > 0 & !missing(yplgrs_dv) - - -collapse (mean) employed [aweight=dwt], by(dgn stm) -drop if missing(dgn) -reshape wide employed, i(stm) j(dgn) - -foreach var in employed { -rename `var'0 `var'_Female -rename `var'1 `var'_Male -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_employmentByGender", replace) firstrow(variables) - -******************************************************************************** -*Employment by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - - -/* -gen ageGroup = . -replace ageGroup = 2 if dag >= 18 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 64 - -la def ageGrouplb2 /// - 2 "ageGroup_18_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_64" /// - -la val ageGroup ageGrouplb2 -*/ - -gen employed_female = (les_c4 == 1) if dgn == 0 -gen employed_male = (les_c4 == 1) if dgn == 1 - -collapse (mean) employed_female employed_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide employed*, i(stm) j(ageGroup) - - -foreach var in employed_female employed_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_employmentByGenderAndAge", replace) firstrow(variables) - -******************************************************************************** -*Employment of females by age of children in the benefit unit -******************************************************************************** - -*These statistics are a bit weird - need to be double checked. - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -gen child_0_5 = (dag <= 5 & !missing(dag)) -gen child_6_18 = (dag <= 18 & dag >= 6 & !missing(dag)) - -bys idbenefitunit: egen max_child_0_5 = max(child_0_5) -bys idbenefitunit: egen max_child_6_18 = max(child_6_18) - -*gen retired = (ypnoab > 0 & dag >= 50 & les_c3 != 1) -gen emp_with_child_0_5 = (les_c4 == 1) if dgn == 0 & max_child_0_5 == 1 & dag >= 20 & dag <= 65 -gen emp_with_child_6_18 = (les_c4 == 1) if dgn == 0 & max_child_6_18 == 1 & dag >= 20 & dag <= 65 -gen emp_without_child = (les_c4 == 1) if dgn == 0 & max_child_6_18 == 0 & max_child_0_5 == 0 & dag >= 20 & dag <= 65 - -cap drop max* child* - -collapse (mean) emp* [aweight=dwt], by(stm) -drop if missing(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_employmentByMaternity", replace) firstrow(variables) - -******************************************************************************** -*Employment by gender and region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -la def drgn1_lb /// - 1 "region_ITC" /// - 2 "region_ITH" /// - 3 "region_ITI" /// - 4 "region_ITF" /// - 5 "region_ITG" /// - -la val drgn1 drgn1_lb - -keep if dag >= 18 & dag <= 64 - -*gen retired = (ypnoab > 0 & dag >= 50 & les_c3 != 1) => Retired now in les_c4 -gen employed_female = (les_c4 == 1) if dgn == 0 -gen employed_male = (les_c4 == 1) if dgn == 1 - -collapse (mean) employed_female employed_male [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide employed*, i(stm) j(drgn1) - -foreach var in employed_female employed_male { -rename `var'1 `var'_ITC -rename `var'2 `var'_ITH -rename `var'3 `var'_ITI -rename `var'4 `var'_ITF -rename `var'5 `var'_ITG -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_employmentByGenderAndRegion", replace) firstrow(variables) - -******************************************************************************** -*Labour supply by education -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 { -import delimited "C:\Users\Patryk\git\simpaths\input\InitialPopulations\population_initial_IT_`year'.csv", clear - -recode lhw (-9 = .) - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb - -gen labour_supply = lhw * 4.33 * 12 - -qui sum dwt -local mean_dwt = r(mean) -replace dwt = dwt/`mean_dwt' - -collapse (sum) labour_supply [aweight=dwt], by(deh_c3 stm) -drop if missing(deh_c3) | deh_c3 == -9 -reshape wide labour_supply, i(stm) j(deh_c3) - -foreach var in labour_supply { -rename `var'1 `var'_High -rename `var'2 `var'_Medium -rename `var'3 `var'_Low -} - - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics.xlsx, sheet("IT_labourSupplyByEducation", replace) firstrow(variables) - -******************************************************************************** -*Poverty : share of households and share of children at risk of poverty : by region -******************************************************************************** - -/* -Adding validation for poverty would require net values of income to be added to the initial populations, to calculate the equivalised disposable yearly income required for the calculation of the households and children at risk of poverty. - -Would have to check if available for the UK. -*/ \ No newline at end of file diff --git a/input/InitialPopulations/compile/calculate_statistics_UK.do b/input/InitialPopulations/compile/calculate_statistics_UK.do deleted file mode 100644 index dbf70b6b6..000000000 --- a/input/InitialPopulations/compile/calculate_statistics_UK.do +++ /dev/null @@ -1,1822 +0,0 @@ -/**********************************************************************/ - -cd "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations" - -tempfile temp - -******************************************************************************** -*Students by Age -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 14 -replace ageGroup = 1 if dag >= 15 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 24 -replace ageGroup = 3 if dag >= 25 & dag <= 29 -replace ageGroup = 4 if dag >= 30 & dag <= 34 -replace ageGroup = 5 if dag >= 35 & dag <= 39 -replace ageGroup = 6 if dag >= 40 & dag <= 59 -replace ageGroup = 7 if dag >= 60 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_14" /// - 1 "ageGroup_15_19" /// - 2 "ageGroup_20_24" /// - 3 "ageGroup_25_29" /// - 4 "ageGroup_30_34" /// - 5 "ageGroup_35_39" /// - 6 "ageGroup_40_59" /// - 7 "ageGroup_60_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen student = (les_c3 == 2) -cap drop _* - -preserve -collapse (mean) mean=student [aweight=dwt], by(stm) -rename mean ageGroup_All -save `temp', replace -restore - -collapse (mean) mean=student [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide mean, i(stm) j(ageGroup) - -rename mean0 ageGroup_0_14 -rename mean1 ageGroup_15_19 -rename mean2 ageGroup_20_24 -rename mean3 ageGroup_25_29 -rename mean4 ageGroup_30_34 -rename mean5 ageGroup_35_39 -rename mean6 ageGroup_40_59 -rename mean7 ageGroup_60_79 -rename mean8 ageGroup_80_100 - -merge 1:1 stm using `temp', nogen - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_studentsByAge") firstrow(variables) replace - -******************************************************************************** -*Students by Region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -/* -*Define regions -*Regions defined in the drgn1 variable: - UKC("North East", 1), //North East //1 - UKD("North West", 2), //North West //2 - UKE("Yorkshire and the Humber", 4), //Yorkshire and the Humber //4 //Note, there is no 3 in the definition! - UKF("East Midlands", 5), //East Midlands //5 - UKG("West Midlands", 6), //West Midlands //6 - UKH("East of England", 7), //East of England //7 - UKI("London", 8), //London //8 - UKJ("South East", 9), //South East //9 - UKK("South West", 10), //South West //10 - UKL("Wales", 11), //Wales //11 - UKM("Scotland", 12), //Scotland //12 - UKN("Northern Ireland", 13); //Northern Ireland //13? - -*/ - -la def drgn1_lb /// - 1 "region_UKC" /// - 2 "region_UKD" /// - 4 "region_UKE" /// - 5 "region_UKF" /// - 6 "region_UKG" /// - 7 "region_UKH" /// - 8 "region_UKI" /// - 9 "region_UKJ" /// - 10 "region_UKK" /// - 11 "region_UKL" /// - 12 "region_UKM" /// - 13 "region_UKN" /// - -la val drgn1 drgn1_lb - -gen student = (les_c3 == 2) -cap drop _* - -preserve -collapse (mean) mean=student [aweight=dwt], by(stm) -rename mean region_All -save `temp', replace -restore - -collapse (mean) mean=student [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide mean, i(stm) j(drgn1) - -rename mean1 region_UKC -rename mean2 region_UKD -rename mean4 region_UKE -rename mean5 region_UKF -rename mean6 region_UKG -rename mean7 region_UKH -rename mean8 region_UKI -rename mean9 region_UKJ -rename mean10 region_UKK -rename mean11 region_UKL -rename mean12 region_UKM -rename mean13 region_UKN - -merge 1:1 stm using `temp', nogen - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_studentsByRegion", replace) firstrow(variables) - -******************************************************************************** -*Education level over 17 years old (excluding students) -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - - - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c3 == 2) -cap drop _* - -drop if student == 1 -drop if dag < 18 - - -collapse (mean) mean1=educ_high mean2=educ_med mean3=educ_low [aweight=dwt], by(stm) - -rename mean1 educ_high -rename mean2 educ_med -rename mean3 educ_low - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_educationLevel", replace) firstrow(variables) - -******************************************************************************** -*Activity status -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - - -la def les_c4_lb /// - 1 "Employed" /// - 2 "Student" /// - 3 "Not employed" /// - 4 "Retired" - - -la val les_c4 les_c4_lb - -gen as_employed = (les_c4 == 1) -gen as_student = (les_c4 == 2) -gen as_notemployedretired = (les_c4 == 3 | les_c4 == 4) -*gen as_retired = (les_c4 == 4) - -cap drop _* - -collapse (mean) as_* [aweight=dwt], by(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_activityStatus", replace) firstrow(variables) - -******************************************************************************** -*Education level by age group -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c3 == 2) -cap drop _* - -drop if student == 1 -drop if dag < 18 - - -collapse (mean) educ_high = educ_high educ_med=educ_med educ_low=educ_low [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide educ*, i(stm) j(ageGroup) - -foreach var in educ_high educ_med educ_low { -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_educationLevelByAge", replace) firstrow(variables) - -******************************************************************************** -*Education level by region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -la def drgn1_lb /// - 1 "region_UKC" /// - 2 "region_UKD" /// - 4 "region_UKE" /// - 5 "region_UKF" /// - 6 "region_UKG" /// - 7 "region_UKH" /// - 8 "region_UKI" /// - 9 "region_UKJ" /// - 10 "region_UKK" /// - 11 "region_UKL" /// - 12 "region_UKM" /// - 13 "region_UKN" /// - -la val drgn1 drgn1_lb - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - - -la val deh_c3 deh_c3_lb - -gen educ_high = (deh_c3 == 1) -gen educ_med = (deh_c3 == 2) -gen educ_low = (deh_c3 == 3) - -gen student = (les_c4 == 2) -cap drop _* - -*drop if student == 1 -*drop if dag < 18 - - -collapse (mean) educ_high = educ_high educ_med=educ_med educ_low=educ_low [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide educ*, i(stm) j(drgn1) - -foreach var in educ_high educ_med educ_low { -rename `var'1 `var'_UKC -rename `var'2 `var'_UKD -rename `var'4 `var'_UKE -rename `var'5 `var'_UKF -rename `var'6 `var'_UKG -rename `var'7 `var'_UKH -rename `var'8 `var'_UKI -rename `var'9 `var'_UKJ -rename `var'10 `var'_UKK -rename `var'11 `var'_UKL -rename `var'12 `var'_UKM -rename `var'13 `var'_UKN -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_educationLevelByRegion", replace) firstrow(variables) - -******************************************************************************** -*BenefitUnit couple occupancy by region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def drgn1_lb /// - 1 "region_UKC" /// - 2 "region_UKD" /// - 4 "region_UKE" /// - 5 "region_UKF" /// - 6 "region_UKG" /// - 7 "region_UKH" /// - 8 "region_UKI" /// - 9 "region_UKJ" /// - 10 "region_UKK" /// - 11 "region_UKL" /// - 12 "region_UKM" /// - 13 "region_UKN" /// - -la val drgn1 drgn1_lb - -recode dhhtp_c4 (1/2 = 1) (3/4 = 0), gen(partnered) - -duplicates drop stm idbenefitunit partnered, force - -preserve -collapse (mean) partnered [aweight=dwt], by(stm) -rename partnered partnered_All -save `temp', replace -restore - -collapse (mean) partnered [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide partnered, i(stm) j(drgn1) - -foreach var in partnered { -rename `var'1 `var'_UKC -rename `var'2 `var'_UKD -rename `var'4 `var'_UKE -rename `var'5 `var'_UKF -rename `var'6 `var'_UKG -rename `var'7 `var'_UKH -rename `var'8 `var'_UKI -rename `var'9 `var'_UKJ -rename `var'10 `var'_UKK -rename `var'11 `var'_UKL -rename `var'12 `var'_UKM -rename `var'13 `var'_UKN -} - -merge 1:1 stm using `temp', nogen -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_partneredBUShareByRegion", replace) firstrow(variables) - -******************************************************************************** -*Disability by gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -cap drop if dgn == -9 -drop if dag < 16 - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - - -collapse (mean) dlltsd [aweight=dwt], by(dgn stm) -drop if missing(dgn) -reshape wide dlltsd*, i(stm) j(dgn) - -foreach var in dlltsd { -rename `var'0 `var'_female -rename `var'1 `var'_male -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_disabledByGender", replace) firstrow(variables) - -******************************************************************************** -*Disability by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* -drop if dag < 16 - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 49 -replace ageGroup = 1 if dag >= 50 & dag <= 74 -replace ageGroup = 2 if dag >= 75 & dag <= 100 - -la def ageGrouplb /// - 0 "ageGroup_0_49" /// - 1 "ageGroup_50_74" /// - 2 "ageGroup_75_100" - -la val ageGroup ageGrouplb - -gen disabled_female = (dlltsd == 1) if dgn == 0 -gen disabled_male = (dlltsd == 1) if dgn == 1 - -collapse (mean) disabled_female disabled_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide disabled*, i(stm) j(ageGroup) - -foreach var in disabled_female disabled_male { -rename `var'0 `var'_0_49 -rename `var'1 `var'_50_74 -rename `var'2 `var'_75_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_disabledByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Health by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 49 -replace ageGroup = 1 if dag >= 50 & dag <= 74 -replace ageGroup = 2 if dag >= 75 & dag <= 100 - -la def ageGrouplb /// - 0 "ageGroup_0_49" /// - 1 "ageGroup_50_74" /// - 2 "ageGroup_75_100" - -la val ageGroup ageGrouplb - -gen health_female = dhe if dgn == 0 -gen health_male = dhe if dgn == 1 - -collapse (mean) health_female health_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide health*, i(stm) j(ageGroup) - -foreach var in health_female health_male { -rename `var'0 `var'_0_49 -rename `var'1 `var'_50_74 -rename `var'2 `var'_75_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_healthByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Mental health score by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen mental_health_female = dhm if dgn == 0 -gen mental_health_male = dhm if dgn == 1 - -collapse (mean) mental_health_female mental_health_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide mental_health*, i(stm) j(ageGroup) - -foreach var in mental_health_female mental_health_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_mentalHealthByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Psychological distress (caseness) by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -keep if !missing(scghq2_dv) - -gen psych_distress_female = (dhm_ghq == 1) if dgn == 0 -gen psych_distress_male = (dhm_ghq == 1) if dgn == 1 - -collapse (mean) psych_distress_female psych_distress_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide psych_distress*, i(stm) j(ageGroup) - -foreach var in psych_distress_female psych_distress_male { -cap rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_psychDistressByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -*Psychological distress (caseness) by age group and gender, low education -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -keep if deh_c3 == 3 // Low education - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -keep if !missing(scghq2_dv) - -gen psych_distress_female = (dhm_ghq == 1) if dgn == 0 -gen psych_distress_male = (dhm_ghq == 1) if dgn == 1 - -collapse (mean) psych_distress_female psych_distress_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide psych_distress*, i(stm) j(ageGroup) - -foreach var in psych_distress_female psych_distress_male { -cap rename `var'0 `var'_0_9 -cap rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_psychDistressByAgeGroupLowED", replace) firstrow(variables) - -******************************************************************************** -*Psychological distress (caseness) by age group and gender, low education -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -keep if deh_c3 == 2 // Low education - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -keep if !missing(scghq2_dv) - -gen psych_distress_female = (dhm_ghq == 1) if dgn == 0 -gen psych_distress_male = (dhm_ghq == 1) if dgn == 1 - -collapse (mean) psych_distress_female psych_distress_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide psych_distress*, i(stm) j(ageGroup) - -foreach var in psych_distress_female psych_distress_male { -cap rename `var'0 `var'_0_9 -cap rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_psychDistressByAgeGroupMedED", replace) firstrow(variables) - -******************************************************************************** -*Psychological distress (caseness) by age group and gender, high education -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -keep if deh_c3 == 1 // Low education - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -keep if !missing(scghq2_dv) - -gen psych_distress_female = (dhm_ghq == 1) if dgn == 0 -gen psych_distress_male = (dhm_ghq == 1) if dgn == 1 - -collapse (mean) psych_distress_female psych_distress_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide psych_distress*, i(stm) j(ageGroup) - -foreach var in psych_distress_female psych_distress_male { -cap rename `var'0 `var'_0_9 -cap rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_psychDistressByAgeGroupHiED", replace) firstrow(variables) - -******************************************************************************** -*Employment rate by gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -keep if dag >= 18 & dag <= 64 - -*TODO: students in the denominator? Remove if so and check with simulation. Retired? - -*Employed: les_c4 == 1 == EmployedOrSelfEmployed -gen employed = (les_c4 == 1) -*replace employed = 1 if yplgrs_dv > 0 & !missing(yplgrs_dv) - - -collapse (mean) employed [aweight=dwt], by(dgn stm) -drop if missing(dgn) -reshape wide employed, i(stm) j(dgn) - -foreach var in employed { -rename `var'0 `var'_Female -rename `var'1 `var'_Male -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_employmentByGender", replace) firstrow(variables) - -******************************************************************************** -*Employment by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - - -/* -gen ageGroup = . -replace ageGroup = 2 if dag >= 18 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 64 - -la def ageGrouplb2 /// - 2 "ageGroup_18_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_64" /// - -la val ageGroup ageGrouplb2 -*/ - -gen employed_female = (les_c4 == 1) if dgn == 0 -gen employed_male = (les_c4 == 1) if dgn == 1 - -collapse (mean) employed_female employed_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide employed*, i(stm) j(ageGroup) - - -foreach var in employed_female employed_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_employmentByGenderAndAge", replace) firstrow(variables) - -******************************************************************************** -*Employment of females by age of children in the benefit unit -******************************************************************************** - -*These statistics are a bit weird - need to be double checked. - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -gen child_0_5 = (dag <= 5 & !missing(dag)) -gen child_6_18 = (dag <= 18 & dag >= 6 & !missing(dag)) - -bys idbenefitunit: egen max_child_0_5 = max(child_0_5) -bys idbenefitunit: egen max_child_6_18 = max(child_6_18) - -*gen retired = (ypnoab > 0 & dag >= 50 & les_c3 != 1) -gen emp_with_child_0_5 = (les_c4 == 1) if dgn == 0 & max_child_0_5 == 1 & dag >= 20 & dag <= 65 -gen emp_with_child_6_18 = (les_c4 == 1) if dgn == 0 & max_child_6_18 == 1 & dag >= 20 & dag <= 65 -gen emp_without_child = (les_c4 == 1) if dgn == 0 & max_child_6_18 == 0 & max_child_0_5 == 0 & dag >= 20 & dag <= 65 - -cap drop max* child* - -collapse (mean) emp* [aweight=dwt], by(stm) -drop if missing(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_employmentByMaternity", replace) firstrow(variables) - -******************************************************************************** -*Employment by gender and region -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def drgn1_lb /// - 1 "region_UKC" /// - 2 "region_UKD" /// - 4 "region_UKE" /// - 5 "region_UKF" /// - 6 "region_UKG" /// - 7 "region_UKH" /// - 8 "region_UKI" /// - 9 "region_UKJ" /// - 10 "region_UKK" /// - 11 "region_UKL" /// - 12 "region_UKM" /// - 13 "region_UKN" /// - -la val drgn1 drgn1_lb - -keep if dag >= 18 & dag <= 64 - -*gen retired = (ypnoab > 0 & dag >= 50 & les_c3 != 1) => Retired now in les_c4 -gen employed_female = (les_c4 == 1) if dgn == 0 -gen employed_male = (les_c4 == 1) if dgn == 1 - -collapse (mean) employed_female employed_male [aweight=dwt], by(drgn1 stm) -drop if missing(drgn1) -reshape wide employed*, i(stm) j(drgn1) - -foreach var in employed_female employed_male { -rename `var'1 `var'_UKC -rename `var'2 `var'_UKD -rename `var'4 `var'_UKE -rename `var'5 `var'_UKF -rename `var'6 `var'_UKG -rename `var'7 `var'_UKH -rename `var'8 `var'_UKI -rename `var'9 `var'_UKJ -rename `var'10 `var'_UKK -rename `var'11 `var'_UKL -rename `var'12 `var'_UKM -rename `var'13 `var'_UKN -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_employmentByGenderAndRegion", replace) firstrow(variables) - -******************************************************************************** -*Average yearly labour supply by education (for individuals flexible in labour supply) -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -recode lhw (-9 = .) - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb -drop if missing(deh_c3) | deh_c3 == -9 -keep if dag >= 16 & dag <= 75 & les_c4 != 2 & les_c4 != 4 & dlltsd != 1 // Keep those flexible in labour supply - -gen labour_supply = lhw * 4.33 * 12 - -/* -qui sum dwt -local mean_dwt = r(mean) -replace dwt = dwt/`mean_dwt' -*/ - -collapse (mean) labour_supply [aweight=dwt], by(deh_c3 stm) - -reshape wide labour_supply, i(stm) j(deh_c3) - -foreach var in labour_supply { -rename `var'1 `var'_High -rename `var'2 `var'_Medium -rename `var'3 `var'_Low -} - - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_labourSupplyByEducation", replace) firstrow(variables) - -******************************************************************************** -*Homeownership -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - - -cap drop _* - -collapse (mean) dhh_owned [aweight=dwt], by(idbenefitunit stm) -collapse (mean) dhh_owned, by(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_homeownership", replace) firstrow(variables) - -******************************************************************************** -*Gross earnings yearly by education and gender (for employed persons) -******************************************************************************** -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb - -keep if les_c3 == 1 -drop if missing(deh_c3) | deh_c3 == -9 - -*Monetary values in the estimation sample are in 2015 values. Uprate by the CPI. -gen CPI = . -replace CPI = 0.879 if stm == 2009 -replace CPI = 0.901 if stm == 2010 -replace CPI = 0.936 if stm == 2011 -replace CPI = 0.96 if stm == 2012 -replace CPI = 0.982 if stm == 2013 -replace CPI = 0.996 if stm == 2014 -replace CPI = 1 if stm == 2015 -replace CPI = 1.01 if stm == 2016 -replace CPI = 1.036 if stm == 2017 -replace CPI = 1.06 if stm == 2018 -replace CPI = 1.078 if stm == 2019 -replace CPI = 1.089 if stm == 2020 -replace CPI = 1.116 if stm == 2021 -replace CPI = 1.205 if stm == 2022 -replace CPI = 1.286 if stm == 2023 - - -gen grossearnings = sinh(yplgrs_dv)*12*CPI -gen hourlywage = sinh(yplgrs_dv)*CPI/(lhw*4.33) -drop if hourlywage <= 1 | hourlywage >= 1000 -drop if grossearnings <= 50 | grossearnings >= 1000000 -gen grossearnings_female = grossearnings if dgn == 0 -gen grossearnings_male = grossearnings if dgn == 1 - -collapse (mean) grossearnings_male grossearnings_female [aweight=dwt], by(deh_c3 stm) -reshape wide grossearnings*, i(stm) j(deh_c3) - - -foreach var in grossearnings_female grossearnings_male { -rename `var'1 `var'_dehc3_high -rename `var'2 `var'_dehc3_med -rename `var'3 `var'_dehc3_low -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_grossEarningsByGenderAndEdu", replace) firstrow(variables) - - -******************************************************************************** -*Hourly wages by education and gender (for employed persons) -******************************************************************************** -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -recode lhw (-9 = .) - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb - -drop if missing(deh_c3) | deh_c3 == -9 -keep if les_c3 == 1 - - -*Monetary values in the estimation sample are in 2015 values. Uprate by the CPI. -gen CPI = . -replace CPI = 0.879 if stm == 2009 -replace CPI = 0.901 if stm == 2010 -replace CPI = 0.936 if stm == 2011 -replace CPI = 0.96 if stm == 2012 -replace CPI = 0.982 if stm == 2013 -replace CPI = 0.996 if stm == 2014 -replace CPI = 1 if stm == 2015 -replace CPI = 1.01 if stm == 2016 -replace CPI = 1.036 if stm == 2017 -replace CPI = 1.06 if stm == 2018 -replace CPI = 1.078 if stm == 2019 -replace CPI = 1.089 if stm == 2020 -replace CPI = 1.116 if stm == 2021 -replace CPI = 1.205 if stm == 2022 -replace CPI = 1.286 if stm == 2023 - - -gen hourlywage = sinh(yplgrs_dv)*CPI/(lhw*4.33) -drop if hourlywage <= 1 | hourlywage >= 1000 -gen hourlywage_female = hourlywage if dgn == 0 -gen hourlywage_male = hourlywage if dgn == 1 - -collapse (mean) hourlywage_male hourlywage_female [aweight=dwt], by(deh_c3 stm) -reshape wide hourlywage*, i(stm) j(deh_c3) - - -foreach var in hourlywage_female hourlywage_male { -rename `var'1 `var'_dehc3_high -rename `var'2 `var'_dehc3_med -rename `var'3 `var'_dehc3_low -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_hourlywageByGenderAndEdu", replace) firstrow(variables) - -******************************************************************************** -*Hours worked weekly by education and gender (for employed persons) -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -recode lhw (-9 = .) - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb - -keep if les_c3 == 1 - -gen lhw_female = lhw if dgn == 0 -gen lhw_male = lhw if dgn == 1 - -collapse (mean) lhw_male lhw_female [aweight=dwt], by(deh_c3 stm) -drop if missing(deh_c3) | deh_c3 == -9 -reshape wide lhw*, i(stm) j(deh_c3) - - -foreach var in lhw_female lhw_male { -rename `var'1 `var'_dehc3_high -rename `var'2 `var'_dehc3_medium -rename `var'3 `var'_dehc3_low -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_lhwByGenderAndEdu", replace) firstrow(variables) - - -******************************************************************************** -*Hours worked weekly by gender (for employed persons) -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 { -import delimited "C:\Users\Patryk\git\SimPathsFork\input\InitialPopulations - Copy\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -recode lhw (-9 = .) - -la def deh_c3_lb /// - 1 "High" /// - 2 "Medium" /// - 3 "Low" - -la val deh_c3 deh_c3_lb - -drop if missing(deh_c3) | deh_c3 == -9 -keep if les_c3 == 1 - -gen lhw_female = lhw if dgn == 0 -gen lhw_male = lhw if dgn == 1 - -collapse (mean) lhw_male lhw_female [aweight=dwt], by(stm) - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_lhwByGender", replace) firstrow(variables) - - -******************************************************************************** -* MCS Health score by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 { -import delimited "data\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen health_mcs_score_female = dhe_mcs if dgn == 0 -gen health_mcs_score_male = dhe_mcs if dgn == 1 - -collapse (mean) health_mcs_score_female health_mcs_score_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide health_mcs_score*, i(stm) j(ageGroup) - -foreach var in health_mcs_score_female health_mcs_score_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_healthMCSByAgeGroup", replace) firstrow(variables) - -******************************************************************************** -* PCS Health score by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 { -import delimited "data\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -gen ageGroup = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen health_pcs_score_female = dhe_pcs if dgn == 0 -gen health_pcs_score_male = dhe_pcs if dgn == 1 - -collapse (mean) health_pcs_score_female health_pcs_score_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide health_pcs_score*, i(stm) j(ageGroup) - -foreach var in health_pcs_score_female health_pcs_score_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_healthPCSByAgeGroup", replace) firstrow(variables) - - -******************************************************************************** -* Life Satisfaction score by age group and gender -******************************************************************************** - -foreach year in 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 { -import delimited "data\population_initial_UK_`year'.csv", clear - -cap drop _* - -la def dgn_lb /// - 0 "Female" /// - 1 "Male" - -la val dgn dgn_lb - -*Define age groups -`}`}`}Group = . -replace ageGroup = 0 if dag >= 0 & dag <= 9 -replace ageGroup = 1 if dag >= 10 & dag <= 19 -replace ageGroup = 2 if dag >= 20 & dag <= 29 -replace ageGroup = 3 if dag >= 30 & dag <= 39 -replace ageGroup = 4 if dag >= 40 & dag <= 49 -replace ageGroup = 5 if dag >= 50 & dag <= 59 -replace ageGroup = 6 if dag >= 60 & dag <= 69 -replace ageGroup = 7 if dag >= 70 & dag <= 79 -replace ageGroup = 8 if dag >= 80 & dag <= 100 - - -la def ageGrouplb /// - 0 "ageGroup_0_9" /// - 1 "ageGroup_10_19" /// - 2 "ageGroup_20_29" /// - 3 "ageGroup_30_39" /// - 4 "ageGroup_40_49" /// - 5 "ageGroup_50_59" /// - 6 "ageGroup_60_69" /// - 7 "ageGroup_70_79" /// - 8 "ageGroup_80_100" /// - -la val ageGroup ageGrouplb - -gen life_satisfaction_female = dls if dgn == 0 -gen life_satisfaction_male = dls if dgn == 1 - -collapse (mean) life_satisfaction_female life_satisfaction_male [aweight=dwt], by(ageGroup stm) -drop if missing(ageGroup) -reshape wide life_satisfaction*, i(stm) j(ageGroup) - -foreach var in life_satisfaction_female life_satisfaction_male { -rename `var'0 `var'_0_9 -rename `var'1 `var'_10_19 -rename `var'2 `var'_20_29 -rename `var'3 `var'_30_39 -rename `var'4 `var'_40_49 -rename `var'5 `var'_50_59 -rename `var'6 `var'_60_69 -rename `var'7 `var'_70_79 -rename `var'8 `var'_80_100 -} - -rename stm Year - -if `year' == 2011 { -save validation_statistics.dta, replace -} -else { -append using validation_statistics -save validation_statistics.dta, replace -} - -} - -export excel using validation_statistics_UK.xlsx, sheet("UK_lifeSatisfactionByAgeGroup", replace) firstrow(variables) - - -******************************************************************************** -*Poverty : share of households and share of children at risk of poverty : by region -******************************************************************************** - -/* -Adding validation for poverty would require net values of income to be added to the initial populations, to calculate the equivalised disposable yearly income required for the calculation of the households and children at risk of poverty. - -Would have to check if available for the UK. -*/ diff --git a/input/InitialPopulations/compile/do_emphist/00_Master_emphist.do b/input/InitialPopulations/compile/do_emphist/00_Master_emphist.do new file mode 100644 index 000000000..01e9061ac --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/00_Master_emphist.do @@ -0,0 +1,69 @@ +**************************************************************************************************** +* PROJECT: UKMOD update: construct a UKMOD-UKHLS database from UKHLS dataset +* DO-FILE NAME: 00_Master.do +* DESCRIPTION: Main do-file governing the creation of employment history data +* which is required for the generation of some UKMOD variables +* +* PURPOSE: The code reconstructs each respondent’s employment history month by month +* by combining information from the UKHLS and the older BHPS surveys. +* The scripts rebuild employment history using respondents’ reported current activity and interview dates across waves. +* The process links together: +* - the timing of interviews, +* - reported employment and non-employment spells, and +* - transitions between BHPS and UKHLS for legacy sample members. +* The result is a dataset showing, for every person, whether they were employed in each month +* since Jan 2007. +* +* +* The final output liwwh — the total number of months a person has been employed since January 2007. +* This provides a consistent measure of accumulated work experience over the observation window, +* suitable for use in UKMOD and labour-supply model. +* +* +* NOTES: Potentially the timeline could be extended backwards using data from +* the UKHLS Lifetime Employment Status History modules in Waves 1 and 5 +* which collected retrospective work histories from subsets of respondents. +* A sample scripts by Liam Wright are available but outdated: +* https://www.understandingsociety.ac.uk/documentation/mainstage/syntax/user-deposited-syntax/working-life-histories/ +*********************************************************************************************************** +* UKHLS VERSION: UKDA-6931 Special License version 2009-2023 +* AUTHORS: Nick Buck, Ricky Kanabar, Patryk Bronka, Daria Popova +* LAST REVISION: 30 Oct 2025 DP +*********************************************************************************************************** + +************************************************************************ +* Run sub-scripts +************************************************************************ +cd "${dir_data_emphist}" +/* */ +* 01_Intdate.do: set up cross-wave file of interview dates +* ==> needed to link previous wave interview date to each respondent*/ +do "${dir_do_emphist}/01_Intdate.do" + + +* 02_Lwintdat.do: create files of previous wave interview dates for waves c-n +* ==> helps align spells across waves for UKHLS respondents +do "${dir_do_emphist}/02_Lwintdat.do" + +* 03_Bhps_lintdate.do: get last interview date under BHPS +* ==> also creates previous wave interview dates for wave b +do "${dir_do_emphist}/03_Bhps_lintdate.do" + +* 04_Sp0_1_2a.do: create wave-specific spell files for everyone +* ==> each spell = period of employment/non-employment, continuous across months +* ==> Note: This does not pick up all possible variables from employment history, could be modified to pick up additional ones +do "${dir_do_emphist}/04_Sp0_1_2a.do" + +* 05_Newentrant1.do: create spell file based on wave of entry (start of first job) +* ==> captures employment history for new entrants; fills gaps where possible +do "${dir_do_emphist}/05_Newentrant1.do" + +* 06_Aspells1.do: create file containing all spells across waves +* ==> obtains spell start date from previous spell end date +* ==> fills some missing dates; drops cases with insufficient data +do "${dir_do_emphist}/06_Aspells1.do" + +* 07_Empcal1a.do: create monthly employment calendar ==> used to calculate total months in employment per individual +do "${dir_do_emphist}/07_Empcal1a.do" + + diff --git a/input/InitialPopulations/compile/do_emphist/01_Intdate.do b/input/InitialPopulations/compile/do_emphist/01_Intdate.do new file mode 100644 index 000000000..6faacd379 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/01_Intdate.do @@ -0,0 +1,60 @@ +************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS +* FILE: 01_Intdate.do +* +* PURPOSE: +* Creates a *cross-wave file of interview dates* for all waves (a–n) of UKHLS. +* This file is later used in 02_Lwintdate.do to determine the *previous* +* interview date for each respondent. +* +* CONTEXT: +* - Reads xwaveid (cross-wave identifier file) and merges interview date +* variables from each wave’s individual response file (`_indresp`). +* - Excludes proxy interviews (where `ivfio > 1`). +* - Converts interview month/year into a continuous “months since 2009” +* variable (`_mns09`). +* +* OUTPUTS: +* - intdate.dta : combined dataset with interview dates and months-since-2009 +************************************************************************************************* + +cap log close +log using "${dir_log_emphist}/01_Intdate.log", replace + +* The list of waves is defined *globally* in 00_Master.do +local waves $UKHLSwaves // copy global into a local for use here +local n: word count `waves' // number of waves + +******************************************************************** +* MERGE INTERVIEW DATES FROM EACH WAVE +******************************************************************** +use "${dir_ukhls_data}/xwaveid", clear + +forvalues i = 1/`n' { + local w : word `i' of `waves' + + * Merge interview date variables from each wave’s individual response file +merge 1:1 pidp using "${dir_ukhls_data}/`w'_indresp" , /// + keepusing(`w'_intdatd_dv `w'_intdatm_dv `w'_intdaty_dv) + + + * Exclude proxy interviews (ivfio > 1 means proxy or non-response) + replace `w'_intdatd_dv = . if `w'_ivfio > 1 + replace `w'_intdatm_dv = . if `w'_ivfio > 1 + replace `w'_intdaty_dv = . if `w'_ivfio > 1 + + drop _merge + + * Compute months since 2009 for timeline consistency + gen `w'_mns09 = 12 * (`w'_intdaty_dv - 2009) + `w'_intdatm_dv /// + if `w'_intdaty_dv > 0 & `w'_intdatm_dv > 0 + + //tab `w'_mns09 +} + + +save intdate, replace + + +clear +cap log close diff --git a/input/InitialPopulations/compile/do_emphist/02_Lwintdat.do b/input/InitialPopulations/compile/do_emphist/02_Lwintdat.do new file mode 100644 index 000000000..881fba914 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/02_Lwintdat.do @@ -0,0 +1,123 @@ +************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS +* FILE: 02_Lwintdate.do +* +* PURPOSE: +* Creates variables identifying the *previous interview date* for each wave +* (from c to n) based on cross-wave interview date information. +* +* CONTEXT: +* - Uses the cross-wave dataset created in 01_Intdate.do. +* - For each wave, finds the respondent’s most recent previous interview +* (if any) and records its date (year, month, day) and wave number. +* - The first two waves (a, b) have no valid "previous" interview, so +* processing starts from wave c. +* +* OUTPUTS: +* - Variables: _lwint, _lintdaty, _lintdatm, _lintdatd +* - Files: _lint.dta (for each wave c–n) +************************************************************************************************* + +cap log close +log using "${dir_log_emphist}/02_Lwintdate.log", replace + +use intdate, clear + + +************************************************************************************************* +* DEFINE WAVES AND ASSOCIATED VARIABLES +************************************************************************************************* +local waves $UKHLSwaves // copy global into a local for use here + + +* Build lists of corresponding variable names for each wave +local rvars +local yvars +local mvars +local dvars + +foreach w of local waves { + local rvars "`rvars' `w'_ivfio" // fieldwork outcome (1 = full interview) + local yvars "`yvars' `w'_intdaty_dv" // interview year + local mvars "`mvars' `w'_intdatm_dv" // interview month + local dvars "`dvars' `w'_intdatd_dv" // interview day +} + +local nwaves : word count `waves' + + +************************************************************************************************* +* CREATE VARIABLES FOR PREVIOUS INTERVIEW DATES +************************************************************************************************* +forvalues w = 3/`nwaves' { // start from wave c + local curwave : word `w' of `waves' // current wave (e.g., "c") + local prevmax = `w' - 1 // number of prior waves + + di as text "Processing wave `curwave' (previous up to wave `prevmax')" + + * Initialise variables for this wave + gen `curwave'_lwint = 0 // previous wave index number + gen `curwave'_lintdaty = -9 // previous interview year + gen `curwave'_lintdatm = -9 // previous interview month + gen `curwave'_lintdatd = -9 // previous interview day + + * Check all earlier waves to find last valid interview + forvalues i = 1/`prevmax' { + local rw : word `i' of `rvars' + local yw : word `i' of `yvars' + local mw : word `i' of `mvars' + local dw : word `i' of `dvars' + + * Replace if respondent was interviewed in both current and earlier wave + replace `curwave'_lwint = `i' if `curwave'_ivfio==1 & `rw'==1 + replace `curwave'_lintdaty = `yw' if `curwave'_ivfio==1 & `rw'==1 + replace `curwave'_lintdatm = `mw' if `curwave'_ivfio==1 & `rw'==1 + replace `curwave'_lintdatd = `dw' if `curwave'_ivfio==1 & `rw'==1 + } +} + + +************************************************************************************************* +* SAVE INTERMEDIATE DATASET WITH ALL WAVES +************************************************************************************************* +save intdate1, replace +drop if memorig==8 // exclude temporary or non-original household members + + +************************************************************************************************* +* EXPORT WAVE-SPECIFIC FILES +************************************************************************************************* +foreach w of local waves { + if inlist("`w'", "a", "b") continue // skip first two waves (no prior interviews) + + di as text "Saving previous interview data for wave `w'..." + + keep if `w'_ivfio==1 // respondents with valid interview + keep pidp `w'_lwint `w'_lintdaty `w'_lintdatm `w'_lintdatd + + save `w'_lint, replace // e.g., "c_lint.dta", "d_lint.dta", etc. + + use intdate1, clear // reload full dataset for next wave + drop if memorig==8 +} + + + +clear +cap log close + + + + + + + + + + + + + + + + diff --git a/input/InitialPopulations/compile/do_emphist/03_Bhps_lintdate.do b/input/InitialPopulations/compile/do_emphist/03_Bhps_lintdate.do new file mode 100644 index 000000000..1cc1f91d2 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/03_Bhps_lintdate.do @@ -0,0 +1,98 @@ +/************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS & BHPS +* FILE: b_lint.do +* +* PURPOSE: +* Bridges the BHPS and UKHLS panels by identifying the *most recent BHPS interview* +* for each respondent before their first UKHLS interview (wave B). +* +* CONTEXT: +* - The BHPS (1991–2008) sample was incorporated into UKHLS starting in wave B (2009–10). +* - This script links the BHPS interview history to the first UKHLS observation +* so that employment and household histories remain continuous across the two panels. +* - It uses BHPS individual response data (waves L–R) and the combined UKHLS intdate file. +* +* OUTPUTS: +* - bhps_lint.dta : most recent BHPS interview date before UKHLS +* - b_lint.dta : previous interview info for wave B (merged BHPS or wave A) +*************************************************************************************************/ + +cap log close +log using "${dir_log_emphist}/03_Bhps_lintdate.log", replace + +/************************************************************************************************* +* BUILD BHPS LAST INTERVIEW FILE (1991–2008) +*************************************************************************************************/ + +use "${dir_bhps_data}/xwaveid_bh", clear + +gen lwint = 0 +gen lintdatd = 0 +gen lintdatm = 0 +gen lintdaty = 0 + +* Define BHPS waves included (update global once in master file) +local waves $BHPS_waves +local nwaves : word count `waves' + +forvalues i = 1/`nwaves' { + local w : word `i' of `waves' + + * Merge BHPS individual response data for this wave + merge 1:1 pidp using "${dir_bhps_data}/b`w'_indresp", /// + keepusing(b`w'_istrtdatd b`w'_istrtdatm b`w'_istrtdaty b`w'_ivfio) + + * Keep valid (non-proxy) interviews + replace lintdatd = b`w'_istrtdatd if b`w'_ivfio == 1 + replace lintdatm = b`w'_istrtdatm if b`w'_ivfio == 1 + replace lintdaty = b`w'_istrtdaty if b`w'_ivfio == 1 + replace lwint = `i' if b`w'_ivfio == 1 + + drop _merge +} + +keep if lwint > 0 +keep pidp lwint lintdatd lintdatm lintdaty +save bhps_lint, replace + + +/************************************************************************************************* +* LINK BHPS TO UKHLS WAVE B +*************************************************************************************************/ + +use intdate1, clear + +* Merge with BHPS last interview info +merge 1:1 pidp using bhps_lint +drop if _merge == 2 // BHPS-only cases (not in UKHLS) + +* Keep only those with full interviews in wave B +keep if b_ivfio == 1 + +tab memorig + +* Initialise +gen b_lwint = 0 +gen b_lintdaty = -9 +gen b_lintdatm = -9 +gen b_lintdatd = -9 + +* Link to UKHLS wave A (if available) +replace b_lwint = 1 if a_ivfio == 1 +replace b_lintdatd = a_intdatd_dv if a_ivfio == 1 +replace b_lintdatm = a_intdatm_dv if a_ivfio == 1 +replace b_lintdaty = a_intdaty_dv if a_ivfio == 1 + +* Replace with BHPS last interview info where available (merge==3) +replace b_lwint = lwint + 11 if _merge == 3 +replace b_lintdatd = lintdatd if _merge == 3 +replace b_lintdatm = lintdatm if _merge == 3 +replace b_lintdaty = lintdaty if _merge == 3 + +tab b_lwint + +keep pidp b_lwint b_lintdaty b_lintdatm b_lintdatd +save b_lint, replace + +clear +cap log close diff --git a/input/InitialPopulations/compile/do_emphist/04_Sp0_1_2a.do b/input/InitialPopulations/compile/do_emphist/04_Sp0_1_2a.do new file mode 100644 index 000000000..0e76dc342 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/04_Sp0_1_2a.do @@ -0,0 +1,223 @@ +/************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS +* FILE: 04_Sp0_1_2a.do +* +* PURPOSE: +* Constructs employment history “spells” for each UKHLS wave (b–n). +* For each wave, it: +* - Identifies employment/non-employment episodes and transitions +* - Determines start and end dates of each spell +* - Produces three datasets: sp0 (initial), sp1 (main), sp2 (reshaped) +* +* CONTEXT: +* - Uses previous interview information from ${wp}lint.dta +* - Requires individual respondent data from ${original_data}/${wp}indresp.dta +* +* OUTPUTS: +* - ${wp}sp0.dta : initial spell definitions +* - ${wp}sp1.dta : continuation spells +* - ${wp}sp2.dta : reshaped multi-episode structure +*************************************************************************************************/ + +cap log close +log using "${dir_log_emphist}/04_Sp0_1_2a.log", replace + + +local wps ${UKHLS_waves_prefixed} +local wvno ${UKHLS_panel_waves_numbers} + +local n : word count `wps' // number of waves to process + + +/************************************************************************************************* +* LOOP THROUGH EACH WAVE +*************************************************************************************************/ + +forvalues i = 1/`n' { + + global wp : word `i' of `wps' // wave prefix (e.g. b_, c_, etc.) + global wv : word `i' of `wvno' // wave numeric label + + di as text "------------------------------------------------------" + di as text "Processing wave ${wp} (numeric ${wv})..." + di as text "------------------------------------------------------" + + + /************************************************************************************************* + * PREPARE INDRESP DATA AND MERGE WITH PREVIOUS INTERVIEW FILE + *************************************************************************************************/ + + use "${dir_ukhls_data}/${wp}indresp.dta", clear + keep if ${wp}ivfio == 1 // keep full interviews only + drop if ${wp}hhorig == 8 // drop non-original HH members + + merge 1:1 pidp using ${wp}lint + drop _merge + + rename ${wp}* * // remove wave prefix + + keep pidp jbsemp jbstat notempchk - nxtst nxtstelse - cjbatt /// + ff_ivlolw ff_emplw ff_jbsemp ff_jbstat intdatd_dv intdatm_dv intdaty_dv /// + lwint lintdaty lintdatm lintdatd + + + /************************************************************************************************* + * DEFINE EMPLOYMENT FLAGS AND END DATE VARIABLES + *************************************************************************************************/ + + gen aehhas = 1 + replace aehhas = 0 if empchk == -8 & notempchk == -8 + keep if aehhas == 1 + + gen enddatestat = 0 + replace enddatestat = 1 if empchk == 1 + replace enddatestat = 2 if notempchk == 1 & empchk != 1 + replace enddatestat = 3 if empchk == 2 + replace enddatestat = 4 if notempchk == 2 & empchk == -8 + replace enddatestat = 1 if enddatestat == 0 & empchk != -8 + replace enddatestat = 2 if enddatestat == 0 & notempchk != -8 + replace enddatestat = 5 if enddatestat == 1 & (jbsamr == 2 | samejob == 2) + + gen endday = intdatd_dv if enddatestat < 3 + gen endmonth = intdatm_dv if enddatestat < 3 + gen endyear = intdaty_dv if enddatestat < 3 + + replace endday = jbendd if enddatestat == 5 + replace endmonth = jbendm if enddatestat == 5 + replace endyear = jbendy4 if enddatestat == 5 + + replace endday = empstendd if inlist(enddatestat, 3, 4) + replace endmonth = empstendm if inlist(enddatestat, 3, 4) + replace endyear = empstendy4 if inlist(enddatestat, 3, 4) + + save ${wp}sp1a, replace // store intermediate version + + + /************************************************************************************************* + * CREATE SPELL 0 DATASET (INITIAL EPISODE) + *************************************************************************************************/ + + gen startday = lintdatd + gen startmonth = lintdatm + gen startyear = lintdaty + gen stdatestat = 1 + + gen espstat = jbstat + replace espstat = 1 if jbsemp == 2 + replace espstat = 2 if jbsemp == 1 + replace espstat = ff_jbstat if enddatestat == 4 + replace espstat = 1 if enddatestat == 3 & ff_jbsemp == 2 + replace espstat = 2 if enddatestat == 3 & ff_jbsemp == 1 + replace espstat = 2 if enddatestat == 5 & espstat > 2 + + gen wave = ${wv} + gen spell = 0 + + keep pidp wave spell lwint - espstat lintdatd lintdatm lintdaty intdatm_dv intdaty_dv + save ${wp}sp0, replace + + + /************************************************************************************************* + * CREATE SPELL 1 DATASET (CONTINUATION EPISODES) + *************************************************************************************************/ + + use ${wp}sp1a, clear + keep if enddatestat > 2 + + rename endday startday + rename endmonth startmonth + rename endyear startyear + gen stdatestat = 2 + + rename enddatestat edstat1 + + * Determine new end dates + gen enddatestat = 0 + replace enddatestat = 1 if cjob == 1 + replace enddatestat = 3 if cjob == 2 + replace enddatestat = 2 if cstat == 2 & enddatestat == 0 + replace enddatestat = 4 if cstat == 1 & enddatestat == 0 + replace enddatestat = 1 if enddatestat == 0 & jbsemp != -8 + replace enddatestat = 2 if enddatestat == 0 & jbsemp == -8 + + gen endday = intdatd_dv if enddatestat < 3 + gen endmonth = intdatm_dv if enddatestat < 3 + gen endyear = intdaty_dv if enddatestat < 3 + + replace endday = nxtjbendd if enddatestat == 3 + replace endmonth = nxtjbendm if enddatestat == 3 + replace endyear = nxtjbendy4 if enddatestat == 3 + + replace endday = nxtstendd if enddatestat == 4 + replace endmonth = nxtstendm if enddatestat == 4 + replace endyear = nxtstendy4 if enddatestat == 4 + + gen espstat = jbstat if enddatestat == 2 + replace espstat = 1 if jbsemp == 2 & enddatestat == 1 + replace espstat = 2 if jbsemp == 1 & enddatestat == 1 + replace espstat = nxtstelse + 2 if enddatestat == 4 & nxtstelse > 0 + replace espstat = nxtstelse if enddatestat == 4 & nxtstelse > -8 & nxtstelse < 0 + replace espstat = 1 if enddatestat == 3 & nxtjbes == 2 + replace espstat = 2 if enddatestat == 3 & nxtjbes > -8 & nxtjbes < 2 + replace espstat = 2 if enddatestat == 1 & missing(espstat) + + gen wave = ${wv} + gen spell = 1 + + keep pidp wave spell lwint startday - espstat lintdatd lintdatm lintdaty intdatm_dv intdaty_dv + save ${wp}sp1, replace + + + /************************************************************************************************* + * CREATE SPELL 2 DATASET (RESHAPED MULTI-EPISODE STRUCTURE) + *************************************************************************************************/ + + use "${dir_ukhls_data}/${wp}indresp.dta", clear + rename ${wp}* * + keep if ivfio == 1 + drop if hhorig == 8 + + keep pidp nextstat* nextelse* currstat* nextjob* currjob* jobhours* statendd* statendm* statendy4* + + reshape long nextstat nextelse currstat nextjob currjob jobhours statendd statendm statendy4, i(pidp) j(sp2) + drop if nextstat == -8 + + quietly merge m:1 pidp using "${dir_ukhls_data}/${wp}indresp", /// + keepusing(${wp}intdatd_dv ${wp}intdatm_dv ${wp}intdaty_dv) + keep if _merge == 3 + drop _merge + + merge m:1 pidp using ${wp}lint + keep if _merge == 3 + drop _merge + rename ${wp}* * + + gen enddatestat = 0 + replace enddatestat = 1 if currjob == 1 + replace enddatestat = 3 if currjob == 2 + replace enddatestat = 4 if currstat == 1 + replace enddatestat = 2 if currstat > -8 & enddatestat == 0 + + gen endday = intdatd_dv + gen endmonth = intdatm_dv + gen endyear = intdaty_dv + + replace endday = statendd if enddatestat > 2 + replace endmonth = statendm if enddatestat > 2 + replace endyear = statendy4 if enddatestat > 2 + + gen espstat = nextstat + replace espstat = nextelse + 2 if nextelse > 0 + replace espstat = nextelse if nextstat == 2 & nextelse < 0 + replace espstat = 1 if nextjob == 1 + replace espstat = 2 if nextjob > 1 + replace espstat = 2 if nextjob > -8 & nextjob < 0 + + gen spell = sp2 + 1 + gen wave = ${wv} + + keep pidp spell wave endday endmonth endyear enddatestat espstat lintdatd lintdatm lintdaty intdatm_dv intdaty_dv + save ${wp}sp2, replace +} + +cap log close diff --git a/input/InitialPopulations/compile/do_emphist/05_Newentrant1.do b/input/InitialPopulations/compile/do_emphist/05_Newentrant1.do new file mode 100644 index 000000000..6fc5eac90 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/05_Newentrant1.do @@ -0,0 +1,191 @@ +/************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS +* FILE: 05_Newentrant1.do +* +* PURPOSE: +* Constructs “new entrant” employment spells for all available waves (A–latest). +* For each wave, identifies individuals who recently entered employment, +* infers start and end dates, and creates wave-specific spell files. +* +* NOTES: +* Patryk’s comment said that b_jbbgdat{y,m,d} were missing from earlier release data +* and obtained from Graham. It looks like they were added to the new release, +* therefore special treatment of wave B is no longer needed. +*************************************************************************************************/ + +cap log close +log using "${dir_log_emphist}/05_Newentrant1.log", replace + +/****************************************************************************** + * WAVE A: process separately (Nick Buck original logic) + ******************************************************************************/ +di as text "------------------------------------------------------" +di as text "Processing new entrant spells for wave a (numeric 1)" +di as text "------------------------------------------------------" + +capture use "${dir_ukhls_data}/a_indresp.dta", clear + + tab a_jbbgm a_jbsemp + tab a_jbbgy if a_jbbgm > 0 & a_jbsemp > 0 + tab a_jbbgy if a_jbbgm < 0 & a_jbsemp > 0 + tab a_jbhad + drop if a_ivfio==2 + rename a_* * + gen spell=0 + gen wave=1 + gen espstat=jbstat + replace espstat=1 if jbsemp==2 + replace espstat=2 if jbsemp==1 + tab espstat jbsemp + gen endyear=intdaty_dv + gen endmonth=intdatm_dv + gen endday=intdatd_dv + gen startmonth=-9 + gen startyear=-9 + gen startday=-9 + replace startyear=jbbgy if jbsemp > 0 + replace startmonth=jbbgm if jbsemp > 0 + replace startday=jbbgd if jbsemp > 0 + tab jlendm jbhad + replace startyear=jlendy if jbhad==1 + replace startmonth=jlendm if jbhad==1 + replace startday=1 if jbhad==1 + tab jbhad jbsemp + tab jbstat if jbhad==2 + replace startyear=2007 if jbhad==2 + replace startmonth=1 if jbhad==2 + replace startday=1 if jbhad==2 + tab startyear + tab jbstat if startyear < 0 + replace startyear=2007 if startyear < 0 + tab startyear if startmonth < 0 + replace startmonth=1 if startmonth < 0 + tab espstat + tab jbstat + gen ne=1 + keep pidp spell wave espstat endyear endmonth endday startmonth startyear startday intdaty_dv intdatm_dv ne + save a_sp0_ne, replace + + di as text "Saved a_sp0_ne.dta successfully." + + +/****************************************************************************** + * LOOP THROUGH WAVES (b ... n) using master globals + ******************************************************************************/ +local wps ${UKHLS_waves_prefixed} +local wvno ${UKHLS_panel_waves_numbers} + +local n : word count `wps' + +forvalues i = 1/`n' { + local wp : word `i' of `wps' // prefix e.g. b_ + local wn : word `i' of `wvno' // numeric e.g. 2 + + di as text "------------------------------------------------------" + di as text "Processing new entrant spells for wave `wp' (numeric `wn')" + di as text "------------------------------------------------------" + + use "${dir_ukhls_data}/`wp'indresp.dta", clear + + * harmonise variable names (=remove wave prefix) + rename `wp'* * + + /************************************************************************************************* + * CHECK THAT REQUIRED VARIABLES EXIST + * (if some essential vars missing, warn and skip) + *************************************************************************************************/ + local reqvars "pidp ivfio hhorig notempchk empchk jbsemp jbstat intdaty_dv intdatm_dv intdatd_dv jbhad jlendy jlendm jbbgy jbbgm jbbgd" + local missing_vars + + foreach v of local reqvars { + capture confirm variable `v' + if _rc local missing_vars "`missing_vars' `v'" + } + + if "`missing_vars'" != "" { + di as error "WARNING: Missing variables in wave `wp': `missing_vars'" + di as text "Skipping this wave..." + continue + } + + /************************************************************************************************* + * BASIC SUMMARY FOR DIAGNOSTICS + *************************************************************************************************/ + di as text "Variable overview for wave `wp':" + summarize jbsemp jbstat jbhad jbbgy jbbgm jbbgd jlendy jlendm + + /************************************************************************************************* + * FILTER AND PROCESS + *************************************************************************************************/ + drop if ivfio == 2 // exclude proxy interviews + capture confirm variable hhorig + if !_rc { + drop if hhorig == 8 // exclude temporary members (if variable exists) + } + + gen aehhas = 1 + replace aehhas = 0 if notempchk == -8 & empchk == -8 + keep if aehhas == 0 + + * Fill jbbg values if missing + capture confirm variable jbbgdaty + if !_rc { + replace jbbgy=jbbgdaty if jbbgy < 0 & jbbgdaty > 0 & jbbgdaty != . + replace jbbgm=jbbgdatm if jbbgm < 0 & jbbgdatm > 0 & jbbgdatm != . + replace jbbgd=jbbgdatd if jbbgd < 0 & jbbgdatd > 0 & jbbgdatd != . + } + + gen spell = 0 + gen wave = `wn' + + * Define employment status at spell end + gen espstat = jbstat + replace espstat = 1 if jbsemp == 2 + replace espstat = 2 if jbsemp == 1 + + gen endyear = intdaty_dv + gen endmonth = intdatm_dv + gen endday = intdatd_dv + + * Default missing start dates + gen startyear = -9 + gen startmonth = -9 + gen startday = -9 + + * Fill start date from job start info (if employed) + replace startyear = jbbgy if jbsemp > 0 + replace startmonth = jbbgm if jbsemp > 0 + replace startday = jbbgd if jbsemp > 0 + + * For those who had a job previously (jbhad == 1) + replace startyear = jlendy if jbhad == 1 + replace startmonth = jlendm if jbhad == 1 + replace startday = 1 if jbhad == 1 + + * If no job since 2007, assign default early date + replace startyear = 2007 if jbhad == 2 | startyear < 0 + replace startmonth = 1 if jbhad == 2 | startmonth < 0 + replace startday = 1 if jbhad == 2 | startday < 0 + + * Flag for new entrant + gen ne = 1 + + /************************************************************************************************* + * SAVE WAVE-SPECIFIC SPELL FILE + *************************************************************************************************/ + keep pidp spell wave espstat endyear endmonth endday /// + startmonth startyear startday intdaty_dv intdatm_dv ne + + save `wp'sp0_ne, replace + + di as text "Saved `wp'sp0_ne.dta successfully." +} + +/****************************************************************************** + * END + ******************************************************************************/ +di as text "------------------------------------------------------" +di as text "All available waves processed. Check logs for warnings." +di as text "------------------------------------------------------" + +cap log close diff --git a/input/InitialPopulations/compile/do_emphist/06_Aspells1.do b/input/InitialPopulations/compile/do_emphist/06_Aspells1.do new file mode 100644 index 000000000..d1a43ddbb --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/06_Aspells1.do @@ -0,0 +1,160 @@ +/************************************************************************************************* +* PROJECT: UKMOD update – create employment history data from UKHLS +* FILE: 06_Aspells1.do +* +* PURPOSE: +* Combines all wave-specific employment spell files (sp0, sp0_ne, sp1, sp2) +* into a single dataset covering all available waves. +* Derives consistent start and end dates, imputes missing dates, +* and removes invalid or inconsistent spells. +* +* NOTES: +* - BHPS-origin members receive approximate start dates if missing. +*************************************************************************************************/ + +cap log close +log using "${dir_log_emphist}/06_Aspells1.log", replace + +/************************************************************************************************* + * INITIALISE AND APPEND SPELL FILES + *************************************************************************************************/ + +di as text "------------------------------------------------------" +di as text "Combining wave-specific spell files into one dataset" +di as text "------------------------------------------------------" + +* Start with wave a +use a_sp0_ne, clear + +* Loop through later waves using global list from master file +local wps ${UKHLS_waves_prefixed} +local n : word count `wps' + +forvalues i = 1/`n' { + local wp : word `i' of `wps' + di as text "Appending spell files for wave `wp'..." + + capture append using `wp'sp0 + capture append using `wp'sp0_ne + capture append using `wp'sp1 + capture append using `wp'sp2 +} + +di as text "All wave-specific spell files appended successfully." + +/************************************************************************************************* + * MERGE WITH CROSS-WAVE IDENTIFIER + *************************************************************************************************/ + +di as text "Merging with xwaveid file to obtain memorig variable..." +merge m:1 pidp using "${dir_ukhls_data}/xwaveid", keepusing(memorig) +keep if _merge == 3 +drop _merge + +/************************************************************************************************* + * IMPUTE MISSING BHPS INTERVIEW DATES + *************************************************************************************************/ + +di as text "Applying BHPS date fix for legacy members..." +gen bhps = 0 +replace bhps = 1 if memorig > 2 & memorig < 7 + +replace startyear = 2008 if bhps == 1 & startyear == -9 +replace startmonth = 9 if bhps == 1 & startmonth == -9 +replace startday = 1 if bhps == 1 & startday == -9 + +/************************************************************************************************* + * ADJUST START AND END DATES USING INTERVIEW TIMING + *************************************************************************************************/ + +di as text "Adjusting spell dates relative to previous and current interviews..." + +gen valdat1 = 0 +replace valdat1 = 1 if lintdaty > 0 & lintdatm > 0 & endyear > 0 & endmonth > 0 +gen durat1 = 12 * (endyear - lintdaty) + (endmonth - lintdatm) if valdat1 == 1 + +gen valdat2 = 0 +replace valdat2 = 1 if lintdaty > 0 & lintdatm > 0 & startyear > 0 & startmonth > 0 +gen durat2 = 12 * (startyear - lintdaty) + (startmonth - lintdatm) if valdat2 == 1 + +replace endyear = lintdaty if durat1 < 0 +replace endmonth = lintdatm if durat1 < 0 +replace endday = lintdatd if durat1 < 0 +replace startyear = lintdaty if durat2 < 0 +replace startmonth = lintdatm if durat2 < 0 +replace startday = lintdatd if durat2 < 0 + +/************************************************************************************************* + * FILL START DATES FROM PREVIOUS SPELLS + *************************************************************************************************/ + +sort pidp wave spell +replace startyear = endyear[_n-1] if spell > 1 +replace startmonth = endmonth[_n-1] if spell > 1 +replace startday = endday[_n-1] if spell > 1 + +/************************************************************************************************* + * COMPUTE MIDPOINT DATES (FOR MISSING VALUES) + *************************************************************************************************/ + +gen lint00 = 12 * (lintdaty - 2000) + lintdatm if lintdaty > 0 & lintdatm > 0 +gen int00 = 12 * (intdaty_dv - 2000) + intdatm_dv if intdaty_dv > 0 & intdatm_dv > 0 +gen interval = int00 - lint00 +gen mint00 = lint00 + round(interval / 2) +gen midyear = 2000 + int(mint00 / 12) +gen midmonth = mint00 - 12 * int(mint00 / 12) +replace midyear = midyear - 1 if midmonth == 0 +replace midmonth = 12 if midmonth == 0 + +/************************************************************************************************* + * MANUAL IMPUTATIONS FOR PARTIAL MISSING MONTHS + *************************************************************************************************/ + +replace endmonth = 1 if endyear == intdaty_dv & endmonth < 0 +replace endmonth = 12 if endyear == lintdaty & endmonth < 0 +replace endmonth = 6 if endyear > lintdaty & endyear < intdaty_dv & endmonth < 0 + +replace startmonth = endmonth[_n-1] if spell == 1 & startmonth < 0 & startyear > 0 & endmonth[_n-1] > 0 + +gen valstart = (startmonth > 0 & startyear > 0) +gen valend = (endmonth > 0 & endyear > 0) + +replace startmonth = midmonth if valstart == 0 & midmonth != . +replace startyear = midyear if valstart == 0 & midyear != . +replace endmonth = midmonth if valend == 0 & midmonth != . +replace endyear = midyear if valend == 0 & midyear != . + +/************************************************************************************************* + * COMPUTE SPELL DURATION AND VALIDATION + *************************************************************************************************/ + +gen valdat = (startyear > 0 & startmonth > 0 & endyear > 0 & endmonth > 0) +gen durat = 12 * (endyear - startyear) + (endmonth - startmonth) if valdat == 1 + +save allspells1, replace + +/************************************************************************************************* + * FILTER AND CLEAN SPELLS + *************************************************************************************************/ + +use allspells1, clear + +gen d2 = (valdat == 0) +bys pidp: egen nd2 = sum(d2) +tab nd2 + +keep if nd2 == 0 +keep if durat >= 0 +drop if durat == . +drop if espstat < 0 + +save allspells1ok, replace + +/************************************************************************************************* + * END + *************************************************************************************************/ +di as text "------------------------------------------------------" +di as text "All spells processed and saved as allspells1ok.dta" +di as text "------------------------------------------------------" + +cap log close diff --git a/input/InitialPopulations/compile/do_emphist/07_Empcal1a.do b/input/InitialPopulations/compile/do_emphist/07_Empcal1a.do new file mode 100644 index 000000000..f4b7a3ac2 --- /dev/null +++ b/input/InitialPopulations/compile/do_emphist/07_Empcal1a.do @@ -0,0 +1,324 @@ +/************************************************************************************************* +* PROJECT: UKMOD update – create employment calendar and per-wave employment history +* FILE: 07_Empcal1a.do +* +* PURPOSE: +* - Build a monthly employment calendar (2007 onward) from all employment spells. +* - Derive per-wave employment history variables needed for UKMOD. +* - Output one per-wave file (b_emphist, ..., n_emphist) with summary measures. +* +* INPUTS: +* allspells1ok.dta - individual-level employment spells constructed in 06_Aspells1.do +* ${original_data}\_indresp.dta - wave-specific interview response data +* +* OUTPUTS: +* ${data}\_emphist.dta - per-wave employment history summary files +* ${data}\temp_liwwh.dta - long file with all waves appended +*************************************************************************************************/ +local baseyr 2007 //==> All subsequent month indexing is relative to January 2007. + +use allspells1ok, clear // Load the prepared spell data + +*-------------------------------------------------------------* +* Convert start and end dates into months since base year (Jan 2007) +*-------------------------------------------------------------* + +gen stmy07 = 12 * (startyear - `baseyr') + startmonth +gen enmy07 = 12 * (endyear - `baseyr') + endmonth + +*-------------------------------------------------------------* +* Simplified employment status: 2 = employed, 1 = not employed +*-------------------------------------------------------------* +fre espstat +gen emp=1 if espstat > 2 +replace emp=2 if espstat < 3 +tab espstat emp + +*-------------------------------------------------------------* +* Determine full observed month range +*-------------------------------------------------------------* +summ enmy07, meanonly +local maxm = r(max) +local minm = 1 // start from month 1 to avoid negatives + +di as txt "Detected month range: " as res "`minm'–`maxm' (" as res `=`maxm'-`minm'+1' " months total)" + +*-------------------------------------------------------------* +* Generate monthly employment indicators (esp# = status each month) +*-------------------------------------------------------------* +forvalues i = `minm'/`maxm' { + gen esp`i' = 0 + replace esp`i' = emp if `i' >= stmy07 & `i' <= enmy07 +} + +*-------------------------------------------------------------* +* Collapse multiple spells per person (2 overrides 1) +*-------------------------------------------------------------* +forvalues i = `minm'/`maxm' { + bys pidp: egen memp`i' = max(esp`i') +} + +*-------------------------------------------------------------* +* Keep one row per person and retain key variables +*-------------------------------------------------------------* +bys pidp: gen seq = _n +keep if seq == 1 +keep pidp memorig memp`minm'-memp`maxm' + +/*-------------------------------------------------------------* +* Count employed months per financial year (April–March) ==> not sure is this is needed so coded out for now +*-------------------------------------------------------------* +summ memp*, meanonly + +local fy_start = `baseyr' +local fy_end = floor(`baseyr' + (`maxm' + 8) / 12) // +8 ensures FY covers Apr–Mar + +forvalues y = `fy_start'/`fy_end' { + local fy = substr("`y'",3,2) // e.g. 2007 → "07" + local start = (12 * (`y' - `baseyr')) + 4 // April of FY + local end = (12 * (`y' - `baseyr' + 1)) + 3 // March next year + + * Clip to observed range + if `start' < `minm' local start = `minm' + if `end' > `maxm' local end = `maxm' + + * Count months employed (status = 2) + gen efy`fy' = 0 + forvalues i = `start'/`end' { + replace efy`fy' = efy`fy' + 1 if memp`i' == 2 + } + + di as txt "FY" `y' "/" `= `y'+1' " → months " as res "`start'–`end'" +} +*/ + +save empcal1a, replace +/*we end up with a monthy calendar of activity (i.e. employed or not) for each individual from Jan 2007*/ + +/************************************************************************************************* + Derive wave-specific employment history summaries + -------------------------------------------------------------------- + For each wave, merge with interview date, calculate employment duration + up to that interview month (liwwh), and short-term employment indicators: + empmonth - months employed in 6 months before interview + mismonth - months missing in last 6 months + empmonth12 - months employed in 12 months before interview +*************************************************************************************************/ + +local waves $UKHLS_panel_waves +//local waves b + +foreach w of local waves { + + di "---------------------------------------------------------" + di "Processing WAVE `w' ..." + di "---------------------------------------------------------" + + use empcal1a, clear + + merge 1:1 pidp using "${dir_ukhls_data}/`w'_indresp", /// + keepusing(`w'_intdatm_dv `w'_intdaty_dv `w'_ivfio) + keep if _merge == 3 + drop _merge + drop if `w'_ivfio == 2 // exclude proxy interviews + + * Interview month index relative to base year (Jan 2007) + gen inmy07 = 12*(`w'_intdaty_dv - `baseyr') + `w'_intdatm_dv + + + *------------------------------------------ + * Total months employed up to interview + *------------------------------------------ + gen liwwh = 0 + summarize inmy07, meanonly + local maxm = r(max) + forvalues i = 1/`maxm' { + replace liwwh = liwwh + 1 if memp`i' == 2 & `i' <= inmy07 + } + + *------------------------------------------ + * Short-term employment summaries + *------------------------------------------ + summarize inmy07, meanonly + local maxm = r(max) + local start6m = `maxm' - 6 + local start12m = `maxm' - 12 + + gen empmonth = 0 + gen mismonth = 0 + gen empmonth12 = 0 + + forvalues i = `start6m'/`maxm' { + replace empmonth = empmonth + 1 if memp`i' == 2 & inmy07 == `maxm' + replace mismonth = mismonth + 1 if memp`i' == 0 & inmy07 == `maxm' + } + forvalues i = `start12m'/`maxm' { + replace empmonth12 = empmonth12 + 1 if memp`i' == 2 & inmy07 == `maxm' + } + + *------------------------------------------ + * Keep and label key variables + *------------------------------------------ + keep pidp `w'_intdatm_dv `w'_intdaty_dv liwwh empmonth mismonth empmonth12 //efy1 efy2 + label var liwwh "Total months in employment up to current interview" + label var empmonth "Months employed in last 6 months before interview" + label var mismonth "Months missing in last 6 months before interview" + label var empmonth12 "Months employed in last 12 months before interview" + + save `w'_emphist, replace +} + +di as txt "All waves (B–N) processed successfully." + +*------------------------------------------ +* Combine per-wave employment history files +*------------------------------------------ + +* Convert global into a local list and remove first letter (because we start from wave c) +local waves $UKHLS_panel_waves +local first : word 1 of `waves' +local waves : list waves - first + +display "Waves to append: `waves'" + +use b_emphist, clear +gen wave = "b" + +foreach w of local waves { + display "Appending wave `w'..." + append using `w'_emphist, generate(flag_`w') + replace wave = "`w'" if flag_`w' == 1 + drop flag_`w' +} + +* generate wave identifier +gen swv = . + +local letters $UKHLS_panel_waves +local numbers $UKHLS_panel_waves_numbers + +local n : word count `letters' +forval i = 1/`n' { + local wv : word `i' of `letters' + local num : word `i' of `numbers' + replace swv = `num' if wave == "`wv'" +} + +gen idperson=pidp + +save temp_liwwh.dta, replace + +duplicates report swv idperson +bys swv: sum liwwh + +cap log close + +/************************************************************************************** +* clean-up and exit +*************************************************************************************/ + +#delimit ; +local files_to_drop +allspells1.dta +a_sp0_ne.dta +bhps_lint.dta +b_emphist.dta +b_lint.dta +b_sp0.dta +b_sp0_ne.dta +b_sp1.dta +b_sp1a.dta +b_sp2.dta +c_emphist.dta +c_lint.dta +c_sp0.dta +c_sp0_ne.dta +c_sp1.dta +c_sp1a.dta +c_sp2.dta +d_emphist.dta +d_lint.dta +d_sp0.dta +d_sp0_ne.dta +d_sp1.dta +d_sp1a.dta +d_sp2.dta +e_emphist.dta +e_lint.dta +e_sp0.dta +e_sp0_ne.dta +e_sp1.dta +e_sp1a.dta +e_sp2.dta +f_emphist.dta +f_lint.dta +f_sp0.dta +f_sp0_ne.dta +f_sp1.dta +f_sp1a.dta +f_sp2.dta +g_emphist.dta +g_lint.dta +g_sp0.dta +g_sp0_ne.dta +g_sp1.dta +g_sp1a.dta +g_sp2.dta +h_emphist.dta +h_lint.dta +h_sp0.dta +h_sp0_ne.dta +h_sp1.dta +h_sp1a.dta +h_sp2.dta +intdate.dta +intdate1.dta +i_emphist.dta +i_lint.dta +i_sp0.dta +i_sp0_ne.dta +i_sp1.dta +i_sp1a.dta +i_sp2.dta +j_emphist.dta +j_lint.dta +j_sp0.dta +j_sp0_ne.dta +j_sp1.dta +j_sp1a.dta +j_sp2.dta +k_emphist.dta +k_lint.dta +k_sp0.dta +k_sp0_ne.dta +k_sp1.dta +k_sp1a.dta +k_sp2.dta +l_emphist.dta +l_lint.dta +l_sp0.dta +l_sp0_ne.dta +l_sp1.dta +l_sp1a.dta +l_sp2.dta +m_emphist.dta +m_lint.dta +m_sp0.dta +m_sp0_ne.dta +m_sp1.dta +m_sp1a.dta +m_sp2.dta +n_emphist.dta +n_lint.dta +n_sp0.dta +n_sp0_ne.dta +n_sp1.dta +n_sp1a.dta +n_sp2.dta + ; +#delimit cr // cr stands for carriage return + +foreach file of local files_to_drop { + erase "$dir_data_emphist/`file'" +} + diff --git a/input/reg_fertility.xlsx b/input/reg_fertility.xlsx index 27644860a6db2b4f511280d015c22e47c74351ef..d36df9aa3b5b12837265941f7381af13b929c9b9 100644 GIT binary patch literal 19179 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