ernbilen · sansrijal · Jan 27, 2026 · Jan 30, 2026 · Jan 30, 2026 · Jan 30, 2026
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diff --git a/Data 400 Project Proposal 1.pdf b/Data 400 Project Proposal 1.pdf
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+
+# Data 400 Project Proposal 1 
+### Exploring the Relationship Between Remittances and Economic Stability in Nepal
+
+### Research Question: Can remittance inflows help predict changes in household consumption and inflation in Nepal?
+###
+### Motivation
+Nepal is one of the most remittance dependent economies in the world with 25% of its total GDP coming from remittance. Since a large share of household income comes from citizens working abroad, remittances are important for consumption and functioning of households and for stabilizing the economy. Remittances are studied in development economics in Nepal but are usually studied by describing trends rather than making predictions. I want to use this project to examine whether remittance inflows can help predict changes in household consumption and inflation in Nepal.
+### 
+### Data Sources
+For this project I will use publicly available macroeconomic time-series data. Data on remittance inflows can be obtained from the Nepal Rastra Bank and the World Bank datasets. I will source household consumption, gross domestic product (GDP), and inflation data from the World Bank and the International Monetary Fund. All datasets are aggregated, numeric, and reported at monthly or yearly frequencies which makes them suitable for exploratory analysis and predictive modeling.
+####
+### Methodology
+I will begin this project with exploratory data analysis (EDA) to examine trends/relationships between remittance inflows, household consumption, and inflation. This will include summary statistics and visualizations such as time-series plots and correlation matrices. If time allows I will also consider economic shock periods like the 2015 earthquake and the COVID-19 pandemic to observe how these variables behaved during times of stress. For the predictive modelling, I will use models such as linear regression to assess whether remittance inflows can help predict changes in consumption and inflation. 
+
+### Implications for Stakeholders
+The findings from this project would be useful for policymakers and central bank officials in Nepal who are interested in economic forecasting and planning. Development organizations and researchers would benefit from understanding whether remittance flows provide signals of changes in economic conditions. The project highlights the economic role of migrant workers and the importance of external income flows in shaping domestic outcomes.
+###
+### Ethical Considerations
+This project relies on aggregated and publicly available data which does not involve personal or sensitive information. However, the analysis acknowledges societal issues related to labor migration, including household separation and unequal access to migration opportunities. I will avoid causal claims and  state its limitations to ensure the interpretation of predictive results is clear.
+#### 
+### Challenges 
+I may face challenges in aligning data from different sources which are reported at different time intervals or contain missing values. I will clearly document data limitations and modeling assumtions so that results can be interpreted with caution. 
+
+
diff --git a/Data_400_Project_Proposal_1.md (3).html b/Data_400_Project_Proposal_1.md (3).html
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+<!DOCTYPE html><html><head><meta charset="utf-8"><title>Data 400 Project Proposal 1.md</title><style></style></head><body id="preview">
+<h1 class="code-line" data-line-start=1 data-line-end=2 ><a id="Data_400_Project_Proposal_1_1"></a>Data 400 Project Proposal 1</h1>
+<h3 class="code-line" data-line-start=2 data-line-end=3 ><a id="Exploring_the_Relationship_Between_Remittances_and_Economic_Stability_in_Nepal_2"></a>Exploring the Relationship Between Remittances and Economic Stability in Nepal</h3>
+<h3 class="code-line" data-line-start=4 data-line-end=5 ><a id="Research_Question_Can_remittance_inflows_help_predict_changes_in_household_consumption_and_inflation_in_Nepal_4"></a>Research Question: Can remittance inflows help predict changes in household consumption and inflation in Nepal?</h3>
+<h3 class="code-line" data-line-start=5 data-line-end=6 ><a id="_5"></a></h3>
+<h3 class="code-line" data-line-start=6 data-line-end=7 ><a id="Motivation_6"></a>Motivation</h3>
+<p class="has-line-data" data-line-start="7" data-line-end="8">Nepal is one of the most remittance dependent economies in the world with 25% of its total GDP coming from remittance. Since a large share of household income comes from citizens working abroad, remittances are important for consumption and functioning of households and for stabilizing the economy. Remittances are studied in development economics in Nepal but are usually studied by describing trends rather than making predictions. I want to use this project to examine whether remittance inflows can help predict changes in household consumption and inflation in Nepal.</p>
+<h3 class="code-line" data-line-start=8 data-line-end=9 ><a id="_8"></a></h3>
+<h3 class="code-line" data-line-start=9 data-line-end=10 ><a id="Data_Sources_9"></a>Data Sources</h3>
+<p class="has-line-data" data-line-start="10" data-line-end="11">For this project I will use publicly available macroeconomic time-series data. Data on remittance inflows can be obtained from the Nepal Rastra Bank and the World Bank datasets. I will source household consumption, gross domestic product (GDP), and inflation data from the World Bank and the International Monetary Fund. All datasets are aggregated, numeric, and reported at monthly or yearly frequencies which makes them suitable for exploratory analysis and predictive modeling.</p>
+<h4 class="code-line" data-line-start=11 data-line-end=12 ><a id="_11"></a></h4>
+<h3 class="code-line" data-line-start=12 data-line-end=13 ><a id="Methodology_12"></a>Methodology</h3>
+<p class="has-line-data" data-line-start="13" data-line-end="14">I will begin this project with exploratory data analysis (EDA) to examine trends/relationships between remittance inflows, household consumption, and inflation. This will include summary statistics and visualizations such as time-series plots and correlation matrices. If time allows I will also consider economic shock periods like the 2015 earthquake and the COVID-19 pandemic to observe how these variables behaved during times of stress. For the predictive modelling, I will use models such as linear regression to assess whether remittance inflows can help predict changes in consumption and inflation.</p>
+<h3 class="code-line" data-line-start=15 data-line-end=16 ><a id="Implications_for_Stakeholders_15"></a>Implications for Stakeholders</h3>
+<p class="has-line-data" data-line-start="16" data-line-end="17">The findings from this project would be useful for policymakers and central bank officials in Nepal who are interested in economic forecasting and planning. Development organizations and researchers would benefit from understanding whether remittance flows provide signals of changes in economic conditions. The project highlights the economic role of migrant workers and the importance of external income flows in shaping domestic outcomes.</p>
+<h3 class="code-line" data-line-start=17 data-line-end=18 ><a id="_17"></a></h3>
+<h3 class="code-line" data-line-start=18 data-line-end=19 ><a id="Ethical_Considerations_18"></a>Ethical Considerations</h3>
+<p class="has-line-data" data-line-start="19" data-line-end="20">This project relies on aggregated and publicly available data which does not involve personal or sensitive information. However, the analysis acknowledges societal issues related to labor migration, including household separation and unequal access to migration opportunities. I will avoid causal claims and  state its limitations to ensure the interpretation of predictive results is clear.</p>
+<h4 class="code-line" data-line-start=20 data-line-end=21 ><a id="_20"></a></h4>
+<h3 class="code-line" data-line-start=21 data-line-end=22 ><a id="Challenges_21"></a>Challenges</h3>
+<p class="has-line-data" data-line-start="22" data-line-end="23">I may face challenges in aligning data from different sources which are reported at different time intervals or contain missing values. I will clearly document data limitations and modeling assumtions so that results can be interpreted with caution.</p>
+
+</body></html>
diff --git a/Untitled_Document.md b/Untitled_Document.md
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+## Data Mini Porject Proposal 2 
+### Research Question 
+Can macroeconomic and climate indicators help predict food price inflation volatility in South Asian countries 
+
+### Motivation 
+Food prices play a central role in household welfare across South Asia where a large share of income is spent on basic food consumption. While average food inflation is important, sudden increases or fluctuations in food prices can be even more harmful especially for low-income households that have limited ability to smooth consumption. Periods of high food price volatility can increase food insecurity and economic stress, even when overall inflation remains moderate.
+
+South Asian countries are  vulnerable to external shocks such as global price changes, climate variability, and macroeconomic instability. This project aims to examine whether commonly used macroeconomic indicators and climate variables can help predict changes in food price inflation volatility. Understanding these relationships can help identify early warning signals of economic stress and contribute to better policy planning.
+
+### Data Sources 
+This project will use publicly available country level panel data for South Asian countries including India, Nepal, Bangladesh, Sri Lanka, and Pakistan.
+
+Food price data will be obtained from the Food and Agriculture Organization (FAO) food price indices. Macroeconomic indicators such as overall inflation will be sourced from the World Bank. Climate variables, including rainfall anomalies and temperature deviations, will be obtained from publicly available climate datasets.
+
+### Methodology 
+The project will begin with exploratory data analysis to examine trends in food price inflation and its volatility across countries and over time. This will include time-series plots, summary statistics, and comparisons across countries to identify periods of unusually high volatility.
+
+To model food price inflation volatility, I will construct a volatility measure using changes in food price inflation over time. I will then use macroeconomic and climate variables as predictors.
+
+As a baseline, I will estimate a linear regression model with lagged predictors to examine whether past macroeconomic and climate conditions are associated with future food price volatility. To allow for potential non-linear relationships, I will also estimate a Random Forest regression model and compare its predictive performance to the linear model.
+
+### Implications for Stakeholders 
+The findings from this project may be useful for policymakers and central banks in South Asia who monitor inflation and food security risks. Early identification of rising food price volatility could support more timely policy responses such as targeted subsidies or social protection measures.
+
+International organizations and development agencies may also benefit from understanding how climate and macroeconomic factors interact to influence food price instability. 
+
+### Ethical Considerations
+The topic raises important societal concerns related to inequality and food insecurity. Food price volatility disproportionately affects low-income households who spend a larger share of their income on food and have limited ability to adjust consumption.
diff --git a/Untitled_Document.md.html b/Untitled_Document.md.html
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+<!DOCTYPE html><html><head><meta charset="utf-8"><title>Untitled Document.md</title><style></style></head><body id="preview">
+<h2 class="code-line" data-line-start=0 data-line-end=1 ><a id="Data_Mini_Porject_Proposal_2_0"></a>Data Mini Porject Proposal 2</h2>
+<h3 class="code-line" data-line-start=1 data-line-end=2 ><a id="Research_Question_1"></a>Research Question</h3>
+<p class="has-line-data" data-line-start="2" data-line-end="3">Can macroeconomic and climate indicators help predict food price inflation volatility in South Asian countries</p>
+<h3 class="code-line" data-line-start=4 data-line-end=5 ><a id="Motivation_4"></a>Motivation</h3>
+<p class="has-line-data" data-line-start="5" data-line-end="6">Food prices play a central role in household welfare across South Asia where a large share of income is spent on basic food consumption. While average food inflation is important, sudden increases or fluctuations in food prices can be even more harmful especially for low-income households that have limited ability to smooth consumption. Periods of high food price volatility can increase food insecurity and economic stress, even when overall inflation remains moderate.</p>
+<p class="has-line-data" data-line-start="7" data-line-end="8">South Asian countries are  vulnerable to external shocks such as global price changes, climate variability, and macroeconomic instability. This project aims to examine whether commonly used macroeconomic indicators and climate variables can help predict changes in food price inflation volatility. Understanding these relationships can help identify early warning signals of economic stress and contribute to better policy planning.</p>
+<h3 class="code-line" data-line-start=9 data-line-end=10 ><a id="Data_Sources_9"></a>Data Sources</h3>
+<p class="has-line-data" data-line-start="10" data-line-end="11">This project will use publicly available country level panel data for South Asian countries including India, Nepal, Bangladesh, Sri Lanka, and Pakistan.</p>
+<p class="has-line-data" data-line-start="12" data-line-end="13">Food price data will be obtained from the Food and Agriculture Organization (FAO) food price indices. Macroeconomic indicators such as overall inflation will be sourced from the World Bank. Climate variables, including rainfall anomalies and temperature deviations, will be obtained from publicly available climate datasets.</p>
+<h3 class="code-line" data-line-start=14 data-line-end=15 ><a id="Methodology_14"></a>Methodology</h3>
+<p class="has-line-data" data-line-start="15" data-line-end="16">The project will begin with exploratory data analysis to examine trends in food price inflation and its volatility across countries and over time. This will include time-series plots, summary statistics, and comparisons across countries to identify periods of unusually high volatility.</p>
+<p class="has-line-data" data-line-start="17" data-line-end="18">To model food price inflation volatility, I will construct a volatility measure using changes in food price inflation over time. I will then use macroeconomic and climate variables as predictors.</p>
+<p class="has-line-data" data-line-start="19" data-line-end="20">As a baseline, I will estimate a linear regression model with lagged predictors to examine whether past macroeconomic and climate conditions are associated with future food price volatility. To allow for potential non-linear relationships, I will also estimate a Random Forest regression model and compare its predictive performance to the linear model.</p>
+<h3 class="code-line" data-line-start=21 data-line-end=22 ><a id="Implications_for_Stakeholders_21"></a>Implications for Stakeholders</h3>
+<p class="has-line-data" data-line-start="22" data-line-end="23">The findings from this project may be useful for policymakers and central banks in South Asia who monitor inflation and food security risks. Early identification of rising food price volatility could support more timely policy responses such as targeted subsidies or social protection measures.</p>
+<p class="has-line-data" data-line-start="24" data-line-end="25">International organizations and development agencies may also benefit from understanding how climate and macroeconomic factors interact to influence food price instability.</p>
+<h3 class="code-line" data-line-start=26 data-line-end=27 ><a id="Ethical_Considerations_26"></a>Ethical Considerations</h3>
+<p class="has-line-data" data-line-start="27" data-line-end="28">The topic raises important societal concerns related to inequality and food insecurity. Food price volatility disproportionately affects low-income households who spend a larger share of their income on food and have limited ability to adjust consumption.</p>
+
+</body></html>