Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

Popular Econometrics content with code; Simple Linear Regression, Multiple Linear Regression, OLS, Event Study including Time Series Analysis, Fixed Effects and Random Effects Regressions for Panel Data, Heckman_2_Step for selection bias, Hausman Wu test for Endogeneity in Python, R, and STATA.

fast and flexible Difference-in-Differences

AI-powered trading research platform. Test any idea on stocks, futures, and crypto with event studies, backtesting, and statistical validation. MCP server with 8 tools. pip install varrd.

An Implementation of Parametric and Nonparametric Event Study

archived : use csdid instead

This repository introduces the event study model.

End-to-end incrementality sandbox on M5-style retail data (DiD + Synthetic Control + placebo tests) with Streamlit dashboard.

R package: crseEventStudy

Causal evaluation of a staged product or feature rollout using Difference-in-Differences and event-study methods, with explicit pre-trend validation and Go/No-Go decision framing.

The article evaluates the effect of the enforcement activities of the Federal Antimonopoly Service of Russia on the market value of companies in the oil industry [reputational costs] (In Russian)

Use Kalman Filters for Event Study Designs

Difference-in-Differences analysis of the 2008 financial crisis impact on youth employment in Italy using EU-LFS microdata (2004-2010)

Replication and extension of Besley & Burgess (2004) using modern DiD, event-study diagnostics, heterogeneity, and robustness checks in R.

Offline event study MATLAB application

Difference-in-Differences analysis of refugee inflows and crime rates in German regions (2010–2020)

Quantitative analysis of Federal Reserve rate hikes (2022-2023) and their impact on Growth vs. Value stocks. Features Event Studies, GARCH(1,1) volatility modeling, and LSTM price forecasting using Python.

Proyecto de tesis para título profesional: "Evaluación de impacto del programa Juntos sobre nutrición infantil: una estimación con modelos de regresión de diferencias en diferencias escalonadas"

LUISS Computational Finance thesis using CAPM event analysis, pooled OLS panel regression, and train-test split validation to model stock return reactions to the 2025 U.S. steel and aluminum tariffs.

Multi-pillar L/S equity research on DoorDash (DASH): alt-data signals → GOV surprise forecast → revenue / contribution-margin / EBITDA chain → DASH-vs-UBER cross-sectional spread → CAR event study. Pre-registered Q1 2026 prediction.