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

Agent skills that help you publish in the AER faster — identification-first empirics, AEA-compliant replication, Keith-Head intros, R&R rebuttals for AER / AER:Insights / AEJ. | 助你更快发表 AER 论文的 agent skill 栈：识别优先实证、AEA 合规复现、Keith Head 式引言、R&R 审稿回复，覆盖选题到投稿全流程。

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.

Open Agent Skill for exploratory financial astrology event studies across investment assets

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.

Offline event study MATLAB application

Minute-level market microstructure event study analyzing extended-hours price discovery and orderflow around MSFT earnings. Integrates SEC 8-K Loughran-McDonald sentiment analysis with intraday Polygon proxies (CVD, realized volatility, and spread).

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

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

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.

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.