ModernDiD documentation#
Version: 0.2.0
Useful links: Installation | Introduction to DiD | Source Repository | Issue Tracker | PyPI
ModernDiD is a scalable, GPU-accelerated difference-in-differences library for Python. It consolidates modern DiD estimators from leading econometric research and various R and Stata packages into a single framework with a consistent API. Runs on a single machine, NVIDIA GPUs, and distributed Spark and Dask clusters.
Getting started
New to ModernDiD? Check out the Getting Started guide for installation instructions and an introduction to difference-in-differences methodology.
User guide
The user guide provides in-depth tutorials and practical guidance for implementing DiD estimators with real-world data scenarios.
API reference
The API reference contains detailed documentation on all of ModernDiD’s estimators, methods, and classes including function signatures and parameters.
Development
Want to contribute to ModernDiD? The development guide covers setup, coding standards, testing, and submission guidelines.