A Python package for causal inference using Synthetic Controls

A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more

Synthetic difference in differences for Python

Factor-Based Imputation for Missing Data

A Penalized Synthetic Control Estimator for Disaggregated Data (JASA, 2021)

Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.

Causal Inference Using Quasi-Experimental Methods

fast synthetic control estimators for panel data problems

data repository for publicly available code and data of "Low-intensity fires mitigate the risk of catastrophic wildfires in California's forests"

Replication materials for the paper "Evaluating the Effect of Homicide Prevention Strategies in São Paulo, Brazil: A Synthetic Control Approach" (2016)

Replication code for "RNN-based counterfactual prediction, with an application to homestead policy and public schooling"

Tutorials for the synthetic control method for causal inference using PyMC

Comparative Case Studies using The Synthetic Control Method

julia implementation of Synthetic Control estimation

Prevalence of Cannabis Use Disorder Post Legalization – Uruguay Case Study (Synthetic Control Method)

Using simulated data to understand synthetic control

A PyTorch implementation of the "robust" synthetic control model

Source code to replicate the results of our article published in Revista de Historia Económica: Another case of the middle-income trap: Chile, 1900-1939

Synthenic Control Method

SynthX: A Python Library for Advanced Synthetic Control Analysis