freshtaste / CausalModel
CausalModel implements widely used casual inference methods as well as an interference based method proposed by our paper.
☆16Updated 10 months ago
Alternatives and similar repositories for CausalModel:
Users that are interested in CausalModel are comparing it to the libraries listed below
- Machine Learning for Economics☆19Updated last year
- Implementation of Double Machine Learning☆35Updated last year
- Approximately balanced estimation of average treatment effects in high dimensions.☆34Updated 3 years ago
- Paper Repository☆11Updated 2 years ago
- Optimized regression discontinuity designs☆29Updated 2 years ago
- Code for DID chapter☆11Updated last year
- Design of Simulations using WGAN☆49Updated 2 years ago
- Double Machine Learning for Multiple Treatments☆40Updated 4 years ago
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 2 years ago
- ☆93Updated last year
- A Penalized Synthetic Control Estimator for Disaggregated Data (JASA, 2021)☆35Updated last month
- ☆42Updated 3 years ago
- Policy learning via doubly robust empirical welfare maximization over trees☆78Updated 9 months ago
- Robust empirical Bayes confidence intervals☆10Updated 7 months ago
- Teaching materials☆14Updated 9 months ago
- This repository contains the Python code to estimate the Forward and Augmented DID estimators.☆12Updated 4 months ago
- Replication code for "Log with zeros? Some problems and solutions"☆13Updated 9 months ago
- Course Materials for AEA Short Course on Modern Sampling Methods☆29Updated 3 years ago
- Specification test for the propensity score☆13Updated 2 years ago
- Inference for synthetic controls☆39Updated 3 years ago
- Treatment Effects in Interactive Fixed Effects Model☆17Updated last month
- Time series forecasting with Lasso-type shrinkage methods☆13Updated 6 months ago
- A package for Bayesian causal inference with time-series cross-sectional data☆26Updated last year
- R implementation of Generic Machine Learning Inference (Chernozhukov, Demirer, Duflo and Fernández-Val, 2020).☆67Updated 2 months ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆25Updated last year
- pytorch implementation of BLP'95☆26Updated 5 years ago
- An Interface to Specify Causal Graphs and Compute Balke Bounds☆17Updated last month
- Sufficient Representation for Categorical Variables https://arxiv.org/abs/1908.09874v1☆14Updated 4 years ago
- R package cfcausal☆27Updated 2 years ago
- Machine Learning Estimation of Heterogeneous Causal Effects☆24Updated 3 years ago