Alternatives and similar repositories for winter23:

Users that are interested in winter23 are comparing it to the libraries listed below

• dballinari / Calibrating-doubly-robust-estimators-with-unbalanced-treatment-assignment
  Code to replicate the simulation study in the paper "Calibrating doubly-robust estimators with unbalanced treatment assignment"
  ☆13Updated 10 months ago
• lihualei71 / cfcausalPaper
  Paper Repository
  ☆11Updated 2 years ago
• CausalAIBook / MetricsMLNotebooks
  Notebooks for Applied Causal Inference Powered by ML and AI
  ☆109Updated this week
• d2cml-ai / csdid
  CSDID
  ☆26Updated 2 months ago
• QuantLet / Meta_learner-for-Causal-ML
  This repository provides R-code for the estimation of the conditional average treatment effect (CATE) using machine learning (ML) methods…
  ☆33Updated last month
• kolesarm / 517
  Econometric Theory I
  ☆21Updated 5 months ago
• Mixtape-Sessions / Regression-Discontinuity
  Regression Discontinuity Mixtape Track taught by Rocio Titiunik
  ☆48Updated 3 months ago
• Mixtape-Sessions / Heterogeneous-Effects
  Machine Learning and Heterogeneous Effects taught by Brigham Frandsen
  ☆54Updated last month
• keihirano / modern-sampling
  Course Materials for AEA Short Course on Modern Sampling Methods
  ☆29Updated 3 years ago
• Mixtape-Sessions / Synthetic-Control-and-Clustering
  Synthetic-Control-and-Clustering taught by Alberto Abadie
  ☆49Updated 3 months ago
• AStrittmatter / ML-for-Econometrics
  ☆8Updated last year
• kwuthrich / scinference
  Inference for synthetic controls
  ☆39Updated 3 years ago
• rdpackages / rdrobust
  Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.
  ☆78Updated 4 months ago
• d2cml-ai / 14.388_py
  This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …
  ☆16Updated last year
• jeremylhour / pensynth
  A Penalized Synthetic Control Estimator for Disaggregated Data (JASA, 2021)
  ☆35Updated 2 weeks ago
• jonathandroth / Econ1630_Github
  ☆84Updated 10 months ago
• alexanderquispe / 14.38_Causal_ML
  JupyterNotebook for the MIT course
  ☆15Updated 2 years ago
• Mixtape-Sessions / Frontiers-in-DID
  Frontiers in Difference-in-Differences taught by Brantly Callaway
  ☆33Updated 3 months ago
• shoepaladin / causalinference_crashcourse
  Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
  ☆92Updated 2 weeks ago
• nppackages / scpi
  Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.
  ☆32Updated last month
• victor5as / RieszLearning
  Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…
  ☆13Updated 2 years ago
• mwelz / GenericML
  R implementation of Generic Machine Learning Inference (Chernozhukov, Demirer, Duflo and Fernández-Val, 2020).
  ☆65Updated last month
• pedrohcgs / pstest
  Specification test for the propensity score
  ☆13Updated 2 years ago
• Mixtape-Sessions / Difference-in-Differences
  Difference-in-Differences
  ☆41Updated 2 years ago
• d2cml-ai / 14.388_r
  This Jupyterbook has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and …
  ☆13Updated last year
• zachporreca / staggered_adoption_synthdid
  NO LONGER MAINTAINED. Links to alternative packages are in the readme. Code to incorporate staggered treatment adoption (based on appendi…
  ☆21Updated last year
• sdfordham / pysyncon
  A python module for the synthetic control method
  ☆64Updated 2 months ago
• Mixtape-Sessions / Causal-Inference-3
  Causal Inference 3 Mixtape Session taught by Scott Cunningham
  ☆42Updated last month
• bernardodionisi / differences
  difference-in-differences in Python
  ☆100Updated last year
• Mixtape-Sessions / Design-Based-Inference
  Design-Based Inference Mixtape Session taught by Peter Hull
  ☆43Updated 3 months ago