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"
  ☆14Updated last year
• d2cml-ai / csdid
  CSDID
  ☆39Updated this week
• bernardodionisi / differences
  difference-in-differences in Python
  ☆107Updated 2 years 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…
  ☆35Updated 11 months ago
• shoepaladin / causalinference_crashcourse
  Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
  ☆111Updated 2 weeks ago
• CausalAIBook / MetricsMLNotebooks
  Notebooks for Applied Causal Inference Powered by ML and AI
  ☆143Updated 9 months ago
• Mixtape-Sessions / Machine-Learning
  Machine Learning and Causal Inference taught by Brigham Frandsen
  ☆220Updated 3 months ago
• lihualei71 / cfcausalPaper
  Paper Repository
  ☆12Updated 3 years ago
• MisraLab / cml.github.io
  ☆31Updated 2 years ago
• jonathandroth / Econ1630_Github
  ☆91Updated last month
• susanathey / MCPanel
  Matrix Completion Methods for Causal Panel Data Models
  ☆103Updated 4 years ago
• MCKnaus / causalML-teaching
  This repository consolidates my teaching material for "Causal Machine Learning".
  ☆260Updated 2 months ago
• Mixtape-Sessions / Synthetic-Control-and-Clustering
  Synthetic-Control-and-Clustering taught by Alberto Abadie
  ☆58Updated last year
• rdpackages / rdrobust
  Statistical inference and graphical procedures for RD designs using local polynomial and partitioning regression methods.
  ☆88Updated 5 months ago
• keihirano / modern-sampling
  Course Materials for AEA Short Course on Modern Sampling Methods
  ☆29Updated 4 years 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 …
  ☆18Updated 2 years ago
• Mixtape-Sessions / Heterogeneous-Effects
  Machine Learning and Heterogeneous Effects taught by Brigham Frandsen
  ☆68Updated 2 months ago
• kolesarm / 517
  Econometric Theory I
  ☆30Updated last year
• jgreathouse9 / FDIDTutorial
  This repository contains the Python code to estimate the Forward and Augmented DID estimators.
  ☆12Updated last year
• Mixtape-Sessions / Regression-Discontinuity
  Regression Discontinuity Mixtape Track taught by Rocio Titiunik
  ☆55Updated last year
• pedrohcgs / DRDID
  Doubly Robust Difference-in-Differences Estimators
  ☆94Updated last month
• alexanderquispe / 14.38_Causal_ML
  JupyterNotebook for the MIT course
  ☆16Updated 8 months ago
• mwelz / GenericML
  R implementation of Generic Machine Learning Inference (Chernozhukov, Demirer, Duflo and Fernández-Val, 2020).
  ☆76Updated last month
• Mixtape-Sessions / Design-Based-Inference
  Design-Based Inference Mixtape Session taught by Peter Hull
  ☆43Updated last year
• apoorvalal / TestingInEventStudies
  tests for cohort-level heterogeneity in panel regression
  ☆11Updated 10 months ago
• demirermert / MLInference
  ☆100Updated 5 years ago
• Mixtape-Sessions / Causal-Inference
  Causal Inference Mixtape Sessions
  ☆99Updated 3 years ago
• MartinSpindler / hdm
  ☆18Updated last year
• MartinSpindler / Machine-Learning-in-Econometrics
  Collection of lecture notes and excercises for a course "Machine Learning in Econometrics"
  ☆28Updated 9 years ago
• NickCH-K / TheEffectAssignments
  Homework assignments to go along with The Effect
  ☆70Updated 4 months ago