d2cml-ai / mgtecon634_pyLinks
This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in the MGTECON 634 at Stanford. Scripts were translated into Python.
☆12Updated 2 years ago
Alternatives and similar repositories for mgtecon634_py
Users that are interested in mgtecon634_py are comparing it to the libraries listed below
Sorting:
- 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 2 years ago
- This Jupyterbook has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and …☆13Updated 2 years ago
- This repository provides R-code for the estimation of the conditional average treatment effect (CATE) using machine learning (ML) methods…☆35Updated 7 months ago
- Code to replicate the simulation study in the paper "Calibrating doubly-robust estimators with unbalanced treatment assignment"☆14Updated last year
- Jupyter Notebook adaptation of the code from Huber (2023) - Causal Analysis☆11Updated last year
- Notebooks for Applied Causal Inference Powered by ML and AI☆129Updated 5 months ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆25Updated 2 years ago
- Design of Simulations using WGAN☆53Updated 2 years ago
- Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks☆103Updated 4 months ago
- Lectures and Tutorials for the Causal AI course☆44Updated this week
- ☆20Updated 4 years ago
- Course Materials for AEA Short Course on Modern Sampling Methods☆29Updated 3 years ago
- difference-in-differences in Python☆103Updated last year
- Packages of Example Data for The Effect☆142Updated 9 months ago
- Empirical Bayes Mixtape Session taught by Christopher Walters☆16Updated 8 months ago
- Difference-in-Differences☆41Updated 3 years ago
- Implementation of Double Machine Learning☆36Updated 4 months ago
- Notes and simulations on graduate level causal inference in statistics with applications to social sciences.☆23Updated 6 years ago
- Slides for the Seattle University Causal Inference Class☆141Updated 4 years ago
- Econometric Theory I☆27Updated 10 months ago
- Code for the paper "CAREER: Transfer Learning for Economic Prediction of Labor Sequence Data"☆45Updated last year
- CSDID☆33Updated last month
- ☆22Updated last year
- Machine Learning for Economics☆18Updated 2 years ago
- Synthetic difference in differences for Python☆84Updated last year
- Unstructured Code with interesting analysis☆37Updated 10 months ago
- JupyterNotebook for the MIT course☆16Updated 3 months ago
- Homework assignments to go along with The Effect☆66Updated 3 months ago
- A python module for the synthetic control method☆72Updated 4 months ago
- Synthetic-Control-and-Clustering taught by Alberto Abadie☆53Updated 8 months ago