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A graduate course on Computational Macroeconomics
Total Factor Productivity with Undesirable Outputs in Stata
Design-Based Inference Mixtape Session taught by Peter Hull
Causal Inference 3 Mixtape Session taught by Scott Cunningham
Causal Inference 1 Mixtape Session taught by Scott Cunningham
tebounds is a port of the Stata command 'tebounds' for R.
Regression Discontinuity Mixtape Track taught by Rocio Titiunik
Machine Learning and Heterogeneous Effects taught by Brigham Frandsen
Doing Applied Economics Research Mixtape Track taught by Mark Anderson and Daniel Rees
R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.
Synthetic-Control-and-Clustering taught by Alberto Abadie
difference-in-differences in Python
Poisson pseudo-likelihood regression with multiple levels of fixed effects
Shift-Share Instrument Mixtape Track taught by Peter Hull
Machine Learning and Causal Inference taught by Brigham Frandsen
Keeping track of what is going on with the latest DiD innovations.
Causal Inference II Mixtape Session taught by Scott Cunningham
Instrumental Variables Mixtape Track taught by Peter Hull
Code that I show on my YouTube Channel
R & stats illustrations by @allison_horst
Advanced Differnce-in-Differences Mixtape Track taught by Jonathan Roth
This template can be used to begin projects that are reproducible from raw data through published paper or thesis.
Software and data accompanying the paper "A Discrete Choice Model for Subset Selection".
Provides a simple way to run Selenium Grid with Chrome, Firefox, and Edge using Container Platform, making it easier to perform browser automation at scale