Teaching and notes
Medicare Advantage Data Cleaning: Python code for cleaning Medicare Advantage data.
Code to download, clean, and merge publicly available data from the Centers for Medicare & Medicaid Services (CMS).
Post-processing layer for the Jung et al. Medicare Advantage encounter data pipeline.
Econometrics I: Solutions for textbook exercises and notes from weekly TA sessions for first year econometrics. It covers probability theory, basic mathematical statistics and regression analysis. The exercises are from Introduction to Econometrics and Econometrics.
Advanced Econometrics (with Machine learning): Python tutorials and solutions to homework problems from An Introduction to Statistical Learning. It covers causal inference and machine learning.
Empirical Industrial Organization: Tutorials in Python and Julia on BLP, dynamic discrete choice, and auctions.
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Numerical Analysis: Solving exercises for numerical analysis including solving linear equations, approximation, solving differential equations in Julia.