Master's Projects

Paper Replication in Python

This project replicates the first half of the main results from Cengiz, D., Dube, A., Lindner, A., & Zentler-Munro, D. (2022). Following the authors, I apply machine learning methods to identify the potencial workers who are actually affected by the minimum wage policy. In contrast to the original code, which was written in Stata and R, I replicated the study in Python, streamlining all the code into a single programming language that is both free and open source.

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Machine learning in an IV setting using R

I study the performance of three-based methods (random forest and boosting) in an IV setting with a binary endogenous explanatory variable. In particular, I apply these machine learning methods to estimate the returns to college attendance, simulating the data used by Carneiro, Heckman, and Vytlacil (2011). I use R.

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