I'm currently a Ph.D. student in Economics at MIT, where I'm also part of the Interdisciplinary Ph.D. in Statistics (IDPS) program. I received my bachelor's degree in Economics and Statistics from the University of Chicago in 2017 and completed the Stanford GSB Research Fellows Program in 2019. My main research fields are econometrics and environmental economics. I work on adapting machine learning and high-dimensional statistical tools for causal inference, particularly in panel data contexts. I aim to create methods helpful for applied analysis in microeconomics, particularly for agricultural and environmental economics.
I'm on the 2024-2025 job market, and my department website can be found here.
Dynamic Biases of Static Panel Data Estimators, Job Market Paper (2024)
[preprint]Estimating Continuous Treatment Effects in Panel Data using Machine Learning with a Climate Application (2022)
[arXiv]Optimal Insurance Scope: Theory and Evidence from US Crop Insurance (2024)
[preprint]Bagged Polynomial Regression and Neural Networks (2022)
[arXiv]Automatic Double Machine Learning for Continuous Treatment Effects (2021)
[arXiv]Synthetic Differences-in-Differences with Covariates (2024)
[pdf]The Long-Term Effect of Childhood Exposure to Technology Using Surrogates (2022)
[pdf]hdm
High-Dimensional Metrics (R package).