What can LLMs tell us about the ETI?
We investigate how large language models perceive and simulate behavioral responses to tax policy changes, with implications for using LLMs in policy analysis.
Research
My research focuses on tax policy, microsimulation, and the application of AI/ML to economic analysis.
Working papers & publications
AI Model Policy Impact Forecasts: A Narrative Prompting Approach
Examining the use of large language models for forecasting policy outcomes under different U.S. presidential administrations using narrative prompting techniques.
Enhancing Survey Microdata with Administrative Records
A novel approach to microsimulation dataset construction that combines Current Population Survey data with IRS administrative records for improved tax-benefit modeling.
Interactive research projects
These are full research articles built with Jupyter Book, featuring interactive visualizations and executable code.
PolicyEngine research
As CEO of PolicyEngine, I contribute to numerous policy analyses. Visit the PolicyEngine Research page for our full portfolio of published work on tax and benefit policy.