Joel Middleton

Joel Middleton is an Assistant Professor in the Department of Political Science at the University of California, Berkeley. He is a leading expert in causal inference and experimental design, with methodological innovations in spectral analysis and statistical modeling for randomized experiments.

• Expertise in causal inference and randomized controlled trials
• Developed unified framework for evaluating experimental designs
• Focus on precision and efficiency in statistical estimation

His recent research includes work on bias correction in linear adjustment (2024, Econometrica) and optimized variance estimation under interference (2024, Journal of the American Statistical Association). Applications span from education policy in Afghanistan to electoral dynamics in the U.S. Publications emphasize methodological rigor and practical implementation.