Research

Professor Peter Hull, Brown University

"Robust Signal Maximization in Spillover Experiments"
Friday, 5th of February 2027. 15:00
Online

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Abstract

We study the optimal design and analysis of experiments for estimating spillover effects. Assuming a known (e.g., linear) exposure mapping, we characterize the treatment-assignment distribution and regression-based estimator that minimize worst-case asymptotic variance against a broad class of distributions of unobservables. The design problem yields an intuitive solution in which the planner trades off spillover signal strength against diffusion of spillover variation. The analysis problem yields a simple recentered instrumental variable estimator to best leverage this variation. This framework produces natural solutions in several benchmark cases—such as clustered exposure—and suggests computationally tractable approximations for general networks, including bipartite settings. We illustrate these new tools in semi-synthetic experiments based on two applications from development economics. Our approach yields large standard error reductions in both experiments, increasing effective sample sizes by 50–100% or more.

Bio

Peter Hull is a Professor of Economics at Brown University, where he studies applied econometrics and applied topics in education, healthcare, discrimination, and crime. Hull received his Ph.D. in Economics from MIT in 2017 and was previously an Assistant Professor of Economics at the University of Chicago. He is a Research Associate at the NBER and a coeditor at the American Economic Journal: Applied Economics.

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First published: 15 September 2026