Working paper with Jiawei Fu and Cyrus Samii Download the manuscript here Why this paper matters Group interaction experiments—such as deliberation studies, classroom experiments, group therapy sessions, and lab coordination games—are widely used across political science, economics, psychology, and public health. Yet researchers often analyze these designs using off-the-shelf methods (individual-level regressions, cluster-robust standard errors, or simple difference-in-means)

Working paper with Jonne Kamphorst, Liesbet Hooghe, and Gary Marks Download the manuscript here This paper investigates how and why the contemporary gender gap in voting emerges—specifically, why women are more likely to support GAL (Green–Alternative–Liberal) parties and less likely to support TAN (Traditional–Authoritarian–Nationalist) parties than men. Grounded in social role theory, we argue that the gender gap is not solely rooted in early-life traits or stable psycholog

Working paper, with Michael Jetsupphasuk; an earlier version of the paper is entitled "Causal Inference under Temporal and Spatial Interference." Download the manuscript here Why this paper matters Longitudinal causal inference in biostatistics, epidemiology, and social sciences often relies on marginal structural models (MSMs), which summarize the effects of time-varying treatments and can be consistently estimated using inverse probability weighting (IPW) under sequential

PNAS 2023, with Ruixue Jia , Margaret Roberts , and Eddie Yang Download the manuscript here This paper documents how U.S.–China political tensions have reshaped scientific production in the United States. We study NIH-initiated investigations that began in 2018 and targeted undisclosed foreign funding, with most cases involving China. Using large-scale publication data from 2010–2021, we compare U.S. life scientists who had collaborated with researchers in China to similar s

Annals of Applied Statistics, 2025, with Cyrus Samii , Haoge Chang, and P Aronow . Why this paper matters Many policy experiments and field interventions, such as forest conservation programs, public health campaigns, and policing deployments, take place in geographic space. In these settings, treatment at one location can affect outcomes nearby, creating spatial interference that violates the stable unit treatment value assumption (SUTVA). Existing solutions to this proble