Causal Inference

Kenichi Ariga   (University of Toronto)

Abstract: Compositional outcomes are not unusual in political science research. Political scientists have analyzed the factors...

Nuannuan Xiang and Kevin Quinn (University of Michigan)

*Award for Best Graduate Student Poster - Methods*

Abstract: In this paper, we develop a class of Gaussian Process models to...

Ye Wang (New York University)

Abstract: Many social events and policies generate spillover effects in both time and space. Their occurrence influences not only the outcomes of interest...

Thomas Leavitt (Columbia University)

Abstract: Difference-in-Differences (DID) is a popular method for design-based causal inference. Design-based methods typically quantify uncertainty...

Connor Jerzak (Harvard University)

Abstract: With the rise of online social networks, there has been growing interest in modeling how experimental units influence each another---a phenomenon...

Melody Huang (University of California, Los Angeles), Erin Hartman (University of California, Los Angeles), Naoki Egami (Columbia University) and Luke Miratrix (Harvard University)

*Awa...

Jacob Brown (Harvard University), Matthew Blackwell (Harvard University), Sophie Hill (Harvard University), Kosuke Imai (Harvard University) and Teppei Yamamoto (Massachusetts Institute of