QUANTITATIVE RESEARCH METHODS WORKSHOP
Abstract: We develop new tools for estimating the causal effects of treatments or instruments that combine multiple sources of variation according to a known formula. Examples include treatments capturing spillovers in social and transportation networks, simulated instruments for policy eligibility, and shift-share instruments. We show how exogenous shocks to some, but not all, determinants of such variables can be leveraged while avoiding omitted variables bias. Our solution involves specifying counterfactual shocks that may as well have been realized and adjusting for a summary measure of non-randomness in shock exposure: the average treatment (or instrument) across such counterfactuals. We further show how to use shock counterfactuals for valid finite-sample inference, and characterize the valid instruments that are asymptotically efficient. We apply this framework to address bias when estimating employment effects of market access growth from Chinese high-speed rail construction, and to boost power when estimating coverage effects of expanded Medicaid eligibility.
Kirill Borusyak is an assistant professor at UCL’s Economics Department. Prior to that he received his PhD from Harvard University in 2018 and worked as a postdoctoral researcher at Princeton University. His research covers the areas of international trade and applied econometrics.
This virtual workshop is open to the Yale community. To receive Zoom information, please subscribe to the Quantitative Research Methods Workshop at this link: https://csap.yale.edu/quantitative-research-methods-workshop.
The series is sponsored by the ISPS Center for the Study of American Politics and The Whitney and Betty MacMillan Center for International and Area Studies at Yale with support from the Edward J. and Dorothy Clarke Kempf Fund. This workshop is being hosted jointly with the Leitner Political Economy Seminar.