Seminar - "Identification Under Universal Policy Exposure" - Vedant Vohra

Join us for a presentation by Vedant Vohra, a PhD candidate at the University of California, San Diego.

Seminar Title: Identification Under Universal Policy Exposure

Brief Abstract: Many important policies change the cost of taking up treatment for an entire population at the same time. In the absence of a control group unexposed to the policy change, how can we identify the causal effect of the policy? A key observation is that while there is no cross-sectional variation in policy exposure, treatment take-up varies across units and over time. To leverage this variation for identification, I adapt the local average treatment effect framework to a panel setting in which units make treatment take-up decisions in each period. A unit's latent compliance type, defined by potential treatment choices with and without the policy, can therefore change over time. I establish that there are two routes to point identification under parallel trends. The first approach restricts the selection mechanisms governing treatment take-up, ruling out specific changes in compliance types over time. The second restricts heterogeneity in treatment effects across compliance types. To relax both restrictions, I develop a marginal treatment effects approach that delivers sharp bounds under economically motivated shape restrictions. Applying the framework to Medicare Part D, I estimate that prescription-drug coverage improved medication access and reduced labor supply among individuals induced to obtain it by the reform.

Short Biography: Vedant is an applied econometrician working on developing new methods for causal identification and inference in challenging yet frequently encountered policy settings. He also works on topics in public and labor economics. His work has been published in journals such as The Review of Economics and Statistics and the Journal of Public Economics.