Hi everyone!

This week at the Applied Statistics Workshop we will be welcoming Matthew Blackwell, an Assistant Professor of Government at Harvard University.  He will be presenting work entitled Identification and Estimation of Joint Treatment Effects with Instrumental Variables.  Please find the abstract below and on the website.

As usual, we will meet in CGIS Knafel Room 354 and lunch will be provided.  See you all there!

-- Aaron Kaufman

Title: Identification and Estimation of Joint Treatment Effects with Instrumental Variables

Abstract:  Over the last twenty years, a literature spanning several fields of applied statistics has analyzed how to identify and estimate causal effects of a nonrandomized treatment when a instrumental variable (IV) is available. But researchers often have multiple treatments and want to estimate either the direct or joint effect of these treatments. This paper introduces a set of novel estimands for instrumental variables with multiple treatments and multiple instruments. These estimands are similar to previous IV estimands as they are ``local’’ to strata defined by the joint compliance status across the treatments. Furthermore, I show that these estimands are nonparametrically identified under standard instrumental variable assumptions. The paper further develops nonparametric estimators for these quantities and assess their performance relative to classic parametric approaches like two-stage least squares. Finally, I demonstrate the method through an empirical application to a voter mobilization field experiment with both a telephone and in-person treatments.

--
Aaron R Kaufman
PhD Candidate, Harvard University
Department of Government
818.263.5583