MTE with Misspecification


This paper studies the implication of a fraction of the population not responding to the instrument when selecting into treatment. We show that, in general, the presence of non-responders biases the Marginal Treatment Effect (MTE) curve and many of its functionals. We obtain partial identification results for the MTE, the LATE and the MPRTE. Moreover, in a linear-in-covariates model we obtain a testable implication for the presence of non-responders. Simulation results show that our proposed estimators, using the range of the propensity score, work well.

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Pietro Emilio Spini
Pietro Emilio Spini
Lecturer (Assistant Professor) in Economics

Welcome to my personal page! I am a Lecturer (Assistant professor) at the University of Bristol, where I started in September 2022. I received my PhD in Economics from the University of California, San Diego. My research focus is in Econometrics and Policy Evaluation. I study how to robustify causal inference procedures against data limitations that typically arise in applied economic research.