MTE with Misspecification
Abstract
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.
Supplementary notes can be added here, including code and math.
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.