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. Yet, we show that, when the propensity score is fully supported on the unit interval, it is still possible to restore identification of the MTE curve and its functionals with a appropriate re-weighting.

Click the Slides button above to demo Academic’s Markdown slides feature.

Supplementary notes can be added here, including code and math.

Pietro Emilio Spini
Pietro Emilio Spini
PhD candidate in Economics

Welcome to my personal page! I am a PhD Candidate in Economics at 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. I will be joining the University of Bristol as a Lecturer (Assistant professor) at the end of the Summer 2022.