Econometrics Seminar Series. On the Identifying Power of Generalized Monotonicity for Average Treatment Effects
Published: 20 November 2025
5 December 2025. Professor Edward Vytlacil, Yale University
Professor Edward Vytlacil, Yale University
"On the Identifying Power of Generalized Monotonicity for Average Treatment Effects"
Friday, 5 December 2025. 16:00
Online
Abstract
In the context of a binary outcome, treatment, and instrument, Balke and Pearl (1993, 1997) establish that the monotonicity condition of Imbens and Angrist (1994) has no identifying power beyond instrument exogeneity for average potential outcomes and average treatment effects in the sense that adding it to instrument exogeneity does not decrease the identified sets for those parameters whenever those restrictions are consistent with the distribution of the observable data. This paper shows that this phenomenon holds in a broader setting with a multi-valued outcome, treatment, and instrument, under an extension of the monotonicity condition that we refer to as generalized monotonicity. We further show that this phenomenon holds for any restriction on treatment response that is stronger than generalized monotonicity provided that these stronger restrictions do not restrict potential outcomes. Importantly, many models of potential treatments previously considered in the literature imply generalized monotonicity, including the types of monotonicity restrictions considered by Kline and Walters (2016), Kirkeboen et al. (2016), and Heckman and Pinto (2018), and the restriction that treatment selection is determined by particular classes of additive random utility models. We show through a series of examples that restrictions on potential treatments can provide identifying power beyond instrument exogeneity for average potential outcomes and average treatment effects when the restrictions imply that the generalized monotonicity condition is violated. In this way, our results shed light on the types of restrictions required for help in identifying average potential outcomes and average treatment effects.
Bio
Ph.D., Economics, University of Chicago, June 2000 B.A., Economics, University of Chicago, June 1994 (with General Honors & Departmental Special Honors) Edward Vytlacil is an econometrician, whose work has focused on the micro-econometric methodology for treatment effect and policy evaluation using disaggregate data. A theme in his work has been in allowing for the effects of a treatment to vary across people, and allowing individuals to have some knowledge of their own idiosyncratic treatment effect and to act upon that knowledge. In addition to his work in econometric methodology, he has published empirical work in labor economics and health economics evaluating the returns to schooling, the returns to job training programs, and the effectiveness of medical interventions. Ed received his PhD in Economics from the University of Chicago in 2000. He is rejoining the Yale faculty, having also previously been on the faculty at Stanford University, Columbia University, and most recently New York University.
For further information, please contact business-seminar-series@glasgow.ac.uk.
We are committed to providing a collegial, inclusive, and intellectually stimulating environment for all our seminars, in accordance with our established Code of Conduct.
First published: 20 November 2025
<< 2025