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Endogeneity and non-response bias in treatment evaluation - nonparametric identification of causal effects by instruments


This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for non-response/attrition, we identify the average treatment effect on compliers as well as the total population and suggest non- and semiparametric estimators. We apply the latter to a randomized experiment at a Swiss University in order to estimate the effect of gym training on students' self-assessed health. The treatment (gym training) and attrition are instrumented by randomized cash incentives paid out conditional on gym visits and by a cash lottery for participating in the follow-up survey, respectively.

Martin Huber (University of Fribourg)
Short bio: 
Martin Huber received his PhD in Economics and Finance from the University of St. Gallen and is currently professor of Applied Econometrics and Evaluation of Public Policies at the Unversity of Fribourg (Switzerland). His main research interest is the policy/treatment effect evaluation in labor, health, and education economics using semi- and nonparametric microeconometric methods for causal inference. His work is published, among others, in international journals such as the Review of Economics and Statistics, Journal of Econometrics, Journal of Health Economics, or the Journal of Business and Economic Statistics. In 2014, was awarded the Latsis Prize of the University of St. Gallen and in 2013 he was awarded Austrian Young Economists Award as well as the Labour Prize in Theoretical or Applied Microeconometrics.
10 December 2015 - 17:00

Vicolo dalla Piccola 12, Trento