Topic:
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Sharp Testable Implications of Encouragement Designs |
Time&Date:
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10:00 am-11:30 am, December 13, 2024 (Friday)
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Venue
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Room 904, Teaching Complex D Building
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Speaker:
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Prof. Yuehao Bai (University of Southern California)
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Abstract: |
This paper studies the sharp testable implications of an additive random utility model with a discrete multi-valued treatment and a discrete multi-valued instrument, in which each value of the instrument only weakly increases the utility of one choice. Borrowing the terminology used in randomized experiments, we call such a setting an encouragement design. We derive inequalities in terms of the conditional choice probabilities that characterize when the distribution of the observed data is consistent with such a model. Through a novel constructive argument, we further show these inequalities are sharp in the sense that any distribution of the observed data that satisfies these inequalities is generated by this additive random utility model.
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Biography:
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Yuehao Bai is an assistant professor of economics at the University of Southern California. He received his PhD in economics in 2020 from the University of Chicago. His research interests lie in econometric theory, with recent focus on experimental design and identification and inference with multi-valued treatments and instruments. His papers have been published in journals including the American Economic Review, Journal of the American Statistical Association, Journal of Econometrics, and Quantitative Economics.
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