LIDS Seminar | Rakesh Vohra

Abstract:  We study Bayesian updating when actions reveal feasible sets of posterior beliefs rather than exact beliefs. In market segmentation, for example, demand curves are unobserved, but optimal prices reveal information about latent demand. With exact posterior beliefs, the splitting lemma requires only that the prior equal the average posterior. With posterior envelopes, average consistency is not enough: each interval of types must contain sufficient prior mass to support gaps between posterior bounds. Applied to segmentation, these restrictions characterize aggregate demand and yield bounds on price sensitivity, welfare, and counterfactual revenue. The framework also applies to auctions, admissions, and classification design.

‍Rakesh V. Vohra is the George A. Weiss and Lydia Bravo Weiss University Professor in the Department of Economics and the Department of Electrical and Systems Engineering at the University of Pennsylvania. His research spans market design, game theory, optimization, and algorithmic economics, with applications to auctions, matching markets, pricing, and learning.

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