Robust mechanismsthe curvature case

Resumo

This paper considers the problem of a Principal who faces a privately informed Agent and only knows one moment of the type’s distribution. Preferences are nonlinear in the allocation, and the Principal maximizes her worst-case expected profits. The robustness property of the optimal mechanism imposes restrictions on the Principal’s ex-post payoff function: subject to the allocation being nonzero, ex-post payoffs are linear in the Agent’s type. The robust mechanism entails exclusion of low types, distortions at the intensive margin and efficiency at the top. We show that, under some conditions, distortions in the optimal mechanism are decreasing in types. This monotonicity has relevant consequences for several applications discussed. Our characterization uses an auxiliary zero-sum game played by the Principal and an adversarial Nature who seeks to minimize her expected payoffs which also gives us a characterization of the worst-case distribution from the Principal’s perspective. Applications of our framework to insurance provision, optimal taxation, nonlinear pricing and regulation are discussed. © 2018 Springer-Verlag GmbH Germany, part of Springer Nature

Ficha do documento

Tipo

Artigo científico

Ano

2018

Instituição

Springer New York LLC

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Acesso restrito

DOI

10.1007/s00199-018-1120-1

Identificador

oai:repositorio.fgv.br:10438/25610

Palavras-chave

Monopolistic screening under uncertaintyPrincipal–agent modelRobust mechanism designIncerteza