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Optimal Delegation in a Multidimensional World

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  • Andreas Kleiner

Abstract

We study a model of delegation in which a principal takes a multidimensional action and an agent has private information about a multidimensional state of the world. The principal can design any direct mechanism, including stochastic ones. We provide necessary and sufficient conditions for an arbitrary mechanism to maximize the principal's expected payoff. We also discuss simple conditions which ensure that some convex delegation set is optimal. A key step of our analysis shows that a mechanism is incentive compatible if and only if its induced indirect utility is convex and lies below the agent's first-best payoff.

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  • Andreas Kleiner, 2022. "Optimal Delegation in a Multidimensional World," Papers 2208.11835, arXiv.org.
    • Handle: RePEc:arx:papers:2208.11835
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    References listed on IDEAS

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    Cited by:

    1. Navin Kartik & SangMok Lee & Daniel Rappoport, 2022. "Single-Crossing Differences in Convex Environments," Papers 2212.12009, arXiv.org, revised Jun 2023.

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