Incentive Compatible Estimators

Kfir Eliaz and Ran Spiegler ()

No 12804, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We study a model in which a "statistician" takes an action on behalf of an agent, based on a random sample involving other people. The statistician follows a penalized regression procedure: the action that he takes is the dependent variable's estimated value given the agent's disclosed personal characteristics. We ask the following question: Is truth-telling an optimal disclosure strategy for the agent, given the statistician's procedure? We discuss possible implications of our exercise for the growing reliance on "machine learning" methods that involve explicit variable selection.

Date: 2018-03
New Economics Papers: this item is included in nep-big and nep-cmp
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Journal Article: On incentive-compatible estimators (2022)
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