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Policy Learning with Confidence

Victor Chernozhukov, Sokbae (Simon) Lee, Adam Rosen and Liyang Sun

Papers from arXiv.org

Abstract: This paper introduces a rule for policy selection in the presence of estimation uncertainty, explicitly accounting for estimation risk. The rule belongs to the class of risk-aware rules on the efficient decision frontier, characterized as policies offering maximal estimated welfare for a given level of estimation risk. Among this class, the proposed rule is chosen to provide a reporting guarantee, ensuring that the welfare delivered exceeds a threshold with a pre-specified confidence level. We apply this approach to the allocation of a limited budget among social programs using estimates of their marginal value of public funds and associated standard errors.

Date: 2025-02, Revised 2026-01
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Citations: View citations in EconPapers (3)

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http://arxiv.org/pdf/2502.10653 Latest version (application/pdf)

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Working Paper: Policy learning with confidence (2025) Downloads
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