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arXiv · 2502.10653

Policy Learning with Confidence

Victor Chernozhukov·Sokbae Lee·Adam M. Rosen·Liyang Sun
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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.

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Victor Chernozhukov, Sokbae Lee, Adam M. Rosen, Liyang Sun. 2026-01-18. Policy Learning with Confidence. https://arxiv.org/abs/2502.10653

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