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Dynamically Consistent Statistical Decisions

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  • Cheaheon Lim
  • Yechan Park

Abstract

A large literature in econometrics proposes decision rules with optimality guarantees based on ex ante criteria, such as minimax regret. We develop a framework for analyzing the dynamic consistency of such rules and show that, in many empirically relevant settings, the researcher may wish to deviate from the interim prescription of ex ante optimal rules after observing the data realization. To address this problem, we propose and axiomatize two classes of optimality criteria that yield dynamically consistent decision rules.

Suggested Citation

  • Cheaheon Lim & Yechan Park, 2026. "Dynamically Consistent Statistical Decisions," Papers 2607.10519, arXiv.org.
    • Handle: RePEc:arx:papers:2607.10519
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    File URL: https://arxiv.org/pdf/2607.10519
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