The Winner’s Curse in Data-Driven Decision-Making: Evidence and Solutions
(A2026-132248)

AUTHORS

Sikun Xu, Washington Univeristy in St. Louis; Raphael Thomadsen, Washington University in St. Louis; Dennis Zhang, Washington University in St. Louis

ABSTRACT

In this paper, we first provide a theoretical demonstration that selecting the optimal decision based on estimated effects from data leads to systemic overly-optimistic evaluations of that decision’s value — a phenomenon known as the winner’s curse — even when the estimators are unbiased and regardless of the optimization procedure used. We then empirically show that an economically significant winner’s curse exists across a broad set of marketing applications with realistic parameter settings, including A/B testing, personalized targeting, and assortment optimization, and propose a correction method based on a non-continuous bootstrap.