Ranking Statistical Experiments via the Linear Convex Order: Economic Applications

Kailin Chen

Papers from arXiv.org

Abstract: This paper introduces a novel ranking of statistical experiments based on the linear convex order. This ranking encompasses a broader range of scenarios where intuition suggests that one experiment is more informative than another, and offers more tractable characterizations than the Blackwell order, which is based on the convex order. Moreover, this ranking admits an elegant geometric characterization through the Lorenz zonoid, which generalizes the Lorenz curve to multidimensional settings. We apply the ranking to compare experiments in binary-action decision problems and in problems with quasiconcave payoffs, as analyzed by Kolotilin, Corrao, and Wolitzky (2025). Furthermore, the ranking enables comparison of experiments in moral hazard problems, complementing the findings in Holmstr\"om (1979) and Kim (1995). Finally, the ranking applies to comparing experiments generating ex post signals in screening problems.

Date: 2025-02, Revised 2025-09
New Economics Papers: this item is included in nep-exp
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