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arXiv AI By Lauri Lov\'en, Sasu Tarkoma

The Endogeneity of Miscalibration: Impossibility and Escape in Scored Reporting

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The paper examines how an agent’s probability report is evaluated twice—once by a strictly proper scoring rule and again by an approval rule that determines a decision. It shows that when the approval rule is welfare‑maximizing, it cannot be affine, yet the resulting distortion is predictable and can be mitigated by a reserve report that neutralizes the cost of pretending to be the marginal type. A Lipschitz rule with a single kink achieves first‑best welfare, while smooth rules cannot, and the key constraint is the steepness of the rule rather than its smoothness.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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