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Dynamic Information Design with Diminishing Sensitivity Over News

Jetlir Duraj and Kevin He

Papers from arXiv.org

Abstract: A benevolent sender communicates non-instrumental information over time to a Bayesian receiver who experiences gain-loss utility over changes in beliefs ("news utility"). We show how to inductively compute the optimal dynamic information structure for arbitrary news-utility functions. With diminishing sensitivity over the magnitude of news, unlike in piecewise-linear news-utility models, one-shot resolution of uncertainty is strictly suboptimal under commonly used functional forms. We identify additional conditions that imply the sender optimally releases good news in small pieces but bad news in one clump. By contrast, information structures that deliver bad news gradually are never optimal. When the sender lacks commitment power, good-news messages confront a credibility problem given the receiver's diminishing sensitivity. Without loss aversion, the babbling equilibrium is essentially unique. More loss-averse receivers may enjoy higher equilibrium news-utility, contrary to the commitment case.

New Economics Papers: this item is included in nep-des, nep-mic and nep-upt
Date: 2019-07, Revised 2019-09
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