噪声信息处理下的自愿披露
Disclosure under Noisy Information Processing
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中文总结 AI 辅助
本文研究噪声信息处理下企业的自愿披露行为，发现噪声会推翻部分披露均衡，并刻画了完全披露与阈值均衡的条件及中介费用对披露的影响。
中文摘要 AI 辅助
我们研究当投资者通过审计师、分析师、评级机构或数据提供商等噪声信息中介观察公司报告时的自愿披露行为。任何处理噪声都会推翻标准理论中关于唯一部分披露均衡的预测。在低披露成本下，尽管存在正成本，模型仍会完全披露。在较高成本下，博弈存在两个阈值均衡，其特征为不同的披露概率。我们刻画了完全披露的成本阈值及均衡集合如何随噪声和基本面不确定性变化。在高披露环境中，不确定性和处理噪声均会降低披露水平，而更高的认证成本反而可能增加披露。将披露成本内生化作为最优费用，揭示了利润最大化的中介如何在不同均衡之间进行选择，可能产生高费用、高披露的制度。具有有界支撑、不确定信息禀赋、内生噪声和竞争性信息源的扩展将相关洞见应用于一般信息环境。研究结果警示我们，不应将更大的摩擦必然解读为减少披露。
英文摘要
We study voluntary disclosure when investors observe firm reports through noisy information intermediaries such as auditors, analysts, rating agencies, or data providers. Any processing noise overturns the standard prediction of a unique partial-disclosure equilibrium. With low disclosure costs, the model unravels to full disclosure despite positive costs. With higher costs, the game admits two threshold equilibria featuring different disclosure probabilities. We characterize how the cost threshold for unraveling and the equilibrium set respond to changes in noise and fundamental uncertainty. In settings with high disclosure, both uncertainty and processing noise reduce disclosure, while higher certification costs can counterintuitively increase it. Endogenizing disclosure costs as optimal fees shows how profit-maximizing intermediaries select among equilibria, potentially generating a high-fee, high-disclosure regime. Extensions with bounded support, uncertain information endowment, endogenous noise, and competing information sources apply the insights to general information environments. The results caution against interpreting greater frictions as necessarily reducing disclosure.
发表机构
- Washington University in St Louis（华盛顿大学圣路易斯分校）
- University of Hong Kong（香港大学）
机构由 AI 辅助整理，请以论文原文为准。
