This article develops a computational framework to analyze dynamic auctions and uses it to investigate the impact of information sharing among bidders. We show that allowing for the dynamics implicit in many auction environments enables the emergence of equilibrium states that can only be reached when firms are responding to dynamic incentives. The impact of information sharing depends on the extent of dynamics and provides support for the claim that information sharing, even of strategically important data, need not be welfare reducing. Our methodological contribution is to show how to adapt the experience‐based equilibrium concept to a dynamic auction environment and to provide an implementable boundary‐consistency condition that mitigates the extent of multiple equilibria.

中文翻译：

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分析动态拍卖的计算框架：信息共享的市场影响

本文开发了一种计算框架来分析动态拍卖，并使用它来研究投标者之间信息共享的影响。我们表明，允许在许多拍卖环境中隐含的动力学能够使均衡状态的出现，只有在企业响应动态激励时才能达到平衡状态。信息共享的影响取决于动态程度，并为以下主张提供了支持：信息共享，即使是具有战略意义的数据，也不必减少福利。我们在方法论上的贡献是展示如何使基于经验的均衡概念适应动态拍卖环境，并提供可实施的边界一致性条件，以减轻多重均衡的程度。