Collaborative Research: New Applications of Dynamic Games with Asymmetric Information: Mergers, Capacity Discipline and Price Rigidity

合作研究：信息不对称动态博弈的新应用：兼并、容量约束和价格刚性

• 批准号: 1658613
• 负责人: Lawrence Mazur
• 金额: $ 4.89万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1658613&HistoricalAwards=false
• 关键词: Collaborative; Research; New; Applications; Dynamic

This research investigates how asymmetric information between firms can affect prices and consumer welfare, and how antitrust policies might be changed to account for these effects. Currently almost all analyses of markets -- whether to quantify market power or perform counterfactuals -- assume complete information, in which all firms know the demand, the marginal costs and the objectives of their rivals exactly. However, if firms know more about their own positions, then they might try to use their pricing or capacity choices to influence what their rivals believe in order to affect how those rivals might behave in the future. Some simple examples suggest that even small amounts of asymmetric information can distort prices significantly, and potentially explain why prices rise significantly after mergers; why prices appear rigid even when menu costs should be small; and, why some industries, such as airlines, appear to go through periods of capacity discipline. This research will make theoretical, empirical and methodological contributions. The investigators first characterize non-collusive Markov Perfect Bayesian equilibria in multi-period oligopoly pricing, bidding and capacity choice games with asymmetric information. The project further develops computational methods to solve such equilibria, which often require solving very large numbers of differential equations. The associated code will be made available to other researchers. The investigators also test and calibrate the models using scanner data on consumer packaged goods and data on capacity investments in airline markets. In addition, the project analyzes changes in prices and firm behavior around actual mergers to understand whether asymmetric information can explain why outcomes were significantly different from what the antitrust authorities expected when the mergers were approved. Lastly, this research trains graduate students so that they can use these and other techniques in their own research.

这项研究调查了公司之间的不对称信息如何影响价格和消费者福利，以及如何更改反托拉斯政策以解决这些影响。 目前，几乎所有对市场的分析（是量化市场力量还是执行反事实）都采用完整的信息，在这些信息中，所有企业都知道竞争对手的需求，边际成本和目标。但是，如果公司对自己的立场有了更多的了解，那么他们可能会尝试利用自己的定价或能力选择来影响竞争对手所相信的东西，以影响这些竞争对手将来的行为。 一些简单的例子表明，即使少量的不对称信息也会大大扭曲价格，并有可能解释为什么在合并后价格显着上涨。为什么即使菜单成本应该很小，价格也显得很僵硬？而且，为什么某些行业（例如航空公司）似乎经历了能力纪律的时期。 这项研究将做出理论，经验和方法论贡献。调查人员首先将非集中的马尔可夫完美贝叶斯均衡表征在多周期寡头定价，竞标和能力选择游戏中，并具有非对称信息。该项目进一步开发了解决这种均衡的计算方法，该方法通常需要解决大量的微分方程。相关的代码将提供给其他研究人员。调查人员还使用扫描仪数据测试和校准了有关消费者包装商品以及有关航空公司市场能力投资的数据的模型。此外，该项目还分析了实际合并周围价格和公司行为的变化，以了解不对称信息是否可以解释为什么结果与批准合并后预期的反托拉斯当局的预期有显着差异。最后，这项研究对研究生进行培训，以便他们可以在自己的研究中使用这些技术和其他技术。