Imperfect Play and Incomplete Information In Multi-Stage Games: Theory and Experiments

多阶段博弈中的不完美游戏和不完整信息：理论与实验

• 批准号: 9223701
• 负责人: Thomas Palfrey
• 金额: $ 26.19万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-03-15 至 1997-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9223701&HistoricalAwards=false
• 关键词: Imperfect; Play; Incomplete; Information; Multi

This project continues research begun under an earlier NSF grant on the dynamics and learning in multistage games. Since experiments, oligopoly experiments, bargaining experiments, committee experiments, and experiments in many other settings studied by social scientists are conducted by multi-stage games, a better understanding of these dynamics is critical to the kinds of inferences that can be made from the data. This project develops a unified theoretical and econometric approach with a structure that permits the rigorous analysis of diverse experimental data from multi-stage games. The theoretical development involves modification of standard game theoretic analysis by introducing random errors in actions (trembles) and beliefs (home-made priors and non-Bayesian updating). Different specifications of these random components, including assumptions about the degree to which subjects take errors into account in their own decision making, lead to several classes of models which can be rigorously evaluated and compared using data from simple experimental games. These alternative models can also be used to rigorously analyze - for the first time - data from earlier experiments that offer descriptive evidence about what appear to be systematic departures from fully rational behavior.

该项目继续根据早期的NSF拨款开始研究多阶段游戏的动态和学习。 由于实验，寡头实验，议价实验，委员会实验以及社会科学家研究的许多其他环境中的实验都是由多阶段游戏进行的，因此对这些动态的更好理解对于可以根据数据可以做出的这些推论至关重要。 该项目开发了一种统一的理论和计量经济学方法，其结构允许对多阶段游戏的各种实验数据进行严格的分析。 理论发展涉及通过引入动作（颤抖）和信念（自制的先验和非贝斯尼亚更新）的随机错误来修改标准游戏理论分析。 这些随机组件的不同规格，包括对受试者在自己的决策中考虑错误的程度的假设，导致几类模型可以使用简单实验游戏中的数据进行严格评估和比较。 这些替代模型也可以用来严格地分析（首次来自早期实验的数据，这些数据提供了有关似乎有系统地偏离完全理性行为的描述性证据。