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.

这个项目继续在早期的NSF资助下开始的关于多阶段游戏的动态和学习的研究。由于实验、寡头垄断实验、讨价还价实验、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通过多阶段博弈进行的，因此更好地理解这些动态对于从数据中得出的各种推论至关重要。该项目开发了一种统一的理论和计量经济学方法，其结构允许对来自多阶段博弈的各种实验数据进行严格分析。理论发展涉及通过引入行动（颤抖）和信念（自制先验和非贝叶斯更新）中的随机误差来修改标准博弈论分析。这些随机组件的不同规格，包括受试者在自己的决策中考虑错误的程度的假设，导致可以使用简单实验游戏的数据严格评估和比较的几种模型。这些可供选择的模型也可以用来严格分析——这是第一次——来自早期实验的数据，这些实验提供了描述性证据，证明了什么似乎是系统性地偏离了完全理性的行为。