An Experimental Examination of Models of Bounded Rationality

对经济学之外的“理性选择理论”的怀疑是基于这样一种信念，即人们会犯错，并期望他人以一种不可完全预测的方式行事。经济学家已经开始认真对待这些批评，最近的理论研究发现了许多情况，在这些情况下，即使是与完全理性的决策很小的偏离，也可能导致预期收益的格局发生戏剧性变化。在预期收益函数的斜率对不影响纳什均衡基本结构的参数敏感的市场或博弈中，“有限理性”的影响尤为重要。这个项目使用实验室实验来评估经济学家广泛感兴趣的一系列情况下的行为：不完美的价格竞争、协调、拍卖和互动模型。在每种情况下，均衡和动态学习模型的理论预测都是在一个极端的完全理性和另一个极端的完全随机决策的普遍背景下推导出来的。任何看过嘈杂实验室数据的人都知道，大多数人的行为都在这两个极端之间，这种直觉可以通过指定模型来评估，这种模型允许对误差和实验室数据中的学习参数进行计量经济学估计。这些实验受到“嘈杂”均衡和学习模型的谨慎激励，因此处理方法的变化对纳什均衡没有影响，但它们确实改变了基于有限理性模型的预测。该提案中报告的初始数据模式与动态轨迹和最终预测的均衡水平都很好地吻合。这项研究的一个目标是提供一个数据基础，以仔细记录的经验规则为指导，刺激关于战略行为的进一步理论工作。

Skepticism about "rational choice theory" outside of economics is based on the conviction that people make mistakes and expect others to behave in a manner that is not perfectly predictable. Economists have started to take these criticisms seriously, and recent theoretical research has identified numerous situations in which even small departures from perfectly-rational decision making can cause a dramatic change in the landscape of expected payoffs. The effects of "bounded rationality" are particularly important in markets or games where the slopes of expected payoff functions are sensitive to parameters that do not affect the underlying structure of the Nash equilibria. This project uses laboratory experiments to evaluate behavior in a series of situations of wide interest to economists: imperfect price competition, coordination, auctions, and interactive models. In each case, the theoretical predictions of both equilibrium and dynamic learning models are derived in a generalized context that spans perfect rationality in one extreme and perfectly random decision making in the other. Anyone who has looked at noisy laboratory data knows that most human behavior lies somewhere in between these extremes, and this intuition can be evaluated by specifying models in a manner that permits econometric estimation of error and learning parameters from laboratory data.The experiments are carefully motivated by "noisy" equilibrium and learning models, so that the treatment changes have no effect on the Nash equilibria, but they do alter the predictions based on models of bounded rationality. Initial data patterns reported in this proposal conform nicely to both the dynamic trajectories and eventual equilibrium levels predicted. One goal of this research is to provide a data base that will stimulate further theoretical work on strategic behavior that is guided by carefully documented empirical regularities.