【2h】

Maximization learning and economic behavior

机译:最大化学习和经济行为

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摘要

The rationality assumption that underlies mainstream economic theory has proved to be a useful approximation, despite the fact that systematic violations to its predictions can be found. That is, the assumption of rational behavior is useful in understanding the ways in which many successful economic institutions function, although it is also true that actual human behavior falls systematically short of perfect rationality. We consider a possible explanation of this apparent inconsistency, suggesting that mechanisms that rest on the rationality assumption are likely to be successful when they create an environment in which the behavior they try to facilitate leads to the best payoff for all agents on average, and most of the time. Review of basic learning research suggests that, under these conditions, people quickly learn to maximize expected return. This review also shows that there are many situations in which experience does not increase maximization. In many cases, experience leads people to underweight rare events. In addition, the current paper suggests that it is convenient to distinguish between two behavioral approaches to improve economic analyses. The first, and more conventional approach among behavioral economists and psychologists interested in judgment and decision making, highlights violations of the rational model and proposes descriptive models that capture these violations. The second approach studies human learning to clarify the conditions under which people quickly learn to maximize expected return. The current review highlights one set of conditions of this type and shows how the understanding of these conditions can facilitate market design.
机译:尽管可以发现系统地违反了其预测的事实,但主流经济学理论基础上的合理性假设已被证明是一个有用的近似。就是说,理性行为的假设对于理解许多成功的经济制度的运作方式很有用,尽管真实的人类行为系统地缺乏完美理性也是正确的。我们考虑这种明显不一致的可能解释,这表明基于合理性假设的机制在创建一种环境时会成功,在这种环境中,他们尝试促进的行为会导致平均所有代理人获得最佳回报,而大多数的时间。基础学习研究的回顾表明,在这种情况下,人们可以快速学习以最大化预期回报。这篇评论还表明,在许多情况下,经验并不能增加最大化。在许多情况下,经验会导致人们偏重一些罕见事件。此外,当前的论文表明,区分两种行为方法以改进经济分析是很方便的。在对判断和决策感兴趣的行为经济学家和心理学家中,第一个也是更常规的方法突出显示了对理性模型的违反,并提出了描述性模型来捕捉这些违反。第二种方法研究人类学习,以阐明人们快速学习以最大化预期回报的条件。当前的评论重点介绍了一组此类条件,并说明了对这些条件的理解如何有助于市场设计。

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