An Exploration of Behavior in Dynamic Games

动态博弈中行为的探索

• 批准号: 1629193
• 负责人: Emanuel Vespa
• 金额: $ 19.29万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1629193&HistoricalAwards=false
• 关键词: Exploration; Behavior; Dynamic; Games

Economic models of dynamic environments are highly important for forming policy, and applied theory for these settings has been influential across the entire economic spectrum: public finance, environmental economics, macroeconomics, labor economics, and industrial organization. However, while economic theory for dynamic environments is well-developed, in general it does not provide a precise prediction. Quite the opposite. General theorems instead indicate that most anything can happen in a dynamic environments, dependent on how the participants react to both contemporaneous features of the environment (prices, the number of other competitors in an industry, atmospheric pollutants) and observed features of the past (in particular, other actors behavior). To deal with indeterminacy in the predictions applied economic theory has instead relied on strong assumption - for the most part untested. These assumptions serve to examine both theorized effects from a policy change, but also to produce estimates for use in policy. While these assumptions can make complex environments tractable, failure of the assumption has the potential to produce very different policy outcomes than those posited. Where a societal gain was predicted, a loss may instead be observed. This project's aim is to use controlled observations of human behavior in dynamic environments to examine when these theoretical assumptions are likely to hold true. Greater insight into what features of the environment drive will allow for more-robust policy discussions, and a subsequent benefit to society from better economic policy.The project addresses a topic with growing applied interest in economics, but where theory does not (generically) make precise predictions. It will provide evidence from human behavior, with the overarching aim being the construction of predictive selection criteria to indicate in which settings the standard assumptions are likely to hold true. Further, in those settings where the standard assumptions fail, the project aims to provide evidence for alternatives. Such alternatives can provide greater power when specifying alternative hypotheses. In this project, the PIs propose a series of experiments that will examine behavior in dynamic strategic environments. Four sub-projects are proposed: i) an examination of how uncertainty over other participants' strategic choices affects selection; ii) an examination of the extent to which teams and individuals behave differently in these settings; iii) an examination of the information revealed by self-interested experts across a long-run relationship; and iv) an examination of the effects on behavior from the number of active participants in an environment. In all four sub-projects, the PIs construct a simple baseline environment, and several modifications of it, each of which is chosen to isolate and measure the effects from a relevant feature of interest.Broader impacts from the study follow from a greater understanding of which facets of a strategic environment lead humans to focus on observations from the recent past (historical outputs, prices, extraction levels, etc.) to determine their present actions, as opposed to current conditions (input prices, demand, number of competitors, etc.). In terms of policy, the results aim to produce evidence-based criteria for the most-common assumptions in the applied literature on dynamic games. Greater insight into what drives selection will allow for more-robust policy discussions, and subsequent benefits to society.

动态环境的经济模型对于制定政策至关重要，这些环境的应用理论在整个经济领域都具有影响力：公共金融，环境经济学，宏观经济学，劳动经济学和工业组织。但是，尽管动态环境的经济理论已经发达了，但总的来说，它并没有提供确切的预测。相反。相反，通用定理表明，大多数事情都可以在动态环境中发生，这取决于参与者对环境的同时特征的反应（价格，行业中其他竞争对手的数量，大气污染物）和过去观察到的特征（尤其是其他参与者行为）。在应用经济理论的预测中处理不确定性的是，在大多数情况下未经测试。这些假设可用于检查政策变化的理论效应，同时也可以产生用于政策使用的估计。尽管这些假设可以使复杂的环境可处理，但该假设的失败有可能产生与假设的政策结果截然不同的结果。在预测社会收益的地方，可能会观察到损失。该项目的目的是利用对动态环境中人类行为的受控观察来检查这些理论假设何时可能成立。更深入地了解环境驱动器的哪些特征将允许更加努力的政策讨论，以及随后从更好的经济政策中对社会带来的好处。该项目解决了一个对经济学的应用兴趣越来越大的话题，但是理论（一般而言）并没有做出精确的预测。它将提供人类行为的证据，总体目的是构建预测性选择标准，以指出标准假设可能成立的设置。此外，在标准假设失败的情况下，该项目旨在为替代方案提供证据。在指定替代假设时，这种替代方案可以提供更大的功率。在这个项目中，PI提出了一系列实验，这些实验将检查动态战略环境中的行为。提出了四个子项目：i）检查其他参与者的战略选择的不确定性如何影响选择； ii）检查团队和个人在这些环境中的行为的程度； iii）对长期关系中自我利益专家揭示的信息的检查； iv）检查环境中活跃参与者人数对行为的影响。 In all four sub-projects, the PIs construct a simple baseline environment, and several modifications of it, each of which is chosen to isolate and measure the effects from a relevant feature of interest.Broader impacts from the study follow from a greater understanding of which facets of a strategic environment lead humans to focus on observations from the recent past (historical outputs, prices, extraction levels, etc.) to determine their present actions, as opposed to current conditions (input prices, demand, number of竞争对手等）。在政策方面，结果旨在为动态游戏的应用文献中最常见的假设提供基于证据的标准。更深入地了解哪些驱动器选择将允许进行更稳健的政策讨论以及随后对社会的利益。