Cognitive ability in matching with strategic uncertainty: An experimental study

IF 5.2 1区 经济学 Q1 ECONOMICS
Xinquan Hu , Lan Yao
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引用次数: 0

Abstract

Strategyproof mechanisms have become the predominant choice for educational institutions. However, both laboratory experiments and empirical evidence highlight the persistent occurrence of strategic misreporting, leading to adverse consequences. This underscores the need to examine the reporting strategies of students, particularly those with varying cognitive abilities, across different decision environments. We present an experimental comprehension test of reporting strategies using computerized opponents to precisely control the levels of strategic uncertainty. The results reveal that removing strategic uncertainty does not significantly affect truth-telling rates. However, subjects with median cognitive ability are more truthful under strategic uncertainty, especially when information is incomplete. Additionally, providing information about priorities has a negative and significant impact on truth-telling rates. The findings of this research demonstrate that constructing a simplified market environment using computerized agents and providing relevant feedback to students can effectively enhance their understanding of the matching mechanism and nudge them to make optimal strategy choices.
战略不确定性匹配中的认知能力:实验研究
战略防御机制已成为教育机构的主要选择。然而,实验室实验和经验证据都凸显了策略性误报的持续发生,从而导致不良后果。这凸显了研究学生,尤其是认知能力不同的学生在不同决策环境下的报告策略的必要性。我们利用计算机对手精确控制战略不确定性水平,对报告策略进行了实验性理解测试。结果显示,消除策略不确定性并不会显著影响说真话的比率。然而,认知能力处于中位数的受试者在策略不确定性条件下会更真实,尤其是在信息不完整的情况下。此外,提供关于优先级的信息对说真话率也有显著的负面影响。研究结果表明,利用计算机代理构建一个简化的市场环境,并向学生提供相关反馈,可以有效增强他们对匹配机制的理解,促使他们做出最优策略选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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