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重新审视中国的非对称匹配硬币矛盾。

Revisiting the Asymmetric Matching Pennies Contradiction in China.

作者信息

Leng Ailin, Lian Zeng, Lien Jaimie W, Zheng Jie

机构信息

Center for Economic Research, Shandong University, Jinan 250100, China.

International Business School, Beijing Foreign Studies University, Beijing 100089, China.

出版信息

Behav Sci (Basel). 2023 Sep 12;13(9):757. doi: 10.3390/bs13090757.

Abstract

The asymmetric matching pennies contradiction posits that contrary to the prediction of mixed-strategy Nash equilibrium, experimental subjects' choices are, in practice, based heavily on the magnitudes of their own payoffs. Own-payoff effects are robustly confirmed in the literature. Closely following the experimental setups in the literature which support the contradiction, we conduct a series of asymmetric matching pennies games in China, hypothesizing play which is closer to equilibrium frequencies than previously found. Contrary to previous experiments which were conducted in the United States, we find that there are essentially no own-payoff effects among Row players who face large payoff asymmetry. In a Quantal Response Equilibrium framework allowing for altruism or spite, the behavior of our subjects corresponded to a positive spite parameter, whereas the results of previous studies corresponded to altruism. Our results may be consistent with recent psychology literature that finds people from collectivist cultures are substantially more adept at taking the perspective of others compared with people from individualist cultures, a feature of the reasoning needed to obtain mixed-strategy equilibrium.

摘要

非对称匹配硬币矛盾表明,与混合策略纳什均衡的预测相反,在实践中,实验对象的选择很大程度上基于他们自身收益的大小。自身收益效应在文献中得到了有力证实。紧密遵循文献中支持该矛盾的实验设置,我们在中国进行了一系列非对称匹配硬币博弈,假设博弈行为比之前发现的更接近均衡频率。与之前在美国进行的实验相反,我们发现,在面临巨大收益不对称的行参与者中,基本上不存在自身收益效应。在一个允许利他主义或恶意的量子响应均衡框架中,我们实验对象的行为对应着一个正的恶意参数,而之前研究的结果对应着利他主义。我们的结果可能与最近的心理学文献一致,该文献发现,与来自个人主义文化的人相比,来自集体主义文化的人在从他人角度思考方面要熟练得多,这是获得混合策略均衡所需推理的一个特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12a4/10525248/a6107df8813f/behavsci-13-00757-g001.jpg

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