Impacts of CEO-employee pay disparity on investor behavior and market dynamics: Evidence from laboratory asset markets

IF 5.2 1区 经济学 Q1 ECONOMICS
Xiaolan Yang , Jiaqi Wang , Shu Chen
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引用次数: 0

Abstract

This study explores the impacts of CEO-to-employee pay disparity on investor behavior and market dynamics using an experimental methodology. We employed two laboratory asset markets with identical company valuations but differing CEO-employee pay ratios. Our findings reveal that a higher pay ratio leads investors to quote higher prices for the company's stock. This effect is driven by two conflicting mechanisms of social preference: inequality aversion, which motivates investors who value fairness to quote lower prices for stocks of companies with high pay ratios, and social comparison, where the high pay ratio prompts investors to compare their wealth with that of CEOs, thus becoming more risk-seeking and quoting higher prices. Moreover, higher pay ratios contribute to increased stock prices, fostering larger market bubbles, enhancing the dispersion of investor opinions, boosting trading volumes, and escalating market volatility. This study enriches our understanding of how asset markets react to CEO-to-employee pay disparities, providing valuable insights for policymakers and market participants.

首席执行官与雇员薪酬差距对投资者行为和市场动态的影响:来自实验室资产市场的证据
本研究采用实验方法探讨首席执行官与员工薪酬差距对投资者行为和市场动态的影响。我们采用了两个公司估值相同但首席执行官与员工薪酬比率不同的实验室资产市场。我们的研究结果表明,薪酬比率越高,投资者对公司股票的报价就越高。这种效应是由两种相互冲突的社会偏好机制驱动的:不平等厌恶和社会比较,前者促使重视公平的投资者为高薪酬比率公司的股票报出较低的价格,后者则促使投资者将自己的财富与首席执行官的财富进行比较,从而变得更加追求风险并报出更高的价格。此外,较高的薪酬比率还有助于提高股票价格,催生更大的市场泡沫,增强投资者意见的分散性,提高交易量,加剧市场波动。这项研究丰富了我们对资产市场如何对首席执行官与员工薪酬差距做出反应的理解,为政策制定者和市场参与者提供了宝贵的见解。
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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