基于学习行为的资本结构同伴效应实证研究
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  • 英文篇名:Peer Effects of Capital Structure Decision Based on Learning Behavior:An Empirical Study
  • 作者:张天宇 ; 钟田丽
  • 英文作者:ZHANG Tianyu;ZHONG Tianli;College of Business and Administration,Northeastern University;
  • 关键词:资本结构决策 ; 同伴效应 ; 社会学习理论 ; 中国上市企业 ; 工具变量
  • 英文关键词:capital structure decision;;peer effects;;social learning theory;;Chinese listed firms;;instrumental variable
  • 中文刊名:JCJJ
  • 英文刊名:Journal of Management Science
  • 机构:东北大学工商管理学院;
  • 出版日期:2019-03-20
  • 出版单位:管理科学
  • 年:2019
  • 期:v.32;No.182
  • 基金:国家自然科学基金(71150002)~~
  • 语种:中文;
  • 页:JCJJ201902008
  • 页数:14
  • CN:02
  • ISSN:23-1510/C
  • 分类号:98-111
摘要
资本结构理论通常假设企业最优资本结构是其自身特征的函数,与其他个体无关。但是,已有研究发现同伴企业决策对焦点企业决策产生重要影响,即存在同伴效应。考察中国资本市场上企业资本结构决策是否存在同伴效应以及为何存在同伴效应等重要问题,能够为同伴效应研究提供发展中国家资本市场的经验证据,并拓展国外同伴效应产生机制的相关研究。利用2001年至2014年中国A股沪深两市非金融上市企业面板数据,依据参照组内线性均值模型,以同伴企业股票收益波动作为工具变量解决映射问题,采用个体固定效应和差分变量控制资本结构行业特征对应的关联效应问题,实证检验是否存在同伴效应。为进一步研究同伴效应的学习机制,基于包含同伴信息的决策模型,推导焦点企业的经理人能力、外部环境不确定性、同伴企业信息质量和高管团队信息交流程度4个重要因素如何影响同伴效应的强弱,进行分样本实证数据检验,探索同伴效应是否由学习机制导致。研究结果表明,中国上市企业资本结构决策显著地受同一行业内其他同伴企业资本结构决策影响,存在正向同伴效应;分样本实证检验结果证实,当焦点企业经理人能力较弱、外部环境不确定性较强、同伴信息质量较高和焦点企业高管团队信息交流程度高时,同伴效应较强,这与基于学习行为的资本结构决策模型理论假设吻合,表明对同伴决策的学习行为能够解释中国上市企业资本结构决策的同伴效应。一方面,研究结果从理论上丰富了现有资本结构理论,为企业决策研究提供了一个重要但被忽略的研究角度,深化了同伴效应产生机制的理论和实证研究;另一方面,对监管层具有实践意义,政府机构应恰当运用同伴效应所特有的乘数效应,通过鼓励学习引导有效决策的扩散。
        Modern capital structure theory centers on the assumption that optimal capital structure of a firm depends only on its own individualistic characteristics and that others' actions are totally irrelevant. On the contrary,current studies outside China point out that peer firms' decisions exert significant influence on focal firms' decisions. In other words,peer effects do exist. Investigating whether peer effects of capital structure decision exist in the Chinese capital market and which mechanism leads to peer effects not only provides us with empirical evidence from a developing country,but also extends current mechanism study of peer effects.Using peers' stock return shock as a valid instrumental variable,this paper exploits Linear-in-means regression model on panel data of non-financial Chinese listed firms on Shanghai and Shenzhen A-share stock market from 2001 to 2014. In order to exclude correlated effects,i. e.,co-movement of capital structure decision within industries,differencing variables,along with firm-level fixed effects are applied. In this way,whether peer effects exist is empirically examined. In order to further dig into the learning mechanism,our research introduces the capital structure decision model containing peer information from observational learning and derives the hypotheses on how senior managers' capabilities of focal firms,exterior environmental uncertainties,peers' informational disclosure quality and informational exchange level among TMT of focal firms affect the intensity of peer effects. Basing on comparison between sub-samples analysis and theoretical hypotheses,we are able to explore whether learning causes peer effects.Empirical results show that capital structure of focal firms is significantly influenced by that of peer firms within the same industry. In addition,sub-sample analysis demonstrates that peer effects are stronger when senior managers of focal firms are less competent and exterior operational and financial environmental uncertainties are higher. Similarly,peer effects intensity increases in peer firms' informational quality and the degree of information transfer within focal firms' TMT. In short,sub-sample results speak in favor of all theoretical predictions originated from peer learning decision model. It implies that learning from peers' decisions is a non-negligible explanatory factor of peer effects.Our research,on the one hand,enriches current capital structure theory by providing an important but yet neglected research angle and deepens the study on mechanism in both theory and practice. On the other hand,it has practical implication for regulators in the sense that policy makers would take full advantage of"social multiplier effect"and proliferate effective firm decisions through encouraging learning.
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