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作 者:侯晓辉[1] 王腾宇 HOU Xiao‑hui;WANG Teng‑yu(School of Economics and Finance of Xi’an Jiaotong University,Xi’an,Shannxi,710061,China)
机构地区:[1]西安交通大学经济与金融学院,陕西西安710061
出 处:《经济管理》2024年第7期168-189,共22页Business and Management Journal ( BMJ )
摘 要:公司欺诈一直是资本市场的难点问题。在2010年达到低点之后,中国A股上市公司欺诈发生概率逐步升高,这是否由机构投资者的监督失效所导致?本文以中国A股2002—2018年上市公司数据为样本,考察了机构投资者持股对公司欺诈行为的影响。研究发现:机构投资者持股比例越高,公司发生欺诈行为的概率越低。在进行稳健性检验和考虑内生性影响之后,结论依然成立。然而,2010年之后机构投资者对企业欺诈行为的抑制作用大幅度减弱,这可能导致了企业欺诈行为“不降反升”;机制分析结果显示,在受教育水平和市场化程度更高的地区,机构投资者的监督作用更强,并且分析师关注度、企业盈利能力和融资约束是主要的作用渠道;异质性分析表明,证券投资基金的监督能力更强,并且总部在中东部地区、非国有企业和当年参与并购的企业,机构投资者持股对企业欺诈行为的抑制作用更显著。最后,本文通过训练六种机器学习模型并与基准回归模型进行交叉验证,进一步支持了基准回归模型设定的有效性和可信性。本文阐述了机构投资者持股抑制公司欺诈行为的作用机制、时变特征和差异化影响,为有效治理公司欺诈行为提供了可行的分析思路。Corporate fraud has always been a challenging issue in the capital market.After reaching a low point in 2010,the probability of corporate fraud in China A‑share listed companies gradually increased.Is this due to the failure of supervisory measures by institutional investors?This study examines the impact of institutional investor ownership on corporate fraud using data from China A‑share listed companies from year 2002 to 2018.The research findings indicate that the higher the proportion of institutional investor ownership,the lower the probability of corporate fraud.Even after robustness and endogeneity tests,the conclusion still holds.Furthermore,the study reveals that the restraining effect of institutional investors on corporate fraud has weakened since 2010,which may have contributed to the increase in the probability of corporate fraud.Mechanism analysis show that institutional investors have a stronger supervisory role in regions with higher levels of education and marketization.Analyst attention,firm profitability,and financing constraints are identified as the main channels through which institutional investors exert their influence.Heterogeneity analysis indicates that securities investment funds demonstrate stronger supervisory capabilities,and institutional investor ownership has a more pronounced restraining effect on corporate fraud in companies headquartered in the eastern and central regions,non‑state‑owned enterprises,and companies involved in mergers and acquisitions during the analyzed period.There are two cultures in statistical modeling for drawing conclusions from data:“data modeling”and“algorithmic modeling”.Data modeling assumes the data is generated by a given model,whereas algorithmic modeling views the data mechanism as unknown.Based on the core principles that“algorithmic modeling”and“data modeling”are complementary,this paper conducts cross‑validation of six machine learning models on a benchmark regression model.The results show that the random forest model
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