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Enforcement actions and their effectiveness in securities regulation: Empirical evidence from management earnings forecasts

机译:执法行动及其在证券监管中的有效性:来自管理层收益预测的经验证据

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Due to resource constraints, securities regulators cannot find or punish all firms that have conducted irregular or even illegal activities (hereafter referred to as fraud). Those who study securities regulations can only find the instances of fraud that have been punished, not those that have not been punished, and it is these unknown cases that would make the best control sample for studies of enforcement action criteria. China’s mandatory management earnings forecasts solve this sampling problem. In the A-share market, firms that have not forecasted as mandated are likely in a position to be punished by securities regulators or are attempting to escape punishment, and their identification allows researchers to build suitable study and control samples when examining securities regulations. Our results indicate that enforcement actions taken by securities regulators are selective. The probability that a firm will be punished for irregular management forecasting is significantly related to proxies for survival rates. Specifically, fraudulent firms with lower return on assets (ROAs) or higher cash flow risk are more likely to be punished. Further analysis shows that selective enforcement of regulations has had little positive effect on the quality of listed firms’ management forecasts.
机译:由于资源的限制,证券监管机构无法发现或惩罚所有进行了不规则甚至非法活动(以下称为欺诈)的公司。那些研究证券法规的人只能找到已经受到惩罚的欺诈实例,而不是那些没有受到惩罚的欺诈实例,正是这些未知的案例才是研究执法行动标准的最佳控制样本。中国的强制性管理收入预测解决了这一抽样问题。在A股市场中,未按预期要求进行预测的公司很可能会受到证券监管机构的惩罚或试图逃避处罚,其身份识别使研究人员可以在研究证券法规时建立适当的研究和控制样本。我们的结果表明,证券监管机构采取的执法行动具有选择性。公司因不定期的管理预测而受到惩罚的可能性与生存率的高低密切相关。具体而言,资产回报率(ROA)较低或现金流量风险较高的欺诈性公司更可能受到惩罚。进一步的分析表明,有选择地执行法规对上市公司的管理预测质量几乎没有积极影响。

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