企业将之前的糟糕表现归咎于COVID-19,是否会影响利益相关者的预期?

Hrishikesh Desai
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引用次数: 0

摘要

美国证券交易委员会(SEC) S-K条例第503(c)项要求公司在其10-K(年度)或10-Q(季度)SEC文件中的1A项风险因素披露中披露影响其的“最重要”因素。在2019冠状病毒病之前,公司在1A项披露中讨论了流动性、竞争等风险因素。当前的大流行导致COVID-19风险因素作为公司1A项风险因素披露的一部分被广泛讨论。对这一短暂风险因素的“公司特定”讨论是独特的,因为它可以影响其他已经披露的、不那么短暂但对投资者和其他利益相关者重要的风险因素的显著性。使用68家受COVID-19严重打击且先前业绩不佳的公司的样本,我发现,与那些没有以特定方式披露COVID-19风险因素的公司相比,市场对其1A项风险因素披露的反应要积极得多。这些结果表明,利益相关者对公司风险概况的看法在某种程度上是有偏见的,因为在评估公司风险概况时,已经影响到这些公司的不那么短暂但其他重要的风险因素似乎被低估了。我使用精化可能性模型的元理论框架进一步解释了这种偏见。我还提出了一个解决这个问题的方案,其中包括以风险矩阵的形式进行这些披露。JEL分类:G38, M10, M40, M41, M48
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Are Firms Biasing Stakeholder Expectations by Attributing Prior Poor Performance to COVID-19?
Item 503(c) of the United States Securities and Exchange Commission’s (SEC’s) Regulation S-K requires firms to disclose the ‘most significant’ factors that affect them in their Item 1A risk factor disclosures made in their 10-K (annual) or 10-Q (quarterly) SEC filings. Prior to COVID-19, firms discussed risk factors such as liquidity, competition, etc. as part of their Item 1A disclosures. The current pandemic has resulted in the COVID-19 risk factor being widely discussed as part of firms’ Item 1A risk factor disclosures. A ‘firm-specific’ discussion on this transient risk factor is unique in the sense that it can affect the salience of other, already disclosed, less transient but significant risk factors to investors and other stakeholders. Using a sample of 68 firms hard hit by COVID-19 with prior poor performance, I find that market reactions to their Item 1A risk factor disclosures were significantly more positive for firms that disclosed the COVID-19 risk factor in a certain firm-specific manner compared to those that didn’t. These results suggest that stakeholder perceptions of firms’ risk profiles are being biased to some extent as the less transient but other significant risk factors that were already affecting these firms seem to be underweighted by them in evaluating the firms’ risk profiles. I explain this bias further using the meta-theoretical framework of the elaboration likelihood model. I also propose a solution to this problem that involves making these disclosures in the form of risk matrices. JEL Classifications: G38, M10, M40, M41, M48
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CiteScore
3.90
自引率
31.20%
发文量
25
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