Artikel

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

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.

Sprache
Englisch

Erschienen in
Journal: China Journal of Accounting Research ; ISSN: 1755-3091 ; Volume: 5 ; Year: 2012 ; Issue: 1 ; Pages: 59-81 ; Amsterdam: Elsevier

Klassifikation
Management
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Bureaucracy; Administrative Processes in Public Organizations; Corruption
Accounting
Thema
Enforcement actions
Management earnings forecasts
Irregularities
Selection bias

Ereignis
Geistige Schöpfung
(wer)
Song, Yunling
Ji, Xinwei
Ereignis
Veröffentlichung
(wer)
Elsevier
(wo)
Amsterdam
(wann)
2012

DOI
doi:10.1016/j.cjar.2012.03.003
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Song, Yunling
  • Ji, Xinwei
  • Elsevier

Entstanden

  • 2012

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