The role of corporate governance in forecasting bankruptcy: Pre- and post-SOX enactment
Chia-Ying Chan,
De-Wai Chou,
Jane-Raung Lin and
Feng-Ying Liu
The North American Journal of Economics and Finance, 2016, vol. 35, issue C, 166-188
Abstract:
This paper contributes to the literature by documenting the improved performance of bankruptcy prediction models after including corporate governance variables. The empirical results demonstrate better predictive power for financial bankruptcy than previous bankruptcy prediction models, particularly in the post-SOX period. Our theoretical argument emphasizes the urgent need for such improvements to the bankruptcy prediction model following the introduction of the SOX Act, with the empirical results providing intuitive economic meaning for all relevant market participants. Policymakers may consider enacting laws to include designs for corporate governance monitoring mechanisms, entrepreneurs may use this model to improve their own governance structures and compensation mechanisms to avoid financial bankruptcy, and investors may refer to it to ensure that ‘losers’ are excluded from their investment portfolios.
Keywords: Bankruptcy prediction model; Sarbanes-Oxley Act; Corporate governance (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940815000959
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:35:y:2016:i:c:p:166-188
DOI: 10.1016/j.najef.2015.10.008
Access Statistics for this article
The North American Journal of Economics and Finance is currently edited by Hamid Beladi
More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().