Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Foreman (2003)
A logistic analysis of bankruptcy within the US local telecommunications industryJournal of Economics and Business, 55
Anthony Santomero (1978)
Financial crisis, institutions and markets in a fragile environment: Edward I. Altman and Arnold W. Sametz, eds., (John Wiley & Sons, New York, 1977) pp. xv + 288Journal of Banking and Finance, 2
Kenneth Kim (1999)
Corporate Governance and the Role of the Securities Regulator in the Aftermath of the Asian Financial CrisisReview of Pacific Basin Financial Markets and Policies, 02
James Ohlson (1980)
FINANCIAL RATIOS AND THE PROBABILISTIC PREDICTION OF BANKRUPTCYJournal of Accounting Research, 18
Simon Johnson, Peter Boone, A. Breach, E. Friedman (2000)
Corporate Governance in the Asian Financial CrisisJournal of Financial Economics, 58
T. Johnsen, R. Melicher (1994)
Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit modelsJournal of Economics and Business, 46
R. Porta, Florencio Silanes, Andrei Shleifer, Robert Vishny (1999)
Investor Protection and Corporate GovernanceChicago Booth: Fama-Miller Working Paper Series
Daniel Martin (1977)
Early warning of bank failure: A logit regression approachJournal of Banking and Finance, 1
Jianguo Chen, Ben Marshall, J. Zhang, S. Ganesh (2006)
Financial Distress Prediction in ChinaReview of Pacific Basin Financial Markets and Policies, 09
Q. Luo, T. Hachiya (2005)
Corporate Governance, Cash Holdings, and Firm Value: Evidence from JapanReview of Pacific Basin Financial Markets and Policies, 08
T. Gestel, B. Baesens, J. Suykens, D. Poel, Dirk-Emma Baestaens, Marleen Willekens (2006)
Bayesian kernel based classification for financial distress detectionEur. J. Oper. Res., 172
Yin‐Hua Yeh, Tsun-siou Lee, Tracie Woidtke (2001)
Family Control and Corporate Governance: Evidence from TaiwanInternational Review of Finance, 2
Yin‐Hua Yeh, Tsun-siou Lee (2004)
Corporate Governance and Financial Distress: Evidence from TaiwanWiley-Blackwell: Corporate Governance: An International Review
M. Zmijewski (1984)
METHODOLOGICAL ISSUES RELATED TO THE ESTIMATION OF FINANCIAL DISTRESS PREDICTION MODELSJournal of Accounting Research, 22
A. Lau (1987)
A 5-State Financial Distress Prediction ModelJournal of Accounting Research, 25
H. Platt (1995)
A Note on Identifying Likely IPO Bankruptcies: A Symphonic ParadoxJournal of Accounting, Auditing & Finance, 10
This study aims to investigate the timescale effects of the corporate governance measure on predicting financial distress of corporations. A new corporate governance measure is adopted in the logistic regression model. Historical data of the companies listed on the Taiwan Stock Exchange Corporation (TSEC) were used in the empirical analysis. The analysis was based on three different prediction horizons comprising one-, two- and three-year horizons. The results confirmed that the accuracy of the logistic regression model for predicting corporate financial distress can be improved by incorporating the corporate governance measure. Moreover, the improvements of the correct rate for classification by incorporating the corporate governance measure increased as the prediction horizon was raised. The improvements of the correct rate for classification by incorporating the corporate governance measure are 2.9%, 4.4% and 5.8% for "Year 1", "Year 2" and "Year 3" models respectively.
Review of Pacific Basin Financial Markets and Policies – World Scientific Publishing Company
Published: Mar 1, 2008
Keywords: Corporate governance financial distress financial ratios logistic regression
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.