Does Corporate Governance Improve Bankruptcy Prediction

INTRODUCTION In 1968 Altman's Z-Score was a game changer; this quantitative model was widely accepted and became the norm for bankruptcy prediction for academicians and practitioners. But it also had several skeptics; it spawned numerous research articles with the Z-Score itself coming under intense scrutiny. Over the years it has proven to be sample sensitive, providing inconsistent results for different sample sets and time periods. The original model was developed for firms in the manufacturing industry. Due to the continuous changes and complications in the business environment, non-financial as well as structural factors are contributing to a firm's performance and survival. Over the years several factors have been used as a proxy for the non-financial factors such as corporate governance. Variables such as Board of Director's characteristics, Board Committees, internal control and auditing systems add to the understanding of the firms' corporate governance. Corporate governance can be used as a comprehensive measure for the agency problems that directly affect the firm structure and survival. In this research article we aim to improve the predictability of the Altman model by employing a corporate governance index, a better proxy for the firms' riskiness and/or probability of a firm going bankrupt. Our basic research question is whether or not the addition of corporate governance index would affect, or more specifically, improve, the predictability of the Altman's bankruptcy prediction model using recent data. Bankruptcy prediction would be helpful to investors, creditors, auditors and the capital market in general. The accuracy of predicting the business failure, i.e., bankruptcy, serves as guide and/or warning sign to managers, investors and creditors. We believe that the market will be more confident of audit opinions if it in sync with the bankruptcy prediction. Most studies in the literature used financial ratios, i.e., quantitative measures, as proxy measures for bankruptcy prediction purposes. Our main contribution will be to use a corporate governance index as a non-financial variable to improve the Altman's bankruptcy prediction model. Following the same methodology developed by Altman in his original paper, we use discriminant analysis, to classify subjects of the selected sample into groups (bankrupt firms or non-bankrupt firms) based on the combination of financial and non-financial measures employed. The rest of the paper is organized as follows: Section II is a literature review of two topics: bankruptcy prediction and corporate governance, Section III describes the data selection process and the methodology used, Section IV discusses and analyzes the results, and finally, Section V presents the conclusion and limitations of this study. LITERATURE REVIEW Bankruptcy Prediction Literature Altman (1968) was one of the earliest researchers who aimed at predicting corporate bankruptcy. Altman developed a quantitative bankruptcy prediction model based on five financial ratios. The sample was composed of 66 firms (33 firms filed for bankruptcy and a matched sample of 33 firms). The model accurately predicted bankruptcy 94% in the total sample and 95% accuracy within each group. Altman's results suggested that financial ratios can significantly predict corporate bankruptcy. He concluded by suggesting that this model could be used for business credit evaluations, internal control and serve as an investment guideline. Libby (1975) concluded that traditional confidence in ratio analysis for credit rating seems justified. However, inconsistent results were reported by Casey's (1980) replication of Libby's. The researchers reported that, first, subjects' predictive achievement was significantly lower due to poor performance on bankrupt firms; second, individual differences in information-processing style and confidence level may explain a statistically significant portion of variance in subjects' predictive achievement; third, a composite judge prediction model did not outperform the average subject. …