기업지배구조가 상장폐지에 미치는 영향 분석: 기업지배구조 평가점수를 중심으로

This paper empirically analyzes the impact of the corporate governance on corporate distress by using the corporate governance scores of KCGS(Korea Corporate Governance Service). The corporate governance scores of 50 delisted companies and 657 listed companies were used for the empirical analysis. The logistic regression model was used for the empirical analysis and whether delisting was used as the dependent variable. In the model, two groups of the independent variables were used. One group was composed of 6 types corporate governance scores and the other group was composed of main 50 types financial ratios in the BOK(Bank of Korea). t-test and correlation analysis were performed for the 50 financial ratios in order to build a logistic regression model effectively, and finally a total of five financial ratios(net income before tax to total assets, dividends to net income, net working capital to total assets, current liabilities ratio, total assets turnover) were chosen as explanatory variables.
Logistic regression analysis are summarized as follows. First, corporate governance has great influence closer to the time of delisting (at year t). If the delisting time is assumed as the year t, the corporate governance at the year t-1 before delisting affected the greatest impact on the delisting. Second, total score, shareholder’s right, disclosure and distribution of business profits in corporate governance scores of the KCGS showed significant results in a negative direction at the 10% significance level for the delisting. And net working capital to total assets and total assets turnover in the financial ratio showed significant results in a negative direction at the 10% significance level for the delisting. Total assets turnover showed a particularly large impact on the results of this relatively delisting compared to other explanatory variables.
The impact of the delisting of financial ratios are generally known that large. In the empirical results of this paper, also impact on the delisting of the financial ratios were relatively large. However, since the model that was combined with corporate governance scores and finance ratios had a lower significance probability and higher explanatory power than the model that was constructed with only financial ratios, the corporate governance scores as well as the financial ratios are expected to contribute enough to determine whether the company distressed. In addition, the logistic regression model presented in this paper can be used to distress prediction model considering the non-financial aspect like the corporate governance. Also the model is expected to find risk factors and prevent corporate distress in advance, and finally to contribute to efficient investment decisions.