會計師簽證意見與公司治理之探討

過去文獻上對於財務危機預警模型的建構，主要採用財務比?為變?，或財務比率輔以公司治理變數為研究方向，本文旨在探討公司治?變?對企業財務危機發生機?之預測能?。本研究以1999?至2007?之106家財務危機公司與212家財務正常公司為研究樣本。本文分別以九種公司治理變數，運用Logistic 迴歸分析，探討公司治?變?對企業財務危機發生機?之預測能?。研究結果顯示，就股權結構指標??，以董監事持股比率對於財務危機發生機?的負向影響，董監事設質比率對財務發生機率為正向影響，且在研究期間皆達1%顯著水準。內部人員異動變?方面，以總經理或董事長異動對財務危機機?有顯著的正向影響。就外部監督機構變???，以會計師事務所更換後審查意見變佳對財務危機機?有最為顯著的正向影響。在模型預測正確?方面，對財務危機預測正確機?分別為前半?為86.8%，前一?為84.6%，前一?半為82.4%，前二?為81.4%，前二?半為77.8%，前三?為75.2%。本文的發現對於財務危機預警模型的建構，具有重要的啟示與貢獻。

In contrast the traditional modeling of financial distress construction in the firm level using financial ratio variables or accompanied by corporate governance variables, this paper only uses corporate governance variables to construct models for probability of business financial distress. We adopted 106 companies of financial distress and 212 healthy companies to be our samples during the period 1999 to 2007. For matching is used in the analysis, we construct 9 corporate governance variables, and then use the logistic regression to examine the effects of corporate governance variables on the predictive power of financial distress probability. The empirical results show that, for ownership structure index, ratio of director ownership has a negative effect on financial distress while pledging ratio of shareholdings of directors and supervisors has a positive effect, and both reach a significant level of 1% during the period of research. For interior personnel change variables, reshuffle of general manager or board director has a significantly positive effect on financial distress. For variables of exterior corporate governance institution, positive CPA’s opinion after CPA switch has a significantly positive effect on financial distress. For accuracy of model prediction, the predicted probability of financial crisis for the distressed companies in the sample is 86.8%, 84.6%, 82.4%, 81.4%, 77.8% and 75.2% for half a year, one year, one and a half years, two years, two and a half years and three years before the financial distress, respectively. This finding has a substantial implication and contribution to the financial warning modeling of corporate distress.