過去文獻上對於財務危機預警模型的建構,主要採用會計報表上之比率變數,本文旨在探討盈餘管理指標、會計比率與公司治理變數對企業財務危機發生機率之預測能力。本研究以1998年至2004年之63家財務危機公司與126家財務正常公司為研究樣本。本文分別建構七種財務預警模型,並運用Logistic迴歸分析,探討盈餘管理指標、會計比率與公司治理變數所組成之各種模型對企業財務危機發生機率之預測能力。研究結果顯示,就盈餘管理指標來說,裁決性應計項目對於財務危機發生機率的正向影響,在不同模型下顯著水準不一致,就會計資訊變數來說,以現金流量比率對財務危機機率有最顯著的負向影響。就公司治理變數來說,以董監事持股質押比率對財務危機機率有最為顯著的正向影響。而由會計比率、公司治理及盈餘管理指標所建構的財務預警模型比其他模型有最佳的預測正確率,對財務危機預測正確機率分別為前一年為95.24%,前二年為84.13%,前三年為71.43%。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 to the traditional modelling of financial distress construction in the firm level using only accounting ratio variables in financial statements, this paper uses earnings management index, accounting variables, and corporate governance variables to construct models for business financial distress. We adopted 63 companies of financial distress and 126 healthy companies to be our samples during the period 1998 to 2004. For matching is used in the analysis, we construct 7 warning models for financial distress, and then use the logistic regression to examine the effects of earnings management index, accounting ratio variables and corporate governance variables on the predictive power of financial distress. The empirical results show that, for earnings management index, discretionary accruals item has positive effect on financial distress, but the significant level is not consitent in different models. For accounting ratio variables, the cash flow ratio has significantly negative effect on financial distress probability. For corporate governance variables, the pledging ratio of shareholdings of directors and supervisors has significantly positive effect on financial distress probability. The financial early warning model constructed using earnings management index, accounting variables and corporate governance variables has the highest predictive power of accuracy. The predicted probability of financial crisis for the distressed companies in the sample is 95.24%, 84.13% and 71.4% for one year, two 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.
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