2020年新冠肺炎疫情爆發以來，全球經濟則受到嚴重的打擊，且許多大型企業營運週轉不靈因此倒閉，突如其來的黑天鵝事件，帶給經濟許多不可逆的影響，因此過去許多評價模型中存在企業永續經營的假設，將備受質疑，而如何估計一間企業預期倒閉的時間則成為本研究的目標。本研究參考Copeland, Copeland and Song(2021)的企業隱含倒閉時間模型，並且將台灣產業分為民生、車輛、工業、通信和科技產業，計算出台灣企業平均隱含倒閉時間約為32年，而以車輛產業平均39年為最高，且在新冠肺炎期間所有產業平均都有更佳的表現。另外本研究針對隱含倒閉時間計算結果進行迴歸實證，得出影響不同產業隱含倒閉時間的關鍵變數。

Since the outbreak of COVID-19 in 2020, the global economy has been severely hit and many large enterprises have failed to turn around and therefore closed down. The sudden black swan event has had many irreversible effects on the economy, so the assumption of perpetual operation of the enterprise in many evaluation models will be questioned, and how to estimate implied time to failure for Taiwanese firms is the goal of this study.This study refers to Copeland, Copeland and Song(2021) implied mortality model and divides Taiwanese firms into five industries, livelihood, automotive, industrial, communications and technology. The average implied time to failure for Taiwanese firms was calculated to be about 32 years, and the highest average implied time to failure is about 39 years for the automotive industry. In addition, this study conducted a regression to identify the key variables affecting the implied time to failure for different industries.

Altman, Edward I., 1968, Financial Ratios, Discriminant analysis and the prediction of corporate bankruptcy, Journal of Finance 23, 589-609.

Chava, Sudheer, and Robert A. Jarrow, 2004, Bankruptcy prediction with industry effects, Review of Finance 8, 537-569.

Chen, Huafeng, 2011, Firm life expectancy and the heterogeneity of the book-to-market effect, Journal of Financial Economics 100, 402-423.

Copeland, Maggie, Thomas Copeland, and Timothy Copeland, 2017, Revising equity valuation with tail risk, Journal of Portfolio Management 43, 100-111.

Copeland, Maggie, Thomas Copeland, and Koda Song, 2021, Implied mortality for the firm: The market tells the tail, Journal of Portfolio Management 47, 122-134.

Darrat, Ali F., Stephen Gray, Jung Chul Park, and Yanhui Wu, 2016, Corporate Governance and Bankruptcy Risk, Journal of Accounting, Auditing & Finance 31, 163–202.

Fackler, Daniel, Claus Schnabel, and Joachim Wagner, 2012, Establishment exits in Germany: The role of size and age, Small Business Economics 41, 683-700.

Gordon, Myron J., and Eli Shapiro, 1956, Capital equipment analysis: The required rate of profit, Management science 3, 102-110.

Kaplan, Steven N., and Richard S. Ruback, 1995, The valuation of cash flow forecasts: An empirical analysis, Journal of Finance 50, 1059-1093.

Ohlson, James A., 1980, Financial Ratios and the Probabilistic Prediction of Bankruptcy, Journal of Accounting Research 18, 109-131.

Queen, Maggie, and Richard Roll, 1987, Firm mortality: Using market indicators to predict survival, Financial Analysts Journal 43, 9-26.

Shirata, Cindy Yoshiko, 1998, Financial ratios as predictors of bankruptcy in Japan: an empirical research, In Proceedings of The Second Asian Pacific Interdisciplinary Research in Accounting Conference, 437–445.

Shumway, Tyler, 2001, Forecasting bankruptcy more accurately: A simple hazard model, Journal of Business 74, 101-124.

Situm, Mario, 2014, The age and size of the firm as relevant predictors for bankruptcy, Journal of Applied Economics and Business 2, 5–30.

Wu, Y., C. Gaunt, and S. Gray, 2010, A comparison of alternative bankruptcy prediction models, Journal of Contemporary Accounting & Economics 6, 34-45.

中華民國經濟部，經濟部電子報，擷取日期111年6月3日，檢自：https://www.moea.gov.tw/mns/populace/news/EpaperDetail.aspx?volume=20120713

工商時報與中華徵信所，台灣50產業地圖，擷取日期111年6月3日，檢自：https://ctee.com.tw/topic/tw0050