本文主要探討臺灣期間利差、國發會所編制的領先指標綜合指數、同時指標綜合指數以及其組成成分對台灣景氣衰退機率的預測能力，資料期間為2001年1月至2019年12月，資料型態為月資料，經PROBIT模型實證結果顯示，當估計期間是針對一至三個月後的景氣狀態做預測，股價指數與同時指標綜合指數與景氣衰退機率有顯著的負向關係；當估計期間是針對一至六個月後的景氣狀態做預測，領先指標綜合指數對於景氣衰退機率有顯著的負向關係；當估計期間是針對六至九個月後的景氣狀態做預測，期間利差對於景氣衰退機率有顯著的負向關係；當估計期間是針對十二個月至二十四個月的景氣狀態，期間利差對於景氣衰退機率有顯著的負向關係，領先指標綜合指數對於景氣衰退機率有顯著的正向關係，而領先指標綜合指數內的外銷訂單動向指數、半導體設備進口值及建築物開工樓面積可能已經失去提供景氣訊號的能力。

一.中文文獻
利秀蘭、陳惠薇(2005)，台灣景氣領先及同時變數之探討，國家發展委員會經濟研究期刊第五期，頁27-53
李承璟(2004)，台股趨勢與景氣指標之分析，台灣大學經濟學研究所學位論文
林大超(2003)，台灣與美國兩地景氣循環指標關聯性之研究，成功大學企業管理研究所學位論文
曾惠淇(2005)，台灣領先指標綜合指數與總體經濟活動關聯性之研究，逢甲大學財務金融研究所學位論文
黃明隆(2011)，貨幣供給、銀行信用與景氣循環及台股指數先後順序關係之探 討，國立東華大學管理學院高階經營管理碩士在職專班學位論文
黃建銘(2012)，利用動態Probit模型預測台灣景氣衰退，中正大學國際經濟研究所學位論文
劉欣姿(2013)，領先指標預測能力之研究，國家發展委員會經濟研究期刊第十三期，頁79-108
劉欣姿(2018)，經濟結構變遷下對台灣景氣同時指標之影響與檢討改進，國家發展委員會經濟研究期刊第十八期，頁1-23
蔡佩珍(2018)，精進領先指標對台灣景氣動向預測之能力，國家發展委員會經濟研究期刊第十八期，頁24-58
簡劭騏(2019)，以Probit模型預測景氣衰退機率，國家發展委員會經濟研究期刊第二十期，頁17-46
簡瑀萱(2014)，以財務與能源變數預測台灣景氣衰退─ Probit模型應用，中正大學國際經濟研究所學位論文

二.英文文獻
Bernard, H., & Gerlach, S. (1998). Does the term structure predict recessions? The international evidence. International journal of finance & economics, 3(3), 195-215.

Bordo, M. D., & Haubrich, J. G. (2008). The yield curve as a predictor of growth: long-run evidence, 1875–1997. The review of economics and statistics, 90 (1), 182-185.

Borio, C. E., Drehmann, M., & Xia, F. D. (2019). Predicting recessions: financial cycle versus term spread, BIS working papers No.818,Basel.

Burns, A. F., and W. C. Mitchell.(1946). Measuring business cycles,New York: National bureau of economic research.

Camacho, M., & Perez‐Quiros, G. (2002). This is what the leading indicators lead. Journal of applied econometrics, 17 (1), 61-80.

Chang, D., Mattson, R. S., & Tang, B. (2019). The predictive power of the user cost spread for economic recession in China and the US. International journal of financial studies, 7(2), 34.

Chauvet, M., & Potter, S. (2005). Forecasting recessions using the yield curve. Journal of forecasting, 24 (2), 77-103.

Diebold, F. X., & Rudebusch, G. D. (1989). Scoring the leading indicators. Journal of business, 369-391.

Diebold, F. X., & Rudebusch, G. D. (1991). Forecasting output with the composite leading index: A real-time analysis. Journal of the American statistical association, 86 (3), 603-610.

Dueker, M. J. (1997). Strengthening the case for the yield curve as a predictor of US recessions. Federal Reserve Bank of St. Louis review, 79 (2), 41.

Estrella, A., & Mishkin, F. S. (1997). The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank. European economic review, 41 (7), 1375-1401.

Fossati, S. (2015). Forecasting US recessions with macro factors. Applied economics, 47(53), 5726-5738.

Giacomini, R., & Rossi, B. (2006). How stable is the forecasting performance of the yield curve for output growth?. Oxford bulletin of economics and statistics, 68, 783-795.

Hao, L., & Ng, E. C. (2011). Predicting Canadian recessions using dynamic probit modelling approaches. Canadian journal of economics revue canadienne d'économique, 44(4), 1297-1330.

Hsu, T. (2016).U.S. recession forecasting using Probit models with asset index predictor variables.Economics department,The university of Maryland Baltimore County.

Kauppi, H., & Saikkonen, P. (2008). Predicting US recessions with dynamic binary response models. The review of economics and statistics, 90 (4), 777-791.

Lange, R. H. (2018). The predictive content of the term premium for GDP growth in Canada: Evidence from linear, Markov-switching and probit estimations. The North American journal of economics and finance, 44, 80-91.

Lin, A. J., Chang, H. Y., & Hsiao, J. L. (2019). Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?. Transportation research part e:Logistics and transportation review, 127, 265-283.

Lucas Jr, Robert.E. (1977). Understanding business cycles.Carnegie-Rochester conference series on public policy,5,7–29.

Nyberg, H. (2010). Dynamic probit models and financial variables in recession forecasting. Journal of forecasting, 29 (1‐2), 215-230.

Stock, J. H., & Watson, M. W. (1991). A Probability Model of the Coincident Economic Indicators . Leading economic indicators: New approaches and forecasting records, K. Lahiri and G. Moore, Eds.

Wright, J. H. (2006). The yield curve and predicting recessions. Finance and economics discussion paper 2006-07 , Board of government of the Federal Reserve.