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題名 台灣景氣轉折點預測-Probit模型與組合預測的應用
Forecasting the Turning Points of Taiwan Business Cycles by using Probit Model and Combined Forecasts作者 李勁宏 貢獻者 徐士勛
李勁宏關鍵詞 景氣轉折點
Probit模型
期間利差
領先指標
組合預測
business cycle turning point
Probit model
yield spread
leading indicator
combination forecasting日期 2015 上傳時間 13-Jul-2015 11:16:25 (UTC+8) 摘要 本文使用具有事前訊息的領先指標與期間利差作為預測變數,根據不同利差與落後期選擇的 Probit 模型,利用遞迴的方式預測景氣轉折點發生機率,並進一步將個別預測結果進行組合,試圖找出能降低不確定性且優於個別預測結果的方法。實證結果發現,使用 Diebold and Mariano 檢定的預測包容法為其中最優的組合方法,無論是轉折點訊號或預測誤差都能優於半數以上的個別預測。此外,本文亦估計即期景氣轉折點的發生機率,根據模型的估計結果推斷,自 2012 年 2 月至 2015 年 3 月為止,景氣仍處於擴張階段。 參考文獻 何棟欽(2011),影響景氣循環的因素,台灣經濟論衡,9,55-82。徐之強、黃裕烈(2005)，運用領先指標預測景氣變化之研究，行政院經濟建設委員會委託研究報告。徐志宏、周大森(2010),近期台灣景氣循環峰谷之認定,經濟研究,10,1-35。劉瑞文、管中閔、陳思寬(2014),台灣真實經濟成長率的估計:卡門過濾法之應用,應用經濟論叢,95,1-33。Bry and Boschan(1971). Cyclical analysis of times series: selected procedures and computer programs. NBER.Chikako and Turgut (2011).Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast CombinationsC. Primo, C. A. T. Ferro , I. T. Jolliffe and D. B. Stephenson (2008).Combination and Calibration Methods for Probabilistic Forecasts of Binary Events. Working Paper.Christian R. Proano and Thomas Theobald(2014). Predicting recessions with a composite real-time dynamic probit model. International Journal of Forecasting ,30,898-917.C. Genest , Zidek and J. V. (1986). Combining probability distributions: A critique and an annotated bibliography. Statistical Science, 1, 114-148.Estrella, A. and Hardouvelis, G. A. (1991). The term structure as a predictor of real economic activity. Journal of Finance, 46, 555-576.Estrella, A. and Mishkin, F. S. (1998). Predicting US recessions: financial variables as leading indicators. Review of Economics and Statistics,80, 45-61.Henri Nyberg (2010). Dynamic probit models and financial variables in recession forecasting. Journal of ForecastingH. Nyberg (2010). Dynamic probit models and financial variables in recession forecasting. Journal of Forecasting, 29, 215-230.J. Scott Armstrong(2001).Combining forecasts Principles of forecasting. 417-439Joseph Atta-Mensah and Greg Tkacz(1998). Predicting Canadian Recessions Using Financial Variables: A Probit Approach. Working Papers 98-5, Bank of Canada.Kauppi, H. and Saikkonen, P. (2008). Predicting US recessions with dynamic binary response models. The Review of Economics and Statistics, 90,777–791.Monica Billio , Roberto Casarin, Francesco Ravazzolo and Herman K. van Dijk(2011).Econometrics and Tinbergen InstitutesR. T. Clemen and R. L. Winkler(1987). Calibrating and combining precipitation probability forecasts.Probability and Bayesian Statistics ,97-110.Rudebusch, G. D. and Williams, J. C. (2009). Forecasting recessions: the puzzle of the enduring power of the yield curve. Journal of Business and Economic Statistics, 27(4), 492-503.Roopesh Ranjan and Tilmann Gneiting(2008).Combining Probability Forecasts,Technical Report, 543Thomas Theobald(2012).Combining Recession Probability Forecasts from a Dynamic Probit Indicator.Macroeconomic Policy Institute.T. S. Wallsten , D. V. Budescu , I. Erev and A. Diederich (1997): Evaluating and Combining Subjective Probability Estimates. Journal of Behavioral Decision Making, 10, 243-268.Rudebusch, G. D. and Williams, J. C. (2009). Forecasting recessions: the puzzle of the enduring power of the yield curve. Journal of Business and Economic Statistics, 27(4), 492-503.Roopesh Ranjan and Tilmann Gneiting(2008).Combining Probability Forecasts,Technical Report, 543Timmermann, A. (2006). Forecast combinations. In Handbook of economic forecasting ,135-196.Ulrich Fritsche and Vladimir Kuzin, (2005). Prediction of Business Cycle Turning Points in Germany,Journal of Economics and Statistics 225(1), 22-43.Wright, J.H. (2006). The yield curve and predicting recessions. Technical report, Division of Monetary Affairs, Federal Reserve Board. 描述 碩士
國立政治大學
經濟學系
102258035
103資料來源 http://thesis.lib.nccu.edu.tw/record/#G0102258035 資料類型 thesis dc.contributor.advisor 徐士勛 zh_TW dc.contributor.author (Authors) 李勁宏 zh_TW dc.creator (作者) 李勁宏 zh_TW dc.date (日期) 2015 en_US dc.date.accessioned 13-Jul-2015 11:16:25 (UTC+8) - dc.date.available 13-Jul-2015 11:16:25 (UTC+8) - dc.date.issued (上傳時間) 13-Jul-2015 11:16:25 (UTC+8) - dc.identifier (Other Identifiers) G0102258035 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76469 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 102258035 zh_TW dc.description (描述) 103 zh_TW dc.description.abstract (摘要) 本文使用具有事前訊息的領先指標與期間利差作為預測變數,根據不同利差與落後期選擇的 Probit 模型,利用遞迴的方式預測景氣轉折點發生機率,並進一步將個別預測結果進行組合,試圖找出能降低不確定性且優於個別預測結果的方法。實證結果發現,使用 Diebold and Mariano 檢定的預測包容法為其中最優的組合方法,無論是轉折點訊號或預測誤差都能優於半數以上的個別預測。此外,本文亦估計即期景氣轉折點的發生機率,根據模型的估計結果推斷,自 2012 年 2 月至 2015 年 3 月為止,景氣仍處於擴張階段。 zh_TW dc.description.tableofcontents 1 前言 12 文獻回顧 32.1 景氣循環預測相關文獻 32.2 組合預測相關文獻 43 研究方法與模型 53.1 Probit模型 53.2 組合預測方法 63.2.1 簡單平均加權法 73.2.2 Theobald兩階段加權法 83.2.3 最小平方加權法 93.2.4 預測包容加權法 94 實證模型結果 124.1 資料來源與分析 124.2 樣本內個別預測評估 134.3 樣本外組合預測評估 144.4 不同模型結果比較與預測表現檢定 164.5 轉折點機率預測 165 結論 17參考文獻 18圖目錄1 古典循環與成長循環是意圖 212 樣本內個別向前預測1、2、3個月衰退機率 263 樣本外衰退機率組合預測 294 樣本外衰退機率組合預測 305 第14次景氣循環轉折點預測 33表目錄1 已認定之台灣景氣循環基準日期 212 領先指標與同時指標高峰谷底比較 223 向前預測1個月樣本內Probit模型配適結果 234 向前預測2個月樣本內Probit模型配適結果 245 向前預測3個月樣本內Probit模型配適結果 256 樣本內個別預測評估 277 樣本外組合結果評估 288 樣本外評估與結果比較 319 Diebold-Mariano檢定統計量 32 zh_TW dc.format.extent 1417164 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0102258035 en_US dc.subject (關鍵詞) 景氣轉折點 zh_TW dc.subject (關鍵詞) Probit模型 zh_TW dc.subject (關鍵詞) 期間利差 zh_TW dc.subject (關鍵詞) 領先指標 zh_TW dc.subject (關鍵詞) 組合預測 zh_TW dc.subject (關鍵詞) business cycle turning point en_US dc.subject (關鍵詞) Probit model en_US dc.subject (關鍵詞) yield spread en_US dc.subject (關鍵詞) leading indicator en_US dc.subject (關鍵詞) combination forecasting en_US dc.title (題名) 台灣景氣轉折點預測-Probit模型與組合預測的應用 zh_TW dc.title (題名) Forecasting the Turning Points of Taiwan Business Cycles by using Probit Model and Combined Forecasts en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 何棟欽(2011),影響景氣循環的因素,台灣經濟論衡,9,55-82。徐之強、黃裕烈(2005)，運用領先指標預測景氣變化之研究，行政院經濟建設委員會委託研究報告。徐志宏、周大森(2010),近期台灣景氣循環峰谷之認定,經濟研究,10,1-35。劉瑞文、管中閔、陳思寬(2014),台灣真實經濟成長率的估計:卡門過濾法之應用,應用經濟論叢,95,1-33。Bry and Boschan(1971). Cyclical analysis of times series: selected procedures and computer programs. NBER.Chikako and Turgut (2011).Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast CombinationsC. Primo, C. A. T. Ferro , I. T. Jolliffe and D. B. Stephenson (2008).Combination and Calibration Methods for Probabilistic Forecasts of Binary Events. Working Paper.Christian R. Proano and Thomas Theobald(2014). Predicting recessions with a composite real-time dynamic probit model. International Journal of Forecasting ,30,898-917.C. Genest , Zidek and J. V. (1986). Combining probability distributions: A critique and an annotated bibliography. Statistical Science, 1, 114-148.Estrella, A. and Hardouvelis, G. A. (1991). The term structure as a predictor of real economic activity. Journal of Finance, 46, 555-576.Estrella, A. and Mishkin, F. S. (1998). Predicting US recessions: financial variables as leading indicators. Review of Economics and Statistics,80, 45-61.Henri Nyberg (2010). Dynamic probit models and financial variables in recession forecasting. Journal of ForecastingH. Nyberg (2010). Dynamic probit models and financial variables in recession forecasting. Journal of Forecasting, 29, 215-230.J. Scott Armstrong(2001).Combining forecasts Principles of forecasting. 417-439Joseph Atta-Mensah and Greg Tkacz(1998). Predicting Canadian Recessions Using Financial Variables: A Probit Approach. Working Papers 98-5, Bank of Canada.Kauppi, H. and Saikkonen, P. (2008). Predicting US recessions with dynamic binary response models. The Review of Economics and Statistics, 90,777–791.Monica Billio , Roberto Casarin, Francesco Ravazzolo and Herman K. van Dijk(2011).Econometrics and Tinbergen InstitutesR. T. Clemen and R. L. Winkler(1987). Calibrating and combining precipitation probability forecasts.Probability and Bayesian Statistics ,97-110.Rudebusch, G. D. and Williams, J. C. (2009). Forecasting recessions: the puzzle of the enduring power of the yield curve. Journal of Business and Economic Statistics, 27(4), 492-503.Roopesh Ranjan and Tilmann Gneiting(2008).Combining Probability Forecasts,Technical Report, 543Thomas Theobald(2012).Combining Recession Probability Forecasts from a Dynamic Probit Indicator.Macroeconomic Policy Institute.T. S. Wallsten , D. V. Budescu , I. Erev and A. Diederich (1997): Evaluating and Combining Subjective Probability Estimates. Journal of Behavioral Decision Making, 10, 243-268.Rudebusch, G. D. and Williams, J. C. (2009). Forecasting recessions: the puzzle of the enduring power of the yield curve. Journal of Business and Economic Statistics, 27(4), 492-503.Roopesh Ranjan and Tilmann Gneiting(2008).Combining Probability Forecasts,Technical Report, 543Timmermann, A. (2006). Forecast combinations. In Handbook of economic forecasting ,135-196.Ulrich Fritsche and Vladimir Kuzin, (2005). Prediction of Business Cycle Turning Points in Germany,Journal of Economics and Statistics 225(1), 22-43.Wright, J.H. (2006). The yield curve and predicting recessions. Technical report, Division of Monetary Affairs, Federal Reserve Board. zh_TW
