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題名: | 三分類Qual VAR模型-美國景氣預測之應用 | 作者: | 蔡郁敏 Tsai,Yu-Min |
貢獻者: | 鍾經樊 Chung,Ching-Fan 蔡郁敏 Tsai,Yu-Min |
關鍵詞: | 景氣循環 屬質變數 Qual VAR Gibbs sampling Probit Model |
日期: | 2004 | 上傳時間: | 14-九月-2009 | 摘要: | 追求長期穩定的經濟成長是每個國家欲追求的目標,在經濟發展過程中,外在衝擊常常導致經濟體系的景氣循環波動,而短期間景氣循環的大幅波動將不利於經濟體系穩定發展,因為民眾的消費、廠商的投資決策以及政府政策的規劃與實施,都深深受到景氣變動的影響。因此準確預測景氣動向,深受經濟學者、政府以及一般民眾的重視。\r\n 預估景氣循環擴張和衰退持續期間的長短並不容易,由美國國家經濟研究局 提供的資料得知,第二次世界大戰後,美國景氣擴張最長的時間,曾經延續了一百零六個月,而最短的則只有十二個月;在景氣衰退方面,最短是六個月,最長則為十六個月。而二次大戰前,時間變化的幅度就更大了。由於景氣變化前的徵兆並不是很顯著,因此許多經濟學者從各種方面來探討與分析景氣循環。\r\n 本篇論文引用 ordered Probit 模型對 Dueker (2005) 文章作一個擴展與應用,將Dueker文中原本的二分類:景氣衰退、景氣擴張延伸為景氣三分類:景氣衰退、景氣狀態不明與景氣擴張,帶入 Qual VAR 模型並利用Gibbs sampling模擬未知參數與變數,藉由統計分析,希望能對景氣循環提出一個更為詳細的詮釋。而本篇論文的目的希望在相對於二分類模型,在總體現象上能提供一個更為完善與更明確的描述,使得在分析上能更完整。參考 NBER 所公佈的景氣轉折點並輔以其他指標,將景氣區分為三分類,以 Qual VAR 模型模擬出景氣三分類的景氣指標,再對這個指標做預測分析,並比較美國景氣在二分類與三分類之下的異同。結果指出三分類模型成功的預測出 2002 年第一季到 2003 年第三季美國景氣擴張的狀態,而三選擇模型的模型比起二選擇模型,對於預測景氣狀態有更為明確的判斷,且加入一分類指標,提供新的景氣變動解釋,幫助人們做出更為合適的決策。 | 參考文獻: | Albert, J.H., and Chib, S. (1993), “Bayesian Analysis of Binary and Polychotomous Response Data,” Journal of the American Statistical Association, 88, 669-679. Blandchard, O.J. (1981), “What Is Left of The Multiplier-Accelerator?,” American Economic Association Papers and Proceedings, 71, 150-154. Dueker, M. (1997), “Strengthening the Case for the Yield Curve as a Predictor of U.S. Recessions,” Federal Reserve Bank of St. Louis Review, 79(2), 41-50. Dueker, M. (1999), “Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs Sampling Approach to the Bank Prime Rate,” Journal of Business and Economic Statistics, 17, 466-472. Dueker, M. (2005), “Dynamic Forecasts of Qualitative Variables: A Qual VAR Model of U.S. Recessions,” Journal of Business and Economic Statistics, 23, 96-104. Eichengreen, B., Watson, M.W., and Grossman, R.S. (1985), “Bank Rate Policy Under the Interwar Gold Standard,” Economic Journal, 95, 725-745. Estrella, A., and Mishkin, F.S. (1995), “Predicting U.S. Recessions: Financial Variables as Leading Indicators,” NBER Working Paper, NO. W5379. Gelfand, A.E., and Smith, A.F.M. (1990), “Sampling-Based Approaches to Calculating Marginal Densities,” Journal of the American Statistical Association, 85, 398–409. Granger, C.W.J. (1969), “Investigating Causal Relations by Econometrics Models and Spectral Methods,” Econometrica, 37, 424-438. Griffiths, W.E., Hill, R.C., and Pope, P.J. (1987), “Small Sample Properties of Probit Model Estimators,” Journal of the American Statistical Association, 82, 929-937. Nelson, C.R., and Plosser, C.I. (1982), “Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications,” Journal of Monetary Economics, 10, 62-139. Sichel, D.E. (1993), “Business Cycle Asymmetry: A Deeper Look,” Economic Inquiry, 31, 224-236. Tanner, T. A., and Wong, W. H. (1987), “The Calculation of Posterior Distribution by Data Augmentation,” Journal of the American Statistical Association, 82, 528-549. Zeger, S.L., and Karim, M.R. (1991), “Generalized Linear Models with Random Effects: A Gibbs Sampling Approach,” Journal of the American Statistical Association, 86, 79-86. Zellner, A., and Rossi, P.E. (1984), “Bayesian Analysis of Dichotomous Quantal Response Models,” Journal of Econometrics, 25, 365-393. |
描述: | 碩士 國立政治大學 經濟研究所 92258027 93 |
資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0922580271 | 資料類型: | thesis |
Appears in Collections: | 學位論文 |
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