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題名 運用菲利浦曲線預測物價
Forecasting Taiwan Inflation using Phillips Curve作者 王宣智 貢獻者 饒秀華<br>徐士勛
王宣智關鍵詞 Phillips 曲線
通貨膨脹率
模擬樣本外預測
Diebold-Mariano 檢定
結構穩定性
遞迴迴歸
組合預測模型日期 2016 上傳時間 1-Jul-2016 15:24:10 (UTC+8) 摘要 大多數國家的中央銀行均以「穩定物價,控制通貨膨脹」視為貨幣政策的主要目標,因此本研究以 Stock and Watson (1999) 為基本架構,運用2000年1月至2015年12月台灣失業率與其他經濟指標之 Phillips 曲線模型,以遞迴迴歸 (recursive regression) 的方式進行模擬樣本外預測1個月與12個月核心消費者物價指數通貨膨脹率及消費者物價指數通貨膨脹率,及檢驗模型結構穩定性,並利用組合預測方式,進行模型預測績效比較。其實證結果顯示:核心消費者物價指數年增率模型的預測績效優於消費者物價指數模型的預測績效,而比較失業率及其他經濟指標之 Phillips 曲線各個單一模型,在模擬樣本外預測1個月核心消費者物價指數年增率之預測績效,為營造工程物價指數 (cci) 表現最好,再者發現預測12個月核心消費者物價指數之 Rel. RMSFE 比預測1個月核心消費者物價指數之 Rel. RMSFE 來的小,另外Diebold-Mariano 檢定對於核心消費者物價指數 (cpix) 和消費者物價指數 (cpix) 做為通貨膨脹率之組合預測模型樣本外預測1個月通貨膨脹率之預測績效皆沒有改善效果,反而是部分組合預測模型在樣本外預測12個月通貨膨脹率之預測績效具有改善效果,皆顯示長期預測12個月比短期預測1個月之各個經濟變數的組合預測模型預測績效有明顯的改善,可能係在檢定預測12個月核心消費者物價指數 (cpix) 之 Phillips 曲線模型具有結構性改變影響所致。 參考文獻 中華民國中央銀行全球資訊網,貨幣政策簡介侯德潛、徐千婷(2002),「我國通貨膨脹預測模型之建立」,中央銀行季刊,第二十四卷第三期,9-40陳柏琪(1997),「物價膨脹與失業率之抵換關係-菲力蒲曲線分析之檢討」,自由中國之工業,第87卷第7期,19-32。黃立佳(2001),「澳門的菲利浦士曲線和它對總體經濟政策的啟示」,澳門經濟:澳門經濟學會學報,第15期,第28-37頁。張慈恬(2011),「台灣消費者物價指數的預測評估與比較」,國立政治大學經濟學系碩士論文郭佳平(2012),「台灣自然失業率與短期菲利浦曲線之實證研究」,國立清華大學經濟系碩士學位論文張育菁(2012),「通貨膨脹預測:以台灣為例」,國立清華大學經濟系碩士學位論文葉盛、田慧琦(2004),「台灣的物價情勢:影響因素探析與計量實證模型應用」,中央銀行季刊,26(4),第69-116頁劉淑敏(2011),「低通膨與低利率下的菲力普曲線與貨幣政策–台灣之實證分析」賴景昌(2013),「總體經濟學」,三版,雙葉書廊有限公司Akaike, H. (1974), “A new look at the statistical model identification.” , IEEE Transactions on Automatic Control 19 (6): 716–723Atkeson, A. and L.E. Ohanian (2001), “Are Phillips Curves Useful for Forecasting Inflation? ” Federal Reserve Bank of Minneapolis Quarterly Review, 25, 2-11.Bates, J. and C. Granger (1969), “The Combination of Forecasts.” Operational Research Quarterly, 20, 451-468.Bessler, D. A. and J. A. Brandt (1979), “Composite Forecasting of Livestock Prices:An Analysis of Combining Alternative Forecasting Methods.” Purde University Agricultural Experiment Station.Blanchard, O and Johnson, David R. (2012) “MACROECONOMICS.” Sixth Edition, Pearson Education, Inc.Blanchard, O. (2016) “The US Phillips Curve: Back to the 60s? ”Peterson Institute for International Economics, PB16-1.Dickey, David A. and Fuller, Wayne A. (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association, 74(366), 427-431.Diebold, F.X. and R.S. Mariano. (1995), “Comparing Predictive Accuracy.” Journal of Business and Economic Statistics, 13: 253-63.Friedman, Milton (1968), “The Role of Monetary Policy,” American Economic Review, 58,1 – 17.Fisher, J. D. M., C.T. Liu and R. Zhou (2002), “When Can We Forecast Inflation? ” Federal Reserve Bank of Chicago Economic Perspectives, 26, 32-44.Granger, C. W. J. and Newbold, P. (1974), “Spurious Regressions in Econometrics.”Journal of Econometrics, 2, 111-120.Giacomini, R. and H. White (2006),”Tests of Conditional Predictive Ability.”Econometrica, 74, 1545-1578.Gordon, R. J. (2011) “The history of the Phillips curve: Consensus and bifurcation.”Economica 78, issue 309: 10–50.Harvey, D. , Leybourne, S. and Newbold, P. (1997) “Testing the equality of prediction mean squared errors.” International Journal of Forecasting, 13, 281-291Haldrup, N. and Jansson, M. (2006) “Improving size and power in unit root testing.” In: Patterson, K., Mills, T.C. (eds.), Palgrave Handbook of Econometrics. Vol. 1: Econometric Theory, Palgrave Macmillan, 252-277.Michelle L、Barnes and Giovanni P、Olivei. (2003) “Inside and Outside Bounds: Threshold Estimates of the Phillips Curve.” Federal Reserve Bank of Boston NewEngland Economic Review, 3-18.Philips, A.W. (1985) “The Relation between Unemployment and Rate of Change of Money Wage Rates on the United Kingdom 1861-1957.” Economica 25 :283-289.Quandt, R.E. (1960), “Tests of the hypothesis that a linear regression system obeys two separate regimes.” Journal of American Statistical Association 55, 320-330.Peach, R., Rich, R. and Cororaton, A. (2011) “How Does Slack Influence Inflation? ” Current Issues in Economics and Finance, Vol. 17, No. 3, July 2011.Schwarz, G. (1987), “Estimating the Dimension of a Model.” The Annals of Statistics, Vol.6, No. 2. , 461-464.Stock, J.H. and M.W. Watson (1999), “Forecasting Inflation.” Journal of Monetary Economics, 44, 293-335.Stock, J.H. and M.W. Watson (2008), “Phillips Curve Inflation Forecasts.” Working paper.Stock, J.H. and M.W. Watson (2011), “Introduction to Econometrics.” 3rd Edition, Pearson Education, Inc.Tobin, J. (1971), “Phillips Curve Algebra.” in Essays in Economics, Vol. 2, Amsterdam: North Holland Press.Razzak, W.A.(2002), “Monetary Policy and Forecasting Inflation With and Without the Out Gap.” ,Discussion Paper Series, DP2002/03, Reserve Bank of New Zealand. 描述 碩士
國立政治大學
經濟學系
103258024資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103258024 資料類型 thesis dc.contributor.advisor 饒秀華<br>徐士勛 zh_TW dc.contributor.author (Authors) 王宣智 zh_TW dc.creator (作者) 王宣智 zh_TW dc.date (日期) 2016 en_US dc.date.accessioned 1-Jul-2016 15:24:10 (UTC+8) - dc.date.available 1-Jul-2016 15:24:10 (UTC+8) - dc.date.issued (上傳時間) 1-Jul-2016 15:24:10 (UTC+8) - dc.identifier (Other Identifiers) G0103258024 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/98643 - 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) 103258024 zh_TW dc.description.abstract (摘要) 大多數國家的中央銀行均以「穩定物價,控制通貨膨脹」視為貨幣政策的主要目標,因此本研究以 Stock and Watson (1999) 為基本架構,運用2000年1月至2015年12月台灣失業率與其他經濟指標之 Phillips 曲線模型,以遞迴迴歸 (recursive regression) 的方式進行模擬樣本外預測1個月與12個月核心消費者物價指數通貨膨脹率及消費者物價指數通貨膨脹率,及檢驗模型結構穩定性,並利用組合預測方式,進行模型預測績效比較。其實證結果顯示:核心消費者物價指數年增率模型的預測績效優於消費者物價指數模型的預測績效,而比較失業率及其他經濟指標之 Phillips 曲線各個單一模型,在模擬樣本外預測1個月核心消費者物價指數年增率之預測績效,為營造工程物價指數 (cci) 表現最好,再者發現預測12個月核心消費者物價指數之 Rel. RMSFE 比預測1個月核心消費者物價指數之 Rel. RMSFE 來的小,另外Diebold-Mariano 檢定對於核心消費者物價指數 (cpix) 和消費者物價指數 (cpix) 做為通貨膨脹率之組合預測模型樣本外預測1個月通貨膨脹率之預測績效皆沒有改善效果,反而是部分組合預測模型在樣本外預測12個月通貨膨脹率之預測績效具有改善效果,皆顯示長期預測12個月比短期預測1個月之各個經濟變數的組合預測模型預測績效有明顯的改善,可能係在檢定預測12個月核心消費者物價指數 (cpix) 之 Phillips 曲線模型具有結構性改變影響所致。 zh_TW dc.description.tableofcontents 1 緒論 11.1 研究背景與動機 11.2 論文架構與流程 42 文獻回顧探討 52.1 國外文獻 52.2 國內文獻 83 研究模型建立 123.1 Phillips 曲線模型之演進 123.2 Phillips 曲線模型之數學模型 134 研究方法 204.1 單根檢定 204.2 依據訊息準則選擇模型落後長度 214.3 結構穩定性檢定 214.4 模擬樣本外預測 234.5 組合預測 244.6 評估預測模型之表現 255 實證結果分析 275.1 研究期間及資料變數 275.2 ADF 單根檢定結果 285.3 結構性改變 (QLR) 檢定結果 295.4 預測誤差均方根 (RMSFE) 比較 295.5 組合預測模型效果 30圖 1 美國1948-1969 年通貨膨脹與失業率之關係 37圖 2 美國1970-2010 年通貨膨脹率與失業率之關係 37圖 3 美國1970-2010 年通貨膨脹變動率與失業率之關係 38圖 4 臺灣2000-2015 年通貨膨脹率與失業率 (一階差分) 之關係 39圖 5 臺灣2000-2015 年通貨膨脹變動率與失業率 (一階差分) 之關係 39圖 6 臺灣2000-2015 年通貨膨脹率與失業變動率之關係 40圖 7 臺灣2000-2015 年通貨膨脹變動率與失業變動率之關係 40表 1 解釋變數代號 41表 2 變數轉換代號 41表 3 ADF 單根檢定 (原始變數 P-value 表) 42表 4 ADF 單根檢定 (變數轉換後 P-value 表) 43表 5 QLR test,核心消費者物價指數 (cpix),預測1 個月 44表 6 QLR test,核心消費者物價指數 (cpix),預測12 個月 45表 7 QLR test,消費者物價指數 (cpi),預測1 個月 46表 8 QLR test,消費者物價指數 (cpi),預測12 個月 47表 9 樣本外預測1 個月之RMSFE 48表 10 樣本外預測12 個月之RMSFE 49表 11 組合預測模型 cpix-du,樣本外預測1 個月 50表 12 組合預測模型 cpix-du,樣本外預測12 個月 51表 13 組合預測模型 cpi-du,樣本外預測1 個月 52表 14 組合預測模型 cpi-du,樣本外預測12 個月 53表 15 組合預測模型 cpix-u,樣本外預測1 個月 54表 16 組合預測模型 cpix-u,樣本外預測12 個月 55表 17 組合預測模型 cpi-u,樣本外預測1 個月 56表 18 組合預測模型 cpi-u,樣本外預測12 個月 57表 19 Diebold-Mariano 檢定之 P-Value (cpix-du) 58表 20 Diebold-Mariano 檢定之 P-Value (cpi-du) 59表 21 Diebold-Mariano 檢定之 P-Value (cpix-u) 60表 22 Diebold-Mariano 檢定之 P-Value (cpi-u) 61參考文獻 62 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103258024 en_US dc.subject (關鍵詞) Phillips 曲線 zh_TW dc.subject (關鍵詞) 通貨膨脹率 zh_TW dc.subject (關鍵詞) 模擬樣本外預測 zh_TW dc.subject (關鍵詞) Diebold-Mariano 檢定 zh_TW dc.subject (關鍵詞) 結構穩定性 zh_TW dc.subject (關鍵詞) 遞迴迴歸 zh_TW dc.subject (關鍵詞) 組合預測模型 zh_TW dc.title (題名) 運用菲利浦曲線預測物價 zh_TW dc.title (題名) Forecasting Taiwan Inflation using Phillips Curve en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中華民國中央銀行全球資訊網,貨幣政策簡介侯德潛、徐千婷(2002),「我國通貨膨脹預測模型之建立」,中央銀行季刊,第二十四卷第三期,9-40陳柏琪(1997),「物價膨脹與失業率之抵換關係-菲力蒲曲線分析之檢討」,自由中國之工業,第87卷第7期,19-32。黃立佳(2001),「澳門的菲利浦士曲線和它對總體經濟政策的啟示」,澳門經濟:澳門經濟學會學報,第15期,第28-37頁。張慈恬(2011),「台灣消費者物價指數的預測評估與比較」,國立政治大學經濟學系碩士論文郭佳平(2012),「台灣自然失業率與短期菲利浦曲線之實證研究」,國立清華大學經濟系碩士學位論文張育菁(2012),「通貨膨脹預測:以台灣為例」,國立清華大學經濟系碩士學位論文葉盛、田慧琦(2004),「台灣的物價情勢:影響因素探析與計量實證模型應用」,中央銀行季刊,26(4),第69-116頁劉淑敏(2011),「低通膨與低利率下的菲力普曲線與貨幣政策–台灣之實證分析」賴景昌(2013),「總體經濟學」,三版,雙葉書廊有限公司Akaike, H. (1974), “A new look at the statistical model identification.” , IEEE Transactions on Automatic Control 19 (6): 716–723Atkeson, A. and L.E. Ohanian (2001), “Are Phillips Curves Useful for Forecasting Inflation? ” Federal Reserve Bank of Minneapolis Quarterly Review, 25, 2-11.Bates, J. and C. Granger (1969), “The Combination of Forecasts.” Operational Research Quarterly, 20, 451-468.Bessler, D. A. and J. A. Brandt (1979), “Composite Forecasting of Livestock Prices:An Analysis of Combining Alternative Forecasting Methods.” Purde University Agricultural Experiment Station.Blanchard, O and Johnson, David R. (2012) “MACROECONOMICS.” Sixth Edition, Pearson Education, Inc.Blanchard, O. (2016) “The US Phillips Curve: Back to the 60s? ”Peterson Institute for International Economics, PB16-1.Dickey, David A. and Fuller, Wayne A. (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association, 74(366), 427-431.Diebold, F.X. and R.S. Mariano. (1995), “Comparing Predictive Accuracy.” Journal of Business and Economic Statistics, 13: 253-63.Friedman, Milton (1968), “The Role of Monetary Policy,” American Economic Review, 58,1 – 17.Fisher, J. D. M., C.T. Liu and R. Zhou (2002), “When Can We Forecast Inflation? ” Federal Reserve Bank of Chicago Economic Perspectives, 26, 32-44.Granger, C. W. J. and Newbold, P. (1974), “Spurious Regressions in Econometrics.”Journal of Econometrics, 2, 111-120.Giacomini, R. and H. White (2006),”Tests of Conditional Predictive Ability.”Econometrica, 74, 1545-1578.Gordon, R. J. (2011) “The history of the Phillips curve: Consensus and bifurcation.”Economica 78, issue 309: 10–50.Harvey, D. , Leybourne, S. and Newbold, P. (1997) “Testing the equality of prediction mean squared errors.” International Journal of Forecasting, 13, 281-291Haldrup, N. and Jansson, M. (2006) “Improving size and power in unit root testing.” In: Patterson, K., Mills, T.C. (eds.), Palgrave Handbook of Econometrics. Vol. 1: Econometric Theory, Palgrave Macmillan, 252-277.Michelle L、Barnes and Giovanni P、Olivei. (2003) “Inside and Outside Bounds: Threshold Estimates of the Phillips Curve.” Federal Reserve Bank of Boston NewEngland Economic Review, 3-18.Philips, A.W. (1985) “The Relation between Unemployment and Rate of Change of Money Wage Rates on the United Kingdom 1861-1957.” Economica 25 :283-289.Quandt, R.E. (1960), “Tests of the hypothesis that a linear regression system obeys two separate regimes.” Journal of American Statistical Association 55, 320-330.Peach, R., Rich, R. and Cororaton, A. (2011) “How Does Slack Influence Inflation? ” Current Issues in Economics and Finance, Vol. 17, No. 3, July 2011.Schwarz, G. (1987), “Estimating the Dimension of a Model.” The Annals of Statistics, Vol.6, No. 2. , 461-464.Stock, J.H. and M.W. Watson (1999), “Forecasting Inflation.” Journal of Monetary Economics, 44, 293-335.Stock, J.H. and M.W. Watson (2008), “Phillips Curve Inflation Forecasts.” Working paper.Stock, J.H. and M.W. Watson (2011), “Introduction to Econometrics.” 3rd Edition, Pearson Education, Inc.Tobin, J. (1971), “Phillips Curve Algebra.” in Essays in Economics, Vol. 2, Amsterdam: North Holland Press.Razzak, W.A.(2002), “Monetary Policy and Forecasting Inflation With and Without the Out Gap.” ,Discussion Paper Series, DP2002/03, Reserve Bank of New Zealand. zh_TW
