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博碩士論文 etd-0730107-144100 詳細資訊
Title page for etd-0730107-144100
論文名稱
Title
匯率目標區之非線性研究-德,義,法三國之實證分析
Modeling Target Zone with nonlinear regression-the cases of German, Italy and France
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
86
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-06-20
繳交日期
Date of Submission
2007-07-30
關鍵字
Keywords
平滑轉換迴歸、目標區、非線性模型
nonlinear model, target zone, smooth transition regression
統計
Statistics
本論文已被瀏覽 5766 次,被下載 2397
The thesis/dissertation has been browsed 5766 times, has been downloaded 2397 times.
中文摘要
Krugman (1991) 匯率目標區 (exchange-rate target zone) 在 1990 年代初期受到很多學者的討論。意指央行只有在匯率脫離目標區上限匯率 (upper exchange rates) 及下限匯率 (lower exchange rates) 所構成的區間 (band) 時,才會進入外匯市場買賣外匯,讓匯率回復至區間內的水準;否則,央行會放手讓匯率于區間內自由浮動。根據 Krugman (1991) 提出匯率目標區之想法,當經濟體系面對隨機干擾時,相對於浮動匯率體制,匯率目標區政策有助於減緩匯率波動的幅度,也就是匯率目標區本質上具有安定的作用,此種安定功能稱為``蜜月效果' (honeymoon effect) 。

近十幾年來,有許多文獻針對 Krugman (1991) 提出匯率目標區進行實證研究,本文將以 Lundbergh and Terasvirta (2006) 所提出之平滑轉換自我迴歸目標區模型 (smooth transition autoregression with target zone;簡稱 STARTZ) 模型及本研究所建構之雙門檻的羅吉斯函數平滑轉換模型(logistic smooth transition regression with two thresholds;簡稱 LSTR2)來進行樣本內資料的配適,藉著模型所建立的均數方程式及變異數方程式來補捉匯率在目標區的非線性波動動態行為,並檢定 Krugman 匯率目標區模型的兩個基本假定:(1)區間是有公信力 (credibility assumption)(2)邊際干預 (marginal interventions)是否成立。本文以法國、德國、義大利三國為研究對象,研究樣本期間取自1987年1月14日至1989年12月29日之匯率 (ECU),共755筆日資料。並將樣本分為樣本內 (570 個觀測值) 與樣本外 (185 個觀測值),利用 STARTZ-GARCH 與 LSTR2-STGARCH 模型來建構樣本內模型,並以 Wohard (2006) 所提出之 Bootstrap 法做出樣本外資料的預測值。

最後,依循 Diebold and Mariano (1995) 所介紹的六種主要檢定方法,比較模型 STARTZ 與 LSTR2 模型間的樣本外預測能力。實證結果指出,LSTR2 模型相較於 STARTZ 模型在樣本內配適與樣本外預測皆有不錯的表現能力。
Abstract
The exchange rate target zone has been paid much attention in the early 1990 initially by Krugman (1991).It expressed when exchange rate surpasses the band of exchange rate that implicitly or explicitly determined by the central bank, the central Bank will intervene the foreign exchange by buying or selling foreign exchange to ensure the exchange rate staying inside the band, otherwise, the exchange rate will be allowed to fluctuate inside the band freely.According to Krugman (1991), when economic system faces random disturbances, the exchange rate target zone regime is helpful to narrow down the exchange rate volatility contrast to that in the floating exchange rate regime. That is, the exchange rate target zone has more essential stability,which is called ``honeymoon effect".

In recent decade, Krugman's exchange rate target zone model has been tested empirically.In this thesis, the smooth transition autoregression with target zone (STARTZ) proposed originally by Lundbergh and Ter"{a}svirta (2006) and logistic smooth transition regression with two thresholds (LSTR2) are used to make comparisons for in-sample fitness and out-of-sample forcastability.Furthermore, we also test two important assumptions of the exchange rate target zone model: the credibility assumption and marginal interventions.

The data are constructed with 755 daily spot exchange rates, denominated in Eurpean Currency Unit (ECU), from January 14, 1987 to December 29, 1989, in German, France, and Italy.We split the sample into in-sample (570 observations), and out-of-sample (185 observations), and make use of STARTZ-GARCH and LSTR2-STGARCH to fit the in-sample regimes, and apply Rapach and Wohard (2006)'s Bootstapping to generate the out-of-sample forecasts.

Finally,we make use of Diebold and Mariano (1995)'s predictive accuracy tests to compare the out-of-sample forecastability between STARTZ and LSTR2 models.According to the empirical results, we can find that LSTR2 model has not bad performance in fitting the in-sample and forecasting the out-of-sample data compared to STARTZ model.
目次 Table of Contents
1 緒論 12
1.1研究動機與目的…………………………………………………………… 12
1.2 研究架構…………………………………………………………………..13
1.3 研究流程…………………………………………………………………..14
2 文獻回顧與理論模型 15
2.1文獻回顧…………………………………………………………………….15
2.1.1 匯率目標區…………………………………………………………..15
2.1.2 匯率目標區的檢定…………………………………………………..18
2.1.3 歐洲貨幣制度與歐洲匯率機制………………………………………21
3 計量方法與模型介紹 23
3.1 非線性模型 STARTZ model 介紹………………………………………….23
3.2 非線性模型 LSTR2 model 介紹…………………………………………..27
3.3 樣本內模型的診斷性檢定 Misspecification Test……………………35
3.3.1 無剩餘非線性檢定 (NRN test)…………………………………..35
3.3.2 參數不變性檢定 (PC test)……………………………………….36
3.3.3 估計模型選擇之準則 (MSE)………………………………………37
3.4 樣本外預測值的估計與檢定……………………………………………38
3.4.1 Bootstrapping method 建構樣本外預測值…………………….38
3.4.2 信賴區間的檢定……………………………………………………39
3.5 預測模型的檢定…………………………………………………………..40
3.5.1 DM 檢定 (Diebold-Mariano Test)…………………………….41
3.5.2 符號檢定 (The Sign Test)…………………………………….41
3.5.3 魏克森符號檢定 (Wilcoxon’s Signed-Rank Test)…………42
3.5.4 F檢定 (或稱 Chow Test)………………………………………42
3.5.5 MGN 檢定 (The Morgan-Granger-Newbold Test)…………….43
3.5.6 MR 檢定 (The Meese-Rogoff Test)…………………………..44
4. 實證研究方法 46
4.1 資料說明………………………………………………………………….46
4.2 實證模型估計結果;樣本內的配適………………………………………50
4.2.1 實證模型估計結果:STARTZ 與 LSTR2 模型………………….50
4.2.2 STARTZ 與 LSTR2 模型配適度比較…………………………..53
4.3 實證模型估計結果;樣本外的預測……………………………………..53
4.3.1 信賴區間檢定結果……………………………………………….53
4.3.2 STARTZ 與 LSTR2 模型配預測力比較………………………55
5. 結論 58
5.1 結論……………………………………………………………………….58
附表 68
參考文獻 81
參考文獻 References
1. 李榮謙, (1997), 國際貨幣與金融, 智勝文化 臺北市.
2. 高昆照, (2006), 美日跨期經常帳動態之非線性分析, 高雄大學經營管理研究所碩士論文.
3. 陳若蓁, (2007), 貨幣存量對經常帳動態之影響-G4工業化國家之研究, 中山大學經濟學研究所碩士論文.
4. 劉美玲, (2004), 應用平滑轉換迴歸在匯率目標區之實證, 中原大學國際貿易研究所碩士論文.
5. 葉銘德, (2000), 匯率目標區之研究, 台灣大學經濟學研究所碩士論文.
6. 賴景昌, (1994), 國際金融理論: 進階篇, 台北: 茂昌.
7. Akaike, H., (1974), ``A new look at the statistical model identification. Automatic Control," IEEE Transactions of Automatic Control, 19/6, 716-723.
8. Bacon, D.W., and D.G. Watts, (1971), ``Estimating the transition between two intersecting straight lines,' Biometrika, 58/3, 525.
9. Bekaert, G., and S.F. Gray (1998), ``Target Zones and Exchange Rates: An Empirical Investigation," Journal of International Economics, 45/1, 1-35.
10. Bertola, G., and R.J. Caballero, (1992), ``Target Zones and Realignments," The American Economic Review, 82/3, 520-536.
11. Bollerslev, T., (1986), ``Generalized Autoregressive Conditional Heteroskedasticity," Journal of Econometrics, 31/3, 307-327.
12. de Jong, F, (1994), ``A Univariate Analysis of EMS Exchange Rates Using a Target Zone Model," Journal of Applied Econometrics, 9/1, 31-45.
13. Diebold, F.X., and R.S. Mariano, (1995), ``Comparing Predictive Accuracy’’. Journal of Business and Economic Statistics," 13/3, 253-263.
14. Dominguez, K.M., and P.B. Kenen, (1991), ``On the Need to Allow for the Possibility that Governments Mean What They Say: Interpreting the Target-Zone Model of Exchange-Rate Behavior in the Light of EMS xperience," National Bureau of Economic Research.
15. Dominguez, K.M.E., and P.B. Kenen, (1993), ``Intramarginal Intervention in the EMS and the Target-Zone Model of Exchange-Rate Behavior," National Bureau of Economic Research.
16. Flood, R., and P. Garber, (1992), ``The Linkage between Speculative Attacks and Target Zone Interest Rates," Quarterly Journal of Econmics, 106, 1367-1372.
17. Froot, K.A., and M. Obstfeld, (1991), ``Exchange Rate Dynamics Under Stochastic Regime Shifts: A Unified Approach," Jounal of International Economics, 31, 203-299.
18. Granger, C.W.J., and T. Terasvirta, (1993), Modelling Nonlinear Economic Relationships, Cambridge: Oxford University Press.
19. Iannizzotto, M., and M.P. Taylor, (1999), ``The Target Zone Model, Non-Linearity and Mean Reversion: is the Honeymoon Really Over?" The Economic Journal, 109/454, 96-110.
20. Krugman, P.R., (1991), ``Target Zones and Exchange Rate Dynamics," The Quarterly Journal of Economics, 106/3, 669-682.
21. Lundbergh, S., and T. Terasvirta, (2003), ``A Time Series Model for an Exchange Rate in a Target Zone with Applications," Working Paper Sseries in Economics and Finance, SSE/EEI.
22. Lundbergh, S., and T. Terasvirta, (2006), ``A Time Series Model for an Exchange Rate in a Target Zone with Applications," Journal of Econometrics, 579-609.
23. Lutkepohl, H., and M. Kratzig, (2004), Applied Time Series Econometrics, Cambridge: Cambridge University Press.
24. Maddala, G., (1977), Econometrics, McGraw-Hill,New York.
25. Nelder, J., (1961), ``The Fitting of a Generalization of the Logistic Curve," Biometrics, 17/1, 89-110.
26. Quandt, R.E., (1985), ``The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes," Journal of the American Statistical Association, 53/284, 873-880.
27. Rapach, D.E., and M.E. Wohar, (2006), ``The Out-of-Sample Forecasting Performance of Nonlinear Models of Real Exchange Rate Behavior" International Journal of Forecasting, 22, 341-361.

28. Rissanen, J., (1978), ``Modeling by shortest data description," Automatica, 14/5, 465–471.
29Schwarz, G., (1978), ``Estimating the Dimension of a Model," The Annals of Statistics, 6/2, 461-464.
30. Sollis, R., S.P. Leybourne, and P. Newbold, (1999), ``Unit roots and asymmetric smooth transitions," Journal of Time Series Analysis, 20, 671677.
31. Svensson, L.E.O., (1991a), ``The Simplest Test of Target Zone Credibility," Washington:IMF Staff Paper, 38, 655-65.
32. Svensson, L.E.O., (1991b), ``The Term Structure of Interest Rate Differentials in a Target Zone: Theory and Swedish Data," Journal of Momentary Economics, 28, 87-116.
33. Svensson, L.E.O., (1992), ``An Interpretation of Recent Research on Exchange Rate Target Zones," The Journal of Economic Perspectives, 6/4, 119-144.
34. Taylor, M.P., and M. Iannizzotto, (2001), ``On the Mean-Reverting Properties of Target Zone Exchange Rates: A Cautionary Note," Economics Letters, 71/1, 117-129.
35. Terasvirta, T., (1994), ``Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models," Journal of the American Statistical Association, 89/425, 208-218.
36. Terasvirta, T., (1998), ``Modeling Economic Relationships wirth Smooth Transition Regression," Handbook of Applied Economic Statistics, 508-552.
37. Tong, H., (1990), Non-Linear Time Series, Clarendon Press, Oxford.
38. van Dijk, D., T. Terasvirta, and P.H. Franses, (2000), ``Smooth Transition Autoregressive Models: A Survey of Recent Developments," FEW-Econometrie en besliskunde, Erasmus University Host.
39. Wallis, K.F., (2003), ``Chi-squared Tests of Interval and Density Forecasts, and the Bank of England's Fan Charts," International Journal of Forecasting, 19/2, 165-175.
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