本文探討結構模型在名目匯率預測上之表現是否受資料期間涵蓋機動匯率制度時期之影響。藉由隨機漫步模型(Random walk)、未拋補利率平價模型(UIP)、購買力平價模型(PPP)、貨幣模型、泰勒法則模型(1)及泰勒法則模型(2)六種模型，利用滾動樣本迴歸估計法(rolling regression)與遞迴樣本迴歸估計法(recursive regression) 進行樣本外預測，並以Theil’s U比率、CW檢定和DM檢定三種衡量指標比較五種結構模型與隨機漫步模型預測能力之優劣。實證結果顯示，當樣本期間包含機動匯率制度期間，結構模型之樣本外預測能力明顯劣於隨機漫步模型，反之模型之預測能力則有明顯的改善。此乃因機動匯率期間之匯率受央行干預影響之轉變較大，故結構模型之預測能力受影響。





關鍵字：名目匯率、機動匯率制度、樣本外預測

This paper examines the capability of structural models to beat the random walk when the sample period includes the period of managed float.
Five different structural models are adopted, and they are the uncovered interest rate model (UIP), the purchasing power parity model (PPP), the flexible price monetary model and two taylor rule models. Both rolling and recursive regression are used in forecasting. We found that the performance of structural models in out-of-sample forecast is good relative to the driftless random walk when the period of managed float is excluded, but it is poor when the period is included.
The reason could be that exchange rates during the period of managed float are not free market rates since they are significantly affected by central bank’s intervention.




Keywords: nominal exchange rates, Managed floating exchange rate system, out-of-sample forecast

目錄

謝辭 ii
摘要 iii
Abstract iv
目錄 v
圖次 vi
表次 vii
第一章 緒論 1
第一節 研究目的與動機 1
第二節 研究架構 2
第二章文獻回顧 3
第三章 研究方法與模型設定 14
第一節 樣本及資料來源 14
第二節 模型建立 16
第三節 預測方法 22
第四節 績效評估與檢定 25
第四章 實證結果 28
第一節資料範圍涵蓋機動匯率制度 28
第二節資料範圍排除機動匯率制度 32
第三節綜合比較 36
參考文獻 42
中文部分 42
英文部分 42

中文部分

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5. 鍾惠民、周賓凰、孫而音(2009)，“財務計量：Eviews的應用”，臺北：新陸書局，初版。


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