以貨幣學派模型出發，並遵循Kim (2009) 之分析法，探討不同預期機制下之匯率模型隱含的名目匯率之統計特性是否與實際資料之統計特性接近。比較標準為長期匯率預測方程式之迴歸係數 β ̂、變異數比率及名目匯率樣本外預測。在台灣與韓國之實證研究中，皆反映現值學習機制模型所隱含的名目匯率，其統計特性較能與實際資料的統計特性相近。

This paper adopts Kim (2009)’s method.To examine whether the statistical properties of nominal exchange rates implied by different learning models are close to those implied by exchange rate data. The standards of comparison are the slope coefficient of long-term exchange rates prediction equation, the variance ratio, and out-of-sample test. Our empirical results from Taiwan and Korea indicate that the statistical properties of nominal exchange rates implied by the present-value learning model are close to those from exchange rate data.

論文審定書………………………………………………………………………….…………………………………….. i
謝辭…………………………………………………………………………………………..……………………………….. ii
中文摘要…………………………………………………………………………………………………………….……... iii
英文摘要………………………………………………………………………………………………………….….……..iv
第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究流程 2
第二章 文獻回顧 3
第三章 理論模型 13
第一節 貨幣學派模型 13
第二節 理性預期下的名目匯率決定 15
第三節 適應性預期下的名目匯率決定 16
第四節 現值學習機制下的名目匯率決定 18
第四章 研究方法 20
第一節 變異比率分析法 20
第二節 樣本外預測 21
第三節 資料模擬 23
第四節 Wald檢定 25
第五章 實證結果 27
第一節 資料來源與說明 27
第二節 實際資料之結果 28
第三節 理性預期、適應性預期與現值學習機制下的名目匯率決定分析 29
第四節 樣本外預測 37
第五節 Wald檢定分析 39
第六章 結論 42
參考文獻 43
附錄 46

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