本文推導出一個半母數 (semi-parametric method) 的方法去推論一個緩長記憶模型 (I(d) process) 的差分係數，模擬結果顯示在有限樣本下，這個方法有極小的型一誤差的扭曲 (size distortion ) 和良好的檢定力 (power) 表現。最後本文以兩個實例來說明如何應用這個方法。

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目 錄
第一章 緒 論 １
第一節 研究動機與目的 １
第二節 研究方法與研究架構 ２
第二章 文獻回顧及探討 ３
第一節 文獻回顧 ３
第二節 文獻探討 ４
第三章 創新過程的基本假設 ６
第一節 創新過程的基本假設 ６
第二節 輔助定理 ７
第四章 模型和估計式 １０
第一節 一般非穩定 ( nonstationary ) 的I(d) 過程 １０
第二節 統計的極限分配 １３
第五章 分數差分參數的統計推論 １９
第一節 0.5< d < 1 的檢定 １９
第二節 當d=1 的檢定 ２７
第三節 當0< d <0.5的檢定 ２８
第六章 在有限樣本下的型一誤差的扭曲和檢定力 ２９
第七章 實證應用 ３３
第一節 實質利率水準資料 ３３
第二節 失業率的資料 ３４
第八章 結 論 ３８
參 考 文 獻 ４０

表 目 錄
表一 : Z(d)和Zu(d)統計的臨界值 ２３
表二 :GPH，Z(d)和Zu(d)統計的型一誤差的扭曲和檢定力 ３１
表三-1 :Zu(d)檢定在 Mishikin 的資料 ３５
表三-2 : Zu(d)在失業率資料之檢定 ３６

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