通貨膨脹是否為定態的時間資料，以往於追蹤資料(panel data)採用無序列相關且無當期相關(serially uncorrelated and contemporaneously uncorrelated)的假設，序列相關的問題可以使用增廣項(augmented part)解決，但是若假設橫截面不相關(cross-sectionally uncorrelated)，與現今經濟體相互影響的特性不符，使得檢定方法產生錯誤的統計推論。故近年來的追蹤資料增加橫截面相關(cross-sectionally correlated)的設定，以求統計推論更形正確。
本文採用Smeekes (2011)的計量模型，主要根據測試者自行設定的定態比例依序檢定，不僅將追蹤資料橫截面相關納入考量，更使用區間拔靴法(block bootstrap)的方式求得臨界值，藉此增加追蹤資料導入橫斷面相關假設後的檢定力。本文針對(1)21個OECD國家時間序列62年的通貨膨脹率做追蹤資料單根檢定，得到有0.2比例國家通貨膨脹資料為定態的結論，(2)21個OECD國家時間序列216季的通貨膨脹率做追蹤資料單根檢定，得到沒有國家通貨膨脹資料為定態的結論。

O’Connell (1998) points out that traditional panel unit root tests designed for cross-sectionally independent panels can be highly distorted for cross-sectionally correlated panels. Therefore, new methods were proposed to study stationarity of variables in a cross-sectional dependence panel. Smeekes (2011) proposes bootstrap sequential quantile tests to investigate the stationarity of individual units in panel data based on testing user-defined increasing proportions of hypothesized stationary units sequentially. Valid critical values are obtained by a block bootstrap method which can gain power from dependence structure while test statistics are calculated through order statistics of individual units. In this paper, the proposed test is applied to examine the stationarity of inflation for 21 OECD countries. Empirical results fail to reject the null hypothesis that the proportion of stationary series in the panel being 0.2 and 0 for annual and quarterly data, respectively.

第1章、緒論....................................................................................................1
第2章、單根檢定法之文獻回顧..........................................................................4
第2.1節、傳統的單根檢定..............................................................................5
第2.2節、第一代追蹤資料單根檢定.................................................................7
第2.3節、第二代追蹤資料單根檢定................................................................10
第3章、通貨膨脹恆定性之文獻回顧...................................................................15
第4章、模型設定和研究方法.............................................................................19
第4.1節、模型設定........................................................................................19
第4.2節、研究方法........................................................................................20
第4.2.1節、依序分位數拔靴法檢定...............................................................20
第4.2.2節、依序分位數拔靴法檢定力的改進(BSQT2)......................................26
第4.2.3節、疊代依序分位數拔靴法檢定.........................................................29
第4.2.4節、重複檢定架構下的依序方法.........................................................31
第5章、實證分析...............................................................................................33
第5.1節、傳統單根檢定..................................................................................34
第5.2節、第一代追蹤資料單根檢定..................................................................37
第5.3節、第二代追蹤資料單根檢定(BSQT).......................................................39
第6章、結論......................................................................................................41
參考文獻...........................................................................................................43

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