手法を比較

	フーリエKPSS定常性検定（滑らかな構造的変化あり）	Hadriパネル定常性検定 (Panel KPSS Test)	Zivot-Andrews 単位根検定（構造的ブレーク1時点あり）
分野	計量経済学	計量経済学	計量経済学
系統	Regression model	Regression model	Hypothesis test
提唱年	2006	2000	1992
提唱者	Becker, Enders, and Lee	Hadri (2000), extending Kwiatkowski, Phillips, Schmidt, and Shin (1992)	Eric Zivot & Donald Andrews
種類	Stationarity test	Panel stationarity test	Sequential unit-root test with endogenous break-point selection
原典	Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409.	Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. Econometrics Journal, 3(2), 148-161.	Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270.
別名	Fourier KPSS, flexible Fourier stationarity test, F-KPSS, KPSS with Fourier approximation	KPSS panel stationarity test, panel stationarity test, Hadri LM test, panel KPSS	ZA Test, Zivot-Andrews Break Test, Endogenous Break Unit-Root Test, Zivot-Andrews Birim Kök Testi
関連	3	6	3
概要	The Fourier KPSS test extends the standard KPSS stationarity test by embedding a flexible Fourier series in the deterministic component of the model. This approach captures smooth, gradual structural breaks in the level or trend of a time series without requiring the researcher to specify the number or timing of those breaks, yielding more reliable inference under structural change.	The Panel KPSS test, introduced by Hadri (2000), tests the null hypothesis that all series in a panel are stationary against the alternative that some or all contain a unit root. It extends the univariate KPSS framework to panel data by aggregating individual LM statistics, providing higher power than unit-root tests when most series are in fact stationary.	The Zivot-Andrews (ZA) test, introduced by Eric Zivot and Donald Andrews in 1992, is a sequential unit-root test that allows for a single structural break at an unknown date. It extends the augmented Dickey-Fuller framework by endogenously selecting the break point that provides the strongest evidence against the unit-root null hypothesis, making it particularly useful for macroeconomic and financial time series that may have been disrupted by events such as policy changes, financial crises, or supply shocks.