方法对比

	稳健 Phillips-Perron (PP) 单位根检验	稳健增广迪基-福勒（ADF）单位根检验
领域	计量经济学	计量经济学
方法族	Regression model	Regression model
起源年份	1988 (base); 2000s–2010s (robust extensions)	1996-2001
提出者	Phillips & Perron (1988); robustification by Cavaliere & Taylor (2008) and related authors	Ng and Perron (2001); Elliott, Rothenberg, and Stock (1996)
类型	Unit root / stationarity test	Unit root / stationarity test
开创性文献	Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346.	Ng, S., and Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica, 69(6), 1519-1554.
别名	robust Phillips-Perron test, heteroskedasticity-robust PP test, nonparametric robust unit root test, robust PP	robust ADF test, HAC-corrected ADF, heteroscedasticity-robust unit root test, GLS-detrended ADF
相关	6	6
摘要	The Robust Phillips-Perron unit root test extends the classical PP test by applying corrections — such as heteroskedasticity-consistent covariance estimation or wild-bootstrap critical values — that maintain valid inference when the error variance of a time series is non-constant or exhibits unconditional heteroskedasticity, conditions under which the standard PP test is severely size-distorted.	The Robust ADF unit root test extends the classical ADF procedure with improvements that correct for size distortions arising from heteroscedastic or serially correlated errors, and from poor lag-length selection. Drawing on GLS detrending (Elliott, Rothenberg, and Stock 1996) and modified information criteria (Ng and Perron 2001), it delivers reliable size and power in the presence of non-standard error processes common in macroeconomic and financial time series.