Regression modelEconometrics / time series
Augmented Dickey-Fuller (ADF) Unit Root Test
The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance.
EconMind ile uygulaSoonVideoSoon
Tam yöntemi oku
Members only
Sign inSign in with a free account to read this section.
Sources
- Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. DOI: 10.1093/biomet/71.3.599 ↗
- Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. DOI: 10.2307/2286348 ↗
Related methods
Referenced by
ARIMA modelAutoregressive modelBayesian ADF unit root testBayesian PP unit root testEngle-Granger Cointegration TestFourier ADF unit root testFourier PP unit root testFourier Zivot-Andrews testGranger Causality TestNonlinear ADF Unit Root TestNonlinear PP unit root testPanel ADF Unit Root TestPanel KPSS testPanel PP unit root testPanel Zivot-Andrews testPhillips-Perron unit root testRobust ADF Unit Root TestRobust PP Unit Root TestStructural Break ADF Unit Root TestStructural Break AR ModelStructural Break KPSS TestStructural Break OLSStructural break Zivot-Andrews testTime-varying parameter Zivot-Andrews testToda-Yamamoto causality testZivot-Andrews Structural Break Test