Unit root test
In statistics, a unit root test tests whether a time series variable is non-stationary and possesses a unit root. The null hypothesis is generally defined as the presence of a unit root and the alternative hypothesis is either stationarity, trend stationarity or explosive root depending on the test used.
General approach
In general, the approach to unit root testing implicitly assumes that the time series to be tested can be written as,where,
- is the deterministic component
- is the stochastic component.
- is the stationary error process.
Main tests
Other popular tests include:- augmented Dickey–Fuller test
- : this is valid in large samples.
- Phillips–Perron test
- KPSS test
- : here the null hypothesis is trend stationarity rather than the presence of a unit root.
- ADF-GLS test