ur.df: Augmented-Dickey-Fuller Unit Root Test

In urca: Unit Root and Cointegration Tests for Time Series Data

Augmented-Dickey-Fuller Unit Root Test

Description

Performs the augmented Dickey-Fuller unit root test.

Usage

ur.df(y, type = c("none", "drift", "trend"), lags = 1,
      selectlags = c("Fixed", "AIC", "BIC")) 

Arguments

y	Vector to be tested for a unit root.
type	Test type, either "none", "drift" or "trend".
lags	Number of lags for endogenous variable to be included.
selectlags	Lag selection can be achieved according to the Akaike "AIC" or the Bayes "BIC" information criteria. The maximum number of lags considered is set by lags. The default is to use a "fixed" lag length set by lags.

Details

The function ur.df() computes the augmented Dickey-Fuller test. If type is set to "none" neither an intercept nor a trend is included in the test regression. If it is set to "drift" an intercept is added and if it is set to "trend" both an intercept and a trend is added. The critical values are taken from Hamilton (1994) and Dickey and Fuller(1981).

Value

An object of class ur.df.

Author(s)

Bernhard Pfaff

References

Dickey, D. A. and Fuller, W. A. (1979), Distributions of the Estimators For Autoregressive Time Series with a Unit Root, Journal of the American Statistical Association, 75, 427–431.

Dickey, D. A. and Fuller, W. A. (1981), Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root, Econometrica, 49, 1057–1072.

Hamilton (1994), Time Series Analysis, Princeton University Press.

See Also

ur.df-class.

Examples

data(Raotbl3)
attach(Raotbl3)
lc.df <- ur.df(y=lc, lags=3, type='trend')
summary(lc.df)

urca documentation built on Aug. 30, 2022, 1:10 a.m.