# ur.kpss: Kwiatkowski et al. Unit Root Test In urca: Unit Root and Cointegration Tests for Time Series Data

## Description

Performs the KPSS unit root test, where the Null hypothesis is stationarity. The test types specify as deterministic component either a constant "mu" or a constant with linear trend "tau".

## Usage

 1 2 ur.kpss(y, type = c("mu", "tau"), lags = c("short", "long", "nil"), use.lag = NULL)

## Arguments

 y Vector to be tested for a unit root. type Type of deterministic part. lags Maximum number of lags used for error term correction. use.lag User specified number of lags.

## Details

lags="short" sets the number of lags to \root 4 \of {4 \times (n/100)}, whereas lags="long" sets the number of lags to \root 4 \of {12 \times (n/100)}. If lags="nil" is choosen, then no error correction is made. Furthermore, one can specify a different number of maximum lags by setting use.lag accordingly.

## Value

An object of class ur.kpss.

Bernhard Pfaff

## References

Kwiatkowski, D., Phillips, P.C.B., Schmidt, P. and Shin, Y., (1992), Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?, Journal of Econometrics, 54, 159–178.

ur.kpss-class

## Examples

 1 2 3 4 5 data(nporg) gnp <- na.omit(nporg[, "gnp.r"]) gnp.l <- log(gnp) kpss.gnp <- ur.kpss(gnp.l, type="tau", lags="short") summary(kpss.gnp)

### Example output

#######################
# KPSS Unit Root Test #
#######################

Test is of type: tau with 3 lags.

Value of test-statistic is: 0.1976

Critical value for a significance level of:
10pct  5pct 2.5pct  1pct
critical values 0.119 0.146  0.176 0.216

urca documentation built on May 29, 2017, 3:27 p.m.