Phillips-Perron Unit Root Test

Usage

PP.test(x, lshort = TRUE)

Arguments

x a numeric vector or univariate time series.
lshort a logical indicating whether the short or long version of the truncation lag parameter is used.

Description

Computes the Phillips-Perron test for the null hypothesis that x has a unit root.

Details

The general regression equation which incorporates a constant and a linear trend is used and the corrected t-statistic for a first order autoregressive coefficient equals one is computed. To estimate sigma^2 the Newey-West estimator is used. If lshort is TRUE, then the truncation lag parameter is set to trunc(4*(n/100)^0.25), otherwise trunc(12*(n/100)^0.25) is used. The p-values are interpolated from Table 4.2, p. 103 of Banerjee et al. (1993).

Missing values are not handled.

Value

A list with class "htest" containing the following components:
statistic the value of the test statistic.
parameter the truncation lag parameter.
p.value the p-value of the test.
method a character string indicating what type of test was performed.
data.name a character string giving the name of the data.

Author(s)

A. Trapletti

References

A. Banerjee, J. J. Dolado, J. W. Galbraith, and D. F. Hendry (1993): Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data, Oxford University Press, Oxford.

P. Perron (1988): Trends and Random Walks in Macroeconomic Time Series. Journal of Economic Dynamics and Control 12, 297-332.

Examples

x <- rnorm(1000)
PP.test(x)
y <- cumsum(x) # has unit root
PP.test(y)


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