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Phillips–Perron test

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In statistics, the Phillips–Perron test is a unit root test. That is, it is used in time series analysis to test the null hypothesis that a time series is I(1). It builds on the Dickey–Fuller test, but unlike the augmented Dickey–Fuller test, which extends the Dickey–Fuller test by including additional lagged variables as regressors in the model on which the test is based, the Phillips–Perron test makes a non-parametric correction to the t-test statistic to capture the effect of autocorrelation present when the underlying autocorrelation process is not AR(1) and the error terms are not homoscedastic.

Reference

  • Phillips, P.C.B and P. Perron (1988), "Testing for a Unit Root in Time Series Regression", Biometrica, 75, 335–346
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