Bandwidth selection, prewhitening, and the power of the Phillips-Perron test

This study examines several important practical issues concerning nonparametric estimation of the innovation variance for the Phillips-Perron (PP) test. A Monte Carlo study is conducted to evaluate the potential effects of kernel choice, data-based bandwidth selection, and prewhitening on the power property of the PP test in finite samples. The Monte Carlo results are instructive. Although the kernel choice is found to make little difference, data-based bandwidth selection and prewhitening can lead to power gains for the PP test. The combined use of both the Andrews (1991, Econometrica 59, 817-858) data-based bandwidth selection procedure and the Andrews and Monahan (1992, Econometrica 60, 953-966) prewhitening procedure performs particularly well. With the combined use of these two procedures, the PP test displays relatively good power in comparison with the augmented Dickey-Fuller test. © 1997 Cambridge University Press.