Practitioners' corner: Panel unit-root tests for cross-sectionally correlated panels: A Monte Carlo comparison

This paper deals with the finite-sample performance of a set of unit-root tests
for cross-correlated panels. Most of the available macroeconomic time series
cover short time periods. The lack of information, in terms of time
observations, implies that univariate tests are not powerful enough to reject
the null of a unit-root while panel tests, by exploiting the large number of
cross-sectional units, have been shown to be a promising way of increasing
the power of unit-root tests. We investigate the finite sample properties of
recently proposed panel unit-root tests for cross-sectionally correlated panels.
Specifically, the size and power of Choi’s [Econometric Theory and Practice:
Frontiers of Analysis and Applied Research: Essays in Honor of Peter C. B.
Phillips, Cambridge University Press, Cambridge (2001)], Bai and Ng’s
[Econometrica (2004), Vol. 72, p. 1127], Moon and Perron’s [Journal of
Econometrics (2004), Vol. 122, p. 81], and Phillips and Sul’s [Econometrics
Journal (2003), Vol. 6, p. 217] tests are analysed by a Monte Carlo simulation
study. In synthesis, Moon and Perron’s tests show good size and power
for different values of T and N, and model specifications. Focusing on Bai and Ng’s procedure, the simulation study highlights that the pooled Dickey–
Fuller generalized least squares test provides higher power than the pooled
augmented Dickey–Fuller test for the analysis of non-stationary properties of
the idiosyncratic components. Choi’s tests are strongly oversized when the
common factor influences the cross-sectional units heterogeneously.