This paper extends the cross-sectionally augmented IPS (CIPS) test of Pesaran (2006) to a three-dimensional (3D) panel. This 3D-CIPS test is correctly sized in the presence of cross-sectional dependency. Comparing its power performance to that of a bootstrapped IPS (BIPS) test, we find that the...

This paper generalises the monthly seasonal unit root tests of Franses (1991) for a heterogeneous panel following the work of Im, Pesaran, and Shin (2003), which we refer to as the F-IPS tests. The paper presents the mean and variance necessary to yield a standard normal distribution for the...

This paper uses the approach of Im, Pesaran and Shin (2003) to propose seasonal unit root tests for dynamic heterogeneous panels based on the means of the individuals HEGY test statistics. The standardised t-bar and F-bar statistics are simply averages of the HEGY tests across groups. These...

This paper presents two alternative methods for modifying the HEGY-IPS test in the presence of cross-sectional dependency. In general, the bootstrap method (BHEGY-IPS) has greater power than the method suggested by Pesaran (2007) (CHEGY-IPS), although for large T and high degree of...

The panel variant of the KPSS tests developed by Hadri (2000) for the null of stationarity suffers from size distortions in the presence of cross section dependence. However, applying the bootstrap methodology we find that these tests are approximately correctly sized.

This paper estimates response surface coefficients for a large range of quantiles of the cross-sectionally augmented IPS (CIPS) test of Pesaran (<CitationRef CitationID="CR13">2007</CitationRef>), for different specifications of the deterministic components. An Excel programme is available to calculate the P value associated with a CIPS...</citationref>

This paper calculates response surface models for a large range of quantiles of the Leybourne (Oxf Bull Econ Stat 57:559–571, <CitationRef CitationID="CR9">1995</CitationRef>) test for the null hypothesis of a unit root against the alternative of (trend) stationarity. The response surface models allow the estimation of critical values...</citationref>