In this paper we propose a simple extension to the panel case of the covariate-augmented Dickey Fuller (CADF) test for unit roots developed in Hansen (1995). The extension we propose is based on a p-values combination approach that takes into account cross-section dependence. We show that the...

The Italian labour market is characterized by large and persistent regional unemployment differentials. This study uses recent panel unit root and cointegration tests to derive the long-run properties of the Italian regional unemployment disparities. The empirical evidence suggests that the...

Sequential panel selection methods (spsms) are based on the repeated application of panel unit root tests and are increasingly used to identify I (0) time series in macro- panels. We check the reliability of spsms by using Monte Carlo simulations based on generating the individual test...

In this paper we propose a simple extension to the panel case of the covariate- augmented Dickey Fuller (CADF) test for unit roots developed in Hansen (1995). The extension we propose is based on a p values combination approach that takes into account cross-section dependence. We show that the...

In this paper we propose the extension of the covariate-augmented Dickey Fuller (CADF) test for unit roots developed by Hansen (1995} to the panel case. We show that the extension is viable and gives power gains with respect to the time series approach. Particular attention is paid to cross-unit...

This paper provides a theoretical functional representation of the density function related to the Dickey- Fuller random variable. The approach is extended to cover the multivariate case in two special frameworks: the independence and the perfect correlation of the series.

The aim of this paper is to test the stochastic convergence in real per capita GDP for 15 European countries using non-stationary panel data approaches over the period 1950-2003. Cross-sectional dependence is assumed due to the existence of strong linkages among European economies. However,...

The false discovery rate (FDR) first introduced in Benjamini and Hochberg (1995) is a powerful approach to multiple testing. Benjamini and Yekutieli (2001) proved that the original procedure developed for independent test statistics controls the FDR also for positively dependent test statistics....

The false discovery rate (FDR, Benjamini and Hochberg 1995) is a powerful approach to multiple testing. However, the original approach developed by Benjamini and Hochberg (1995) applies only to independent tests. Yekutieli (2008) showed that a modification of the Benjamini-Hochberg (BH) approach...