Panel Unit Root Tests under Cross-sectional Dependence: an Overview

نویسنده

  • LAURA BARBIERI
چکیده

The increasing availability of new datasets where the time-series dimension and the cross-section dimension are of the same order of magnitude asks for new techniques for the analysis of this peculiar kind of data. In the panel unit root test framework, two generations of tests have been developed: a first generation whose main limit is the assumption of cross-sectional independence across units; a second generation of tests that rejects the cross-sectional independence hypothesis. Although within this second generation of tests different approaches can be distinguished on the basis of the way in which the cross-sectional dependence is modelled the one that has encountered the most attention among researchers is the factor structure approach. This paper provides an updated overview of the main tests belonging to the second generation, and underlines the main issues which remain to be solved.

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تاریخ انتشار 2009