Tests For Convergence Clubs

In many applications common in testing for convergence the number of cross-sectional units is large and the number of time periods are few. In these situations tests which are founded upon an omnibus null hypothesis are characterised by a number of problems. In this paper the authors consider a broad class of tests of convergence based on multivariate time series and panel data methodologies, and track a gradual progression away from tests based on an omnibus null, to sequential tests and tests that are founded upon multiple pairwise comparisons. In a previous study Corrado, Martin and Weeks (2005) test for regional convergence across the European Union allowing for an endogenous selection of regional clusters using a multivariate test for stationarity.

Provided by: University of Cambridge Topic: Data Management Date Added: Jan 2011 Format: PDF

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