This study suggests a two-step approach to identifying and interpreting regional
convergence clubs in Europe. The first step involves identifying the number and composition
of clubs using a space-time panel data model for annual income growth rates in
conjunction with Bayesian model comparison methods. A second step uses a Bayesian
space-time panel data model to assess how changes in the initial endowments of variables
(that explain growth) impact regional income levels over time. These dynamic
trajectories of changes in regional income levels over time allow us to draw inferences regarding
the timing and magnitude of regional income responses to changes in the initial
conditions for the clubs that have been identified in the first step. This is in contrast
to conventional practice that involves setting the number of clubs ex ante, selecting the
composition of the potential convergence clubs according to some a priori criterion (such
as initial per capita income thresholds for example), and using cross-sectional growth
regressions for estimation and interpretation purposes. (authors' abstract)
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3966 |
| Date | 10 1900 |
| Creators | Fischer, Manfred M., LeSage, James P. |
| Publisher | WU Vienna University of Economics and Business |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Paper, NonPeerReviewed |
| Format | application/pdf |
| Relation | http://epub.wu.ac.at/3966/ |
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