We investigate club convergence in income per capita in 194 European NUTS-2 regions using a nonlinear, time-varying factor model that allows for individual and transitional heterogeneity. Moreover, we extend an existing club clustering algorithm with two post-clustering merging algorithms that finalize club formation. We also apply an ordered response model to assess the role of initial and structural conditions, as well as geographic factors. Our results indicate the presence of four convergence clubs in the EU-15 countries. In support of the club convergence hypothesis, we find that initial conditions matter for the resulting income distribution. Geographic clustering is quite pronounced; besides a north-to-south division, we detect highincome clusters for capital cities. We conclude that the main supranational policy challenge is the politically sensitive handling of a multi-speed Europe.
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