Ekonomická konvergence makroregionů EU a formování konvergenčních klubů

This thesis deals with the analysis of the economic convergence process of the European Union macro-regions in the period from 2004 to 2024. Given the empirical failure of traditional neoclassical models of global catching-up, the thesis aims to evaluate the real dynamics of the European space using modern econometric methods. The analysis on a large panel of 88 macro-regions combines spatial econometrics tools with the non-linear Phillips and Sul clustering algorithm. The results prove that Europe is not converging towards a single common steady state, but endogenously splits into five distinct convergence clubs. This division confirms the lead of the innovation core and the lagging of the southern and eastern periphery, with the gap between these areas being significantly deepened by the asymmetric impacts of recent crisis shocks (the Great Recession and the COVID-19 pandemic). The estimation of the ordered logit model further reveals the structural determinants of club membership. The key driver of successful regional convergence is educated human capital, while direct investments in research and development emerge as statistically insignificant without sufficient regional absorptive capacity. The findings question the effectiveness of blanket cohesion policy and emphasize the need for massive support for education in structurally weak areas.