The analysis of regional convergence often stays at the level of documentation, with limited attention placed on the drivers of convergence/divergence dynamics. This article offers a systematic analysis of this, examining the role of first-nature (location, proximity, physical geography) and second-nature geography (economic structure, agglomeration, economic potential) in accounting for regional synchronicity in growth trajectories (stochastic convergence). Utilising historical data for Greece at the prefectural level and up-to-date time-series econometric techniques, we test for the presence of stochastic convergence in the country over three decades prior to the crisis; identify the pairs of regions which exhibit co-movement in their growth dynamics; and examine the covariates of this. Our results unveil a picture of limited-only and cluster-like convergence, driven predominantly by factors related to accessibility, sectoral specialisations, labour market dynamism, market potential and selected locational characteristics. This supports two propositions: (a) convergence is an endogenous process, related to shared and incongruent characteristics of regions; and, by implication, (b) regional disparities are structural (in the sense that they are linked to economic and spatial structure) and thus require targeted policies in order to be addressed.
- first and second nature geography
- pairwise approach
- stochastic convergence