By Stilianos Alexiadis
Do dynamic externalities, within the kind of expertise construction, adoption and spatial agglomeration form the trend of neighborhood progress in Europe? This learn presents an alternate view on nearby convergence. A version is constructed which attributes club-convergence to latest adjustments with recognize to the measure of know-how adoption. within the first example, empirical effects recommend that the NUTS-2 areas of the EU-27 converge at a truly sluggish fee. additional exams, although, point out that convergence is particular to a particular subset of areas. Such conclusions are verified additional, utilizing another version of club-convergence, which contains the influence of spatial interplay, agglomeration externalities and expertise. This exhibits that the convergence-club in Europe follows a undeniable geographical trend and all contributors percentage comparable features concerning know-how construction and adoption, and agglomeration externalities.
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Extra resources for Convergence Clubs and Spatial Externalities: Models and Applications of Regional Convergence in Europe
Hence, ‘poor’ regions have low a capital-labour ratio whilst ‘rich’ regions are characterised by a high capital-labour ratio. These differences between regions are, however, due to different structural characteristics embodied in the savings propensity s and rate of population growth n. In the framework outlined thus far, the prediction of regional convergence to the same equilibrium depends on the condition that all regions have the same structural characteristics. However, a crucial question remains as to how ‘poor’ regions catch up to ‘rich’ regions even if there are no differences in structural characteristics.
2 The Neoclassical Approach to Regional Growth 19 The impact of technological change may be modelled in a number of ways. 7 Hence, the rate of output growth is driven by three separate sources (Richardson, 1973b): capital accumulation, an increase in labour supply and a residual, which may be called technical progress, and which includes everything that improves the efficiency of a given stock of resources. In the neoclassical model technological progress may also be incorporated into the production function in a ‘labour-augmented’ form.
Additional investment in physical capital is not as profitable in the ‘rich’ region (i) as each addition to the capital stock in region i generates smaller additions to output in comparison to region j. The ‘poor’ region will grow faster than the ‘rich’ region, or more specifically, the region with the lower capital-labour ratio will grow at a faster rate, as both regions move towards the same steady-state level of kÃ . Although highly restrictive in terms of assumptions, the neoclassical model nevertheless provides significant insights into how a ‘poor’ region might catch up with a ‘rich’ one.