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56th Congress of the European Regional Science Association: "Cities & Regions: Smart, Sustainable, Inclusive?", 23-26 August 2016, Vienna, Austria
The purpose of this study is to investigate the relation between regional convergence inside of countries in EU and overall economic growth, and, based on it, to establish some relevant behavioural regimes. As data sources we are using the available dataset NUTS 2 from EUROSAT for the period 2000-2013. Thus, a number of 272 regions grouped in 28 countries we used as primary database. Then, because six countries (Cyprus, Estonia, Latvia, Lithuania, Luxembourg, and Malta) are not divided in regions in NUTS 2 database, we made few aggregations, finally resulting 24 countries or groups of countries. In order to study the correlation between the convergence process and economic growth we focused, as it is usually used in specialised literature to analyse the real convergence, on the dynamics of GDP per capita expressed in case of EU by PPS (Purchasing Power Standard). On the one hand, as a method to estimate of a trend of convergence/divergence among regions within a country or group of countries we used the dynamics of the coefficient of variation. On the other hand, within EU, we used for each country or group of countries the dynamics of the ratio between the individual level of GDP per capita and the average EU GDP per capita. Thus we evaluate how the position of a country it was changed relative to the average level in EU of GDP per capita. Moreover, the correlation between the regional convergence (within a country) and the changes in its position in EU (in matter of GDP per capita) was estimated. Based on such methodology, we succeeded to elaborate a general typology that permitted us to classify countries of EU in four major groups: 1) countries that improved their position in EU (as GDP per capita), but only by scarifying the regional convergence; 2) countries in which it was registered a regional convergence, but only by scarifying their position in EU; 3) countries for which both their position in EU was decreasing and a regional divergence it was registered (the most unfavourable dynamics); 4) countries for which both their position in EU was increasing and a regional convergence was registered (the most favourable dynamics). Moreover, by using the above results and by applying linear regression models we estimated four discrete regimes, depending on the level of GDP per capita, in which countries evolved in the analysed period (corresponding to the four groups of countries) and three transitional regimes. Finally, we propose a nonlinear model (estimated by using real registered data) that permits us to simulate a smooth trajectory of convergence as a continuous function of development level (expressed by GDP per capita) and could offer to policy makers a large menu of sub-regimes.
GDP per capita
GDP per capita
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