TESTING SIGMA CONVERGENCE ACROSS EU-28

Abstract

ABSTRACT. The main goal of this research is to assess the degree of convergence in European Union- 28 (EU-28) during 2000-2012. After a spatial analysis of macroeconomic indicators using maps and graphs that were built in GeoDa, the sigma convergence was tested. For this purpose, variation indicators in the simple and weighted variant for GDP per capita in PPS were utilized, the weights being given by the population weights in each country of the EU-28. The results indicated a decrease in divergence process in 2012 compared to 2000, but there is still not enough evidence for the closeness of an acceptable degree of convergence. However, there is a low degree of divergence in EU-28 compared to EU-27 in 2012 with respect to 2000. In 2012, the EU-28 populations explained better the GDP compared to the number of employed persons.JEL Classification: C18, C88, F2, F15Keywords: convergence, sigma convergence, GDP per capita, standard deviation, variance, coefficient of variation.(ProQuest: ... denotes formulae omitted.)IntroductionFor measuring the degree of realization for the convergence process one should assess the levels of different indicators that refer to: variability/homogeneity, polarization, concentration, complementarity, entropy. These indicators might confirm or not different aspects of the convergence process. The most known and applied is the sigma convergence measured by variation indicators.This paper is structured in several parts. After this brief introduction, a short literature review is made, underlying the latest results regarding the convergence assessment. The methodological part consists in the presentation of the statistical indicators used in measuring the variation in GDP/capita. The empirical application supposes the calculation of variation measures for European Union-28. The results put into evidence that during 2000-2012 the convergence criterion was not fulfilled, even if the degree of variability decreased in time. A section dedicated to main conclusions was presented in the end.1. LiteratureAccording to Sala-i-Martin (1996), band s indicators are new tools for measuring the degree of convergence and the speed for getting convergence. s indicator shows the convergence and divergence tendency depending on the value of sample variance. b parameter shows the speed for accomplish the convergence when it has a negative sign. Mankiw, Romer and Weil (1992) and Islam (1995) introduced in the model control variables like saving rate and population growth, showing that the economies with a low initial income tend to grow faster than the economies with higher income. On the other hand, alternative econometric models were developed by Quah (1996) and Durlauf (1996) to show that the transversal growth model is consistent with the multiple mechanisms of endogenous growth and inconsistent with the convergence. The behavior and evolution of convergence-clubs were deeply analyzed. The conventional theory of convergence and the empirical researches hide the convergence-clubs and the polarization of countries in rich in poor. Some economists like Friendman (1992) and Quah (1996) considered the beta indicator as irrelevant for the real convergence process of the economic growth. There are several forms for this tool utilized in econometric analysis: absolute beta convergence, club convergence and conditional beta convergence. The beta and sigma indicators are related and reciprocal checked. The assumption of diminishing yield of the neo-classical theory states that poor economies tend to grow faster than rich ones. This conclusion has the following implications: the coefficient of variation for GDP/capita slowly decreases and there is an inverse relationship between the rate of economic growth for GDP/capita and the initial level of GDP/capita. However, the Sala-i-Martin (1996) suggested that different relationships may occur between these two types of convergence. …