Socio-Economic Inequality and Economic Growth: Measurements for Central and Eastern Europe

The objective of this work is the study of social and economic inequality in the space of Central and Eastern  Europe and its impact on economic growth. Our study includes a three-stage methodology: (1) application of a clustering method based on neural network (Self Organising Maps), to the series of panel data in order to divide countries into clusters, corresponding to the degree of economic and social inequality; (2) computing a composed index of economic and social inequality, using Principal Component Analysis and an extension of the method provided by OECD for computing composite indicators; (3) constructing an econometric model to establish the impact of social and economic inequality on economic growth and a VAR model to determine the causality between main determinants to growth and inequality as well as the response to shocks to the dynamics of the variables. The 24 Eastern and Central European countries have been grouped in five clusters, according to 11 attributes. In the results obtained, the third cluster comprises countries with the most equitable income distribution: Czech Republic, Croatia, Hungary, Slovak Republic, Slovenia. To the opposite side is the fifth cluster with the deepest inequality, including only one country, namely Georgia. The second and third steps of our methodology, were applied only for the extreme clusters namely, the clusters with the highest (C5) and lowest (C3) inequality respectively.