ENVIRONMENTAL PROTECTION IN ROMANIA THROUGH EUROPEAN STRUCTURAL FUNDS – A SPATIAL ECONOMETRICS APPROACH

European Structural Funds have been created with the clear goal to redistribute money among European Union members in such a way as to help poorer regions diminish the gaps between them and the richer ones. The present study assesses this problem for the Structural Operational Programme Environment in Romania. Using spatial econometrics methods, we evaluate two issues on the sample of 42 Romanian counties. The first one is if any clusterization process takes place in what regards contracting funds through ESF for environmental protection projects. The second one is intended to test whether the main principle of the ESF is satisfied – helping the poor in a sustainable development process. Using the quartile maps and the spatial Moran’s I autocorrelation coefficient we show different results for the clusterization topic. When considering the budget value of the projects implemented through SOP ENV, both as total and as eligible share, Romanian counties group based on a positive global spatial autocorrelation. This means that counties with approximately the same budget levels are neighbours. Transylvanian counties have gained the most out of the projects on environment. When the number of contracts is assessed, the distribution of the counties proves to be random and no global spatial autocorrelation was found. Moreover, the map analysis shows that, in general, there is a negative relationship between the value of the budget and the number of contracts. The spatial regression analysis shows the violation of the ESF principle. The coefficients of the GDP are positive. This implies a direct relationship between the richness of the county and the projects implemented through the SOP ENV. Thus, instead of being used by the poorer regions, money goes to the richer ones. The higher the GDP, the higher the value of the budget for the environmental protection programmes financed through European funds. The GDP also positively influences the number of contracts scheduled or signed, but the only at a 10% significance level.