Content №1 от 2017
Russian NEET Youth: Analysis of Regional Differentiation
The paper analyzes regional differences in the NEET youth (acronym from «Not in Employment, Education or Training))) marking indicators. It shows that this group has a high-risk for socio-economic marginalization and exclusion. The empirical research base is constituted by the Labor Force Survey and regional statistical data for 2014. To investigate spatial effects, we have used the Moran's I coefficient and spatial econometric models. The research results indicate that the NEET rate vividly differs depending on a region, with cross-regional NEET rate variations in unemployment prove to be more obvious as compared to the NEET economic inactivity indicator differentiations. The results obtained illustrate the positive spatial correlation between the regional NEET unemployment rates, which testifies to territorial interconnections and regional clusterization. We assess factors having an impact on the regional differentiation in the NEET unemployment and NEET economic inactivity rates. The cross-regional variations are determined by the GRP per capita, urban population share, industry employment structure, youth education level, and birth and death rates. The NEET rate for young men and young women varies being affected by different factors, where with the former it is more often linked to individual behavioral characteristics, while with the latter one it is, to a greater extent, influenced by socio-economic indicators for the regions. Thus, we confirm the significance of a regionally differentiated approach to working out and exercising a youth employment policy aimed at maximizing their labor potential.
