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Modern-Day Contrasts of Inter-Regional Migration in Russia
The paper studies an interregional competition for a unique scarce resource, namely human capital assets, which is unfolding in the Russian migration space. It is visualized within a model of a current seven-cluster structure of migration in regions of Russia which uses ten classic indicators of migration. The database comprises material from Russian Federal State Statistics Service. We show that our cluster structure of migration in regions, although slightly “patched-up” in its geography, has profound and stable migration contrasts and dissonances. In general, it proves a dangerous migration trend of the last three decades which still remains in the second decade of the XXI century—migration flows are highly center-oriented; it leaves eastern and northern frontiers of the country deserted and does not react to any attempts to rectify the situation in the framework of the Concept of State Migration Policy of the Russian Federation till 2025 as approved by the President. We confirm that the Russian migration space is “self-organized” and has hierarchical structure. The Cluster No. 1, pole of attraction for migration flows, stands on top and accumulates population from the borders. The cluster of “migration catastrophe” (Cluster No. VII) is the lowest; it destabilizes economic and sociocultural environment creating catastrophically large migration loss
Keywords: internal interregional migration region cluster analysis indicators of migration clusters of migration catastrophe concept of state migration policy migration contrasts
Diagnostics of Siberian Innovation Development
The paper considers methodological aspects of diagnosing the regional innovation development, and illustrates such aspects by the results obtained by the factor, regression and cluster analysis of the innovation development indicators. This allowed identifying the innovation profiles of Russia and the Siberian Federal District in 2007 and 2010. We show how the sets of factors and indicators which statistically explain the innovation development in the country and Siberia in different years differ from each other. By a cluster analysis we identify three groups of the Siberian regions which have similar innovation profiles, and we also build the GRP regressions on innovation indicators for the SFD regions.
Kaneva M. A . mkaneva@ieie.nsc.ru
Untura G. A. untura@ieie.nsc.ru
Keywords: innovation status innovation strategy region scientific and research works innovation strategy region R&D factor analysis
