Regional Differentiation of Human Potential Indicators
DOI:
https://doi.org/10.17059/2015-4-15Keywords:
human potential, quality of population, human resources, cluster analysis, regional level, typology of regions, economic indicators, social indicators, subjects of the Federation, interregional analysisAbstract
We purpose of the article is the interregional analysis of human potential. In comparison with the quality of life of the population, the quality of population itself is studied far less. The article presents an expanded characteristic of human potential in seven directions: economic activity, demographic processes, physical health, cultural potential, social health, educational potential and the attitude of the population to the environment. On the basis of statistics for 2008-2012 years, 63 indicators of human potential for all directions are selected. In the final result, the correlation analysis has led to the substantiation of the system of indicators consisting of 10 indicators. Three economic and seven social indicators characterizing human potential are included into this system. On the basis of the indicators by means of hierarchical agglomerative methods of cluster analysis, a classification of the Russian regions is carried out in two versions: with economic indicators and without them. The result of the calculations is a stable temporal typology of regions by indicators of human potential covering 74.4 % of the population of Russia. We article provides a substantial interpretation of dividing regions into groups, identifies the strengths and weaknesses of each cluster, shows the specific features of the regions included into the clusters. We obtained results can be used in the development of measures for the reduction of the interregional inequality in terms of human potential. It is possible to define what measures can be effective by studying the strategic directions of the development of regions in the cluster which is the most successful regarding the characteristics of human potential.References
Ryumia, Ye. V. (2014). Ekologicheskaya kharakteristika kachestva naseleniya [Ecological characteristic of quality of the population]. Ekonomika regiona [Economy of region], 3, 82–90.
Lokosov, V. V. (Ed.). (2015). Narodonaselenie sovremennoy Rossii. Vosproizvodstvo i razvitie [Population of modern Russia. Reproduction and development]. Moscow: Ekon-Inform Publ., 411.
Sorokin, P. (1922). Sovremennoye sostoyanie Rossii [Current state of Russia]. Prague: Khutor Publ., 112.
Soboleva, I. V. (2007). Chelovecheskiy potentsial rossiyskoy ekonomiki: problemy sokhraneniya i razvitiya [Human potential of the Russian economy: problems of preservation and development]. Moscow: Nauka Publ., 202.
Frolov, I. E. (Ed.). (1999). Chelovecheskiy potentsial: opyt kompleksnogo podkhoda [Human potential: experience of an integrated approach]. Moscow: Editorial URSS Publ., 176.
Chelovecheskoye razvitie. Novoye izmerenie sotsialno-ekonomicheskogo progressa [Human development. New measurement of social and economic progress]. Moscow: Prava cheloveka Publ., 636.
Bobylev, S. N. (Ed.) (2013). Doklad o chelovecheskom razvitii v Rossiyskoy Federatsii 2013 «Ustoychivoye razvitie: vyzovy Rio» [Report on human development in the Russian Federation 2013 «A sustainable development: challanges of Rio»]. Moscow: RA ILF Publ., 202.
Grigoryev, L. M. & Bobylev, S. N. (2014). Doklad o chelovecheskom razvitii v Rossiyskoy Federatsii za 2014 god [The report on human development in the Russian Federation for 2014]. Moscow: Analiticheskiy tsentr pri Pravitelstve Rossiyskoy Federatsii Publ., 204.
Human Development Report 2013. The Rise of the South: Human Progress in a Diverse World. (2014). New York: UNDP, 216.
Human Development Report 2014: Sustaining Human Progress. Reducing Vulnerabilities and Building Resilience. (2014). New York: UNDP, 239.
Toksanbaeva, M. S. (2006). Sotsialnyye interesy rabotnikov i ispolyzovanie trudovogo potentsiala [Social interests of workers and use of labor potential]. Moscow: Nauka Publ., 259.
Ayvazyan, S. A., Bukhshtaber, V. M., Yenyukov, I. S. & Meshalkin, L. D. (1989). Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti [Applied statistics. Classification and decrease in dimension]. Moscow: Finansy i statistika Publ., 607.
Everitt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster analysis. Fifth Edition. U.K: John Wiley & Sons, 346.
Rokach, L. A (2010). Survey of Clustering Algorithms. Data Mining and Knowledge Discovery Handbook. Second Edition. In: Oded Maimon and Lior Rokach (Eds). New York: Springer, 269–298.
Dan, A. Simovici & Chabane Djeraba (2014). Mathematical Tools for Data Mining. Second edition. London: Springer-Verlag, 831.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2015 Vyacheslav Veniaminovich Lokosov, Yelena Viktorovna Ryumina, Vladimir Vasilyevich Ulyanov

This work is licensed under a Creative Commons Attribution 4.0 International License.

