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Title: | The use of cluster analysis for demographic policy development: Evidence from Russia |
Authors: | Shubat, O. Bagirova, A. Abilova, M. Ivlev, A. |
Issue Date: | 2016 |
Publisher: | European Council for Modelling and Simulation |
Citation: | The use of cluster analysis for demographic policy development: Evidence from Russia / O. Shubat, A. Bagirova, M. Abilova, et al. — DOI 10.7148/2016-0159 // Proceedings - 30th European Conference on Modelling and Simulation, ECMS 2016. — 2016. — P. 159-165. |
Abstract: | Russia has been experiencing a demographic crisis since the 1990s. The most obvious manifestations include an excess of mortality over fertility rates, population decline and an ageing population. The last 20 years have seen considerable activity to come up with new demographic policy measures to mitigate these adverse trends, with single solutions developed for all regions in Russia. This paper presents the results of a study where cluster analysis was applied to enable the identification of groups of regions with significant differences in the dynamics of socio-demographic indicators. We used hierarchical cluster analysis to classify and group Russian regions on the basis of social and economic development indices for 2002 and 2008. The validity of the profiling was confirmed using parametric and non-parametric tests. The analysis identified three clusters of Russian regions. These clusters have significant differences in socio-demographic indicators and the associated dynamics. The results of our analysis identified 'growth points' for each cluster: the fertility correlates that should be factored into the development of effective demographic policy measures. © ECMS Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose (Editors). |
Keywords: | BIRTH RATE CLUSTER ANALYSIS DEMOGRAPHIC POLICY FERTILITY RUSSIAN REGIONS CLUSTER ANALYSIS HIERARCHICAL SYSTEMS BIRTH RATES FERTILITY HIERARCHICAL CLUSTER ANALYSIS NON-PARAMETRIC TEST POLICY DEVELOPMENT POPULATION DECLINE RUSSIAN REGIONS SOCIAL AND ECONOMIC DEVELOPMENT POPULATION STATISTICS |
URI: | http://elar.urfu.ru/handle/10995/102761 |
Access: | info:eu-repo/semantics/openAccess |
SCOPUS ID: | 84978763003 |
WOS ID: | 000386310800021 |
PURE ID: | 7993ff2c-7c3c-437d-918f-0069e71b9a83 1059596 |
ISBN: | 9780993244025 |
DOI: | 10.7148/2016-0159 |
Appears in Collections: | Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC |
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