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dc.contributor.authorShubat, O.en
dc.contributor.authorBagirova, A.en
dc.contributor.authorAbilova, M.en
dc.contributor.authorIvlev, A.en
dc.date.accessioned2021-08-31T15:05:16Z-
dc.date.available2021-08-31T15:05:16Z-
dc.date.issued2016-
dc.identifier.citationThe 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.en
dc.identifier.isbn9780993244025-
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access, Green3
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978763003&doi=10.7148%2f2016-0159&partnerID=40&md5=02f6c9bf7d32b7bd246327d82f516e49
dc.identifier.urihttp://elar.urfu.ru/handle/10995/102761-
dc.description.abstractRussia 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).en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherEuropean Council for Modelling and Simulationen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceProc. - Eur. Conf. Model. Simul., ECMS2
dc.sourceProceedings - 30th European Conference on Modelling and Simulation, ECMS 2016en
dc.subjectBIRTH RATEen
dc.subjectCLUSTER ANALYSISen
dc.subjectDEMOGRAPHIC POLICYen
dc.subjectFERTILITYen
dc.subjectRUSSIAN REGIONSen
dc.subjectCLUSTER ANALYSISen
dc.subjectHIERARCHICAL SYSTEMSen
dc.subjectBIRTH RATESen
dc.subjectFERTILITYen
dc.subjectHIERARCHICAL CLUSTER ANALYSISen
dc.subjectNON-PARAMETRIC TESTen
dc.subjectPOLICY DEVELOPMENTen
dc.subjectPOPULATION DECLINEen
dc.subjectRUSSIAN REGIONSen
dc.subjectSOCIAL AND ECONOMIC DEVELOPMENTen
dc.subjectPOPULATION STATISTICSen
dc.titleThe use of cluster analysis for demographic policy development: Evidence from Russiaen
dc.typeConference Paperen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.7148/2016-0159-
dc.identifier.scopus84978763003-
local.contributor.employeeShubat, O., Ural Federal University, Ekaterinburg, 620002, Russian Federation
local.contributor.employeeBagirova, A., Ural Federal University, Ekaterinburg, 620002, Russian Federation
local.contributor.employeeAbilova, M., Magnitogorsk State Technical University, Magnitogorsk, 455000, Russian Federation
local.contributor.employeeIvlev, A., Magnitogorsk State Technical University, Magnitogorsk, 455000, Russian Federation
local.description.firstpage159-
local.description.lastpage165-
dc.identifier.wos000386310800021-
local.contributor.departmentUral Federal University, Ekaterinburg, 620002, Russian Federation
local.contributor.departmentMagnitogorsk State Technical University, Magnitogorsk, 455000, Russian Federation
local.identifier.pure7993ff2c-7c3c-437d-918f-0069e71b9a83uuid
local.identifier.pure1059596-
local.identifier.eid2-s2.0-84978763003-
local.identifier.wosWOS:000386310800021-
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