Population movement in the Republic of Bashkortostan: a multi-factor analysis on panel data

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Introduction. The study deals with natural movement of the population in the Republic of Bashkortostan at the regional and municipal levels.

The aim of the study is to assess the factors affecting the natural movement of the population of the Republic of Bashkortostan (RB).

Material and methods. The information base was the official statistical materials of the Territorial Body of the Federal State Statistics Service for the Republic of Bashkortostan: collections “Demographic Processes in the Republic of Bashkortostan”, “Socio-Economic Situation of Municipal Areas and Urban Districts of the Republic of Bashkortostan”; Rosstat data: collections “Regions of Russia. Socio-economic indices”. We considered data consisting of observations on rural municipalities in RB 54 municipal districts and 21 cities (urban communities and urban settleme;ts), tracked in dynamics for 16 years (2002–2017). At the first stage, municipalities were divided into five groups using cluster analysis based on natural growth indices. Then, to study the influence of medico-demographic, socio-infrastructural, socio-economic factors on the indices of the population’s natural movement, multivariate regression analysis was used. Due to the panel nature of the data, models with fixed individual and time effects were used.

Results. In the studied groups of municipalities, formed using cluster analysis, the significance of individual factors in terms of their influence on the performance indicator is significantly different, which necessitates taking this spatial heterogeneity into account when developing socio-economic policy measures. To confirm the existence of a relationship between the rate of natural population growth and per capita money income, the general rate of marriages, divorces, the proportion of women of fertile age, unemployment, and the ratio of the population over working age, we based the constructed regression models with fixed effects on panel data

Conclusion. Analysis of the results obtained and comparing them with the literature data allow us to determine the priorities of socio-economic, demographic policy at the regional level. 

作者简介

Rasul Askarov

Russian State Geological Prospecting University

编辑信件的主要联系方式.
Email: noemail@neicon.ru
ORCID iD: 0000-0001-7980-4113
俄罗斯联邦

Marina Frants

Ufa State Aviation Technical University

Email: noemail@neicon.ru
ORCID iD: 0000-0002-5324-2463
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Zagira Askarova

Bashkir State Medical University

Email: zagira_a@mail.ru
ORCID iD: 0000-0001-9772-1311

MD, Ph.D., DSci., Professor of the Department of Hospital Therapy No. 2, Bashkir State Medical University, Ufa, 450008, Russian Federation.

e-mail: zagira_a@mail.ru

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Irina Utyasheva

Territorial Agency of the Federal State Statistics Service for the Republic of Bashkortostan

Email: noemail@neicon.ru
ORCID iD: 0000-0001-6444-1452
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Guzel Abdrakhmanova

Bashkir State Medical University

Email: noemail@neicon.ru
ORCID iD: 0000-0001-8848-0181
俄罗斯联邦

参考

  1. Gorina E.A., Burdyak A.Ya. Quality of life in big city through the urban environment perceptions. Sotsiologiya goroda. 2015; (2): 11–31. (in Russian)
  2. Demographic Processes in the Republic of Bashkortostan: Statistical Collection [Demograficheskie protsessy v Respublike Bashkortostan: Statisticheskiy sbornik]. Ufa: Bashkortostanstat; 2000-2018. (in Russian)
  3. Demographic Yearbook of Russia [Demograficheskiy ezhegodnik Rossii]. Moscow: Rosstat; 2000-2017. (in Russian)
  4. Socio-Economic Situation of Municipal Districts and Urban Districts of the Republic of Bashkortostan: Statistical Collection [Sotsial’no-ekonomicheskoe polozhenie munitsipal’nykh rayonov i gorodskikh okrugov Respubliki Bashkortostan: Statisticheskiy sbornik]. Ufa: Bashkortostanstat; 2000-2018. (in Russian)
  5. Regions of Russia. Socio-Economic Indicators. Statistical Collection [Regiony Rossii. Sotsial’no-ekonomicheskie pokazateli. Statisticheskiy sbornik]. Moscow: Rosstat; 2002-2018. (in Russian)
  6. Ratnikova T.A., Furmanov K.K. Analysis of Panel Data and Data on the Duration of States [Analiz panel’nykh dannykh i dannykh o dlitel’nosti sostoyaniy]. Moscow; 2014. (in Russian)
  7. Isakin M.A. Modification of the k-means method with an unknown number of classes. Prikladnaya ekonometrika. 2006; (4): 62–73. (in Russian)
  8. Plyuta V. Wielowymiarowa analiza porownawcza w badaniach ekonomicznych: Metody taksonomiczne i analizy czynnikowej. Warszawa: Państwowe Wydaw. Ekonomiczne; 1977. (in Polish)
  9. Askarov R.A., Karelin A.O., Lakman I.A., Rozanova L.F., Askarova Z.F. Segmentation of territories of the Republic of Bashkortostan on the level of mortality from malignant neoplasms. Zdravookhranenie Rossiyskoy Federatsii. 2019; 63(1): 4–13. https://doi.org/10.18821/0044-197X-2019-63-1-4-13 (in Russian)
  10. Tapilina V.S. Socio-economic status and population’s health. Sotsiologicheskie issledovaniya. 2004; (3): 126–37. (in Russian)

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