Statistical Analysis of Uneven Digitalization Across Russian Regions and Its Impact on the Total Fertility Rate

被引:0
作者
Tonkikh, Natalia V. [1 ,2 ]
Kataev, Vladislav A. [3 ]
Kochkina, Elena M. [3 ]
机构
[1] Ural State Univ Econ, Dept Lab Econ & Personnel Management, 62-45,8 Marta Narodnoy Voli St, Ekaterinburg 620144, Russia
[2] Ural State Univ Econ, Sci & Educ Ctr Technol Innovat Dev, Dept Scientometr R&D & Rankings, 62-45,8 Marta Narodnoy Voli St, Ekaterinburg 620144, Russia
[3] Ural State Univ Econ, 62-45,8 Marta Narodnoy Voli St, Ekaterinburg 620144, Russia
基金
俄罗斯科学基金会;
关键词
digitalisation; information and communication technologies; digital employment; Russian regions; regional differentiation; total fertility rate; cluster analysis; reproductive behaviour; multivariate statistical analysis; fertility factors; CHILDBIRTH; EMPLOYMENT; WOMEN;
D O I
10.17059/ekon.reg.2024-1-7
中图分类号
K9 [地理];
学科分类号
0705 ;
摘要
Russia has been historically characterised by a high regional socio-economic differentiation, including in the sphere of population. Nowadays, information and communication technologies are spreading at different speeds in various regions. Since the impact of digitalisation on fertility is under- studied, it is necessary to find methods for identifying connections between them. The paper assesses the development of Russian regions in terms of the total fertility rate (TFR) in regions differently using information and communication technologies. To this end, the study obtained data from the Federal State Statistics Service, namely, from the section "Information and communication technologies" of re- ports "Regions of Russia: socio-economic indicators". Univariate and multivariate statistical methods were applied. Russian regions were clustered according to 16 indicators characterising their digital de- velopment. Data for 2014 and 2019 were analysed. Three clusters - << best >>, << average >> and << worst >> - were identified. The higher polarisation was observed in 2014: 4 regions were included in the "average" cluster, 29 in the "best" cluster, and 46 in the "worst" cluster. In 2019, the polarisation diminished: 45 re- gions belonged to the "average" cluster, 33 to the "best" cluster, only 4 to the "worst" cluster (Republics of Dagestan, North Ossetia-Alania, Tyva, Chechen Republic). The results show that the total fertility rate is lower in clusters with higher values of digital development. In 2014-2019, TFR decreased by 31.1 % in the "best" and by 47.7 % in the "average" clusters; on the other hand, this indicator increased by 37.7 % in the "worst" cluster. However, it is difficult to assess the exact effect of specific digitalisation factors on fertility due to their complexity and interdependence. Further studies can focus on statistical evaluation of the impact of employment on reproductive behaviour.
引用
收藏
页码:92 / 105
页数:14
相关论文
共 28 条
  • [1] Arkhangelskiy V. N, 2006, Fertility Factors, P399
  • [2] Does broadband Internet affect fertility?
    Billari, Francesco C.
    Giuntella, Osea
    Stella, Luca
    [J]. POPULATION STUDIES-A JOURNAL OF DEMOGRAPHY, 2019, 73 (03): : 297 - 316
  • [3] Opportunities and Threats of Digitalisation for Human Capital Development at the Individual and Regional Levels
    Chernenko, Ilia M.
    Kelchevskaya, Natalya R.
    Pelymskaya, Irina S.
    Almusaedi, Hasan Khayoon Abbas
    [J]. EKONOMIKA REGIONA-ECONOMY OF REGION, 2021, 17 (04): : 1239 - 1255
  • [4] Women's employment patterns after childbirth and the perceived access to and use of flexitime and teleworking
    Chung, Heejung
    van der Horst, Mariska
    [J]. HUMAN RELATIONS, 2018, 71 (01) : 47 - 72
  • [5] Fedorova Alena, 2022, Digitalization of Society, Economics and Management: A Digital Strategy Based on Post-pandemic Developments. Lecture Notes in Information Systems and Organisation (53), P269, DOI 10.1007/978-3-030-94252-6_20
  • [6] A THEORY OF THE VALUE OF CHILDREN
    FRIEDMAN, D
    HECHTER, M
    KANAZAWA, S
    [J]. DEMOGRAPHY, 1994, 31 (03) : 375 - 401
  • [7] Offline effects of online connecting: the impact of broadband diffusion on teen fertility decisions
    Guldi, Melanie
    Herbst, Chris M.
    [J]. JOURNAL OF POPULATION ECONOMICS, 2017, 30 (01) : 69 - 91
  • [8] [Гурова И.М. Gurova I.M.], 2020, [МИР (Модернизация. Инновации. Развитие), MIR (Modernization. Innovation. Research), MIR (Modernizatsiya. Innovatsii. Razvitie)], V11, P128, DOI 10.18184/2079-4665.2020.11.2.128-147
  • [9] [Калабихина Ирина Евгеньевна Kalabikhina I.E.], 2019, [Вестник Московского университета. Серия 6: Экономика, Vestnik Moskovskogo universiteta. Seriya 6: Ekonomika], P147
  • [10] Kalabikhina I. E., 2020, Vestnik Moskovskogo un-ta. Ser. 6. Ekonomika Moscow University Economic Bulletin, V6, P90