Preview

Voprosy statistiki

Advanced search

Statistical Estimates of the Decline of the Russian Fertility: Regional Specifcs

https://doi.org/10.34023/2313-6383-2021-28-5-39-48

Abstract

The study focuses on analyzing regional features of the decline in the birth rate in Russia in 2016–2019. Taking into account regional specifcs is crucial when perfecting the implemented measures for improving the general demographic situation in the Russian Federation.

The information base of the study contained time series of the total fertility rate in selected Russian regions. The author used methods of descriptive statistics and assessed convergent trends based on the sigma-, beta- and gamma-convergence methods. Spatial effects in regional differentiation of fertility were assessed based on Moran's I.

As a result of the analysis, the following features were established. Firstly, in recent years in Russia, there has been a high degree of differentiation in the recorded declining birth rates. Secondly, the processes of falling fertility in the regions have specifc characteristics, the absence of typical trajectories in those subjects where it fell most or least of all. Thirdly, in Russia, there are no pronounced territo rial localizations of the processes of fertility decline. And fourthly, based on a comparison of the birth rate dynamics in Russian regions, no convergent trends have been identifed, i. e., there is no convergence of territorial entities in terms of the birth rate.

According to the author, the demographic policy of recent years has not yet responded positively either in terms of birth rate growth or leveling of regional differences. The results obtained indicate that unifed approaches are unsuited to solving the demographic problems of Russian territories, and there is a need for demographic policy measures that take into account regional variability and are aimed at smoothing regional disproportions. Consequently, it is necessary to conduct regular statistical and demographic studies of the specificity of regional situations using methods of convergence and spatial autocorrelation analysis, rarely used in demography

About the Author

O. M. Shubat
Ural Federal University named after the frst President of Russia B.N. Yeltsin
Russian Federation

 Oksana M. Shubat – Cand. Sci. (Econ.), Associate Professor; Associate Professor, Academic Department of Economics and Management of Metallurgy and Industrial Enterprises

 19, Mira Str., 620002, Ekaterinburg 



References

1. Glinskiy V.V., Serga L.K. The Differentiation of Social and Economic Development of Territories Incentives or Inhibit the Growth of Russian Economy. In: V.I. Klistorina, O.V. Tarasova (eds) Economy of Siberia in the Context of Global Challenges of the XXI Century: Collection of Articles. Novosibirsk: Institute of Economics and Organization of Industrial Production RAS; 2018. P. 54–63. (In Russ.)

2. Barro R. Economic Growth in a Cross Section of Countries.Quarterly Journal of Economics. 1991;106(2):407–443. Available from: https://doi.org/10.2307/2937943.

3. Barro R., Sala-I-Martin X. Convergence. Journal of Political Economy. 1992;100(2):223-251. Available from: https//doi.org/10.1086/261816.

4. Sala-I-Martin X. The Classical Approach to Convergence Analysis. The Economic Journal. 1996;106(437):1019–1036. Available from: https://doi.org/10.2307/2235375.

5. Boyle G.E., McCarthy T.G. Simple Measures of Convergence in Per Capita GDP: A Note in Some Further International Evidence. Applied Economics Letters. 1999;6(6):343–347. Available from: https://doi.org/10.1080/135048599353041.

6. Shubat O.M. Regional Convergence of Fertility in Russia. Economy of Region. 2019;15(3):736–748. (In Russ.). Available from: https://doi.org/10.17059/2019-3-9.7.

7. Moran P.A.P. Notes on Continuous Stochastic Phenomena. Biometrika. 1950;37(1–2):17–23. Available from:https://doi.org/10.1093/biomet/37.1-2.17.

8. Fischer M.M. Spatial Analysis in Geography. In: N.J. Smelser, P.B. Baltes (eds). International Encyclopedia of the Social & Behavioral Sciences. Pergamon; 2001. P. 14752–14758. Available from: https://doi.org/10.1016/B0-08-043076-7/02489-X.

9. Shubat O., Ivanenko G., Shubat M. The Study of Spatial Autocorrelation of Fertility in Russia. In: T. Löster, T. Pavelka (eds). The 14th International Days of Statistics and Economics: Conf. Proc., 10–12 September 2020, Prague, Czech Republic. Prague: MELANDRIUM; 2020. P. 988–997. Available from: https://doi.org/10.18267/pr.2020.los.223.0.

10. Harris R., Moffat J., Kravtsova V. In Search of ‘W’. Spatial Economic Analysis. 2011;6(3):249–270. Available from: https://doi.org/10.1080/17421772.2011.586721.

11. Cleland J., Wilson C. Demand Theories of the Fertility Transition: An Iconoclastic View. Population Studies.1987;41(1):5–30. Available from: https://doi.org/10.1080/0032472031000142516.

12. Vitali A., Billari F.C. Changing Determinants of Low Fertility and Diffusion: A Spatial Analysis for Italy. Population, Space and Place. 2015;23(2). Available from: https://doi.org/10.1002/psp.1998.

13. Carioli A., Devolder D., Recano J. The Changing Geographies of Fertility in Spain (1981–2018). Journal of Regional Research. 2021;50:147–167. Available from:https://doi.org/10.38191/iirr-jorr.21.015.

14. Grigoriev A.A. Spatial Autocorrelation of Educational Attainment in the Russian Federation. Psychology. Journal of Higher School of Economics. 2018;15(1):164–173. (In Russ.) Available from: https://doi.org/10.17323/1813-8918-2018-1-164-173.

15. Inozemcev E.S., Kochetygova O.V. Spatial Panel Analysis of Fertility and Life Expectancy in Russia. Izvestiya of Saratov University. Ser. Economics. Management. Law. 2018;18(3):314–321. (In Russ.). Available from: https://doi.org/10.18500/1994-2540-2018-18-3-314-321.

16. Anselin L., Florax R. (eds) New Directions in Spatial Econometrics. Advances in Spatial Science. Springer-Verlag Berlin Heidelber; 1995. 420 p. Available from: https://doi.org/10.1007/978-3-642-79877-1.


Review

For citations:


Shubat O.M. Statistical Estimates of the Decline of the Russian Fertility: Regional Specifcs. Voprosy statistiki. 2021;28(5):39-48. (In Russ.) https://doi.org/10.34023/2313-6383-2021-28-5-39-48

Views: 715


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


ISSN 2313-6383 (Print)
ISSN 2658-5499 (Online)