Assessment of spatial heterogeneity of employment in Russian regions
https://doi.org/10.26425/1816-4277-2023-10-105-114
Abstract
The article studies the problem of spatial heterogeneity of employment in Russian regions. Despite the rather high indicators for Russia and their positive dynamics, the situation in the regions is strikingly different. Heterogeneity of employment distribution between regions can be intensified as a result of the influence of some territories on others. The purpose of the study is to assess spatial heterogeneity and spatial autocorrelation effects between Russian regions in terms of employment. As the main research method, the paper applies Moran’s methodology to calculate local and global spatial autocorrelation indices and Anselin’s methodology to form a spatial matrix. The results of the study demonstrate that among Russian regions there is a high potential for clustering by the number of employed people. At the same time, a group of western regions is clearly distinguished, which have greater territorial cohesion characterized by pronounced spatial mutual influence. The results of the study can be used in formulating strategies for Russian regions development, in particular, the Far Eastern regions, as well as in determining priority development goals.
Keywords
Supporting agencies: The article was prepared within the framework of the state assignment of the Institute of Economics of the Ural Branch of the Russian Academy of Sciences for 2021–2023 No. 03272021-0019 “Modeling of territorial spatial development from the position of ensuring economic security”
About the Authors
R. I. Vasilyeva
Institute of Economics of the Ural Branch of the Russian Academy of Sciences
Russian Federation
Russian Federation
Rogneda I. Vasilyeva - Junior Researcher.
Ekaterinburg
D. M. Ampenova
Ural Federal University named after the First President of Russia B.N. Yeltsin
Russian Federation
Russian Federation
Darya M. Ampenova - Graduate Student.
Ekaterinburg
References
1. Demyanova A.V., Ryzhikova Z.A. Employment and unemployment: what do alternative measures tell? www.econorus.org/con2020/program.phtml?vid=report&eid=3495 (assessed 26.07.2023). (In Russian).
2. Giltman M.A. Individual Determinants of Employment in Russia: Regional and Industrial Peculiarities. Tomsk State University Journal of Economics. 2018;43:88–106. https://doi.org/10.17223/19988648/43/6 (In Russian).
3. Zubarevich N.V., Safronov S.G. Regional inequality in large post-Soviet countries. Regional Research of Russia. 2011;1(1):15–26. https://doi.org/10.1134/S2079970511010138
4. Ministry of Economic Development of the Russian Federation. Spatial development strategy of the Russian Federation for the period up to 2025. https://www.economy.gov.ru/material/directions/regionalnoe_razvitie/strategicheskoe_planirovanie_prostranstvennogo_razvitiya/strategiya_prostranstvennogo_razvitiya_rossiyskoy_federacii_na_period_do_2025_goda/ (assessed 26.07.2023). (In Russian).
5. Indutenko A.N., Vladika M.V., Gasij S.K. Regional budget and its problems scarce. The Bryansk State University Herald. 2014;4:116–119. (In Russian).
6. Unified interdepartmental information and statistical system. Level of population employment. https://www.fedstat.ru/indicator/34027 (accessed 26.07.2023). (In Russian).
7. Furková A., Chocholatá M. Spatial econometric approach to the EU regional employment process. Central European Journal of Operations Research. 2021;29:1037–1056. https://doi.org/10.1007/s10100-020-00714-5
8. Kivi L. Spatial Interactions of Regional Labor Markets in Europe. SSRN Electronic Journal. 2019;3330778. https://doi. org/10.2139/ssrn.3330778
9. Kivi L., Paas T. Spatial interactions of employment in European labor markets. Eastern Journal of European Studies. 2021;12:196–211. https://doi.org/10.47743/ejes-2021-SI09
10. Demidova O.A., Daddi P., Medvedeva E.V., Signorelli M. Modeling the Employment Rate in Russia: A Spatial-Econometric Approach. Economy of Region. 2019;14(4):1383–1398. https://doi.org/10.17059/2018-4-25
11. Naumov I.V., Barybina A.Z. The Spatial Autoregression Model of Innovative Development of Russian Regions. Tomsk State University Journal of Economics. 2020;52:215–232. https://doi.org/10.17223/19988648/52/13 (In Russian).
12. Naumov I.V, Dubrovskaya J.V, Kozonogova E.V. Digitalisation of Industrial Production in the Russian Regions: Spatial Relationships. Economy of Region. 2020;3(16):896–910. https://doi.org/10.17059/ekon.reg.2020-3-17
13. Chen Y. New Approaches for Calculating Moran’s Index of Spatial Autocorrelation. PLoS ONE. 2013;7(8):e68336. https://doi.org/10.1371/journal.pone.0068336
14. Metelli L., Natoli F. The International Transmission of US Tax Shocks: A Proxy-SVAR Approach. IMF Economic Review. 2021;2(69):325–356. https://doi.org/10.1057/s41308-021-00136-6
15. russian Federation. The Decree of the President Federation dated 21.07.2020 No. 474 “On national development goals of Russian Federation for the period up to 2030”. http://www.consultant.ru/document/cons_doc_LAW_357927/ (assessed 26.07.2023). (In Russian).
16. russian Federation. Order of the Russian Government dated 13.02.2019 No. 207-R “On acceptance of Spatial Development Strategy of the Russian Federation for the period up to 2025”. http://government.ru/docs/35733/ (assessed 26.07.2023). (In Russian).
17. Ministry of Labor and Social Protection of the Russian Federation. The Forecast of labor resources balance for 2022–2024. https://mintrud.gov.ru/docs/mintrud/migration/1324?ysclid=lgj4hjzl5p398366467 (assessed 26.07.2023).
18. Soloveva T.S. Features of the Russian population employment in the context of spatial development of the territories. Ekonomika truda. 2022;7(9):1147–1166. https://doi.org/10.18334/et.9.7.114801 (In Russian).
19. rusanovskiy V.A., Markov V.A. Employment and Labor Productivity in Macroregions of Russia: Spatial Interdependence. Studies on Russian Economic Development. 2018;2(29):135–143. https://doi.org/10.1134/S1075700718020120
20. Federal State Statistics Service. Regions of Russia. Socio-economic indicators. https://gks.ru/bgd/regl/b21_14p/Main.htm (assessed 26.07.2023). (In Russian).
21. Naumov I.V. Certificate of state registration of the computer program No. 2022680630. Spatial autocorrelation analysis of indicators of regional socio-economic development according to the P. Moran’s method. https://sciact.uiec.ru/ru/public/patent/33 (accessed 26.07.2023). (In Russian).
22. Anselin L. Local Indicators of Spatial Association-LISA. Geographical Analysis. 1995;2(27):93–115.
23. Naumov I.V., Otmakhova Yu.S., Krasnykh S.S. Methodological approach to modeling and forecasting the impact of the spatial heterogeneity of the COVID-19 spread on the economic development of Russian regions. Computer Research and Modeling. 2021;3(13):629–648. https://doi.org/10.20537/2076-7633-2021-13-3-629-648 (In Russian).
Review
For citations:
Vasilyeva R.I., Ampenova D.M. Assessment of spatial heterogeneity of employment in Russian regions. Vestnik Universiteta. 2023;(10):105-114. (In Russ.) https://doi.org/10.26425/1816-4277-2023-10-105-114
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