Econometric analysis of unemployment and its impact on the economic growth of the Ural Federal District

Cover Page

Cite item

Full Text

Abstract

Introduction. Labour market is one of the key areas ensuring the growth of the national economy. However, unique geographical and social economic features of various federal districts of the Russian Federation generate regions’ unequal contribution to the labour market development. This demands analysis of labour market processes and identification of key factors for labour market growth. The purpose of this article is to analyze unemployment in the Ural Federal District of the Russian Federation and reveal the key factors that have a significant impact on employment dynamics. Materials and Methods. The paper refers to the official information database of the Federal State Statistics Service of the Russian Federation. The authors developed a set of econometric models determined by correlation and regression analysis methods. Results. The study shows that the regional unemployment rate is defined by various key indicators such as wages, effective demand, and inflation. Two hypotheses were worded to support the dominant factors for the GRP growth in the Ural Federal District. To justify these hypotheses, the authors referred to a set of six relevant econometric models which give distinctive results and define the degree the analyzed indicators impact GRP and economic growth of some regions in the Ural Federal District. Conclusions. Higher wages, curbing inflation and stimulated consumer demand by higher actual incomes of population are the most efficient measures to reduce unemployment, and stimulate economic growth of the Ural Federal District. These findings should be taken into account in developing social economic projects and programmes for the Ural Federal District.

About the authors

Ilona V. Tregub

Financial University under the Government of the Russian Federation

Author for correspondence.
Email: itregub@fa.ru
Scopus Author ID: 57189715735
ResearcherId: A-5855-2017

Doctor of Science (Economics), Professor, Professor at the Department of Business Informatics

Russian Federation, Moscow

Lev A. Krasulin

Norsi-trans OAO

Email: l.a.krasulin@gmail.com
Scopus Author ID: 58742968000

technical support specialist

Russian Federation, Moscow

References

  1. Borjas G. Labor economics. New York, McGraw-Hill, 1996. 469 p.
  2. Sapsford D., Tzannatos Z. The Economics of the Labour Market. London, Macmillan, 1993. 463 p.
  3. Fallon P., Verry D. The Economics of Labour Markets. London, Philip Allan, 1988. 288 p.
  4. Hamermesh D. S. Labor Demand. Princeton, Princeton University Press, 1993. 448 p.
  5. Blundell R., Macurdy T. Chapter 27 – Labor supply: A review of alternative approaches. Handbook of Labor Economics. Ed. by O. C. Ashenfelter, D. Card, 1999, vol. 3, part A, pp. 1559–1695. doi: 10.1016/S1573-4463(99)03008-4
  6. Mikhalkina E. V., Skachkova L. S. Overview of the Russian methods of competences labour demand and supply forecasting. Terra Economicus, 2014, vol. 12, no. 4, pp. 59–67. (In Russ.). EDN TJHHSJ
  7. Sibirskaya E. V., Mikheykina L. A. The assessment of underutilization of labour force in the Russian Federation regions. Federalizm, 2019, no. 1 (93), pp. 24–37. (In Russ.). doi: 10.21686/2073-1051-2019-1-24-37. EDN DNYYEK
  8. Kulentsan А. L., Marchuk N. А. Regional development: Analysis and forecasting of the number of unemployed in the Southern Federal District. Vestnik of the Mari State University. Chapter “Agriculture. Economics”, 2021, vol. 7, no. 1 (25), pp. 70–80. (In Russ.). doi: 10.30914/2411-9687-2021-7-1-70-79. EDN NWZGUO
  9. Aivazian S. А., Bereznyatsky А. N., Brodsky B. Е. Modeling Russian social indicators. Applied Econometrics, 2018, no. 3 (51), pp. 5–32. (In Russ.). EDN UZBFHY
  10. Becker G. S. Human capital: A theoretical and empirical analysis with special reference to education. University of Chicago Press, 1964. 412 p.
  11. Card D. Chapter 30 – The causal effect of education on earnings. Handbook of Labor Economics. Ed. by O. C. Ashenfelter, D. Card, vol. 3, part A. North Holland, 1999, pp. 1801–1863. doi: 10.1016/S1573-4463(99)03011-4
  12. Stroev V. V. Assessment of investments in education impact on the Russian regional economic stability. Vestnik universiteta, 2024, no. 2, pp. 133–141. (In Russ.). doi: 10.26425/1816-4277-2024-2-133-141. EDN ZJKLAP
  13. Kulentsan А. L., Matchuk N. А. Analysis of the dynamics of the level of unemployed population aged 15-72 years. News of higher educational institutions. The series “Economics, Finance and production management”, 2019, no. 4 (42), pp. 77–82. (In Russ.). EDN MYNNZH
  14. Demidova О. А. Spatial-autoregressive model for the two groups (eastern and western parts of Russia). Applied Econometrics, 2014, no. 2 (34), pp. 19–35. (In Russ.). EDN SFODVD
  15. Pakhomov А. V., Pakhomova Е. А., Rozhkova О. V. Econometric modeling of employment on the basis of the industrial distinctions. National Interests: Priorities and Security, 2017, vol. 13, iss. 11 (356), pp. 2018–2034. (In Russ.). doi: 10.24891/ni.13.11.2018. EDN ZUCRYV
  16. Topilin А. V., Vorobyova О. D. Dynamics and regional features of labour market recovery during COVID-19. Ekonomika regiona = Economy of Region, 2023, vol. 19, no. 1, pp. 85–98. (In Russ.). doi: 10.17059/ekon.reg.2023-1-7. EDN KPKUFE
  17. Podvoisky G. L. The world labour market: The consequences of global economic crisis. Finance: Theory and Practice, 2015, no. 4 (88), pp. 132–138. (In Russ.). doi: 10.26794/2587-5671-2015-0-4-132-138. EDN UHJRRJ
  18. Tikhonova N. Е., Karavai А. V. The impact of the 2014–2016 economic crisis on the employment of Russian. Monitoring of Public Opinion: Economic and Social Changes, 2017, no. 2 (138), pp. 1–17. (In Russ.). doi: 10.14515/monitoring.2017.2.01. EDN ZMQADN
  19. Govorova N. V. European labour market in pandemic reality. Sovremennaya Evropa = Contemporary Europe, 2020, no. 7 (100), pp. 67–78. (In Russ.). doi: 10.15211/soveurope72020128139. EDN TLHAGS
  20. Vakulenko Е. S. Analysis of the relationship between regional labour markets in Russia using Okun’s model. Applied Econometrics, 2015, no. 4 (40), pp. 28–48. (In Russ.). EDN VGSVVH
  21. Vakulenko Е. S., Gurvich Е. T. The relationship of GDP, unemployment rate and employment: In-depth analysis of Okun’s law for Russia. Voprosy ekonomiki, 2015, no. 3, pp. 5–27. (In Russ.). doi: 10.32609/0042-8736-2015-3-5-27. EDN TKIMTL
  22. Akhundova O. V., Korovkin A. G., Korolev I. B. Vzaimosvyaz' dinamiki VVP i bezrabotitsy: teoreticheskii i prakticheskii analiz. Nauchnye trudy: Institut narodnokhozyaistvennogo prognozirovaniya RAN, 2005, vol. 3, pp. 471–495. (In Russ.). EDN KWODOL
  23. Tregub I. V., Tregub A. V. Metody analiza i planirovaniya ekonomicheskoi dinamiki. Moscow, 2024. 186 p. (In Russ.).
  24. Tregub I. V. Econometrics: Models of Real Systems. Moscow, 2016. 164 p.

Supplementary files

Supplementary Files
Action
1. JATS XML

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).