Econometric Analysis of the Labor Market in the North Caucasus Region

Capa

Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Somente assinantes

Resumo

The purpose of this study is an econometric analysis of the labor market in the North Caucasus region in the Russian Federation. The article examines the main indicators characterizing the labor market, such as the average monthly nominal accrued wages of workers across the entire spectrum of economic organizations as a whole by business entities, the real average monthly accrued wages of workers, the share of the number of workers employed in work with harmful and/or dangerous conditions labor in organizations, Labor productivity index, Level of innovative activity of organizations, Degree of depreciation of fixed assets in the constituent entities of the Russian Federation of the Russian Federation across the entire spectrum of organizations, Consumer price indices for all goods and services by subject at the end of the period, Number of graduates of higher educational institutions that have a direct impact on the level of unemployment and labor force in the region. The relevance of the chosen topic is due to the study of the role of these indicators in the analysis of the region’s activities in an economic and social key. The structure of the article provides for a consistent presentation of the results of the analysis of each of the models, an assessment of their adequacy and explanatory power, as well as an interpretation of the obtained modeling results. Particular attention is paid to how changes in economic indicators and policies can affect the labor market and unemployment rates in the region. In conclusion, conclusions based on the results of the study are formulated and recommendations are proposed to stimulate economic growth and reduce unemployment in the North Caucasus Federal District.

Sobre autores

Ruslan Dzgoev

ATB Bank

Email: rusdzgoev@yandex.ru

специалист по работе с крупными иностранными клиентами

Rússia, Moscow

Lev Krasulin

Financial University under the Government of the Russian Federation; JSC «Norsi-trans»

Email: l.a.krasulin@gmail.com
Código SPIN: 7137-8206

Faculty of Information Technologies and Big Data Analysis, Technical support specialist

Rússia, Moscow; Moscow

Ilona Tregub

Financial University under the Government of the Russian Federation

Autor responsável pela correspondência
Email: itregub@fa.ru
ORCID ID: 0000-0001-7329-8344
Código SPIN: 2192-9453
Scopus Author ID: 57189715735
Researcher ID: A-5855-2017

Dr. Sci. (Econ.), Professor

Rússia, Moscow

Bibliografia

  1. URL: https://cyberleninka.ru/article/n/ekonomicheskiy-rost-severo-kavkazskogo-makroregiona-v-usloviyah-globalizatsii-indeks-usloviy-vneshney-torgovli-ekonometricheskaya (date of application: 31.03.2024).
  2. URL: https://cyberleninka.ru/article/n/srednesrochnyy-prognoz-ekonomicheskogo-rosta-severo-kavkazskogo-makroregiona-na-osnove-ols-metoda-i-panelnyh-dannyh (date of application: 31.03.2024).
  3. URL: https://cyberleninka.ru/article/n/innovatsionnoe-razvitie-promyshlennosti-regiona-i-ego-rol-v-formirovanii-konkurentosposobnyh-proizvodstv (date of application: 31.03.2024).
  4. URL: https://cyberleninka.ru/article/n/import-substitution-of-agricultural-products-as-a-factor-of-sustainable-development-the-north-caucasus-federal-district (date of application: 31.03.2024).
  5. Becker, G. S. (1964). Human capital: a theoretical and empirical analysis, with a special focus on education. University of Chicago Press.
  6. Blundell R. and Makurdi T. (1999). Labor supply: an overview of analytical materials. In O. Aschenfelter and D. Card (eds.), Handbook of Labor Economics (Volume 3A, 1559–1695).
  7. Gichiev N.S. Economic growth of the North Caucasian macroregion in the context of globalization: index of foreign trade conditions, econometric growth model // RPE. 2018. No.12 (98). URL: https://cyberleninka.ru/article/n/ekonomicheskiy-rost-severo-kavkazskogo-makroregiona-v-usloviyah-globalizatsii-indeks-usloviy-vneshney-torgovli-ekonometricheskaya (date of application: 03/31/2024).
  8. Gichev N.S. Medium-term forecast of economic development of the North Caucasian macrogroup based on the method and results of the analysis // RPPZ. 2021. No. 10 (132). URL: https://cyberleninka.ru/article/n/srednesrochnyy-prognoz-ekonomicheskogo-rosta-severo-kavkazskogo-makroregiona-na-osnove-ols-metoda-i-panelnyh-dannyh (date of application: 03/31/2024).
  9. Idziev G. I., Tsapieva O. K., Esetova A.M. Innovative development of industry in the region and its role in the formation of competitive industries // PSE. 2012. No.2. URL: https://cyberleninka.ru/article/n/innovatsionnoe-razvitie-promyshlennosti-regiona-i-ego-rol-v-formirovanii-konkurentosposobnyh-proizvodstv (date of reference: 03/31/2024).
  10. Card, D. (1999). Directly-government influence on the results. In O. Aschenfelter and D. Card (eds.), «Handbook of Equestrian Labor» (Volume 3, 1801–1863). Elzevir.
  11. Mecherakova Zh.V., Skorkina N.V., Khalupovsky I.M. Import substitution of agricultural products as a factor of sustainable development of the North Caucasus Federal District // Economics and Business: theory and practice. 2018. No.7. URL: https://cyberleninka.ru/article/n/import-substitution-of-agricultural-products-as-a-factor-of-sustainable-development-the-north-caucasus-federal-district (date of application: 03/31/2024).
  12. Pissarides, K. A. Theory of equilibrium unemployment. Publishing House of the Massachusetts Institute of Technology. 2000.
  13. Myaktinova T.A., Tregub I.V. Is it worth studying longer? Econometric assessment of the impact of education // Accounting and statistics. 2022. No. 4 (68). pp. 103–112.
  14. Tregub I.V. Development of economic tools for stabilizing the economy of the region: the experience of the Yaroslavl region // Management and politics. 2022. Vol. 1. No. 3. pp. 27–34.

Arquivos suplementares

Arquivos suplementares
Ação
1. JATS XML
2. Fig. 1. Confidence interval to check the adequacy of the model 3.

Baixar (50KB)
3. Fig. 2. Confidence interval to check the adequacy of the model 4.

Baixar (50KB)
4. Fig. 3. Confidence interval for checking the adequacy of model 5.

Baixar (43KB)
5. Fig. 4. Confidence interval for checking the adequacy of the model 6.

Baixar (46KB)


Este site utiliza cookies

Ao continuar usando nosso site, você concorda com o procedimento de cookies que mantêm o site funcionando normalmente.

Informação sobre cookies