Regional Economics: Theory and Practice
 

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Modeling of the relationship between gross regional product, labor force, and employment: The Lipetsk Oblast case study

Vol. 18, Iss. 5, MAY 2020

PDF  Article PDF Version

Received: 16 April 2020

Received in revised form: 20 April 2020

Accepted: 24 April 2020

Available online: 15 May 2020

Subject Heading: SUSTAINABLE DEVELOPMENT OF REGIONS

JEL Classification: С3, С51, J21, R15

Pages: 870–890

https://doi.org/10.24891/re.18.5.870

Kozlova E.I. Lipetsk State Technical University (LSTU), Lipetsk, Russian Federation
kozlova.e.i@kzlvs.com

https://orcid.org/0000-0001-5116-6543

Novak M.A. Lipetsk State Technical University (LSTU), Lipetsk, Russian Federation
ferz235@mail.ru

https://orcid.org/0000-0003-4613-8948

Karlova M.Yu. Lipetsk State Pedagogical P. Semenov-Tyan-Shansky University (LSPU), Lipetsk, Russian Federation
m.karlova79@gmail.com

https://orcid.org/0000-0002-0354-9897

Subject. This article discusses the prospects for growth of Russia and its regions' economies.
Objectives. The article aims to identify causal relationships between gross regional product as the main economic growth indicator of a particular region and labor costs.
Methods. For the study, we used a correlation and regression analysis.
Results. The article presents trend forecast models and linear equations of multiple regression. It finds that all capital factors have a stronger impact on public product of the Lipetsk Oblast than the labor ones. Regarding labor factors, only the average per capita income of the population has a direct impact on the formation of the Lipetsk Oblast's GRP.
Conclusions. The identified relationships between the Lipetsk Oblast's GRP and exogenous variables help define the hierarchy of linear models that provide extensive analytical information on the formation of the Lipetsk Oblast's GRP. In linear models, there is no significant relationship between the changes in the working population of the Oblast and the regional product. To adequately describe the dynamics of the Lipetsk Oblast's GRP, it makes sense to apply a set of linear models of multiple regression.

Keywords: population, source, labor, gross regional product, trend analysis, linear model, multivariate regression

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