Cluster analysis of the Russian labour market sectors

Author:

Nikolenko Sofia O.ORCID,Moiseev Nikita A.ORCID,Smirnova Elena I.ORCID

Abstract

Subject. In the face of significant change, with companies suspending or completely terminating their operations in the Russian Federation, there are supply and logistical challenges, and planning issues arise. It is still necessary to plan financial support for industries that are most likely to be affected by these changes. The changes affect not only the output, but also the employment and wages in the sectors. A comprehensive analysis of the developments is required to make the most effective decisions. In this study, we considered the relationship between sectors of the economy in terms of average wages, which is an important factor reflecting the development vector in the sector.Objectives. The purpose of the study was to analyse the specific features of the Russian labour market, based on average wages by sector and to identify similar sectors.Methodology. In the study, we used the classification of economic sectors based on the methodology developed by the Federal State Statistics Service. Throughout the study, the terms “economic sector” and “industry” are used as synonyms. The following scientific methods were used: measurement, description, and modelling. The research is based on reviewing topical scientific literature, both Russian and foreign.Results. We grouped economic sectors based on characteristics such as chained rate of increase, average rate of increase, minimum and maximum value, standard deviation, and the range of the studied time series. The resulting clusters reflect the specific features of the industries included, which supports the results of the analysis.Conclusions. The analysis revealed three clusters with industries sharing a common development dynamic. The first cluster includes industries that are part of the primary sector of the economy. The second cluster includes state-supported industries, while the third cluster represents industries that are part of the manufacturing sector.

Funder

Russian Science Foundation

Publisher

Voronezh State University

Reference22 articles.

1. Alekseeva, E. S. , Shvetsova, V. A. (2016). Genetic map of population health. Financing and innovation in healthcare. Symbol of science, 11(4), 2. (In Russian.).

2. Garnov, A. P. , Garnova, V. Yu. (2016). Cluster economy: ways of raising the efficiency of state industrial policy. Vestnik Rossiyskogo ekonomicheskogo universiteta imeni G. V. Plekhanova, 6. (In Russian.).

3. Ershova, V. Yu. (2012). The role of clusters in economic development. Nauchnye issledovaniia v obrazovanii, 7. (In Russian.).

4. Iskandaryan, M. V. , Fadeeva, E. A. (2021) Unemployment in the context of the pandemic. Journal of Economy and Business, 9(1), 4-5. (In Russian.). https://doi.org/10.24412/2411-0450-2021-9-1-101-104

5. Kaukin, A. S. , Miller, E. M. (2022). Industrial Production Dynamics in Q2 2022. Russian Economic Development, 9, 4-5. (In Russian.).

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