Cluster Appoach to Analyzing Registered Unemployment in the Region
https://doi.org/10.21686/2413-2829-2023-1-89-93
Abstract
The topic of the research is acute due to the fact that for a couple of years labour market of each region and Russia as a whole has been suffering turbulence because of changes in economic situation. It always responds sharply to all changes taking place in the field of economy. The article provides results of differentiation of cities and city districts of the Orenburg region by registered unemployment rate in 2017 and 2020. The choice of time slots for the research is stipulated by changes in regional labour market connected with the pass-over to digitalization, as well as impact of crisis events in economy. Estimation of varying parameters allows us to see heterogeneity in cities and city districts of Orenburzhiya. As a result of cluster analysis groups of administrative territories of the Orenburg region were found that are characterized by high, average and low level of registered unemployment indicators. Slight changes in cluster structure were identified. Results of cluster-groups comparison can be used as a foundation for devising regional employment policy aiming at smoothing differences between cities and city districts in the Orenburg region by key indicators of this sphere of economy development.
About the Author
L. V. Portnova
Orenburg branch of the Plekhanov Russian University of Economics
Russian Federation
Russian Federation
Lidiya V. Portnova PhD, Assistant Professor, Assistant Professor of the Department for Finance and Management
50/51–53 Pushkin/ Leninskaya Str., Orenburg, 460000
References
1. Bashina O. E., Ivanova N. Yu. Mnogomernye statisticheskie gruppirovki [Multivariate Statistical Groupings]. Moscow, Izd-vo MGUK, 2001. (In Russ.).
2. Zolotova L. V., Portnova L. V. Tendentsii razvitiya rynka truda Orenburgskoy oblasti [Trends in the Development of the Labor Market in the Orenburg Region]. Sfera uslug: innovatsii i kachestvo [Services Sector: Innovation and Quality], 2021, No. 54, pp. 37–46. (In Russ.).
3. Lokhtina T. N., Metelitsa V. I. Rynok truda i sotsialno-ekonomicheskie problemy naseleniya Rossii [The Labor Market and Socio-Economic Problems of the Population of Russia]. Vestnik evraziyskoy nauki [The Eurasian Scientific Journal], 2019, Vol. 11, No. 1, pp. 1–11. (In Russ.).
4. Portnova L. V. Primenenie metoda klasternogo analiza v otsenke i prognozirovanii urovnya bezrabotitsy v regione [Application of the Cluster Analysis Method in Assessing and Forecasting the Level of Unemployment in the Region]. Vestnik Orenburgskogo gosudarstvennogo universiteta [Bulletin of the Orenburg State University], 2012, No. 4 (140), pp. 158–163. (In Russ.).
5. Charykova O. G., Markova E. S. Regionalnaya klasterizatsiya v tsifrovoy ekonomike [Regional Clustering in the Digital Economy]. Ekonomika regiona [Economy of Regions], 2019, Vol. 15, Issue 2, pp. 409–419. (In Russ.).
6. Blus P. I., Plotnikov R. V. Spatial Clustering for Reducing Intraregional Unevenness. Journal of New Economy, 2022, Vol. 23, No. 1, pp. 88–108.
Review
For citations:
Portnova L.V. Cluster Appoach to Analyzing Registered Unemployment in the Region. Vestnik of the Plekhanov Russian University of Economics. 2023;20(1):89-93. (In Russ.) https://doi.org/10.21686/2413-2829-2023-1-89-93
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