Measuring the Efficiency of Public Employment Services in Russia: Which Regions Have Similarities?
DOI:
https://doi.org/10.17059/ekon.reg.2024-3-12Keywords:
public employment services, employees, unemployed people, job performance, regional classification, agglomerative hierarchical clustering procedure, Ward’s methodAbstract
Public Employment Services provide support for firms and individuals in finding new employment opportunities. They are important actors at the labour market, since well-functioning services reduce costs of search friction and increase matching efficiency. In this paper we adopt the regional classification scheme to identify similarities of regions and their PES on the basis of regional labour market-oriented characteristics. The purpose of the scientific search is the theoretical justification and empirical confirmation of Russian regions’ similarity in terms of employment level and the formulation of areas for increasing the efficiency of public employment services. The tasks were solved using expert analytical methods, analysis of statistical rows, clustering and cartography. The clustering is based on Ward’s hierarchical method, clusters are plotted on weighted standardised data. The official information from the Federal State Statistics Service of the Russian Federation (Rosstat) are analysed. We identified 7 clusters, in which PES have rather similar conditions. The heterogeneity of conditions is higher between clusters. PES within a cluster are valid for comparison and the adoption of new services and best practice examples. We show that the classification of the Russian Economic Zones does not necessarily cover similarities at local labour markets. The practical significance of the results is due to the possibility of using them to develop decisions for long – and short-term support for employment and the formation of an optimal labour market structure both at the state level and at the level of constituent entities of the Federation.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Матушкина Наталья
This work is licensed under a Creative Commons Attribution 4.0 International License.