Cluster analysis of effectiveness of labour market policy in the European Union

Main Article Content

Ewa Rollnik-Sadowska
Edyta Dąbrowska

Abstract

Research background: In the era of demographic changes and the need for rationalization of public expenditure, the European Union social policy promotes the activation approach. In addition, a growing importance of increasing the effectiveness and efficiency of public entities can be noticed. These phenomena are visible in the implementation of the labour market policy. However, the EU countries represent a different approach to spending public funds on issues related to the implementation of  labour market policy.


Purpose of the article: The authors are presenting the main theoretical assumptions concerning effectiveness and efficiency of labour market policy. Moreover, in the paper the EU countries are classified in clusters according to their level of expenditure on different categories of LMP. A comparison of the situation over ten years — in 2004 and 2014 — has also been conducted. In 2004, ten new members entered the EU, and the year 2014 presents the most current data in the analyzed area.


Methods: As a research method cluster analysis was applied. Cross-country labour market situation throughout the EU is presented by the analysis of the Eurostat data. The countries are grouped in clusters following Ward's and k-means methods.


Findings & Value added: There is a need to work out a complex evaluation of labour market policies in the EU to provide comparative analysis of the EU countries (or groups of countries). It would allow to determine the level of development of the country in terms of the efficiency of labour market policies. The EU countries with the best labour market indicators represent diverse levels of LMP expenditure.

Article Details

How to Cite
Rollnik-Sadowska, E., & Dąbrowska, E. (2018). Cluster analysis of effectiveness of labour market policy in the European Union. Oeconomia Copernicana, 9(1), 143-158. https://doi.org/10.24136/oc.2018.008
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