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The multivariate techniques in evaluation of unemployment analysis of Polish regions

Author

Listed:
  • Anna Tatarczak

    (Maria Curie Sk³odowska University in Lublin, Poland)

  • Oleksandra Boichuk

    (Maria Curie Sk³odowska University in Lublin, Poland)

Abstract

Research background: The labour market situation is considered to be the most widely discussed part of economic development. However, it should be noted that the unemployment situation of young people (aged 15–24 years) in Poland in general terms seems to be problematic. Overall, the unemployment rate among young people in Poland is significantly higher than the overall unemployment rate in the EU. Moreover, the situation varies greatly across the regions. Purpose of the article: Using multivariate techniques as a theoretical framework, the main goal of the paper is to identify groups of Polish regions that share similar patterns regarding unemployment among young people. To reach this goal, first a set of labour market indicators were selected. Next, the authors compared the labour market situation of young people between the Polish regions in 2005 and in 2014. Finally, the conclusions regarding the conducted analysis are explored. Methods: The initial calculation is based on the concept of the taxonomic measure developed by Hellwig. The final method used to create clusters of objects (across 16 voivodeships of Poland) is cluster analysis. A segmentation of the voivodeships is observed for the years 2005 and 2014, based on selected indicators to determine the labour market situation. The data was gathered from the databases of the Central Statistical Office of Poland and Eurostat. Findings & Value added: Through the exploration of the advantages of multivariate methods, the nature of youth unemployment is revealed in more detail. Indeed, dendrogram analysis divided the voivodeships into five groups, which are characterized by similar features associated with the labour market. It was found that the groups which emerged in 2005 have a different composition of regions than in 2014; this difference seems to be connected with the economic crisis.

Suggested Citation

  • Anna Tatarczak & Oleksandra Boichuk, 2018. "The multivariate techniques in evaluation of unemployment analysis of Polish regions," Oeconomia Copernicana, Institute of Economic Research, vol. 9(3), pages 361-380, September.
    • Handle: RePEc:pes:ieroec:v:9:y:2018:i:3:p:361-380
    DOI: 10.24136/oc.2018.018
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Ewa Rollnik-Sadowska & Marta Jarocka & Edyta Dabrowska, 2020. "Diversity of Regional Labour Markets in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 33-51.
    3. repec:ers:journl:v:xxiv:y:2021:i:2:p:108-121 is not listed on IDEAS
    4. Katarzyna Cheba & Iwona Bąk, 2021. "Environmental Production Efficiency in the European Union Countries as a Tool for the Implementation of Goal 7 of the 2030 Agenda," Energies, MDPI, vol. 14(15), pages 1-19, July.
    5. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    6. Beata Bieszk-Stolorz & Krzysztof Dmytrów, 2021. "Impact of Changes to Procedures on the Evaluation of the Effectiveness of Forms of Professional Activation in Poland," Economies, MDPI, vol. 9(2), pages 1-18, June.
    7. Ludmila-Daniela MANEA & Iulian Adrian SORCARU, 2021. "Cluster Analysis on the Unemployment Rate during Lockdown Period," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 29-36.
    8. Małgorzata Cygańska & Magdalena Kludacz-Alessandri, 2021. "Determinants of Electrical and Thermal Energy Consumption in Hospitals According to Climate Zones in Poland," Energies, MDPI, vol. 14(22), pages 1-24, November.
    9. Kądziołka Kinga, 2021. "A Proposal of Data – Driven Method for Determining the Weights of Composite Indicators," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(1), pages 49-62, March.

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    More about this item

    Keywords

    labour market; unemployment; young people; cluster analysis;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets

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