School-to-Work Transition in the Youth Labor Market in Central and Eastern Europe: A Cluster Analysis Approach

Authors

  • Tomislav Korotaj Faculty of Economics & Business Zagreb
  • James Ming Chen Michigan State University, College of Law,
  • Nataša Kurnoga Faculty of Economics & Business Zagreb

DOI:

https://doi.org/10.2478/bsrj-2024-0020

Keywords:

hierarchical cluster analysis, complete-link method, time series, youth population, wage ratio, NEET, early departures from education, central and eastern Europe

Abstract

Background: This study analyzes education, training, and the youth labor market in central and eastern Europe. Objectives: This study aims to evaluate similarities and differences in youth labor markets among eleven central and eastern European countries from 2008 to 2021. It specifically examines three aspects: wage ratios, early departure from education or training, and the share of the population not in employment, education, or training. Methods/Approach: This study applies hierarchical clustering and multidimensional scaling to panel data. The complete-link method organizes countries into clusters. This study combines three-dimensional Cartesian projections and two-dimensional projections based on multidimensional scaling with dendrograms and heatmaps, to graphically illustrate the "school-to-work" transition across this region. Results: Clustering highlights the Visegrád countries, the Baltics, and the Balkans as zones with internally homogeneous yet externally heterogeneous challenges for the youth generation. As the outliers in each of these regions, Poland, Estonia, and Bulgaria support clustering solutions that deviate from conventional understandings of central and eastern Europe. Conclusions: Historical and geographical ties continue to define this region’s youth labor markets across political and economic dimensions. Clustering analysis identifies triumphs and struggles in policymaking in some of the poorest and most politically challenging member-states of the European Union.

Author Biographies

Tomislav Korotaj, Faculty of Economics & Business Zagreb

Tomislav Korotaj is a Teaching and Research Assistant at the Department of Statistics, Faculty of Economics and Business, University of Zagreb, Croatia. He holds a bachelor's degree in business economics and a master's degree in accounting and auditing from the University of Zagreb. He teaches the following courses: Statistics, Business Statistics, and Methods of Multivariate Analysis. He is pursuing a PhD in Economics, focusing on the youth labour market, wage policies, and income inequality. In addition to the above, his research interests include cluster analysis, panel data models, and school-to-work transition. The author can be contacted at tkorotaj@efzg.hr.

James Ming Chen, Michigan State University, College of Law,

James Ming Chen is Professor of Law and Justin Smith Morrill Chair in Law at Michigan State University, U.S.A. He holds a degree in law, magna cum laude, from Harvard University and a master's degree in data science from Northwestern University. He is a member of the American Law Institute and a senior fellow of the Administrative Conference of the United States. He is licensed to practice law in Virginia and the District of Columbia. His research interests include law (particularly administrative law, competition law, and economic regulation), machine learning, mathematical and behavioural finance, and computational social science. The author can be contacted at chenjame@law.msu.edu.

Nataša Kurnoga, Faculty of Economics & Business Zagreb

Nataša Kurnoga is a Full Professor (Tenured) at the Department of Statistics, Faculty of Economics and Business, University of Zagreb, Croatia. She teaches the following courses at different study levels: Statistics, Business Statistics, Quantitative Methods, and Methods of Multivariate Analysis. She has participated in various scientific research projects and published numerous papers in scientific journals, conference proceedings, and books. She is a reviewer for numerous international scientific journals. Her research interests include business and economics statistics, especially multivariate data analysis methods. The author can be contacted at nkurnoga@efzg.hr.

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Published

2024-10-03