Convergence and determinants of young people not in employment, education or training: An European regional analysis

• Published in: Economic modelling 2022-05, Vol.110, p.105808, Article 105808
• Main Authors: Maynou, Laia, Ordóñez, Javier, Silva, José Ignacio
• Format: Article
• Language: English
• Subjects: Convergence; European Union; NEET rates; Youth unemployment
• ISSN: 0264-9993; 1873-6122
• DOI: 10.1016/j.econmod.2022.105808

In this paper, we study the convergence in the rates of young people Not in Employment, Education or Training (NEET) across the 274 European regions from 2000 to 2019. First, we apply the club convergence methodology and identify the presence of four important clusters with different trends in NEET rates. The estimated clusters consist of sub-national regions in quite distinct parts of Europe. Then, a spatio-temporal econometric model is used to confirm the presence of a reduction in the disparities (β–convergence) of these rates across the European regions. We identify the main drivers in each cluster and calculate the long-run NEET rates. The unemployment rate and the percentage of early leavers from education and training are the main drivers of NEET rates in all clusters. •We study the rate of young people Not in Employment, Education or Training (NEET).•We perform a convergence analysis across 274 European regions from 2000 to 2019.•Regional convergence analysis reveals the existence of four clusters in Europe.•We identify the main drivers of the NEET rates in each cluster.•The main drivers are the rates of unemployment and early leavers from education.