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

Maynou, Laia; Ordóñez, Javier; Silva, José I.

doi:10.1016/j.econmod.2022.105808

Cited by 14 publications

(10 citation statements)

References 45 publications

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“…Dvouletý et al (2020) and Marelli and Vakulenko (2016) showed a higher unemployment rate for younger individuals, Dvouletý et al (2020), Lallukka et al (2019), Lim and Lee (2019), Petrakis (2021) and Schioppa and Lupi (2002) for females and Dvouletý et al (2020) for people from ethnic minority groups. Similar results were also achieved by Dagume and Gyekye (2016), Maynou et al (2022) and Wesseling (2021). They have shown that among all characteristics of an individual (e.g.…”

Section: Literature Reviewsupporting

confidence: 85%

“…The quality of education measured in this way directly impacted the lower unemployment rate immediately after graduation. The positive impact of education in the short term was also observed by Dvouletý et al (2020), Maynou et al (2022) and Tomić (2018). They indicate that education of good quality and training programs contribute to school-to-work transition.…”

Section: Discussionmentioning

confidence: 70%

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Determinants of youth unemployment rate: case of Slovakia

Papík

Mihaľová

Papíková

2022

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Research background: The employment rate of young individuals in the labour market has considerably decreased in developed countries recently. Due to lower labour capital, skills, and generic and job-specific work experience, youth consider finding suitable job challenging. If they fail to succeed in the labour market soon after graduation, it leads to long-term unemployment, unstable and low-quality jobs, and even social exclusion. Purpose of the article: This paper aims to analyse the unemployment rate of high school-graduated students and the factors impacting this unemployment rate, such as GDP per capita, total unemployment rate, apartment price per square meter and results from state exams. Identifying the determinants affecting youth unemployment is crucial for theoretical knowledge and for policymakers to ensure youth inclusion in the economic mainstream. As a result, society can reduce social and economic costs and avoid structural problems in the future. Methods: Data about 464 Slovak high schools from National Institute for Certified Educational. Data include the graduate unemployment rate for each high school in Slovakia. Furthermore, two logistic regression models have been developed to investigate the impact of selected factors on high school graduates? unemployment rate immediately after graduation and nine months after graduation. Findings & value added: This paper indicates the existence of statistical dependency between unemployment of high school graduates and overall unemployment rate in the region, GDP per capita in the region, quality of high school education and cost of living in the region immediately after graduation. Analysis of the period nine months after graduation has shown the important decline of education quality provided by high schools. To reduce youth unemployment, the state should focus primarily on improving overall unemployment itself by implementing a dual-learning system, simplifying business opportunities, making part-time work available, or introducing lifelong learning to help transform the economy into a knowledge base.

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Section: Literature Reviewsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 70%

Determinants of youth unemployment rate: case of Slovakia

Papík

Mihaľová

Papíková

2022

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“…In this model, globalization uses the geographical scope to relocate ideas and innovation, from which the production and allocation of resources are improving. Maynou, Ord oñez, and Silva (2022) apply the beta-convergence concept to study the vulnerabilities of young people in labor market participation and social inclusion across 274 European regions from 2000 to 2019. For Bordignon, Gatti, and Gaetano (2022), a convergent process prevails among Euro area countries despite the 2008 great crisis and the 2010-2012 sovereign debt crisis.…”

Section: Convergence In Mexico: a Review Of The Literaturementioning

confidence: 99%

Long‐term regional convergence in Mexico: A new look

Germán–Soto

Gluschenko

2022

Review Development Economics

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This paper explores the convergence hypothesis of Mexican states with the national level and with one another from 1940 to 2015. Interpreting convergence as catching-up, we also capture other types of regular evolution, namely, invariance of the income gap over time, permanent absence of the gap, and steadily increasing gap (deterministic divergence). As a tool of econometric analysis, we use a novel model that describes convergence by asymptotically decaying trends and covers other types of evolution as particular cases. The results obtained suggest one or other type of regularity to be peculiar to roughly ca. 40% of income gaps both with the national level and between states. However, convergence is observed only in 6% to 15% of cases.Regarding convergence at the national level, an additional analysis by three 50-year subperiod shows that in many cases the type of evolution changes for the same state from one subperiod to another. Analyzing convergence between states, we find that convergence between neighboring states is more frequent than between other states; however, the effect of the neighborhood is not too strong.

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“…The second issue is directly related to the question whether theoretical growth models can contribute to our understanding of observed cross-sectional differences in living standards and whether these growth models are able to identify channels through which these differences decrease or increase over time (i.e. see Maynou et al 2022). Neglecting automation capital, Sala-i-Martin (1992, 2004), Mankiw et al (1992), and Sala-i-Martin (1994,1996 estimate convergence rates in the range between 2%-3%, which are considerably smaller to what endogenous growth models suggests.…”

Section: Related Literaturementioning

confidence: 99%

Fragile robots, economic growth and convergence

Klarl

2022

Economic Modelling

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

Cited by 14 publications

References 45 publications

Determinants of youth unemployment rate: case of Slovakia

Determinants of youth unemployment rate: case of Slovakia

Long‐term regional convergence in Mexico: A new look

Fragile robots, economic growth and convergence

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