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By studying the factors underlying differences in trade performance across European economies, this paper derives six different “trade models” for 22 EU countries and explores their developmental and distributional dynamics. We first introduce a typology of trade models by clustering countries on the basis of four key dimensions of trade performance: endowments, technological specialisation, labour market characteristics and regulatory requirements. The resulting clusters comprise countries that base their export success on similar trade models. Our results indicate the existence of six different trade models: the ‘primary goods model’ (Latvia, Estonia), the ‘finance model’ (Luxembourg), the ‘flexible labour market model’ (UK), the ‘periphery model’ (Greece, Portugal, Spain, Italy, France), the ‘industrial workbench model’ (Slovenia, Slovakia, Poland, Hungary, the Czech Republic), and the ‘hightech model’ (Sweden, Denmark, Netherlands, Belgium, Ireland, Finland, Germany and Austria). Subsequently, we provide a comparative analysis of the economic development and trends in inequality across these trade models. Inter alia, we observe a shrinking wage share and increasing personal income inequality in most of them, yet find that the ‘high-tech model’ is an exceptional case, being characterised by relatively stable economic development and an institutional setting that managed to counteract rising inequality.

Labour market and education policy makers and researchers are increasingly focusing on the NEET indicator as a supplement to the youth unemployment rate. Analyses of factors influencing NEET have concentrated primarily on individual characteristics such as gender and migration background on one hand, and on macro-level factors of nations such as economic growth and minimum wage regulations on the other. However, nations are not homogenous, especially when a country is divided into several federal states, as is the case with Austria. This article aims to analyse regional differences within Austria. In order to explain the differences, we define a multilevel model that contains four contextual factors: the importance of upper secondary education; the importance of dual education; vacant jobs; and expenditures for active labour market policy. Because the institutional level addresses different age groups, the analysis was split into two age groups: 15-19 and 20-24 years. The results have shown that, besides the social structure of the population, contextual factors like the upper secondary education, the dual education, vacant jobs, and expenditures for active labour market policy are also relevant for explaining regional differences in the NEET rates. But one main insight was that the impact of the contextual factors varies between different social groups. [ABSTRACT FROM AUTHOR]

Abstract: No single institution can reduce (long‐term) youth unemployment. Welfare and labour market institutions function as “bundles”, through multiple inter‐institutional synergies. Based on a focused literature review for theory and on cluster analysis for empirics, the author identifies five such regimes across the EU‐27 and estimates their effects on the youth unemployment ratio and on long‐term youth unemployment. The most helpful institutional arrangement for young people in the labour market would be a combination of strong dual apprenticeship embedded in a corporatist labour market regime with high levels of social security, active labour market policy, and spending on education and childcare. [ABSTRACT FROM AUTHOR]

One of the biggest challenges currently facing European society is the dramatically high level of youth unemployment. Commonly, political solutions and strategies can be found in those countries that have been able to keep youth unemployment low in spite of the financial and economic crises. Austria is such a case. On the basis of European Union Member State data, the article gives a multifactorial explanation of youth unemployment and asks whether these factors can explain relatively low youth unemployment in Austria. With the country's 'youth safety net' presented in detail, it is shown that active labour market policy reduces youth unemployment in Austria. The article also points out the limitations of cross-country comparisons of youth unemployment rates and proposes the use of a greater number of indicators. Finally, the article argues for economic policies to stimulate demand, which have to be based on a political and social commitment to full employment. [ABSTRACT FROM AUTHOR]

Due to the limited relevance of traditional labour market indicators for youth unemployment, researchers and policy-makers focus on an indicator known as not in employment, education or training (‘NEET’). The underlying assumption is that NEET indicates young people with a high risk of social exclusion. For political solutions, it is necessary to consider the heterogeneity of the NEET group. This paper examines the socio-structural attributes that characterise NEET youth in Austria, the main reasons for the NEET situation and whether NEET status, once assigned to an individual, is permanent or temporary. Latent cluster analyses identify seven subgroups of NEET youth, all of which face different challenges. The data source used is the Austrian Labour Force Survey (micro census) from the years 2008–2010, and young people between 16 and 24 years old are analysed. A panel data-set is created to analyse NEET permanence. Drawing on the identified reasons for a permanent NEET situation, this paper argues for more job and training opportunities that fit the needs of young people, especially those with illnesses. Finally, this study asks whether the definition of NEET should be adapted to exclude young mothers with care responsibilities who are not actively looking for a job. [ABSTRACT FROM AUTHOR]