Small differences matter: how regional distinctions in educational and labour market policy account for heterogeneity in NEET rates

Abstract

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.© The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

How to involve rural NEET youths in agriculture? Highlights of an untold story

“…The latest research developments have also stressed the importance of disparities between urban, suburban, and rural areas within countries as a source of variation between NEET subgroups (e.g. Bacher et al, 2017). These findings are further upheld by worrisome figures,…”

“…Macrosystemic factors may also influence NEETs' involvement in agriculture, especially at the policy-making level. Active labor market policy, fiscal incentives, or community ability to attract investment are all factors at a regional/national level that may give an impulse to NEETs' involvement (Bacher et al, 2017). However, in Europe, macroregulations dictated by the Common Agriculture Policy (CAP) play a more decisive role in stimulating or preventing youth involvement in the sector.…”

“…At an exosystemic level, although agriculture is not rural NEETs' first choice, a quick dissemination of a successful project may occur; in fairly small communities, this leads to risks of market saturation (Bacher et al, 2017). Therefore, it might be important that initial experiences in agriculture are followed-up by progressive production specialization (whether the production focuses on greens, flowers, or honey, depending on local features such as demand, climate, etc.).…”

“I Don’t Want to Work in Agriculture!” The Transition from Agricultural Education to the Labor Market in Rural Russia

“…This transition increases the unemployment spell of youth, who may wind up in an inactive status that is neither employed nor in education or training (termed the NEET rate). As stressed in the transition labor market literature, this potential erosion of the youth labor force gives rise to large disadvantaged groups (Bacher et al ; Bollmann and Bryden ; Philip and Shucksmith ; Unay‐Gailhard ). A disadvantaged group is defined as a population that has a higher risk of long‐term unemployment or an inactive spell in the school‐to‐work transition period, giving rise to social exclusion (Philip and Shucksmith ; Shucksmith ).…”

NEET-Jugendliche in Österreich: Problemausmaß, volkswirtschaftliche Kosten und Handlungsempfehlungen

“…9 (1) Analyse auf Bezirksebene ermöglichen. InBacher et al (2017) konnten wir nachweisen, dass numerisch kleine Unterschiede zwischen den Bundesländern Effekte auf die NEET-Rate haben.…”