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ABSTRACT
What drives employment growth and social inclusion in the regions of the European Union? Regional Studies. The European Union promotes development strategies aimed at producing growth with ‘a strong emphasis on job creation and poverty reduction’. However, whether the economic conditions in place in European Union regions are ideal for the generation of high- and low-skilled employment and labour market inclusion is unclear. This paper assesses how the key factors behind European Union growth strategies – infrastructure, human capital, innovation, quality of government – condition employment generation and labour market exclusion in European regions. The findings indicate that the dynamics of employment and social exclusion vary depending on the conditions in place in a region. While higher innovation and education contribute to overall employment generation in some regional contexts, low-skilled employment grows the most in regions with a better quality of government. Regional public institutions, together with the endowment of human capital, emerge as the main factors for the reduction of labour market exclusion – particularly in the less developed regions – and the promotion of inclusive employment growth across Europe.
摘要
什麽驱动了欧盟各区域中的就业成长与社会包容？ Regional Studies。欧盟推动以引发成长同时“强调创造就业和降低贫穷”为目标的发展策略。但在欧盟各区域中，适当的经济条件对生产高技术与低技术就业和劳动市场包容而言是否理想，则不甚清楚。本文评估欧洲各区域的就业生成与劳动市场排除，如何取决于欧盟成长策略背后的关键因素—基础设施，人力资本，创新，以及政府素质。研究发现指出，就业和社会排除的动态，根据区域中的适当条件而有所不同。当较高的创新和教育在若干区域脉络中促进了总体就业创造时，在政府质量较好的区域中，低技术就业则成长最多。区域公共制度与人力资本的才能，共同浮现成为降低劳动市场排除—特别是在较低度发展的区域—以及提倡欧洲各地包容性就业成长的主要因素。
RÉSUMÉ
Quel est le moteur de la croissance de l’emploi et de l’inclusion sociale dans les régions de l’Union européenne? Regional Studies. L’Union européenne promouvoit des stratégies de développement visant à stimuler la croissance et dont ‘l’accent est mis sur la création de l’emploi et la réduction de la pauvreté’. Néanmoins, il n’est pas tout à fait évident si, oui ou non, le milieu économique actuel dans les régions de l’Union européenne est propice à la création de l’emploi à la fois qualifié et non-qualifié. Ce présent article évalue comment les facteurs clés qui étayent les stratégies de croissance de l’Union européenne – à savoir l’infrastructure, le capital humain, l’innovation, la compétence de l’administration – déterminent la création de l’emploi et l’exclusion sur le marché du travail dans les régions européennes. Les résultats laissent indiquer que la dynamique de l’emploi et de l’exclusion sociale varient suivant le milieu économique actuel dans une région particulière. Tandis que des niveaux supérieurs d’innovation et d’éducation contribuent à la création globale de l’emploi dans certains contextes régionaux, la croissance de l’emploi non-qualifié est plus évidente dans les régions où la compétence de l’administration s’avère mieux. Il s’avère que les établissements publics régionaux, conjointement avec la dotation en capital humain, sont les principaux facteurs susceptibles d’expliquer la réduction de l’exclusion sur le marché du travail – notamment dans les régions moins développées – et la promotion de la croissance de l’emploi inclusif à travers l’Europe.
ZUSAMMENFASSUNG
Was fördert Beschäftigungswachstum und soziale Eingliederung in den Regionen der Europäischen Union? Regional Studies. Die Europäische Union fördert Entwicklungsstrategien zur Erzeugung von Wachstum mit 'einem starken Schwerpunkt auf der Schaffung von Arbeitsplätzen und Verringerung der Armut'. Hierbei ist allerdings unklar, ob die vorhandenen Wirtschaftsbedingungen in den Regionen der Europäischen Union zur Schaffung von hoch und niedrig qualifizierten Arbeitsplätzen und zur Eingliederung in den Arbeitsmarkt ideal sind. In diesem Beitrag wird untersucht, wie die zentralen Faktoren der Wachstumsstrategien der Europäischen Union – Infrastruktur, Humankapital, Innovation, Qualität der Regierungsführung – die Schaffung von Arbeitsplätzen und Ausgrenzung aus dem Arbeitsmarkt in europäischen Regionen konditionieren. Aus den Ergebnissen geht hervor, dass die Dynamik der Beschäftigung und sozialen Ausgrenzung je nach den in einer Region vorhandenen Bedingungen unterschiedlich ausfällt. Während ein höheres Maß an Innovation und Bildung in einigen regionalen Kontexten zur generellen Schaffung von Arbeitsplätzen beiträgt, steigt die Anzahl der niedrig qualifizierten Arbeitsplätze in Regionen mit besserer Regierungsführung am stärksten. Als wichtigste Faktoren für die Verringerung der Ausgrenzung aus dem Arbeitsmarkt – insbesondere in schwächer entwickelten Regionen – und die Förderung eines inklusiven Beschäftigungswachstums in ganz Europa erweisen sich regionale öffentliche Einrichtungen sowie die Ausstattung mit Humankapital.
RESUMEN
¿Qué fomenta el crecimiento de empleo y la inclusión social en las regiones europeas? Regional Studies. La Unión Europea fomenta estrategias de desarrollo con el objetivo de generar crecimiento con ‘un fuerte énfasis en la creación de empleo y reducción de la pobreza’. Sin embargo, no está claro si las condiciones económicas existentes en las regiones de la Unión Europa son ideales para generar empleo de baja y alta calificación y la inclusión en el mercado laboral. En este artículo evaluamos cómo influyen los factores principales de las estrategias de crecimiento de la Unión Europea –infraestructura, capital humano, innovación, calidad gubernamental– en la creación de empleo y la exclusión del mercado laboral en las regiones europeas. Los resultados indican que las dinámicas de empleo y exclusión social varían según las condiciones existentes en cada región. Mientras que un nivel más alto de innovación y educación contribuye a generar empleo total en algunos contextos regionales, el empleo de menor calificación es el que más crece en las regiones con mejor calidad de gobierno. Resulta que los principales factores para reducir la exclusión del mercado laboral –especialmente en las regiones menos desarrolladas– y el fomento del crecimiento de empleo integrador en toda Europa son las instituciones públicas de ámbito regional, junto con la dotación de capital humano.
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ACKNOWLEDGEMENTS
The authors thank the editor, Tomasz Mickiewicz, as well as three anonymous reviewers for their rounds of comments and suggestions on earlier versions of the manuscript. Comments by participants at conferences and seminars in Lisbon, Louvain-la-Neuve, Lund, Valencia and Washington, DC, are gratefully acknowledged.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
SUPPLEMENTAL DATA
Supplemental data for this article can be accessed at https://doi.org/10.1080/00343404.2016.1255320
Notes
1. Social exclusion is a broad concept involving factors that may leave specific groups in society vulnerable. These include unemployment, lack of access to education, to childcare and to healthcare facilities, inadequate living conditions, and scarce social participation. This study focuses particularly on labour market exclusion.
2. For each of these elements, a large body of empirical research has examined their effect on economic growth in the EU regional context. For example, see Rodríguez-Pose and Vilalta-Bufí (Citation2005) and OECD (Citation2009) for human capital; Fagerberg, Verspagen, and Caniëls (Citation1997), Bottazzi and Peri (Citation2003), and Crescenzi and Rodríguez-Pose (Citation2011) for innovation; Moreno, Artís, López-Bazo, and Suriñach (Citation1997), and Crescenzi and Rodríguez-Pose (Citation2012) for infrastructure; and Crescenzi, Di Cataldo, and Rodríguez-Pose (Citation2016) for institutions.
3. This paper uses the definitions of levels of education adopted by the EU Labour Force Survey (LFS), which are based on UNESCO's International Standard Classification of Education (ISCED).
4. While the share of unemployed being long-term unemployed reached the lowest level in 2009, the long-term unemployment rate, as a result of the crisis, grew considerably in that very year. Hence, the long-term unemployment rate reflects to a greater extent the immediate shock of the crisis than the share of unemployed being long-term unemployed. Since 2009, however, both variables have co-evolved in a similar way, rising moderately between 2009 and 2012. Both indicators are correlated at 75% during the period of analysis. Because of the one-off shock provoked by the crisis in the long-term unemployment rate, the share of unemployed being long-term unemployed is preferable as an indicator that is less affected by the immediate short-term shock linked to the beginning of the crisis. In any case, in order to assess the robustness of the results, the paper resorts to the long-term unemployment rate as an alternative to the share of unemployed being long-term unemployed in the GMM analysis presented in . The results of using either social exclusion variable in the dynamic panel analysis are virtually unchanged.
5. Long-term unemployed are defined by EUROSTAT as those individuals unemployed for 12 months or more. Unemployment refers to the population of jobseekers aged 15–74 who are available to start work within the next two weeks and who have actively sought employment at some time during the last four weeks.
6. The variable is available at the regional level only for Austria, Belgium, Czech Republic, Italy, Ireland, Spain, Romania, Sweden and Slovakia.
7. ISCED = International Standard Classification of Education.
8. Using a different normalization, e.g., kilometres of roads divided by thousand inhabitants, leaves the econometric results essentially unaltered (regression results are available from the authors upon request).
9. For more details on the methodology used to combine the Regional Quality of Government Index with the World Bank Governance Indicators, see Charron et al. (Citation2014).
10. EUROSTAT provides data on regional employment in the primary, secondary and tertiary sectors. The three variables are collinear when included simultaneously in the model. Therefore, primary and secondary sector employment (excluding services) were chosen for reasons of data availability.
11. The share of employees was selected over the share of self-employed because the former variable has more observations.
12. The choice of geographical level for regions follows Crescenzi and Rodríguez-Pose (Citation2012) and Crescenzi et al. (Citation2016) in selecting the regional units by country which are more meaningful in terms of institutional and governance features. This implies NUTS-2 regions for Austria, Czech Republic, Finland, France, Hungary, Ireland, Italy, Netherlands, Poland, Romania, Slovakia, Slovenia, Spain and Sweden. NUTS-1 are used for Belgium, Germany and the UK.
13. GMM-system (Arellano & Bover, Citation1995; Blundell & Bond, Citation1998) is preferred to GMM-difference because the lagged levels of the variables are likely to be weak instruments for first-differences of endogenous variables. Instruments are collapsed in order to avoid issues of instrument ‘proliferation’ (Roodman, Citation2009). As the Arellano–Bond autoregressive test reports first-order lags as endogenous, they are excluded as instruments (Di Cataldo & Rodriguez-Pose, Citation2016). In all GMM estimations the Hansen test for over-identifying restrictions reports a p-value indicating that instruments as a group are exogenous. Alternative versions of GMM estimations demonstrate that the results are not sensitive to the introduction of further restrictions on the set of instruments used, for example, by excluding lower-order time lags (regression tables are available from the authors upon request).
14. Models (1) and (3) are also estimated using the long-term unemployment rate as a control variable instead of the share of unemployed being long-term unemployed. All the main results remain unchanged. The long-term unemployment rate is negative and significantly correlated with employment growth. These regression results are available from the authors upon request.
15. As this empirical test is performed on reduced samples, in order to keep the number of instruments in the GMM model close to the number of groups (Roodman, Citation2009), only second- to sixth-order lags in the estimations for core regions and second- to fifth-order lags in the estimations for peripheral regions are considered.
16. Germany has committed to a reduction in long-term unemployment of 320,000 individuals; Sweden has pledged to reduce long-term unemployment and long-term sick leave by 14% (see http://ec.europa.eu/europe2020/pdf/targets_en.pdf).