Assimilation and discrimination effects among the UK migrant labour force

This paper analyses the performance of foreign born male individuals on the British labour market. Using data from the Quarterly Labour Force Survey over the period 1992-2009, we find consistent evidence of positive economic assimilation of immigrants, with their labour market outcomes improving with duration of stay in the country. We also find that the performance of individuals who came to the UK to complete their education is significantly higher than that experienced by labour market entrants.Immigrants, Earnings, Employment

The hub continent? Immigrant networks, emigrant diasporas and FDI

This paper studies the effects of immigrant networks on the bilateral FDI of France, Germany, Italy, Spain and the UK, and, for Italy and Spain, also of the emigrant diasporas. It analyses the effects of skilled and unskilled immigrants and of networks linked to developing and developed countries. Results show that the FDIs of the UK, Germany and France are affected by the networks of skilled immigrants, while those of Italy and Spain are prompted only by the emigrant diasporas. Networks linked to OECD and non-OECD countries have similar effectsmigration, networks, skills, diasporas, FDI

Migrant Business Networks and FDI

This paper studies the effects of migration on the bilateral FDI of four European countries, Germany, Italy, France and the U.K. It is based on four distinct datasets with time spans going from 1990 to 2004. It focuses on the impact on FDI of skilled and less-skilled immigrants and on the networks’ ties with the less developed countries. Results are that the effects of skilled immigrants are positive and robust for both inward and outward FDI, and that networks linked to the developing countries mostly have stronger effects on the outward FDI than those related to the developed economies.Migrant Business Networks, Skills, FDI

Trends and dynamics in the Italian labour market. An empirical evaluation using RFL data, 1993-2007

The empirical analysis carried out in this paper represents the basis for the construction of the labour market module in the dynamic microsimulation model CAPP_DYN. Using LFS longitudinal data for the period 1993-2007, we describe the recent trends on the Italian labour market and provide an international comparison with other European countries. In order to investigate the determinants of labour market transitions, multinomial logistic regressions are implemented, and the estimated parameters are then used to model transition probabilities in the dynamic microsimulation model.Labour Mobility, Multinomial Logit

Trends and dynamics in the Italian labour market. An empirical evaluation using RFL data, 1993-2007

The empirical analysis carried out in this paper represents the basis for the construction of the labour market module in the dynamic microsimulation model CAPP_DYN. Using LFS longitudinal data for the period 1993-2007, we describe the recent trends on the Italian labour market and provide an international comparison with other European countries. In order to investigate the determinants of labour market transitions, multinomial logistic regressions are implemented, and the estimated parameters are then used to model transition probabilities in the dynamic microsimulation modelLabour Mobility; Multinomial Logit

The hub continent? Immigrant networks, emigrant diasporas and FDI

This paper studies the effects of immigrant networks on the bilateral FDI of France, Germany, Italy, Spain and the UK, and, for Italy and Spain, also of the emigrant diasporas. It analyses the effects of skilled and unskilled immigrants and of networks linked to developing and developed countries. Results show that the FDIs of the UK, Germany and France are affected by the networks of skilled immigrants, while those of Italy and Spain are prompted only by the emigrant diasporas. Networks linked to OECD and non-OECD countries have similar effectsmigration, networks, skills, diasporas, FDI

Student mobility in tertiary education: institutional factors and regional attractiveness

Member States have committed themselves to promoting the learning mobility of young people following the 2011 Communication on an agenda for the modernisation of Europe’s higher education system (COM(2011) 567). The Council conclusions on a benchmark for learning mobility (2011/C 372/08) specified that by 2020 ‘an EU average of at least 20% of higher education graduates should have had a period of higher education-related study or training abroad’. In this report, two types of mobility are distinguished, namely degree mobility and credit mobility, both of which are included in the benchmark. Little research has been carried out on international student mobility determinants in general and on Erasmus students in particular, especially taking into account the regional dimension of learning mobility. This report focuses on student mobility in the EU between 2011 and 2014, through the description of the main destinations of mobile students, as well as on inward mobility across and within countries (measured as the share of mobile students on total student population), with a particular focus on institutions and regions. It also analyses the main factors associated with degree and credit mobility, taking into account different tertiary education levels (i.e. undergraduate, master and PhD level), through the comparison between institutional factors (teaching and research activities of universities as well as their reputation) and regional attractiveness (level of urbanisation, employment opportunities and regional education systems). There are five main conclusions from this report. First, in relation to the most attractive destinations, degree mobility appears to be very concentrated in a few countries, while credit mobility tends to be more equally distributed across Member States. Second, degree mobility is higher than credit mobility across and within countries. Third, institutional characteristics tend to be associated with student mobility more than regional ones. Fourth, among institutional characteristics, better quality universities and those with a higher reputation are associated with a higher share of mobile students, while research orientation and excellence are more relevant for degree mobile PhD students. Fifth, among regional characteristics, the level of urbanisation of the region is an important factor in shaping students’ mobility: high-density regions have higher degree mobility rates, but a lower share of credit mobile students.JRC.B.4-Human Capital and Employmen

Monitoring the Evolution of Education and Training Systems: A Guide to the Joint Assessment Framework

This technical report represents the official guide to DG EAC’s Joint Assessment Framework (JAF). The JAF methodology was first introduced by DG EMPL in 2010 to standardise the monitoring of benchmarks and indicators under the Employment Guidelines. Since two of the Employment Guidelines concern education and training, DG EAC was directly involved in developing the methodology and has since introduced it into its own monitoring approach concerning the strategic framework for European cooperation in education and training (ET 2020). The JRC’s Centre for Research on Education and Lifelong Learning (CRELL) has helped EAC to adapt the JAF to the context of education and training, developing the quantitative part of the methodology for the ET 2020 benchmarks. This report details the main empirical, theoretical and policy arguments behind the selection of the various sub-groups and sub-indicators for each of the six operational ET 2020 benchmarks; it also lists the methodological criteria adopted throughout the JAF development work. Finally, the report provides explanations on how to interpret the JAF charts that are produced annually by CRELL for the quantitative assessment.JRC.DDG.01-Econometrics and applied statistic