Mismatch: Skills and Education Kick off meeting Brighton Work package 5: Mismatch: Skills and Education Kick off meeting Brighton 1st April 2014

WP 5 – Skill Mismatch Task 1: Drivers of overeducation (ESRI) Task 2: Transitions and labour market flows – who moves where and why? (MUP) Task 3: Are students crowding out low-skilled youth? (SGI, CEPS) Task 4: Recruitment and education provision effects on graduate overeducation and overskilling (ESRI) Task 5: Policy synthesis and integrative report (all partners) www.style-research.eu

Task 1 Drivers of Overeducation While a considerable amount of work has been undertaken on the personal characteristics of mismatched workers, relatively little is known of the macro-economic and institutional drivers of mismatch. The lack of knowledge in this area has been constrained by the over-reliance of country specific micro-data sets. As an alternative, we propose to construct a time-series of youth over-education, along with relevant economic and institutional variables, across a range of countries . Research Questions: 1) What is the impact of a range factors on the incidence of youth over-education across countries over time.? 2) Are there common themes in the drivers of youth overeducation internationally, or does the nature of the policy response vary from country to country? www.style-research.eu

Data and methods: we propose to use EU LFS data, augmented by nationally available data, to construct a time-series of youth over-education, along with relevant economic and institutional variables, across a range of countries. In addition to youth overeducation, we will use the EU LFS extract a series of covariates from each wave of the micro data that reflect sectoral composition of employment, demand for labour at each educational level (based on education specific unemployment rates), demand/supply indicators (based on ratios of employed to unemployed by education), population structure measures etc. The data will be augmented from other sources for measures of labour market institutions and other pertinent macroeconomic variables such as GDP per capita, university fees, trade-union density, employment protection legislation, educational quality etc. The determinants of youth overeducation will be assessed using time-series econometric techniques. www.style-research.eu

Open questions: In general: To what extent are the patterns and determminants of youth overeducation likely to differ from those of adult overeducation? What are the principal benefits \ drawbacks of a time-series apprach as opposed to one based on cross-sectional or panel data? www.style-research.eu

Task 2 Transitions and labour market flows – who moves where and why? European analyses of labour market flows typically concern the working- age population as a whole; i.e. not the youth and their sub-groups. In addition, they often lack international dimension and/or longitudinal structure because of data limitations. As an alternative, we intend to analyse the youth labour market flows and flow transition rates in a cross- country perspective, using the most recent longitudinal EU-SILC. Research Questions: 1) How is the worsening performance of youth labour markets reflected in transitions between employment, unemployment, and inactivity? 2) Which factors affect the probability of a young individual to change the current status? 3) Are variations in youth unemployment rates attributed predominantly to changes in inflow rates to or outflow rates from unemployment? www.style-research.eu

Data and methods: We propose to use longitudinal EU-SILC to construct chains of labour market flows and flow transition rates (total youth, gender and educational breakdowns). The longest-lasting panels are of four- year duration. However, we propose to use several two-year panels, which are of much larger (unweighted) sample sizes, to ensure sufficient representativeness for various data breakdowns. Conditional probability of leaving the current labour market status will be estimated by discrete time hazard models with current status duration, gender, age, education, family characteristics, urbanisation etc. as explanatory variables. We aim to derive the steady-state unemployment rates that would prevail if the flow rates into and flow rates from unemployment remain constant. In reality, however, the inflow and outflow rates vary over time. The (log) decomposition makes it possible to show how much of the variance of unemployment accounts for changes in all the relevant transition rates. www.style-research.eu

Open questions: 1) In EU-SILC, the monthly labour market states are self-reported and stated retrospectively for the previous year. Among other consequences, the definition of unemployment thus differs from the ILO definition used in quarterly national LFSs. To what extent are the results based on these data sources likely to differ? 2) We decompose variations of the steady state unemployment rates; not variations of the actual ones. Especially in a shorter run, the steady state approach may not mirror the developments in actual unemployment rates accurately. To what extend would this obstacle limit the relevance of our results? www.style-research.eu

Task 3: Are student workers crowding out the low-skilled? Background: Massification of tertiary education across Europe is taking place along other structural processes and changes which enhances job polarization and competition for low-skilled jobs Research questions: 1) To what extent are growing numbers of university students replacing low-skilled workers in low-skilled jobs? 2) How has this been affected by the crisis? 3) What are employers’ preferences in low-skilled and student jobs? 22/11/2018

Data and methods Using EU LFS data to study age and education composition of low skilled jobs: analysis of jobs/occupations (ISCO) over time and across EU countries Using online data from private and public portals to study characteristics of student jobs as designated by employers in job advertisements Building on previous work conducted within NEUJOBS and INGRID projects: Analysis of “low-skillness” across Europe, analysis of online job adverts to study employers’ skill demand, analysis of jobseekers profiles based on web data 22/11/2018

Contribution and open questions Task contributes to: understanding patterns of student employment in low-skilled jobs across Europe (temporary mismatch) – employment possibilities for studying youth vary due to different labor market structures, labor market legislation, different demand of education systems, etc. understanding preferences of employers in low-skilled jobs and ‘student jobs’ Open questions: Country selection 22/11/2018

Task 4 Recruitment methods and educational provision effects on mismatch We will assess the extent to which mismatch on labour market entry is determined by the route into employment and the degree to which such relationships vary across countries. The research will investigate the degree to which graduate overeducation and overskilling is related to content and delivery of third-level degree programs and the type of job- search undertaken by graduates., formal lectures, internships, practical as opposed to theoretical knowledge, project based learning etc Research Questions: 1) To what extent is labour market mismatch related to the variations in the structure of degree programs.? 2) Is graduate mismatch related to the nature of the route into employment. Are certain forms of job-search more heavily correlated with overeducation and overskilling? www.style-research.eu

Data and methods: The Flexible Professional in the Knowledge Society (REFLEX) data set published in 2010 contains information on university graduates from 15 European countries who completed their degree programmes in 2000/1 and were subsequently surveyed in 2005. The dataset contains information on the extent of both over- education and over-skilling in first and current employment. The Reflex data contains detailed information on the composition of degree programs and specifically the extent of formal lectures, internships, practical as opposed to theoretical knowledge, project based learning, work experience etc. Modes of job entry considered captured in the data. Methods of job- search include newspaper advertisements, public employment agencies, private employment agencies, through internet, self- initiated contact with employers, approached by employers, through work placement, personal contacts etc. www.style-research.eu

Open questions: 1) Do job-search methods have a causal effect on mismatch or is it the case that sub-optimal jobs are more likely to be advertised in certain ways? Can we separate out the two effects? 2) In relation to degree program structure, is it possible that lower ability graduates, who are more likely to be observed as mismatched, opt for certain types of degrees? How can we control for such unobserved bias in a cross-section? www.style-research.eu