Abstract. This paper provides a meta-analysis of microeconometric evaluation studies on the effectiveness of active labor market policies. The analysis is built upon a systematically assembled data set of causal impact estimates from 57 experimental and quasi-experimental studies, providing 654 estimates published between January 1990 and December 2017. We distinguish between the short and longer term impacts in our analysis; at 6, 12, 24, and 36 months after program start. After correcting for publication bias and country-specific macroeconomic characteristics, subsidized labor and public employment programs have negative short-term impacts, which gradually turn positive in the longer run. Schemes with enhanced services including job-search assistance and training programs do not have these negative short-term effects, and stay positive from 6 until 36 months after program start.

Background In this paper, we investigate the predictors for enrollment and success in Science, Technology, Engineering, and Mathematics (STEM) programs in higher education. We develop a sequential logit model in which students enroll in STEM education, may drop out from STEM higher education, or continue studying until they graduate in an STEM field. We use rich Dutch register data on student characteristics and high school exam grades to explain the differences in enrollment, success, and dropout rates. Results We find that females are less likely to enroll in STEM-related fields, while students with higher high school mathematics grades are more likely to enroll in STEM. Female students have lower first-year dropout rates at university of applied sciences STEM programs. With respect to study success, we find that conditional on enrollment in STEM, women are less likely to graduate than men within the nominal duration or the nominal duration plus one additional year. However, female students do perform equally well as male students in terms of graduation within 10 years. Conclusions We conclude that STEM programs are less popular among female students and that female students are less likely to graduate on time. However, females perform equally well in STEM higher education in the long run. For this reason, policy should be geared at increasing study success in terms of nominal graduation rates among female STEM students.

Purpose -The purpose of this paper is to present the results of a discrete choice experiment (DCE) on the competencies of potential information technology (IT)-retrainees. The results give insights in the monetary value and relative returns to both soft and hard skills. Design/methodology/approach -The authors apply a DCE in which the authors propose seven pairs of hypothetical candidates to employers based in the municipality of Amsterdam, the Netherlands. These hypothetical candidates differ on six observable skill attributes and have different starting wages. The authors use the inference from the DCE to calculate the marginal rates of substitution (MRS). The MRS gives an indication of the monetary value of each skill attribute. Findings -Employers prefer a candidate who possesses a degree in an exact field over a similar candidate from another discipline. Programming experience from previous jobs is the most highly valued characteristic for an IT-retrainee. Employers would pay a candidate with basic programming experience a 53 percent higher starting wage. The most high-valued soft skill is listening skills, for which employers are willing to pay a 46 percent higher wage. The results of this paper show that both hard and soft skills are important, but not all soft skills are equally important. Originality/value -The results on the returns to skills provide guidelines to tailor IT training and retraining programs to the needs of the business environment. A key strength of this paper is that the authors have information on the preference orderings for different skills and kinds of experience.

We analyse the relation between bank competition and the transmission of unconventional monetary policy (UMP) for 14 European countries. We estimate an error-correction model to analyse the relation between the passthrough of UMP to long-term commercial interest rates and the level of competitiveness. We estimate this model for three different measures: the Herfindahl Index (HHI), the Boone indicator and the H-statistic. Our results indicate that bank concentration as measured by the HHI is not a good proxy of competitive conditions in the market, whereas the other two measures are more meaningful in this context. The pass-through of UMP is increasing in the degree of bank competition as measured by the Boone indicator and the H-statistic. The relationship between pass-through and the level of market concentration is less well defined, suggesting that competition and market concentration do not go hand in hand in the banking sector.