This article unravels the migrants' incidence of skill mismatch taking into consideration different migration flows. Mismatch is the situation in which workers have jobs for which lower skill levels are required compared to their education. We use a dataset (from a large multi-country web survey) particularly suited to investigate differences in skill mismatch between native and migrant workers. The main advantages are its ample size and the large variety of country of origin and destination combinations, which allows for detailed analysis of different migration flows. This provides an innovative multi-country perspective, including nations and migrants from all continents. We also identify the relation between overeducation and some of the most widely accepted theoretical explanations for the phenomenon among native workers and test whether it holds for migrants. These results are achieved by fulfilling three research objectives, which are to investigate (1) the factors affecting overeducation and whether migrants are more often overqualified, (2) the relation between overeducation and different country of origin and destination combinations, and (3) whether a range of theoretically based assumptions affect the incidence of overeducation and the extent to which they are relevant in the case of migrant workers. Skill mismatch is found to be more common among migrants compared to native workers, although the incidence differs across migrants depending on the country of residence. Differences in the incidence of overeducation between native and migrant workers are not only related to the country of residence but also to the combination of country of origin and destination. When theoretically based assumptions are used to explain overeducation, the relation found for the total population does not always hold in the case of migrants. All these findings are confirmed by both an explorative and a in-depth analysis. JEL codes: J24; J61; J15

This paper studies the relationship between a vacancy population obtained from web crawling and vacancies in the economy inferred by a National Statistics Office (NSO) using a traditional method. We compare the time series properties of samples obtained between 2007 and 2014 by Statistics Netherlands and by a web scraping company. We find that the web and NSO vacancy data present similar time series properties, suggesting that both time series are generated by the same underlying phenomenon: the real number of new vacancies in the economy. We conclude that, in our case study, web-sourced data are able to capture aggregate economic activity in the labor market.

Purpose The purpose of this paper is to explore the matching process before and after the Great Recession in the Netherlands. The Dutch case is interesting because it is characterised by increasing matching efficiency. Design/methodology/approach This paper uses data from 2001 to 2014 to study the Dutch labour market matching process accounting for the three labour market states and their heterogeneities. Findings The elasticity of hires with respect to the short-term employed was significant, positive and countercyclical, while elasticities relating to new entrants were procyclical. The matching function (MF) displays constant returns to scale (CRTS) when using an alternative labour supply (LS) measure that includes the short-term employed as jobseekers. The findings are at odds with the idea of mismatch and a shortage of skills. Search frictions for employers were lower and vacancies were filled faster. This can be related to the fact that in a loose labour market context with increasing short-term employment, employers increase their hiring of employed workers which generates negative externalities on unemployed. Originality/value The implications concern the specification of the MF and the CRTS assumption when using unemployment as a LS measure.