In this subproject we aim to map changing labor markets. While many argue that robots and artificial intelligence will soon replace humans on the job, we still know little about the actual effects of technological change on work. A dominant hypothesis in the literature is that technology decreases the demand for jobs requiring many routine and codifiable tasks and causes employers to seek ever more skilled workers. However, previous studies imprecisely measure employer demand for skills and tend to assume that it only varies across occupations, neglecting how the content of daily work might change within occupations.

To overcome these limitations, in this subproject we use a rich but little used data source: the novel big data on online job postings. We analyze the skill requirements of millions of job postings in the United-Kingdom and the Netherlands to map employer demand both across and within occupations over the last decade. Are employers indeed demanding greater skills than before? How has the demand for soft skills changed in relation to occupation-specific skills? We aim to provide a comprehensive overview of how the demand for skills has changed in recent years. In a second step, we will link these macro-level trends to individual-level panel data to analyze how the employment trajectories of individuals are affected by changes in skill requirements, providing insight into which educational groups are best equipped to meet employer demand.

Decisions about which educational degree individuals pursue have consequences for their work lives. In this subproject we study whether and to what extend vocationally trained workers have different careers than generally trained workers. Vocational education which prepares students to work in specific occupations is assumed to provide easy entrance into the labor market but lower employment prospects and lower income in the late career. In contrast, students who completed general degrees which convey broad knowledge, basic numeracy, and literacy skills tend to struggle in the first years but benefit in later career stages. Based on that finding, scholars argue that in times of rapid technological change occupation-specific skills outdate too quickly leaving vocational graduates with limited options. General education in turn equips workers with the required flexibility to operate on changing labor markets.

While research so far has found indication of a late-career penalty for vocationally trained workers in various countries, little yet is known about why these disparities between workers trained differently exist. This subproject aims to identify and examine the drivers of education-based career inequality such as labor market mobility, cumulative (dis)advantage, and differences in institutional context. To this end, we analyze employment trajectories from large panel surveys and register data from various countries.

In this subproject, we look at the theoretical mechanisms that drive the career differences between general and vocational graduates, by zooming in on employers’ evaluations and decisions. In rapidly changing labor markets and work contexts, a common way of thinking about the maintenance of employability throughout a career, points to education and skills-updating. Previous research shows that more specific degrees pay off differently in the labor market compared to more general degrees, raising the question why this is the case. Specifically, in this project we ask how employers as gatekeepers evaluate the skills and credentials over applicants’ life courses and how these evaluations translate into hiring decisions.

To answer these questions, we first conduct in-depth interviews with employers in Germany and later, a factorial survey experiment with German and British employers. In the interviews, we focus on how the hiring professionals practice their evaluations and how the applied criteria differ for applicants with different skill-sets and educational credentials in different career stages. Further, we compare different cases as occupations, including software development and Human Resource Management. In the survey experiment, we then take a national-comparative angle to further zoom in on the late-career penalty mechanisms and on how the evaluations play out in different institutional contexts.