Swiss Universities in the Digital Age Preparing Students for the Changing Needs of the Labour Market
In the coming years, Switzerland and many other economies will experience substantial shifts in the demand for skills and labour both across and within occupations due to digitalisation. This can create labour shortages in some occupations and excess supply in others, as well as skill mismatch within occupations. The extent of possible disparities caused by digitalisation will crucially depend on how labour supply responds to these developments, though. New labour market entrants play a particularly important role in this context because they can tailor their educational and occupational choices to these changes. While firms can react to changing needs relatively easily in terms of the number, types and contents of apprenticeships they offer, it is much more difficult for them to influence the educational and occupational choices of students entering university. Therefore, it is particularly important to understand whether and if so how university entrants respond to the changes in demanded skills caused by digitalisation.
In this project, we aim to answer the following questions: To which extent are students aware of the changes in demanded skills and labour market prospects in different occupations caused by digitalisation? Do they respond to these changes in terms of their educational and occupational choices and if so, how? Do students’ choices result in skill mismatch between labour demand and supply because students have biased beliefs or place too little weight on future labour market conditions? What are the consequences for graduates’ labour market outcomes? Can the provision of information about changes in labour demand and their importance for graduates’ labour market prospects help to reduce skill mismatch and to improve graduates’ labour market outcomes? Do changes in the courses offered to students in response to changing needs of the labour market that are caused by digitalisation help in this dimension as well? Thus, the objectives of this project are twofold. Firstly, we want to document students’ knowledge and beliefs about their labour market prospects in different occupations and changes thereof caused by digitalisation. Secondly, we want to quantify the causal relationships between their subjective expectations, the provision of information about changing labour market needs, available study options, their educational and occupational choices, and their realized labour market outcomes. To obtain the information we require for this research, we conduct a comprehensive panel survey with the students at the University of Basel. We survey students each semester while they study as well as directly after graduation and one, three and five years thereafter. We will implement the surveys as online questionnaires that we distribute via the students’ university email addresses. For the exit and follow-up surveys, we will ask for the provision of private email addresses during the student surveys in order to be able to follow students after graduation.
The first student survey will collect information on important background characteristics that we do not observe in-house, on the expectations regarding labour market conditions in different occupations after graduation, on the determinants of major, course and occupational choices as well as on the students’ plans for the time after graduation. The subsequent student surveys will repeat all questions except those regarding background characteristics in order to track changes in expectations, determinants and plans over time. The exit and follow-up surveys will collect detailed information on job search activities and labour market outcomes. For these, we can build on our experience from a pilot study we are currently conducting at our home faculty where we collect similar information from our students. Whenever possible, we will rely on the questions included in the Swiss graduate survey conducted by the Swiss Federal Statistical Office. These questions have been tested extensively and will allow us to assess the comparability of our data with the nationally representative survey. Our administrative staff will link the survey data to our in-house data on the students, all courses they have completed, study duration and grades. This allows us to measure the skills acquired by students in a very detailed way. We will receive these data in anonymized form to comply with data privacy regulations. The resulting database will be unique, and it will allow answering a wide range of questions related to students’ educational and occupational choices as well as their labour market outcomes after graduation.
Because the data will contain multiple observations per student, we are able to employ panel data methods to study the determinants of students’ choices and the causal relationships between subjective expectations, choices and labour market outcomes. These methods allows us to account for time-constant unobserved student characteristics that drive the relationships. Together with the rich set of information that we plan to collect on possible drivers this should result in credible estimates of the relationships of interest. Additionally, we will employ methods typically used in laboratory experiments to induce exogenous variation in subjective expectations that we can exploit to quantify the causal effect of expectations on the choices of interest. We will present different sets of subjective expectations regarding labour market prospects in different occupations and demanded skills to students within the student survey and let them state their preferences regarding different study options and occupations.
To study the effect of the provision of information on expectations, choices and labour market outcomes, we will subject our students to repeated randomized information treatments. The overall objective is to assess whether information campaigns can help to reduce skill mismatch caused by digitalisation and to improve graduates’ labour market outcomes. After the baseline survey, we will randomize students into groups that receive either no information, or different sets of information on labour market prospects and demanded skills in different occupations. As inputs, we will use two sources of information. Firstly, we will exploit the information on the demand for skills and expected changes therein that we collect in the employer-employee surveys. Secondly, we will exploit the Swiss Job Market Monitor of the University of Zurich. It comprises representative random samples of job advertisements covering all relevant advertising channels for each year since 1950. They capture the complete texts of the job ads and apply standardized procedures to extract certain information from the ads. In particular, the data include demanded education, occupation and specific demanded skills, which will be important to measure changes in these dimensions over time. To uncover and quantify the causal channels through which information affects the choices and outcomes of interest we will employ recently developed methods for mediation analysis.
Finally, we will investigate how participation in courses that are particularly helpful with respect to the changing needs of the labour market affect students’ occupational choices and labour market outcomes. Besides existing courses, the University of Basel and our home faculty are currently planning to introduce a number of new courses and changes in the curricula to accommodate changing needs of the labour market due to digitalisation. To facilitate exogenous variation in the take-up of both existing and these new offers, we will subject students to randomized information treatments about the availability and importance of these courses prior to their start.