University-to-work transitions in Germany – do graduate job seekers benefit from migration and work experience?

ABSTRACT

This paper investigates the effects of migration and work experience on university-to-work transitions of German university graduates. We use a job search model, signaling and social network theory to discuss different links between the duration of labor market entry, graduate mobility and work experience. We apply event history analyses and make use of administrative social security records to examine whether work experience and pre-study as well as post-study migration accelerates the labor market entry of graduates. Our regression results stress the importance of both mobility and work experience for the length of the transition period. However, whether the effect is beneficial or adverse depends on the type of graduate migration and previous employment.

KEYWORDS:

• Labor market entry
• migration
• work experience
• graduates
• Germany

JEL CLASSIFICATION:

• C41
• I23
• J61
• R23

Acknowledgment

The authors would like to thank two anonymous referees and the editor, Colin Green, for helpful remarks and suggestions. We have also benefited from useful discussions with seminar participants at the Winter Seminar 2019 of the Gesellschaft für Regionalforschung (GfR). Furthermore, we would like to thank Ingo Liefner for helpful remarks and suggestions. The usual disclaimer applies.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 In the winter semester 2017/18, 59.5% of the students in Germany carried out side jobs during higher education. On average, these jobs make up 40% of their monthly budget and may therefore contribute to a great extent to the financing of the livelihood of many graduates (Studitemps GmbH and Maastricht University 2019).

2 In the empirical analysis, we consider that some graduates are directly hired by the firm they worked for during studies because employers might use student jobs as a screening device. These young workers receive a job offer and probably manage to enter the labor market very quickly although their search effort is likely zero.

3 In the model, students have an infinite horizon and they know the job offer arrival function, the cost function and the wage offer distribution. However, they have no information on the time of job offer arrivals and the corresponding wages in advance. Van der Klaauw and Van Vuuren (2010) assume that graduates maximize the expected present value of future utility, which is influenced by the costs of job search, arrival rate, discount rate, and the wage or welfare benefits, depending on whether the graduate accepts a job offer or becomes unemployed after graduation. We refrain from a more detailed description of the formal model and refer to the presentation by Van der Klaauw and Van Vuuren (2010).

4 Arcidiacono (2004) and Kinsler and Pavan (2015) provide evidence for the relevance of corresponding selection processes when choosing the field of study.

5 We are grateful to a referee for suggesting this additional argument.

6 Our theoretical arguments and our empirical model refer to job search within the country in which the young workers graduate. We do not consider international migration to take up a first job after graduation. Mobility therefore means leaving the region of study and moving to another labour market region in Germany.

7 Moreover, there is also an argument for reverse causality. Teichert et al. (2020), for instance, note that the pressure to migrate may rise as the length of a residence spell in the university region increases if the duration reflects the length of unsuccessful job search in the university region. A longer transition period might thus also cause migration.

8 We refrain from developing a formal model since this is beyond the scope of the present paper, which focuses on the empirical analysis of graduates’ labor market entry.

9 We assume that $\lambda$ increases as grades improve. The grades might capture the effects of various study-related factors that influence the likelihood of receiving a job offer. We do not discuss in detail the effects of graduate characteristics $x$ on $\lambda$ because $x$ is thought to represent distinct attributes whose effects on $\lambda$ are supposed to differ.

10 However, we might assume that this specific effect of work experience gained during studies on the transition time arises only during the first few months after graduation. We are grateful to a referee for this suggestion. Yet, as we identify net effects in the empirical analysis, it is not possible to provide evidence on this supposition.

11 E.g. Waldorf and Yun (2016) or Iammarino and Marinelli (2015) interpret migration in the context of a reduced probability to get an education-job mismatch, i.e. overeducation.

12 To be precise, the hazard rate is the probability divided by time and therefore may be larger than one. In the continuous case, it can vary between zero and infinity and is rather a rate than a probability. When we speak of probabilities later in the results section, it should be understood against this background.

13 The six universities included in the analysis are medium-sized higher education institutions which offer each a broad range of study fields, and attract on average 44% of the graduates in our sample from their own university region (Table A2).

14 We also estimated the models with a minimum duration of six and twelve months. The results confirm the findings discussed in this paper.

15 The data at hand do not allow us to control for the intensity and timing of job searching in our models. A significant number of graduates start searching for jobs before final examinations (Böpple 2010; Van der Klaauw and Van Vuuren 2010). In the empirical model, we cannot differentiate between early job search before graduation and job search that starts after final exams. However, our empirical model assumes (like most of the other duration analyses) that only after the date of certification the graduates are at risk of taking up a first regular employment.

16 We exclude graduates with a bachelor degree from the analysis because at least in Germany most of them do not immediately enter the labor market, but pursue a Master’s degree. Furthermore, the two groups have very different requirements for entering the labor market and are therefore not comparable. Another reason is that we cannot subsequently observe graduates with a bachelor’s degree in the data when they continue studying for a Master’s degree.

17 Most graduates in human medicine and dentistry complete studies with a professional doctoral degree, and internships of two years after studies are obligatory for teachers and graduates in law.

18 For a complete list of all control variables, definitions and summary statistics, see Tables A 1, A 2 and A3 in the Appendix.

19 For additional information on the German education system, please see Appendix A4.

20 There are 401 NUTS 3 regions in Germany, which consist of urban (‘kreisfreie Städte’) and rural counties (‘Landkreise’).

21 In this study, we refer only to internal migration of higher education graduates after labor market entry in Germany. We cannot observe external migration when graduates take up a job abroad after studies.

22 Our results are in line with findings in Baerts et al. (2021) and the studies discussed in their literature review. However, the authors focus on internships and do not further differentiate the type of work experience as we do. Their overview points to robust evidence on beneficial effects of different types of internships on various labor market outcomes. The considered studies use a wide variety of research designs and quantitative methods, suggesting that the influence of the chosen method on the results is negligible.

23 Unfortunately, we cannot control for work experience that graduates gained abroad because information on employment in other countries is not available in our administrative data. This might introduce a measurement error that will in particular affect work experience of graduates who obtained their university entry certificate abroad. Assuming that our information on work experience is subject to a systematic measurement error the estimated effect of work experience on the probability of entering the labor market will suffer from an attenuation bias. However, we are confident that this measurement problem should not severely affect our regression results because the corresponding group of graduates is rather small and it mainly concerns work experience acquired before enrollment.

24 However, the beneficial influence of previous employers could also point to a human capital effect, i.e. firm-specific knowledge.

25 A test shows that the difference between the estimates for marginal employment during higher education for sector and non-sector specific experience is significant. The results indicate that marginal employment generally exhibits a negative relationship irrespective whether it is sector-specific or not.

26 We have estimated the regression models without graduates in the pharmaceutical field. This does not change the regression results significantly.