Vocational education, occupational choice and unemployment over the professional career


This study investigates the relationship between occupational choice and unemployment over the professional career with German administrative linked employer–employee data that track more than 800,000 graduates from vocational education over 25 years. Using short-run fluctuations in local and sectoral occupation-specific labor demand as instruments, it finds that choosing an occupation that later turns out to suffer from low or negative employment growth has a statistically and economically significant impact on unemployment over the professional career. On average, an unanticipated one-standard deviation decrease in occupation-specific employment growth raises unemployment by about 116 days over the life cycle.

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  1. 1.

    Because the linked employer–employee data set only includes East German individuals from around 1991 onward, these are excluded from the analysis. All individuals in the sample experienced a recession at about the time they entered the labor market, when the second energy crisis hit West Germany (this happened in 1981/1982, i.e., somewhat later than for instance in the USA).

  2. 2.

    Equation 2.1 assumes that there is a linear relationship between \(\Delta L^{\eta }_{i}\) and lifetime unemployment. An important sensitivity check below shows that this seems to be a good approximation for the relationship between the two variables but that in fact the impact of \(\Delta L^{\eta }_{i}\) on \(u_{i}\) becomes somewhat stronger with increases in \(\Delta L^{\eta }_{i}\).

  3. 3.

    Lange and Neuser (1985) provide an overview of the career counseling services provided by Germany’s Federal Employment Agency in the early 1980s. According to the overview, in the years 1981, 1982 and 1983 about 1,200,000, 1,300,000 and 1,400,000 clients were provided with career counseling in the Agency’s regional offices, respectively. In addition to that, in each of the 3 years the regional offices organized around 90,000 information sessions in secondary schools and more than 20,000 other events.

  4. 4.

    Cf. von Henninges et al. (1976) for details on the impact of the Institute for Employment Research’s analytical and advisory work regarding trends and forecasts of occupation-specific labor demand on the Federal Employment Agency’s career guidance services in the 1970s.

  5. 5.

    For instance, a worker’s Occupational Sector might be manufacturing occupations, his or her Occupational Sub-sector nutritional occupations and his or her Occupational Group baker or confectioner. Cf. Hoffmeyer-Zlotnik and Warner (2014) for details on the German Classification of Occupations.

  6. 6.

    In spite of the Federal Employment Agency’s efforts to provide occupational guidance, prospective trainees in Germany’s vocational education system might potentially form their expectations through different processes, for instance based on past occupation-specific employment growth. In fact, a growing body of literature including Betts (1996), Jensen (2010), Nguyen (2010) and Wiswall and Zafar (2015) documents that students across the globe tend not to be well aware of labor market prospects by occupation or program of study. At the same time, an alternative specification of estimation Eq. 2.5 where unanticipated occupation-specific labor demand shocks are constructed by subtracting from actual occupation-specific employment growth past observed occupation-specific employment growth (over the 5 years prior to trainees’ entry into the vocational education system) shows no statistically significant relationship between this variable and lifetime unemployment. Results from this alternative specification are not depicted here but available upon request.

  7. 7.

    There are also comprehensive schools (Gesamtschulen) and some other less prevalent school types that offer some kind of combination of the three main types of secondary schools.

  8. 8.

    Cf. Hippach-Schneider et al. (2007) and Solga et al. (2014) for more details on the institutional setup of Germany’s vocational education system.

  9. 9.

    Cf. Hunt (1995) for a detailed analysis of the relationship between being registered as unemployed and receiving unemployment benefits in Germany for the first half of this study’s observation period. According to Hunt (1995), between 1983 and 1988 87% of individuals registered as unemployed drew unemployment benefits.

  10. 10.

    Comparable tables for employment growth between 1981 and 2006 as well as between 1982 and 2007 are not depicted here but available upon request. They show very similar patterns.

  11. 11.

    Cf. “Appendix A” for summary statistics for the control variables as well as for details on sample selection and data cleansing.

  12. 12.

    Even two-way clustering might be considered. Unfortunately, to the author’s best knowledge no procedure exists to perform two-way clustering in a Tobit IV regression. Outputs of regressions not reported here but available upon request demonstrate that regular IV regressions that cluster standard errors both on the county and the sector level confirm a statistically significant impact of occupational choice on lifetime unemployment.

  13. 13.

    Following Del Bono and Weber (2008) and Schmillen and Möller (2012), two or more employment spells that last for at least 2 months but for less than 11 months and end at about the same time in consecutive calendar years are defined as a seasonal job.

  14. 14.

    This study’s sample covers 327 counties but only 143 labor market districts.

  15. 15.

    Estimates for a third group, trainees pursuing a career in agricultural or mining occupations, are omitted given the comparatively small size of this group.

  16. 16.

    Cf. Aiyar and Ramcharan (2010) for a discussion of the role of luck in labor markets. An alternative interpretation of this study’s main finding might put less emphasis on the effects of occupational choice at the beginning of the professional career (i.e., a decision) and more on the occurrence of an unanticipated drop in occupation-specific employment growth (i.e., an event). The alternative interpretation emphasizes this study’s connection to research by Oreopoulos et al. (2012) that demonstrates substantial and long-lasting wage losses for some groups of young displaced workers and by Schmillen and Umkehrer (2017) and others according to which early-career unemployment can have long-term scarring effects.


  1. Acemoglu D, Pischke J-S (1996) Why do firms train? Theory and evidence. NBER working paper 5605

  2. Aiyar S, Ramcharan V (2010) What can international cricket teach us about the role of luck in labor markets? IMF working paper 10/225

  3. Angrist J, Imbens G, Rubin D (1996) Identification of causal effects using instrumental variables. J Am Stat Assoc 91:444–455

    Article  Google Scholar 

  4. Bartik T (1991) Who benefits from state and local economic development policies? W.E. Upjohn Institute for Employment Research, Kalamazoo

  5. Betts J (1996) What do students know about wages? Evidence from a survey of undergraduates. J Hum Resour 31:27–56

    Article  Google Scholar 

  6. Blüm A, Frenzel U (1975) Quantitative und qualitative Vorausschau auf den Arbeitsmarkt der Bundesrepublik Deutschland – Stufe 3., IAB, Nürnberg

  7. Bundesinstitut für Berufsbildung (2006) Schaubilder zur Berufsbildung. Bundesinstitut für Berufsbildung, Bonn

  8. Del Bono E, Weber A (2008) Do wages compensate for anticipated working time restrictions? Evidence from seasonal employment in Austria. J Labor Econ 26:181–221

    Article  Google Scholar 

  9. Dorner M, Heining J, Jacobebbinghaus P, Seth S (2010) Sample of integrated labour market biographies (SIAB) 1975–2008. FDZ Datenreport 01/2010

  10. Fitzenberger B, Wilke R (2010) Unemployment durations in West Germany before and after the reform of the unemployment compensation system during the 1980s. German Econ Rev 11:336–366

    Article  Google Scholar 

  11. Fletcher J, Sindelar J (2009) Estimating causal effects of early occupational choice on later health: evidence using the PSID. NBER working paper 15256

  12. Foote C, Ryan R (2015) Labor-market polarization over the business cycle. NBER Macroecon Annu 29:371–413

    Article  Google Scholar 

  13. Gregg P (2001) The impact of youth unemployment on adult unemployment in the NCDS. Econ J 109:626–653

    Article  Google Scholar 

  14. Hanushek E, Schwerdt G, Wößmann L, Zhang L (2016) General education, vocational education, and labor-market outcomes over the life-cycle. J Hum Resour 14:262–280

    Google Scholar 

  15. Heckman J (1993) Assessing Clinton’s program on job training, workfare, and education in the workplace. NBER working paper 4428

  16. Hethey-Maier T, Seth S (2010) The Establishment history panel (BHP) 1975–2008. FDZ Datenreport 04/2010

  17. Hippach-Schneider U, Krause M, Woll C (2007) Vocational education and training in Germany: short description. European Centre for the Development of Vocational Training, Thessaloniki

  18. Hoffmeyer-Zlotnik J, Warner U (2014) Harmonising demographic and socio-economic variables for cross-national comparative survey research. Springer, Berlin

    Book  Google Scholar 

  19. Hunt J (1995) The effect of unemployment compensation on unemployment duration in Germany. J Labor Econ 13:88–120

    Article  Google Scholar 

  20. Jaimovich N, Siu H (2012) The trend is the cycle: job polarization and jobless recoveries. NBER working paper 18334.

  21. Jensen R (2010) The (perceived) returns to education and the demand for schooling. Q J Econ 125:515–548

    Article  Google Scholar 

  22. Kahn L (2010) The long-term labor market consequences of graduating from college in a bad economy. Labour Econ 17:303–316

    Article  Google Scholar 

  23. Kambourov G, Manovskii I (2009) Occupational specificity of human capital. Int Econ Rev 50:63–115

    Article  Google Scholar 

  24. Lange E, Neuser H (1985) Die Berufswahlvorbereitung durch Berufsberatungund Schule: Bestandsaufnahme und Ansätze zur Weiterentwicklung. Mitteilungen aus der Arbeitsmarkt- und Berufsforschung 18:223–246

    Google Scholar 

  25. Ljungqvist L, Sargent T (1998) The European unemployment dilemma. J Polit Econ 106:514–550

    Article  Google Scholar 

  26. Ljungqvist L, Sargent T (2004) European unemployment and turbulence revisited in a matching model. J Eur Econ Assoc 2:456–468

    Article  Google Scholar 

  27. Ljungqvist L, Sargent T (2008) Two questions about European unemployment. Econometrica 76:1–29

    Article  Google Scholar 

  28. Mroz T, Savage T (2006) The long-term effects of youth unemployment. J Hum Resour 41:259–293

    Article  Google Scholar 

  29. Neumark D (2002) Youth labor markets in the United States: shopping around vs. staying put. Rev Econ Stat 84:462–482

    Article  Google Scholar 

  30. Nguyen T (2010) Information, role models and perceived returns to education: experimental evidence from Madagascar. Unpublished paper, MIT

  31. Oreopoulos P, von Wachter T, Heisz A (2012) The short- and long-term career effects of graduating in a recession. Am Econ J Appl Econ 4:1–29

    Article  Google Scholar 

  32. Parnes H (1962) Forecasting educational needs for economic and social development. OECD, Paris

    Google Scholar 

  33. Raaum O, Røed K (2006) Do business cycle conditions at the time of labor market entry affect future employment prospects? Rev Econ Stat 88:193–210

    Article  Google Scholar 

  34. Schmillen A, Möller J (2012) Distribution and determinants of lifetime unemployment. Labour Econ 19:33–47

    Article  Google Scholar 

  35. Schmillen A, Umkehrer M (2017) The scars of youth: effects of early-career unemployment on future unemployment experience. Int Labour Rev 156:465–494

    Article  Google Scholar 

  36. Schneider H, Zimmermann KF (2010) Agenda 2020: strategies to achieve full employment in Germany. IZA policy paper 15

  37. Smith R, Blundell R (1986) An exogeneity test for a simultaneous equation tobit model with an application to labor supply. Econometrica 54:679–685

    Article  Google Scholar 

  38. Solga H, Protsch P, Ebner C, Brzinsky-Fay C (2014) The German vocational education and training system: its institutional configuration, strengths, and challenges. WZB discussion paper 2014–502

  39. Tobin J (1958) Estimation of relationships for limited dependent variables. Econometrica 26:24–36

    Article  Google Scholar 

  40. von Henninges H, Stooß F, Troll L (1976) Berufsforschung im IAB: Versuch einer Standortbestimmung. Mitteilungen aus der Arbeitsmarkt- und Berufsforschung 9:1–18

    Google Scholar 

  41. von Wachter T, Bender S (2006) In the right place at the wrong time: the role of firms and luck in young workers’ careers. Am Econ Rev 96:1679–1705

    Article  Google Scholar 

  42. Wiswall M, Zafar B (2015) Determinants of college major choice: identification using an information experiment. Rev Econ Stud 82:791–824

    Article  Google Scholar 

  43. Wooldridge J (2002) Econometric analysis of cross section and panel data. MIT Press, Cambridge

    Google Scholar 

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I thank Joachim Möller, Philipp vom Berge, David Card, Richard Frensch, Jolien Helsel, Patrick Kline, Nels Lind, Juliane Parys, Jesse Rothstein, Matthias Umkehrer as well as conference and seminar participants in Berkeley, Carlisle, Frankfurt, Nuremberg, Regensburg and Vancouver and two anonymous reviewers for helpful comments and suggestions. Special thanks are due to Heiko Stüber for providing insight and expertise that greatly assisted this research. An early part of this research was conducted while I was visiting the University of California, Berkeley, whose hospitality is gratefully acknowledged. The findings, interpretations and conclusions expressed in this paper are entirely my own. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

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Correspondence to Achim Schmillen.

Appendix A: sample selection, data cleansing and summary statistics

Appendix A: sample selection, data cleansing and summary statistics

As mentioned in Sect. 2, this study focuses on 852,872 individuals that entered the West German labor market in 1981, 1982 or 1983. All of these men and women graduated from Germany’s vocational education system. East Germans are excluded, because their employment history has only been recorded in the IEB data since the early 1990s. Thus, all analyses are based on a group that is fairly homogeneous with regard to experience, training and background.

Table 10 Summary statistics for explanatory variables

While the information contained in the administrative linked employer–employee data set can generally be considered highly reliable, it is not completely free of questionable information. For example, the IEB contain a small number of occupational codes that have been documented as erroneous. In order to ensure valid and undistorted results, all main and control variables including lifetime unemployment and the unanticipated occupation-specific employment growth were carefully checked and implausible data points were replaced with missing values.

Table 10 presents summary statistics for all variables. It shows for instance that women comprise 42% of the sample and that only 3% of sampled individuals held an Abitur upon graduation from vocational education. Concerning the age at graduation from vocational education, 8% of individuals were 17 years old or younger, and 25% were 18 years old, 29% 19 years old, 20% 20 years old and 18% 21 years old or older. Almost half of trainees were in training firms with less than 25 workers (a reflection of the strong role of small- and medium-sized firms in Germany’s vocational education system), 10% in firms with 25–50 workers, 9% in firms with 51–100 workers, another nine percent in firms with 101–250 workers, 7% in firms with 251 to 500 workers, 6% in firms with 501–1000 workers and 10% in firms with 1000 workers or more. The median daily wage of the training firm was euro 41.80.

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Schmillen, A. Vocational education, occupational choice and unemployment over the professional career. Empir Econ 57, 805–838 (2019). https://doi.org/10.1007/s00181-018-1484-x

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  • Occupational choice
  • Unemployment
  • Vocational education

JEL Classification

  • J24
  • J64
  • I21