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Optimal Career Strategies and Brain Drain in Academia


Some areas of science face the problem that many academics prefer the private sector over academia. This negatively affects the quality and the quantity of the research output as well as the availability of competent lecturers in these areas. The present paper investigates by means of an optimal control model how the reward of competencies in research and teaching in the private sector affects investments into these skills as well as the decision on whether and when to optimally leave academia. As the decision between academia and industry is obvious if a scientist has strong preference for either, we focus on scenarios where this is not the case. We notably show that the dynamic trade-off between academia and industry results in various forms of brain drain. In this regard, we first confirm that if academic competencies are well rewarded in the private sector, the most competent academics will leave academia. Further, we find scenarios where a scholar with intermediate competencies will try to improve his or her skills as much as possible before leaving academia and scenarios in which it is optimal to not put much effort into work and let competencies slowly depreciate before leaving. Even if scientists are highly skilled and motivated to stay, if poor working conditions do not support knowledge acquisition, competencies will inevitably fall and academia will consist solely of mediocre scholars. The results suggest that brain drain can be destructive for academia in the long run.

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  1. In the business academic discipline, for instance, doctoral programs give graduates options for professional versatility; see [7].

  2. According to [9], taste for science means a strong preference for freedom to choose research projects, the ability to publish and the desire to conduct basic research.

  3. By “scientist” we actually refer to all kinds of staff doing scientific work including professors, researchers and lecturers. Note that scientists with non-permanent employment contracts might face uncertainty about whether an academic position can be maintained over the course of their career. We assume for simplicity that scientists do not include this uncertainty in their general career planning.

  4. Below we omit time argument \(t\) unless necessary.

  5. Within this paper, we study the case where the scientist can leave the academic sector and join, e.g., a private firm, but switches back are not possible. In general, moving back to academia is possible and leads to interesting questions for further research. However, in this case the second period in the non-academic sector would also have to be modeled with continuous time.

  6. The third and fourth eigenvalues can also be expressed analytically, but they are omitted here because they are not necessary for the proof.

  7. By publication lists, extent of previous teaching activities, rewards, evaluations, etc.

  8. By the term “scientist starts at the dashed (dotted, dashed-dotted) line” we mean that \((x_{10},x_{20})\) lies on the dashed (dotted, dashed-dotted) line.

  9. Here we assume parameters \(b_1\) and \(b_2\) are smaller than the parameters used for the calculations of Fig. 5. For \(b_1=b_2=0.5\), the additional complementary term would simply increase the attractiveness of the private sector such that it would always be optimal to leave.

  10. Parameters \(b_1\) and \(b_2\) are the same as in Fig. 5.


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Correspondence to Gustav Feichtinger.

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This research was supported by the Austrian Science Fund (FWF) under Grants P25979-N25 and P25275-G11.

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Seidl, A., Wrzaczek, S., El Ouardighi, F. et al. Optimal Career Strategies and Brain Drain in Academia. J Optim Theory Appl 168, 268–295 (2016).

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  • Optimal control
  • Academic career
  • History dependence
  • Human capital

Mathematics Subject Classification

  • 49N90
  • 90B70
  • 49N10
  • 91B08