Optimal scientific production over the life cycle

The paper develops an optimization model of the career of a scientist. Recognizing that research efforts and networking get more efficient if the scientist is more knowledgeable, history dependent solutions are developed. We give a theoretical underpinning of the four different research patterns detected in Way et al. (2017, Proceedings of the National Academy of Sciences). If the scientist does not bother about his reputation at the end of his career, we show that a sufficient education level is needed for the scientist to develop a typical research pattern where productivity increases in the beginning of his career, while it declines towards retirement. If the education level is not sufficient, a fading research pattern will result where productivity declines over time. On the other hand, when the scientist appreciates to have a good reputation at the end of his career, sufficient education will result in increasing productivity over the career lifetime, preventing a midlife slump

On the Matthew effect in research careers: Abnormality on the boundary

The observation that a socioeconomic agent with a high reputation gets a disproportionately higher recognition for the same work than an agent with lower reputation is typical in career development and wealth. This phenomenon, which is known as Matthew effect in the literature, leads to an increasing inequality over time. The present paper employs an optimal control model to study the implications of the Matthew effect on the optimal efforts of a scientist into reputation. The solution of the model exhibits, for suffiently low effort costs, a new type of unstable equilibrium at which effort is at its upper bound. This equilibrium, which we denote as Stalling Equilibrium, serves as a threshold level separating success and failure in academia. In addition we show that at the Stalling Equilibrium the solution can be abnormal. We provide a clear economic interpretation for this solution characteristic

On the Matthew effect in research careers: Abnormality on the boundary

The observation that a socioeconomic agent with a high reputation gets a disproportionately higher recognition for the same work than an agent with lower reputation is typical in career development and wealth. This phenomenon, which is known as Matthew effect in the literature, leads to an increasing inequality over time. The present paper employs an optimal control model to study the implications of the Matthew effect on the optimal efforts of a scientist into reputation. The solution of the model exhibits, for sufficiently low effort costs, a new type of unstable equilibrium at which effort is at its upper bound. This equilibrium, which we denote as Stalling Equilibrium, serves as a threshold level separating success and failure in academia. In addition we show that at the Stalling Equilibrium the solution can be abnormal. We provide a clear economic interpretation for this solution characteristic

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