Y. Yegorov

University of Vienna (AUSTRIA)
The issue of optimal management of an interaction between changing industrial demand for specialists, changing pattern of research schools and university teaching was rarely addressed in theoretical framework. Here we have three evolving heterogeneities: industrial demand for particular specialists, dynamics of research schools and dynamics of curriculum for university students. Since many university professors are also doing research, there is some correlation between their research topics and those special courses that they can teach. At the same time, some professors work as consultants for industry (see Rentocchini et al, 2013), and this makes information links between universities and industry. However, there are several other important factors to be considered.

The first is related to the skills of students. They are choosing faculty in university taking into account both their initial talents for different sciences and also looking at the expected reward in a certain profession. The second factor is related to the skills in a pool of professors at a certain moment. In a static environment (when there are no temporal changes in the demand for certain professions) an equilibrium mapping of particular talents into faculties can occur. If the markets are efficient, renumeration of certain professions will adjust correspondingly, and students with higher aptitude for a certain profession will select corresponding studies. The list of university courses will correspond to the demand of economy for certain specialists, while professors will evolve towards learning all required topics to be able to teach students.

However, in a real world we have the dynamic change of required professions caused both by industrial innovations and economic changes. Those changes are often unforeseen, and since education requires time, there is at least some time gap between new demand for specialists and their supply. Another factor is related to self-interest of professors for whom it is costly to learn quickly new skills required by industry.

The paper presents several simple models in this field and discusses policy implications. It is shown that even under rational individual decision making the gap between industrial demand for certain skills may differ substantially from university curriculum and that students may not always choose the profession where their aptitudes are the highest.