пространственная эконометрика,
российские университеты,
молодые преподаватели
Abstract
The aging of university faculty is a crucial problem. We study the issue of attracting young faculty to leading and non-leading Russian universities in 2014–2022. It is the first work where spatial econometric methods use the Russian higher education sector data to account for university interdependence. The study uses three different weight matrices—neighborhood matrix, five nearest neighbors matrix, and inverse distances matrix. An important methodological aspect is the adaptation of matrices built on macrodata (regions) to mesodata (universities). The regression analysis results are robust to the change of spatial matrices. There is a spatial dependence between Russian universities. It is especially noticeable in two separate clusters: leading and non-leading universities; leading universities appear to compete with each other for young faculty. To attract young faculty, Russian universities may increase the remuneration level and decrease the pressure regarding young scholars' publishing activity.
