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As an inevitable result of Russia’s higher education policies of the past two decades, new university leaders in and outside of Moscow and St. Petersburg have emerged, and vertical differentiation has increased. Inequality of educational potential has a strong regional dimension, exerting a considerable delayed impact on regional socioeconomic development. Differences in universities’ resources affected their ability to adapt their instructional, research, and administrative processes to change during the pandemic, thus broadening the education and research quality gap in higher education. Some regions may face an increased outflow of youth talent to leading universities or just any colleges based in Moscow and St. Petersburg, which will certainly weaken the socioeconomic growth prospects of Russia’s regions. The pandemic accelerated the debate over this problem and demonstrated readiness of universities for joint efforts. Groundwork was laid for deploying a policy to create a cooperative network of universities and their stakeholders so as to reduce institutional differentiation and promote exchange of experience and competence among universities. This paper investigates into the main characteristics of vertical differentiation in Russian higher education that had been in place when the pandemic broke out and determined whether universities succeeded or failed in switching to distance learning. Furthermore, lockdown measures and their economic impact on different types of universities are analyzed. Finally, we discuss possible avenues and specific considerations for expanding cross-institutional collaboration and engaging stakeholders inuniversity development.

The population migration has attracted attention for more than a decade. As migration consequences differ in terms of characteristics and directions, governments worldwide are looking for solutions to regulate migration flows. The study aims to systematise push-pull factors of migration by analysing existing cases, as well as to build a model for predicting migration considering the quantitative interpretation of such factors. While migration factors are quite similar regardless of the country of residence, their main differences are compatibility and hierarchy. The most frequently mentioned factors include the expectation of income increase, improvement in the quality of life, professional aspects. Simultaneously, a certain pattern emerges: if a migrant’s material and economic needs are satisfied in the country of departure, they pay more attention to intangible/non-economic benefits (quality of life, infrastructure, etc.). A dynamic forecasting model for scientific migration has been developed based on the theory of positional games. The model demonstrates the changes in migration flows by describing the behaviour of a rational individual who seeks to maximise benefits from migration. The result of the simulation is a short-term forecast of trends in scientific migration of Ural scholars to key migration countries. The model predicts the intensification of migration flows to the leading Asian countries, their alignment with flows to America, and a decrease in migration to European countries. This forecast is characterised by a direct dependence of the dynamics of scientific migration flows on the socio-economic development of migration destinations. Practical implications of this study include the development of a predictive model describing migration flows in the short term as an analytical tool and systematisation of pull-push factors as key indicators for managing the migration flows of scientists. In addition, the research proposes measures positively affecting the balance of scientific migration.

Purpose – The study focuses on the relationship between universities’ publication activity and such indicators of their economic performance as revenues from extrabudgetary sources and revenues from research. Research methodology – The study relies on the economic, structural and scientometric data of 49 large Russian universities in a four-year period obtained from the Monitoring of the Efficiency of Higher Education Institutions and the analytical tool SciVal. The research method is a regression analysis with panel data models. Findings – The study has brought to light some interesting relations between scientometric and economic indicators: among other things, it was shown that higher rates of internationally coauthored publications are positively related with the share of universities’ revenues from extrabudgetary sources. The rates of citation of universities’ publications in journals indexed in major international databases are positively associated with revenues from research. Interestingly, there was a negative relationship between the share of nationally co-authored and the revenue from research. Practical implications – The results can be used for the strategic management of universities and for developing national policies in the sphere of higher education and science. Originality/Value – Apart from the most frequently used scientometric indicators such as the number of publications and citations, the following indicators were also included in the analysis: the share of internationally and nationally co-authored (domestic) publications, the share of publications in economics and management, in physics, arts and humanities.