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GEOGRAPHIC INFORMATION SYSTEM IN MODELING OF EDUCATIONAL MIGRATION: GRAVITY MODEL OF THE UNIVERSITY
Abstract
The Higher Education and universities have high impact for regional development and youth migration. We suggest what the migration of people with a high level of knowledge (called ?brain drain?) is detrimental for the region of emigration. High level universities attract the best students and growth the brain drain. There are close relationships between neighboring regions. Distance can be understood as a barrier of human capital growth. Geographical distance between parental home and college poses a potential barrier to higher education entry, and could be a deciding factor when choosing between institutions. Similar issues potentially arise when considering who goes to which universities, because students with different backgrounds and abilities choose different types and qualities of universities, and the spatial distribution of both university types and student characteristics is not uniform. But at the same time there are the researches which don?t find the impact of distance to accessibility of higher education. The distance a pupil lives from their nearest university has little effect on the likelihood that they go to university. There are many articles describe the social Neighborhood Effects of universities. But the question about geography and place is too often overlooked. The paper of Cullinan and Duggan presents a gravity model of student migration flows to HEIs in Ireland. Their analysis suggests that while geography plays a very important role in explaining student flows. Available studies about student migration cover the territory of England, Ireland, Romania, Poland, US, Canada etc. But we don?t have the works which explain the spatial effect of Russian universities to youth migration. In this article we observe the example of Kazan federal university and her spatial effect to educational migration. The case of Kazan federal university is very important. It?s a one of ten federal university of Russia. More of 30.000 students study in university, 80% of them is from Volga Federal district. The study allowed to find the neighbors of the first and second order, who are influenced by a strong neighbor.
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