Abstract
Purpose. This study aims to analyze the regional differentiation of youth migration flows and typify the regions of Ukraine according to the characteristics of the migratory behavior of the youth. Accordingly, the research questions are as follows: 1) what is the relationship between economic indicators (income, unemployment, investment) and youth migration at the regional level? 2) how do the regions of Ukraine differ in the scale, structure, and dynamics of youth migration flows? 3) what types of regions can be identified, and can they be considered to determine the young people’s intention to migrate? Research methods. Pearson's correlation coefficients were calculated to assess the relationship between youth migration and economic indicators at the regional level. To prevent skewed indicators distribution, the city of Kyiv was excluded from the analysis. In order to study the regional differentiation of youth migration, we used cluster analysis and constructed Kohonens self-organizing maps. Based on the analysis of spatial and temporal (from 2002 to 2019) trends, we also developed an empirical typification of the regions according to the migration behavior of young people. Main findings. The analysis of spatial differences in youth migration in urban and rural areas shows the diversity and complicated multidirectionality of migration flows. Youth migration has been found to be linked to unemployment and investment attractiveness at the regional level. The assumption that the migration of young people from rural areas is influenced not only by economic factors but also by the lack of prospects for tertiary education, jobs, and the ‘culture of migration’ has been confirmed. The analysis of the relationship between income and out-migration scale shows some signs of a inverse U-shape curve. In general, the results of the study confirmed that at the regional level, economic indicators (unemployment, investment, and income) affect youth migration in Ukraine, but their impact needs to be studied in the broader context of place-specific human capital and life-course transition. Based on the results of cluster analysis and construction of Kohonen self-organizing maps, five clusters of Ukraine’s regions by the similarity of youth migration were identified. The analysis of youth migrations in 2002-2019 allowed to identify six models of their dynamics (monotonically decreasing, abrupt dynamics with a tendency to decrease, abrupt dynamics without changes, abrupt dynamics with a tendency to increase, monotonically increasing, without changes). According to the combination of selected clusters of regions and models of youth migration dynamics, we empirically typified Ukraine’s regions into three groups that can be considered those that, to some extent, determine the young people’s intention to migrate. However, further research should be aimed at analyzing the individualization of migration behavior and liquid migration of Ukrainian youth. Scientific novelty and practical value. The main novelty of the study is its focus on the spatial dimension of youth migration in Ukraine, particularly identifying the features of regional differentiation of migration flows, factors, trends and regional problems associated with youth migration. The practical value of the obtained results lies in the possibility for certain types of regions to become ‘guidelines’ for the migration policy in the regions of Ukraine.
Highlights
The article analyzes the regional differentiation of youth migration flows and develops an empirical typification of the Ukrainian regions according to the special features of youth migration behavior
The study results confirmed that economic indicators affect youth migration in Ukraine at the regional level
Regions of Ukraine differ in scale, structure, and dynamics of youth migration flows
Summary
We used the indicators of youth migration in general, youth migration in urban settlements and rural areas, male and female, external youth migration, as well as economic indicators (average monthly wages, disposable income and expenditure per capita, the employment rate of the entire population and youth employment rate, unemployment rate of the entire population and young people and fixed capital investment per capita) showing individual regions of Ukraine. Pearson's correlation coefficients were calculated to assess the relationship between youth migration and economic indicators The relationship between youth migration and unemployment is moderately inverse (r=-0.66 and r=-0.59 for the whole population and youth unemployment, respectively) It is moderately direct (r=0.63) between migration and fixed capital investment per capita
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