乌克兰青年移徙:区域层面

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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. 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引用次数: 0

摘要

目的。本研究旨在分析青年移民流动的区域差异,并根据青年移民行为的特点对乌克兰地区进行类型化。因此,本文的研究问题如下:1)在区域层面上,经济指标(收入、失业、投资)与青年移民之间的关系是什么?2)乌克兰各地区在青年移民流动的规模、结构和动态方面有何不同?3)可以确定哪些类型的区域,是否可以考虑这些区域来决定年轻人的迁移意向?研究方法。计算Pearson相关系数以评估青年移民与区域层面经济指标之间的关系。为了防止指标分布歪斜,基辅市被排除在分析之外。为了研究青年移民的区域分异,我们采用聚类分析方法,构建Kohonens自组织图。在分析时空(2002 - 2019年)趋势的基础上,我们还根据年轻人的迁移行为对各区域进行了实证分类。主要发现。城乡青年移民的空间差异分析显示了移民流动的多样性和复杂的多向性。已发现青年移徙与区域一级的失业和投资吸引力有关。青年人从农村地区移徙不仅受到经济因素的影响,而且还受到缺乏高等教育、就业前景和"移徙文化"的影响,这一假设已得到证实。对收入与外迁规模关系的分析显示出一些反u型曲线的迹象。总体而言,研究结果证实,在区域层面,经济指标(失业、投资和收入)影响乌克兰青年移民,但其影响需要在更广泛的地方特定人力资本和生命历程过渡背景下进行研究。基于聚类分析和构建Kohonen自组织地图的结果,确定了乌克兰青年移民相似性的五个区域聚类。通过对2002-2019年青年移民的分析,可以确定其动态的六种模型(单调减少、有减少趋势的突然动态、无变化的突然动态、有增加趋势的突然动态、单调增加、无变化)。根据选择的区域集群和青年迁移动态模型的组合,我们经验地将乌克兰的地区分为三组,这些区域可以被认为是在某种程度上决定年轻人迁移意图的群体。然而,进一步的研究应着眼于分析乌克兰青年迁移行为的个体化和流动迁移。具有科学新颖和实用价值。该研究的主要新颖之处在于其关注乌克兰青年移徙的空间维度,特别是确定与青年移徙有关的移徙流动、因素、趋势和区域问题的区域差异特征。所得结果的实际价值在于,某些类型的地区有可能成为乌克兰各地区移民政策的“指导方针”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Youth migration in Ukraine: regional dimension
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.
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