The migratory impact of COVID-19: The role of time and distances in the migration decisions of Hungarians during the COVID-19 pandemic

IF 2.6 2区 社会学 Q1 DEMOGRAPHY
László Zoltán Zöldi, Anna Sára Ligeti, Zoltán Csányi
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Abstract

Despite obvious consequences of pandemics on human mobility, attempts to quantify the migratory impact of COVID-19 remained scarce, largely due to a general lack of data necessary for such assessments. The guiding principle of this paper is that common statistical definitions of migration—linked to usual residences—fail to capture a considerable share of the fast-changing and diverse universe of cross-border movements, which characterized the years of the pandemic. In this study, panels of short- and longer-term movements were created, and hybrid (machine learning-supported) interrupted time series analyses were performed on the basis of pre-pandemic monthly migration flows data to quantify the impact of COVID-19 on international migration. Social insurance data up to 2019 was used to estimate counterfactual emigration and return flows of Hungarians for 2020 and 2021 and compared with actual migration data a posteriori. Beyond the durations of staying abroad, we sought to look at how COVID-related impacts on migration differ by destinations. In accordance with the results, 25% of expected emigrations in cumulative terms had not taken place due to the pandemic if only long-term migrations are considered. This share is 22% when a more flexible conceptualization of geographic mobilities is applied. Behind this relatively small difference, however, there are large variations by destinations. Although similar cumulative impact cannot be detected in case of return migrations, the outbreak of the coronavirus resulted in an unprecedented wave of backwards mobilities, the impact of which however was fading away by the end of the 2-years period.

Abstract Image

COVID-19 的移民影响:时间和距离在 COVID-19 大流行期间匈牙利人移民决定中的作用
尽管大流行病对人类流动性的影响显而易见,但量化 COVID-19 对移民影响的尝试仍然很少,这主要是由于普遍缺乏进行此类评估所需的数据。本文的指导原则是,与常住地挂钩的常见移民统计定义未能捕捉到瞬息万变、多种多样的跨境流动中的相当一部分,而这正是大流行病发生的那几年的特点。在本研究中,我们创建了短期和长期流动的面板,并根据疫情爆发前的月度移民流量数据进行了混合(机器学习支持的)中断时间序列分析,以量化 COVID-19 对国际移民的影响。截至 2019 年的社会保险数据被用来估算 2020 年和 2021 年匈牙利人的反事实移民和回流情况,并与实际移民数据进行后验比较。除了在国外逗留的时间,我们还试图了解 COVID 对移民的影响因目的地而异。结果显示,如果只考虑长期移民,25% 的预期累计移民由于疫情而未能成行。如果采用更灵活的地域流动概念,这一比例则为 22%。然而,在这一相对较小的差异背后,不同目的地之间存在着巨大的差异。虽然在回流移民中无法检测到类似的累积影响,但冠状病毒的爆发导致了前所未有的回流移民潮,但其影响在两年期结束时已逐渐消失。
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来源期刊
CiteScore
5.00
自引率
12.50%
发文量
87
期刊介绍: Population, Space and Place aims to be the leading English-language research journal in the field of geographical population studies. It intends to: - Inform population researchers of the best theoretical and empirical research on topics related to population, space and place - Promote and further enhance the international standing of population research through the exchange of views on what constitutes best research practice - Facilitate debate on issues of policy relevance and encourage the widest possible discussion and dissemination of the applications of research on populations - Review and evaluate the significance of recent research findings and provide an international platform where researchers can discuss the future course of population research
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