Linking internal and international migration over the life course: A sequence analysis of individual migration trajectories in Europe

Abstract

Because internal and international migration are typically conceptualized and measured separately, empirical evidence on the links between these two forms of population movement remains partial. This paper takes a step towards integration by establishing how internal and international migration precede one another in various sequenced relationships from birth to age 50 in 20 European countries. We apply sequence and cluster analysis to full retrospective migration histories collected as part of the Survey of Health, Ageing and Retirement in Europe in 2008–09 and 2017, for individuals born between 1950 and 1965. The results show that nearly all international migrants engage in internal mobility at some point in their lives. However, individual migration trajectories are delineated by the order of internal and international moves, the duration and timing of stays abroad, and the extent to which individuals engage in return international migration. Institutional and economic conditions shape the diversity of migration experiences.

Keywords:

• internal migration
• international migration
• immigrants
• Survey of Health, Ageing and Retirement in Europe (SHARE)
• migration histories
• repeat migration
• emigration
• immigration

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Aude Bernard is based in the Queensland Centre for Population Research, School of Earth and Environmental Sciences, The University of Queensland, Australia. Sergi Vidal is based in the Centre d’Estudis Demogràfics (CERCA Center) and the Universitat Autònoma de Barcelona, Spain.

2 Aude Bernard kindly acknowldged funding from the Australian Research Council under its Discovery Scheme (DP200100760).

3 Please direct all correspondence to Aude Bernard, Queensland Centre for Population Research, School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Qld 4062, Australia; or by email: [email protected].

4 Sergi Vidal acknowledges financial support from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101043981) and from the Spanish Ministry of Science and Innovation (I+D+I Generación del Conocimiento; PID2021-125351OB-I00).

5 This paper uses data from SHARE Waves 3 and 7 (10.6103/SHARE.w3.800, 10.6103/SHARE.w7.800); see Börsch-Supan et al. (2013) for methodological details. The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA No. 211909, SHARE-LEAP: GA No. 227822, SHARE M4: GA No. 261982, DASISH: GA No. 283646) and Horizon 2020 (SHARE-DEV3: GA No. 676536, SHARE-COHESION: GA No. 870628, SERISS: GA No. 654221, SSHOC: GA No. 823782, SHARE-COVID19: GA No. 101015924) and also by DG Employment, Social Affairs & Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, RAG052527A), and various national funding sources is gratefully acknowledged (see www.share-project.org).