Interaction between childbearing and partnership trajectories among immigrants and their descendants in France : an application of multichannel sequence analysis
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While there is a large literature investigating migrant marriage or fertility, little research has examined how childbearing and partnerships are interrelated. In this paper, we investigate how childbearing and partnership trajectories evolve and interact over the life course for immigrants and their descendants and how the relationship varies by migrant origin. We apply multichannel sequence analysis to rich longitudinal survey data from France and find significant differences in family-related behaviour between immigrants, their descendants, and the native French. Immigrants’ family behaviour is characterized by stronger association between marriage and childbearing than in the native population. However, there are significant differences across migrant groups. Turkish immigrants exhibit the most conservative family pathways. By contrast, the family behaviour of European immigrants is similar to that of the native population. The study also demonstrates that the family behaviour of some descendant groups has gradually become indistinguishable from that of the native French, whereas for other groups significant differences in family behaviour persist.
Delaporte , I & Kulu , H 2022 , ' Interaction between childbearing and partnership trajectories among immigrants and their descendants in France : an application of multichannel sequence analysis ' , Population Studies-A Journal of Demography , vol. Latest Articles . https://doi.org/10.1080/00324728.2022.2049856
Population Studies-A Journal of Demography
Copyright © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DescriptionThis project is led by Hill Kulu and funded by the European Research Council under the European Commission’s Horizon 2020 Framework Programme: H2020 Excellent Science (H2020 European Research Council, grant number 834103).
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