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Visualising immigrant fertility: Profiles of childbearing and their implications for migration research

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posted on 2019-09-06, 13:29 authored by Marianne Tønnessen, Ben WilsonBen Wilson
Abstract: The literature on immigrant fertility uses many different measures of fertility, such as the period total fertility rate, cohort completed fertility or measures of parity transitions. Each measure has strengths and limitations, and no single measure captures every aspect of the complex phenomenon of immigrant childbearing. Building upon recent research, this paper introduces a novel visual measure that describes life course profiles of immigrant childbearing in a multifaceted way. It develops the well-known cohort fertility curve – showing the average number of children ever born over the life course – and adds lines for immigrant women arriving at different ages, using their average number of children ever born on arrival as a starting point. These immigrant fertility profiles can illustrate a number of important aspects of childbearing simultaneously, including children born before arrival, fertility after arrival, and completed fertility at the end of childbearing. In addition to showing numbers of children born (i.e. fertility quantum), the slopes of each profile indicate the tempo of fertility and how this changes by age and duration of residence. The fertility profiles of different immigrant groups can be plotted in the same graph, and can be compared and contrasted with non-immigrant groups – at origin as well as destination – through the augmentation of each visualisation. Using Nordic register data, we provide a range of examples that illustrate how these fertility profiles can be used to illuminate our knowledge of immigrant childbearing and to investigate various hypotheses of migrant fertility.

Funding

The Swedish Research Council for Health, Working life and Welfare (FORTE), grant numbers 2016-07105 and 2018-00310

The Swedish Research Council (Vetenskapsrådet) via grant number 2017-01021

The Swedish Initiative for Research on Microdata in the Social and Medical Sciences (SIMSAM), grant number 340-2013-5164

History

ISSN

2002-617X

Publication date

2019-09-06