2015
DOI: 10.4054/demres.2015.32.33
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Smoothing internal migration age profiles for comparative research

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Cited by 28 publications
(19 citation statements)
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References 34 publications
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“…Building on an inventory of migration data collections for 193 UN member states (Bell et al, ), an international team of researchers has assembled internal migration data covering 135 countries (Bell et al, ) and built a bespoke software platform, the IMAGE Studio, to compute multiple migration indicators using flexible geographies (Daras, ; Stillwell et al, ). Papers have explored methodological issues (Bell et al, ) and made cross‐national comparisons of overall internal migration intensities (Bell et al, , ) and migration age profiles (Bernard et al, , ; Bernard & Bell, ), globally as well as for selected regions and group of countries (Bell et al, ; Charles‐Edwards et al, ).…”
Section: Introductionmentioning
confidence: 99%
“…Building on an inventory of migration data collections for 193 UN member states (Bell et al, ), an international team of researchers has assembled internal migration data covering 135 countries (Bell et al, ) and built a bespoke software platform, the IMAGE Studio, to compute multiple migration indicators using flexible geographies (Daras, ; Stillwell et al, ). Papers have explored methodological issues (Bell et al, ) and made cross‐national comparisons of overall internal migration intensities (Bell et al, , ) and migration age profiles (Bernard et al, , ; Bernard & Bell, ), globally as well as for selected regions and group of countries (Bell et al, ; Charles‐Edwards et al, ).…”
Section: Introductionmentioning
confidence: 99%
“…Bernard et al (2014b) demonstrate that age and intensity at the peak are the optimum measures to capture cross-national differences in the age profile of migration, since these measures encompass both the breadth and symmetry of the peak among young adults. They also demonstrate (Bernard and Bell, 2015) that considerable care is needed in the choice of technique for data smoothing, since conventional model migration schedules may obscure subtle but important shifts over time in the age at which peak migration occurs. It follows that careful attention to the choice and computation of migration indicators is needed if shifts over time in the overall level of migration within a country, and their underlying causes, are to be properly understood.…”
Section: Selecting Robust Migration Indicatorsmentioning
confidence: 98%
“…Following existing approaches to forecasting cohort fertility (Chen, ; Goldstein, ), we extrapolate age‐specific migration rates into the future to allow cohorts to complete their migration career. To that end, we use Gaussian kernel regression to (a) smooth observed single‐year age‐specific migration rates (Bernard & Bell, ) and (b) impute migration rates to age 60 for cohorts born between 1955 and 1964, to age 52 for the 1965–1969 cohort, and to age 47 for the 1970–1974 cohort. These ages represent the maximum number of missing values that can be reliably imputed using kernel regression.…”
Section: What Is the Future Of Migration In China?mentioning
confidence: 99%