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Pré-publication, Document de travail Année : 2022

New methods for measuring the educational gradient of period fertility in Europe. A Bayesian approach based on parity-specific fertility estimates using harmonized survey data

Résumé

This article provides new measures allowing comparing within-country differences in current fertility behavior in Europe. By mobilizing data from the European Union’s Survey of Income and Living Conditions (EU-SILC), we measure the educational gradient of female period fertility for a large set of European countries. A semi-retrospective approach serves to observe fertility behavior of cohorts that are currently at childbearing age, while at the same time recording the educational level correctly. Bayesian statistics allow us to obtain credible intervals for the age, education- and parity specific birth probabilities for each country. These birth probabilities are then combined into a multi-state life table in order to obtain parity-specific and total birth intensities by education. A post-stratification of birth probabilities leads us to be consistent with national fertility estimates, enabling international comparisons for specific groups (e.g. highly educated women) or for particular dimensions of fertility behavior (e.g. childlessness). This analytical set-up allows us to reveal if there are significant differences between education groups in fertility behavior within each European country and in how far these differentials vary between European countries. More precisely, we answer the question if –all birth orders combined– heterogeneity in period fertility behavior is larger among the higher or the lower educated across Europe. In addition, we show for which parity the heterogeneity between education groups is the largest.
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Dates et versions

halshs-03709241, version 1 (05-10-2023)

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Paternité - CC BY 4.0

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Angela Greulich, Laurent Toulemon. New methods for measuring the educational gradient of period fertility in Europe. A Bayesian approach based on parity-specific fertility estimates using harmonized survey data. 2022. ⟨halshs-03709241⟩
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Dernière date de mise à jour le 20/04/2024
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