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Modeling fertility in modern populations

Author

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  • Paraskevi Peristera

    (Athens University of Economics and Business)

  • Anastasia Kostaki

    (Athens University of Economics and Business)

Abstract

The age-specific fertility pattern has a typical shape common in all human populations through years. In order to describe this shape a number of parametric models have been proposed. Recently, the fertility pattern in developed countries exhibits a deviation from the classical one. Recent data sets of United Kingdom, Ireland and US show distortions in terms of a bulge in fertility rates of younger women. Furthermore in countries with distorted fertility, the pattern of first births also exhibits an intense hump in younger ages, stronger than that of the total fertility pattern. This heterogeneity indicated by the recent fertility distributions of European countries and the US might be related to marital status, religion, educational level and differences in social and economic conditions. Additionally in the United States this heterogeneity in fertility patterns might be related to ethnic differences in the timing and the number of births. As expected, the existing models are unable to describe the new shape of the fertility pattern and therefore the use of more appropriate representations is required. In this paper, a new flexible model for describing both the old and the new patterns of fertility is proposed. In order to evaluate the adequacy of the model, we fit it to a variety of empirical fertility schedule.

Suggested Citation

  • Paraskevi Peristera & Anastasia Kostaki, 2007. "Modeling fertility in modern populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 16(6), pages 141-194.
    • Handle: RePEc:dem:demres:v:16:y:2007:i:6
    DOI: 10.4054/DemRes.2007.16.6
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    References listed on IDEAS

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    Cited by:

    1. Marion Burkimsher, 2017. "Evolution of the shape of the fertility curve: Why might some countries develop a bimodal curve?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(11), pages 295-324.
    2. Joshua R. Goldstein, 2010. "A behavioral Gompertz model for cohort fertility schedules in low and moderate fertility populations," MPIDR Working Papers WP-2010-021, Max Planck Institute for Demographic Research, Rostock, Germany.
    3. Ryohei Mogi & Michael Dominic del Mundo, 2020. "Decomposing changes in first birth trends: Quantum, timing, or variance," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 18(1), pages 167-184.
    4. Cristina Rueda-Sabater & Pedro Alvarez-Esteban, 2008. "The analysis of age-specific fertility patterns via logistic models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(9), pages 1053-1070.
    5. Sigurd Dyrting & Andrew Taylor & Tom Wilson, 2024. "Application of P-TOPALS for Smoothing Input Data for Population Projections ‘At the Edge’," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(2), pages 1-28, April.
    6. Joanne Ellison & Erengul Dodd & Jonathan J. Forster, 2020. "Forecasting of cohort fertility under a hierarchical Bayesian approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 829-856, June.
    7. Mogi, Ryohei & del Mundo, Michael, 2018. "Remaining childless or postponing first birth?," SocArXiv hy98w, Center for Open Science.
    8. Jose Maria Fernandez-Crehuet & Luis Alberiko Gil-Alana & Cristina Martí Barco, 2020. "Unemployment and Fertility: A Long Run Relationship," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 1177-1196, December.
    9. Mikko Myrskylä & Joshua R. Goldstein & Yen-hsin Alice Cheng, 2012. "New cohort fertility forecasts for the developed world," MPIDR Working Papers WP-2012-014, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. Hautphenne, Sophie & Massaro, Melanie & Turner, Katharine, 2019. "Fitting Markovian binary trees using global and individual demographic data," Theoretical Population Biology, Elsevier, vol. 128(C), pages 39-50.
    11. Ezra Gayawan & Samson B. Adebayo & Reuben A. Ipinyomi & Benjamin Oyejola, 2010. "Modeling fertility curves in Africa," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(10), pages 211-236.

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    More about this item

    Keywords

    heterogeneity; parametric models; age-specific fertility rate (ASFR); high early-ages fertility; parity-specific fertility; parametric modeling;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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