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Age-period-cohort analysis of U.S. fertility: a realistic approach

Author

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  • Francesco Billari

    (Bocconi University
    Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University
    Bocconi Institute for Data Science and Analytics, Bocconi University)

  • Rebecca Graziani

    (Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University
    Bocconi Institute for Data Science and Analytics, Bocconi University
    Department of Decision Sciences)

Abstract

A key question for the explanation of fertility trends in advanced societies is whether, in addition to age, period- rather than cohort-related factors matter. In this paper, we analyze a standard set of age-specific fertility rates – from the Human Fertility Database – on the United States between 1933 and 2015. More specifically, we describe and apply an Age-Period-Cohort (APC) modeling approach that relies on second differences as identifiable parameters. Results of our APC analyses tend to be consistent with an interpretation that gives a greater weight to period effects over shorter time horizons, with a significant presence of smooth cohort effects over the longer term.

Suggested Citation

  • Francesco Billari & Rebecca Graziani, 2024. "Age-period-cohort analysis of U.S. fertility: a realistic approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3021-3040, August.
    • Handle: RePEc:spr:qualqt:v:58:y:2024:i:4:d:10.1007_s11135-023-01787-5
    DOI: 10.1007/s11135-023-01787-5
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    References listed on IDEAS

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    1. D. Kuang & B. Nielsen & J. P. Nielsen, 2008. "Identification of the age-period-cohort model and the extended chain-ladder model," Biometrika, Biometrika Trust, vol. 95(4), pages 979-986.
    2. Mikko Myrskylä & Joshua R. Goldstein & Yen-hsin Alice Cheng, 2013. "New Cohort Fertility Forecasts for the Developed World: Rises, Falls, and Reversals," Population and Development Review, The Population Council, Inc., vol. 39(1), pages 31-56, March.
    3. María Dolores Martínez Miranda & Bent Nielsen & Jens Perch Nielsen, 2015. "Inference and forecasting in the age–period–cohort model with unknown exposure with an application to mesothelioma mortality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 29-55, January.
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