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Modeling fertility curves in Africa

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Author Info

  • Ezra Gayawan

    (Redeemer’s University, Redemption City, Nigeria)

  • Samson Adebayo

    (Society for Family Health, Abuja)

  • Reuben A. Ipinyomi

    (University of Ilorin)

  • Benjamin Oyejola

    (University of Ilorin)

Registered author(s):

    Abstract

    The modeling of fertility patterns is an essential method researchers use to understand world-wide population patterns. Various types of fertility models have been reported in the literature to capture the patterns specific to developed countries. While much effort has been put into reducing fertility rates in Africa, models which describe the fertility patterns have not been adequately described. This article presents a flexible parametric model that can adequately capture the varying patterns of the age-specific fertility curves of African countries. The model has parameters that are interpretable in terms of demographic indices. The performance of this model was compared with other commonly used models and Akaike’s Information Criterion was used for selecting the model with best fit. The presented model was able to reproduce the empirical fertility data of 11 out of 15 countries better than the other models considered.

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    File URL: http://www.demographic-research.org/volumes/vol22/10/22-10.pdf
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    Bibliographic Info

    Article provided by Max Planck Institute for Demographic Research, Rostock, Germany in its journal Demographic Research.

    Volume (Year): 22 (2010)
    Issue (Month): 10 (February)
    Pages: 211-236

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    Handle: RePEc:dem:demres:v:22:y:2010:i:10

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    Web page: http://www.demogr.mpg.de/

    Related research

    Keywords: African countries; age-specific fertility rates; Akaikes Information Criterion; complementary error function; cubic/quadratic spline; polynomial model;

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    References

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    1. Carl Schmertmann, 2005. "Quadratic spline fits by nonlinear least squares," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 12(5), pages 105-106, March.
    2. Anastasia Kostaki & Paraskevi Peristera, 2007. "Modeling fertility in modern populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 16(6), pages 141-194, March.
    3. Carl Schmertmann, 2003. "A system of model fertility schedules with graphically intuitive parameters," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 9(5), pages 81-110, October.
    4. Koehler, Anne B. & Murphree, Emily S., 1988. "A comparison of results from state space forecasting with forecasts from the Makridakis Competition," International Journal of Forecasting, Elsevier, vol. 4(1), pages 45-55.
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    Cited by:
    1. Ezra Gayawan & Samson B. Adebayo, 2013. "A Bayesian semiparametric multilevel survival modelling of age at first birth in Nigeria," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(45), pages 1339-1372, June.

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