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Probabilistic projection of subnational total fertility rates

Author

Listed:
  • Hana Sevcikova

    (University of Washington)

  • Adrian E. Raftery

    (University of Washington)

  • Patrick Gerland

    (United Nations Population Division)

Abstract

Background: We consider the problem of probabilistic projection of the total fertility rate (TFR) for subnational regions. Objective: We seek a method that is consistent with the UN’s recently adopted Bayesian method for probabilistic TFR projections for all countries and works well for all countries. Methods: We assess various possible methods using subnational TFR data for 47 countries. Results: We find that the method that performs best in terms of out-of-sample predictive performance and also in terms of reproducing the within-country correlation in TFR is a method that scales each national trajectory from the national predictive posterior distribution by a region-specific scale factor that is allowed to vary slowly over time. Conclusions: Probabilistic projections of TFR for subnational units are best produced by scaling the national projection by a slowly time-varying region-specific scale factor. This supports the hypothesis of Watkins (1990, 1991) that within-country TFR converges over time in response to country-specific factors, and thus extends the Watkins hypothesis to the last 50 years and to a much wider range of countries around the world. Contribution: We have developed a new method for probabilistic projection of subnational TFR that works well and outperforms other methods. This also sheds light on the extent to which within-country TFR converges over time.

Suggested Citation

  • Hana Sevcikova & Adrian E. Raftery & Patrick Gerland, 2018. "Probabilistic projection of subnational total fertility rates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(60), pages 1843-1884.
  • Handle: RePEc:dem:demres:v:38:y:2018:i:60
    DOI: 10.4054/DemRes.2018.38.60
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    References listed on IDEAS

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    Cited by:

    1. Afua Durowaa-Boateng & Dilek Yildiz & Anne Goujon, 2023. "A Bayesian model for the reconstruction of education- and age-specific fertility rates: An application to African and Latin American countries," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(31), pages 809-848.
    2. Ilaria Zambon & Kostas Rontos & Cecilia Reynaud & Luca Salvati, 2020. "Toward an unwanted dividend? Fertility decline and the North–South divide in Italy, 1952–2018," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 169-187, February.
    3. Jesus Rodrigo-Comino & Gianluca Egidi & Luca Salvati & Giovanni Quaranta & Rosanna Salvia & Antonio Gimenez-Morera, 2021. "High-to-Low (Regional) Fertility Transitions in a Peripheral European Country: The Contribution of Exploratory Time Series Analysis," Data, MDPI, vol. 6(2), pages 1-14, February.

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    More about this item

    Keywords

    total fertility rate (TFR); autoregressive model; Bayesian hierarchical model; correlation; subnational projections; scaling model;
    All these keywords.

    JEL classification:

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

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