Volume 38 - Article 60 | Pages 1843–1884
Probabilistic projection of subnational total fertility rates
|Date received:||09 Mar 2017|
|Date published:||08 Jun 2018|
|Keywords:||autoregressive model, Bayesian hierarchical model, correlation, scaling model, subnational projections, total fertility rate (TFR)|
|Additional files:||readme.38-60 (text file, 727 Byte)|
|38-60_supplementary materials (pdf file, 11 MB)|
|demographic-research.38-60 (zip file, 108 kB)|
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.
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