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March 2024 Bayesian projections of total fertility rate conditional on the United Nations sustainable development goals
Daphne H. Liu, Adrian E. Raftery
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Ann. Appl. Stat. 18(1): 375-403 (March 2024). DOI: 10.1214/23-AOAS1793


Women’s educational attainment and contraceptive prevalence are two mechanisms identified as having an accelerating effect on fertility decline and that can be directly impacted by policy. Quantifying the potential accelerating effect of education and family planning policies on fertility decline in a probabilistic way is of interest to policymakers, particularly in high-fertility countries. We propose a conditional Bayesian hierarchical model for projecting fertility, given education and family planning policy interventions. To illustrate the effect policy changes could have on future fertility, we create probabilistic projections of fertility that condition on scenarios such as achieving the sustainable development goals (SDGs) for universal secondary education and universal access to family planning by 2030.

Funding Statement

This work was supported by NICHD grant R01 HD070936.


The authors would like to thank Leontine Alkema, Vladimíra Kantorová, Peiran Liu, Ema Perković, Hana Ševčíková, Nathan Welch, and Mark Wheldon for their helpful discussion and methodological support. We also thank the referees, Associate Editor, and Editor for their helpful comments.


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Daphne H. Liu. Adrian E. Raftery. "Bayesian projections of total fertility rate conditional on the United Nations sustainable development goals." Ann. Appl. Stat. 18 (1) 375 - 403, March 2024.


Received: 1 April 2022; Revised: 1 March 2023; Published: March 2024
First available in Project Euclid: 31 January 2024

MathSciNet: MR4698612
Digital Object Identifier: 10.1214/23-AOAS1793

Keywords: Bayesian hierarchical model , fertility , sustainable development goals

Rights: Copyright © 2024 Institute of Mathematical Statistics

Vol.18 • No. 1 • March 2024
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