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BAYESIAN PROJECTIONS OF TOTAL FERTILITY RATE CONDITIONAL ON THE UNITED NATIONS SUSTAINABLE DEVELOPMENT GOALS.

Daphne H Liu1, Adrian E Raftery2

  • 1Department of Statistics, University of Washington.

The Annals of Applied Statistics
|September 30, 2024
PubMed
Summary
This summary is machine-generated.

Policy changes in women

Keywords:
Bayesian hierarchical modelSustainable Development Goalsfertility

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Area of Science:

  • Demography
  • Public Health
  • Policy Analysis

Background:

  • Fertility decline is influenced by women's education and contraceptive use.
  • Policy interventions can accelerate fertility decline.
  • Policymakers need probabilistic quantification of these effects, especially in high-fertility nations.

Purpose of the Study:

  • To develop a probabilistic model for projecting fertility based on education and family planning policies.
  • To quantify the impact of policy interventions on fertility decline.

Main Methods:

  • A conditional Bayesian hierarchical model was developed.
  • Probabilistic fertility projections were created.
  • Scenarios included achieving Sustainable Development Goals (SDGs) for education and family planning.

Main Results:

  • The model provides probabilistic fertility projections under different policy scenarios.
  • Illustrates the potential accelerating effect of policy on fertility decline.

Conclusions:

  • The proposed model can inform policymakers about the impact of education and family planning policies on fertility.
  • Supports evidence-based policy decisions for fertility management.