A flexible model to reconstruct education-specific fertility rates: Sub-saharan Africa case study

<p><strong>A flexible model to reconstruct education-specific fertility rates: Sub-saharan Africa case study</strong></p> <p>The fertility rates are consistent with the United Nation&nbsp;World Population Prospects (UN WPP) 2022 fertility rates.</p> <p>The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a <a href="https://epub.oeaw.ac.at/0xc1aa5576_0x003e65e0.pdf">working paper</a>.&nbsp;</p> <p><strong>Abstract</strong></p> <p>The future world population growth and size will be largely determined by the pace of fertility decline in sub-Saharan Africa. Correct estimates of education-specific fertility rates are crucial for projecting the future population. Yet, consistent cross-country comparable estimates of education-specific fertility for sub-Saharan African countries are still lacking. We propose a flexible Bayesian hierarchical model to reconstruct education-specific fertility rates by using the patchy Demographic and Health Surveys (DHS) data and the United Nations&rsquo; (UN) reliable estimates of total fertility rates (TFR). Our model produces estimates that match the UN TFR to different extents (in other words, estimates of varying levels of&nbsp; consistency with the UN). We present three model specifications: consistent but not identical with the UN, fully-consistent (nearly identical) with the UN, and consistent with the DHS. Further, we provide a full time series of education-specific TFR estimates covering five-year periods between 1980 and 2014 for 36 sub-Saharan African countries. The results show that the DHS-consistent estimates are usually higher than the UN-fully-consistent ones. The differences between the three model estimates vary substantially in size across countries, yielding 1980-2014 fertility trends that differ from each other mostly in level only but in some cases also in direction.</p> <p><strong>Funding</strong></p> <p>The&nbsp;data set&nbsp;are part of the&nbsp;<a href="https://www.oeaw.ac.at/vid/research/research-projects/bayesedu">BayesEdu Project&nbsp;</a>at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the &ldquo;Innovation Fund Research, Science and Society&rdquo; by the Austrian Academy of Sciences (&Ouml;AW).</p> <p>We provide education-specific total fertility rates (ESTFR) from three model specifications: (1) estimated TFR consistent but not identical with the TFR estimated by the UN (&ldquo;Main model (UN-consistent)&rdquo;; (2) estimated TFR fully consistent (nearly identical) with the TFR estimated by the UN (&nbsp;&ldquo;UN-fully -consistent&rdquo;, and (3) estimated TFR consistent only with the TFR estimated by the DHS (&nbsp;&ldquo;DHS-consistent&rdquo;).</p> <p>For education- and age-specific fertility rates that are UN-fully&nbsp;consistent, please see&nbsp;https://doi.org/10.5281/zenodo.8182960</p> <p><strong>Variables</strong></p> <p>Country: Country names</p> <p>Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education.</p> <p>Year: Five-year periods between 1980 and 2015.</p> <p>ESTFR: Median education-specific&nbsp;total fertility rate estimate&nbsp;</p> <p>sd: Standard deviation</p> <p>Upp50: 50% Upper Credible Interval</p> <p>Lwr50: 50% Lower Credible Interval</p> <p>Upp80: 80% Upper Credible Interval</p> <p>Lwr80: 80% Lower Credible Interval</p> <p>Model: Three model specifications as explained above and in the working paper. DHS-consistent,&nbsp;Main model (UN-consistent) and UN-fully consistent.</p> <p>List of countries:</p> <p>Angola,&nbsp;Benin, Burkina Faso,&nbsp;Burundi, Cote D&#39;Ivoire,&nbsp;Cameroon, Central African Republic,&nbsp;Chad, Comoros, Congo,&nbsp;Democratic Republic of Congo,&nbsp;Eswatini,&nbsp;Ethiopia, Gabon,&nbsp;Gambia,&nbsp;Ghana,&nbsp;Guinea,&nbsp;Kenya,&nbsp;Lesotho,&nbsp;Liberia,&nbsp;Madagascar,&nbsp;Malawi,&nbsp;Mali, Mozambique,&nbsp;Namibia,&nbsp;Niger,&nbsp;Nigeria,&nbsp;Rwanda,&nbsp;Senegal, Sierra Leone,&nbsp;South Africa,&nbsp;Tanzania,&nbsp;Togo,&nbsp;Uganda,&nbsp;Zambia,&nbsp;Zimbabwe</p> <p>&nbsp;</p>