Probabilistic Estimation and Projection of the Annual Total Fertility Rate Accounting for Past Uncertainty: A Major Update of the bayesTFR R Package

The bayesTFR package for R provides a set of functions to produce probabilistic projections of the total fertility rates for all countries, and is widely used, including as part of the basis for the United Nations official population projections for all countries. Liu and Raftery (2020) extended th...

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Bibliographic Details
Main Authors: Peiran Liu, Hana Ševčíková, Adrian E. Raftery
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2023-03-01
Series:Journal of Statistical Software
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/4235
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Summary:The bayesTFR package for R provides a set of functions to produce probabilistic projections of the total fertility rates for all countries, and is widely used, including as part of the basis for the United Nations official population projections for all countries. Liu and Raftery (2020) extended the theoretical model by adding a layer that accounts for the past total fertility rate estimation uncertainty. A major update of bayesTFR implements the new extension. Moreover, a new feature of producing annual total fertility rate estimation and projections extends the existing functionality of estimating and projecting for five-year time periods. An additional autoregressive component has been developed in order to account for the larger autocorrelation in the annual version of the model. This article summarizes the updated model, describes the basic steps to generate probabilistic estimation and projections under different settings, compares performance, and provides instructions on how to summarize, visualize and diagnose the model results.
ISSN:1548-7660