Optimized Random-Combinations of Total Fertility Rates and Life Expectancies at Birth for Probabilistic Population Projections

Man Li, Shanwen Zhu, Zhenglian Wang, Qiushi Feng, Junni Zhang, Fengqing Chao, Wei Tang, Linda George, Emily Grundy, Michael Murphy, Michael Lutz, Adrian Dobra, Kenneth Land () and Yi Zeng ()
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Man Li: Soochow University
Shanwen Zhu: Shanghai Institute of Technology
Zhenglian Wang: China Population and Development Research Center
Qiushi Feng: National University of Singapore
Junni Zhang: National School of Development, Peking University
Fengqing Chao: Chinese University of Hongkong
Wei Tang: National School of Development, Peking University
Linda George: Duke University
Emily Grundy: University of Essex
Michael Murphy: London School of Economics and Political Science
Michael Lutz: Duke University School of Medicine
Adrian Dobra: University of Washington
Kenneth Land: Duke University
Yi Zeng: National School of Development, Peking University

Population Research and Policy Review, 2025, vol. 44, issue 1, No 7, 22 pages

Abstract: Abstract Many studies indicate that Total fertility rates (TFR(t)) are negatively correlated with life expectancies at birth (e0(t)). We found that complete random-combinations of TFR(t) and e0(t) would result in about 24% and 22.2% of improbable combinations in probabilistic population projections (PPPs) for developing and developed countries, respectively, namely, high (or low) TFR(t) combined with high (or low) female e0(t). Thus, we propose optimized random-combinations of probabilistically projected TFR(t) and e0(t) for PPPs, and we use different strategies of the optimized randomcombinations across developing and developed countries due to different empirical patterns observed. As illustrative applications, we conducted PPPs for 11 developing countries (Brazil, China, Indonesia, Madagascar, Pakistan, Philippines, Saudi Arabia, Singapore, Sri Lanka, Thailand, Viet Nam), and 6 developed countries (Canada, France, Italy, Japan, the United Kingdom, the United States), using our proposed optimized random-combinations of probabilistically projected TFR(t) and e0(t). We found that optimized random-combinations largely reduce percentages of improbable combinations of TFR(t) and e0(t) and substantially narrow the prediction intervals width compared to complete random-combinations in both developing countries and developed countries. This is important in a real-world practical sense since it would substantially improve the accuracy of PPPs, which are useful for socioeconomic planning. The present study is part of our ongoing research program on probabilistic households and living arrangement projections (PHPs) that builds upon and is consistent with the UNPD PPPs. The PHPs are useful for various studies of healthy aging and sustainable development.

Keywords: Probabilistic population projections; Probabilistic households and living arrangement projections; Correlations between total fertility rates and life expectations at birth; Optimized random-combinations; Complete random-combinations (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11113-024-09926-y

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