Estimates and probabilistic projections of total marriage rates and total divorce rates for probabilistic household and living arrangement projections to inform healthy aging and sustainable development in Singapore and Indonesia

Minhui Liu^1†, Yi Sun^1†, Qiushi Feng^1†, Zhenglian Wang^2†, Ying Lu³, Zhuoru Ma³, Wei Tang⁴, Yan Mo¹, Zuqi Cai¹, Evi Nurvidya Arifin⁵, Kenneth Land^6*, Aris Ananta^5,7*, Yi Zeng^3,8*

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¹ Department of Sociology and Centre for Family and Population Research, Faculty of Arts and Social Sciences, National University of Singapore , Singapore

² China Population and Development Research Center, Beijing , China

³ National School of Development, Faculty of Economics and Management, Peking University, Beijing , China

⁴ School of Politics and Public Administration, Southern China Normal University, Guangzhou, Guangdong , China

⁵ Centre for Advanced Research, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei-Muara District , Brunei Darussalam

⁶ Department of Sociology and Population Research Institute, Trinity College of Arts and Sciences, Duke University, Durham, North Carolina , United States of America

⁷ Faculty of Economics and Business, Universitas Indonesia, Depok, West Java , Indonesia

⁸ Geriatrics Division, Center for the Study of Aging and Human Development, School of Medicine, Duke University, Durham, North Carolina , United States of America

†These authors contributed equally to this work.

IJPS, 026190107 https://doi.org/10.36922/IJPS026190107

Received: 8 May 2026 | Revised: 4 August 2026 | Accepted: 5 August 2026 | Published online: 9 September 2026

© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

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Abstract

Household and living arrangement projections are very important for socioeconomic planning and policy-making. In this article, we present time-series estimates of total marriage rates (TMR[t]) and total divorce rates (TDR[t]) for Singapore and Indonesia, using conventionally available demographic datasets. We also present probabilistic projections of TMR(t) and TDR(t) in 2021–2060 for Singapore and Indonesia. In addition to probabilistically projected total fertility rates (TFR[t]) and sex-specific life expectations at birth (e0[s,t]) publicly released by the United Nations Population Division, the probabilistically projected TMR(t) and TDR(t) were used for probabilistic household and living arrangement projections (PHPs) in future years. This is crucial for PHPs using the ProFamy approach, because PHPs largely depend on the projected summary measures TMR(t), TDR(t), TFR(t), and e0(s,t). Finally, we discuss our ongoing research on optimized random combinations of TMR(t), TDR(t), TFR(t), e0(s,t), and other further research needed for PHPs.

Keywords

Total marriage rate

Total divorce rate

Bayesian AR1 model

DemoRates R package

ProFamy probabilistic household and living arrangement projection

Socioeconomic planning

Informed policy-making

Funding

This study was funded by the International Collaborative Research Program of the Ministry of Finance and the Ministry of Foreign Affairs of China, and the Ministry of Education of Singapore (grant number MOE-T2EP40222-0002). The study funders provided financial support for the scientific research but had no role in the writing of the paper, interpretation of the results, and submission for consideration of publication.

Conflict of interest

The authors declare that there are no potential conflicts of financial or non-financial interests relevant to this work.

References

Alkema, L., Raftery, A. E., Gerland, P., Clark, S. J., Pelletier, F., Buettner, T., & Heilig, G. K. (2011). Probabilistic projections of the total fertility rate for all countries. Demography, 48(3), 815–839. https://doi.org/10.1007/s13524-011-0040-5

Bradbury, M., Peterson, M. N., & Liu, J. (2014). Long-term dynamics of household size and their environmental implications. Population and Environment, 36(1), 73–84. https://doi.org/10.1007/s11111-014-0203-6

Dreyer, K., Steventon, A., Fisher, R., & Deeny, S. R. (2018). The association between living alone and health care utilisation in older adults: A retrospective cohort study of electronic health records from a London general practice. BMC Geriatrics, 18, 269. https://doi.org/10.1186/s12877-018-0939-4

Feng, Q., Wang, Z., Gu, D., & Zeng, Y. (2011). Household vehicle consumption forecasts in the United States, 2000 to 2025. International Journal of Market Research, 53(5), 593–618. https://doi.org/10.2501/IJMR-53-5-593-618

Feng, Q., Wang, Z., Tang, W., Mo, Y., Lu, Y., Cai, Z., & Zeng, Y. (2024). Usefulness, illustrative applications and methodology of DemoRates R packages: A user-friendly R program of data preparation for household and living arrangement projections using the ProFamy method/software and for other demographic analyses (Version 3.0) [Software documentation]. http://www.profamy.com.cn/#/download

Gerland, P., Raftery, A. E., Ševčíková, H., Li, N., Gu, D., Spoorenberg, T., Alkema, L., Fosdick, B. K., Chunn, J. L., Lalic, N., Bay, G., Buettner, T., Heilig, G. K., & Wilmoth, J. (2014). World population stabilization unlikely this century. Science, 346(6206), 234–237. https://doi.org/10.1126/science.1257469

Grundy, E. (2001). Living arrangements and the health of older persons in developed countries. In United Nations (Ed.), Living arrangements of older persons: Critical issues and policy responses (Population Bulletin of the United Nations, Special Issue Nos. 42/43, pp. 311–329). United Nations. https://digitallibrary.un.org/record/464936

Gu, D., Feng, Q., Wang, Z., & Zeng, Y. (2015). Recommendation to consider the crucial impacts of changes in smaller household size and its structure on sustainable development goals [Scientific brief]. United Nations Sustainable Development Knowledge Platform. https://sdgs.un.org/documents/brief-gsdr-2015-recommendation-consider-t-20857

Keilman, N. (2003). Biodiversity: The threat of small households. Nature, 421(6922), 489–490. https://doi.org/10.1038/421489a

Li, M., Zhu, S., Wang, Z., Feng, Q., Zhang, J., Chao, F., Tang, W., George, L. K., Grundy, E., Murphy, M., Lutz, M., Dobra, A., Land, K. C., & Zeng, Y. (2025). Optimized random-combinations of total fertility rates and life expectancies at birth for probabilistic population projections. Population Research and Policy Review, 44, 7. https://doi.org/10.1007/s11113-024-09926-y

Mazzuco, S., Meggiolaro, S., Ongaro, F., & Toffolutti, V. (2017). Living arrangement and cognitive decline among older people in Europe. Ageing & Society, 37(6), 1111–1133. https://doi.org/10.1017/S0144686X16000374

Prskawetz, A., Jiang, L., & O’Neill, B. C. (2004). Demographic composition and projections of car use in Austria. Vienna Yearbook of Population Research, 1(2004), 175–202. https://doi.org/10.1553/populationyearbook2004s175

Raftery, A. E., Chunn, J. L., Gerland, P., & Ševčíková, H. (2013). Bayesian probabilistic projections of life expectancy for all countries. Demography, 50(3), 777–801. https://doi.org/10.1007/s13524-012-0193-x

Smith, S. K., Rayer, S., & Smith, E. A. (2008). Aging and disability: Implications for the housing industry and housing policy in the United States. Journal of the American Planning Association, 74(3), 289–306. https://doi.org/10.1080/01944360802197132

Smith, S. K., Rayer, S., Smith, E. A., Wang, Z., & Zeng, Y. (2012). Population aging, disability, and housing accessibility: Implications for sub-national areas in the United States. Housing Studies, 27(2), 252–266. https://doi.org/10.1080/02673037.2012.649468

Wang, Z., Feng, Q., Mo, Y., Tang, W., Lu, Y., Cai, Z., & Zeng, Y. (2026). User guide of DemoRates: A user-friendly R program of data preparation for household and living arrangement projections using the ProFamy extended method/software and for other demographic analyses (Version 3.0) [User manual]. http://www.profamy.com.cn/#/download

Yang, G., & Zhang, L. (2023). Relationship between aging population, birth rate, and disposable income per capita in the context of COVID-19. PLoS ONE, 18(8), e0289781. https://doi.org/10.1371/journal.pone.0289781

Zeng, Y., Chen, H., Wang, Z., & Land, K. C. (2015). Implications of changes in households and living arrangements on future home-based care costs for disabled elders in China. Journal of Aging and Health, 27(3), 519–550. https://doi.org/10.1177/0898264314552690

Zeng, Y., Land, K. C., Gu, D., & Wang, Z. (2014). Household and living arrangement projections: The extended cohort-component method and applications to the U.S. and China. Springer. https://doi.org/10.1007/978-90-481-8906-9

Zeng, Y., Wang, Z., Feng, Q., Gu, D., Zhang, J., Tang, W., & Land, K. (2024). Extend the ProFamy cohort-component method to conduct probabilistic households and living arrangement projections. China Population and Development Studies, 8(4), 378–403. https://doi.org/10.1007/s42379-024-00171-6

Zeng, Y., Yang, H., Wang, Z., & Li, L. (2021). Impacts of family household dynamics on residential energy demands in Hebei Province of China. Genus, 77, 35. https://doi.org/10.1186/s41118-021-00148-0

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