Heterogeneity in Fertility Intentions for Another Child across Different Groups: A Bayesian Network Analysis Using 3off2 Algorithm
- DOI
- 10.2991/978-94-6463-744-1_22How to use a DOI?
- Keywords
- Fertility groups; subsequent fertility intentions; bayesian network
- Abstract
In contrast to prior studies that primarily rely on logistic regression to independently examine factors influencing fertility intentions, this study introduces a novel Bayesian network analysis approach to explore the complex interplay among multiple factors affecting subsequent fertility decisions. Using data from the 2019 China Social Survey (CSS), we identify distinct patterns of fertility intentions among groups who have already given birth to one child. Our findings reveal that individuals born in the 1980s with higher education and stable em-ployment exhibit the strongest likelihood of having a second child. Notably, for this subgroup, the cost of education exerts minimal influence on fertility inten-tions, while family relationships emerge as a key priority. These insights contrib-ute to a deeper understanding of fertility dynamics in China’s evolving policy landscape and provide actionable recommendations for policymakers.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tian Tian AU - Xinlei Zhou AU - Chunling Luo AU - Juping Shou PY - 2025 DA - 2025/05/28 TI - Heterogeneity in Fertility Intentions for Another Child across Different Groups: A Bayesian Network Analysis Using 3off2 Algorithm BT - Proceedings of the 2025 5th International Conference on Public Management and Intelligent Society (PMIS 2025) PB - Atlantis Press SP - 201 EP - 207 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-744-1_22 DO - 10.2991/978-94-6463-744-1_22 ID - Tian2025 ER -