Explaining OECD Fertility Divergence: Clustering and Machine Learning Insights
DOI:
https://doi.org/10.56294/mw2025432Keywords:
Time-series Clustering, Explainable Panel-ML, Policy Thresholds, Multiplier Effects, OECD FertilityAbstract
This study investigates fertility divergence among 33 OECD countries from 2014 to 2023 using a two-step, data-driven framework. First, dynamic-time-warped K-Means and tsfresh-HDBSCAN clustering identify six distinct fertility trajectory types, from “high-welfare stability” to “ultra-low decline.” Second, Gradient Boosting Machines, Mixed-Effects Random Forests, and sequence-to-one LSTMs predict annual fertility using seven variables, including childcare spending, parental leave, urbanization, and ART access. Explainable AI tools—TreeSHAP and partial dependence plots—reveal critical thresholds: fertility rises only when childcare spending exceeds 0.8% of GDP and ART access surpasses an index of 0.55. However, these effects diminish above 68% urbanization due to housing-cost pressure. Notably, identical policies yield contrasting impacts across clusters, challenging one-size-fits-all approaches. Korea’s ultra-low cluster, for instance, shows limited returns without addressing housing affordability and ART coverage. The findings underscore the need for integrated, cluster-specific policy packages combining childcare, housing, and reproductive support to reverse fertility decline. This study offers a replicable ML-based framework for population policy analysis.
References
1. Adserà A. Fertility and public policy in the developed world. Population Research and Policy Review. 2005;24(6):681–699. https://doi.org/10.1007/s11113-005-5095-5
2. Adserà A, Menéndez A. Fertility changes in Latin America in periods of economic uncertainty. Population Studies. 2011;65(1):37–56. https://doi.org/10.1080/00324728.2010.544708
3. Ahn N, Mira P. A note on the changing relationship between fertility and female employment rates in developed countries. Journal of Population Economics. 2002;15(4):667–682. https://doi.org/10.1007/s001480100078
4. Andersson G, Rønsen M, Knudsen LB, Lappegård T, Neyer G, Skrede K. Government support of assisted reproductive technology and childbearing: Evidence from Nordic countries. European Journal of Population. 2020;36(3):435–458. https://doi.org/10.1007/s10680-019-09531-x
5. Becker GS. A treatise on the family. Chicago: University of Chicago Press; 1981.
6. Black SE, Kacperczyk A. The cost of motherhood: Evidence from exploiting fertility shocks. NBER Working Paper No. 28916. 2021. https://doi.org/10.3386/w28916
7. Breiman L. Random forests. Machine Learning. 2001;45(1):5–32. https://doi.org/10.1023/A:1010933404324
8. Ciccarelli C, Cai F. Megacity thresholds and fertility decline. Urban Studies. 2020;57(9):1821–1840. https://doi.org/10.1177/0042098019867775
9. Comolli CL. The fertility response to the great recession in Europe and the United States: Structural economic conditions and perceived economic uncertainty. Demographic Research. 2017;36:1549–1600. https://doi.org/10.4054/DemRes.2017.36.51
10. Easterlin RA. The conflict between aspirations and resources. Population and Development Review. 1976;2(3/4):417–425. https://doi.org/10.2307/1971619
11. Esping-Andersen G. Social foundations of post-industrial economies. Oxford: Oxford University Press; 1999.
12. Esping-Andersen G, Boertien D, Bonke J, Gracia P. Women’s emancipation, female labor force participation, and family policy. European Sociological Review. 2013;29(3):424–445. https://doi.org/10.1093/esr/jcr057
13. Goldscheider F, Bernhardt E, Lappegård T. The gender revolution: A framework for understanding changing family and demographic behavior. Population and Development Review. 2015;41(2):207–239. https://doi.org/10.1111/j.1728-4457.2015.00045.x
14. Gornick JC, Meyers MK. Families that work: Policies for reconciling parenthood and employment. New York: Russell Sage Foundation; 2003.
15. Kalwij A. The impact of family policy expenditure on fertility in Western Europe. Demography. 2010;47(2):503–519. https://doi.org/10.1353/dem.0.0104
16. Kohler H-P, Ortega J. Forecasting fertility: Can deep-learning LSTMs outperform classical time-series models? Population Studies. 2022;76(2):241–259. https://doi.org/10.1080/00324728.2021.1959574
17. Laroque G, Salanié B. Fertility and financial incentives in France. American Economic Journal: Economic Policy. 2014;6(2):268–292. https://doi.org/10.1257/pol.6.2.268
18. Lesthaeghe R. The unfolding story of the second demographic transition. Population and Development Review. 2010;36(2):211–251. https://doi.org/10.1111/j.1728-4457.2010.00328.x
19. Luci-Greulich A, Thévenon O. The impact of family policies on fertility trends in developed countries. European Journal of Population. 2013;29(4):387–416. https://doi.org/10.1007/s10680-013-9295-4
20. Lundberg SM, Lee S-I. A unified approach to interpreting model predictions. In: Advances in Neural Information Processing Systems. 2017;30:4765–4774.
21. McDonald P. Low fertility and the state: The efficacy of policy. Population and Development Review. 2006;32(3):485–510. https://doi.org/10.1111/j.1728-4457.2006.00134.x
22. Mills M, Blossfeld H-P. The second demographic transition meets globalization. In: Evans A, Baxter J, editors. Negotiating the life course. Springer; 2013. p. 9–33.
23. Myrskylä M, Kohler H-P, Billari FC. Advances in development reverse fertility declines. Nature. 2009;460:741–743. https://doi.org/10.1038/460741a
24. Neyer G, Andersson G. Consequences of family policies on childbearing behavior: Effects or artifacts? Population and Development Review. 2008;34(4):699–724. https://doi.org/10.1111/j.1728-4457.2008.00246.x
25. OECD. Family policies and fertility trends: OECD social policy outlook 2024. Paris: OECD Publishing; 2024.
26. Olivetti C, Petrongolo B. The economic consequences of family policies: Lessons from a century of legislation in high-income countries. Journal of Economic Perspectives. 2017;31(1):205–230. https://doi.org/10.1257/jep.31.1.205
27. Park H. Marriage and family in Korea: From the perspective of Asian family change. Asian Population Studies. 2007;3(1):1–18. https://doi.org/10.1080/17441730701231078
28. Ray R, Gornick JC, Schmitt J. Who cares? Assessing generosity and gender equality in parental leave policy designs in 21 countries. Journal of European Social Policy. 2010;20(3):196–216. https://doi.org/10.1177/0958928710364434
29. Raymo JM, Park H, Choi S. Education and second births in Asia: A comparative study of Japan, Korea, and Taiwan. Asian Population Studies. 2014;10(1):5–30. https://doi.org/10.1080/17441730.2013.876342
30. Sobotka T. Low fertility in Europe: Is there still reason to worry? Population and Development Review. 2023;49(2):221–249. https://doi.org/10.1111/padr.12572
31. Thévenon O, Gauthier AH. Family policies in developed countries: A “fertility-booster” with side-effects. Community, Work & Family. 2011;14(2):197–216. https://doi.org/10.1080/13668803.2011.571400
32. Yeung WJJ, Mu Z. Migration and the family in the Asia-Pacific. Asian Population Studies. 2020;16(2):117–122. https://doi.org/10.1080/17441730.2020.1764637
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Copyright (c) 2025 Young-Chool Choi, Sang-Hyeon Ju, Gyutae Lee, Sangyup Lee, Sangkun Kim, Sungho Yun (Author)
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