The efficiency of sustainable development goals 4 and 8 in China: impact of low fertility
DOI: https://doi.org/10.3846/tede.2025.24427Abstract
China’s declining birth rate is gradually eroding the demographic dividend, potentially affecting education, employment, and the economy. This study constructs a meta two-stage dynamic Directional Distance Function (DDF) Data Envelopment Analysis (DEA) model under exogenous variable. It considers the birth rate as an exogenous variable to assess the efficiency of 30 Chinese provinces in achieving SDGs 4 and 8. Key findings include: (1) Integrating the birth rate into the analytical framework has enhanced overall efficiency in most provinces, particularly in the central region. The average efficiency across 30 provinces was 0.8, with minimal regional disparities. (2) The birth rate positively influences both SDG 4 and SDG 8, notably boosting SDG 4 efficiency. (3) Efficiency varies by province: 17 exhibit high efficiency in both SDG 4 and SDG 8, one shows low SDG 4 but high SDG 8 efficiency, two have high SDG 4 but low SDG 8 efficiency, and ten are inefficient in both goals. (4) Hebei, Shandong, and Guangdong have significant redundancy in education and social security investments. Hebei, Henan, and Shanxi show considerable deficiency in economic growth and employment, while Xinjiang and Inner Mongolia require further enhancements in energy efficiency.
First published online 23 September 2025
Keywords:
low fertility, SDG4 efficiency, SDG8 efficiency, meta two-stage dynamic DDF DEA model under exogenous variable, efficiency optimizationHow to Cite
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Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
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References
Avsec, S., & Jagiełło-Kowalczyk, M. (2021). Investigating possibilities of developing self-directed learning in architecture students using design thinking. Sustainability, 13(8), Article 4369. https://doi.org/10.3390/su13084369
Barbier, E. B., & Burgess, J. C. (2020). Sustainability and development after COVID-19. World Development, 135, Article 105082. https://doi.org/10.1016/j.worlddev.2020.105082
Becker, G. S., & Lewis, H. G. (1973). On the interaction between the quantity and quality of children. Journal of Political Economy, 81(2), S279–S288. https://doi.org/10.1086/260166
Becker, G. S., & Tomes, N. (1979). An equilibrium theory of the distribution of income and intergenerational mobility. Journal of Political Economy, 87(6), 1153–1189. https://doi.org/10.1086/260831
Blázquez, M., Herrarte, A., & Moro-Egido, A. I. (2024). Well-being effects of the digital platform economy: The case of temporary and self-employment. Technological and Economic Development of Economy, 30(6), 1618–1651. https://doi.org/10.3846/tede.2024.21858
Bloom, D. E., & Williamson, J. G. (1998). Demographic transitions and economic miracles in emerging Asia. The World Bank Economic Review, 12(3), 419–455. https://doi.org/10.1093/wber/12.3.419
Collste, D., Pedercini, M., & Cornell, S. E. (2017). Policy coherence to achieve the SDGs: Using integrated simulation models to assess effective policies. Sustainability Science, 12, 921–931. https://doi.org/10.1007/s11625-017-0457-x
Crespo Cuaresma, J., Lutz, W., & Sanderson, W. (2014). Is the demographic dividend an education dividend?. Demography, 51(1), 299–315. https://doi.org/10.1007/s13524-013-0245-x
de La Croix, D., & Doepke, M. (2003). Inequality and growth: Why differential fertility matters. American Economic Review, 93(4), 1091–1113. https://doi.org/10.1257/000282803769206214
Do, D. N. M., Hoang, L. K., Le, C. M., & Tran, T. (2020). A human rights-based approach in implementing sustainable development goal 4 (Quality Education) for ethnic minorities in Vietnam. Sustainability, 12(10), Article 4179. https://doi.org/10.3390/su12104179
Ehrenstein, M., Calvo-Serrano, R., Galán-Martín, Á., Pozo, C., Zurano-Cervelló, P., & Guillén-Gosálbez, G. (2020). Operating within Planetary Boundaries without compromising well-being? A data envelopment analysis approach. Journal of Cleaner Production, 270, Article 121833. https://doi.org/10.1016/j.jclepro.2020.121833
Fanti, L., & Gori, L. (2011). Child policy ineffectiveness in an overlapping generations small open economy with human capital accumulation and public education. Economic Modelling, 28(1–2), 404–409. https://doi.org/10.1016/j.econmod.2010.08.008
Färe, R., Grosskopf, S., & Whittaker, G. (2007). Network DEA. In J. Zhu & W. D. Cook (Eds.), Modeling data irregularities and structural complexities in data envelopment analysis (pp. 209–240). Springer. https://doi.org/10.1007/978-0-387-71607-7_12
Ferguson, T., & Roofe, C. G. (2020). SDG 4 in higher education: Challenges and opportunities. International Journal of Sustainability in Higher Education, 21(5), 959–975. https://doi.org/10.1108/IJSHE-12-2019-0353
Ferguson, T., Roofe, C., & Cook, L. D. (2021). Teachers’ perspectives on sustainable development: The implications for education for sustainable development. Environmental Education Research, 27(9), 1343–1359. https://doi.org/10.1080/13504622.2021.1921113
Friedman, J., York, H., Graetz, N., Woyczynski, L., Whisnant, J., Hay, S. I., & Gakidou, E. (2020). Measuring and forecasting progress towards the education-related SDG targets. Nature, 580(7805), 636–639. https://doi.org/10.1038/s41586-020-2198-8
Gregg, N. (2007). Underserved and unprepared: Postsecondary learning disabilities. Learning Disabilities Research & Practice, 22(4), 219–228. https://doi.org/10.1111/j.1540-5826.2007.00250.x
Grotlüschen, A., Nienkemper, B., & Duncker-Euringer, C. (2020). International assessment of low reading proficiency in the adult population: A question of components or lower rungs? International Review of Education, 66, 235–265. https://doi.org/10.1007/s11159-020-09829-y
Hanemann, U. (2019). Examining the application of the lifelong learning principle to the literacy target in the fourth Sustainable Development Goal (SDG 4). International Review of Education, 65, 251–275. https://doi.org/10.1007/s11159-019-09771-8
Haslip, M. J., & Gullo, D. F. (2018). The changing landscape of early childhood education: Implications for policy and practice. Early Childhood Education Journal, 46, 249–264. https://doi.org/10.1007/s10643-017-0865-7
Hu, J. L., & Chang, T. P. (2016). Total-factor energy efficiency and its extensions: Introduction, computation and application. In J. Zhu (Ed.), Data envelopment analysis: A handbook of empirical studies and applications (pp. 45–69). Springer. https://doi.org/10.1007/978-1-4899-7684-0_3
Hu, J.-L., & Wang, S.-C. (2006). Total-factor energy efficiency of regions in China. Energy Policy, 34(17), 3206–3217. https://doi.org/10.1016/j.enpol.2005.06.015
Huan, Y., Liang, T., Li, H., & Zhang, C. (2021). A systematic method for assessing progress of achieving sustainable development goals: A case study of 15 countries. Science of the Total Environment, 752, Article 141875. https://doi.org/10.1016/j.scitotenv.2020.141875
Jędrzychowska, A., Kwiecień, I., Poprawska, E., Cichowicz, E., & Gałecka-Burdziak, E. (2024). How do lifecycle, employment, and childcare support contribute to the gender pension gap in Europe? The clustering methods analysis. Technological and Economic Development of Economy, 30(6), 1862–1889. https://doi.org/10.3846/tede.2024.21887
Kreinin, H., & Aigner, E. (2022). From “Decent work and economic growth” to “Sustainable work and economic degrowth”: A new framework for SDG 8. Empirica, 49, 281–311. https://doi.org/10.1007/s10663-021-09526-5
Kroll, C., Warchold, A., & Pradhan, P. (2019). Sustainable Development Goals (SDGs): Are we successful in turning trade-offs into synergies?. Palgrave Communications, 5, Article 140. https://doi.org/10.1057/s41599-019-0335-5
Łącka, I., & Brzezicki, Ł. (2022). Joint analysis of national eco-efficiency, eco-innovation and SDGS in Europe: DEA approach. Technological and Economic Development of Economy, 28(6), 1739–1767. https://doi.org/10.3846/tede.2022.17702
Lewis, W. A. (1954). Economic development with unlimited supplies of labour. https://la.utexas.edu/users/hcleaver/368/368lewistable.pdf
Li, H., Zhang, J., & Zhu, Y. (2008). The quantity-quality trade-off of children in a developing country: Identification using Chinese twins. Demography, 45(1), 223–243. https://doi.org/10.1353/dem.2008.0006
Lutz, W., Crespo Cuaresma, J., Kebede, E., Prskawetz, A., Sanderson, W. C., & Striessnig, E. (2019). Education rather than age structure brings demographic dividend. Proceedings of the National Academy of Sciences, 116(26), 12798–12803. https://doi.org/10.1073/pnas.1820362116
Markowska, M., & Strahl, D. (2024). COVID-19 impact on labour market in EU countries–differences in men and women employment rate tendencies. Technological and Economic Development of Economy, 30(4), 854–875. https://doi.org/10.3846/tede.2024.20811
Menon, S., & Suresh, M. (2020). Synergizing education, research, campus operations, and community engagements towards sustainability in higher education: A literature review. International Journal of Sustainability in Higher Education, 21(5), 1015–1051. https://doi.org/10.1108/IJSHE-03-2020-0089
Miola, A., & Schiltz, F. (2019). Measuring sustainable development goals performance: How to monitor policy action in the 2030 Agenda implementation?. Ecological Economics, 164, Article 106373. https://doi.org/10.1016/j.ecolecon.2019.106373
Muff, K., Kapalka, A., & Dyllick, T. (2017). The Gap Frame – Translating the SDGs into relevant national grand challenges for strategic business opportunities. The International Journal of Management Education, 15(2), 363–383. https://doi.org/10.1016/j.ijme.2017.03.004
Murray, J. (2021). Informal early childhood education: The influences of parents and home on young children’s learning. International Journal of Early Years Education, 29(2), 117–123. https://doi.org/10.1080/09669760.2021.1928966
National Bureau of Statistics. (2021). Communiqué of the Seventh National Population Census (No. 6). https://www.stats.gov.cn/sj/tjgb/rkpcgb/qgrkpcgb/202302/t20230206_1902006.html
O’Donnell, C. J., Rao, D. S. P., & Battese, G. E. (2008). Metafrontier frameworks for the study of firm-level efficiencies and technology ratios. Empirical Economics, 34, 231–255. https://doi.org/10.1007/s00181-007-0119-4
Omori, T. (2009). Effects of public education and social security on fertility. Journal of Population Economics, 22, 585–601. https://doi.org/10.1007/s00148-009-0244-9
Owens, T. L. (2017). Higher education in the sustainable development goals framework. European Journal of Education, 52(4), 414–420. https://doi.org/10.1111/ejed.12237
Rai, S. M., Brown, B. D., & Ruwanpura, K. N. (2019). SDG 8: Decent work and economic growth – A gendered analysis. World Development, 113, 368–380. https://doi.org/10.1016/j.worlddev.2018.09.006
Ranjbari, M., Shams Esfandabadi, Z. S., Scagnelli, S. D., Siebers, P.-O., & Quatraro, F. (2021). Recovery agenda for sustainable development post COVID-19 at the country level: Developing a fuzzy action priority surface. Environment, Development and Sustainability, 23, 16646–16673. https://doi.org/10.1007/s10668-021-01372-6
Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94(5), 1002–1037. https://doi.org/10.1086/261420
Rosenzweig, M. R., & Zhang, J. (2009). Do population control policies induce more human capital investment? Twins, birth weight and China’s “one-child” policy. The Review of Economic Studies, 76(3), 1149–1174. https://doi.org/10.1111/j.1467-937X.2009.00563.x
Saini, M., Sengupta, E., Singh, M., Singh, H., & Singh, J. (2023). Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a genetic algorithm. Education and Information Technologies, 28, 2031–2069. https://doi.org/10.1007/s10639-022-11265-4
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Tian, P., & Lin, B. (2018). Regional technology gap in energy utilization in China’s light industry sector: Non-parametric meta-frontier and sequential DEA methods. Journal of Cleaner Production, 178, 880–889. https://doi.org/10.1016/j.jclepro.2018.01.017
Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197(1), 243–252. https://doi.org/10.1016/j.ejor.2008.05.027
Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124–131. https://doi.org/10.1016/j.omega.2013.04.002
Xu, Z., Chau, S. N., Chen, X., Zhang, J., Li, Y., Dietz, T., Wang, J., Winkler, J. A., Fan, F., Huang, B., Li, S., Wu, S., Herzberger, A., Tang, Y., Hong, D., Li, J., & Liu, J. (2020). Assessing progress towards sustainable development over space and time. Nature, 577, 74–78. https://doi.org/10.1038/s41586-019-1846-3
Yan, Y., Wang, C., Quan, Y., Wu, G., & Zhao, J. (2018). Urban sustainable development efficiency towards the balance between nature and human well-being: Connotation, measurement, and assessment. Journal of Cleaner Production, 178, 67–75. https://doi.org/10.1016/j.jclepro.2018.01.013
Zuo, Z., Guo, H., Li, Y., & Cheng, J. (2022). A two-stage DEA evaluation of Chinese mining industry technological innovation efficiency and eco-efficiency. Environmental Impact Assessment Review, 94, Article 106762. https://doi.org/10.1016/j.eiar.2022.106762
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