Education rather than age structure brings demographic dividend
Open accessAbstract
The relationship between population changes and economic growth has been debated since Malthus. Initially focusing on population growth, the notion of demographic dividend has shifted the attention to changes in age structures with an assumed window of opportunity that opens when falling birth rates lead to a relatively higher proportion of the working-age population. This has become the dominant paradigm in the field of population and development, and an advocacy tool for highlighting the benefits of family planning and fertility decline. While this view acknowledges that the dividend can only be realized if associated with investments in human capital, its causal trigger is still seen in exogenous fertility decline. In contrast, unified growth theory has established human capital as a trigger of both demographic transition and economic growth. We assess the relative importance of changing age structure and increasing human capital for economic growth for a panel of 165 countries during the time period of 1980-2015. The results show a clear dominance of improving education over age structure and give evidence that the demographic dividend is driven by human capital. Declining youth dependency ratios even show negative impacts on income growth when combined with low education. Based on a multidimensional understanding of demography that considers education in addition to age, and with a view to the additional effects of education on health and general resilience, we conclude that the true demographic dividend is a human capital dividend. Global population policies should thus focus on strengthening the human resource base for sustainable development.
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Education is tied to a number of beneficial outcomes outside wage earnings, so the PWLFDR taps into a trend of relevance to population health, stability and resilience.
“Furthermore, since education is tied to a number of beneficial outcomes outside wage earnings, the PWLFDR taps into a trend of relevance also much more generally to population health, stability and resilience (Lutz et al., 2019.).”
From Future population ageing and productivity in Finland under different education and fertility scenarios (2022) · cites this paper as Lutz et al., 2019
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- [5]Simon J. L., The Ultimate Resource (Princeton University Press, Princeton, NJ, 1981).
- [6]National Research Council, Population Growth and Economic Development: Policy Questions (National Academy Press, Washington, DC, 1986).
- [8]Coale A. J., Hoover E. M., Population Growth and Economic Development in Low-Income Countries: A Case Study of India’s Prospects (Princeton University Press, Princeton, NJ, 1958).
- [9]Kelley A. C., Schmidt R. M., Saving, dependency and development. J. Popul. Econ. 9, 365– 386 (1996). 12292225
- [12]Lutz W., Cuaresma J. C., Sanderson W., Economics. The demography of educational attainment and economic growth. Science 319, 1047– 1048 (2008). 18292326
- [13]Crespo Cuaresma J., Lutz W., Sanderson W., Is the demographic dividend an education dividend? Demography 51, 299– 315 (2014). 24302530
- [15]Benhabib J., Spiegel M., “Human capital and technology diffusion.” in Handbook of Economic Growth, Agion P., Durlauf S., Eds. (Elsevier, 2005), vol. 1, part A, pp. 935– 966.
- [16]Galor O., Unified Growth Theory (Princeton University Press, Princeton, NJ, 2011).
- [20]Cervellati M., Sunde U., Human capital formation, life expectancy, and the process of development. Am. Econ. Rev. 95, 1653– 1672 (2005). 29125727
- [22]Shryock H. S., Siegel J. S., Eds. The Methods and Materials of Demography (Elsevier Academic, San Diego, CA, ed. 2, 2004).
- [23]Keyfitz N., Applied Mathematical Demography (Springer Verlag, New York, NY, ed. 2, 1985).
- [24]Rogers A., Multiregional Demography: Principles, Methods and Extensions (Wiley, Chichester, UK, 1995).
- [26]Lutz W., Kc S., Global human capital: Integrating education and population. Science 333, 587– 592 (2011). 21798940
- [27]Lutz W., Butz W. P., Samir K. C., Eds. World Population and Human Capital in the Twenty-First Century (Oxford University Press, Oxford, UK, 2014).
- [30]Cuaresma J. C., Will the Sustainable Development Goals be fulfilled? Assessing present and future global poverty. Palgrave Commun. 4, 29 (2018).
- [32]Lutz W., Global sustainable development priorities 500 y after Luther: Sola schola et sanitate. Proc. Natl. Acad. Sci. U.S.A. 114, 6904– 6913 (2017). 28630291 PMC5502620
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Marois, G., Rotkirch, A., & Lutz, W. (2022) · Finnish Yearbook of Population Research · doi:10.23979/fypr.119666 · Cited by 11 · see citing works
“Furthermore, since education is tied to a number of beneficial outcomes outside wage earnings, the PWLFDR taps into a trend of relevance also much more generally to population health, stability and resilience (Lutz et al., 2019.).”
BackgroundSelf-citationShould we be concerned about low fertility? A discussion of six possible arguments
Kravdal, Ø. (2025) · Demographic Research · doi:10.4054/demres.2025.53.14 · Cited by 5 · see citing works
- Authors
- Lutz, W., Crespo Cuaresma, J., Kebede, E., Prskawetz, A., Sanderson, W. C., & Striessnig, E.
- Affiliations
- Vienna University of Economics and Business (AT)
- Wittgenstein Centre for Demography and Global Human Capital (International Institute for Applied Systems Analysis, Vienna Institute of Demography/Austrian Academy of Sciences, Vienna University of Economics and Business Administration), International Institute for Applied Systems Analysis, Laxenburg, Lower Austria 2361, Austria;
- Corresponding author
- Lutz, Wolfgang
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2019-06-10
- Volume
- 116
- Issue
- 26
- Pages
- 12798-12803
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6600906
- OpenAlex
- W2952218646
- Cited by
- 139
- References
- 0
- Citations by year
- 2026: 13 · 2025: 19 · 2024: 25 · 2023: 25 · 2022: 25 · 2021: 19 · 2020: 11 · 2019: 1 · 2014: 1
- FWCI
- 17.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ePubWU Institutional Repository (Wirtschaftsuniversität Wien) (submittedVersion, cc-by)
- IIASA PURE (International Institute of Applied Systems Analysis) (submittedVersion)
- WU Research (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- EC | Horizon 2020 (741105)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Growth and Productivity
- Physical Sciences › Computer Science › Information Systems › Economic Growth and Development
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Economic Development and Digital Transformation
- Keywords
- demographic dividend, human capital, education, age structure, economic growth, fertility decline, youth dependency ratio, population and development, unified growth theory, population policy, working-age population
- MeSH terms
- Age Factors, Demography, Educational Status, Humans, Economic Development
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