Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

The effect of education on determinants of climate change risks


Increased educational attainment is a sustainable development priority and has been posited to have benefits for other social and environmental issues, including climate change. However, links between education and climate change risks can involve both synergies and trade-offs, and the balance of these effects remains ambiguous. Increases in educational attainment could lead to faster economic growth and therefore higher emissions, more climate change and higher risks. At the same time, improved attainment would be associated with faster fertility decline in many countries, slower population growth and therefore lower emissions, and would also be likely to reduce vulnerability to climate impacts. We employ a multiregion, multisector model of the world economy, driven with country-specific projections of future population by level of education, to test the net effect of education on emissions and on the Human Development Index (HDI), an indicator that correlates with adaptive capacity to climate impacts. We find that improved educational attainment is associated with a modest net increase in emissions but substantial improvement in the HDI values in developing country regions. Avoiding stalled progress in educational attainment and achieving gains at least consistent with historical trends is especially important in reducing future vulnerability.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Population size for three population–education projections based on the SSP2 scenario.
Fig. 2: Percentage of the population living in households by the education level of the household head, in 2000 and in 2050, for three education projections.
Fig. 3: Total carbon emissions from energy use in the SSP2 scenario for three education variants.
Fig. 4: Proportional differences in 2100 in emissions, population, per capita emissions and per capita GDP.
Fig. 5: HDI for all three SSP2 variants over time.

Similar content being viewed by others

Data availability

The samples of census datasets analysed during the current study are publicly available from IPUMS International at The national sample household survey data analysed for this study are publicly available for Brazil (, China (, India (Human Development Survey,, Mexico (, South Africa ( and Uganda (, after registering and submitting requests. The national survey data for some countries are available but restrictions apply to the availability of these data, which were used under licence for the current study and so are not publicly available. These include India (National Sample Survey 2004–2005 and 2011–2012, and Indonesia ( While these original full datasets have restrictions on availability, tables of derived results from the original datasets can be provided upon request.

Code availability

The code for the version of the iPETS model used to produce economic and emissions projections for this analysis is available upon request. It will eventually be publicly available at


  1. Smith, W. C., Anderson, E., Salinas, D., Horvatek, R. & Baker, D. P. A meta-analysis of education effects on chronic disease: the causal dynamics of the population education transition curve. Soc. Sci. Med. 127, 29–40 (2015).

    Article  Google Scholar 

  2. Coady, D. & Dizioli, A. Income inequality and education revisited: persistence, endogeneity and heterogeneity. Appl. Econ. 50, 2747–2761 (2018).

    Article  Google Scholar 

  3. Hanmer, L. & Klugman, J. Exploring women’s agency and empowerment in developing countries: where do we stand? Fem. Econ. 22, 237–263 (2016).

    Article  Google Scholar 

  4. Transforming Our World: The 2030 Agenda for Sustainable Development (United Nations, 2015).

  5. A Guide to SDG Interactions: From Science to Implementation (International Council for Science, 2017).

  6. McCollum, D. L. et al. Connecting the sustainable development goals by their energy inter-linkages. Environ. Res. Lett. 13, 033006 (2018).

    Article  Google Scholar 

  7. Pradhan, P., Costa, L., Rybski, D., Lucht, W. & Kropp, J. P. A systematic study of sustainable development goal (SDG) interactions. Earth’s Future 5, 1169–1179 (2017).

    Article  Google Scholar 

  8. Moyer, J. D. & Bohl, D. K. Alternative pathways to human development: assessing trade-offs and synergies in achieving the Sustainable Development Goals. Futures 105, 199–210 (2019).

    Article  Google Scholar 

  9. Gomez-Echeverri, L. Climate and development: enhancing impact through stronger linkages in the implementation of the Paris Agreement and the Sustainable Development Goals (SDGs). Phil. Trans. R. Soc. A 376, 20160444 (2018).

    Article  Google Scholar 

  10. Oppenheimer, M. et al. in IPCC Climate Change 2014: Impacts, Adaptation and Vulnerability (eds Field, C. B. et al.) 1039–1100 (Cambridge Univ. Press, 2014).

  11. O’Neill, B. C. et al. Global demographic trends and future carbon emissions. Proc. Natl Acad. Sci. USA 107, 17521–17526 (2010).

    Article  Google Scholar 

  12. Crespo Cuaresma, J., Lutz, W. & Sanderson, W. Is the demographic dividend an education dividend? Demography 51, 299–315 (2014).

    Article  Google Scholar 

  13. Lutz, W., Muttarak, R. & Striessnig, E. Universal education is key to enhanced climate adaptation. Science 346, 1061–1062 (2014).

    Article  CAS  Google Scholar 

  14. Gall, M. Indices of Social Vulnerability to Natural Hazards: A Comparative Evaluation (Univ. South Carolina, 2007).

  15. Füssel, H.-M. Review and Quantitative Analysis of Indices of Climate Change Exposure, Adaptive Capacity, Sensitivity, and Impacts (World Bank, 2010);

  16. KC, S. & Lutz, W. The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100. Glob. Environ. Change 42, 181–192 (2017).

    Article  Google Scholar 

  17. O’Neill, B. C. et al. The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

    Article  Google Scholar 

  18. Riahi, K. et al. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  19. Ren, X. et al. Avoided economic impacts of climate change on agriculture: integrating a land surface model (CLM) with a global economic model (iPETS). Clim. Change 146, 517–531 (2018).

    Article  CAS  Google Scholar 

  20. Ren, X., Lu, Y., O'Neill, B. C. & Weitzel, M. Economic and biophysical impacts on agriculture under 1.5 °C and 2 °C warming. Environ. Res. Lett. 13, 115006 (2018).

    Article  CAS  Google Scholar 

  21. Böhringer, C. & Löschel, A. Computable general equilibrium models for sustainability impact assessment: status quo and prospects. Ecol. Econ. 60, 49–64 (2006).

    Article  Google Scholar 

  22. Scrieciu, S. S. The inherent dangers of using computable general equilibrium models as a single integrated modelling framework for sustainability impact assessment. A critical note on Böhringer and Löschel (2006). Ecol. Econ. 60, 678–684 (2007).

    Article  Google Scholar 

  23. Lutz, W. & Skirbekk, V. in World Population & Human Capital in the Twenty-First Century: An Overview (eds Lutz, W. et al.) 14–38 (Oxford Univ. Press, 2014).

  24. IPCC: Summary for Policymakers. In Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

  25. Fuso Nerini, F. et al. Mapping synergies and trade-offs between energy and the sustainable development goals. Nat. Energy 3, 10–15 (2018).

    Article  Google Scholar 

  26. Wiedenhofer, D., Smetschka, B., Akenji, L., Jalas, M. & Haberl, H. Household time use, carbon footprints, and urban form: a review of the potential contributions of everyday living to the 1.5 °C climate target. Curr. Opin. Environ. Sustain. 30, 7–17 (2018).

    Article  Google Scholar 

  27. Duarte, R. et al. Modeling the carbon consequences of pro-environmental consumer behavior. Appl. Energy 184, 1207–1216 (2016).

    Article  CAS  Google Scholar 

  28. Dickson, J. R., Hughes, B. B. & Irfan, M. T. Advancing Global Education (Routledge, 2010).

  29. Burke, M., Davis, W. M. & Diffenbaugh, N. S. Large potential reduction in economic damages under UN mitigation targets. Nature 557, 549–553 (2018).

    Article  Google Scholar 

  30. IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer, L. A.) (IPCC, 2014).

  31. Casey, G. & Galor, O. Is faster economic growth compatible with reductions in carbon emissions? The role of diminished population growth. Environ. Res. Lett. 12, 014003 (2017).

    Article  Google Scholar 

  32. Bongaarts, J. & O’Neill, B. C. Global warming policy: is population left out in the cold? Science 361, 650–652 (2018).

    Article  CAS  Google Scholar 

  33. Jiang, L. & O’Neill, B. C. Global urbanization projections for the shared socioeconomic pathways. Glob. Environ. Change 42, 193–199 (2017).

    Article  Google Scholar 

  34. Dellink, R., Chateau, J., Lanzi, E. & Magné, B. Long-term economic growth projections in the shared socioeconomic pathways. Glob. Environ. Change 42, 200–214 (2017).

    Article  Google Scholar 

  35. Lutz, W. & Kc, S. Global human capital: integrating education and population. Science 333, 587–592 (2011).

    Article  CAS  Google Scholar 

  36. KC, S. et al. Projection of populations by level of educational attainment, age, and sex for 120 countries for 2005–2050. Demogr. Res. 22, 383–472 (2010).

    Article  Google Scholar 

  37. KC, S., Potancokova, M., Bauer, R., Goujon, A. & Striessnig, E. in World Population and Human Capital in the Twenty-First Century (eds Lutz, W. et al.) 434–518 (Oxford Univ. Press, 2014).

  38. Cutler, D. & Lleras-Muney, A. in Encyclopedia of Health Economics (ed. Culyer, A. J.) 232–245 (Elsevier, 2014).

  39. Baker, D. P., Leon, J., Smith Greenaway, E. G., Collins, J. & Movit, M. The education effect on population health: a reassessment. Popul. Dev. Rev. 37, 307–332 (2011).

    Article  Google Scholar 

  40. KC, S. & Lentzner, H. The effect of education on adult mortality and disability: a global perspective. Vienna Yearb. Popul. Res. 8, 201–235 (2010).

    Article  Google Scholar 

  41. Rindfuss, R. R., St. John, C. & Bumpass, L. L. Education and the timing of motherhood: disentangling causation. J. Marriage Fam. 46, 981–984 (1984).

    Article  Google Scholar 

  42. Gerster, M., Ejrnæs, M. & Keiding, N. The causal effect of educational attainment on completed fertility for a cohort of Danish women—does feedback play a role? Stat. Biosci. 6, 204–222 (2014).

    Article  Google Scholar 

  43. Kravdal, Ø. Effects of current education on second- and third-birth rates among Norwegian women and men born in 1964: substantive interpretations and methodological issues. Demogr. Res. 17, 211–246 (2007).

    Article  Google Scholar 

  44. Forced Out: Mandatory Pregnancy Testing and the Expulsion of Pregnant Students in Tanzanian Schools (CRR, 2013);

  45. Bongaarts, J. The causes of educational differences in fertility in Sub-Saharan Africa. Vienna Yearb. Popul. Res. 8, 31–50 (2010).

    Article  Google Scholar 

  46. Clarke, D. Children and their parents: a review of fertility and causality. J. Econ. Surv. 32, 518–540 (2018).

    Article  Google Scholar 

  47. Hoem, J. M. & Kreyenfeld, M. Anticipatory analysis and its alternatives in life-course research. Part 1: the role of education in the study of first childbearing. Demogr. Res. 15, 461–484 (2006).

    Article  Google Scholar 

  48. Calvin, K. et al. The SSP4: a world of deepening inequality. Glob. Environ. Change 42, 284–296 (2017).

    Article  Google Scholar 

  49. Rogelj, J. et al. Scenarios towards limiting global mean temperature increase below 1.5 °C. Nat. Clim. Change 8, 325–332 (2018).

    Article  CAS  Google Scholar 

Download references


We thank the Asian Demographic Research Institute at Shanghai University for hosting research stays for B.C.O. during which parts of this work were carried out. A substantial amount of the work for this study was completed while B.C.O., L.J., E.K.L. and X.R. were at the National Center for Atmospheric Research, Boulder, CO.

Author information

Authors and Affiliations



B.C.O. led, and L.J., S.KC and S.P. contributed to, the design of the study. B.C.O. coordinated the paper and led the writing, with contributions from L.J., S.KC, S.P. and E.K.L. L.J., R.F., S.P. and E.K.L. led the analysis of household survey data, with contributions from T.Z. and W.Z. S.KC carried out the population–education projections. L.J. carried out the household projections. X.R. carried out the iPETS model projections, with contributions from B.C.O. B.C.O., L.J., S.KC, S.P., E.K.L. and X.R. interpreted results.

Corresponding author

Correspondence to Brian C. O’Neill.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Methods 1–3, Tables 1–4, Figs. 1–4 and references.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

O’Neill, B.C., Jiang, L., KC, S. et al. The effect of education on determinants of climate change risks. Nat Sustain 3, 520–528 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing