Large inequality in international and intranational energy footprints between income groups and across consumption categories


Inequality in energy consumption, both direct and indirect, affects the distribution of benefits that result from energy use. Detailed measures of this inequality are required to ensure an equitable and just energy transition. Here we calculate final energy footprints; that is, the energy embodied in goods and services across income classes in 86 countries, both highly industrialized and developing. We analyse the energy intensity of goods and services used by different income groups, as well as their income elasticity of demand. We find that inequality in the distribution of energy footprints varies across different goods and services. Energy-intensive goods tend to be more elastic, leading to higher energy footprints of high-income individuals. Our results consequently expose large inequality in international energy footprints: the consumption share of the bottom half of the population is less than 20% of final energy footprints, which in turn is less than what the top 5% consume.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Energy footprints versus expenditure.
Fig. 2: Energy footprint inequality versus expenditure inequality for 2011.
Fig. 3: Energy intensity and elasticity spectra.
Fig. 4: Elasticity versus energy intensity.
Fig. 5: International Lorenz curves.
Fig. 6: Business-as-usual trends for household energy footprints.

Data availability

The expenditure data used is available at and The IEA data can be downloaded under institutional license from the UK data service at and The underlying GTAP 9 database can be purchased from The concordance matrices used in the footprint calculations are depicted in the Supplementary Tables 3 and 4. The final energy footprint data per consumption category, nation and income group as well as energy intensities, elasticities and scenario parameters are available from the corresponding author on reasonable request. Source data for Figures 1 to 6 are provided with the paper.

Code availability

MATLAB code for obtaining final energy footprints from the MRIO and calculating elasticities and the Gini coefficient is available at

Change history

  • 30 March 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.


  1. 1.

    Alvaredo, F., Chancel, L., Piketty, T., Saez, E. & Zucman, G. World Inequality Report 2018 (World Inequality Lab, 2018).

  2. 2.

    Reward Work, Not Wealth (Oxfam, 2018).

  3. 3.

    Hubacek, K., Baiocchi, G., Feng, K., Sun, L. & Xue, J. Global carbon inequality. Energy, Ecol. Environ. 2, 361–369 (2017).

    Article  Google Scholar 

  4. 4.

    Krieger, T. & Meierrieks, D. Income inequality, redistribution and domestic terrorism. World Dev. 116, 125–136 (2019).

    Article  Google Scholar 

  5. 5.

    Rockström, J. et al. A roadmap for rapid decarbonization. Science 355, 1269–1271 (2017).

    Article  Google Scholar 

  6. 6.

    Steffen, W. et al. Trajectories of the Earth system in the Anthropocene. Proc. Natl Acad. Sci. USA. 115, 1–45 (2018).

    Article  Google Scholar 

  7. 7.

    Teixidó-Figueras, J. et al. International inequality of environmental pressures: decomposition and comparative analysis. Ecol. Indic. 62, 163–173 (2016).

    Article  Google Scholar 

  8. 8.

    Steinberger, J. K., Krausmann, F. & Eisenmenger, N. Global patterns of materials use: a socioeconomic and geophysical analysis. Ecol. Econ. 69, 1148–1158 (2010).

    Article  Google Scholar 

  9. 9.

    Ivanova, D. et al. Environmental impact assessment of household consumption. J. Ind. Ecol. 20, 526–536 (2015).

  10. 10.

    Galvin, R. & Sunikka-blank, M. Economic inequality and household energy consumption in high-income countries: a challenge for social science based energy research. Ecol. Econ. 153, 78–88 (2018).

    Article  Google Scholar 

  11. 11.

    Creutzig, F. et al. Towards demand-side solutions for mitigating climate change. Nat. Clim. Chang. 8, 268–271 (2018).

    MathSciNet  Article  Google Scholar 

  12. 12.

    Baker, L. Of embodied emissions and inequality: Rethinking energy consumption. Energy Res. Soc. Sci. 36, 52–60 (2018).

    Article  Google Scholar 

  13. 13.

    Grubler, A. et al. A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies. Nat. Energy 3, 515–527 (2018).

    Article  Google Scholar 

  14. 14.

    Shove, E. & Walker, G. What is energy for? Social practice and energy demand. Theory, Cult. Soc. 31, 41–58 (2014).

    Article  Google Scholar 

  15. 15.

    Fell, M. J. Energy services: a conceptual review. Energy Res. Soc. Sci. 27, 129–140 (2017).

    Article  Google Scholar 

  16. 16.

    Shue, H. Subsistence emissions and luxury emissions. Law Policy 15, 39–59 (1993).

    Article  Google Scholar 

  17. 17.

    Access to Electricity (% of Population) (World Bank, 2019);

  18. 18.

    Hubacek, K., Baiocchi, G., Feng, K. & Patwardhan, A. Poverty eradication in a carbon constrained world. Nat. Commun. 8, 912 (2017).

    Article  Google Scholar 

  19. 19.

    Scherer, L. et al. Trade-offs between social and environmental sustainable development goals. Environ. Sci. Policy 90, 65–72 (2018).

    Article  Google Scholar 

  20. 20.

    Lamb, W. F. & Rao, N. D. Human development in a climate-constrained world: what the past says about the future. Glob. Environ. Chang. 33, 14–22 (2015).

    Article  Google Scholar 

  21. 21.

    Rao, N. D. & Min, J. Decent living standards: material prerequisites for human wellbeing. Soc. Indic. Res. 138, 225–244 (2018).

    Article  Google Scholar 

  22. 22.

    Goldemberg, J. Basic needs and much more with one kilowatt per capita. A J. Hum. Environ. 14, 190–200 (1985).

  23. 23.

    Jess, A. What might be the energy demand and energy mix to reconcile the world’s pursuit of welfare and happiness with the necessity to preserve the integrity of the biosphere? Energy Policy 38, 4663–4678 (2010).

    Article  Google Scholar 

  24. 24.

    Chakravarty, S. et al. Sharing global CO2 emission reductions among one billion high emitters. Proc. Natl Acad. Sci. USA 106, 1–5 (2009).

    Article  Google Scholar 

  25. 25.

    Rao, N. D., Min, J. & Mastrucci, A. Energy requirements for decent living in India, Brazil and South Africa. Nat. Energy 4, 1025–1032 (2019).

    Article  Google Scholar 

  26. 26.

    Owen, A., Scott, K. & Barrett, J. Identifying critical supply chains and final products: an input–output approach to exploring the energy–water–food nexus. Appl. Energy 210, 632–642 (2018).

    Article  Google Scholar 

  27. 27.

    Steinberger, J. K., Timmons Roberts, J., Peters, G. P. & Baiocchi, G. Pathways of human development and carbon emissions embodied in trade. Nat. Clim. Chang. 2, 81–85 (2012).

    Article  Google Scholar 

  28. 28.

    Wu, X. D., Guo, J. L., Meng, J. & Chen, G. Q. Energy use by globalized economy: total-consumption-based perspective via multi-region input–output accounting. Sci. Total Environ. 662, 65–76 (2019).

    Article  Google Scholar 

  29. 29.

    Wiedmann, T. O. et al. The material footprint of nations. Proc. Natl Acad. Sci. USA 112, 6271–6276 (2015).

    Article  Google Scholar 

  30. 30.

    Moran, D. Carbon footprints of 13,000 cities. Environ. Res. Lett. 13, 064041 (2018).

    Article  Google Scholar 

  31. 31.

    Peters, G. P., Andrew, R. & Lennox, J. Constructing and environmentally-extended multi-regional input–output table using the GTAP database. Econ. Syst. Res. 23, 131–152 (2011).

    Article  Google Scholar 

  32. 32.

    Global Consumption Database (World Bank, 2018);

  33. 33.

    Consumption Expenditure of Private Households (hbs) (Eursostat, accessed 1 September 2018);

  34. 34.

    Wiedenhofer, D., Lenzen, M. & Steinberger, J. K. Energy requirements of consumption: Urban form, climatic and socio-economic factors, rebounds and their policy implications. Energy Policy 63, 696–707 (2013).

    Article  Google Scholar 

  35. 35.

    Isreal-Akinbo, S. O., Snowball, J. & Gavin, F. An investigation of multidimensional energy poverty among South African low-income households. S. Afr. J. Econ. 86, 468–487 (2018).

    Article  Google Scholar 

  36. 36.

    Narasimha, D. R. & Shonali, P. Energy access and living standards: some observations on recent trends. Environ. Res. Lett. 12, (2017).

  37. 37.

    Brand-Correa, L. I. & Steinberger, J. K. A framework for decoupling human need satisfaction from energy use. Ecol. Econ. 141, 43–52 (2017).

    Article  Google Scholar 

  38. 38.

    Steinberger, J. K. & Roberts, J. T. From constraint to sufficiency: The decoupling of energy and carbon from human needs, 1975-2005. Ecol. Econ. 70, 425–433 (2010).

    Article  Google Scholar 

  39. 39.

    Service, U. D. IEA Energy Balances (accessed 1 October 2018);

  40. 40.

    Davis, S. J. et al. Net-zero emissions energy systems. Science 9793, eaas9793 (2018).

  41. 41.

    Devlin, S. & Bernick, S. Managing Aviation Passenger Demand with a Frequent Flyer Levy (New Economics Foundation, 2015).

  42. 42.

    Shepherd, A. Zero Carbon Britain: Making it Happen. (Centre for Alternative Technology, 2017).

  43. 43.

    Alvaredo, F., Chancel, L., Piketty, T., Saez, E. & Zucman, G. The elephant curve of global inequality and growth. AEA Pap. Proc. 108, 103–108 (2018).

    Article  Google Scholar 

  44. 44.

    Classifications of Expenditure According to Purpose (United Nations, 1999).

  45. 45.

    Milanovic, B. Global income inequality in numbers: in History and Now. Glob. Policy 4, 198–208 (2013).

    Article  Google Scholar 

  46. 46.

    Liberati, P. The world distribution of income and its inequality, 1970–2009. Rev. Income Wealth 64, 248–273 (2015).

  47. 47.

    Lawrence, S., Liu, Q. & Yakovenko, V. M. Global inequality in energy consumption from 1980 to 2010. Entropy 15, 5565–5579 (2013).

    Article  Google Scholar 

  48. 48.

    Duro, J. A. On the automatic application of inequality indexes in the analysis of the international distribution of environmental indicators. Ecol. Econ. 76, 1–7 (2012).

    Article  Google Scholar 

  49. 49.

    Miller, R. E. & Blair, P. D. InputOutput Analysis: Foundations and Extensions 2nd edn (Cambridge University Press, 2009);

  50. 50.

    Dorfman, R. A formula for the Gini coefficient. Rev. Econ. Stat. 61, 146–149 (1979).

    MathSciNet  Article  Google Scholar 

  51. 51.

    Deltas, G. The small-sample bias of the Gini coefficient: results and implications for empirical research. Rev. Econ. Stat. 85, 226–234 (2003).

    Article  Google Scholar 

  52. 52.

    GDP Long-Term Forecast (OECD, accessed 8 October 2019);

  53. 53.

    World Population Prospects 2019 (United Nations, accessed 8 October 2019);

  54. 54.

    GDP (Constant 2010 US$) (World Bank, 2019);

  55. 55.

    Girod, B. & de Haan, P. More or better? A model for changes in household greenhouse gas emissions due to higher income. J. Ind. Ecol. 14, 31–49 (2010).

    Article  Google Scholar 

  56. 56.

    Min, J. & Rao, N. D. Estimating uncertainty in household energy footprints. J. Ind. Ecol. 22, 1307–1317 (2018).

    Article  Google Scholar 

Download references


Y.O. is supported by the Leverhulme Trust’s Research Leadership Award ‘Living Well Within Limits’ (RL2016–048) project awarded to J.K.S. J.K.S was partly supported by an International Academic Fellowship of the Leverhulme Trust (IAF-2018–018). The contributions of A.O. were supported by EPSRC Fellowship award EP/R005052/1. We also would like to thank M. Baltruszewicz, J. Vogel, J. Millward-Hopkins, P. Brockway and L. Hardt for helpful discussions.

Author information




Y.O., J.K.S. and A.O. jointly designed the study, sourced the data, designed the analysis and wrote the paper. Y.O. conducted the analysis.

Corresponding author

Correspondence to Yannick Oswald.

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 Notes 1–15, Tables 1–9, Figs. 1–9 and refs. 1–5.

Source data

Source Data Fig. 1

Energy footprints per capita, expenditure per capita.

Source Data Fig. 2

Gini coefficients of countries in energy and expenditure.

Source Data Fig. 3

Elasticities and energy intensities per country and consumption category.

Source Data Fig. 4

Population-weighted average of elasticities and energy intensities.

Source Data Fig. 5

Cumulative population and cumulative energy resources needed to generate Lorenz curves, Raw consumption-based energy accounts per country and consumption category.

Source Data Fig. 6

Share of aggregated consumption categories in energy over time, Raw consumption-based energy accounts per country and consumption category with additional business as usual forecasts, OECD given and applied growth forecasts.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Oswald, Y., Owen, A. & Steinberger, J.K. Large inequality in international and intranational energy footprints between income groups and across consumption categories. Nat Energy 5, 231–239 (2020).

Download citation

Further reading


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