Skip to main content

Advertisement

SpringerLink
Log in

Measurement of inequality using household energy consumption data in rural China

  • Article
  • Published:

From Nature Energy

View current issue Submit your manuscript

Abstract

Measuring inequality can be challenging due to the limitations of using household income or expenditure data. Because actual energy consumption can be measured more easily and accurately and is relatively more stable, it may be a better measure of inequality. Here we use data on energy consumption for specific devices from a large nation-wide household survey (n = 3,404 rural households from 12 provinces) to assess inequality in rural China. We find that the overall inequality of energy consumption and expenditure varies greatly in terms of energy type, end-use demand, regions and climatic zones. Biomass, space heating and cooking, intraregional differences, and climatic zones characterized as cold or hot summer/cold winter contribute the most to total inequality for each indicator, respectively. The results suggest that the expansion of infrastructure does not accompany alleviation of energy inequality, and that energy affordability should be improved through income growth and targeted safety-net programmes instead of energy subsidies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: Lorenz curve of energy and household income/expenditure.
Fig. 2: Difference between Lorenz curves.
Fig. 3: Lorenz curve of energy with income on X axis.
Fig. 4: Lorenz curve of energy consumption by energy type and end uses.
Fig. 5: Decomposition of energy consumption-based Gini coefficient by energy sources and end-use activities.
Fig. 6: Lorenz curve by region and climatic zones.
Fig. 7: Decomposition of Gini coefficient by region and climatic zones.

Similar content being viewed by others

References

  1. Xie, Y. & Zhou, X. Income inequality in today’s China. Proc. Natl Acad. Sci. USA 111, 6928–6933 (2014).

    Article  Google Scholar 

  2. Kaiman, J. China gets richer but more unequal. The Guardian (28 July 2014).

  3. Woellert, L. & Chen, S. China’s Income Inequality Surpasses US, Posing Risk for Xi. Bloomberg (28 March 2014).

  4. Kanbur, R. & Zhang, X. Which regional inequality? The evolution of rural–urban and inland–coastal inequality in China from 1983 to 1995. J. Compar. Econ. 27, 686–701 (1999).

    Article  Google Scholar 

  5. Cai, H., Chen, Y. & Zhou, L.-A. Income and consumption inequality in urban China: 1992–2003. Econ. Devel. Cult. Change 58, 385–413 (2010).

    Article  Google Scholar 

  6. Benjamin, D., Brandt, L. & Giles, J. The evolution of income inequality in rural China. Econ. Devel. Cult. Change 53, 769–824 (2005).

    Article  Google Scholar 

  7. Cutler, D. M. & Katz, L. F. Rising inequality? Changes in the distribution of income and consumption in the 1980’s. Amer. Econ. Rev 82, 546–551 (1992).

    Google Scholar 

  8. Hassett, K. A. & Mathur, A. A new measure of consumption inequality. AEI Econ. Stud. 2, (2012) http://www.aei.org/wp-content/uploads/2012/06/-a-new-measure-of-consumption-inequality_142931647663.pdf.

  9. Reform and Innovation for Better Rural Health Services in China (The World Bank, Washington DC, 2015); http://www.worldbank.org/en/results/2015/04/02/reform-innovation-for-better-rural-health-services-in-china.

  10. Li, J. J. & Su, C. How face influences consumption. Int. J. Market Res. 49, 237–256 (2007).

    Google Scholar 

  11. Corneo, G. & Jeanne, O. Conspicuous consumption, snobbism and conformism. J. Public Econ. 66, 55–71 (1997).

    Article  Google Scholar 

  12. Krueger, D. & Perri, F. Does income inequality lead to consumption inequality? Evidence and theory. Rev. Econ. Stud. 73, 163–193 (2006).

    Article  MATH  Google Scholar 

  13. Chen, X. & Nordhaus, W. D. Using luminosity data as a proxy for economic statistics. Proc. Natl Acad. Sci. USA 108, 8589–8594 (2011).

    Article  Google Scholar 

  14. Arora, V. & Lieskovsky, J. Electricity Use as an Indicator of US Economic Activity EIA Working Paper Series (EIA, Washington DC, 2014).

  15. Henderson, J. V., Storeygard, A. & Weil, D. N. Measuring economic growth from outer space. Amer. Econ. Rev. 102, 994–1028 (2012).

    Article  Google Scholar 

  16. Joyeux, R. & Ripple, R. D. Household energy consumption versus income and relative standard of living: A panel approach. Energ. Policy 35, 50–60 (2007).

    Article  Google Scholar 

  17. Aklin, M., Cheng, C.-Y., Urpelainen, J., Ganesan, K. & Jain, A. Factors affecting household satisfaction with electricity supply in rural India. Nat. Energy 1, 16170 (2016).

    Article  Google Scholar 

  18. Jorgenson, A. K., Alekseyko, A. & Giedraitis, V. Energy consumption, human well-being and economic development in central and eastern European nations: A cautionary tale of sustainability. Energ. Policy 66, 419–427 (2014).

    Article  Google Scholar 

  19. Anderson, D. in World Energy Assessment: Energy and the Challenge of Sustainability (eds. United Nations Development Programme) (UNDP, New York, 2000).

  20. Kammen, D. M. & Kirubi, C. Poverty, energy, and resource use in developing countries. Ann. NY Acad. Sci 1136, 348–357 (2008).

    Article  Google Scholar 

  21. China to realize nationwide electricity coverage. State Council (4 August 2015); http://english.gov.cn/state_council/ministries/2015/08/04/content_281475160764026.htm

  22. Fleisher, B., Li, H. & Zhao, M. Q. Human capital, economic growth, and regional inequality in China. J. Dev. Econ 92, 215–231 (2010).

    Article  Google Scholar 

  23. Jacobson, A., Milman, A. D. & Kammen, D. M. Letting the (energy) Gini out of the bottle: Lorenz curves of cumulative electricity consumption and Gini coefficients as metrics of energy distribution and equity. Energ. Policy 33, 1825–1832 (2005).

    Article  Google Scholar 

  24. Han, J., Mol, A. P. & Lu, Y. Solar water heaters in China: a new day dawning. Energ. Policy 38, 383–391 (2010).

    Article  Google Scholar 

  25. Dube, I. Impact of energy subsidies on energy consumption and supply in Zimbabwe. Do the urban poor really benefit? Energ. Policy 31, 1635–1645 (2003).

    Article  Google Scholar 

  26. Kebede, B. Energy subsidies and costs in urban Ethiopia: The cases of kerosene and electricity. Renew. Energ 31, 2140–2151 (2006).

    Article  Google Scholar 

  27. Pitt, M. M. Equity, externalities and energy subsidies The case of kerosine in Indonesia. J. Dev. Econ 17, 201–217 (1985).

    Article  Google Scholar 

  28. Alam, M., Sathaye, J. & Barnes, D. Urban household energy use in India: efficiency and policy implications. Energ. Policy 26, 885–891 (1998).

    Article  Google Scholar 

  29. Soile, I. & Mu, X. Who benefit most from fuel subsidies? Evidence from Nigeria. Energ. Policy 87, 314–324 (2015).

    Article  Google Scholar 

  30. Coady, D., Parry, I. W. H., Sears, L. & Shang, B. How Large Are Global Energy Subsidies? International Monetary Fund Working Paper No. 15/105 42 (IMF, Washington DC, 2015).

  31. Saboohi, Y. An evaluation of the impact of reducing energy subsidies on living expenses of households. Energ. Policy 29, 245–252 (2001).

    Article  Google Scholar 

  32. Larson, D. F., Lampietti, J., Gouel, C. & Cafiero, C. Food security and storage in the Middle East and North Africa. World Bank Econ. Rev 28, 48–73 (2014).

    Article  Google Scholar 

  33. Meyer, B. D., Mok, W. K. C. & Sullivan, J. X. Household surveys in crisis. J. Econ. Perspect. 29, 199–226 (2015).

    Article  Google Scholar 

  34. Zheng, X. et al. Characteristics of residential energy consumption in China: Findings from a household survey. Energ. Policy 75, 126–135 (2014).

    Article  Google Scholar 

  35. Bian, Y. & Li, L. The Chinese general social survey (2003–8). Chinese Sociol. Rev. 45, 70–97 (2012).

    Article  Google Scholar 

  36. Tol, R. S., Downing, T. E., Kuik, O. J. & Smith, J. B. Distributional aspects of climate change impacts. Glob. Environ. Change 14, 259–272 (2004).

    Article  Google Scholar 

  37. Groot, L. Carbon Lorenz curves. Resour. Energy Econ. 32, 45–64 (2010).

    Article  Google Scholar 

  38. Jacmart, M. C., Arditi, M. & Arditi, I. The world distribution of commercial energy consumption. Energ. Policy 7, 199–207 (1979).

    Article  Google Scholar 

  39. Druckman, A. & Jackson, T. Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient. Ecol. Econ. 65, 242–252 (2008).

    Article  Google Scholar 

  40. Damgaard, C. & Weiner, J. Describing inequality in plant size or fecundity. Ecology 81, 1139–1142 (2000).

    Article  Google Scholar 

  41. Shorrocks, A. F. Decomposition procedures for distributional analysis: a unified framework based on the Shapley value. J. Econ. Inequal. 11, 99–126 (2013).

    Article  Google Scholar 

  42. Yang, D. T. Urban-biased policies and rising income inequality in China. Amer. Econ. Rev. 89, 306–310 (1999).

    Article  Google Scholar 

  43. Wei, C., Wu, S. & Zheng, X. Figshare Digital Repository (2017); https://doi.org/10.6084/m9.figshare.5172496.v1

Download references

Acknowledgements

We thank J. Guo, Z.T. Huang, J.Q. Hu and J.S. Fu for their input in survey design and implementation and data collection. We are grateful to J. Tang and W.D. Wang for their technical guidance and Y.C. Liu, R.L. Yang and Y. Zhang for their support to CRECS. Funding for this work was provided by the National Science Foundation of China (Grant no. 71622014, 41771564, 71774165), Ministry of Education of China (Grant nos 14JJD790033, 16YJA790049) and Beijing Natural Science Foundation (Grant no. 9152011).

Author information

Authors and Affiliations

  1. Department of Energy Economics, School of Economics, Renmin University of China, No 59, Zhongguancun Street, Haidian district, Beijing, 100872, China

    Shimei Wu, Xinye Zheng & Chu Wei

Authors
  1. Shimei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xinye Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chu Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to survey design and data collection. S.M.W. conducted the data analysis. X.Y.Z. secured project funding. C.W. drafted the manuscript. S.M.W. and C.W. edited the manuscript.

Corresponding author

Correspondence to Chu Wei.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

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

Electronic supplementary material

Supplementary Information

Supplementary Notes 1–2, Supplementary Figures 1–6, Supplementary Tables 1–2, and Supplementary References

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, S., Zheng, X. & Wei, C. Measurement of inequality using household energy consumption data in rural China. Nat Energy 2, 795–803 (2017). https://doi.org/10.1038/s41560-017-0003-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41560-017-0003-1

  • Springer Nature Limited

This article is cited by

Search

Navigation