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The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

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  • Yanan Liu

    (School of Management and Economics, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Center for Energy and Environmental Policy Research, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China)

  • Yixuan Gao

    (School of Management and Economics, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Center for Energy and Environmental Policy Research, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Department of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA)

  • Yu Hao

    (School of Management and Economics, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Center for Energy and Environmental Policy Research, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China)

  • Hua Liao

    (School of Management and Economics, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Center for Energy and Environmental Policy Research, Beijing Institute of Technology, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
    Collaborative Innovation Center of Electric Vehicles in Beijing, 5 Zhongguancun South Street, Haidian District, Beijing 100081, China)

Abstract

There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector.

Suggested Citation

  • Yanan Liu & Yixuan Gao & Yu Hao & Hua Liao, 2016. "The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data," Energies, MDPI, vol. 9(10), pages 1-11, October.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:831-:d:80647
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    References listed on IDEAS

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    Cited by:

    1. Li, Chuan-Zhong & Wei, Chu & Yu, Yang, 2020. "Income threshold, household appliance ownership and residential energy consumption in urban China," China Economic Review, Elsevier, vol. 60(C).
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    3. Djula Borozan, 2018. "Efficiency of Energy Taxes and the Validity of the Residential Electricity Environmental Kuznets Curve in the European Union," Sustainability, MDPI, vol. 10(7), pages 1-16, July.
    4. Poblete-Cazenave, Miguel & Pachauri, Shonali, 2020. "A simulation-based estimation model of household electricity demand and appliance ownership," MPRA Paper 103403, University Library of Munich, Germany.
    5. Onisanwa Idowu Daniel & Adaji Mercy Ojochegbe, 2020. "Electricity consumption and its determinants in Nigeria," Journal of Economics and Management, Sciendo, vol. 41(3), pages 87-104, September.
    6. Rehermann, F. & Pablo-Romero, M., 2018. "Economic growth and transport energy consumption in the Latin American and Caribbean countries," Energy Policy, Elsevier, vol. 122(C), pages 518-527.
    7. Poblete-Cazenave, Miguel & Pachauri, Shonali, 2021. "A model of energy poverty and access: Estimating household electricity demand and appliance ownership," Energy Economics, Elsevier, vol. 98(C).
    8. Fei Wang & Yili Yu & Xinkang Wang & Hui Ren & Miadreza Shafie-Khah & João P. S. Catalão, 2018. "Residential Electricity Consumption Level Impact Factor Analysis Based on Wrapper Feature Selection and Multinomial Logistic Regression," Energies, MDPI, vol. 11(5), pages 1-26, May.

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