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Identifying electricity-saving potential in rural China: Empirical evidence from a household survey

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  • Yu, Yihua
  • Guo, Jin

Abstract

In recent years, there has been a fast-growing body of literature examining energy-saving potential in relation to electricity. However, empirical studies focusing on non-Western nations are limited. To fill this gap, this study intends to examine the electricity-saving potential of rural households in China using a unique data set from the China Residential Electricity Consumption Survey (CRECS) in collaboration with the China General Social Survey (CGSS), conducted nationwide at the household level in rural China. We use a stochastic frontier model, which allows us to decompose residential electricity consumption into the minimum necessary amount of consumption based on physical characteristics (e.g. house size, house age, number of televisions or refrigerators) and estimate the consumption slack (i.e. the amount of electricity consumption that could be saved), which depends on various factors. We find that rural households in China are generally efficient in electricity saving and the saving potential is affected by (fast) information feedback and social-demographic characteristics, instead of by the (averaged) electricity price, or energy efficiency labelling signals. In addition, we find no evidence of regional heterogeneity on electricity saving potential for rural households. Policy implications are derived.

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  • Yu, Yihua & Guo, Jin, 2016. "Identifying electricity-saving potential in rural China: Empirical evidence from a household survey," Energy Policy, Elsevier, vol. 94(C), pages 1-9.
  • Handle: RePEc:eee:enepol:v:94:y:2016:i:c:p:1-9
    DOI: 10.1016/j.enpol.2016.03.031
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    More about this item

    Keywords

    Electricity saving; Information feedback; Stochastic frontier; Rural China; D1; Q4; C21; R10;
    All these keywords.

    JEL classification:

    • D1 - Microeconomics - - Household Behavior
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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