Skip to main navigation Skip to search Skip to main content

A meta-analysis on the price elasticity and income elasticity of residential electricity demand

Xing Zhu, Lanlan Li, Kaile Zhou*, Xiaoling Zhang*, Shanlin Yang

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Price elasticity and income elasticity can quantitatively measure the impact of price volatility and income diversity on household electricity demand. To analyze household electricity demand and better identify the main factors affecting residential electricity demand elasticity in previous literature, a meta-analysis based on a comprehensive and systematic summary of 103 articles is presented in this study. The influencing factors are identified, with a weighed least squares (WLS) linear regression model to evaluate their strength. The price elasticities and income elasticities are discussed from three dimensions, namely short-term, long-term and unmarked. The results show that residential electricity demand is almost price-inelastic and income-inelastic in the short-term. But in the long-term, some residential electricity demand is price-elastic and income-elastic. The results also reveal that residential electricity demand elasticity is affected by many factors, such as time interval and sample period. These conclusions can support the formulation of more effective electricity price and energy policy.
    Original languageEnglish
    Pages (from-to)169-177
    JournalJournal of Cleaner Production
    Volume201
    Online published7 Aug 2018
    DOIs
    Publication statusPublished - 10 Nov 2018

    Research Keywords

    • Electricity demand
    • Income elasticity
    • Meta-analysis
    • Price elasticity

    RGC Funding Information

    • RGC-funded

    Fingerprint

    Dive into the research topics of 'A meta-analysis on the price elasticity and income elasticity of residential electricity demand'. Together they form a unique fingerprint.

    Cite this