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Short- and long-run elasticities of electricity demand in the Korean service sector

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  • Lim, Kyoung-Min
  • Lim, Seul-Ye
  • Yoo, Seung-Hoon

Abstract

This paper attempts to examine the electricity demand function in the Korean service sector using the annual data covering the period 1970–2011. The short- and long-run elasticities of electricity demand with respect to price and income are empirically estimated using a co-integration and error-correction model. The short- and long-run price elasticities are estimated to be −0.421 and −1.002, respectively. The short- and long-run income elasticities are computed to be 0.855 and 1.090, respectively. Electricity demand in the service sector is inelastic to changes in both price and income in the short-run, but elastic in the long-run. Therefore, it appears that a pricing policy is more effective than the direct regulation of reducing electricity demand in the long-run in order to stabilize the electricity demand in the service sector. Moreover, it is necessary to encourage a more efficient use of electricity to cope with increasing demand for electricity following economic growth because the electricity demand in the service sector is income-elastic in the long-run.

Suggested Citation

  • Lim, Kyoung-Min & Lim, Seul-Ye & Yoo, Seung-Hoon, 2014. "Short- and long-run elasticities of electricity demand in the Korean service sector," Energy Policy, Elsevier, vol. 67(C), pages 517-521.
  • Handle: RePEc:eee:enepol:v:67:y:2014:i:c:p:517-521
    DOI: 10.1016/j.enpol.2013.12.017
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    References listed on IDEAS

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    Cited by:

    1. Agustin J. Ros, 2017. "An Econometric Assessment of Electricity Demand in the United States Using Utility-specific Panel Data and the Impact of Retail Competition on Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. García-Gusano, Diego & Suárez-Botero, Jasson & Dufour, Javier, 2018. "Long-term modelling and assessment of the energy-economy decoupling in Spain," Energy, Elsevier, vol. 151(C), pages 455-466.
    3. Gautam, Tej K. & Paudel, Krishna P., 2018. "Estimating sectoral demands for electricity using the pooled mean group method," Applied Energy, Elsevier, vol. 231(C), pages 54-67.
    4. Lim, Seul-Ye & Kim, Hyo-Jin & Yoo, Seung-Hoon, 2016. "The demand function for residential heat through district heating system and its consumption benefits in Korea," Energy Policy, Elsevier, vol. 97(C), pages 155-160.
    5. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    6. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.
    7. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.

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