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Time-varying Long-run Income and Output Elasticities of Electricity Demand

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Abstract

It is widely accepted that long-run elasticities of demand for electricity are not stable over time. We model long-run sectoral electricity demand using a time-varying cointegrating vector. Specifically, the coefficient on income (residential sector) or output (commercial and industrial sectors) is allowed to follow a smooth semiparametric function of time, providing a flexible specification that allows more accurate out-of-sample forecasts than either fixed or discretely changing regression coefficients. We fit the model to Korean data over 1995:01-2012:12 for the residential sector and 1985:01-2012:12 for the commercial and industrial sectors. The rapid development of Korea over this period provides a very clear case for allowing the coefficient on income/output to vary over time, but the essential modeling strategy is widely applicable.

Suggested Citation

  • Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
  • Handle: RePEc:umc:wpaper:1409
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    File URL: https://economics.missouri.edu/working-papers/2014/wp1409_miller.pdf
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    Cited by:

    1. Fukushige, Mototsugu & Yamawaki, Hiroshige, 2015. "The relationship between an electricity supply ceiling and economic growth: An application of disequilibrium modeling to Taiwan," Journal of Asian Economics, Elsevier, vol. 36(C), pages 14-23.
    2. repec:eee:eneeco:v:67:y:2017:i:c:p:366-374 is not listed on IDEAS
    3. repec:eee:enepol:v:106:y:2017:i:c:p:233-243 is not listed on IDEAS
    4. Ozturk, Ilhan & Arisoy, Ibrahim, 2016. "An estimation of crude oil import demand in Turkey: Evidence from time-varying parameters approach," Energy Policy, Elsevier, vol. 99(C), pages 174-179.
    5. Julián Pérez-García & Julián Moral-Carcedo, 2017. "Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis," Energies, MDPI, Open Access Journal, vol. 10(3), pages 1-20, March.
    6. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2016. "Disentangling temporal patterns in elasticities: A functional coefficient panel analysis of electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 232-243.
    7. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    8. Daniel de Abreu Pereira Uhr & Júlia Gallego Ziero Uhr, André Luis Squarize Chagas, 2017. "Estimation of price and income elasticities for the Brazilian household electricity demand," Working Papers, Department of Economics 2017_12, University of São Paulo (FEA-USP).
    9. Pérez-García, Julián & Moral-Carcedo, Julián, 2016. "Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain," Energy, Elsevier, vol. 97(C), pages 127-143.

    More about this item

    Keywords

    electricity demand; income elasticity of demand; output elasticity of conditional factor demand; cointegration; time-varying coefficients;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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