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Residential electricity demand for Spain: new empirical evidence using aggregated data

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  • Blazquez Leticia

    (Department of Spanish and International Economics, Econometrics and Economic History and Institutions)

  • Nina Boogen

    (Centre for Energy Policy and Economics (CEPE), Department of Management, Technology and Economics, ETH Zurich)

  • Massimo Filippini

    (Centre for Energy Policy and Economics (CEPE), Department of Management, Technology and Economics, ETH Zurich and Department of Economics, University of Lugano, Switzerland)

Abstract

This paper presents an empirical analysis on the residential demand for electricity. This analysis has been performed using aggregate panel data at the province level for 47 Spanish provinces for the period from 2000 to 2008. For this purpose, we estimated a log-log demand equation for electricity consumption using a dynamic partial adjustment approach. This dynamic demand function has been estimated using OLS, a fixed effect model, and a GMM estimator proposed by Blundell and Bond (1998). The purpose of this empirical analysis has been to highlight some of the characteristics of the Spanish residential electricity demand. Particular attention has been paid to the influence of price, income, and weather conditions on electricity demand. The estimated short and long-run own price elasticities are, as expected, negative, but lower than 1. Furthermore, weather variables have a significant impact on electricity demand.

Suggested Citation

  • Blazquez Leticia & Nina Boogen & Massimo Filippini, 2012. "Residential electricity demand for Spain: new empirical evidence using aggregated data," CEPE Working paper series 12-82, CEPE Center for Energy Policy and Economics, ETH Zurich.
    • Handle: RePEc:cee:wpcepe:12-82
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    References listed on IDEAS

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    3. Chen, Han & Huang, Ye & Shen, Huizhong & Chen, Yilin & Ru, Muye & Chen, Yuanchen & Lin, Nan & Su, Shu & Zhuo, Shaojie & Zhong, Qirui & Wang, Xilong & Liu, Junfeng & Li, Bengang & Tao, Shu, 2016. "Modeling temporal variations in global residential energy consumption and pollutant emissions," Applied Energy, Elsevier, vol. 184(C), pages 820-829.
    4. Bertrand, Jean-Louis & Parnaudeau, Miia, 2019. "Understanding the economic effects of abnormal weather to mitigate the risk of business failures," Journal of Business Research, Elsevier, vol. 98(C), pages 391-402.
    5. Gautam, Tej & Paudel, Krishna, 2016. "The Demand For Electricity And Natural Gas In The Northeastern United States," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230114, Southern Agricultural Economics Association.
    6. Nauman Ahmed & Uzma Nisar, 2019. "Electricity Demand in Pakistan: A Household Analysis," Journal of Economic Impact, Science Impact Publishers, vol. 1(2), pages 34-39.
    7. Verbič, Miroslav & Filipović, Sanja & Radovanović, Mirjana, 2017. "Electricity prices and energy intensity in Europe," Utilities Policy, Elsevier, vol. 47(C), pages 58-68.
    8. Dicembrino, Claudio & Trovato, Giovanni, 2013. "Structural Breaks, Price and Income Elasticity, and Forecast of the Monthly Italian Electricity Demand," MPRA Paper 47653, University Library of Munich, Germany.
    9. Lindemann, Henrik, 2015. "Regulatory Objectives and the Intensity of Unbundling in Electricity Markets," Hannover Economic Papers (HEP) dp-544, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Lindemann, Henrik, 2015. "Budgetary Interests and the Degree of Unbundling in Electricity Markets - An Empirical Analysis for OECD Countries," Hannover Economic Papers (HEP) dp-543, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    11. Radulescu, Doina & Pavanini, Nicola & Feger, Fabian, 2016. "Welfare and Redistribution Effects of Alternative Tariffs in Energy Markets with Solar Power," VfS Annual Conference 2016 (Augsburg): Demographic Change 145669, Verein für Socialpolitik / German Economic Association.

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    More about this item

    Keywords

    residential electricity demand; panel data; partial adjustment model; aggregate data;
    All these keywords.

    JEL classification:

    • D - Microeconomics
    • D2 - Microeconomics - - Production and Organizations
    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis

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