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Global warming and electricity demand in the rapidly growing city of Delhi: A semi-parametric variable coefficient approach

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  • Gupta, Eshita
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    Abstract

    This paper estimates the climate sensitivity of electricity demand in Delhi using daily data on electricity demand and apparent temperature for the period 2000–09. The study adopts a semi-parametric variable coefficient model in order to investigate the impact of climatic factors on electricity demand. As evident from previous studies, electricity demand is a U-shaped function of temperature. We find the rising part of the temperature–electricity curve to become more pronounced over time implying an increase in cooling demand per unit increase in summer temperatures. The study therefore predicts the adverse effects of climate change on electricity demand to be asymmetrically distributed in different seasons in the future, resulting in a serious disequilibrium in the hot months.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 34 (2012)
    Issue (Month): 5 ()
    Pages: 1407-1421

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    Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1407-1421

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    Web page: http://www.elsevier.com/locate/eneco

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    Keywords: Temperature–electricity curve; Variable coefficient model;

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    1. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
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    6. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    7. Hekkenberg, M. & Moll, H.C. & Uiterkamp, A.J.M. Schoot, 2009. "Dynamic temperature dependence patterns in future energy demand models in the context of climate change," Energy, Elsevier, vol. 34(11), pages 1797-1806.
    8. Ramesh, S. & Natarajan, Bhaskar & Bhagat, Gopika, 1988. "Peak load prediction using weather variables," Energy, Elsevier, vol. 13(8), pages 671-679.
    9. Henley, Andrew & Peirson, John, 1997. "Non-linearities in Electricity Demand and Temperature: Parametric versus Non-parametric Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(1), pages 149-62, February.
    10. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521012263.
    11. Sailor, D.J & Pavlova, A.A, 2003. "Air conditioning market saturation and long-term response of residential cooling energy demand to climate change," Energy, Elsevier, vol. 28(9), pages 941-951.
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