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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

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.

Suggested Citation

  • Gupta, Eshita, 2012. "Global warming and electricity demand in the rapidly growing city of Delhi: A semi-parametric variable coefficient approach," Energy Economics, Elsevier, vol. 34(5), pages 1407-1421.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1407-1421
    DOI: 10.1016/j.eneco.2012.04.014
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    References listed on IDEAS

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    1. Bessec, Marie & Fouquau, Julien, 2008. "The non-linear link between electricity consumption and temperature in Europe: A threshold panel approach," Energy Economics, Elsevier, vol. 30(5), pages 2705-2721, September.
    2. 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.
    3. Sailor, David J, 2001. "Relating residential and commercial sector electricity loads to climate—evaluating state level sensitivities and vulnerabilities," Energy, Elsevier, vol. 26(7), pages 645-657.
    4. Wadud, Zia & Noland, Robert B. & Graham, Daniel J., 2010. "A semiparametric model of household gasoline demand," Energy Economics, Elsevier, vol. 32(1), pages 93-101, January.
    5. 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.
    6. 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.
    7. Ramesh, S. & Natarajan, Bhaskar & Bhagat, Gopika, 1988. "Peak load prediction using weather variables," Energy, Elsevier, vol. 13(8), pages 671-679.
    8. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    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 149-162, February.
    10. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    11. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521012263, April.
    12. repec:dau:papers:123456789/8180 is not listed on IDEAS
    13. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
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    Citations

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    Cited by:

    1. Brandon Moore & André Coleman & Mark Wigmosta & Richard Skaggs & Erik Venteris, 2015. "A High Spatiotemporal Assessment of Consumptive Water Use and Water Scarcity in the Conterminous United States," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5185-5200, November.
    2. repec:eee:energy:v:127:y:2017:i:c:p:534-543 is not listed on IDEAS
    3. Eshita Gupta, 2016. "The Effect Of Development On The Climate Sensitivity Of Electricity Demand In India," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-49, May.
    4. Byrne, Paul & Fournaison, Laurence & Delahaye, Anthony & Ait Oumeziane, Yacine & Serres, Laurent & Loulergue, Patrick & Szymczyk, Anthony & Mugnier, Daniel & Malaval, Jean-Luc & Bourdais, Romain & Gue, 2015. "A review on the coupling of cooling, desalination and solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 703-717.
    5. Xu, Bin & Lin, Boqiang, 2016. "Reducing CO2 emissions in China's manufacturing industry: Evidence from nonparametric additive regression models," Energy, Elsevier, vol. 101(C), pages 161-173.
    6. Eshita Gupta, 2014. "The Effect of development on the climate sensitivity of electricity demand in India," Indian Statistical Institute, Planning Unit, New Delhi Discussion Papers 14-05, Indian Statistical Institute, New Delhi, India.
    7. Marilyn Brown & Matt Cox & Ben Staver & Paul Baer, 2016. "Modeling climate-driven changes in U.S. buildings energy demand," Climatic Change, Springer, vol. 134(1), pages 29-44, January.
    8. Xu, Bin & Lin, Boqiang, 2015. "How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models," Energy Economics, Elsevier, vol. 48(C), pages 188-202.
    9. repec:eee:energy:v:127:y:2017:i:c:p:786-802 is not listed on IDEAS
    10. Marilyn A. Brown & Matt Cox & Ben Staver & Paul Baer, 2016. "Modeling climate-driven changes in U.S. buildings energy demand," Climatic Change, Springer, vol. 134(1), pages 29-44, January.

    More about this item

    Keywords

    Temperature–electricity curve; Variable coefficient model;

    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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