IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/8899.html
   My bibliography  Save this paper

Forecasting Demand for Electricity: Some Methodological Issues and an Analysis

Author

Listed:
  • Pillai N., Vijayamohanan

Abstract

Electricity demand projection is of utmost importance as electricity has become a vital input to the wellbeing of any society, driving the demand for it from an ever-expanding set of diverse needs to grow on an increasing rate, which in turn places increasing demands on scarce resources of capital investment, material means, and man-power. More specifically, the continuing ‘energy crisis’ has made crucial the need for accurate projection of electricity demand; hence the importance of the forecasting methods. The present paper critically evaluates the electricity demand forecasting methodology and proposes a methodology in the classical time series framework.

Suggested Citation

  • Pillai N., Vijayamohanan, 2008. "Forecasting Demand for Electricity: Some Methodological Issues and an Analysis," MPRA Paper 8899, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:8899
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/8899/1/MPRA_paper_8899.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. N. Vijayamohanan Pillai, 2001. "Electricity demand analysis and forecasting: The tradition is questioned," Centre for Development Studies, Trivendrum Working Papers 312, Centre for Development Studies, Trivendrum, India.
    2. Lester D. Taylor, 1975. "The Demand for Electricity: A Survey," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 74-110, Spring.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olmstead, Sheila M. & Michael Hanemann, W. & Stavins, Robert N., 2007. "Water demand under alternative price structures," Journal of Environmental Economics and Management, Elsevier, vol. 54(2), pages 181-198, September.
    2. Céline Nauges & Arnaud Reynaud, 2001. "Estimation de la demande domestique d'eau potable en France," Revue Économique, Programme National Persée, vol. 52(1), pages 167-185.
    3. Massimo Filippini, 1995. "Swiss Residential Demand for Electricity by Time-of-Use: An Application of the Almost Ideal Demand System," The Energy Journal, , vol. 16(1), pages 27-39, January.
    4. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "A meta-analysis on the price elasticity of energy demand," Energy Policy, Elsevier, vol. 102(C), pages 549-568.
    5. Arbues, Fernando & Garcia-Valinas, Maria Angeles & Martinez-Espineira, Roberto, 2003. "Estimation of residential water demand: a state-of-the-art review," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(1), pages 81-102, March.
    6. Acuña, Guillermo, 2017. "Elasticidades de la demanda de agua en Chile [Elasticities of water demand in Chile]," MPRA Paper 82916, University Library of Munich, Germany.
    7. Fuente, David & Kabubo-Mariara, Jane & Kimuyu, Peter & Mwaura, Mbutu & Whittington, Dale, 2017. "Assessing the Performance of Alternative Water and Sanitation Tariffs: The Case of Nairobi, Kenya," EfD Discussion Paper 17-21, Environment for Development, University of Gothenburg.
    8. Dergiades, Theologos & Tsoulfidis, Lefteris, 2008. "Estimating residential demand for electricity in the United States, 1965-2006," Energy Economics, Elsevier, vol. 30(5), pages 2722-2730, September.
    9. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    10. Gautam, Tej K. & Paudel, Krishna P., 2018. "The demand for natural gas in the Northeastern United States," Energy, Elsevier, vol. 158(C), pages 890-898.
    11. Hendrik S. Houthakker, 1980. "Residential Electricity Revisited," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    12. Hendrik Schmitz & Reinhard Madlener, 2020. "Heterogeneity in price responsiveness for residential space heating in Germany," Empirical Economics, Springer, vol. 59(5), pages 2255-2281, November.
    13. Asci, Serhat & Borisova, Tatiana & Dukes, Michael D., 2015. "Price- and Non-Price Water Demand Management Strategies for Water Utilities," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196768, Southern Agricultural Economics Association.
    14. Ishmael Ackah, 2014. "Determinants of natural gas demand in Ghana," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 272-295, September.
    15. René Cabral & Luciano Ayala & Victor Hugo Delgado, 2017. "Residential Water Demand and Price Perception under Increasing Block Rates," Economics Bulletin, AccessEcon, vol. 37(1), pages 508-519.
    16. Gunnar Eskeland & Torben Mideksa, 2010. "Electricity demand in a changing climate," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(8), pages 877-897, December.
    17. Fell, Harrison & Li, Shanjun & Paul, Anthony, 2014. "A new look at residential electricity demand using household expenditure data," International Journal of Industrial Organization, Elsevier, vol. 33(C), pages 37-47.
    18. Ivan Faiella & Luciano Lavecchia, 2021. "Households' energy demand and the effects of carbon pricing in Italy," Questioni di Economia e Finanza (Occasional Papers) 614, Bank of Italy, Economic Research and International Relations Area.
    19. Henry Lim & Glenn Jenkins, 2000. "Electricity Demand And Electricity Value," Development Discussion Papers 2000-01, JDI Executive Programs.
    20. Kiran B Krishnamurthy, Chandra & Kriström, Bengt, 2013. "A cross-country analysis of residential electricity demand in 11 OECD-countries," CERE Working Papers 2013:5, CERE - the Center for Environmental and Resource Economics, revised 30 Jun 2014.

    More about this item

    Keywords

    Electricity demand; Forecasting; Kerala; Time series analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:8899. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.