IDEAS home Printed from https://ideas.repec.org/p/crs/wpaper/2020-06.html
   My bibliography  Save this paper

A Vector Autoregressive Model of Forecast Electricity Consumption in France

Author

Listed:
  • Stéphane AURAY

    (CREST-ENSAI and ULCO)

  • Vincent CAPONI

    (CREST-ENSAI and IZA)

Abstract

This provides a VARX approach for the estimation of electricity demand in metropolitan France. Our methodology takes into account the complex relation- ship between weather variables and electricity demand, especially in the short and medium run, and the correlation in the longer run, between electricity and macroeconomic variables. We are able to provide a reliable conditional forecasting that, within the VAR framework, takes into account the common dependency of electricity consumption and other variables. While the VAR approach is not novel within this literature, our main contributions lie on the use of exible functions that capture the role of weather to explain electricity consumption together with macroeconomic trend and cycle variables, and on the use of very detailed and comprehensive data on actual metered consumption of electricity in France. In- sample and out-sample forecasts provide evidence that our method is reliable for predicting future scenarios conditional on exogenous variables.

Suggested Citation

  • Stéphane AURAY & Vincent CAPONI, 2020. "A Vector Autoregressive Model of Forecast Electricity Consumption in France," Working Papers 2020-06, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2020-06
    as

    Download full text from publisher

    File URL: http://crest.science/RePEc/wpstorage/2020-06.pdf
    File Function: CREST working paper version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    2. Lim, Kyoung-Min & Lim, Seul-Ye & Yoo, Seung-Hoon, 2014. "Short- and long-run elasticities of electricity demand in the Korean service sector," Energy Policy, Elsevier, vol. 67(C), pages 517-521.
    3. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    4. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    5. Stéphane Auray & Vincenzo Caponi & Benoît Ravel, 2019. "Price Elasticity of Electricity Demand in France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 513, pages 91-103.
    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. Rabindra Nepal & Muhammad Indra al Irsyad & Tooraj Jamasb, 2021. "Sectoral Electricity Demand and Direct Rebound Effects inNew Zealand," The Energy Journal, , vol. 42(4), pages 153-174, July.
    2. Gautam, Tej K. & Paudel, Krishna P., 2018. "Estimating sectoral demands for electricity using the pooled mean group method," Applied Energy, Elsevier, vol. 231(C), pages 54-67.
    3. Tselika, Kyriaki & Tselika, Maria & Demetriades, Elias, 2024. "Quantifying the short-term asymmetric effects of renewable energy on the electricity merit-order curve," Energy Economics, Elsevier, vol. 132(C).
    4. Srivastava, A. & Van Passel, S. & Valkering, P. & Laes, E.J.W., 2021. "Power outages and bill savings: A choice experiment on residential demand response acceptability in Delhi," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    5. Ciarreta, Aitor & Espinosa, Maria Paz & Pizarro-Irizar, Cristina, 2023. "Pricing policies for efficient demand side management in liberalized electricity markets," Economic Modelling, Elsevier, vol. 121(C).
    6. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    7. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    8. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    9. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Yang, Yuting, 2022. "Electricity interconnection with intermittent renewables," Journal of Environmental Economics and Management, Elsevier, vol. 113(C).
    11. Lim, Juin Yau & Safder, Usman & How, Bing Shen & Ifaei, Pouya & Yoo, Chang Kyoo, 2021. "Nationwide sustainable renewable energy and Power-to-X deployment planning in South Korea assisted with forecasting model," Applied Energy, Elsevier, vol. 283(C).
    12. A. Azadeh & M. Saberi & A. Gitiforouz, 2013. "An integrated fuzzy mathematical model and principal component analysis algorithm for forecasting uncertain trends of electricity consumption," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2163-2176, June.
    13. Simon Pezzutto & Gianluca Grilli & Stefano Zambotti & Stefan Dunjic, 2018. "Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence," Energies, MDPI, vol. 11(6), pages 1-18, June.
    14. Meng, Ming & Niu, Dongxiao, 2011. "Modeling CO2 emissions from fossil fuel combustion using the logistic equation," Energy, Elsevier, vol. 36(5), pages 3355-3359.
    15. Frédéric Cherbonnier & Christian Gollier, 2022. "Risk-adjusted Social Discount Rates," Post-Print hal-04012977, HAL.
    16. You, Zhengjie & Lumpp, Sebastian Dirk & Doepfert, Markus & Tzscheutschler, Peter & Goebel, Christoph, 2024. "Leveraging flexibility of residential heat pumps through local energy markets," Applied Energy, Elsevier, vol. 355(C).
    17. Dorothée Charlier & Mouez Fodha & Djamel Kirat, 2023. "Residential CO2 Emissions in Europe and Carbon Taxation: A Country-Level Assessment," The Energy Journal, , vol. 44(5), pages 187-206, September.
    18. Harish, Santosh & Singh, Nishmeet & Tongia, Rahul, 2020. "Impact of temperature on electricity demand: Evidence from Delhi and Indian states," Energy Policy, Elsevier, vol. 140(C).
    19. Lin, Jiang & Xu Liu, & Gang He,, 2020. "Regional electricity demand and economic transition in China," Utilities Policy, Elsevier, vol. 64(C).
    20. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2015. "Long term outlook of primary energy consumption of the Italian thermoelectric sector: Impact of fuel and carbon prices," Energy, Elsevier, vol. 87(C), pages 153-164.

    More about this item

    Keywords

    Electricity Forecast.;

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

    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:crs:wpaper:2020-06. 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: Secretariat General (email available below). General contact details of provider: https://edirc.repec.org/data/crestfr.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.