IDEAS home Printed from https://ideas.repec.org/p/alf/wpaper/2020-01.html
   My bibliography  Save this paper

Covid 19 and loss of production – an estimate for Portugal from electricity consumption

Author

Listed:
  • Miguel St.Aubyn

Abstract

The relationship between electricity consumption and economic activity has been widely studied. It comes then as no surprise that the need to obtain a fast estimate for the GDP drop following the perceived devastating economic effects resulting from the Covid-19 pandemic would lead forecasting practitioners into exploiting this relationship. This drive is further explained, at least in the case of Portugal, by the fact that electricity consumption daily data are published almost in real-time as compared to delays in other potentially informative variables. As usual, there is a trade-off between speed and estimate accuracy. Any result of this kind is not a suitable replacement for better and more complete information, and, in due time, complete and accurate measurements will be available. In the meantime, less precise but already available instruments provide us with some guidance and insight.

Suggested Citation

  • Miguel St.Aubyn, 2020. "Covid 19 and loss of production – an estimate for Portugal from electricity consumption," CFP Working Papers 01/2020, Portuguese Public Finance Council.
  • Handle: RePEc:alf:wpaper:2020-01
    as

    Download full text from publisher

    File URL: https://www.cfp.pt/en/publications/other-publications/covid-19-and-loss-of-production-an-estimate-for-portugal-from-electricity-consumption
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    forecast; economic activity; electricity consumption; Portugal;
    All these keywords.

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • 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
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:alf:wpaper:2020-01. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Helena Rua (email available below). General contact details of provider: https://edirc.repec.org/data/cfpgvpt.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.