IDEAS home Printed from https://ideas.repec.org/a/ids/ijbfmi/v7y2022i3p259-276.html
   My bibliography  Save this article

Application of extreme value theorem in modelling oil consumption of organisation of petroleum exporting countries

Author

Listed:
  • Masha Ahoba Buah
  • Victor Amoako Temeng
  • Samuel Kwesi Asiedu Addo
  • Yao Yevenyo Ziggah

Abstract

In this study, oil consumption of organisation of petroleum exporting countries (OPEC) from 1973 to 2018 is modelled using extreme value theorem (EVT). The main objective of this paper was to employ both the block maxima method and peak over threshold method to determine the best fitting distribution to extreme oil consumption of OPEC. In both approaches, the maximum likelihood estimation was applied to determine the distribution parameters. Findings from the study revealed that the optimal model from the generalised extreme value (GEV) distribution was the Weibull distribution with shape, scale, and location parameter values of -0.63, 6,217.54 and 26,773.21. The optimal model from the generalised Pareto distribution (GPD) was Pareto type II distribution with shape and scale parameters of 0.04 and 666.64 at a threshold value of 34,000. A comparison of the return levels revealed that GPD gave higher return level estimates than GEV. In the study, GEV was chosen over GPD because the difference between the 95% lower and upper confidence intervals and the actual return level for the BMM was found to be lower as compared to the POT approach.

Suggested Citation

  • Masha Ahoba Buah & Victor Amoako Temeng & Samuel Kwesi Asiedu Addo & Yao Yevenyo Ziggah, 2022. "Application of extreme value theorem in modelling oil consumption of organisation of petroleum exporting countries," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 7(3), pages 259-276.
    • Handle: RePEc:ids:ijbfmi:v:7:y:2022:i:3:p:259-276
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=122899
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijbfmi:v:7:y:2022:i:3:p:259-276. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=156 .

    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.