IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v31y2021i3p137-152id1582.html
   My bibliography  Save this article

Prediction of pork meat prices by selected methods as an element supporting the decision-making process

Author

Listed:
  • Monika Zielińska-Sitkiewicz
  • Mariola Chrzanowska

Abstract

Forecasts of economic processes can be determined using various methods, and each of them has its own characteristics and is based on specific assumptions. In the case of agriculture, forecasting is an essential element of efficient management of the entire farming process. The pork sector is one of the main agricultural sectors in the world. Pork consumption and supply are the highest among all types of meat, and Poland belongs to the group of large producers. The article analyses the price formation of class E pork, expressed in € per 100 kg of carcass, recorded from May 2004 to December 2019. The data comes from the Agri-food data portal. A creeping trend model with segments of linear trends of various lengths and the methodology of building ARIMA models are used to forecast these prices. The accuracy of forecasts is verified by forecasting ex post and ex ante errors, graphical analysis, and backcasting analysis. The study shows that both methods can be used in the prediction of pork prices.

Suggested Citation

  • Monika Zielińska-Sitkiewicz & Mariola Chrzanowska, 2021. "Prediction of pork meat prices by selected methods as an element supporting the decision-making process," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(3), pages 137-152.
  • Handle: RePEc:wut:journl:v:31:y:2021:i:3:p:137-152:id:1582
    DOI: 10.37190/ord210307
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/1582%20-%20published.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.37190/ord210307?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:wut:journl:v:31:y:2021:i:3:p:137-152:id:1582. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.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.