IDEAS home Printed from https://ideas.repec.org/a/afj/journl/v13y2011iconferencep53-70.html
   My bibliography  Save this article

Are World Commodity Prices Relevant in Predicting Inflation in Botswana?

Author

Listed:
  • Kagiso Mangadi
  • Francis Okurut
  • Dauda Yinusa

    (University of Botswana)

Abstract

The causal relationship between world commodity prices and inflation has been investigated in numerous empirical studies with no clear cut consensus. The key issue in the debate is whether changes in commodity prices can be used to predict the future path of consumer prices. Using a Vector Error Correction Model (VECM), this study seeks to provide empirical evidence on the relevance of world commodity prices in predicting inflation focusing on Botswana, a small open economy that is heavily dependent on the import and export of primary commodities. The results revealed the existence of long run relationships between commodity prices indices and headline inflation in Botswana. The main implication of the findings of this study is that world commodity prices could play an informational role in the conduct of monetary policy in Botswana.

Suggested Citation

  • Kagiso Mangadi & Francis Okurut & Dauda Yinusa, 2011. "Are World Commodity Prices Relevant in Predicting Inflation in Botswana?," The African Finance Journal, Africagrowth Institute, vol. 13(Conferenc), pages 53-70.
    • Handle: RePEc:afj:journl:v:13:y:2011:i:conference:p:53-70
    as

    Download full text from publisher

    File URL: http://www.journals.co.za/ej/ejour_finj.html
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Prices and Inflation; VECM; Botswana;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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

    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:afj:journl:v:13:y:2011:i:conference:p:53-70. 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: Kirk De Doncker (email available below). General contact details of provider: https://edirc.repec.org/data/afrgrza.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.