IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v46y2014i1p102-110.html
   My bibliography  Save this article

Identification problems in Granger causality tests based on the net oil price increase

Author

Listed:
  • J. Stevens

Abstract

The net oil price increase is one of the most popular models used to study the relationship between changes in the price of oil and macroeconomic activity. The model postulates that an increase in the price of oil has negative consequences for the economy if the new price exceeds the maximum price observed over a reference period of arbitrary length. The relationship between the net oil price increase and other economic variables is often evaluated with Granger causality tests, the results of which are sensitive to the choice of the reference period. If the reference price is chosen to best fit the data, it becomes an unidentified nuisance parameter under the null hypothesis, causing standard tests to over-reject the null. This article proposes a simple method to obtain correct critical values. Using US data for the period 1954 to 2012, it is found that these corrected critical values reduce, but do not eliminate support for the proposition that the net oil price increase Granger causes real USGDP growth.

Suggested Citation

  • J. Stevens, 2014. "Identification problems in Granger causality tests based on the net oil price increase," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 102-110, January.
    • Handle: RePEc:taf:applec:v:46:y:2014:i:1:p:102-110
    DOI: 10.1080/00036846.2013.831170
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2013.831170
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2013.831170?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
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Patrick De lamirande & Jason Stevens, 2016. "Predicting events with an unidentified time horizon," Economics Bulletin, AccessEcon, vol. 36(2), pages 729-735.

    More about this item

    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:taf:applec:v:46:y:2014:i:1:p:102-110. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.