IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v18y1993i1p1-19.html
   My bibliography  Save this article

Autocorrelation and Heteroskedasticity in Equations Describing the Demand for Money during Rapid Inflations

Author

Listed:
  • Jaksch, Hans Jurgen

Abstract

Estimating econometric equations with linear autoregressive error terms is standard if the covariance matrix of these error terms are homoskedastic. However, if heteroskedasticity prevails, this heteroskedasticity should be taken into account in order to obtain efficient estimates. In this paper, the well-known maximum-likelihood estimation method due to Beach and MacKinnon (1978) is extended to the heteroskedastic case and then applied to equations describing the demand for money in advanced inflations. Since this method is not a straightforward generalization of the Beach-MacKinnon procedure, it not necessarily leads to estimates which are to be preferred to those obtained under the assumption of homoskedasticity.

Suggested Citation

  • Jaksch, Hans Jurgen, 1993. "Autocorrelation and Heteroskedasticity in Equations Describing the Demand for Money during Rapid Inflations," Empirical Economics, Springer, vol. 18(1), pages 1-19.
  • Handle: RePEc:spr:empeco:v:18:y:1993:i:1:p:1-19
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:empeco:v:18:y:1993:i:1:p:1-19. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.