IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Information Content of DQAF Indicators; Empirical Entropy Analysis

  • Mico Mrkaic
Registered author(s):

    The study presents an analysis of the information content of IMF’s Data Quality Assessment Framework (DQAF) indicators. There are significant differences in the quantity of information between DQAF dimensions and sub-dimensions. The most informative DQAF dimension is accessibility, followed by the prerequisites of quality and accuracy and reliability. The least informative DQAF dimensions are serviceability and assurances of integrity. The implication of these findings is that the current DQAF indicators do not maximize the amount of information that could be obtained during data ROSC missions. An additional set of assessments that would refine the existing DQAF indicators would be beneficial in maximizing the information gathered during data ROSC mission. The entropy of DQAF indicators could also be used in the construction of a cardinal index of data quality.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=24186
    Download Restriction: no

    Paper provided by International Monetary Fund in its series IMF Working Papers with number 10/204.

    as
    in new window

    Length: 25
    Date of creation: 01 Sep 2010
    Date of revision:
    Handle: RePEc:imf:imfwpa:10/204
    Contact details of provider: Postal: International Monetary Fund, Washington, DC USA
    Phone: (202) 623-7000
    Fax: (202) 623-4661
    Web page: http://www.imf.org/external/pubind.htm
    Email:


    More information through EDIRC

    Order Information: Web: http://www.imf.org/external/pubs/pubs/ord_info.htm

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Jochen Hartwig, 2008. "Trying to assess the quality of macroeconomic data: The case of Swiss labour productivity growth as an example," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2008(1), pages 37-61.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:10/204. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jim Beardow)

    or (Hassan Zaidi)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.