IDEAS home Printed from https://ideas.repec.org/p/mcm/qseprr/415.html
   My bibliography  Save this paper

On the Sensitivity of Aggregate Productivity Growth Rates to Noisy Measurement

Author

Listed:
  • Frank T. Denton

Abstract

Aggregate rates of productivity growth are among the most closely watched indicators of economic performance. They are also among the most difficult to measure accurately. This paper explores the sensitivity of such rates to random measurement error using a simple generic model. The model allows for errors in the input and output components of the productivity ratio, with different variances, and for serial and cross correlation of the errors. The effects of the errors are considered from the point of view of growth rates themselves, changes in growth rates, and comparisons between rates in different countries.

Suggested Citation

  • Frank T. Denton, 2007. "On the Sensitivity of Aggregate Productivity Growth Rates to Noisy Measurement," Quantitative Studies in Economics and Population Research Reports 415, McMaster University.
    • Handle: RePEc:mcm:qseprr:415
    as

    Download full text from publisher

    File URL: http://socserv.mcmaster.ca/qsep/p/qsep415.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    productivity; growth rates; measurement error;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mcm:qseprr:415. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/demcmca.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.