IDEAS home Printed from https://ideas.repec.org/p/fpr/ifprid/1710.html

Correlated non-classical measurement errors, ‘second best’ policy inference and the inverse size-productivity relationship in agriculture

Author

Listed:
  • Abay, Kibrom A.
  • Abate, Gashaw T.
  • Barrett, Christopher B.
  • Bernard, Tanguy

Abstract

We show analytically and empirically that non-classical measurement errors in the two key variables in a hypothesized relationship can bias the estimated relationship between them in any direction. Furthermore, if these measurement errors are correlated, correcting for either one alone can aggravate bias in the parameter estimate of interest relative to ignoring mismeasurement in both variables, a ‘second best’ result with implications for a broad class of economic phenomena of policy interest. We illustrate these results empirically by demonstrating the implications of mismeasured agricultural output and plot size for the long-debated (inverse) relationship between size and productivity.

Suggested Citation

  • Abay, Kibrom A. & Abate, Gashaw T. & Barrett, Christopher B. & Bernard, Tanguy, 2018. "Correlated non-classical measurement errors, ‘second best’ policy inference and the inverse size-productivity relationship in agriculture," IFPRI discussion papers 1710, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifprid:1710
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/10568/146659
    Download Restriction: no
    ---><---

    Other versions of this item:

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:fpr:ifprid:1710. 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/ifprius.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.