IDEAS home Printed from https://ideas.repec.org/a/oup/erevae/v52y2025i5p1390-1409..html

Estimating technical efficiency at farm level when plot-level data are available

Author

Listed:
  • Yashree Mehta
  • Bernhard Brümmer

Abstract

Ownership of multiple plots by a farmer leads to hierarchical structure of data on production. Researchers use averaging of plot-level technical efficiency scores for computing the farm-level technical efficiency score. With Monte Carlo simulation, we checked the performance of averaging and that of the linear mixed effects model in estimating the true farm efficiency. We generated true efficiency scores under half-normal, normal, and skew-normal distributions of the farm-level random effect. Plot-level score averaging did not estimate the true efficiency. The linear mixed effects model preserved the ranking as well as estimated the true farm-level efficiency score.

Suggested Citation

  • Yashree Mehta & Bernhard Brümmer, 2025. "Estimating technical efficiency at farm level when plot-level data are available," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 52(5), pages 1390-1409.
    • Handle: RePEc:oup:erevae:v:52:y:2025:i:5:p:1390-1409.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/erae/jbaf022
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    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:oup:erevae:v:52:y:2025:i:5:p:1390-1409.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.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.