IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v84y2002i5p1264-1270.html
   My bibliography  Save this article

Entropy-Based Methods of Modeling Stochastic Production Efficiency

Author

Listed:
  • Douglas J. Miller

Abstract

No abstract is available for this item.

Suggested Citation

  • Douglas J. Miller, 2002. "Entropy-Based Methods of Modeling Stochastic Production Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(5), pages 1264-1270.
    • Handle: RePEc:oup:ajagec:v:84:y:2002:i:5:p:1264-1270
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/1467-8276.00388
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lakshmi Balasubramanyan & Spiro Stefanou & Jeffrey Stokes, 2012. "An entropy approach to size and variance heterogeneity in U.S. commercial banks," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 728-749, July.
    2. Binlei Gong, 2020. "New Growth Accounting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 641-661, March.
    3. Randall Campbell & Kevin Rogers & Jon Rezek, 2008. "Efficient frontier estimation: a maximum entropy approach," Journal of Productivity Analysis, Springer, vol. 30(3), pages 213-221, December.

    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:oup:ajagec:v:84:y:2002:i:5:p:1264-1270. 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/aaeaaea.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.