IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v74y1992i4p1029-1039..html
   My bibliography  Save this article

Estimating the Technology Coefficients in Linear Programming Models

Author

Listed:
  • Bruce L. Dixon
  • Robert H. Hornbaker

Abstract

Estimation of a linear programming model's technology coefficients using data from a sample of firms is viewed as an application of random coefficient regression (RCR). An RCR estimator restricting predicted coefficient values to be nonnegative is proposed. The estimator's finite sample performance is examined in Monte Carlo experiments. The proposed estimator performs well compared with inequality-restricted least squares, despite its use of an estimated covariance matrix. In sampling a population of firms, a dependency may arise between coefficients and activity levels. Two tests for dependence are proposed and examined in Monte Carlo experiments. The tests' reliability varies with characteristics of the sampled population.

Suggested Citation

  • Bruce L. Dixon & Robert H. Hornbaker, 1992. "Estimating the Technology Coefficients in Linear Programming Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(4), pages 1029-1039.
    • Handle: RePEc:oup:ajagec:v:74:y:1992:i:4:p:1029-1039.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.2307/1243201
    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. Yves Léony & Ludo Peeters & Maurice Quinqu & Yves Surry, 1999. "The Use of Maximum Entropy to Estimate Input‐Output Coefficients From Regional Farm Accounting Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 425-439, September.
    2. Gocht, Alexander, 2008. "Estimating input allocation for farm supply models," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6469, European Association of Agricultural Economists.

    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:74:y:1992:i:4:p:1029-1039.. 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.