IDEAS home Printed from https://ideas.repec.org/a/eee/matsoc/v141y2026ics016548962600034x.html

From utility functions and generalized means to distance functions: A Stone–Geary approach and related duality results

Author

Listed:
  • Briec, Walter

Abstract

This article demonstrates how a large number of efficiency measures known in the literature in production economics can be interpreted through the notion of utility function, based on the concept of Stone–Geary utility. Several relationships between these utility functions and distance functions, a commonly used tool in production theory, are established. To achieve these objectives, a generalized mean distance function is introduced, inspired by the Atkinson inequality index, itself derived from the notion of the Aczel mean. It measures the maximum sum of netput expansions required to reach an efficient point. Several duality theorems are established, linking the new distance functions to the profit function. For all feasible production vectors, the results include as special cases most of the dual correspondences previously established in the literature. Finally, a large class of measures is identified for which these duality results can be obtained without requiring convexity. A numerical example is provided.

Suggested Citation

  • Briec, Walter, 2026. "From utility functions and generalized means to distance functions: A Stone–Geary approach and related duality results," Mathematical Social Sciences, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:matsoc:v:141:y:2026:i:c:s016548962600034x
    DOI: 10.1016/j.mathsocsci.2026.102527
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016548962600034X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.mathsocsci.2026.102527?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:eee:matsoc:v:141:y:2026:i:c:s016548962600034x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505565 .

    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.