IDEAS home Printed from https://ideas.repec.org/p/cfe/wpcefa/2010_02.html
   My bibliography  Save this paper

GME versus OLS - Which is the best to estimate utility functions?

Author

Listed:
  • Luís Alberto Godinho Coelho

    (CEFAGE)

  • Andreia Teixeira Marques Dionísio

    (University of Évora, Department of Management, CEFAGE-UÉ)

  • Cesaltina Maria Pacheco Pires

    (University of Évora, Department of Economics and CEFAGE)

Abstract

This paper estimates von Neumann andMorgenstern utility functions comparing the generalized maximum entropy (GME) with OLS, using data obtained by utility elicitation methods. Thus, it provides a comparison of the performance of the two estimators in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover the GME estimator is more precise than the OLS one. Overall the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data is generated by utility elicitation methods.

Suggested Citation

  • Luís Alberto Godinho Coelho & Andreia Teixeira Marques Dionísio & Cesaltina Maria Pacheco Pires, 2010. "GME versus OLS - Which is the best to estimate utility functions?," CEFAGE-UE Working Papers 2010_02, University of Evora, CEFAGE-UE (Portugal).
    • Handle: RePEc:cfe:wpcefa:2010_02
    as

    Download full text from publisher

    File URL: https://api.cefage.uevora.pt/assets/6c12316d-e790-43a2-88ae-91530a03a7b0
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Rui Fragoso & Maria Leonor da Silva Carvalho, 2013. "Estimation of cost allocation coefficients at the farm level using an entropy approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1893-1906, September.

    More about this item

    Keywords

    Generalized maximum entropy; Maximum entropy principle; von Neumann and Morgenstern utility; Utility elicitation.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cfe:wpcefa:2010_02. 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: Angela Pacheco (email available below). General contact details of provider: https://edirc.repec.org/data/cfevopt.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.