IDEAS home Printed from
   My bibliography  Save this article

Estimación Bayesiana en modelos de producción con frontera determinista/Bayesian Estimation in Deterministic Frontier Production Models



    () (Departamento de Economía Aplicada I, Facultad de Ciencias Económicas y Empresariales. UNIVERSIDAD DE SEVILLA)


    () (Departamento de Economía Aplicada I, Facultad de Ciencias Económicas y Empresariales. UNIVERSIDAD DE SEVILLA.)


Como consecuencia de no ser válidos, en los modelos de producción con frontera determinista, las condiciones usuales de regularidad (que justifican la consistencia y normalidad asintótica de los estimadores máximo verosímiles), desconocemos las propiedades generales de estos estimadores. Una alternativa son los métodos de inferencia bayesiana que, gracias al algoritmo de Gibbs, son relativamente fáciles de aplicar. En nuestro trabajo proponemos una distribución a priori no informativa para este modelo y, por simulación, analizamos el comportamiento de los estimadores e intervalos bayesianos. As a consequence of non valid regularity conditions, we unknown the general properties (consistency and asymptotic normality) of the maximun likelihood estimators in the deterministic frontier production models. An alternative to these estimators are the bayesian inference methods. Thanks to Gibbs’ algorithm, these methods are relativity easy to apply. In our work, we propose a prior noninformative distribution for the deterministic frontier models, and, by simulation, we study the Bayesian estimators and intervals behaviour.

Suggested Citation

  • Ortega Irizo, Fco. Javier & Basulto Santos, Jesús, 2009. "Estimación Bayesiana en modelos de producción con frontera determinista/Bayesian Estimation in Deterministic Frontier Production Models," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 27, pages 573(22á)-57, Agosto.
  • Handle: RePEc:lrk:eeaart:27_2_15

    Download full text from publisher

    File URL:
    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.

    References listed on IDEAS

    1. D. S. Prasada Rao & Bart van Ark, 2013. "Introduction," Chapters,in: World Economic Performance, chapter 1, pages 1-6 Edward Elgar Publishing.
    2. Léopold Simar, 2007. "How to improve the performances of DEA/FDH estimators in the presence of noise?," Journal of Productivity Analysis, Springer, vol. 28(3), pages 183-201, December.
    3. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    4. Forsund, Finn R. & Lovell, C. A. Knox & Schmidt, Peter, 1980. "A survey of frontier production functions and of their relationship to efficiency measurement," Journal of Econometrics, Elsevier, vol. 13(1), pages 5-25, May.
    5. Daouia, Abdelaati & Simar, Leopold, 2007. "Nonparametric efficiency analysis: A multivariate conditional quantile approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 375-400, October.
    6. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Modelos de producción con frontera; Modelo Half-Normal; Estimación Bayesiana; Algoritmo de Gibbs ; Frontier Production Models; Half-Normal Model; Bayesian Estimation; Gibbs Sampling.;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables


    Access and download statistics


    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:lrk:eeaart:27_2_15. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Beatriz Rodríguez Prado). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.