IDEAS home Printed from https://ideas.repec.org/p/ris/uadetd/2000_022.html
   My bibliography  Save this paper

Análisis de eficiencia aplicado a la regulación ¿Es importante la Distribución Elegida para el Término de Ineficiencia?

Author

Listed:
  • Rossi, Martín

    (Universidad Argntina de la Empresa)

Abstract

En este trabajo se describen las dos distribuciones más utilizadas para el término de ineficiencia de una frontera estocástica: Media Normal y Exponencial. Luego se realiza una aplicación empírica empleando bases de trabajos previos, encontrándose que la eficiencia media es sensible a la distribución asumida. Se halló que en todos los casos la distribución Exponencial reconoce un mayor número de empresas eficientes que la distribución Media Normal. No obstante, los rankings de las firmas no se ven afectados por ambas distribuciones.

Suggested Citation

  • Rossi, Martín, 2000. "Análisis de eficiencia aplicado a la regulación ¿Es importante la Distribución Elegida para el Término de Ineficiencia?," UADE Textos de Discusión 22_2000, Instituto de Economía, Universidad Argentina de la Empresa.
    • Handle: RePEc:ris:uadetd:2000_022
    as

    Download full text from publisher

    File URL: http://www.uade.edu.ar/DocsDownload/Publicaciones/4_226_1573_STD022_2000.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Benitez, Daniel A. & Estache, Antonio & Kennet, D. Mark & Ruzzier, Christian A., 2002. "The potential role of economic cost models in the regulation of telecommunications in developing countries," Information Economics and Policy, Elsevier, vol. 14(1), pages 21-38, March.
    2. Antonio Estache & MartÌn A. Rossi, 2002. "How Different Is the Efficiency of Public and Private Water Companies in Asia?," The World Bank Economic Review, World Bank, vol. 16(1), pages 139-148, June.
    3. Rossi, Martin A., 2001. "Technical change and efficiency measures: the post-privatisation in the gas distribution sector in Argentina," Energy Economics, Elsevier, vol. 23(3), pages 295-304, May.
    4. Christian Ritter & Léopold Simar, 1997. "Pitfalls of Normal-Gamma Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 8(2), pages 167-182, May.
    5. Waldman, Donald M., 1982. "A stationary point for the stochastic frontier likelihood," Journal of Econometrics, Elsevier, vol. 18(2), pages 275-279, February.
    6. 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.
    7. Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
    8. Rossi, Martín, 2000. "Midiendo el valor social de la calidad de los servicios públicos: el agua," UADE Textos de Discusión 20_2000, Instituto de Economía, Universidad Argentina de la Empresa.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    10. Andrei Shleifer, 1985. "A Theory of Yardstick Competition," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 319-327, Autumn.
    11. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Canay, Iván, 2002. "Eficiencia y Productividad en Distribuidoras Eléctricas: Repaso de la Metodología y Aplicación," UADE Textos de Discusión 35_2002, Instituto de Economía, Universidad Argentina de la Empresa.
    2. Rodríguez Pardina, Martín & Rossi, Martín, 1999. "Medidas de eficiencia y regulación: una ilustración del sector de distribuidoras de gas en la Argentina," UADE Textos de Discusión 14_1999, Instituto de Economía, Universidad Argentina de la Empresa.
    3. William C. Horrace & Ian A. Wright, 2020. "Stationary Points for Parametric Stochastic Frontier Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(3), pages 516-526, July.
    4. Estache, Antonio & Rossi, Martín, 1999. "Estimación de una frontera de costos estocástica para empresas del sector agua en Asia y Región del Pacífico," UADE Textos de Discusión 4_1999, Instituto de Economía, Universidad Argentina de la Empresa.
    5. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    6. Christian M. Hafner & Hans Manner & Léopold Simar, 2018. "The “wrong skewness” problem in stochastic frontier models: A new approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 380-400, April.
    7. Léopold Simar & Ingrid Keilegom & Valentin Zelenyuk, 2017. "Nonparametric least squares methods for stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 47(3), pages 189-204, June.
    8. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    9. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.
    10. Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
    11. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2021. "Density deconvolution with Laplace errors and unknown variance," Journal of Productivity Analysis, Springer, vol. 56(2), pages 103-113, December.
    12. Belén Iráizoz Apezteguía & Manuel Rapún Gárate, 1997. "Technical efficiency in the Spanish agrofood industry," Agricultural Economics, International Association of Agricultural Economists, vol. 17(2-3), pages 179-189, December.
    13. Phill Wheat & Alexander D. Stead & William H. Greene, 2019. "Robust stochastic frontier analysis: a Student’s t-half normal model with application to highway maintenance costs in England," Journal of Productivity Analysis, Springer, vol. 51(1), pages 21-38, February.
    14. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    15. Uwe Jensen & Hermann Gartner & Susanne Rässler, 2010. "Estimating German overqualification with stochastic earnings frontiers," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(1), pages 33-51, March.
    16. Xingyuan Zhang, 2000. "A Monte Carlo Study on the Finite Sample Properties of the Gibbs Sampling Method for a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 14(1), pages 71-83, July.
    17. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    18. Sakouvogui Kekoura & Shaik Saleem & Doetkott Curt & Magel Rhonda, 2021. "Sensitivity analysis of stochastic frontier analysis models," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 71-90, March.
    19. William Greene, 2003. "Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function," Journal of Productivity Analysis, Springer, vol. 19(2), pages 179-190, April.
    20. Alecos Papadopoulos, 2021. "Stochastic frontier models using the Generalized Exponential distribution," Journal of Productivity Analysis, Springer, vol. 55(1), pages 15-29, February.

    More about this item

    Keywords

    frontera estocástica; eficiencia;

    JEL classification:

    • L50 - Industrial Organization - - Regulation and Industrial Policy - - - General

    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:ris:uadetd:2000_022. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mariano E. Gonzalez (email available below). General contact details of provider: https://edirc.repec.org/data/ieuadar.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.