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

Author

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  • 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
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    References listed on IDEAS

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    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. Christian Ritter & Léopold Simar, 1997. "Pitfalls of Normal-Gamma Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 8(2), pages 167-182, May.
    4. Andrei Shleifer, 1985. "A Theory of Yardstick Competition," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 319-327, Autumn.
    5. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    6. 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.
    7. Waldman, Donald M., 1982. "A stationary point for the stochastic frontier likelihood," Journal of Econometrics, Elsevier, vol. 18(2), pages 275-279, February.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    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.
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    More about this item

    Keywords

    frontera estocástica; eficiencia;

    JEL classification:

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

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