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

Listed author(s):
  • Rossi, Martín

    (Universidad Argntina de la Empresa)

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.

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File URL: http://www.uade.edu.ar/DocsDownload/Publicaciones/4_226_1573_STD022_2000.pdf
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Paper provided by Instituto de Economía, Universidad Argentina de la Empresa in its series UADE Textos de Discusión with number 22_2000.

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Length: 25 pages
Date of creation: 01 Nov 2000
Handle: RePEc:ris:uadetd:2000_022
Contact details of provider: Web page: http://www.uade.edu.ar/paginas/InstEconomiaIDE.aspx

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  1. Rossi, Martín, 2000. "Technical Change and Efficiency Measures: The Post-privatisation in the Gas Distribution Sector in Argentina," UADE Working Papers 7_2000, Instituto de Economía, Universidad Argentina de la Empresa.
  2. 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.
  3. 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.
  4. Ritter, C. & Simar, L., "undated". "Pitfalls of normal-gamma stochastic frontier models," CORE Discussion Papers RP 1272, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. 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.
  6. 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.
  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. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
  9. 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.
  10. Benitez, Daniel A. & Estache, Antonio & Kennet, D. Mark & Ruzzier, Christian A., 2000. "Potential Role of Economic Cost Models in the Regulation of Telecommunications in Developing Countries," UADE Working Papers 10_2000, Instituto de Economía, Universidad Argentina de la Empresa.
  11. Andrei Shleifer, 1985. "A Theory of Yardstick Competition," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 319-327, Autumn.
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