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Identifiability of the Stochastic Frontier Models

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  • Bandyopadhyay, Debdas
  • Das, Arabinda

Abstract

This paper examines the identifiability of the standard single-equation stochastic frontier models with uncorrelated and correlated error components giving, inter alia, mathematical content to the notion of “near-identifiability” of a statistical model. It is seen that these models are at least locally identifiable but suffer from the “near-identifiability” problem. Our results also highlight the pivotal role played by the Signal to Noise Ratio in the “near-identifiablity” of the stochastic frontier models.

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File URL: http://mpra.ub.uni-muenchen.de/8032/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 8032.

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Date of creation: Jun 2007
Date of revision: Jan 2008
Handle: RePEc:pra:mprapa:8032

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Keywords: Identification; Stochastic frontier model; Information Matrix; Signal to Noise Ratio;

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  1. 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.
  2. Murray D Smith, 2004. "Stochastic Frontier Models With Correlated Error Components," Econometric Society 2004 Australasian Meetings 121, Econometric Society.
  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 435-44, June.
  4. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
  5. RITTER, Christian & SIMAR, Leopold, 1994. "Pitfalls of Normal-Gamma Stochastic Frontier Models," CORE Discussion Papers 1994041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. A. Capitanio & A. Azzalini & E. Stanghellini, 2003. "Graphical models for skew-normal variates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 30(1), pages 129-144.
  7. Debdas Bandyopadhyay & Arabinda Das, 2006. "On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components," Journal of Productivity Analysis, Springer, vol. 26(2), pages 165-180, October.
  8. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
  9. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-91, May.
  10. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
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