Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function
AbstractThe normal-gamma stochastic forntier model was proposed in Greene and Beckers and Hammond as an extension of the normal-exponential proposed in the original derivations of the stochastic frontier by Aigner, Lovell, and Schmidt. The normal-gamma model has the virtue of providing a richer and more flexible parameterization of the inefficiency distribution in the stochastic frontier model than either of the canonical forms, normal-half norma and normal-exponential.
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Bibliographic InfoPaper provided by New York University, Leonard N. Stern School of Business- in its series New York University, Leonard N. Stern School Finance Department Working Paper Seires with number 00-05.
Length: 18 pages
Date of creation: 2000
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Postal: U.S.A.; New York University, Leonard N. Stern School of Business, Department of Economics . 44 West 4th Street. New York, New York 10012-1126
Phone: (212) 998-0100
Web page: http://w4.stern.nyu.edu/finance/
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MODELS ; DISTRIBUTION ; MATHEMATICAL ANALYSIS;
Other versions of this item:
- 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.
- William H. Greene, 2000. "Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function," Working Papers 00-05, New York University, Leonard N. Stern School of Business, Department of Economics.
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