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A Stochastic Frontier Model with Correction for Sample Selection

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  • William Greene
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  • William Greene, 2008. "A Stochastic Frontier Model with Correction for Sample Selection," Working Papers 08-9, New York University, Leonard N. Stern School of Business, Department of Economics.
    • Handle: RePEc:ste:nystbu:08-9
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    File URL: http://w4.stern.nyu.edu/economics/docs/workingpapers/2008/StochasticFrontier_Selection.pdf
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    References listed on IDEAS

    as
    1. William H. Greene, 1997. "FIML Estimation of Sample Selection Models for Count Data," Working Papers 97-02, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
    3. 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.
    4. Subal Kumbhakar & Efthymios Tsionas & Timo Sipiläinen, 2009. "Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming," Journal of Productivity Analysis, Springer, vol. 31(3), pages 151-161, June.
    5. Alan Collins & Richard I. D. Harris, 2005. "The Impact Of Foreign Ownership And Efficiency On Pollution Abatement Expenditure By Chemical Plants: Some Uk Evidence," Scottish Journal of Political Economy, Scottish Economic Society, vol. 52(5), pages 747-768, November.
    6. Terza, J.V., 1995. "An Estimator for Nonlinear Regression Models with Endogenous Switching and Sample Selection," Papers 04-95-04, Pennsylvania State - Department of Economics.
    7. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    8. Gary Koop & Mark F J Steel, 1999. "Bayesian Analysis of Stochastic Frontier Models," Edinburgh School of Economics Discussion Paper Series 19, Edinburgh School of Economics, University of Edinburgh.
    9. M. Weeks, 2003. "Discrete choice methods with simulation, Kenneth E. Train, Cambridge University Press, 2003, ISBN: 0-521-81696-3, pp. 334," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 379-383.
    10. Joseph Terza, 2009. "Parametric Nonlinear Regression with Endogenous Switching," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 555-580.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, September.
    12. Kopp, Raymond J. & Mullahy, John, 1990. "Moment-based estimation and testing of stochastic frontier models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 165-183.
    13. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    14. Sanzidur Rahman & Aree Wiboonpongse & Songsak Sriboonchitta & Yaovarate Chaovanapoonphol, 2009. "Production Efficiency of Jasmine Rice Producers in Northern and North‐eastern Thailand," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(2), pages 419-435, June.
    15. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
    16. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    17. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    18. R. Winkelmann, 1998. "Count data models with selectivity," Econometric Reviews, Taylor & Francis Journals, vol. 17(4), pages 339-359.
    19. Kaparakis, Emmanuel I & Miller, Stephen M & Noulas, Athanasios G, 1994. "Short-Run Cost Inefficiency of Commercial Banks: A Flexible Stochastic Frontier Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(4), pages 875-893, November.
    20. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    21. William H. Greene, 1995. "Sample Selection in the Poisson Regression Model," Working Papers 95-06, New York University, Leonard N. Stern School of Business, Department of Economics.
    22. W. David Bradford & Andrew N. Kleit & Marie A. Krousel-Wood & Richard N. Re, 2001. "Stochastic Frontier Estimation Of Cost Models Within The Hospital," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 302-309, May.
    23. Newhouse, Joseph P., 1994. "Frontier estimation: How useful a tool for health economics?," Journal of Health Economics, Elsevier, vol. 13(3), pages 317-322, October.
    24. Boyes, William J. & Hoffman, Dennis L. & Low, Stuart A., 1989. "An econometric analysis of the bank credit scoring problem," Journal of Econometrics, Elsevier, vol. 40(1), pages 3-14, January.
    25. Wang, Hung-Jen, 2006. "Stochastic frontier models," MPRA Paper 31079, University Library of Munich, Germany.
    26. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    27. 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

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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