A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity
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Bibliographic Info
Article provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 153 (2004)
Issue (Month): 3 (March)
Pages: 624-640
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Web page: http://www.elsevier.com/locate/eor
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- Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
- Bojani, Antonio N. & Caudill, Steven B. & Ford, Jon M., 1998. "Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 108(1), pages 140-148, July.
- Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
- Schmidt, Peter, 1976. "On the Statistical Estimation of Parametric Frontier Production Functions," The Review of Economics and Statistics, MIT Press, vol. 58(2), pages 238-39, May.
- 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.
- 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.
- Richmond, J, 1974. "Estimating the Efficiency of Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 515-21, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- ChunpingLiu & Audrey Laporte & Brian Ferguson, 2007.
"The Quantile Regression Approach to Efficiency Measurement: Insights from Monte Carlo Simulations,"
Health, Econometrics and Data Group (HEDG) Working Papers
07/14, HEDG, c/o Department of Economics, University of York.
- Chunping Liu & Audrey Laporte & Brian S. Ferguson, 2008. "The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1073-1087.
- Giraleas, Dimitris & Emrouznejad, Ali & Thanassoulis, Emmanuel, 2012. "Selecting between different productivity measurement approaches: An application using EU KLEMS data," MPRA Paper 37965, University Library of Munich, Germany.
- José Lorenzo & Isabel Sánchez, 2007. "Efficiency evaluation in municipal services: an application to the street lighting service in Spain," Journal of Productivity Analysis, Springer, vol. 27(3), pages 149-162, June.
- Ahmed Salem Al-Eraqi & Carlos Pestana Barros & Adli Mustaffa & Ahamad Tajudin Khader, 2007. "Evaluating the Location Efficiency of Arabian and African Seaports Using Data Envelopment Analysis (DEA)," Working Papers 2007/19, Department of Economics at the School of Economics and Management (ISEG), Technical University of Lisbon..
- Xie, Xiaoying, 2010. "Are publicly held firms less efficient? Evidence from the US property-liability insurance industry," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1549-1563, July.
- Kyuseok Lee & Kyuwan Choi, 2010. "Cross redundancy and sensitivity in DEA models," Journal of Productivity Analysis, Springer, vol. 34(2), pages 151-165, October.
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