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A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation

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  • Indranil Bardhan
  • William Cooper
  • Subal Kumbhakar

Abstract

A previous paper by Arnold, Bardhan, Cooper and Kumbhakar (1996) introduced a very simple method to estimate a production frontier by proceeding in two stages as follows: Data Envelopment Analysis (DEA) is used in the first stage to identify efficient and inefficient decision-making units (DMUs). In the second stage the thus identified DMUs are incorporated as dummy variables in OLS (ordinary least squares) regressions. This gave very satisfactory results for both the efficient and inefficient DMUs. Here a simulation study provides additional evidence. Using this same two-stage approach with Cobb-Douglas and CES (constant elasticity-of-substitution) production functions, the estimated values for the coefficients associated with efficient DMUs are found to be not significantly different from the true parameter values for the (known) production functions whereas the parameter estimates for the inefficient DMUs are significantly different. A separate section of the present paper is devoted to explanations of these results. Other sections describe methods for estimating input-specific inefficiencies from the first stage use of DEA in the two-stage approaches. A concluding section provides further directions for research and use. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Indranil Bardhan & William Cooper & Subal Kumbhakar, 1998. "A Simulation Study of Joint Uses of Data Envelopment Analysis and Statistical Regressions for Production Function Estimation and Efficiency Evaluation," Journal of Productivity Analysis, Springer, vol. 9(3), pages 249-278, March.
    • Handle: RePEc:kap:jproda:v:9:y:1998:i:3:p:249-278
    DOI: 10.1023/A:1018339122236
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    Cited by:

    1. Shafer, Scott M. & Byrd, Terry A., 2000. "A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis," Omega, Elsevier, vol. 28(2), pages 125-141, April.
    2. Banker, Rajiv D. & Chang, Hsihui & Cooper, William W., 2004. "A simulation study of DEA and parametric frontier models in the presence of heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 153(3), pages 624-640, March.
    3. Barua, Anitesh & Brockett, P. L. & Cooper, W. W. & Deng, Honghui & Parker, Barnett R. & Ruefli, T. W. & Whinston, A., 2004. "DEA evaluations of long- and short-run efficiencies of digital vs. physical product "dot com" companies," Socio-Economic Planning Sciences, Elsevier, vol. 38(4), pages 233-253, December.
    4. R B van der Meer & J Quigley & J E Storbeck, 2005. "Using data envelopment analysis to model the performance of UK coastguard centres," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 889-901, August.
    5. Phillip Fanchon, 2003. "Variable selection for dynamic measures of efficiency in the computer industry," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 9(3), pages 175-188, August.
    6. Brockett, Patrick L. & Cooper, W.W. & Golden, Linda L. & Kumbhakar, Subal C. & Kwinn Jr., Michael J. & Layton, Brian & Parker, Barnett R., 2008. "Estimating elasticities with frontier and other regressions in evaluating two advertising strategies for US Army recruiting," Socio-Economic Planning Sciences, Elsevier, vol. 42(1), pages 1-17, March.
    7. Perelman, Sergio & Santín, Daniel, 2009. "How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement," European Journal of Operational Research, Elsevier, vol. 199(1), pages 303-310, November.
    8. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.
    9. Vincenzo Patrizii & Giuliano Resce, 2015. "Public Sector Contribution To Competitiveness," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(3), pages 401-443, November.
    10. R B Van der Meer & J Quigley & J E Storbeck, 2005. "Using regression analysis to model the performance of UK Coastguard centres," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 630-641, June.
    11. Parmeter, Christopher F., 2021. "Is it MOLS or COLS?," Efficiency Series Papers 2021/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Khezrimotlagh, Dariush, 2022. "Simulation designs for production frontiers," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1321-1334.
    13. Brandon Pope & Andrew Johnson, 2013. "Returns to scope: a metric for production synergies demonstrated for hospital production," Journal of Productivity Analysis, Springer, vol. 40(2), pages 239-250, October.
    14. P L Brockett & W W Cooper & S C Kumbhakar & M J Kwinn & D McCarthy, 2004. "Alternative statistical regression studies of the effects of Joint and Service Specific advertising on military recruitment," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1039-1048, October.
    15. Rossi, Martin Antonio & Ruzzier, Christian Alejandro, 2000. "On the regulatory application of efficiency measures," Utilities Policy, Elsevier, vol. 9(2), pages 81-92, June.
    16. Shih, Jhih-Shyang & Harrington, Winston & Pizer, William A. & Gillingham, Kenneth, 2004. "Economies of Scale and Technical Efficiency in Community Water Systems," Discussion Papers 10788, Resources for the Future.
    17. Krüger, Jens J., 2012. "A Monte Carlo study of old and new frontier methods for efficiency measurement," European Journal of Operational Research, Elsevier, vol. 222(1), pages 137-148.
    18. Lucyna BŁAŻEJCZYK-MAJKA & Radosław KALA, 2015. "On the combined estimation of technical efficiency and its application to agriculture," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(10), pages 441-449.
    19. Banker, R. D. & Chang, H. S. & Cooper, W. W., 2002. ""Small sample properties of ML, COLS and DEA estimators of frontier models in the presence of heteroscedasticity" by A.N. Bojanic, S.B. Caudill and J.M. Ford, European Journal of Operational," European Journal of Operational Research, Elsevier, vol. 136(2), pages 466-467, January.
    20. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    21. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    22. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    23. Groot, Tom & Garcia-Valderrama, Teresa, 2006. "Research quality and efficiency: An analysis of assessments and management issues in Dutch economics and business research programs," Research Policy, Elsevier, vol. 35(9), pages 1362-1376, November.
    24. Adler, Nicole & Raveh, Adi, 2008. "Presenting DEA graphically," Omega, Elsevier, vol. 36(5), pages 715-729, October.

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