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How to generate regularly behaved production data? A Monte Carlo experimentation on DEA scale efficiency measurement

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  • Perelman, Sergio
  • Santín, Daniel

Abstract

Monte Carlo experimentation is a well-known approach used to test the performance of alternative methodologies under different hypotheses. In the frontier analysis framework, whatever the parametric or non-parametric methods tested, experiments to date have been developed assuming single output multi-input production functions. The data generated have mostly assumed a Cobb-Douglas technology. Among other drawbacks, this simple framework does not allow the evaluation of DEA performance on scale efficiency measurement. The aim of this paper is twofold. On the one hand, we show how reliable two-output two-input production data can be generated using a parametric output distance function approach. A variable returns to scale translog technology satisfying regularity conditions is used for this purpose. On the other hand, we evaluate the accuracy of DEA technical and scale efficiency measurement when sample size and output ratios vary. Our Monte Carlo experiment shows that the correlation between true and estimated scale efficiency is dramatically low when DEA analysis is performed with small samples and wide output ratio variations.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:199:y:2009:i:1:p:303-310
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    References listed on IDEAS

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    Cited by:

    1. Brissimis, Sophocles N. & Zervopoulos, Panagiotis D., 2012. "Developing a step-by-step effectiveness assessment model for customer-oriented service organizations," European Journal of Operational Research, Elsevier, vol. 223(1), pages 226-233.
    2. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
    3. Mark Andor & Frederik Hesse, "undated". "The StoNED age: The Departure Into a New Era of Efficiency Analysis? An MC study Comparing StoNED and the "Oldies" (SFA and DEA)," Working Papers 201285, Institute of Spatial and Housing Economics, Munster Universitary.
    4. Géraldine Henningsen & Arne Henningsen & Uwe Jensen, 2015. "A Monte Carlo study on multiple output stochastic frontiers: a comparison of two approaches," Journal of Productivity Analysis, Springer, vol. 44(3), pages 309-320, December.
    5. repec:eee:ejores:v:262:y:2017:i:2:p:792-801 is not listed on IDEAS
    6. Zervopoulos, Panagiotis, 2012. "Dealing with small samples and dimensionality issues in data envelopment analysis," MPRA Paper 39226, University Library of Munich, Germany.
    7. García-Alonso, Carlos R. & Salvador-Carulla, Luis & Fernández-Rodríguez, Vicente, 2015. "Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areasAuthor-Name: Torres-Jiménez, Mercedes," European Journal of Operational Research, Elsevier, vol. 242(2), pages 525-535.
    8. repec:gam:jsusta:v:9:y:2017:i:12:p:2080-:d:120466 is not listed on IDEAS
    9. 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.
    10. Julie Harrison & Paul Rouse & Jamie Armstrong, 2012. "Categorical and continuous non-discretionary variables in data envelopment analysis: a comparison of two single-stage models," Journal of Productivity Analysis, Springer, vol. 37(3), pages 261-276, June.
    11. Lars-Erik Borge & Marianne Haraldsvik, 2009. "Efficiency potential and determinants of efficiency: An analysis of the care of elderly sector in Norway," Working Paper Series 10109, Department of Economics, Norwegian University of Science and Technology.
    12. Andor, Mark & Hesse, Frederik, 2012. "The StoNED age: The departure into a new era of efficiency analysis? An MC study comparing StoNED and the "oldies" (SFA and DEA)," CAWM Discussion Papers 60, University of Münster, Center of Applied Economic Research Münster (CAWM).
    13. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.
    14. Kumbhakar, Subal C., 2012. "Specification and estimation of primal production models," European Journal of Operational Research, Elsevier, vol. 217(3), pages 509-518.
    15. Mellah, Thuraya & Ben Amor, Tawfik, 2016. "Performance of the Tunisian Water Utility: An input-distance function approach," Utilities Policy, Elsevier, vol. 38(C), pages 18-32.

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