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Marginal Rates and Two-dimensional Level Curves in DEA

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  • Dan Rosen
  • Claire Schaffnit
  • Joseph Paradi

Abstract

Of great importance to management, the computation of trade-offs presents particular difficulties within DEA since the piecewise linear nature of the envelopment surfaces does not allow for unique derivatives at every point. We present a comprehensive framework for analyzing marginal rates, and directional derivatives in general, on DEA frontiers. A useful characterization of these derivatives at given points can be provided in terms of the ranges they can take; equivalently, the bounds of these ranges correspond to derivatives “to the right”and “to the left” at these points. We present two approaches for their computation: first, the dual equivalents calculation of minimum and maximum multiplier ratios / finite differences, and then a modified simplex tableau method. The simplex tableau method provides a more general application of the method introduced by Hackman et al. (1994) to generate any two-dimensional section of the isoquant and is a practical tool to generate level plots of the frontier. By giving a complete picture of trade-offs and allowing a better visualization of high dimensional production possibility sets, these tools can be very useful for managerial applications. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Dan Rosen & Claire Schaffnit & Joseph Paradi, 1998. "Marginal Rates and Two-dimensional Level Curves in DEA," Journal of Productivity Analysis, Springer, vol. 9(3), pages 205-232, March.
  • Handle: RePEc:kap:jproda:v:9:y:1998:i:3:p:205-232
    DOI: 10.1023/A:1018382904489
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    Cited by:

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    2. Bana e Costa, Carlos A. & Soares de Mello, João Carlos C.B. & Angulo Meza, Lidia, 2016. "A new approach to the bi-dimensional representation of the DEA efficient frontier with multiple inputs and outputs," European Journal of Operational Research, Elsevier, vol. 255(1), pages 175-186.
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    5. Victor V. Podinovski & Finn R. Førsund, 2010. "Differential Characteristics of Efficient Frontiers in Data Envelopment Analysis," Operations Research, INFORMS, vol. 58(6), pages 1743-1754, December.
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    7. Peixin Duan, 2022. "How large of a grant size is appropriate? Evidence from the National Natural Science Foundation of China," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-14, February.
    8. S.T. Hackman & U. Passy, 2002. "Maximizing a Linear Fractional Function on a Pareto Efficient Frontier," Journal of Optimization Theory and Applications, Springer, vol. 113(1), pages 83-103, April.
    9. Walter Briec & Kristiaan Kerstens & Hervé Leleu & Philippe Eeckaut, 2000. "Returns to Scale on Nonparametric Deterministic Technologies: Simplifying Goodness-of-Fit Methods Using Operations on Technologies," Journal of Productivity Analysis, Springer, vol. 14(3), pages 267-274, November.
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    12. Noah J Miller & Jason S Bergtold & Allen M Featherstone, 2019. "Economic elasticities of input substitution using data envelopment analysis," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-15, August.
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    14. Garcia-Cestona, Miguel & Surroca, Jordi, 2008. "Multiple goals and ownership structure: Effects on the performance of Spanish savings banks," European Journal of Operational Research, Elsevier, vol. 187(2), pages 582-599, June.
    15. Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    16. Kenneth Løvold Rødseth, 2017. "Environmental regulations and allocative efficiency: application to coal-to-gas substitution in the U.S. electricity sector," Journal of Productivity Analysis, Springer, vol. 47(2), pages 129-142, April.
    17. Ángel M. Prieto & José L. Zofío, 2004. "Stock splits: Modelización de la gestión ambiental preventiva mediante estándares," Investigaciones Economicas, Fundación SEPI, vol. 28(1), pages 43-66, January.
    18. Victor V. Podinovski & Robert G. Chambers & Kazim Baris Atici & Iryna D. Deineko, 2016. "Marginal Values and Returns to Scale for Nonparametric Production Frontiers," Operations Research, INFORMS, vol. 64(1), pages 236-250, February.
    19. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    20. Francisco J. André & Inés Herrero & Laura Riesgo, 2007. "Using a modified DEA model to estimate the importance of objectives. An application to agricultural economics," Working Papers 07.09, Universidad Pablo de Olavide, Department of Economics.
    21. A. Ghazi & F. Hosseinzadeh Lotfi, 2023. "Marginal rates in DEA using defining hyperplanes of PPS with CRS technology," Operational Research, Springer, vol. 23(1), pages 1-37, March.
    22. Usman Akbar & Muhammad Asif Khan & Marryum Akmal & Éva Zsuzsanna Tóth Naárné & Judit Oláh, 2020. "Trade-Offs for the Optimal Energy Efficiency of Road Transportation: Domestic Cases in Developing Countries," Energies, MDPI, vol. 13(24), pages 1-14, December.
    23. Francisco J. André & Inés Herrero & Laura Riesgo, 2004. "Using DEA to estimate the importance of objectives for decision makers," Economic Working Papers at Centro de Estudios Andaluces E2004/50, Centro de Estudios Andaluces.
    24. Eliane Gomes & João Soares de Mello & Geraldo Souza & Lidia Angulo Meza & João Mangabeira, 2009. "Efficiency and sustainability assessment for a group of farmers in the Brazilian Amazon," Annals of Operations Research, Springer, vol. 169(1), pages 167-181, July.

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