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Maintaining the Regular Ultra Passum Law in data envelopment analysis

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  • Olesen, Ole B.

    ()
    (Department of Business and Economics)

  • Ruggiero, John

    ()
    (School of Business Administration)

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    Abstract

    The variable returns to scale data envelopment analysis (DEA) model is developed with a maintained hypothesis of convexity in input-output space. This hypothesis is not consistent with standard microeconomic production theory that posits an S-shape for the production frontier, i.e. for production technologies that obey the Regular Ultra Passum Law. Consequently, measures of technical efficiency assuming convexity are biased downward. In this paper, we provide a more general DEA model that allows the S-shape.

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    File URL: http://static.sdu.dk/mediafiles//9/F/7/%7B9F7397A5-CBCD-4DDA-B9AE-CB4B1A3A5C14%7Ddpbe2_2012.pdf
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    Bibliographic Info

    Paper provided by Department of Business and Economics, University of Southern Denmark in its series Discussion Papers of Business and Economics with number 2/2012.

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    Length: 22 pages
    Date of creation: 04 Jan 2012
    Date of revision:
    Handle: RePEc:hhs:sdueko:2012_002

    Contact details of provider:
    Postal: Department of Business and Economics, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark
    Phone: 65 50 32 33
    Fax: 65 50 32 37
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    Web page: http://www.sdu.dk/ivoe
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    Related research

    Keywords: Data envelopment analysis; homothetic production; S-shaped production function; non-convex production set;

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    References

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    1. Olesen, Ole Bent & Petersen, Niels Christian, 2011. "Scale properties in data envelopment analysis," Discussion Papers of Business and Economics 4/2011, Department of Business and Economics, University of Southern Denmark.
    2. Ginsberg, William, 1974. "The multiplant firm with increasing returns to scale," Journal of Economic Theory, Elsevier, vol. 9(3), pages 283-292, November.
    3. Peter Bogetoft, 1996. "DEA on Relaxed Convexity Assumptions," Management Science, INFORMS, vol. 42(3), pages 457-465, March.
    4. Niels Christian Petersen, 1990. "Data Envelopment Analysis on a Relaxed Set of Assumptions," Management Science, INFORMS, vol. 36(3), pages 305-314, March.
    5. Fare, R & Primont, D, 1995. "On Inverse Homotheticity," Bulletin of Economic Research, Wiley Blackwell, vol. 47(2), pages 161-66, April.
    6. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    7. Podinovski, V. V., 2005. "Selective convexity in DEA models," European Journal of Operational Research, Elsevier, vol. 161(2), pages 552-563, March.
    8. Zellner, A & Revankar, N S, 1969. "Generalized Production Functions," Review of Economic Studies, Wiley Blackwell, vol. 36(106), pages 241-50, April.
    9. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    10. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
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    Cited by:
    1. Élisé Wendlassida Miningou & Valérie Vierstraete, 2012. "Households' living situation and the efficient provision of primary education in Burkina Faso," Cahiers de recherche 12-12, Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke.
    2. Olesen, Ole B., 2012. "A homothetic reference technology in Data Envelopment Analysis," Discussion Papers of Business and Economics 14/2012, Department of Business and Economics, University of Southern Denmark.
    3. Olesen, Ole B., 2014. "A homothetic reference technology in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 233(3), pages 759-771.

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