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Cost Allocation and Convex Data Envelopment

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  • Jens Leth Hougaard

    (Department of Economics, University of Copenhagen)

  • Jørgen Tind

    (Department of Mathematical Sciences, University of Copenhagen)

Abstract

This paper considers allocation rules. First, we demonstrate that costs allocated by the Aumann-Shapley and the Friedman-Moulin cost allocation rules are easy to determine in practice using convex envelopment of registered cost data and parametric programming. Second, from the linear programming problems involved it becomes clear that the allocation rules, technically speaking, allocate the non-zero value of the dual variable for a convexity constraint on to the output vector. Hence, the allocation rules can also be used to allocate inefficiencies in non-parametric efficiency measurement models such as Data Envelopment Analysis (DEA). The convexity constraint of the BCC model introduces a non-zero slack in the objective function of the multiplier problem and we show that the cost allocation rules discussed in this paper can be used as candidates to allocate this slack value on to the input (or output) variables and hence enable a full allocation of the inefficiency on to the input (or output) variables as in the CCR model.

Suggested Citation

  • Jens Leth Hougaard & Jørgen Tind, 2008. "Cost Allocation and Convex Data Envelopment," Discussion Papers 08-02, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:0802
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    References listed on IDEAS

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    Cited by:

    1. Albizuri, M.J. & Díez, H. & Sarachu, A., 2014. "Monotonicity and the Aumann–Shapley cost-sharing method in the discrete case," European Journal of Operational Research, Elsevier, vol. 238(2), pages 560-565.
    2. Jens Leth Hougaard & Jørgen Tind, 2013. "Cost Allocation with Limited Information," MSAP Working Paper Series 01_2013, University of Copenhagen, Department of Food and Resource Economics.
    3. Bogetoft, Peter & Hougaard, Jens Leth & Smilgins, Aleksandrs, 2016. "Applied cost allocation: The DEA–Aumann–Shapley approach," European Journal of Operational Research, Elsevier, vol. 254(2), pages 667-678.
    4. Aldanondo, Ana M. & Casasnovas, Valero L., 2016. "A note on the impact of multiple input aggregators in technical efficiency estimation," MPRA Paper 75290, University Library of Munich, Germany.

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    Keywords

    cost allocation; convex envelopment; data envelopment analysis; slack allocation;
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