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Using a modified DEA model to estimate the importance of objectives. An application to agricultural economics

Author

Listed:
  • Francisco J. André

    (Department of Economics, Universidad Pablo de Olavide)

  • Inés Herrero

    (Department of Business Administration, Universidad Pablo de Olavide)

  • Laura Riesgo

    (Department of Economics, Universidad Pablo de Olavide)

Abstract

This paper shows a connection between Data Envelopment Analysis (DEA) and the methodology proposed by Sumpsi et al. (1997) to estimate the weights of objectives for decision makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of Multiple Attribute Decision Analysis the basic contribution of this paper is a new interpretation of the methodology by Sumpsi et al. (1997) in terms of efficiency. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures which does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.

Suggested Citation

  • 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.
    • Handle: RePEc:pab:wpaper:07.09
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    References listed on IDEAS

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    More about this item

    Keywords

    Multicriteria Decision Making; Goal Programming; Weights; Preferences; Data Envelopment Analysis.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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