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Categorical Variables in DEA

Author

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  • Finn R. Forsund

    (Department of Economics, University of Oslo, Norway)

Abstract

The standard DEA model can be applied to a mix of categorical and continuous variables by entering all combinations of them as different types of inputs and/or outputs. Theoretical implications for the nature of feasible peers are investigated.

Suggested Citation

  • Finn R. Forsund, 2002. "Categorical Variables in DEA," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(1), pages 33-44, April.
    • Handle: RePEc:ijb:journl:v:1:y:2002:i:1:p:33-44
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    References listed on IDEAS

    as
    1. Wagner A. Kamakura, 1988. "Note---A Note on "The Use of Categorical Variables in Data Envelopment Analysis"," Management Science, INFORMS, vol. 34(10), pages 1273-1276, October.
    2. Finn R. Førsund & Roberto Zanola, 2001. "Selling Picasso paintings: the efficiency of auction houses," ICER Working Papers 07-2001, ICER - International Centre for Economic Research.
    3. Jaume Puig‐Junoy, 1998. "Technical efficiency in the clinical management of critically ill patients," Health Economics, John Wiley & Sons, Ltd., vol. 7(3), pages 263-277, May.
    4. John J. Rousseau & John H. Semple, 1993. "Notes: Categorical Outputs in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(3), pages 384-386, March.
    5. Rajiv D. Banker & Richard C. Morey, 1986. "The Use of Categorical Variables in Data Envelopment Analysis," Management Science, INFORMS, vol. 32(12), pages 1613-1627, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Finn Forsund & Roberto Zanola, 2002. "The performance of auction houses selling Picasso prints," Others 0210003, University Library of Munich, Germany.
    2. Finn Førsund & Roberto Zanola, 2006. "The art of benchmarking: Picasso prints and auction house performance," Applied Economics, Taylor & Francis Journals, vol. 38(12), pages 1425-1434.
    3. Syrjanen, Mikko J., 2004. "Non-discretionary and discretionary factors and scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 158(1), pages 20-33, October.
    4. 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.
    5. Rodrigo Gómez Monge, 2012. "El sector bancario en México, los depósitos a plazo y las cuentas de ahorro: un análisis de eficiencia durante el periodo de internacionalización a través de la envolvente de datos (dea)," Revista Ciencias Estratégicas, Universidad Pontificia Bolivariana, June.
    6. Löber, Gerrit & Staat, Matthias, 2010. "Integrating categorical variables in Data Envelopment Analysis models: A simple solution technique," European Journal of Operational Research, Elsevier, vol. 202(3), pages 810-818, May.
    7. Finn R. Førsund & Roberto Zanola, 2001. "Selling Picasso paintings: the efficiency of auction houses," ICER Working Papers 07-2001, ICER - International Centre for Economic Research.
    8. Qayyum, Abdul & Ahmed, Munir, 2006. "Efficiency and Sustainability of Micro Finance Institutions in South Asia," MPRA Paper 85467, University Library of Munich, Germany, revised 2014.

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    More about this item

    Keywords

    categorical variable; DEA; efficiency; linear programming; peer;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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