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Aggregate efficiency measures and Simpson's Paradox

Author

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  • ABRAHAM MEHREZ
  • J. RANDALL BROWN
  • MOUTAZ KHOUJA

Abstract

. Much work has been directed to develop aggregate efficiency measures for firms or decision†making units (DMUs) in which we are able to observe only the outputs and inputs. Assuming that each DMU has the same type of observed outputs and inputs and using only this information, Farrell's technical efficiency and the CCR ratio can be used to assign an aggregate measure of efficiency to each DMU, which can then be used to compare the efficiency of the DMUs. This paper considers a subset of the general aggregate efficiency problem called the matched output/input case in which each output is matched to exactly one input, forming a subunit. Dividing the output by the input for each subunit within a DMU yields a subunit ratio that is the output per unit input. For a particular subunit, the subunit ratios for two DMUs can be compared directly. If all the subunit ratios of one DMU exceed the corresponding subunit ratios in another DMU, then we should reasonably expect that any aggregate efficiency measure has the efficiency of the first DMU greater than the efficiency of the other DMU. This requirement is defined as the Matched Output/Input Axiom, which is then shown to be violated for certain data sets satisfying Simpson's Paradox. Both Farrell's technical efficiency and the CCR ratio are then shown to violate the Matched Output/Input Axiom, which raises questions about the overall validity of both procedures. Résumé. Les travaux visant l'élaboration de mesures globales du rendement des unités décisionnelles ou des entreprises, dans lesquelles il n'est possible d'observer que les extrants et les intrants, sont nombreux. En supposant que le même type d'extrants et d'intrants est observé pour chaque unité décisionnelle et que cette information est la seule qui soit utilisée, le rendement technique de Farrell et le ratio CCR (Charnes, Cooper et Rhodes) peuvent être utilisés pour attribuer une mesure globale de rendement à chaque unité décisionnelle, mesure qui peut ensuite permettre de comparer le rendement des différentes unités. Les auteurs étudient un sous†ensemble du problème général de rendement global, le cas de concordance extrant†intrant, dans lequel chaque extrant est associé à exactement un intrant, pour former un sous†ensemble. En divisant l'extrant par l'intrant pour chaque sous†ensemble d'une unité décisionnelle, on obtient, pour chacun d'eux, un ratio représentant l'extrant par unité d'intrant. Pour un sous†ensemble particulier, les ratios de deux unités décisionnelles peuvent faire l'objet d'une comparaison directe. Si la totalité des ratios des sous†ensembles d'une unité décisionnelle excède la totalité des ratios des sous†ensembles correspondants d'une autre unité décisionnelle, on est en droit de s'attendre à ce que l'application d'une mesure globale du rendement, quelle qu'elle soit, indique que le rendement de la première unité est supérieur à celui de la seconde. Les auteurs démontrent que ce principe, défini comme étant l'axiome de concordance extrant†intrant, est transgressé pour certains ensembles de données répondant aux critères du paradoxe de Simpson. Ils démontrent également que le rendement technique de Farrell ainsi que le ratio CCR dérogent à l'axiome de concordance extrant†intrant, ce qui les amène à s'interroger sur la validité globale des deux procédés.

Suggested Citation

  • Abraham Mehrez & J. Randall Brown & Moutaz Khouja, 1992. "Aggregate efficiency measures and Simpson's Paradox," Contemporary Accounting Research, John Wiley & Sons, vol. 9(1), pages 329-342, September.
  • Handle: RePEc:wly:coacre:v:9:y:1992:i:1:p:329-342
    DOI: 10.1111/j.1911-3846.1992.tb00884.x
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    References listed on IDEAS

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    1. Sunder, S, 1983. "Simpson Reversal Paradox And Cost Allocation," Journal of Accounting Research, Wiley Blackwell, vol. 21(1), pages 222-233.
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    5. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    6. Sherman, H. David & Gold, Franklin, 1985. "Bank branch operating efficiency : Evaluation with Data Envelopment Analysis," Journal of Banking & Finance, Elsevier, vol. 9(2), pages 297-315, June.
    7. Charnes, A. & Cooper, W. W., 1980. "Auditing and accounting for program efficiency and management efficiency in not-for-profit entities," Accounting, Organizations and Society, Elsevier, vol. 5(1), pages 87-107, January.
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    1. Rajiv D. Banker, 1992. "Selection of efficiency evaluation models," Contemporary Accounting Research, John Wiley & Sons, vol. 9(1), pages 343-355, September.

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