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Estimating DEA technical and allocative inefficiency using aggregate cost or revenue data

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  • Rajiv Banker

    ()

  • Hsihui Chang

    ()

  • Ram Natarajan

    ()

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    Abstract

    In this paper, we address the question of Data Envelopment Analysis (DEA) evaluation of efficiency when aggregate cost or revenue data must be used. We show that the DEA technical inefficiency measure using total revenues as the single output variable or total costs as the single input variable equals the aggregate technical and allocative inefficiency. We employ this result to estimate allocative inefficiency and construct statistical tests of the null hypothesis of no allocative inefficiency analogous to those of the null hypothesis of no scale inefficiency. We illustrate our method using revenue and personnel data for the top U.S. public accounting firms over 1995–1998. Our empirical results indicate the existence of statistically significant allocative inefficiency in the public accounting industry. Copyright Springer Science+Business Media, LLC 2007

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    File URL: http://hdl.handle.net/10.1007/s11123-006-0027-1
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    Bibliographic Info

    Article provided by Springer in its journal Journal of Productivity Analysis.

    Volume (Year): 27 (2007)
    Issue (Month): 2 (April)
    Pages: 115-121

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    Handle: RePEc:kap:jproda:v:27:y:2007:i:2:p:115-121

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    Web page: http://www.springerlink.com/link.asp?id=100296

    Related research

    Keywords: Data envelopment analysis; Aggregate cost data; Aggregate revenue data; Technical inefficiency; Allocative inefficiency; Public accounting; D24; L11; M41;

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    References

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    1. Bhattacharyya, Arunava & Lovell, C. A. K. & Sahay, Pankaj, 1997. "The impact of liberalization on the productive efficiency of Indian commercial banks," European Journal of Operational Research, Elsevier, Elsevier, vol. 98(2), pages 332-345, April.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, Elsevier, vol. 2(6), pages 429-444, November.
    3. Banker, Rajiv D & Maindiratta, Ajay, 1988. "Nonparametric Analysis of Technical and Allocative Efficiencies in Production," Econometrica, Econometric Society, Econometric Society, vol. 56(6), pages 1315-32, November.
    4. Schaffnit, Claire & Rosen, Dan & Paradi, Joseph C., 1997. "Best practice analysis of bank branches: An application of DEA in a large Canadian bank," European Journal of Operational Research, Elsevier, Elsevier, vol. 98(2), pages 269-289, April.
    5. Banker, Rajiv D. & Chang, Hsihui & Cunningham, Reba, 2003. "The public accounting industry production function," Journal of Accounting and Economics, Elsevier, Elsevier, vol. 35(2), pages 255-281, June.
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    Cited by:
    1. Mircea Epure, 2012. "Benchmarking for routines and organizational knowledge," Economics Working Papers 1399, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2013.
    2. Banker, Rajiv D. & Chang, Hsihui & Lee, Seok-Young, 2010. "Differential impact of Korean banking system reforms on bank productivity," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1450-1460, July.
    3. Ray, Subhash C. & Chen, Lei & Mukherjee, Kankana, 2008. "Input price variation across locations and a generalized measure of cost efficiency," International Journal of Production Economics, Elsevier, Elsevier, vol. 116(2), pages 208-218, December.

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