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Removing the impact of environment with units-invariant efficient frontier analysis: An illustrative case study with intertemporal panel data

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  • Avkiran, Necmi K.
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    Abstract

    The four-stage methodology consists of a units-invariant efficient frontier analysis followed by Tobit regression, adjustment of data, and a repeat of the efficient frontier analysis. The outlined methodology is an improvement over existing similar approaches because the playing field can be levelled by adjusting data based on input as well as output slacks for managers who may have been advantaged or disadvantaged by their environments. The accompanying case study investigates the influence of the general level of interest rates on bank efficiency using intertemporal panel data spanning 8 years and two countries. Key findings support the assertion that changes in interest rates can distort measurement of bank efficiency.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 37 (2009)
    Issue (Month): 3 (June)
    Pages: 535-544

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    Handle: RePEc:eee:jomega:v:37:y:2009:i:3:p:535-544

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    Keywords: DEA Efficiency Case study Banking;

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    Cited by:
    1. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    2. Bernad, Cristina & Fuentelsaz, Lucio & Gómez, Jaime, 2010. "The effect of mergers and acquisitions on productivity: An empirical application to Spanish banking," Omega, Elsevier, vol. 38(5), pages 283-293, October.
    3. Karligash Kenjegalieva & Maximilian J. B. Hall & Richard Simper, 2008. "Environmental Factors Affecting Hong Kong Banking: A Post-Asian Financial Crisis Efficiency Analysis," Discussion Paper Series 2008-01, Department of Economics, Loughborough University, revised Jun 2008.
    4. Edelstein, Barak & Paradi, Joseph C., 2013. "Ensuring units invariant slack selection in radial data envelopment analysis models, and incorporating slacks into an overall efficiency score," Omega, Elsevier, vol. 41(1), pages 31-40.
    5. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.
    6. Chen, Kaihua, 2014. "Weighted Additive DEA Models Associated with Dataset Standardization Techniques," MPRA Paper 55072, University Library of Munich, Germany.
    7. Kuosmanen, Timo & Kazemi Matin, Reza, 2011. "Duality of weakly disposable technology," Omega, Elsevier, vol. 39(5), pages 504-512, October.
    8. Odeck, James, 2009. "Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers," Omega, Elsevier, vol. 37(5), pages 1007-1017, October.
    9. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    10. Avkiran, Necmi K., 2009. "Opening the black box of efficiency analysis: An illustration with UAE banks," Omega, Elsevier, vol. 37(4), pages 930-941, August.
    11. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.

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