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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.

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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  • Avkiran, Necmi K., 2009. "Removing the impact of environment with units-invariant efficient frontier analysis: An illustrative case study with intertemporal panel data," Omega, Elsevier, vol. 37(3), pages 535-544, June.
  • Handle: RePEc:eee:jomega:v:37:y:2009:i:3:p:535-544
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    Cited by:

    1. 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.
    2. 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.
    3. Aiello, Francesco & Bonanno, Graziella, 2014. "On the Sources of Heterogeneity in Banking Efficiency Literature," MPRA Paper 58591, University Library of Munich, Germany.
    4. Fiordelisi, Franco & Molyneux, Phil, 2010. "Total factor productivity and shareholder returns in banking," Omega, Elsevier, vol. 38(5), pages 241-253, October.
    5. Francesco Aiello & Graziella Bonanno, 2016. "Efficiency in banking: a meta-regression analysis," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(1), pages 112-149, January.
    6. Brunilda DURAJ & Elvana MOCI, 2015. "Factors Influencing The Bank Profitability – Empirical Evidence From Albania," Romanian Economic Business Review, Romanian-American University, vol. 10(1), pages 60-72, March.
    7. 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.
    8. Liadaki, Aggeliki & Gaganis, Chrysovalantis, 2010. "Efficiency and stock performance of EU banks: Is there a relationship?," Omega, Elsevier, vol. 38(5), pages 254-259, October.
    9. 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.
    10. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    11. 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.
    12. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2015. "Reprint of “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 74(C), pages 22-36.
    13. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    14. Kuosmanen, Timo & Kazemi Matin, Reza, 2011. "Duality of weakly disposable technology," Omega, Elsevier, vol. 39(5), pages 504-512, October.
    15. Chen, Kaihua, 2014. "Weighted Additive DEA Models Associated with Dataset Standardization Techniques," MPRA Paper 55072, University Library of Munich, Germany.
    16. 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.
    17. Zha, Yong & Liang, Nannan & Wu, Maoguo & Bian, Yiwen, 2016. "Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach," Omega, Elsevier, vol. 60(C), pages 60-72.
    18. Hirofumi Fukuyama & William Weber, 2015. "Measuring Japanese bank performance: a dynamic network DEA approach," Journal of Productivity Analysis, Springer, vol. 44(3), pages 249-264, December.
    19. repec:kap:jproda:v:48:y:2017:i:1:d:10.1007_s11123-017-0504-8 is not listed on IDEAS
    20. Hall, Maximilian J.B. & Kenjegalieva, Karligash A. & Simper, Richard, 2012. "Environmental factors affecting Hong Kong banking: A post-Asian financial crisis efficiency analysis," Global Finance Journal, Elsevier, vol. 23(3), pages 184-201.
    21. Asmild, Mette & Pastor, Jesús T., 2010. "Slack free MEA and RDM with comprehensive efficiency measures," Omega, Elsevier, vol. 38(6), pages 475-483, December.
    22. Azadi, Majid & Shabani, Amir & Khodakarami, Mohsen & Farzipoor Saen, Reza, 2014. "Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 324-338.
    23. 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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    DEA Efficiency Case study Banking;

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