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DEA and benchmarks – an application to Nordic banks

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  • Göran Bergendahl

Abstract

In this paper, Data Envelopment Analysis (DEA) is developed to analyze the efficiencyof a single bank. The inputs are given in terms of cost of personnel, cost of material andexpected cost of credit losses. Outputs concern lending, deposits and gross revenues (interestmargins and non-interest income). The data covers 48 large Nordic banks during the twoyears 1992 and 1993. Fourteen banks are from Denmark, thirteen from Finland, twelve fromNorway and nine from Sweden. For each of these banks, the DEA method is used to form a“reference bank”, which is a convex combination of the best competing banks (those at theefficiency frontier). The three inputs and the three outputs of the reference bank will beused as benchmarks. This procedure implies that one can only say that one single bank isless efficient than its reference bank, not less efficient than another bank. The results showthat 4-7 Nordic banks were situated at the efficiency frontier for those two years. Thesebanks should then be used to form reference banks for other banks, and to set benchmarksfor them. Such benchmarks would have been slightly different, dependent on the “window”to be used, 1992, 1993 or 1992 + 1993. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Göran Bergendahl, 1998. "DEA and benchmarks – an application to Nordic banks," Annals of Operations Research, Springer, vol. 82(0), pages 233-250, August.
  • Handle: RePEc:spr:annopr:v:82:y:1998:i:0:p:233-250:10.1023/a:1018910719517
    DOI: 10.1023/A:1018910719517
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    Cited by:

    1. Dafydd Mali & Hyoung-Joo Lim, 2022. "Does relative (absolute) efficiency affect capital costs?," Annals of Operations Research, Springer, vol. 315(2), pages 1037-1060, August.
    2. Qiwei Xie & Yuanyuan Li & Lizheng Wang & Chao Liu, 2018. "Improving discrimination in data envelopment analysis without losing information based on Renyi’s entropy," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1053-1068, December.
    3. Dimitras, Augustinos I. & Gaganis, Chrysovalantis & Pasiouras, Fotios, 2018. "Financial reporting standards' change and the efficiency measures of EU banks," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 223-233.
    4. George Anayiotos & Hovhannes Toroyan & Athanasios Vamvakidis, 2010. "The efficiency of emerging Europe’s banking sector before and after the recent economic crisis," Financial Theory and Practice, Institute of Public Finance, vol. 34(3), pages 247-267.
    5. 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.
    6. Manogna R. L. & Aswini Kumar Mishra, 2022. "Agricultural production efficiency of Indian states: Evidence from data envelopment analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4244-4255, October.
    7. Min-Chun Yu & Chia-Nan Wang & Nguyen-Nhu-Y Ho, 2016. "A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies," Sustainability, MDPI, vol. 8(9), pages 1-18, August.
    8. Qingxian An & Haoxun Chen & Jie Wu & Liang Liang, 2015. "Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output," Annals of Operations Research, Springer, vol. 235(1), pages 13-35, December.
    9. David A Grigorian & Vlad Manole, 2006. "Determinants of Commercial Bank Performance in Transition: An Application of Data Envelopment Analysis," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 48(3), pages 497-522, September.
    10. Christopoulos, Apostolos G. & Dokas, Ioannis G. & Katsimardou, Sofia & Spyromitros, Eleftherios, 2020. "Assessing banking sectors’ efficiency of financially troubled Eurozone countries," Research in International Business and Finance, Elsevier, vol. 52(C).
    11. Bergendahl, Goran & Lindblom, Ted, 2008. "Evaluating the performance of Swedish savings banks according to service efficiency," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1663-1673, March.
    12. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    13. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    14. Simon de Blas, Clara & Simon Martin, Jose & Gomez Gonzalez, Daniel, 2018. "Combined social networks and data envelopment analysis for ranking," European Journal of Operational Research, Elsevier, vol. 266(3), pages 990-999.
    15. Adriel Martins de Freitas Branco & Alexandre Pereira Salgado Junior & Patrícia Benites Cava & Eduardo Falsarella Junior & Marco Antônio Alves de Souza Junior, 2017. "Efficiency of the Brazilian Banking System in 2014: A DEA-SBM Analysis," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(5), pages 1-2.
    16. Chih-Ching Yang, 2014. "An enhanced DEA model for decomposition of technical efficiency in banking," Annals of Operations Research, Springer, vol. 214(1), pages 167-185, March.
    17. Grigorian David & Manole Vlad, 2013. "Cross-Country Nonparametric Analysis of Bahrains Banking System," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 1(1), pages 23-38, July.
    18. Mehdiloozad, Mahmood & Mirdehghan, S. Morteza & Sahoo, Biresh K. & Roshdi, Israfil, 2015. "On the identification of the global reference set in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(3), pages 779-788.
    19. Emilios Galariotis & Iordanis Kalaitzoglou & Jacek Niklewski & Constantin Zopounidis, 2021. "Optimal level of state ownership in banks: prevention measure versus emergency action—evidence from the new millennia," Annals of Operations Research, Springer, vol. 304(1), pages 165-197, September.
    20. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    21. Apostolos Christopoulos & Ioannis Dokas & Sofia Katsimardou & Eleftherios Spyromitros, 2022. "The Malmquist Productivity measure for UK-listed firms in the aftermath of the global financial crisis," Operational Research, Springer, vol. 22(2), pages 1617-1634, April.
    22. S. Adnan H. A. S. Bukhari & Safdar Ullah Khan, 2008. "Estimating Output Gap for Pakistan Economy: Structural and Statistical Approaches," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 4, pages 31-60.

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