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Measurement of Banks’ Performance by Using Super-Efficiency DEA Model

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Part of the India Studies in Business and Economics book series (ISBE)

Abstract

Banks play a crucial role in channelization of untapped saving into productive uses. This chapter makes an attempt to judge the performance of the banking sector in India since the 1990s, by using data envelopment analysis (DEA)-based super-efficiency model during the period 1992–2012. We find that the performance of the public sector banks improved during the 2002–2012 period in comparison with 1992–2001 Also, the public sector banks witnessed comparatively lesser degree of variation in the efficiency score in comparison with the new private section and the foreign banks. We also find that non-traditional activities play a key role in determining the level of efficiency of the banks in the post-reforms period. Size (in terms of total assets, not in terms of the number of bank branches) and dominance in the deposit market can provide the banks the necessary leeway to embrace technology-embedded products and services. Finally, the study also pinpoints the adverse effect of asset quality with the level of efficiency in the banking sector.

References

  1. Allen, F., & Carletti, E. (2008). The roles of banks in financial systems. In A. Berger, P. Moyneux, & J. Wilson (Eds.), The Oxford handbook of banking. Oxford: Oxford University Press.Google Scholar
  2. Andersen, P., & Petersen, N. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261–1264.CrossRefGoogle Scholar
  3. Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30, 1078–1092.CrossRefGoogle Scholar
  4. Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98, 175–212.CrossRefGoogle Scholar
  5. Berger, A. N., Hunter, W. C., & Timme, S. G. (1993). The efficiency of financial institutions: A review and preview of research past, present and future. Journal of Banking & Finance, 17, 221–249.CrossRefGoogle Scholar
  6. Bhattacharya, A., Bhattacharya, A., & Kumbhakar, S. C. (1997). Changes in economic regime and productivity growth: A study of Indian public sector banks. Journal of Comparative Economics, 25(2), 196–219.CrossRefGoogle Scholar
  7. Casu, B., Girardone, C., & Molyneux, P. (2004). Productivity change in European banking: A comparison of parametric and non-parametric approaches. Journal of Banking & Finance, 28, 2521–2540.CrossRefGoogle Scholar
  8. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.CrossRefGoogle Scholar
  9. Coelli, T., & Perelman, S. (1996). Efficiency measurement, multi-output technologies and distance functions: With application to European railways. Crepp, Wp 96/05.Google Scholar
  10. Coelli, T., Rao, D. S. P., & Battese, G. E. (1999). An introduction to efficiency and productivity analysis. Boston/Dordrecht/London: Kluwer Academic Publishers.Google Scholar
  11. Coelli, T., Rao, D. S. P., O’Donnell, C. J., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis (2nd ed.) Cham: Springer.Google Scholar
  12. Debru, G. (1951). The coefficient of resource utilization. Econometrica, 19, 273–292.CrossRefGoogle Scholar
  13. Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, 120(3), 253–281.CrossRefGoogle Scholar
  14. Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 204, 189–198.CrossRefGoogle Scholar
  15. Frisch, R. (1965). Theory of production. Dordrecht: D. Reidel.CrossRefGoogle Scholar
  16. Gulati, R. (2011). Evaluation of technical, pure technical and scale efficiencies of Indian banks: An analysis from cross-sectional perspective. In The 13th Annual Conference on Money and Finance in the Indian Economy on February 25–26, 2011. Mumbai: Indira Gandhi Institute of Development Research.Google Scholar
  17. Jackson, P. M., & Fethi, M. D. (2000). Evaluating the technical efficiency of Turkish commercial banks: an application of DEA and Tobit analysis (EPRU Discussion Paper, No. 5, University of Leicester, UK).Google Scholar
  18. Koopmans, T. C. (1951). An analysis of production as an efficient combination of activities. In T. C. Koopmans (Ed.), Activity analysis of production and allocation. New York: Wiley.Google Scholar
  19. Kumar, S., & Verma, S. (2003). Technical efficiency, benchmarks and targets: A case study of Indian public sector banks. Prajnan: Journal of Social and Management Sciences, 31(4), 275–300.Google Scholar
  20. Pasiouras, F., Sifodaskalakis, E., & Zopounidis, C. (2007). Estimating and analyzing the cost efficiency of Greek cooperative banks: An application of two-stage data envelopment analysis (Working Paper Series 2007.12, University of Bath, School of Management, Bath, UK).Google Scholar
  21. Rajan, R. G., & Zingales, L. (1998). Financial dependence and growth. The American Economic Review, 88(3), 559–586.Google Scholar
  22. Ray, S. (2004). Data envelopment analysis: Theory and techniques for economics and operations research. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  23. Reserve Bank of India. (2008). Efficiency, productivity and soundness of the banking sector. Report on currency and finance (pp. 393–446).Google Scholar
  24. Seiford, L. M., & Thrall, R. M. (1990). Recent developments in DEA: The mathematical programming approach to frontier analysis. Journal of Econometrics, 46(1–2), 7–38.CrossRefGoogle Scholar
  25. Stolp, C. (1990). Strengths and weaknesses of data envelopment analysis: An urban and regional perspective. Computers, Environment and Urban Systems, 14(2), 103–116.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Economics DepartmentBurdwan UniversityBurdwanIndia
  2. 2.Economics DepartmentShyampur Siddheswari Mahavidyalaya, University of CalcuttaHowrahIndia

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