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Measuring Efficiency of Selected Indian Commercial Banks : A DEA-Based MPI Approach


Affiliations
1 Research Scholar, Department of Management Studies, Indian Institute of Technology, Roorkee (IIT Roorkee), Roorkee - 247 667, Uttarakhand, India
2 Assistant Professor, Department of Management Studies, Indian Institute of Technology, Roorkee (IIT Roorkee), Roorkee - 247 667, India

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This paper attempted to measure the change in productivity of 19 commercial banks in India from 2013 – 2018. The nature of efficiency and productivity change was investigated with the help of the output - oriented Malmquist Productivity Index (MPI) through intermediation approach. The MPI has components that are used in performance measurements, such as changes in technology efficiency, technical efficiency, pure technical efficiency, scale efficiency, and total factor productivity. The results of the study demonstrated that Ratnakar Bank Limited had the highest MPI score against both the technological change and total factor productivity change ; whereas, State Bank of India and Punjab National Bank had the lowest MPI scores. Overall, the private sector banks were found to be more productive compared to the public sector banks for the period under consideration.

Keywords

Malmquist Productivity Index, Pure Technical Efficiency, Scale Efficiency, Technical Efficiency, Technological Change.

JEL Classification : C43, C44, G21, G28.

Paper Submission Date : February 4, 2020 ; Paper sent back for Revision : October 25, 2020 ; Paper Acceptance Date : January 19, 2021 ; Paper Published Online : July 5, 2021.

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  • Adjei-Frimpong, K., Gan, C., Ying, L., Hu, B., & Cohen, D. A. (2015). Efficiency and productivity change in the banking industry : Empirical evidence from New Zealand banks. Investment Management and Financial Innovations, 12(1), 19–25. https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/6286/imfi_en_2015_01_Adjei-Frimpong.pdf

  • Avkiran, N. K. (2011). Association of DEA super-efficiency estimates with financial ratios : Investigating the case for Chinese banks. Omega, 39(3), 323–334. https://doi.org/10.1016/j.omega.2010.08.001

  • Banerjee, A. (2018). An empirical study to compute the efficiency of Indian banks during the pre and post periods of recession with the help of data envelopment analysis. Indian Journal of Finance, 12(4), 37–53. https://doi.org/10.17010/ijf/2018/v12i4/122794

  • Bassem, B. S. (2014). Total factor productivity change of MENA microfinance institutions : A Malmquist productivity index approach. Economic Modelling, 39, 182–189. https://doi.org/10.1016/j.econmod.2014.02.035

  • Camanho, A. S., & Dyson, R. G. (2005). Cost efficiency, production and value-added models in the analysis of bank branch performance. Journal of the Operational Research Society, 56(5), 483–494. https://doi.org/10.1057/palgrave.jors.2601839

  • Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica : Journal of the Econometric Society, 50 (6), 1393–1414. https://doi.org 10.2307/1913388

  • CBI raids Bhusan Steel and Power’s premises in Rs 2,348 crore bank fraud case. (2019, April 6). The Indian Express. https://indianexpress.com/article/india/cbi-raids-bhushan-steel-powers-premises-bank-fraud-case-5662669/

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8

  • CMIE . (2019). Prowess IQ (version 1.96). https://prowessiq.cmie.com

  • Coelli, T. (1996). A guide to DEAP version 2.1: A data envelopment analysis (computer) program (Working Paper 96/08). Centre for Efficiency and Productivity Analysis, University of New England, Australia. https://www.owlnet.rice.edu/~econ380/DEAP.PDF

  • Das, M. K., & Patra, S. (2016). Productivity and efficiency of public sector banks in India after the global financial crisis. https://ssrn.com/abstract=2885161

  • Das, S., Vaish, A., & Goel, U. (2012). Does loan loss provision signal income smoothing ? - An empirical investigation of Indian banking industry. The IUP Journal of Accounting Research & Audit Practices, 11(2), 58–68.

  • Dell'Atti, S., Pacelli, V., & Mazzarelli, G. (2015). The efficiency of the European banking groups and its determinants. Managerial Finance, 41(7), 734–751. https://doi.org/10.1108/MF-12-2013-0335

  • Desta, T. S. (2016). Are the best African banks really the best ? A Malmquist data envelopment analysis. Meditari Accountancy Research, 24(4), 588–610. https://doi.org/10.1108/MEDAR-02-2016-0016

  • Eichengreen, B., & Gupta, P. (2013). The financial crisis and Indian banks: Survival of the fittest ? Journal of International Money and Finance, 39, 138–152. https://doi.org/10.1016/j.jimonfin.2013.06.022

  • Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84(1), 66–83. https://www.jstor.org/stable/2117971

  • Fujii, H., Managi, S., & Matousek, R. (2014). Indian bank efficiency and productivity changes with undesirable outputs: A disaggregated approach. Journal of Banking & Finance, 38, 41–50. https://doi.org/10.1016/j.jbankfin.2013.09.022

  • Grifell-Tatje, E., & Lovell, C. A. (1996). Deregulation and productivity decline : The case of Spanish savings banks. European Economic Review, 40(6), 1281–1303. https://doi.org/10.1016/0014-2921(95)00024-0

  • Guan, J. C., Yam, R. C., Mok, C. K., & Ma, N. (2006). A study of the relationship between competitiveness and technological innovation capability based on DEA models. European Journal of Operational Research, 170(3), 971–986. https://doi.org/10.1016/j.ejor.2004.07.054

  • Gulati, R., & Kumar, S. (2016). Assessing the impact of the global financial crisis on the profit efficiency of Indian banks. Economic Modelling, 58, 167–181. https://doi.org/10.1016/j.econmod.2016.05.029

  • Indian Banks' Association. (2018). Key business statistics. https://www.iba.org.in/depart-res-stcs/key-bus-stcs.html

  • Kumar, M., Charles, V., & Mishra, C. S. (2016). Evaluating the performance of Indian banking sector using DEA during post-reform and global financial crisis. Journal of Business Economics and Management, 17(1), 156–172. https://doi.org/10.3846/16111699.2013.809785

  • Lee, J. Y., & Kim, D. (2013). Bank performance and its determinants in Korea. Japan and the World Economy, 27, 83–94. https://doi.org/10.1016/j.japwor.2013.05.001

  • Lema, T. Z. (2016). Productivity change of Ethiopian banks : A malmquist productivity index approach. Journal of Economics and Sustainable Development, 7(21), 14–20. https://mpra.ub.uni-muenchen.de/77969/

  • Liu, J. S., Lu, L. Y., Lu, W. - M., & Lin, B. J. (2013). A survey of DEA applications. Omega, 41(5), 893–902. https://doi.org/10.1016/j.omega.2012.11.004

  • Lu, L. - T., Liang, S. - K., & Lee, Y. - H. (2013). Application of Malmquist indexes, empirical model and data envelopment analysis: A measure of performance and efficiency of commercial banks in Taiwan. Journal of Economics, Management & Trade, 4(3), 341–348. https://doi.org/10.9734/BJEMT/2014/5565

  • Narayanaswamy, T., & Muthulakshmi, A. P. (2014). Efficiency of private sector banks in India. Indian Journal of Finance, 8(10), 33–47. http://doi.org/10.17010/ijf/2014/v8i10/71847

  • Narayanaswamy, T., & Muthulakshmi, A. P. (2016). Productivity and cost efficiency of commercial banks in India. Indian Journal of Finance, 10(1), 8–27. https://doi.org/10.17010/ijf/2016/v10i1/85839

  • Narwal, K. P., & Pathneja, S. (2015). Determinants of productivity and profitability of Indian banking sector : A comparative study. Eurasian Journal of Business and Economics, 8(16), 35–58. DOI : 10.17015/ejbe.2015.016.03

  • Paradi, J. C., Rouatt, S., & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using data envelopment analysis. Omega, 39(1), 99–109. https://doi.org/10.1016/j.omega.2010.04.002

  • Patel, M. P., & Ranjith, V. K. (2018). Measuring efficiency and productivity change of multi-specialty private sector hospitals in India : A DEA based Malmquist Productivity Index approach. Indian Journal of Finance, 12(5), 25–42. https://doi.org/10.17010/ijf/2018/v12i5/123691

  • Ray, S. C. (2004). Data envelopment analysis : Theory and techniques for economics and operations research. Cambridge University Press.

  • Repkova, I. (2012). Measuring the efficiency in the Czech banking industry : Data envelopment analysis and Malmquist index. In, Proceedings of the 30th International Conference Mathematical Methods in Economics. Silesian University, School of Business Administration, Karviná. http://mme2012.opf.slu.cz/proceedings/pdf/134_Repkova.pdf

  • Reserve Bank of India, Department of Banking and Services. (2017). Revised prompt corrective action framework for banks (Report no 8/11.01.005). https://rbidocs.rbi.org.in/rdocs/notification/PDFs/NOTI2764ED835C9681F48359414E0EB10CB37A0.PDF

  • Reserve Bank of India. (2020). Statistical tables of DBIE database. https://dbie.rbi.org.in/DBIE/dbie.rbi?site=publications

  • Şahin, I. E., Yılmaz, B., & Akgun, A. (2013). Measurement of efficiency in the Turkish banking sector in the 2009 - 2011 period : A DEA approach. Mediterranean Journal of Social Sciences, 4(10), 744–752. DOI : 10.5901/mjss.2013.v4n10p744

  • Sekhri, V. (2011). A DEA and Malmquist Index Approach to measuring productivity and efficiency of banks in India. The IUP Journal of Bank Management, 10(3), 49–64. https://ideas.repec.org/a/icf/icfjbm/v10y2011i3p49-64.html

  • Sharma, D., & Sharma, A. K. (2015). Influence of turbulent macroeconomic environment on productivity change of banking sector : Empirical evidence from India. Global Business Review, 16(3), 439–462. https://doi.org/10.1177/0972150915569932

  • Sufian, F. (2011). Banks total factor productivity change in a developing economy : Does ownership and origins matter ? Journal of Asian Economics, 22(1), 84–98. https://doi.org/10.1016/j.asieco.2010.07.007

  • Sufian, F., & Kamarudin, F. (2014). The impact of ownership structure on bank productivity and efficiency: Evidence from semi-parametric Malmquist Productivity Index. Cogent Economics & Finance, 2(1), 1–2. https://doi.org/10.1080/23322039.2014.932700

  • Syed, A. A., & Tripathi, R. (2020). Macroeconomic vulnerabilities and its effect on nonperforming loans in Indian commercial banks. Indian Journal of Finance, 14(2), 34–49. https://doi.org/10.17010/ijf/2020/v14i2/150555

  • Tzeremes, N. G. (2015). Efficiency dynamics in Indian banking : A conditional directional distance approach. European Journal of Operational Research, 240(3), 807–818. https://doi.org/10.1016/j.ejor.2014.07.029

  • Yeh, Q. - J. (1996). The application of data envelopment analysis in conjunction with financial ratios for bank performance evaluation. Journal of the Operational Research Society, 47(8), 980–988. https://doi.org/10.1057/jors.1996.125

  • Yilmaz, A., & Gunes, N. (2015). Efficiency comparison of participation and conventional banking sectors in Turkey between 2007 - 2013. Procedia-Social and Behavioral Sciences, 195, 383–392. https://doi.org/10.1016/j.sbspro.2015.06.338

  • Zhu, J. (2000). Multi-factor performance measure model with an application to Fortune 500 companies. European Journal of Operational Research, 123(1), 105–124. https://doi.org/10.1016/S0377-2217(99)00096-X


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  • Measuring Efficiency of Selected Indian Commercial Banks : A DEA-Based MPI Approach

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Authors

Vijyapu Prasanna Kumar
Research Scholar, Department of Management Studies, Indian Institute of Technology, Roorkee (IIT Roorkee), Roorkee - 247 667, Uttarakhand, India
Sujata Kar
Assistant Professor, Department of Management Studies, Indian Institute of Technology, Roorkee (IIT Roorkee), Roorkee - 247 667, India

Abstract


This paper attempted to measure the change in productivity of 19 commercial banks in India from 2013 – 2018. The nature of efficiency and productivity change was investigated with the help of the output - oriented Malmquist Productivity Index (MPI) through intermediation approach. The MPI has components that are used in performance measurements, such as changes in technology efficiency, technical efficiency, pure technical efficiency, scale efficiency, and total factor productivity. The results of the study demonstrated that Ratnakar Bank Limited had the highest MPI score against both the technological change and total factor productivity change ; whereas, State Bank of India and Punjab National Bank had the lowest MPI scores. Overall, the private sector banks were found to be more productive compared to the public sector banks for the period under consideration.

Keywords


Malmquist Productivity Index, Pure Technical Efficiency, Scale Efficiency, Technical Efficiency, Technological Change.

JEL Classification : C43, C44, G21, G28.

Paper Submission Date : February 4, 2020 ; Paper sent back for Revision : October 25, 2020 ; Paper Acceptance Date : January 19, 2021 ; Paper Published Online : July 5, 2021.


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DOI: https://doi.org/10.17010/ijf%2F2021%2Fv15i5-7%2F164492