International Journal of Banking, Risk and Insurance

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Performance of Commercial Banks in India : DEA Measurement and Determinants of Technical Efficiency


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1 Department of Econometrics, University of Madras, Chennai, Tamil Nadu, India
     

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As commercial entities, commercial banks are expected to maintain profitability in the face of stiff competition, while serving the mandatory government priorities and policy commitments, and central bank regulations. The performance of commercial banks crucially depends on their technical efficiency of realising the full potential output, which the banks invariably do not. This paper measures the technical efficiency of 94 public, private, foreign, and small financial commercial banks in India in 2019 using the data envelopment analysis (DEA) method; the determinants of technical efficiency are analysed by applying the Tobit regression method. The estimated technical efficiency scores of public sector banks are below average and private banks do little better than average, while the technical efficiency of foreign banks varies widely. The Tobit estimates show that capital adequacy and return on assets positively influence technical efficiency, while bank size reduces the technical efficiency of the banks. The managerial quality, bank profitability, and diversification are irrelevant to the technical efficiency levels of commercial banks. The results suggest that the performance of commercial banks in India may be improved by choosing a proper input-output mix and an appropriate scale size.

Keywords

Commercial Bank Performance, Potential Output, Technical Efficiency, DEA Estimation, Determinants, Tobit Regression.
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  • Aigner, D. J., & Chu, S. F. (1968). On estimating the industry production function. American Economic Review, 58(4), 826-839.

  • Aigner, D. J., Lovell, C. A. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21-37.

  • Assaf, A. G., Barros, C. P., & Matousek, R. (2011). Technical efficiency in Saudi Banks. Expert Systems with Applications, 38(5), 5781-5786.

  • Ataullah, A., & Le, H. (2006). Economic reforms and bank efficiency in developing countries: The case of the Indian banking industry. Applied Financial Economics, 16(9), 653-663.

  • Beck, T. (2006). Creating an efficient financial system: Challenges in a global economy. Policy Research Working Paper, World Bank.

  • Beck, T., Demirguc-Kunt, A., & Levine, R. (2003). Law, endowments, and finance. Journal of Financial Economics, 70(2), 137-181.

  • Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and review. European Journal of Operational Research, 98(2), 175-212.

  • Berger, A. N., Leusner, J. H., & Mingo, J. H. (1997). The efficiency of bank branches. Journal of Monetary Economics, 40(1), 141-162.

  • Bhattacharyya, A., Lovell, C. A. K., & Sahay, P. (1997). The impact of liberalization on the productive efficiency of Indian commercial banks. European Journal of Operational Research, 98(2), 332-345.

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.

  • Coelli, T., Prasada Rao, D. S., & Battese, G. E. (1998). An introduction to efficiency and productivity analysis. Springer.

  • Dimpy, S. K., & Gulati, R. (2010). Assessing the effect of ownership on the efficiency of Indian domestic banks. IUP Journal of Bank Management, 9(3), 76-104.

  • Dwivedi, A. K., & Charyulu, D. K. (2012). Efficiency of Indian banking industry in the post-reform era. International Journal of Business Continuity and Risk Management, 3(3), 234-243.

  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, 120(3), 253-281.

  • Kumar, S. S., & Gulati, R. (2008). An examination of technical, pure technical and scale efficiency in Indian public sector banks using data envelopment analysis. Eurasian Journal of Business and Economics, 1(2), 33-69.

  • Lakshmanasamy, T. (2018). Are commercial banks in India technically efficient? A multiple output - multiple input panel stochastic ray frontier function estimation. WEALTH – International Journal of Money, Banking and Finance, 7(3), 4-16.

  • Lakshmanasamy, T., & Shanmugam, K. R. (2001). Production frontiers and efficiency measures: An analysis of the banking sector in India. Asian-African Journal of Economics and Econometrics, 1(2), 211-228.

  • Lakshmanasamy, T., & Shanmugam, K. R. (2003). Technical efficiency measures for single and multiple output technologies. In P. Thangavel (Ed.), Algorithms and Artificial Systems (pp. 277-295). Chennai: Allied Publishers.

  • Meeusen, W., & van den Broeck, V. (1977). Efficiency estimation from Cobb Douglas production function with composed error. International Economic Review, 18(2), 435-444.

  • Ray, S. C., & Ram Mohan, T. T. (2004). Comparing performance of public and private sector banks – A revenue maximization efficiency approach. Economic and Political Weekly, 39(12), 127-176.

  • San, O. T., Theng, L. Y., & Heng, T. B. (2011). A comparison on efficiency of domestic and foreign banks in Malaysia: A DEA approach. Business Management Dynamics, 1(4), 33-49.

  • Sealey, C. W., & Lindley, J. T. (1977). Inputs, outputs, and a theory of production and cost at depository financial institutions. Journal of Finance, 32(4), 1251-1266.

  • Singh, D., & Fida, B. (2015). Technical efficiency and its determinants: An empirical study on banking sector of Oman. Problems and Perspectives in Management, 13(1), 168-175.

  • Sharma D., Sharma, A. K., & Barua, M. K. (2012). Predicting the probabilities of most and least efficient banks: Data envelopment analysis and logit regression approach. Asia Pacific Journal of Finance and Risk Management, 3(3), 987-1000.

  • Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of Banking and Finance, 9(2), 297-315.

  • Timmer, C. P. (1971). Using a probabilistic frontier production function to measure technical efficiency. Journal of Political Economy, 79(4), 776-794.


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  • Performance of Commercial Banks in India : DEA Measurement and Determinants of Technical Efficiency

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Authors

T. Lakshmanasamy
Department of Econometrics, University of Madras, Chennai, Tamil Nadu, India

Abstract


As commercial entities, commercial banks are expected to maintain profitability in the face of stiff competition, while serving the mandatory government priorities and policy commitments, and central bank regulations. The performance of commercial banks crucially depends on their technical efficiency of realising the full potential output, which the banks invariably do not. This paper measures the technical efficiency of 94 public, private, foreign, and small financial commercial banks in India in 2019 using the data envelopment analysis (DEA) method; the determinants of technical efficiency are analysed by applying the Tobit regression method. The estimated technical efficiency scores of public sector banks are below average and private banks do little better than average, while the technical efficiency of foreign banks varies widely. The Tobit estimates show that capital adequacy and return on assets positively influence technical efficiency, while bank size reduces the technical efficiency of the banks. The managerial quality, bank profitability, and diversification are irrelevant to the technical efficiency levels of commercial banks. The results suggest that the performance of commercial banks in India may be improved by choosing a proper input-output mix and an appropriate scale size.

Keywords


Commercial Bank Performance, Potential Output, Technical Efficiency, DEA Estimation, Determinants, Tobit Regression.

References