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Efficiency Analysis of Scheduled Commercial Banks of Bihar: An Outreach Perspective


Affiliations
1 Assistant Professor, Amity University, Patna, Bihar, India
2 Assistant Professor of Economics, Mahatma Gandhi College, Lalpur, Daldali, Purulia-723130, West Bengal, India
     

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This paper proposes the outreach approach to measure the efficiency of scheduled commercial banks (SCBs) at the district level in Bihar using Data Envelopment Analysis (DEA) for two time periods - 2001 and 2011. An attempt was also made to examine the status of SCBs of Bihar in comparison to other major States of India. This study was conducted in two stages. Firstly, the efficiency scores were calculated using DEA and the result shows that inequality of major States increases in terms of efficiency and within Bihar, it improved during 2001 and 2011. Secondly, the study tried to find out the determinants of banking efficiency using the Tobit regression model. In 2001, the literacy rate and ‘households availing banking services’ are significant at the district level in Bihar. ‘Urbanisation’ is explaining the banking efficiency in 2011, as 88.7 per cent of the people in Bihar live in rural areas. Geographical dummy northeast and southeast regions of Bihar are positively significant in 2001 whereas northwest is significant in 2011. This study calls for policy action to increase the outreach at the sub-regional level by improving efficiency.

Keywords

Banking, Efficiency Analysis, Scheduled Commercial Bank, Data Envelopment Analysis (DEA), Bihar, India.
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  • Asmild, M., Paradi, J.C., Aggarwall, V. and Schaffnit, C. (2004). Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry. Journal of Productivity Analysis, 21(1), 67-89.
  • Banker, R.D., Charnes, A. and Cooper, W.W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092.
  • Benston, G.J. (1965). Branch Banking and Economies of Scale. The Journal of Finance, 20(2), 312331.
  • Berger, A.N., Hanweck, G.A. and Humphrey, D.B. (1987). Competitive Viability in Banking: Scale, Scope, and Product Mix Economies. Journal of Monetary Economics, 20(3), 501-520.
  • Berger, ALN. and Humphrey, D.B. (1997). Efficiency Of Financial Institutions: International Survey and Directions for Future Research. European Journal of Operational Research, 98(2), 175-212.
  • Charnes, A., Cooper, W.W. and Rhodes, E. (1978). Measuring the Efficiency of Decision-Making Units. European journal of operational research, 2(6), 429-444.
  • Coats Jr, W.L. (1990). Lessons of Financial Liberalisation for India: Another View. Economic and Political Weekly, 1043-1046.
  • Coelli, TJ. (1996). A guide to FRONTIER version 4.1: A Computer Program for Stochastic Frontier Production and Cost Function Estimation (Vol. 7, pp. 1-33). CEPA Working papers.
  • Das, A. and Ghosh, S. (2009). Financial Deregulation and Profit Efficiency: A Non-parametric Analysis of Indian Banks. Journal of Economics and Business, 61(6), 509-528.
  • Das, S.K. (2010), January. Financial Liberalization and Banking Sector Efficiency: the Indian Experience. In: 12 Money and Finance Conference (pp. 11-12).
  • Emrouznejad, A. and Yang, G.L. (2018). A Survey and Analysis of the First 40 Years of Scholarly Literature in DEA: 1978-2016. Socio-Economic Planning Sciences, 61, pp.4-8.
  • Farrell, M.J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
  • Henriques, I.C., Sobreiro, V.A., Kimura, H. and Mariano, E.B. (2018). Efficiency in the Brazilian Banking System Using Data Envelopment Analysis. Future Business Journal, 4(2), 157-178.
  • Kaur, S. and Gupta, P.K. (2015). Productive Efficiency Mapping of the Indian Banking System Using Data Envelopment Analysis. Procedia Economics and Finance, 25, 227-238.
  • Kumar, S. & Gulati, R. (2009). Measuring Efficiency, Effectiveness and Performance of Indian Public Sector Banks. International Journal of Productivity and Performance Management, 591), 5174,
  • Ghosh, A., & Dey, S. K. (2014). How Efficiently is Chemical Fertilizer Used in Indian Agriculture? Challenges and Alternatives. Agrarian South: Journal of Political Economy, 3(3), 403-426.
  • Gulati, R. & Kumar, S. (2017). Analysing Banks’ Intermediation And Operating Efficiencies Using The Two-Stage Network DEA Model: The Case of India. International Journal of Productivity and Performance Management, 66(4), 500-516.
  • Kumar, S. (2010). Banking Sector Reforms and Outreach of Scheduled Commercial Banks in the Northern Region in India. Man & Development, 32(1), 1-16.
  • Kumar, M. & Vincent, C. (2011). Benchmarking Indian banks using DEA in Post-Reform Period: A Progressive Time-Weighted Mean Approach. The Service Industries Journal, 31(14), 24552485.
  • Kumar, C. & Mishra, S. (2011), February. Banking Outreach and Household Level Access: Analyzing Financial Inclusion in India. In: 13° Annual Conference on Money and Finance in the Indian Economy (pp. 25-26).
  • Kumbhakar, S.C. & Sarkar, S. (2003). Deregulation, Ownership, and Productivity Growth in the Banking Industry: Evidence from India. Journal of Money, Credit and Banking, 403-424.
  • Mahesh, H.P. & Bhide, S. (2008). Do Financial Sector Reforms Make Commercial Banks More Efficient? A Parametric Exploration of the Indian Case. Margin: The Journal of Applied Economic Research, 2(4), 415-441.
  • Ouenniche, J. & Carrales, S. (2018). Assessing Efficiency Profiles of UK Commercial Banks: A DEA Analysis with Regression-Based Feedback. Annals of Operations Research, 266(1-2), 551-587.
  • Rajan, S. S., Reddy, K.L.N. & Pandit, V. N. (2011). Efficiency and Productivity Growth in Indian Banking. Centre for Development Economics, Department of Economics, Delhi School of Economics (No. 199). Working Paper.
  • Rangarajan, C., & Mampilly, P. (1972). Economies of Scale in Indian Banking, In: Technical Studies for Banking Commission Report, Reserve Bank of India, Bombay, pp. 244-268.
  • Ravi, R., & Ghosh, A. (2018). Problems of Banking Outreach in Bihar: A District Level Study. Man and Development, 40(2), 57-76.
  • Ray, S.C. & Das, A. (2010). Distribution of Cost and Profit Efficiency: Evidence from Indian Banking. European Journal of Operational Research, 201(1), 297-307.
  • Sarma, M. & Pais, J. (2011). Financial Inclusion and Development. Journal of International Development, 23(5), 613-628.
  • A. Sengupta, A. & Pal, N. P. (2010). Primary Education In India: Delivery And Outcome-A District Level Analysis Based on DISE Data. Journal of Educational Planning and Administration 24 (1), 5-21
  • Sengupta, A., & De, S. (2017). Bank in the Liberalization Era: A Study Based on Non-Parametric Super Efficiency with Panel Tobit, The Journal of Income and Wealth, 39(1), 51-58.
  • Sherman, H.D., Gold, F. (1985). Bank Branch Operating Efficiency: Evaluation with Data Envelopment Analysis. Journal of Banking and Finance 9 (2), 297-315.
  • 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.
  • Tone, K. (2001). A Slacks-based Measure of Efficiency in Data Envelopment Analysis. European Journal of Operational Research, 130(3), 498-509.
  • Tran, T.H., Mao, Y., Nathanail, P., Siebers, P.O. & Robinson, D. (2019). Integrating Slacks-Based Measure of Efficiency and Super-Efficiency in Data Envelopment Analysis. Omega, 85, 156-165.
  • Thyagarajan, M. (1975). Expansion of Commercial Banking: An Assessment. Economic and Political Weekly, 1819-1824.
  • Zha, Y., Liang, N., Wu, M. & Bian, Y. (2016). Efficiency Evaluation of Banks in China: A Dynamic Two Stage Slacks-Based Measure Approach. Omega, 60, 60-72.

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  • Efficiency Analysis of Scheduled Commercial Banks of Bihar: An Outreach Perspective

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Authors

Ritesh Ravi
Assistant Professor, Amity University, Patna, Bihar, India
Abhijit Ghosh
Assistant Professor of Economics, Mahatma Gandhi College, Lalpur, Daldali, Purulia-723130, West Bengal, India

Abstract


This paper proposes the outreach approach to measure the efficiency of scheduled commercial banks (SCBs) at the district level in Bihar using Data Envelopment Analysis (DEA) for two time periods - 2001 and 2011. An attempt was also made to examine the status of SCBs of Bihar in comparison to other major States of India. This study was conducted in two stages. Firstly, the efficiency scores were calculated using DEA and the result shows that inequality of major States increases in terms of efficiency and within Bihar, it improved during 2001 and 2011. Secondly, the study tried to find out the determinants of banking efficiency using the Tobit regression model. In 2001, the literacy rate and ‘households availing banking services’ are significant at the district level in Bihar. ‘Urbanisation’ is explaining the banking efficiency in 2011, as 88.7 per cent of the people in Bihar live in rural areas. Geographical dummy northeast and southeast regions of Bihar are positively significant in 2001 whereas northwest is significant in 2011. This study calls for policy action to increase the outreach at the sub-regional level by improving efficiency.

Keywords


Banking, Efficiency Analysis, Scheduled Commercial Bank, Data Envelopment Analysis (DEA), Bihar, India.

References





DOI: https://doi.org/10.25175/jrd%2F2021%2Fv40%2Fi3%2F149505