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Deb, Joyeeta
- Branch Level Efficiency and its Decomposition of Meghalaya Co-Operative Apex Bank Ltd
Authors
1 Department of Commerce, Assam University, Silchar, Assam, IN
Source
Abhigyan, Vol 34, No 4 (2017), Pagination: 53-64Abstract
Co-operative banking, in most of the countries mainly in developing and transitional economies, has gained renewed importance mainly following the major thrust on financial inclusion and inclusive growth. These Institutions are considered as a potential instrument to bring people from far-flung areas under the formal banking network. In our country, several reform measures are initiated for the banking sector in order to make them competitive, operationally efficient and functionally independent and in its response, the post reform era have displayed enormous growth and progress on the part of commercial banks counted on measures like CD ratio, ROA etc. But the co-operative banks are yet to report similar results. Most of these banks are still characterized by poor returns, outreach, CD ratio etc. But importance of these banks can hardly be over emphasized in a region like North-East India where co-operative banks and commercial banks are the major tools for financial intermediation. Ensuring healthy performance of such banks is crucial for the overall economic development of the region. Thus, the present study intends to evaluate the level of efficiency at the branch level of one of the State Co-operative Banks having its presence through a wide network of bank branches in one of the states of the region, i.e.; The Meghalaya Co-operative Apex Bank Limited having its presence in the state of Meghalaya. Besides, the study also intends to identify the major factors responsible for efficiency/inefficiency at the branch level. The study is based on five years data from 2008 to 2012. The Data Envelopment Analysis (DEA) is used to estimate the efficiency scores and further the efficiency scores are regressed using the Tobit model to identify the determinants of efficiency/inefficiency.Keywords
North-Eastern Region, Meghalaya Co-Operative Apex Bank Ltd, Branch Level Efficiency, DEA, Tobit Model.References
- Banker, R.D., Charnes, A., & Cooper, W.W. (1984). Some models for estimating technical and scale efficiencies in data envelopment analysis. Management Science, 30 (9), 1078-1092.
- Camanho, A. S., & Dyson, R.G. (1999). Effciency, size, benchmarks and targets for bank branches: An application of data envelopment analysis. Journal of the Operational Research Society, 50 (9).
- Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operations Research, 2, 429-444.
- Das, A. (1997, June-September). Technical, allocative and scale efficiency of public sector banks in India. RBI Occasional Papers, 18.
- Das, Abhiman, Ray, S.C., & Nag, Ashok (2005, March). Labour use efficiency in indian banking: A branch level analysis. University of Connecticut, Department of Economics, Working Paper Studies Working Paper 200504. Retrieved from
. - Farrell, M.J. (1957). The measurement of productive efficiency. Journal of Royal Statistical Society, Series A (General), 120 (3), 253-290.
- Feroze, P.S. (2012, March). Technical efficiency and its decomposition in district co-operative banks in kerala: A data envelopment analysis approach. South Asian Journal of Marketing and Management Research, 2 (3).
- Golany, B., & Storbeck J.E. (1999, May-June). A data envelopment analysis of the operational efficiency of bank branches. Interfaces, 29 (3) 14-26.
- North Eastern Council. (2006). Basic Statistics of NER 2006, Shillong, Meghalaya: North-Eastern Council Secretariat.
- Ram Mohan, T.T., & Ray, S. (2004a). Comparing performance of public and private sector banks: A revenue maximization efficiency approach. Economic and Political Weekly, 39, 1271-1275.
- Ray, S.C. (2011).Nonparametric measurement of cost efficiency of a demand constrainedbranch network: an application to Indian banking, University of Connecticut, Department of Economics, Working Paper Studies January 8 2011. Retrieved from
.
- Efficiency Determinants of Microfinance Institutions in India: An Indicative DEA Approach
Authors
1 Department of Commerce, Assam University, Silchar, Assam, IN
Source
Abhigyan, Vol 36, No 2 (2018), Pagination: 1-10Abstract
Microfinance Institutions provide financial support to the deprived sections of the society, who are unable to receive formal banking facilities, and thus is considered an integral part for developing an economy. Talking about India, where till date a large mass of population is poor, uneducated, deprived of formal banking services, Microfinance Institutions works as bridge in filling up the gap between such underprivileged population and the formal banking system. Recently the studies on efficiency of Microfinance institutions have received wider attention. Therefore, it is felt relevant to study the efficiency of such institution in Indian context. Besides efficiency, this paper also attempts to identify the determinants of efficiency and specifically answers whether 'sustainability' has any significant impact on efficiency. Relevant data are collected through secondary source from thirty-one Indian Microfinance Intuitions and non-parametric Data Envelopment Analysis (DEA) is used for gauging the efficiency, thereafter, tobit regression is used to identify the determinants of efficiency.
Keywords
Microfinance Institutions, India, Data Envelopment Analysis, Sustainability, Self-Sufficiency.References
- Canhoto A., & Dermine, J. (2002). A note on banking efficiency in Portugal, new vs. old banks. Journal of Banking and Finance, 27(11), 2087-2098.
- Fare.R., Grosskoph.S., Norris. M., & Zhang. Z. (1994). Productivity growth, technical progress and efficiency change in industrialized countries. The American Economic Review, 84 (1), 66-83.
- Gupta.O.K., Doshit.Y., & Chinubhai.A. (2008). Dynamics of productive efficiency of Indian banks. International Journal of Operations Research, 2, 72-90.
- Haq.M., Skully.M., & Pathan.S (2010). Efficiency of micro finance institutions: A data envelopment analysis. Asia-Pacific Financial Markets, 17(1), 63-97.
- India's 25 leading MFIs, CRISIL Ratings, June 2014. Rerieved from www.microfinancegateway.org/library/india's-25leading-mfis.
- Kipesha. E.F. (2013). Production and intermediation efficiency of microfinance institutions in Tanzania. Research Journal of Financel and Accounting, 4(1), 149-159.
- Marakkath. N. (2014). Sustainability of Indian microfinance institutions: A mixed model approach. Indian Studies in Business and Economics. India.: Springer.
- Nieto. B.G., Cinca. C.S., & Molinero. C.M. (2005). Microfinance institutions and efficiency. Omega the International Journal of Management Science, 35, 131-142.
- Nieto. B.G., Cinca. C.S., & Molinero. C.M. (2009). Social efficiency in microfinance institutions The Journal of the Operational Research Society, 60 (1), 104-119.
- Pasupathy K.S. (2002). Modeling undesirable outputs in data envelopment analysis : Various approaches. Unpublished master's thesis, Faculty of the Virginia Polytechnic Institute and State University, USA.
- Quayes.S., & Khalily.B. (2014). Efficiency of microfinance institution in Bangladesh. Economics Bulletine. 34, 1512-1521.
- Sa-Dhan Microfinance Manager Series: Technical Note 13 . Retrieved from http://www.sadhan.co.in/Adls/Technicalnotes/Technical_Notes_13.pdf.
- Sahoo. B. K., Sengupta.J. K., & Mandal. A. (2007). Productive performance evaluation of the banking sector in India using data envelopment analysis. International Journal of Operations Research. 4(2), 67-79.
- Soterriou. A., & Zenios.S.A. (1997). Efficiency, profitability and quality of banking services. Wharton Financial Institutions Center.
- Thanassoulis E., & Boussofiane, A. (1996). A comparison of data envelopment analysis and ratio analysis as tools for performance assessment. Omega International Journal for Management Science, 24(3), 229-244.
- Worthington. A.C. (1998). The determinants of non-bank financial institution efficiency: A stochastic cost frontier approach. Applied Financial Economics. 8(3), 279-289.