The cooperative banking sector in India has received a series of shocks in recent years, resulting in a significant number of bank failures and upsurge in bank merger activities, both voluntary and arranged by RBI. The major legislative and regulatory changes raise a number of important questions about the sector, and issues of bank efficiency become more important as inefficient banks may not survive long. Survival and success in competitive markets demand performance through continuous improvement and learning. Against this backdrop, this paper analyzes and measures the performance and efficiency of the Urban Cooperative Banks (UCBs) of Maharashtra, using Data Envelopment Analysis (DEA), a model that helps to determine the relative efficiency among competing banks, on the basis of their numerical efficiency score. The author also attempts to identify and examine the relationship between size and efficiency of UCBs. However, the scope of efficiency is limited to technical efficiency only.
In
recent years, fundamental changes have taken place in the Indian banking industry.
To a large degree, thse changes have been a consequence of deregulation that has
led to the creation of a more market competitive environment within the banking
sector of India. Survival and success in competitive markets demand achieving
the highest levels of performance through continuous improvement. The performance
of the banks is crucial for the well-being of the whole economy. A measure of
relative efficiency provides a good indicator of the success or failure of a bank
in a competitive market; in fact, it also reflects the potentiality for failure
of a banking institution. According to Saha and Ravishankar (2000), efficiency
indices could also be used in identifying the areas of inefficiency of a bank
and formulating suitable strategies to improve its relative position in the market.
It can also provide a framework to the regulators to assess the health of individual
banks and to work out appropriate interventions to prevent systemic failures.
In
competitive industries, which include the banks also, production units can be
distinguished into two groups: the ones which perform well and those which perform
poorly, by measuring their standards performance. Non-parametric and parametric
frontier efficiency analysis are the yardsticks general yapplied in financial
economics for this purpose. The parametric approach includes stochastic frontier
analysis, the free disposal hull, thick frontier and the distribution free approaches.
The non-parametric includes Data Envelopment Analysis (DEA), which is a linear
programming based technique for measuring the relative performance of organizational
units where the presence of multiple inputs and outputs makes comparisons difficult
(Bauer, 1990; Berger and Humphery, 1997). All over the world, a number of studies
have applied DEA to the questionof efficiency in banking, but very little empirical
research can be observed in case of India. Bhattacharya et al. (1997),
Saha and Ravishankar (1999), Ram Mohan and Ray (2004), and Inderjeet Singh and
Pramod Kumar (2004) are among those few researchers who have examined the performance
of the Indian commercial banks. These scholars have mainly considered the impact
of reforms and different ownership groups,e.g., public, private and foreign. |
