India provides a unique case study whereby banking industry is characterized by a mixed ownership structure and the deregulation of the industry in the nineties had paved the way for a level playing field between the various ownership groups. Historically, the industry was dominated by the public sector banks while the activities of the private sector (both domestic and foreign) were severely controlled by India’s Central Bank, the Reserve Bank of India. However, failing profitability and inefficiency in the banking system precipitated the first set of banking sector reforms in 1992 that facilitated entry deregulation, branch de-licensing, deregulation of interest rates, and operational freedom for public sector banks.
This report basically assesses the relative performance of the state-owned banks, the old & new private banks and the foreign banks in India by analysing a large period of data (viz. 1990-2012).
The period allows us to study the impact of various national and international events on the Indian banking performance.
Essentially, we would be doing the comparison in two parts. The first part further consists of two steps. The first step deals with estimation of efficiency using stochastic frontier analysis. In the next step, measures of productivity are computed based on the stochastic frontier estimates. In the second part, we would try to assess the performance and credit risk of all the banking groups of India by using the simple Error Correction Model (ECM).
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Objective
• To estimate efficiency of Indian banks and then estimate a measure of productivity that includes an efficiency term • To compare the State-owned, Private and Foreign banks in India on the basis of efficiency and productivity • To see the impact of any significant events on Indian banking system by analysing the time series data • To explore the impact of privatization on the pace of performance and credit risk of state-owned, private and foreign banks of India
Hypothesis:
H0: The role of ownership exists in determining the performance of Indian banks in terms of efficiency, productivity and credit risk.
Methodology
To test the hypothesis mentioned above, we adopt two approaches:
Stochastic Frontier Analysis:
As regards the specification of the frontier, banking being a multi-product industry, we take recourse to the cost function for estimating efficiency. We take deposits and loans as output, i.e. the output vector consists of value of fixed deposits (FD), saving deposits (SD), current deposits (CD), investments (INV) and loans and advances (ADV).
Apart from these, we also include the number of branches (B) as an output variable, as a proxy for the quality of services. Labour (L) and Capital (K) are the two variable inputs. The dependent variable is total operating cost (C), which is the sum of labour and capital costs.
Regression Analysis:
We take the panel data of banks for the time period 1990-2012 and divide it into three categories each representing an ownership group of the banking industry. For each group, we’ll run a regression with Yt (RoE) used as the dependent variable while liquidity risk (LR), credit factor, (CF) and capital adequacy (CA) used as independent variables.
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Data source
The dataset comprises annual data over the period 1990–2012 for the various banks in India.
To study the comparison of various ownership groups, we divide the panel data into three groups and have their separate analysis.
The dataset is primarily drawn from the websites of:
• Indian Banks’ Association
• Reserve Bank of India
• www.indiastat.com
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Submitted by:
Ankita Grover
MBE 2011-13
