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Financial Deregulation in the Indian Banking Industry: Has It Improved Cost Efficiency?

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Deregulation and Efficiency of Indian Banks

Part of the book series: India Studies in Business and Economics ((ISBE))

Abstract

This chapter explores whether the cost efficiency of Indian banks since the launching of deregulation programme in 1992 has improved or not. The results suggest that deregulation programme has had a positive impact on the cost efficiency of Indian banks, and the observed cost efficiency gains are predominantly due to improvements in technical efficiency. Regarding the ranking of ownership groups, the results contradict the property rights hypothesis and public choice theory since public sector banks share the place on the podium along with foreign banks, and are more efficient than private banks. Further, while foreign banks are found to be mostly defining the grand technological frontier of the Indian banking system, public sector banks are closely chasing them to stay competitive. The empirical evidence is also in favour of the prevalence of the global advantage hypothesis in Indian banking industry. We also find that medium banks outperform the banks belonging to other size classes in terms of cost efficiency and its components. Further, Indian banks are operating at sub-optimal scale size. The post-DEA analysis unambiguously indicates that size and exposure to off-balance sheet activities are the key determinants of cost efficiency in Indian banking industry.

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Notes

  1. 1.

    For computing the average annual growth rate of efficiency scores for the entire study period, we estimated a log-linear trend equation: ln E t  = α + βt + ε t , where E t is mean efficiency score in the year t (t = 1,2,…,T) and ε t denotes stochastic error term. Following Boyce (1986), a kinked exponential model has been used for estimating the growth rates for the subperiods. The regression equation in kinked exponential model takes the form ln E t  = α + β 1(Dt + (1 − D)k) + β 2(1 − D)(t − k) + ε t , where D is a dummy variable (D = 1 for first subperiod and 0 for second subperiod) and k is the midpoint of the two discontinuous series (k = 7.5 in the present study). The OLS estimates of β 1 and β 2 (i.e. \( {\widehat{\beta}}_1\ \mathrm{and}\ {\widehat{\beta}}_2 \)) give the growth rates for the first and second subperiods, respectively. Further, a temporal pattern of growth may have a tendency to either accelerate or decelerate. To explore such possibilities, we estimated the log quadratic equation: ln E t  = a + bt + ct 2 + u t . A significantly positive value of c indicates acceleration in the growth rate of efficiency; a significantly negative value indicates a deceleration. It is worth mentioning here that the inclusion of time squares on the right-hand side of the aforementioned equation introduces a multicollinearity problem. This is solved by normalising time in mean deviation form. That is, it is set to zero on the midpoint of the time series. For more detailed discussion, interested parties can refer to Majumdar (1998).

  2. 2.

    The Securitisation and Reconstruction of Financial Assets and Enforcement of Security Interest Act, 2002 (SARFAESI), empowers banks to recover their non-performing assets without the intervention of the court.

  3. 3.

    This result is complemented by the rejection of null hypothesis of no difference in efficiency score across distinct ownership groups in majority of the sample years under consideration, particularly in the most recent years. The detailed results are available upon request to the authors.

  4. 4.

    The liability of foreignness is the costs borne by banks operating away from their home market; such costs include monitoring, staff turnover, diseconomies of scale for retail operations and factors such as culture, language and market structure acting as barriers to entry (Miller and Parkhe 2002).

  5. 5.

    The detailed results are available upon request to the authors.

  6. 6.

    LCS’s scale deficiency index = Banks with DRS/(Banks with IRS + Banks with DRS).

  7. 7.

    The skimping hypothesis maintains that the high volume of problem loans may be a conscious decision of a bank because its management might be trading off between short-term operating costs and long-run profitability. Management might rationally decide to reduce short-term expenses by skimping on resources allocated to loan origination and monitoring, at the expense of greater problem loans and costs in the future.

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Authors and Affiliations

  1. Faculty of Economics, South Asian University, New Delhi, India

    Sunil Kumar

  2. Department of Humanities and Social Sciences, Indian Institute of Technology Roorkee, Roorkee, Uttaranchal, India

    Rachita Gulati

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  1. Sunil Kumar
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  2. Rachita Gulati
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Kumar, S., Gulati, R. (2014). Financial Deregulation in the Indian Banking Industry: Has It Improved Cost Efficiency?. In: Deregulation and Efficiency of Indian Banks. India Studies in Business and Economics. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1545-5_6

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