Productivity and efficiency dynamics in Indian banking: An input distance function approach incorporating quality of inputs and outputs
Article first published online: 4 MAY 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
Volume 27, Issue 2, pages 205–234, March 2012
How to Cite
Das, A. and Kumbhakar, S. C. (2012), Productivity and efficiency dynamics in Indian banking: An input distance function approach incorporating quality of inputs and outputs. J. Appl. Econ., 27: 205–234. doi: 10.1002/jae.1183
- Issue published online: 16 FEB 2012
- Article first published online: 4 MAY 2010
- Manuscript Revised: 22 DEC 2009
- Manuscript Received: 8 JUN 2008
Banking technology is typically characterized by multiple inputs and multiple outputs that are associated with various attributes, such as different types of deposits, loans, number of accounts, classes of employees and location of branches. These quality differentials in inputs and outputs are mostly ignored in empirical studies. These omissions make the practical value of productivity studies in organizations like banks questionable because quality is a key component of performance. This paper proposes using hedonic aggregator functions (as a tool of aggregating inputs and outputs with quality attributes) within an input distance function framework and analyzes the impact of banking deregulation on efficiency and total factor productivity (TFP) change in the Indian banking industry using panel data for the period 1996–2005. Empirical results indicate that banks have improved their efficiency (from 61% in 1996 to 72% in 2005) during the post-deregulation period, and the gain in efficiency of state-owned banks has surpassed that of private banks. Improvement in capital base, as indicated by increased capital adequacy ratio, played an important role in ushering efficiency gain. The return to scale estimate suggests that state-owned banks are operating far above their efficient scale and cost savings can be obtained by reducing their size of operations. Overall, TFP growth was above 3.5% annually. Both technical progress and technical efficiency change consistently played an important role in shaping TFP growth. Copyright © 2010 John Wiley & Sons, Ltd.