Financial reforms and technical efficiency in Indian commercial banking: A generalized stochastic frontier analysis

• Author: Sudeshna Pal,Aditi Bhattacharyya
• Date: 01 September 2013
• DOI: http://doi.org/10.1016/j.rfe.2013.04.002
• Published date: 01 September 2013

Financial reforms and technical efficiency in Indian commercial banking:

A generalized stochastic frontier analysis

Aditi Bhattacharyya

a,

⁎, Sudeshna Pal

b,1

a

Department of Economics and International Business, Sam Houston State University, Huntsville, TX 77341, United States

b

Department of Economics and Finance, Georgia College and State University, CBX No. 014, Milledgeville, GA 31061, United States

abstractarticle info

Article history:

Received 12 November 2011

Accepted 31 March 2013

Available online 12 April 2013

JEL classification:

D24

G21

G28

Keywords:

Technical efficiency

Generalized stochastic production frontier

Indian commercial banks

Financial reforms

Liberalization

In this study we estimate technical efficiency of Indian commercial banks from 1989 to 2009, using a

multiple-output generalized stochastic production frontier and analyze the effects of financial reforms on es-

timated efficiency. The generalized method estimates technical efficiency in the presence of multiple outputs,

filling a gap in the existing literature. Our results show that Indian commercial banks were operating with

64% efficiency on average during the sample period. The initial phase of reform had a positive impact on

while the later phase adversely affected technical efficiency of banks. Public sector banks show higher effi-

ciency levels compared to private and foreign banks.

© 2013 Elsevier Inc. All rights reserved.

1. Introduction

The goal of this study is to estimate technical efficiency of Indian

commercial banks and examine the effects of financial sector reforms

on the measured efficiency.

The financial sector in post-independence India hadall the charac-

teristics of financial repression. Banks were nationalized and there

was strong government control over the financial market. “The sector

was characterized, inter alia, by administered interest rates, large

pre-emption of resources by the authorities and extensive micro-

regulations directing the major portion of the flow of funds to and

from financial intermediaries”(Mohan, 2005). The outcome was lack

of competition, high intermediation costs and hence under-lending,

corruption and bureaucratic lethargy (e.g., Banerjee, Cole, & Duflo,

2004; Mohan, 2005; Thomas, 2005). In 1991 the Indian government

launched widespread economic liberalization policies which also per-

vaded the financial sector. Entry barriers were loosened making way

for privateand foreign banks, reformswere initiated to improve“finan-

cial soundness”and bank efficiency targeting capital adequacy

requirements, stronger vigilance of the banking sector and several

other legal and institutional factors (Ahluwalia, 2002; Mohan, 2005).

The banking sectorreforms in India were implemented in two phases,

first in 1991–92followed by a second phase in 1998.

India presents an interesting case in the study of bank efficiency

owing to the co-existence of a large number of government-owned,

private and foreign banks in the economy. India's rapid economic

growth also makes examination of the performance of the banking

sector an attractive subject for research, especially, after the imple-

mentation of widespread economic reforms.

A bank is said to be technically inefficient if the actual output is

lower than the maximum possible output level, given available re-

sources. Common causes of such inefficiency include managerial

error or coordination failure (O'Donnell & Griffiths, 2006). The

existing literature in this field uses mainly two types of methods to

measure technical efficiency of banks —Data Envelopment Analysis

(DEA) and Stochastic Frontier Analysis (SFA).

The DEA method uses linear programming techniques to measure

efficiency of production units that produce multiple outputs. Several

studies use this approach to measure efficiency of Indian banks (see

Bhattacharyya, Lovell, & Sahay, 1997; Das & Ghosh, 2006; Das, Nag,

& Ray, 2005; Kumar & Gulati, 2009; Sathye, 2003). However, this

method fails to capture the effect of random shocks to the production

system. On the other hand, the SFA method posits two main causes

for the deviation of actual output from the maximum possible output,

given the inputs. A part of this deviation is attributed to the symmet-

ric random shocks to a production system that are not under the

Review of Financial Economics 22 (2013) 109–117

⁎Corresponding author. Tel.: +1 936 294 4791.

E-mail addresses: aditibhattacharyya@gmail.com (A. Bhattacharyya),

sudeshna.pal@gmail.com (S. Pal).

1

Tel.: +1 478 445 1240.

1058-3300/$ –see front matter © 2013 Elsevier Inc. All rights reserved.

http://dx.doi.org/10.1016/j.rfe.2013.04.002

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