total factor productivity change: an examination of the commercial banking industry in india and...

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Total factor productivitychange: An examination of thecommercial banking industry inIndia and PakistanBarry Howcroft a & Ali Ataullah ba Loughborough University Banking Centre, TheBusiness School, Loughborough, Leicestershire, LE113TU, UK Phone: +44(0)1509 223118 E-mail:b Durham Business School, University of Durham, MillHill Lane, Durham, DH1 3LB, UK E-mail:Published online: 25 Jan 2007.

To cite this article: Barry Howcroft & Ali Ataullah (2006) Total factor productivitychange: An examination of the commercial banking industry in India and Pakistan, TheService Industries Journal, 26:2, 189-202, DOI: 10.1080/02642060500369305

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Total Factor Productivity Change: AnExamination of the Commercial Banking

Industry in India and Pakistan

BARRY HOWCROFT and ALI ATAULLAH

In the early 1990s, India and Pakistan introduced a series of financial lib-

eralisation initiatives aimed at increasing the productivity of their finan-

cial services sector. Against a background of unprecedented change,

which these initiatives heralded, the paper applies a DEA-type Malmquist

total factor productivity change index to examine productivity growth,

efficiency change, and technical progress in the commercial banking

industries of India and Pakistan during 1992–98. Following Leightner

and Lovell [1998], a Malmquist index is constructed for two different

bank service specifications. The first is derived from the corporate objec-

tives of the commercial banks, and the second from the policy objectives

of the Indian and Pakistani governments. The analysis reveals that in both

countries the improvement in total factor productivity was highest when

the government’s policy objective was used. In addition, the public sector

banks showed very little improvement in total factor productivity due to

their inability to adopt new technology and because of the presence of

high non-performing loans. In contrast, foreign banks witnessed the

highest improvement in total factor productivity due to an improvement

in their efficiency and technological innovation.

INTRODUCTION

Financial liberalisation is an essential component of economic reform and structural

adjustment in developing countries [see Nsouli et al., 2002]. Inter alia, it incorporates

deregulation of interest rates and state-determined credit policies, the privatisation of

public sector banks, the creation of new private domestic financial institutions, and a

reduction in entry barriers for foreign banks [see Caprio et al., 1994]. A key objective

of financial liberalisation in developing countries is to increase the productivity of

financial institutions by limiting state intervention and enhancing the role of

Barry Howcroft is Professor of Retail Banking and Director of Loughborough University Banking Centre,The Business School, Loughborough, Leicestershire, LE11 3TU, UK. Tel:þ 44(0)1509 223118. Email:[email protected]. Ali Ataullah is a doctoral student at Durham Business School, University ofDurham, Mill Hill Lane, Durham DH1 3LB, UK. Email: [email protected]

The Service Industries Journal, Vol.26, No.2, March 2006, pp.189–202ISSN 0264-2069 print=1743-9507 onlineDOI: 10.1080=02642060500369305 # 2006 Taylor & Francis

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market forces. Until recently, however, very few studies have empirically investi-

gated the impact of financial liberalisation on the productivity of financial institutions

in developing countries.1 Accordingly, this paper makes a contribution to the nascent

academic literature by investigating the changes in total factor productivity (TFP) of

commercial banks in India and Pakistan during the 1990s.

As such it is the first study to empirically examine the changes in total factor pro-

ductivity (TFP) in commercial banks in Pakistan.2 A small number of studies have

examined the technical efficiency of commercial banks in India [see, for example,

Bhattacharyya et al., 1997; Sathye, 2003]. However, only one study by Kumbhakar

and Sarkar [2003] has examined the changes in TFP in Indian commercial banks

using an econometric approach. This paper, therefore, augments the existing

empirical literature by examining the impact of financial liberalisation in India and

Pakistan by employing the non-parametric technique Data Envelopment Analysis

(DEA) to construct a Malmquist total factor productivity index for the period

1992–98.

The time period and the countries in question were chosen because the financial

sectors of both countries were simultaneously undergoing radical change that was

directly caused by financial liberalisation policies. The paper, therefore, provides

an opportunity to examine whether comparable financial liberalisation policies lead

to similar outcomes in terms of TFP changes. Although some studies have compared

TFP changes in financial institutions in developed countries, a final contribution of

this paper stems from the fact that no other study has examined the subject from

the perspective of two developing countries using the same time period, the same

estimation technique, and the same input–output specifications.

In addressing these issues the paper is structured as follows. Section 2 highlights

the major changes in the commercial banking industry in India and Pakistan. Section

3 presents a brief overview of existing studies on financial liberalisation and changes

in total factor productivity in financial institutions. Section 4 describes the method-

ology and the data used in this study. Section 5 presents the empirical findings and

section 6 draws some conclusions based on the analysis.

THE COMMERCIAL BANKING INDUSTRY IN INDIA AND PAKISTAN

Since their independence in 1947, India and Pakistan have followed very similar com-

mercial banking policies.3 The commercial banking industry in both countries is

characterised by the coexistence of three distinct ownership groups: public banks,

domestic private banks, and foreign banks. Prior to the late 1960s, public ownership

of commercial banks was limited and private participation in the industry was encour-

aged. However, during the late 1960s and early 1970s, the authorities in the two

countries realised that the commercial banks were predominantly benefiting only

the large and well-established businesses and that emergent, small-scale industries

were being neglected [see Sen and Vaidya, 1998; Zaidi, 1999]. In response to this

problem both countries introduced a policy of ‘social control’, which at its very

heart had the nationalisation of commercial banks high on its agenda. Consequently,

190 THE SERVICE INDUSTRIES JOURNAL

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in India the 14 largest commercial banks were nationalised in 1969 and a further six

followed in 1980. Similarly, in Pakistan all the domestic private banks were merged

and nationalised during the mid-1970s to form five big public sector banks. In both

countries, foreign banks were allowed to coexist with the large pubic sector banks,

but their activities were restricted through entry regulations and strict branch licen-

sing rules. Nationalisation and restrictions on private banks not only reduced the

level of competition but also led to a sharp increase in the market share of public

sector banks: By the early 1990s the public sector banks in both countries controlled

around 90 per cent of total deposits and loans [see Arun and Turner, 2002; SBP,

2000]. In addition to nationalisation and the restrictions placed on private banks,

the governments in India and Pakistan stipulated lending targets for priority

sectors, imposed interest rate ceilings on loans and deposits, and directed public

sector banks to open branches in rural and semi-urban areas in an attempt to widen

customer access to financial services. In aggregate, these policies created an inflexible

environment in which the governments ultimately decided the price of financial

services. As a consequence, the commercial banks themselves had very little direct

control over their outputs.

By the late 1980s, excessive emphasis on the public sector and the imposition of

quantitative targets made the commercial banking industry both unprofitable and

under-capitalised by international standards [Kumbhakar and Sarkar, 2003; SBP,

2000]. Operating costs had increased because of the rapid growth in staff that were

recruited on the basis of political affiliation rather than on conventional criteria.

The non-performing loans of the public sector banks were also very high at more

than 20 per cent of total advances and profitability was, therefore, deteriorating

[Bhide et al., 2002; SBP, 2000].

In response to the decline in public sector bank profitability, coupled with policy

prescriptions of the ‘Washington Consensus’, the governments in India and Pakistan

both introduced their financial liberalisation programmes in 1991. The primary

objective was to establish a more profitable, efficient, and robust commercial

banking system by creating a competitive environment through the deregulation of

interest rates and state-directed credit policies, the removal of entry barriers and

the privatisation of public sector banks. Throughout the last decade, these pro-

grammes have considerably altered the structure of the commercial banking industry

in both countries. In particular, the market share of public sector banks has gradually

declined and the number of foreign and domestic private sector banks has increased

considerably.

FINANCIAL LIBERALISATION AND PRODUCTIVITY

Several empirical studies based on a range of industries have reported productivity

gains due to liberalisation and deregulation in developed countries. However, the evi-

dence on the impact of liberalisation on the productivity of financial institutions has

been mixed. For example, empirical studies in the US suggest that cost productivity in

financial institutions declined after deregulation [see Bauer et al., 1993; Berger and

COMMERCIAL BANKING IN INDIA AND PAKISTAN 191

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Mester, 2001]. Sathye [2001] examined the impact of liberalisation on the pro-

ductivity of Australian banks and found that TFP declined by 3.5 per cent during

1992–95. In contrast, however, Berg et al. [1992] found that productivity increased

in Norwegian banks after the implementation of liberalisation and deregulation

programmes.

Financial liberalisation has brought about considerable change in the financial

sectors of developing countries; however, very few studies have empirically investi-

gated the impact of these changes on the productivity of financial institutions in devel-

oping countries. A common theme or hypothesis in these studies has been that

financial liberalisation creates a more flexible and competitive economic environment

that encourages and enables financial institutions to increase their productivity by uti-

lising their resources more efficiently and by investing in new technology. Leightner

and Lovell [1998] adopted this approach when they examined the impact of financial

liberalisation on the productivity of commercial banks in Thailand during 1989–94.

They used two alternative input–output models based on the commercial banks’

profit maximising objective and the central bank’s regulatory objective. Using the

non-parametric technique Data Envelopment Analysis (DEA), they constructed a

Malmquist total factor productivity index, which showed that the liberalisation

process had a positive impact on the productivity of commercial banks. Using a

similar technique but with different input–output specifications, Gilbert and

Wilson [1998] also found that financial liberalisation in Korea during the early

1990s had a positive impact on the productivity of commercial banks. Similarly,

Isik and Hassan [2003] use DEA to estimate the Malmquist total factor productivity

index for Turkish banks for the period 1980–90. Their results revealed significant

productivity gains that were primarily due to improvement in efficiency rather than

an improvement in bank technology.

As stated earlier, very few studies have examined the impact of financial

liberalisation on the efficiency and productivity of commercial banks in India and

Pakistan. In the case of Pakistan, no study has empirically investigated the changes

in TFP in the aftermath of financial liberalisation.4 Although some studies have

measured the efficiency of Indian banks, these studies are restricted to the technical

efficiency of commercial banks in either the pre-liberalisation [see, for example,

Bhattacharyya et al., 1997] or post-liberalisation eras [see Sathye, 2003]. A recent

study by Kumbhakar and Sarkar [2003] is the only one to have used an econometric

approach to investigate the impact of financial liberalisation on the TFP of banks

during the pre- and post-deregulation eras of 1985–96. Their study measures TFP

growth by estimating the translog cost function for domestic banks in India and

decomposing it into technological change, scale effect and a miscellaneous

component. The analysis was based on disaggregated panel data, which consisted

of 27 public sector banks and 23 domestic private banks but excluded foreign

banks. Their results suggest that the anticipated increase in TFP growth, attributable

to financial liberalisation, did not materialise during the period under investigation.

Private sector banks did improve their performance via their new-found freedom

to expand output but public sector banks did not respond positively to liberalisation.

Kumbhakar and Sarkar suggest that, in common with other developing countries, the


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public sector banks had simply become too big and dominant to be radically affected

by liberalisation. They also identified a ‘weak ownership effect’, which hindered

any noticeable reduction in the performance gap between private and public sector

banks.

METHODOLOGY AND DATA

Measurement of Total Factor Productivity using a Malmquist Index

In the empirical literature, two techniques have been used to measure changes in total

factor productivity (TFP): an econometric approach and an index number approach

[see Coelli et al., 1998]. In this paper, the index number approach is adopted for

two reasons. Firstly, in contrast to the econometric approach, it is non-parametric

and, therefore, does not impose a pre-specified functional form on the production

frontier. Secondly, because the study by Kumbhakar and Sarkar [2003] used an econo-

metric approach to measure TFP change it was decided to ascertain whether their con-

clusions would still hold using the index number approach.

The index number approach incorporates the following three alternatives: the

Fischer Index, the Tornqvist Index, and the Malmquist Index [see Coelli et al.,

1998]. However, it is generally accepted that the Malmquist approach has a

number of advantages compared to the other two methods [see Grifell-Tatje and

Lovell, 1996]. These advantages are based on the following assertions: unlike the

Tornqvist and Fischer indices, the Malmquist Index is posited on much weaker

behavioural assumption, i.e. it does not assume cost minimising or revenue maximising

behaviour. In contrast to the Tornqvist and Fischer indices, the Malmquist index

can also be calculated without any information on the prices of inputs and

outputs. Finally, provided panel data is available, the Malmquist Index provides a

decomposition of productivity change into technical change and efficiency change,

and thereby offers an insight into the potential sources of change in TFP. This is

important because efficiency change reveals whether a firm is moving closer to or

further away from the best practice frontier in a particular industry and technical

change shows whether the best practice frontier (or technology) to which a firm is

being compared is either improving, static or deteriorating. This decomposition of

total factor productivity into efficiency change and technical change will, therefore,

allow the analysis to determine whether the productivity of commercial banks in

India and Pakistan is improving either because of a more efficient utilisation of

resources or because of more investment in new technology (or a combination of

both).

Following Shephard [1970] the ‘distance function in outputs’ of an individual

bank in time t relative to the technology of t(F t) can be expressed as D0t (xt, yt) ¼

minfft,t:(xt, yt/ft,t) [ F t, where yt is the vector of outputs that banks produce, xt

the vector of inputs that banks employ, and (F t) the technology corresponding to

period t. This function D0t is defined as the reciprocal of the maximum expansion

to which it is necessary to subject the vector of outputs of period t(yt), given the

level of inputs (xt), so that the observation stands at the frontier of period t.Malmquist


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TFP change Index, M, can be written as a product of efficiency change and technical

change between the two periods [Fare et al., 1994]:

M0(xtþ1, ytþ1, xt, yt) ¼

Dtþ10 (xtþ1, ytþ1)

Dt0(x

t, yt)

�Dt

0(xtþ1, ytþ1)

Dtþ10 (xtþ1, ytþ1)

� �Dt

0(xt, yt)

Dtþ10 (xt, yt)

� �� 1=2

A value ofM0 greater than 1 indicates a positive total factor productivity growth from

period t to tþ 1, while a value less than 1 represents a decline in total factor pro-

ductivity. The efficiency change is given by the first ratio in the above equation. It

represents the catching up effect, i.e. how much closer to the production frontier a

firm has moved. The geometric mean of the two ratios in brackets measures technical

change, i.e. movements in the production frontier. In the empirical application, the

Malmquist TFP index, and its decomposition, is usually accomplished by DEA

[see Coelli et al., 1998]. DEA is a non-parametric linear programming method

which can be used to construct a piecewise production frontier based on the input–

output data of firms included in the sample [see Thanassoulis, 2001]. In this paper,

DEAP 2.1 is used to calculate a DEA-type Malmquist TFP index, and analyse its

components parts for commercial banks in India and Pakistan.

Input–Output Specifications

The first step in measuring TFP change using DEA is to specify inputs and outputs for

the firms under consideration. In the case of commercial banks, however, there is no

agreement on the choice of appropriate inputs and outputs [see Berger and Humphrey,

1992]. This disagreement is probably due to the dual nature of some bank services.

For example, deposits can be regarded as inputs because they come into banks and

form the essential raw material for loans. However, like integrated saving and check-

ing accounts, they can also be regarded as outputs in the sense that they are a value

added service provided by the banks to their customers.5

As the measurement of efficiency is extremely sensitive to the input–output spe-

cification, two alternative input–output models are used to measure changes in TFP.

Following Lightener and Lovell [1998], it is postulated that commercial banks have a

profit-oriented objective, while the central banks of developing countries have a regu-

latory objective which is primarily concerned with fostering economic growth by pro-

viding financial resources to non-financial firms. In light of these two alternative

objectives, two sets of outputs and a common set of inputs are specified. In the

loan-based model, it is postulated that banks incur operating and interest expenses

when producing loans and advances, and investments. This model is consistent

with the widely used ‘intermediation approach’ to bank operations. In the income-

based model, banks incur operating and interest expenses to produce interest and

non-interest income. It is important to note that the outputs in the two models are

inter-related because bank income depends largely on loans, advances, and


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investments.6 However, because there is a high incidence of non-performing loans

amongst commercial banks in developing countries, productivity improvement in

creating loans and advances may not always translate into productivity improvement

in generating income. These two models are used to conduct the investigation into the

impact of financial liberalisation and non-performing loans on the total factor pro-

ductivity of commercial banks in India and Pakistan. It is assumed that if the financial

liberalisation process provided an environment that encouraged banks to produce

good quality loans based on better monitoring and a legal environment that supported

the recovery of non-performing loans, improvements in TFP via the creation of loans

would translate into the generation of additional income. On the other hand, if finan-

cial liberalisation failed to create a supportive and nurturing environment, income

based productivity would not increase even if banks became more productive in creat-

ing new loans.

The sample includes all of the commercial banks operating in India and Pakistan,

provided at least three years’ data was available. In case of both the countries, the

commercial banks included in our sample cover over 95 per cent of total assets,

deposits, and loans of commercial banking industry. Data for the commercial

banks in Pakistan was obtained from various issues of Banking Statistics of Pakistan,

which is published annually by the State Bank of Pakistan.7 The data for India was

obtained from the website of the Reserve Bank of India.8 All the data was converted

into 1993 prices using a GDP deflator obtained from ADB [2003].

Empirical Findings

The total factor productivity change (TFPCH) indices for commercial banks in India

and Pakistan are shown in Tables 1 and 2. Table 1 relates to the loan-based model and

Table 2 to the income-based model. Both tables provide an insight into total factor

productivity change (TFPCH), which is decomposed into efficiency change

(EFCH) and technical change (TCH). The Malmquist total factor productivity

indices are calculated using the technology of the previous year. Based on ownership

structure, the commercial banking industry in both countries is categorised into

three groups, i.e. public banks, domestic private banks and foreign banks. The post-

liberalisation period is also divided into two sub-periods: 1992–95 represents the

initial period when both governments introduced the new deregulatory policies,

and 1996–98 represents the post-deregulatory period when these policies should

have started to realise tangible benefits in the form of greater flexibility and higher

levels of competitiveness.

The Loan Based Model

The loan-based model, which is premised on the government’s objective of encoura-

ging economic growth by financing non-financial firms, postulates that commercial

banks incur interest expense and operating expense when providing funds to bor-

rowers in the form of loans and advances, and investments. The results shown in

Table 1 indicate that over the entire sample period (1992–98), total factor pro-

ductivity change (TFPCH) in the Indian commercial banking sector improved by

an average of 4.6 per cent. The composite parts of TFPCH, i.e. efficiency change


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TABLE 1

TOTAL FACTOR PRODUCTIVITY CHANGES IN LOAN-BASED MODEL

India Pakistan

EFCH TCH TFPCH EFCH TCH TFPCH

All banks1993 0.964 1.022 0.985 1.053 0.943 0.9941994 0.888 1.087 0.965 1.076 0.959 1.0311995 1.171 0.900 1.054 1.066 0.988 1.0541996 1.212 0.943 1.143 1.067 0.978 1.0441997 1.052 1.029 1.082 1.073 0.999 1.0731998 1.021 1.035 1.057 0.998 1.027 1.025

Public sector banks1993 0.934 1.019 0.951 1.015 0.892 0.9061994 0.886 1.083 0.960 1.007 0.936 0.9421995 1.161 0.898 1.042 1.129 0.978 1.1041996 1.157 0.942 1.089 1.033 0.958 0.9901997 1.011 1.040 1.051 1.072 0.989 1.0601998 1.026 1.044 1.071 1.022 1.045 1.068

Domestic private banks1993 0.889 1.003 0.892 1.058 0.887 0.9391994 0.975 1.062 0.844 1.040 0.919 0.9551995 1.348 1.858 1.156 1.017 0.981 0.9981996 1.240 0.927 1.150 1.051 0.999 1.0501997 1.035 0.980 1.014 1.108 1.020 1.1291998 0.987 1.044 1.031 0.949 1.002 0.951

Foreign banks1993 1.075 1.047 1.126 1.087 0.943 1.0251994 0.959 1.155 1.108 1.189 0.977 1.1621995 1.050 0.948 0.996 1.056 1.003 1.0591996 1.295 0.947 1.226 1.118 1.018 1.1381997 1.105 1.071 1.184 1.042 1.026 1.0691998 1.050 1.010 1.061 1.026 1.060 1.087


All banks1992–98 1.042 1.003 1.046 1.055 0.982 1.0371992–95 1.001 1.000 1.001 1.065 0.963 1.0261996–98 1.092 1.001 1.093 1.046 1.001 1.047

Public sector banks1992–98 1.024 1.002 1.026 1.046 0.965 1.0091992–95 0.987 0.997 0.984 1.049 0.935 0.9811996–98 1.063 1.007 1.070 1.042 0.997 1.039

Domestic private banks1992–98 1.032 0.976 1.008 1.036 0.967 1.0011992–95 0.984 0.970 1.038 0.928 0.9641996–98 1.082 0.983 1.063 1.034 1.007 1.041

Foreign banks1992–98 1.084 1.027 1.114 1.085 1.004 1.0891992–95 1.027 1.047 1.075 1.110 0.974 1.0811996–98 1.146 1.008 1.155 1.061 1.034 1.098

EFCH ¼ Efficiency Change; TCH ¼ Technical Change; PCH ¼ Pure Efficiency Change;SCH ¼ Scale Efficiency Change; TFPCH ¼ Total Factor Productivity Change


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(EFCH) and technical change (TCH), improved by 4.2 per cent and 0.3 per cent,

respectively. The most interesting feature of these results, however, was the mere

0.3 per cent improvement in TCH. An examination of the individual years shows

that this small improvement was primarily due to technological regress in TCH

during 1995 (10 per cent) and 1996 (6.7 per cent). However, these two years also

revealed the highest improvement in EFCH. This suggests that initially the Indian

banks invested heavily in new technology with the expectation that it would allow

them to take full advantage of the competitive opportunities in the recently liberalised

markets. However, it was only in subsequent years that this investment translated into

increased efficiency and improved productivity.

The commercial banking industry in Pakistan had an average improvement in

TFPCH of around 3.7 per cent over the entire period and EFCH improved by 5.5

per cent. In this respect the findings are not that dissimilar to the results relating to

India. However, in contrast to the Indian commercial banking industry, the Pakistan

banks experienced technological regress: TCH decreased by 1.8 per cent over the

entire study period. This decrease is explained by the fact that the Pakistani commer-

cial banks experienced technological regress in all of the post-liberalisation years

except in 1998.

Although this technological regression was more evident in Pakistan, both

countries exhibited low technological improvement and the findings shown in

Table 1 indicate that this was primarily due to the inability of public sector banks

to adopt new technology in the new liberalised environment. As the number and

sheer size of public sector banks, in both countries, dictates that they play a crucial

role in the creation and dispersal of loans and advances, it is important to ascertain

whether the liberalisation process had any positive impact on their productivity. In

this respect Table 1 indicates that throughout the entire post-liberalisation period,

TFPCH of the public sector banks improved by 2.6 per cent in India and a mere

0.9 per cent in Pakistan. However, most of this improvement occurred in the

second half (1996–98) of the liberalisation period. The results also reveal technologi-

cal regression (TCH) of 3.5 per cent amongst the public sector banks in Pakistan and

only a slight technological improvement of 0.7 per cent in India. These findings,

therefore, lend support to Kumbhakar and Sarkar’s [2003] conclusions that the

benefits of financial liberalisation are essentially long term and that the large size

of public sector banks in developing countries makes them impervious to change.

As the public sector banks in India and Pakistan controlled around 90 per cent of

total assets and deposits in their respective countries, these findings would appear

to be well founded. It could be argued, therefore, that the large market share of

public sector banks makes them less responsive to new competition from the emer-

ging private sector.

Table 1 also shows that foreign banks in both countries witnessed the highest

improvement in TFP. These improvements were attributable to both technological

improvements (TCH) and efficiency increases (EFCH). This trend is consistent

with other developing countries, where recent foreign bank entrants typically intro-

duce new financial products such as credit cards, automated teller machines

(ATMs) and consumer credit, etc. In contrast and, again in common with the


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experiences of other developing countries, the domestic banks in India and Pakistan,

especially the public sector banks, were slow to adopt and emulate these new

initiatives.

The Income-Based Model

The income-based model postulates that banks seek to generate income from their

financial activities and is consistent with the banks’ profit maximisation objective

[Leightner and Lovell, 1998]. However, as mentioned earlier, the outputs of this

model are closely linked to the outputs of the loan-based model. This is especially

the case in developing countries where a large part of commercial bank income is

generated from loans and investments rather than fee based income.

The results from the income-based model are shown in Table 2, which shows an

improvement in commercial bank TFP in both India and Pakistan. However, the

income-based model generally reveals lower improvements in TFP than the loan-

based model. For example, over the entire period, income-based TFPCH in the

Indian commercial banks improved by an average of 4.2 per cent (4.6 per cent

loan-based model) and mean EFCH improved by 2.8 per cent (4.2 per cent). Techno-

logical improvement (TCH) was the only exception to this trend, being slightly higher

at 1.4 per cent (0.3 per cent). However, like the loan-based model, it regressed by 0.8

per cent (10 per cent) in 1995 and 1.8 per cent (6.7 per cent) in 1996. Similarly, in

Pakistan, TFPCH improved by 2.9 per cent (3.7 per cent) throughout the period,

with EFCH increasing by 3.4 per cent (5.5 per cent) and TCH regressing by 0.5

per cent (1.8 per cent).

The biggest disparity between the two models was revealed by the changes in TFP

in the public sector banks. In India, for example, the loan-based model indicates a 2.6

per cent increase in TFPCH, whereas the income-based model reveals a mere 0.4 per

cent increase. Likewise, the loan-based model reveals a 0.9 per cent increase in

TFPCH for public sector banks in Pakistan, compared to a decline of 2.5 per cent

in the income-based model.

The disparity between the two models can be explained in a number of different

ways. For example, it could be argued that the banks transferred productivity gains to

their customers, i.e. borrowers and depositors. In other words, with a given level of

resources the banks generated higher volumes of loans but reduced net interest

income by paying higher interest to depositors and levying lower interest for loans

and related services.

Hardy and de Patti [2001] advocated a similar explanation when they examined

the revenue and cost efficiency of commercial banks in Pakistan. This explanation,

however, is not exactly consistent with the prevailing conditions in the commercial

banking industry of India and Pakistan during the 1990s. During this period interest

rate spreads in both countries remained fairly constant and even increased for the

public sector banks [see SBP, 2000; Bhide et al., 2002]. This means that although

there is some evidence to suggest that smaller private and foreign banks did transfer

some of their productivity improvements to their customers, the dominant public

sector banks did not.


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TABLE 2

TOTAL FACTOR PRODUCTIVITY CHANGES IN INCOME-BASED MODEL

India Pakistan


All banks1993 0.922 1.033 0.952 1.026 0.986 1.0121994 1.007 1.033 1.041 1.016 0.955 0.9691995 0.994 0.992 1.003 1.082 1.000 1.0821996 1.078 0.982 1.059 1.078 0.984 1.0611997 1.021 1.021 1.042 1.038 1.009 1.0471998 1.040 1.025 1.066 0.969 1.039 1.007

Public sector banks1993 0.907 1.042 0.945 1.028 0.923 0.9491994 1.003 1.006 1.008 1.036 0.908 0.9401995 0.994 0.987 0.981 1.065 0.978 1.0411996 1.020 0.973 0.993 0.954 0.952 0.9081997 1.019 0.993 1.012 1.033 0.980 1.0121998 1.005 1.021 1.027 0.974 1.032 1.005

Domestic private banks1993 0.900 1.004 0.903 1.036 1.047 1.0841994 0.973 1.080 1.051 0.958 0.980 0.9381995 1.055 0.993 1.049 1.083 0.998 1.0811996 1.001 1.001 1.002 1.197 1.003 1.2011997 0.951 1.031 0.980 1.000 1.011 1.0121998 1.016 1.013 1.030 0.920 1.041 0.958

Foreign banks1993 0.959 1.054 1.010 1.012 0.994 1.0061994 1.047 1.016 1.064 1.055 0.978 1.0331995 0.937 1.048 0.982 1.100 1.024 1.1261996 1.226 0.973 1.192 1.097 0.998 1.0951997 1.097 1.039 1.139 1.082 1.036 1.1211998 1.100 1.040 1.145 1.017 1.043 1.060


All banks1992–98 1.028 1.014 1.042 1.034 0.995 1.0291992–95 1.026 1.008 1.034 1.041 0.980 1.0201996–98 1.030 1.023 1.054 1.027 1.010 1.038

Public sector banks1992–98 1.008 0.996 1.004 1.014 0.961 0.9751992–95 1.006 0.988 0.994 1.043 0.936 0.9761996–98 1.012 1.007 1.020 0.987 0.987 0.974

Domestic private banks1992–98 0.999 1.023 1.022 1.028 1.013 1.0421992–-95 1.009 1.024 1.034 1.024 1.008 1.0321996–98 0.983 1.022 1.005 1.033 1.018 1.052

Foreign banks1992–98 1.077 1.023 1.102 1.060 1.012 1.0731992–95 1.063 1.012 1.076 1.055 0.999 1.0541996–98 1.099 1.039 1.142 1.065 1.026 1.092

EFCH ¼ Efficiency Change; TCH ¼ Technical Change; PCH ¼ Pure Efficiency Change;SCH ¼ Scale Efficiency Change; TFPCH ¼ Total Factor Productivity Change


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Another explanation is based on the argument that the presence of high non-

performing loans (NPLs) could have contributed to the difference between the two

models. In the case of public sector banks, the average value of NPLs as a percentage

of total loans was around 20 per cent in both countries throughout this period [see

Bhide et al., 2002; SBP, 2001]. This suggests that although public sector banks

became more productive in generating loans and advances with a given level of

inputs, the high incidence of NPLs restricted their ability to generate high levels of

income. It could be argued, therefore, that the highly competitive and flexible post-

liberalised environment merely encouraged the public sector banks to increase the

quantity of their loans rather than the quality.

A final possible explanation could be attributable to the lack of success of the

special tribunals, which were set up by the central banks in both countries to

recover NPLs. In India, for example, the establishment of the Board for Industrial

and Financial Reconstruction (BIFR) and the Debt Recovery Tribunals (DRTs) had

only modest success until 1999 [see Bhide et al., 2002]. The failure to recover high

NPLs affected banks’ income generation.

CONCLUSION

After years of heavy government intervention, both India and Pakistan introduced

financial liberalisation programmes in 1991 to improve the productivity of their com-

mercial banking sectors. This paper augments the existing studies on the impact of

these programmes by providing a comparative analysis of the changes in total

factor productivity in the commercial banking industries of both countries. Following

Leightner and Lovell’s methodology [1998], a Malmquist index was constructed for

two different bank service specifications: one was derived from the loan-maximising

objectives of the governments and the other from the income- or profit-maximising

objectives of the commercial banks.

The results indicate that total factor productivity in both countries improved

slowly and, therefore, they reflect the gradual or long term impact of financial liberal-

isation. In India, the loan-based model revealed an improvement in TFPCH of around

4.6 per cent for the entire study period and the income-based model showed a com-

parable improvement of 4.2 per cent. In Pakistan, the improvement was less marked,

with TFPCH improving by 3.7 per cent on the loan-based model, and 2.9 per cent on

the income-based model. The study also revealed that TFPCH in both countries was

adversely affected by the poor performance of public sector banks. They recorded the

smallest improvement in TFPCH because of their inability or unwillingness to adopt

new technology and realise tangible increases in efficiency. In contrast, however,

foreign banks in both the countries witnessed the highest productivity gains.

Finally, the paper examined why the loan-based model showed higher increases in

TFPCH compared to the income-based model. This divergence was particularly

evident in the case of public sector banks in both countries and could be attributed

to the presence of high levels of non-performing loans and the government’s inability

to implement speedy recovery strategies. This adversely affected the public sector


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banks’ ability to generate higher levels of income even when they were successful in

generating additional volumes of outputs. This implies that during the 1990s public

sector banks, especially in Pakistan, had expanded their business by increasing

advances and loan volumes but the crucial issue of asset quality, despite the introduc-

tion of government-backed tribunals, was largely neglected.

ACKNOWLEDGEMENT

The author would like to acknowledge the help and support of his PhD supervisor Professor Tony Cockerill.

NOTES

1. For example, in their extensive survey, Berger and Humphrey [1997] note that out of more than 120efficiency and productivity studies, only three are directed towards financial institutions in developingcountries.

2. A recent study by Hardy and de Patti [2001] examine the changes in cost and revenue efficiency ofcommercial banks in Pakistan using parametric distribution free approach.

3. See Arun and Turner [2002] for Indian commercial banking, and Zaidi [1999] for commercial bankingin Pakistan.

4. A recent study by Hardy and de Patti [2001] examine the changes in cost and revenue efficiency ofcommercial banks in Pakistan using parametric distribution free approach.

5. See, for example, Berger and Humphrey [1997] and Berger and Mester [1997] for various approachesto specify banks’ inputs and outputs.

6. This is especially the case for the commercial banks in the LDCs where, unlike in developed countries,fee income is very low for commercial banks, and banks rely on traditional loans and government secu-rities for income.

7. For Pakistan, decomposition of income into interest and non-interest is not available. So, for Pakistan,the output in Model B is income of commercial banks.

8. Website: http://www.rbi.org.in/annualdata/index.html.

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