bank efficiency ataullan cockrill le

7/27/2019 Bank Efficiency Ataullan Cockrill Le

1/10

Financial liberalization and bank efficiency:

a comparative analysis of India and

Pakistan

A L I A T A U L LA H * , T O N Y C O C K E R IL L and H A N G L Ey

Durham Business School, University of Durham, Mill Hill Lane,

Durham DH1 3LB, UK and yDepartment of Economics and Politics,

Nottingham Trent University, Nottingham, NG1 4BU

This paper provides a comparative analysis of the evolution of the technical

efficiency of commercial banks in India and Pakistan during 19881998, a periodcharacterized by far-reaching changes in the banking industry brought about by

financial liberalization. Data Envelopment Analysis is applied to two alternative

inputoutput specifications to measure technical efficiency, and to decompose

technical efficiency into its two components, pure technical efficiency and scale

efficiency. The consistency of the estimated efficiency scores are checked by examin-

ing their relationship with three traditional non-frontier measures of bank perfor-

mance. In addition, the relationship between bank size and technical efficiency is

examined. It is found that the overall technical efficiency of the banking industry of

both countries improved gradually over the years, especially after 1995. Unlike

public sector banks in India, public sector banks in Pakistan witnessed improvement

in scale efficiency only. It is also found that banks are relatively more efficient in

generating earning assets than in generating income. This is attributed to the

presence of high non-performing loans. In addition, it is found that the gap betweenthe pure technical efficiency of different size groups has declined over the years.

I . I N T R O D U C T I O N

After decades of excessive government regulations and

restrictions, the implementation of financial liberalization

has brought substantial changes in the banking sector of

developing countries: The sector has become relatively

less state-directed, more competitive, and open to foreign

banks and non-bank financial institutions.

1

While consid-erable research has gone into the macroeconomic impacts

of these changes, only a handful of studies have empirically

examined the impact of financial liberalization on the

efficiency of banks in developing countries. Until recently,

the empirical studies on the efficiency of banks have

primarily concentrated on the banking industry of devel-

oped countries, especially of the USA (see Berger and

Humphrey, 1997; Isik and Hassan, 2003). This paper con-

tributes to the burgeoning literature on the efficiency of

banks in developing countries by providing a comparative

analysis of the evolution of the technical efficiency of

commercial banks in two South Asian economies, namely

India and Pakistan, before and after the implementationof financial liberalization in the early 1990s.

Financial liberalization is an integral element of the on-

going Economic and Structural Reforms (ESRs) in India

and Pakistan (see Ahluwalia, 1999; Zaidi, 1999). Financial

liberalization includes, inter alia, a gradual deregulation

*Corresponding author. E-mail: [email protected] See Fry (1995) for changes in the financial sector in developing countries after the implementation of financial liberalizationprogrammes.

Applied Economics ISSN 00036846 print/ISSN 14664283 online # 2004 Taylor & Francis Ltd 1915

http://www.tandf.co.uk/journals

DOI: 10.1080/000368404200068638

Applied Economics, 2004, 36, 19151924


2/10

of interest rates and state-directed credit policies, reduction

in banks reserve requirements, entry of non-bank financial

institutions, reduced restrictions on entry and operations

of private (domestic and foreign) banks, and privatization

of public sector banks2 (see SBP, 2000; Arun and Turner,

2002). Prior to the financial liberalization, the governments

of India and Pakistan followed a policy of social control

that emphasized controlling banks operations eitherthrough state directives or through nationalization. In

India, the 14 largest commercial banks were nationalized

in 1969, and six more banks in 1980. In Pakistan, all

domestic private banks were nationalized and merged dur-

ing the mid 1970s to form five large public sector banks.

By the late 1980s, these nationalized banks controlled more

than 90% of the total deposits and the earning assets of the

banking industry (see SBP, 2000; Arun and Turner, 2002).

Operations of private sector banks, especially foreign

banks, were restricted to a few large cities only. In addition,

the governments stipulated lending targets to priority

sectors (e.g. agriculture), imposed low ceilings on interestrates on loans and deposits, directed public sector banks

to open branches in rural and semi-urban areas, and made

it mandatory for banks to hold government securities

in their asset portfolios in order to finance growing fiscal

deficits (see Sen and Vaidya, 1998; Zaidi, 1999). Under

this policy of social control, the governments determined

the direction and prices of financial services provided by the

banking industry; banks themselves had little control over

their inputs and outputs.

This policy of social control, though augmented

deposit mobilization and provision of loans to the prior-

ity sectors, resulted in a deterioration of banks profit-

ability and capital base and in an unsustainableaccumulation of non-performing loans in public sector

banks asset portfolios. In both countries, on average

the share of non-performing loans in total loans and

advances in public sector banks was above 20% (see

SBP, 2000; Arun and Turner, 2003). In this context, a

key objective of the financial liberalization of the early

1990s was to revive the banking industry by reducing

government regulations and restrictions, underpinning

on-site and off-site bank supervision, strengthening the

capital base of public sector banks, privatizing public

sector banks, and elevating competition through entry

of new foreign and domestic private banks. These meas-ures are expected to enable and encourage banks to

enhance their efficiency, i.e. their ability to transform

inputs into outputs, which, in turn, is expected to

enhance economic growth by increasing the volume of

funds intermediated in the economy.

Although some studies have examined the performance

of commercial banks in India, only a recent study

by Kumbhakar and Sarkar (2003), by using econometric

technique to measure the total factor productivity of

domestic banks, has analysed a time period long enough

to shed some light on the impact of financial liberalization.

In the case of Pakistan, only one study has measured

the efficiency of commercial banks by using aparametric Distribution Free Approach (DFA). These

studies are extended by employing non-parametric Data

Envelopment Analysis (DEA) to calculate the efficiency

of commercial banks in India and Pakistan before and

after the liberalization. Following Bauer et al. (1998), the

consistency of the DEA-based efficiency scores are checked

by examining their relationship with three traditional non-

frontier based performance indicators. In addition, the

relationship between size and the pure technical efficiency

of banks is examined.The comparative analysis of Indian

and Pakistani banking industries suggests that a similar

financial liberalization programme in two developing coun-

tries may lead to different outcomes in terms of its success

in fostering the technical efficiency of banks operating in

those countries.

The rest of the paper is structured as follows. Section II

briefly reviews some recent studies on financial liberali-

zation and the efficiency and productivity of banks in

developing countries. Section III provides an overview

of the measurement of technical efficiency using DEA.

Section IV presents empirical findings. Section V concludes.

I I . F I NANCI AL L I B E RAL I Z AT I ON

AND T HE E F F I CI E NCY OF B ANKSI N DE VE L OP I NG COUNT RI E S

Although many developing countries initiated financial

liberalization in the early 1980s, only recently have a few

studies examined its impact on the efficiency and produc-

tivity of banks operating in these countries. These studies

postulate that financial liberalization enhances the effi-

ciency and productivity of banks by creating a competitive

and flexible environment in which banks have more control

over their operations. For example, financial liberalization

allows banks to set interest rates on their assets and liabil-

ities that were previously determined by the government.

The empirical evidence on the impact of financial liberal-ization on the efficiency of banks is mixed. Leightner and

Lovell (1998) measure the total factor productivity growth

of Thai banks during 19891994 to evaluate the financial

liberalization of the late 1980s. Using two alternative

inputoutput models, one based on commercial banks

2 During the sample period used in this study, the legislative changes in India allowed public sector banks to tap the capital market to theextent of 49% of their total capital (see Bhide et al., 2002). In Pakistan in contrast, a major portion of two public sector banks, MuslimCommercial Bank and Allied Bank of Pakistan, was sold to private investors (see SBP, 2000).

1916 A. Ataullah et al.


3/10

objective to generate revenue and the other based on

central banks objective to intermediate funds, they

construct a Malmquist total factor productivity index for

Thai banks. Leightner and Lovell find that the productivity

of banks improved after the liberalization. Using a similar

approach, Gilbert and Wilson (1998) also find that finan-

cial liberalization in Korea had positive impacts on the

productivity of the Korean banking industry during theearly 1990s. In contrast, Hao et al. (2001) use a parametric

Stochastic Frontier Approach (SFA) to measure the

efficiency of Korean banks, and do not find any positive

relationship between the measured efficiency and financial

liberalization. Isik and Hassan (2003) employ DEA to

construct a Malmquist total factor productivity index for

Turkish banks during 19801990, and suggest that the

performance of banks improved after the implementation

of financial liberalization. In contrast, Yildirim (2002)

analyses the technical efficiency of Turkish banks between

1988 and 1999 using non-parametric DEA, and finds that

the Turkish banks did not achieve any sustained efficiencygains over the sample period.

Although some recent studies have measured the effi-

ciency of Indian banks, their analysis is restricted either

to the pre-liberalization period (see Bhattacharyya et al.,

1997) or to a single year in the post-liberalization period

(see Sathye, 2003). Only a recent study by Kumbhakar and

Sarkar (2003) investigates the impact of financial liberal-

ization by calculating growth in the total factor produc-

tivity (TFP) of 23 public sector banks and 27 private

domestic banks during 19851996 (their study excludes

foreign banks). Kumbhakar and Sarkar (2003) measure

TFP growth by estimating a translog cost function, and

decompose TFP growth into a technological change, ascale, and a miscellaneous component. They find consider-

able over-employment of labour in Indian banks and find

little evidence to suggest that the liberalization enhanced

the productivity of banks, especially that of public sector

banks. Kumbhakar and Sarkar suggest that public sector

banks in India have become too dominant to feel the

impact of changes in the economic environment brought

about by financial liberalization.

Hardy and de Patti (2001) examined the cost and

revenue efficiency of 33 banks in Pakistan during

19811998 by utilizing DFA. They find that during the

post-liberalization period, both costs and revenues ofbanks increased, and therefore conclude that the benefits

of improvements in revenue efficiency were transferred to

customers, e.g. borrowers and depositors. However, it is

submitted here that during the post-liberalization period,

the interest rate margin of the banking industry in Pakistan

increased considerably (see SBP, 2000). That is, banks

charged higher interest rates on their loans, but did not

transfer the higher rates to their depositors. Moreover,

there has been constant criticism in the domestic media

on the quality of services provided by Pakistani banks,

especially by public sector banks. Therefore, it may be

difficult to justify Hardy and de Pattis conclusion that

benefits of improvement in banks performance, if any,

were transferred to customers.

I I I . M E AS URE M E NT OF T E CHNI CAL

E F F I CI E NCY US I NG DE A

The technical efficiency of a firm refers to its success/

failure in transforming its inputs into outputs. It is a rela-

tive concept as its measurement requires a standard

of performance against which the success/failure of the

firm is assessed. Broadly speaking, the contemporary

empirical studies employ parametric or non-parametricfrontier techniques to measure the efficiency of firms rela-

tive to an estimated best-practice frontier that represents

the optimal utilization of resources (see Berger and Mester,

1997).3

The parametric approaches usually involve econometric

estimation of a prespecified stochastic production, cost

or profit function (see Bauer et al., 1998, pp. 9396). In

contrast, non-parametric DEA does not require the speci-

fication of a particular functional form for the frontier.

Instead, the production frontier is constructed through

a piecewise linear combination of the actual inputoutput

correspondence set that envelops the inputoutput corre-

spondence of all the firms in the sample (see Thanassoulis,2001). Hence, efficiency measurement is not contaminated

by a possible misspecification of the production function

(see Bauer et al., 1998). The main weakness of the DEA is

that measurement error and statistical noise are assumed

to be non-existent (Berger andMester, 1997; Yildirim, 2002).

In this paper DEA is employed for two reasons. First, as

discussed above, the existing studies have already employed

parametric techniques to investigate the impact of financial

liberalization on the performance of banks in India and

Pakistan. Therefore, it is pertinent to examine whether

the efficiency scores obtained through DEA calculation

support the conclusions reached by the existing studies.Second, as Bhattacharyya et al. (1997, p. 335) point out,

regulations and other market imperfections in developing

countries (especially decades of excessive regulation in

the banking industry) may distort input/output prices,

and, therefore, may complicate the measurement cost

and/or profit function using parametric approaches.

3 Parametric techniques are: Stochastic Frontier Approach, Distribution Free Approach, and Thick Frontier Approach. Non-parametricapproaches are: Data Envelopment Analysis, and Free Disposal Hull (see Bauer et al., 1998).

Financial liberalization and bank efficiency 1917


4/10

A simple DEA model

Consider N decision-making units (DMUs) (commercial

banks in the present case) producing J outputs using

I inputs (see Thanassoulis, 2001 for details). To measure

the efficiency of a DMU, Charnes et al. (1978) proposed the

use of the maximum of the ratio of weighted outputs to

weighted inputs for that DMU, subject to the condition

that similar ratios for all other DMUs in the sample be

less than or equal to 1. Mathematically,

max eo

PJj1 w

ojy

ojPI

i1 voix

oi

1

subject toPJ

j1 uo

j yn

jPIi1 v

oix

ni

1 n 1, . . . , N

voi , uo

j ! 0 i 1,2, . . . , I; j 1,2, . . . , J

where y

n

j and x

n

i are positive known outputs and inputs,respectively, of the nth DMU, and voi, uo

j are the variable

weights to be determined by solving linear problem 1. The

DMU being measured is indicated by the index o. The

optimization is defined for every DMU in the sample. If

the efficiency score eo 1, the DMUo is 100% efficient

within the sample; otherwise it is DEA inefficient.

Charnes et al. (1978) transformed the above into the fol-

lowing linear programming problem:

max ho XJ

j1uoj y

oj 2

subject to

XIi1

voixoi 1X

Jj1

uoj ynj X

Ii1

voi xni 0

n 1, . . . , N voi ! " uo

j ! "

i 1,2, . . . , I j 1,2, . . . , J

" is an arbitrary small positive number introduced in the

above problem to ensure that all of the known inputs

and outputs have positive weights. When h 1, DMU

is DEA efficient; otherwise it is DEA inefficient with respect

to other DMUs in the sample. The problem is solved N

times to obtain an efficiency score for each DMU in the

sample. The DEA is carried out by assuming either

Constant Returns to Scale (CRS) or Variable Returns toScale (VRS). The estimation with these two assumptions

allows the overall technical efficiency (OTE) to be decom-

posed into two collectively exhaustive components: pure

technical efficiency (PTE) and scale efficiency (SE) (see

Thanassoulis, 2001). PTE refers to managers capability

to utilize firms given resources, while SE refers to exploit-

ing scale economies by operating at a point where the

production frontier exhibits constant returns to scale.

Inputoutput specification and data source

The first step in measuring efficiency using DEA is to

specify the inputs and outputs of banks.4 Following

Leightner and Lovell (1998) two different, albeit comple-

mentary, inputoutput models for banks in India and

Pakistan are specified: Model A (loan-based model) postu-

lates that banks incur operating and interest expenses to

produce loans and advances, and investments; Model B

(income-based model) postulates that banks incur operat-

ing and interest expenses to produce interest and non-

interest income. The analysis covers the period from 1988

to 1998. The sample includes all the commercial banks in

India and Pakistan for which data for at least three years

are available. This will allow, to some extent, one to seewhether the efficiency of a bank is due to the capability of

managers or due to some random factors that cannot be

controlled for in the DEA calculations. In the case of both

the countries, the commercial banks included in the sample

control over 95% of total assets, deposits, and loans of the

commercial banking industry. Data for commercial banks

in Pakistan are obtained from various issues of Banking

Statistics of Pakistan published annually by the State

Bank of Pakistan. In the case of India, data from 1990 to

1998 are obtained from the recently uploaded data set on

the website of the Reserve Bank of India,5 and data from

1988 and 1989 are obtained from various issues of

Financial Analysis of Banks published by the IndianBanks Association. Banks having zero recorded values

for one or more outputs or inputs variables in any year

are excluded from the sample for that year in recog-

nition of the fact that the DEA is sensitive to outliers

(see Yildirim, 2002, p. 2294).

I V . E M P I RI C A L F I N D I NG S

Trends in the efficiency of commercial banks

in India and Pakistan

Tables 1 and 2 present the average annual efficiency

scores of commercial banks in India and Pakistan, respec-

tively, using output-oriented DEA calculated separately for

4 In the case of banks, there is no agreement on the inputs and outputs. This disagreement is due to dual nature of some of the servicesthat banks provide. For example, bank deposits can be regarded as banks inputs as they are the main inputs for loan production. On theother hand, high value added deposits, like integrated saving and checking accounts, can be regarded as banks outputs. See, for example,Berger and Humphrey (1997) for various approaches to specify banks inputs and outputs, especially the intermediation approach andthe production approach.5 Website: http://www.rbi.org.in/annualdata/index.html



5/10

Table 1. Technical efficiency of commercial banks in India

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1

Loan-based model (model A)OTE ABs 67.0 67.3 70.2 67.0 68.7 71.0 70.5 79.1 80.4 78.0 82.1 6

PSBs 73.3 75.1 75.5 75.5 78.3 76.9 73.7 79.5 80.4 82.7 83.2 7DPBs 63.1 62.9 67.9 61.7 67.2 61.9 68.1 75.8 74.7 76.1 79.5 6FBs 64.7 64.1 67.2 63.7 60.6 74.2 69.7 82.1 86.1 75.1 83.4 6

PTE ABs 85.0 84.8 87.2 84.8 88.3 88.3 83.1 88.6 88.8 88.4 91.4 8PSBs 89.2 90.2 93.0 90.6 92.1 91.9 90.3 92.5 92.8 93.5 94.8 9DPBs 81.3 83.6 85.2 80.9 89.8 85.0 76.6 87.3 82.5 82.7 87.2 8FBs 84.6 80.6 83.5 82.7 83.0 87.9 82.5 85.9 91.1 89.0 92.2 8

SE ABs 78.8 79.3 80.4 78.8 77.6 80.3 85.0 89.4 90.6 88.3 89.8 7PSBs 82.1 83.2 81.2 83.3 85.0 83.7 81.6 85.9 86.6 88.5 87.8 8DPBs 77.6 75.2 79.6 76.2 74.8 72.8 88.9 86.8 90.6 92.0 91.2 7FBs 76.5 79.5 80.5 77.0 73.0 84.4 84.5 95.6 94.5 84.4 90.5 7

Income-based model (model B)OTE ABs 58.0 58.2 59.3 60.6 59.6 60.5 62.6 67.9 65.6 69.4 71.6 5

PSBs 49.9 52.5 52.5 53.8 57.2 52.0 54.3 57.1 54.6 60.8 66.2 5DPBs 59.3 57.3 58.3 61.2 57.7 61.6 64.7 64.4 70.7 70.8 72.2 5FBs 64.9 64.7 67.0 66.9 63.8 68.0 68.8 82.3 71.4 76.7 76.5 6

PTE ABs 80.1 79.1 81.4 81.8 81.1 82.6 83.7 86.4 84.7 86.7 87.8 8PSBs 81.0 81.5 83.5 82.1 84.2 84.3 86.1 87.3 89.1 89.0 90.1 8DPBs 79.9 75.7 79.3 80.1 77.6 81.4 79.6 82.3 81.9 85.5 86.0 7FBs 79.4 80.2 81.4 83.1 81.4 82.0 85.5 89.6 83.0 85.5 87.4 8

SE ABs 72.5 73.6 72.9 74.1 73.5 73.4 75.0 78.5 77.9 80.3 81.6 7PSBs 61.6 64.4 62.9 65.5 67.9 61.7 63.1 65.4 61.3 68.3 73.5 6DPBs 74.2 75.8 73.5 76.3 74.3 75.7 81.3 78.3 86.3 82.8 83.9 7FBs 81.7 80.7 82.3 80.5 78.4 82.9 80.5 91.9 86.0 89.7 87.5 8

Note: AbsAll banks; PSBspublic sector banks; DPBs domestic private banks. Foreign Banks: OTE overall technical effi

SE scale efficiency. Figures in parentheses are standard deviations.


6/10

Table 2. Technical efficiency of banks in Pakistan

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 19

Loan-based model (model A)OTE ABs 41.1 37.9 35.6 40.2 44.1 35.9 37.6 39.9 42.4 53.9 57.4 38

PSBs 38.5 33.5 34.4 38.4 32.5 28.4 25.5 33.5 41.7 45.7 48.6 36DPBs n.a. n.a. n.a. n.a. 48.2 36.7 42.5 46.4 45 55.8 59.7 nFBs 43.7 42.3 36.8 42 51.7 42.5 44.9 39.8 40.4 60.3 63.9 4

PTE ABs 88.1 88.9 86.7 86.9 76 68.1 74.8 71.3 73.3 77.9 80.1 87PSBs 92.6 93.2 91.2 89.5 84 78.5 86.1 75.4 74.1 76.7 78.1 9DPBs n.a. n.a. n.a. n.a. 65.3 51.5 56.6 58.5 65.5 70 72.6 nFBs 83.7 84.6 82.1 84.3 78.7 74.3 81.6 79.9 80.2 87 89.6 83

SE ABs 46.9 43 41.2 46.4 59.4 54.9 53.2 57.8 58.4 69.6 71.9 44PSBs 41.6 35.9 37.7 43 38.6 36.1 29.6 44.4 56.2 59.6 62.2 39DPBs n.a. n.a. n.a. n.a. 73.8 71.3 75.1 79.3 68.7 79.7 82.3 nFBs 52.2 50 44.8 49.8 65.7 57.2 55 49.8 50.4 69.3 71.2 49

Income-based model (model B)OTE ABs 45.8 51.7 46 47.4 52.6 52.8 48.4 56.9 63.8 64.4 65.6 47

PSBs 33 37.5 31.6 37.3 37.4 37.7 37.2 37.3 34.5 35.3 40.9 34DPBs n.a. n.a. n.a. n.a. 61.8 55.2 45.4 60.3 80.9 82.4 79.3 nFBs 58.5 66 60.3 57.5 58.8 65.4 62.6 73.1 75.9 75.5 76.6 60

PTE ABs 83.7 87.5 84.3 84.5 78.5 82 76.8 79.3 84.9 86.4 85.2 85PSBs 85.6 89.3 86.2 88.5 76.7 79.4 79.1 80.5 75.8 81.2 79.6 87DPBs n.a. n.a. n.a. n.a. 80.1 80.3 69.1 72.2 88.9 86.4 87.5 nFBs 81.9 85.7 82.4 80.6 78.7 86.2 82.1 85.1 89.9 91.5 88.4 82

SE ABs 55 59.5 54.9 56.7 66.8 64 63 71.9 73.6 73.8 76.2 56PSBs 38.6 42 36.6 42.1 48.7 47.5 47 46.3 45.5 43.4 51.4 39DPBs n.a. n.a. n.a. n.a. 77.1 68.7 65.7 83.5 91 95.4 90.6 nFBs 71.4 77 73.2 71.4 74.7 75.9 76.3 85.9 84.4 82.5 86.6 73

Note: ABsAll banks; PSBspublic sector banks; DPBs domestic private banks. Foreign banks: OTE overall technical effi

SE scale efficiency. Figures in parentheses are standard deviations. n.a. refers to the time period when domestic private banks w


7/10

each country using annual frontiers.6 The banking industry

has been divided into three groups according to ownership:

public, foreign, and domestic private. The whole period

(i.e. 19881998) is divided into three subperiods: 1988

1991 refers to the pre-liberalization period, 19921994 is

considered as the transition period, and 19951998 repre-

sents the post-liberalization period when the liberali-

zation programme is expected to have some impact onthe efficiency of banks.

The banking industry in both the countries exhibits very

low OTE, and witnessed little improvement until 1995.

In the case of India, this is consistent with Kumbhakar

and Sarkars (2003) findings. In both the countries, the

major source of low OTE was low SE, which has not

been examined by the previous empirical studies on

Indian and Pakistan banking industry. The low level of

SE could be attributed to governments restrictions on

private banks to extend their operations, and governments

direction to public sector banks to extend their branch

network to rural and suburban areas. These policies hin-dered banks ability to exploit scale economies. The limited

improvement in OTE until 1995, it is submitted, suggests

that banks adapted slowly and cautiously to the changes

brought about by the liberalization (see Bhattacharyya

et al., 1997).

The average OTE of the Indian banking industry

improved from 67.9% (Model A) and 59.0% (Model B)

in the pre-liberalization period to 79.9% (Model A) and

68.6% (Model B) in the post-liberalization period. In case

of Pakistan, the OTE of the banking industry increased

from 38.6% (Model A) and 47.7% (Model B) in the pre-

liberalization period to 47.8% (Model A) and 62.6%

(Model B) in the post-liberalization period. Unlike inIndia, where improvement in the OTE was due to improve-

ment in both PTE and SE, the improvement in the OTE of

the banking industry in Pakistan was due only to improve-

ment in SE, especially after 19951996 when the govern-

ment allowed public sector banks to reduce the number of

employees and close unprofitable branches in rural areas.

In Model A, the average PTE of the banking industry in

Pakistan declined from 87.6% during the pre-liberalization

period to 75.6% during the post-liberalization period,

while in Model B PTE declined from 85.0% (pre-liberal-

ization) to 83.9% (post-liberalization). This decline in PTE

in the banking industry was due to a sharp decline in thePTE of public sector banks even when the PTE of foreign

banks and private domestic banks improved during

this period. The PTE of public sector banks declined

from 91.6% (Model A) and 87.4% (Model B) in the pre-

liberalization to 76.6% (Model A) and 79.3% (Model B)

in the post-liberalization period. It could be argued that,

unlike in India, the financial liberalization process in

Pakistan failed to encourage the managers of public sector

banks to utilize their resources more efficiently. This could

be due to the fact that although both the countries

followed a similar financial liberalization programme, the

economic environment in Pakistan was marred by high

political instability during the 1990s. This high political

instability could have undermined the Pakistani govern-ments commitment to the liberalization process, and,

therefore, failed to encourage public sector banks to

enhance their resource utilization.

Like Kumbhakar and Sarkar (2003), it is found that,

unlike private sector banks, public sector banks in both

India and Pakistan were relatively slow in improving

their efficiency over the years. Following Kumbhakar

and Sarkar, it is suggested that this group has become

too dominant (controlling more than 90% of the assets

of the banking industry) to feel any need to quickly trans-

form itself in the face of competition from smaller foreign

and private domestic banks. Also, public sector banks

huge non-performing loans and extensive branch-networks

might have made them inflexible even if they wanted

to adapt to the changing environment. However,

after 19951996, public sector banks exhibit more improve-

ment in their efficiency. This could be due to a slight inten-

sification of competition as a result of adopting new

financial technology (e.g. computerization of bank

branches and Automated Teller Machines) and the intro-

duction of new financial products (e.g. credit cards and

car financing schemes) by private banks, especially foreign

banks. Private sector banks, especially foreign banks,

in both the countries witnessed improvement in both

PTE and SE.

Non-performing loans and the gap between

the two inputoutput models

As non-performing loans (NPLs) are a major problem

for the banking industry in India and Pakistan, it is crucial

to examine their impact on the evolution of technical effi-

ciency. This could be achieved by using NPLs as another

input, usually non-discretionary, that banks use (see Berger

and Humphrey, 1997). However, as the bank-level data on

NPLs are not available for India and Pakistan, an attempt

is made to examine their impact by taking a closer look

at the difference between the efficiency scores obtainedfrom the two models, i.e. the loan-based model and the

income-based model. Model A postulates that banks pro-

duce loans, advances and investments with given resources,

while Model B postulates that banks produce income with

given resources. Consequently, the outputs of Model B

(income) depend primarily on the outputs of Model A

6 For DEA estimation, we use DEAP 2.1 is used, developed by Tim Coelli of the University of New England, Australia.



8/10

(loans, advances and investments).7 However, if banks

are unable to enhance their income-based efficiency even

when they are able to improve their loan-based efficiency,

this could be due to the presence of high NPLs in their

portfolios.

In the case of Indian public sector banks, at the start of

financial liberalization in 19911992, the NPLs as a percen-

tage of total advances were around 24% (see Bhide et al.,

2002). This percentage, however, gradually declined to

16% in 19971998. The gap between the efficiency scores

obtained from two inputoutput models follows a similar

trend: during the early years, public sector banks were

much more efficient in generating loans, advances and

investments than in generating income. During the post-

liberalization era, however, this gap gradually declined.

In the case of the public sector banks in Pakistan, the

level of NPLs increased after the implementation of the

financial liberalization from around 18% of total advances

to around 26% (see SBP, 2000). The gap in the efficiencyscores of Pakistani public sector banks also increased over

the years. A similar gap between the efficiency scores of

private sector banks also exists in the two countries.

However, as the level of NPLs of private banks is much

lower than in the public sector banks, the gap between the

efficiency scores obtained from the two models is also

lower. This gap in the efficiency scores from the two models

may reflect the impact of the presence of high NPLs. That

is, over the years, the presence of NPLs impeded banks

ability to generate income even when they were relatively

more efficient in generating earning assets.8 It could be

argued that if the liberalization programme fails to enhance

the efficiency of banks to generate income from theirresources, it could, in the medium- and long-run, impede

their ability to intermediate between savers and borrowers

and to enhance the quality of their services, which, in turn,

may negatively influence the process of economic growth.

Consistency of the DEA efficiency scores

As suggested by Bauer et al. (1998), for the frontier-

based efficiency scores to be useful, the estimated scores

should be positively correlated with the traditional non-

frontier based measures of performance used by regulators,

managers, and industry consultants: Positive rank-order

correlations with these measures would give assurance

that the frontier measures are not simply artificial products

of the assumptions made regarding the underlying optimi-

sation concept (Bauer et al., 1998, p. 108). Table 3 presents

the Spearman Rank correlations between the PTE and SE

of the banking industry in India and Pakistan generated

by DEA and three non-frontier based measures of bank

performance, namely return on assets (ROA), total operat-

ing and interest cost per rupee of assets (TC/TA), and total

cost per rupee of revenue (TC/TR). The first measure is

expected to have a positive correlation with the frontier-

based efficiency scores, while the latter two are expected to

have a negative correlation. The results in Table 3 suggest

that most of the DEA-based efficiency scores are consistent

with the three non-frontier based performance measures.

Only in case of Pakistan, ROA is not consistent with the

loan-based PTE of banks. That is, there is an unexpected

negative correlation between loan-based PTE and ROA

of banks. This could be due to the increasing NPLs of

public sector banks in Pakistan, which suggests that evenwhen banks were becoming more efficient in generating

7 This is especially the case for the commercial banks in developing countries where, unlike in developed countries, fee income is very lowfor commercial banks, and banks rely on traditional loans and government securities for income.8 Another possible explanation for this gap between the efficiency scores obtained from the two models could be that banks transferredthe benefits of improvement in their efficiency to their customers because though banks produced more loans, advances and investments(i.e. intermediated more funds) with given inputs, they did not extract more income from this intermediation process. However,increasing interest margins in both the countries, coupled with constant criticism in the domestic media about the quality of customerservices provided by banks, especially public sector banks, may cast some doubt on this interpretation.

Table 3. Correlation between frontier and non-frontier based measures

India Pakistan

Model A Model B Model A Model B

PTE SE PTE SE PTE SE PTE SE

ROA 0.075* 0.035* 0.304** 0.050* 0.014* 0.002 0.015** 0.094*

TC/TA 0.166* 0.060** 0.088* 0.046 0.019* 0.032** 0.096 0.032TC/TR 0.075** 0.055 0.321** 0.095** 0.099** 0.055* 0.264** 0.072**

Note: PTEpure technical efficiency; SE scale efficiency; ROA return on assets; TC/TA total costs/total assets;TC/TR total costs/total revenue.*Spearman Rank Correlation is statistically significant at 5% level.**Spearman Rank Correlation is statistically significant at 1% level.



9/10

loans and advances, the profitability of banks (i.e. their

ROA) was deteriorating.

Bank size and pure technical efficiency

The evidence on the relationship between size and PTE of

banks is mixed. For example, in the context of Singaporeanbanking sector, Leong and Dollery (2002) find that larger

banks, due to complexity of their operations, exhibit higher

inefficiencies. In contrast, Yildirim (2002) find a positive rela-

tionship between size and PTE of Turkish banks. This posi-

tive relationship is attributed to larger banks market power

and their ability to diversify credit risk in an uncertain

macroeconomic environment. Berger and Humphrey (1997)

also find a positive relationship between size and efficiency

for the US banking industry.

To examine the relationship between size and PTE,

the banking industry in India and Pakistan was divided

into four quartiles according to their size, where the size

of each bank is determined by the total assets of that bankas a percentage of the total assets of the whole commercial

banking industry. Figure 1 presents the evolution of PTE

of different size groups. The figure suggests that in both the

countries, during the pre-liberalization period, the largest

banks outperformed the smaller ones. However, over the

years, the gap between the largest group and other groups

declined, and in case of Pakistan, the gap virtually disap-

peared. The catching-up of smaller banks could be due

to their higher flexibility, which allowed them to adapt

to changes in the banking industry brought about by

the financial liberalization programme. In contrast, the

declining efficiency of the largest group, which primarilyconstitute public sector banks, could be due to their

complex and politically-determined bureaucratic organi-

zational structure that impeded their ability to keep up

with smaller private domestic and foreign banks, which

were quicker to adopt new financial technology

(e.g. Automated Teller Machines) and to introduce new

financial products (e.g. car financing and credit cards)

(see SBP, 2000; RBI, various issues).

V . C O N C L U S I O N

This paper provides a comparative analysis of the evolu-

tion of the technical efficiency of the banking industry in

India and Pakistan before and after the implementation

of the financial liberalization programme of the early

1990s. Using non-parametric DEA, it is found that the

India

Model A Model B

Model A Model B

0

25

50

75

100

0

25

50

75

100

Pakistan

%E

fficiency

%E

fficiency

%E

fficiency

%E

fficiency

0

25

50

75

100

1988 1990 1992 1994 1996 1998

Year

Year Year

0

25

50

75

100

1988 1990 1992 1994 1996 1998

1988 1990 1992 1994 1996 19981988 1990 1992 1994 1996 1998

Year

Largest 2nd Quartile

3rd Quartile Smallest

Fig. 1. PTE scores by size quartile for commercial banks



10/10

overall technical efficiency of the banking industry

improved following the financial liberalization, especially

after 19951996. In the case of India, efficiency increased

due to improvement in both pure technical efficiency

and scale efficiency. In Pakistan, however, the increase in

overall technical efficiency was due primarily to an

improvement in scale efficiency.

The results suggest that the efficiency of commercialbanks is much higher in Model A, which uses earning

assets as outputs, than in Model B, which uses income

as output. This gap in efficiency scores obtained from the

two models could be due to the presence of high non-

performing loans in the asset portfolios of banks in the

two countries. It is argued that even when banks are

becoming more efficient in increasing the quantity of

loans, advances and investments, this efficiency is not

being translated into higher efficiency in generating income.

The results also suggest that the implementation of the

financial liberalization closed the efficiency gap between

large and small banks.

The results suggest that there is still room for improve-

ment in the efficiency of banks in both the countries. A major

problem, however, is the presence of high non-performing

loans. It should be noted that in developing countries the

non-performing loans accumulate not only due to the inef-

fectiveness of banks managers but also due to other factors,

such as economic downturns, politicians, pressure on banks,

managers to provide loans to clients who may not have

economically viable projects, or the weakness of legal sys-

tem to support the recovery of non-performing loans (see,

e.g. Bhide et al., 2002 for the limited success of Debt

Recovery Tribunals in India). A step forward for the liberal-

ization programme, therefore, is not only to deregulateinterest rates and enhance the level of competition but also

to strengthen the institutional structure to support good

practices in the banking industry.

ACKNOW L E DGE M E NT S

Helpful comments by Canan Yildirim and the participants

of the 4th Annual International Economics and Finance

Society Conference, London 2003, are gratefully acknowl-

edged. The usual disclaimer applies.

RE F E RE NCE S

Ahluwalia, M. S. (1999) Indias economic reforms: an appraisal,in India in the Era of Economic Reforms (Eds) J. D. Sachs,A. Varshney and N. Bajpai, Oxford University Press,Oxford. pp. 2780.

Arun, T. G., and Turner, J.D. (2002) Financial sector reformsin developing countries: the Indian experience, WorldEconomy, 25(3), 42945.

Bauer, P. W., Berger, A. N., Ferrier, G. D. and Humphrey, D. B.(1998) Consistency conditions for regulator analysisof financial institutions: a comparison of frontier efficiencymethods, Journal of Economics and Business, 50, 85114.

Berger, A. N. and Humphrey, D. B. (1997) Efficiency offinancial institutions: international survey and directionsfor future research, European Journal of OperationalResearch, 98, 75212.

Berger, A. N. and Mester, L. J. (1997) Inside the black box: whatexplains differences in the efficiencies of financial institutions,Journal of Banking and Finance, 21, 895947.

Bhattacharya, A., Lovell, C. A. K. and Sahay, P. (1997)The impact of liberalization on the productive efficiency ofIndian commercial banks, European Journal of OperationalResearch, 98, 33245.

Bhide, M. G., Prasad, A. and Ghosh, S. (2002) Banking sectorreforms: a critical overview, Economic and Political Weekly,February, 399408.

Charnes, A., Cooper, W. W. and Rhodes, E. (1978) Measuringthe efficiency of decision making unit, European Journalof Operational Research, 2, 42944.

Coelli, T., Rao, D. S. P. and Battese, G. E. (1998) An Introductionto Efficiency and Productivity Analysis, Kluwer AcademicPublisher, USA.

Fry, M. J. (1995) Money, Interest, and Banking in EconomicDevelopment, 2nd edn, Johns Hopkins University Press,Baltimore.

Gilbert, R. A. and Wilson, P. W. (1998) Effects of deregulation

on the productivity of Korean banks, Journal of Economicsand Business, 46, 3964.

Hao, J. Hunter, W. C. and Yang, W. K. (2001) Deregulationand efficiency: the case of private Korean banks, Journalof Economics and Business, 53, 23754.

Hardy, D. C. and di Patti, E. B. (2001) Bank reform and bankefficiency in Pakistan, IMF Working Paper, WP/01/138.

IBA (19861992) Financial Analysis of Banks, Indian BanksAssociation, Bombay.

Isik, I. and Hassan, M. K. (2003) Financial deregulation andtotal factor productivity change: an empirical study ofTurkish commercial banks, Journal of Banking and Finance,27(8), 145585.

Kumbhakar, S. C. and Sarkar, S. (2003) Deregulation, ownership,and productivity growth in banking industry: evidence from

India, Journal of Money Credit and Banking, 35(3), 40324.Leightner, J. E. and Lovell, C. A. K. (1998) The impact of finan-

cial liberalisation on the performance of Thai banks, Journalof Economics and Business, 50, 11531.

Leong, W. H. and Dollery, B. (2002) The productiveefficiency of Singapore banks, Working Papers Seriesin Economics, University of New England, website:http://www.une. edu.au/febl/EconStud/wps.htm.

RBI (various issues), Trend and Progress in Banking in India,Reserve Bank of India, website: http://www.rbi.org.in.

Sathye, M. (2003) Efficiency of banks in a developing economy:the case of India, European Journal of Operational Research,148(3), 66271.

SBP (2000) Pakistan: financial sector assessment 19902000, web-site: http://www.sbp.org.pk/publications/fsa/index.htm.

Sen, K. and Vaidya, R. R. (1998) India, in Financial Reforms inDeveloping Countries (Eds) J. M. Fanelli and M. Rohinton,International Development Research Centre, Ottawa,Canada, pp. 5789.

Thanassoulis, E. (2001) Introduction to the Theory and Applicationof Data Envelopment Analysis, Kluwer Academic Publisher,USA.

Yildirim, C. (2002) Evolution of banking efficiency withinan unstable macroeconomic environment: the case ofTurkish commercial banks, Applied Economics, 34, 2289301.

Zaidi, S.A. (1999) Issues in Pakistans Economy, Oxford,University Press, Karachi.


bank efficiency ataullan cockrill le

Documents