Liberalisation, ownership and efficiency issues:
A comparative study of South East Asian banking
By
Nghia Nguyen and Jonathan Williams
Abstract
This short paper estimates alternative profit efficiency for Asian banks of different
ownership between 1990 and 2002. Using a one-step stochastic frontier methodology
and the Fourier flexible functional form, we find that bank liquidity, the state of capital
regulation in Asian banking sectors, and population density are the most important
determinants of bank efficiency. Our analysis, however, supports foreign bank entry and
the sale of domestic banking assets to foreign owners as the foreign bank sector loses
less of potential profits to inefficiencies compared to other bank ownership forms. The
sale of public banking assets can also be advocated on efficiency grounds. Privatised
banks have become the most efficient banks in Asia although they were very vulnerable
to the 1997 financial crisis but their recovery has outpaced all other banks’. We suggest
that privatisation should try to spread bank ownership as widely as possible given the
relatively strong performance of widely-held banks. However, we add a note of caution
due to the fact that the efficiency of listed banks is relatively weak, which suggests that
capital market discipline needs to more effective.
JEL classification: G21, G28, G32, C14, D21, L33
Keywords: financial liberalisation, bank restructuring, profit efficiency, Asian banks,
stochastic frontier analysis, ownership
Corresponding author: Jonathan Williams, Centre for Banking and Financial Studies,
School for Business and Regional Development, University of Wales, Bangor,
Gwynedd, UK, LL57 2DG.
Email: jon.williams@bangor.ac.uk
1.
Introduction
The objective of this short paper is to examine the relationship between bank ownership
and bank efficiency n South East Asian banking over the period 1990 to 2002. We
construct a dataset of banks from the five South East Asian countries that were most
severely affected by the 1997 financial crisis. Our dataset has 1,713 observations on
banks from Indonesia, Korea, Malaysia, the Philippines and Thailand. Using bank
annual reports and other sources, the ownership criteria of Asian banks is identified and
categorised into ten groups. The dataset categorises changes in bank ownership
including changes brought about by financial restructuring programmes implemented in
after the 1997 financial crisis.
Our approach is to employ a one-step stochastic frontier methodology and the Fourier
flexible functional form to estimate alternative profit efficiency or the potential profit
that banks lose to inefficiencies. We specify a vector of environmental variables that are
postulated to be related to bank efficiency. In addition to the different ownership criteria
found in Asia, we also take account of the relationships between macro economic
variables, banking condition variables, and firm specific variables and efficiency.
The paper has some important policy conclusions. As far as we are aware, this is the
first study of its type to estimate efficiency over a period that covers the implementation
of financial liberalisation programmes, financial crisis, and financial restructuring.
Specifically, we aim to establish what the main determinants of bank efficiency are and
whether bank ownership form is one of the determinants. Our analysis contributes to the
established empirical literature on the privatisation of bank assets, the debate
surrounding foreign bank entry, the continuing presence of the state in domestic
banking, principal agency problems associated with different types of shareholding, to
family-ownership of banks. In addition, since the Asian banking systems were heavily
restructured after the crisis, our results provide possibly the first indication as to how
well banks of different ownership structure are performing in the post-crisis period.
Arguably, Asia's banking system was over-banked before the crisis but the number of
commercial banks has declined considerably thereafter. To strengthen banking systems
and to build strong banks that can compete with large foreign banks, the authorities
continue to consolidate domestic banking systems. Consolidation methods include the
closure or nationalisation of banks and non-bank financial institutions that cannot
continue to operate (disposal/collection of assets taken over; privatization of
nationalized banks), sale to foreign banks or foreign capital, and consolidation of local
banks through a holding-company system (creation of core banks) or other means.
However, the pace of consolidation varies across countries. For instance, the Indonesian
government has largely consolidated its financial system; out of 237 banks in 1997, 69
insolvent banks have been closed, 22 weak and small banks were merged with larger
banks and 17 other were taken over. The total number of commercial banks from 237
banks in 1997 fell to 151 banks at end 2002. In Malaysia, 71 domestic banking
institutions were merged into 10 banking groups in 2001. The pace of consolidation in
Korea was also very rapidly, from 86 banks in 1997 to 76 banks in 1998 and 59 banks at
end 2002. Thailand and Philippines have also consolidated their financial systems
although the pace is very limited.
2
The remainder of the paper is organised as follows. In section 2, we review bank
efficiency studies in South East Asian banking systems. Section 4 presents the
efficiency methodology whilst the parameters of the dataset are discussed in section 5.
The results are reported in section 6 and some conclusions are offered in section 7.
2.
Bank efficiency and financial deregulation in South East Asia
Whilst there are several studies of the effects of financial deregulation on bank
efficiency in developed countries (see Berger and Humphrey, 1997 for an extensive
review) there is a paucity of efficiency studies in South East Asia. The majority of
studies are country specific and we review their main findings and implications below.
Specifically, we discuss relationships between financial liberalisation and bank
efficiency, and ownership form and efficiency.
Gilbert and Wilson (1998) find that privatisation and financial deregulation had a
positive effect on the productivity of Korean banks between 1980 and 1994. Using
Malmquist productivity techniques, Gilbert and Wilson argue that Korean banks
improved their productivity because privatisation and deregulation allowed the banks to
substantially alter their input and output mix which when combined with technological
developments enabled the banks to increase their potential output. The positive outcome
of financial deregulation is not confirmed by Hao et al., (2001) who use a two-step
stochastic frontier methodology to estimate cost efficiency for a sample of private
Korean banks between 1985 and 1995. These authors estimate mean cost efficiency to
be nearly 89% but efficiency is time-invariant. This leads Hao et al., (2001) to suggest
that the positive relationship between deregulation and productivity found by Gilbert
and Wilson was more likely to have occurred between 1980 and 1985, that is, after the
deregulation programme of 1980. According to the authors, the 1991 deregulation had
not yielded any significant association with bank cost efficiency by 1995. However,
their findings have an important implication for bank ownership. Cost efficiency of
Korean banks is positively related to the amount of foreign equity ownership but
negatively related to the share of government ownership.
Leightner and Lovell (1998) find that financial liberalisation generally lead to an
improvement in bank efficiency and productivity in Thailand between 1989 and 1994.
Large domestic-owned banks are found to be the most efficient institutions (85%) with
foreign bank efficiency being comparable to medium sized domestic banks (at 75% and
74%, respectively). However, there is a group of smaller foreign banks that are
estimated to be highly inefficient (22%). The relative success of large domestic
institutions is attributed to their ability to take advantage of regulatory changes in order
to expand their output and input. In addition, the large domestic banks and also the
foreign banks either possessed or could afford to acquire the skills necessary to cope
with the demands of financial liberalisation. The relative under performance of smaller
domestic institutions is attributed to their ownership; these institutions are mostly
family-owned firms that are posited to exist to maximise family assets rather than
profits. Okuda and Mieno (1999) estimate the cost efficiency of domestic banks
between 1985 and 1994 using seemingly unrelated regression and the translog cost
function. Between 1985 and 1994, the level of average cost efficiency is just over 77%.
However, financial liberalisation is accompanied by an increase in the variance of bank
inefficiency. Williams and Intarachote (2002) investigate financial liberalisation and
3
bank profit efficiency in Thailand. They find that after liberalisation, bank profit
efficiency decreases at an increasing rate over time. On average, Thai banks lost 2.66%
of potential profits to inefficiency in 1990 but in 1997 they lost 38.5%. Foreign banks
fared little better with comparative efficiencies of 2.62% and 37.69%, respectively. The
evidence provided by Williams and Intarachote (2002) implies that the deregulationinduced expansion of banking activity ultimately increased financial fragility. Whilst
mean domestic and foreign bank efficiency is comparable, Japanese-owned banks are
significantly more efficient, which supports the limited version of the global advantage
hypothesis that foreign banks from strong home environments may carry efficiency
advantages overseas (see Berger et al., 2000).
Katib and Mathews (2000) use data envelopment analysis (DEA) to estimate the
efficiency of 20 Malaysian commercial banks from 1989 to 1995. Whilst efficiency
ranges between 68% and 80%, the trend in efficiency is downwards. Whereas the bank
efficiency studies in Thailand generally agree that large domestic institutions are more
efficient, it is the medium-sized banks that are found to be more efficient in Malaysia.
Specifically, Katib and Mathews report that large Malaysian banks are beset by scale
inefficiencies whereas smaller banks are characterised by increasing returns to scale.
Okuda et al., (2002) employ a parametric approach to estimate Malaysian bank cost
efficiency between 1991 and 1997 with the intention of analysing the effect of changes
in the industrial structure and efficiency of commercial banks following the financial
liberalisation programmes of the 1990s. For a sample of 19 commercial banks, mean
cost efficiency is estimated to be 83% after controlling for asset quality. Like Katib and
Mathews (2000), Okuda et al., (2002) find that financial liberalisation is accompanied
by an increase in banks’ operational costs over time and negative technological
progress. However, Okuda et al., (2002) report that small sized banks are more cost
efficient than large sized banks.
The only cross-country study of Asian bank efficiency that we are aware of is Laeven
(1999) who uses DEA to estimate efficiency in Indonesia, Korea, Malaysia, the
Philippines and Thailand. Laeven’s study is directly comparable to the present paper
because he investigates the relationship between bank ownership and efficiency under
different ownership structures. Laeven develops an indicator of risk taking which is
measured as excessive loan growth that is defined as being growth above the level of
loans that a bank would have provided if it would have put its inputs at use as efficiently
as in a defined base year. Laeven (1999) concludes that foreign owned institutions took
little risk whereas family-owned and company-owned banks engage in much greater
risk talking behaviour. The risk indicator is used to predict those institutions that would
experience difficulties during the 1997 financial crisis. The banks that were to be
restructured (either through merger or recapitalisation) had excessive credit growth,
were mostly family-owned or company-owned, and were almost never foreign-owned.
In terms of comparative efficiency at the country level, Philippine banks realised a
relative increase in efficiency whereas efficiency decreased for Malaysian banks relative
to banks in the other three countries (see Laeven, 1999).
3.
Efficiency concept and methodology
The combination of technical and allocative inefficiencies is commonly referred to as
X-inefficiency and is regarded as a measure of the quality of management (see
4
Leibenstein, 1966). Technical inefficiency results from bank management employing
too much input to produce output whereas allocative inefficiency arises from
management’s failure to react optimally to the relative price of input. Profit efficiency is
the ratio of predicted actual profit to predicted maximum profit, which could be earned
if a bank was as efficient as the best practice bank after adjusting for random error.
Profit inefficiency estimates may be interpreted as the amount of profit that is being lost
to inefficiency and it emphasises that bank management should pay attention not only to
the marginal cost of raising financial resources, but also to the raising of marginal
revenue.1
Whereas data for loans, assets, capital, and loan loss provision are available from banks’
financial statements, efficiency must be estimated. Inefficiency is estimated using the
stochastic frontier and Fourier flexible form methodologies. Stochastic frontier analysis
was proposed by Aigner et al. (1977), Meeusen and van den Broeck (1977) and Battese
and Corra (1977). These models have a two component error term. The first error
component is symmetric and captures the random variation of the frontier across firms,
statistical noise, measurement error, and random shocks that are external to the firm’s
control. The second error component is a one-sided variable that captures inefficiency
relative to the frontier. Jondrow et al. (1982) enhanced the methodology by developing
a method for estimating firm-level inefficiency.
We estimate bank efficiency using the stochastic frontier model of Battese and Coelli
(1995) in which the inefficiency term is drawn from a truncated normal distribution.
The model is a “one-step” procedure in which the stochastic frontier is specified using
the Fourier flexible functional form whilst the level of firm inefficiency is determined
by a vector of environmental variables that a priori are postulated to affect inefficiency
(see Wang and Schmidt, 2002, for a discussion of one-step and two-step methods). The
importance of specifying environmental variables in order to avoid bias in efficiency
models has been noted in the existing literature (see Dietsch and Lozano-Vivas, 2000;
Chaffai et al, 2001; Lozano-Vivas et al, 2001; Lozano-Vivas et al, 2002). The vector of
environmental variables is described in Table A1 and some descriptive statistics are shown
in Table A2.
The model is written for panel data in equation [1] with the inefficiency effects being
specified in equation [2].
Y
it
 exp  xit   V it  U it 
U
it
=
Z
it
 + W it
[1]
[2]
where
Yit denotes the operating profit for the t-th observation (t = 1, 2 … T) for the i-th firm (i =
1, 2 … N);
xit is a (1 x k) vector of known inputs and outputs associated with the i-th observation at
the t-th period of observation;
ß is a (k x 1) vector of unknown parameters to be estimated;
1
See Berger and Mester (1997) for a discussion of the relative merits of the concepts of cost efficiency,
standard profit and alternative profit efficiency.
5
Vit are independently and identically distributed N(0, σ2v) random errors that are
independently distributed of the Uit’s, which are non-negative random variables accounting
for the inefficiency in production;
Uit are independently distributed, such that Uit is obtained by truncation (at zero) of the
normal distribution with mean, Zitδ, and variance, σ2, that is N(mit, σ2u);
where mit = Zit δ;
Zit is a (1 x m) vector of environmental variables that are allowed to vary over time; and δ
is an (m x 1) vector of unknown coefficients of the environmental efficiency variables.
Wit is defined by the truncation of the normal distribution with zero mean and variance,
σ2, such that the point of truncation is –Zitδ. That is, Wit ≥ -Zitδ, which is consistent with
the Uit’s being non-negative truncations of the N(Zit, δ, σ2) distribution.
Battese and Coelli (1995) show that when equation [1] is assumed, the alternative profit
efficiency for the i-th firm at the t-th observation is defined by equation [3].
TE
it


= exp  U it = exp
 Z   W 
it
it
[3]
The W-random variables are not identically distributed and could be negative if Zit > 0,
that is, Wit ≥ -Zitδ. The W-random variables are independent truncations of the normal
distribution with zero mean and variance, σ2.
The alternative profit function is specified using the Fourier flexible functional form.
The Fourier is a semi-nonparametric approach and is used to tackle the problem arising
when the true functional form of the relationship is unknown. Gallant (1981, 1982),
Mitchell and Onvural (1996), Ivaldi et al. (1996), and Berger et al. (1997) note that the
Fourier is a global approximation, which can represent a broader range of cost and
profit structures than other functional forms. For instance, the Fourier has been shown
to dominate the conventional translog functional form that has been commonly applied
in bank efficiency studies (see Mitchell and Onvural, 1996; Berger and Mester, 1997)
whereas Ivaldi et al. (1996) finds that the Fourier better captures sample heterogeneity
than the translog. In addition, the local point estimate produced by the translog
functional form is found to be inappropriate to approximate the true or underlying
technology of an industry (Ivaldi et al., 1996). Following Berger and Mester (1997), this
study applies the trigonometric Fourier terms only for output, leaving the input price
effects to be defined entirely by the translog terms.2 The bank production process is
modelled according to the intermediation approach which considers banks to be
financial intermediaries that purchase input in order to generate earning assets (see
Sealey and Lindley, 1977). The alternative profit efficiency model has three outputs,
two variable inputs and two fixed netputs. Standard restrictions of linear homogeneity in
input prices and symmetry of the second order parameters are imposed.
The model specification for the alternative profit function is shown in equation [4]:
Following Berger and Mester (1997), 10% is cut off each end of the [0,2π] interval so that the z i span
[0.1 x 2π, 0.9 x 2π] in order to reduce approximation problems near endpoints. The formula for z i is 0.2π
– μ x a + μ x variable, where [a,b] is the range of the variable being transformed, and μ ≡ (0.9 x 2π – 0.1 x
2π/(b-a)).
2
6

ln OP /
1
pz
3
2
i 1
2
2
    1T  1
3

ij
j 1
ln
Q / z ln Q / z 
i
  r ln  z r / z 2   1
2
r 1
3

i 1
2

k 1
3

n 1
3

n 1
2
 ij ln
r 1
2
j
2

2
r 1
i
2
i 1
p 1
np
3
3
p 1
q 1
s 1
rs
i 1
1
r
2
2
k 1
2
2

k 1
r 1
Q / z   
3
i
Q / z    ln P / P 

2
2
i
2
m 1
km
k 1
k
k
2
ln Pk / z 2 ln Pm / z 2 
ln  z r / z 2 ln  z s / z 2 
2
 ki ln Pk / P2 ln
 a
2
2
   1 ln
Q / z ln z / z   
3
3
2 11T
3
2
2
n 1
a
n
kr
ln Pk / P2 ln  z r / z 2 
cos xn   bn sin  xn 
cosxn  x p   bnp sin xn  x p 
  a
npq
cosxn  x p  xq   bnpq sin xn  x p  xq   ln  c  ln  c
where
lnOP is the natural logarithm of operating profit where a constant term, θ, is added if
any bank reports an operating loss. (θ is equal to the absolute of minimum operating
profit plus one so that the natural log is taken of a positive number.)
T is the time trend
lnQi is the natural logarithm of bank output (loans, other earning assets, off-balancesheet items);
lnPk is the natural logarithm of ith variable input prices (the prices of financial capital
and labour);
lnZr is the natural logarithm of fixed netput quantities (physical capital and equity);
Xi are the adjusted values of the log of output lnQi such that they span the interval [0,
2π];
i are identical and independently distributed random variables, which are independent
of the μi, which are non-negative random variables that are assumed to account for
inefficiency.
α, , β, ψ, θ, , , , , a and b are the parameters to be estimated using maximum
likelihood methods.
5.
Data classification
The data for the efficiency estimation are sourced from the BankScope database for the
period 1990 and 2002. The number of banks by country and year are shown in Table 1.
The largest number of banks is from Indonesia (627) followed by the Philippines (301),
Malaysia (289), Korea (259) and Thailand (225). In order to qualify the bank ownership
information and changes that have taken place over time, we have relied upon additional
sources of information including company annual reports, the World Bank and Asian
Development Bank. We are able to identify ten categories of bank ownership though it
should be noted that banks can enter into more than one category. State-owned banks
7
are either public commercial banks or specialised government institutions. The majority
of banks are commercial banks and their ownership is classified as being foreignowned, family-owned, company-owned, and financial-owned (owned by financial
holding company & other banks). We further categorise the sample to distinguish
between widely-held banks (more than three shareholders, but without a majority
shareholder) and listed banks. The final two categories are crisis banks (either private
commercial or state-owned institutions that have been closed or received liquidity
injection during the financial crisis) and privatised banks (privatised banks or banks
taken over by government vehicle and later sold to domestic or foreign-owned
institutions). Our sample contains 576 observations on state-owned banks and 351
observations on foreign-owned banks. There are 285 observations of family-owned
banks, 313 observations of company-held banks, 331 observations of financial-owned
banks and 571 observations of widely-held banks. In addition, there are observations of
545 listed banks, 671 crisis banks, and 70 privatised banks.
Table 1 here
The means and standard deviations of the variables used in the alternative profit
efficiency model are shown in Table 2. For information, we show the descriptive data at
country level and according to bank ownership type. Korean banks have the highest
operating profit whereas the lowest operating profits are posted in Indonesia and the
Philippines. The variation in Korean bank operating profits is extremely large.
Similarly, Korean banks hold a larger amount of loans that is over twice as much as the
next largest loan holder, Thailand. However, Thai banks conduct more off-balancesheet business followed by Philippine and Malaysian banks.
Table 2 here
Re-examining the descriptive data by ownership provides several interesting insights of
banking sector activity in Asia. The largest average profits are made by privatised banks
and they are more than twice as much as the second largest profit maker, the state
banks. In terms of gross operating profit, the lowest volume of profit is recorded by the
foreign banks and family-owned banks. We note the dominance of the relatively small
number of privatised banks in terms of the size of their loan portfolio and other earning
assets. Surprisingly, the largest average value of off-balance-sheet business is held by
family-owned banks; indeed the volume of off-balance-sheet business at family-owned
banks is larger than the on-balance-sheet business.
6.
Results
The results of the efficiency estimation are reported in three sub-sections. First, we
examine the coefficients of the technical inefficiency effects model that is used to
estimate alternative profit efficiency for the sample of Asian banks. These coefficients
are interpreted as determinants of efficiency. In the second sub-section, we present the
estimated profit efficiencies by ownership type for each year from 1990 to 2002.
Finally, we show mean profit efficiency for the whole period for each country and
ownership form and we report the results of t-tests of differences of means across bank
ownership type.
8
6.1
Determinants of efficiency
Using the one-step technical inefficiency effects model allows us to specify a vector of
environmental variables that are regressed against the profit efficiencies of the sample
Asian banks. We now discuss the estimates of the coefficients for the vector of
environmental variables. The estimated coefficients of the profit function and the
technical inefficiency effects model are shown in Table 3.
The parameter estimates imply two types of bank are significantly more profit efficient,
that is, they lose a lesser percentage of potential profit to inefficiencies than banks
organised under alternative ownership forms. The banks are commercial banks and
widely-held banks. State banks, listed banks and crisis banks are estimated to be
significantly less profit efficient. The inclusion of listed banks in this cohort is
somewhat surprising because of the implication that the market has failed to discipline
bank management.
The results suggest that other bank ownership types do not yield a significant impact on
bank efficiency. For information purposes, we report that foreign-owned banks,
financial-owned banks and privatised banks lose less of their potential profit to
inefficiencies but the coefficients are not significant. Similarly, family and companyowned banks lose more of their potential profit to inefficiencies but the loss is not
significant. Nevertheless, the results offer albeit tentative support for previous findings
in the literature.
Table 3 here
Our estimates suggest that the environmental variables are more important determinants
of bank efficiency than ownership type. Macro economic factors play an important role
in determining bank efficiency. As expected, banks operating in countries with a higher
population density are significantly more efficient because they face relatively lower
costs than banks in less dense areas. However, banks operating in richer countries
(measured by real GNP per capita) are significantly less profit efficient. This is an
unusual finding and there are several possible explanations. Bank customers in richer
countries can be expected to be more sophisticated and as a result competition between
banks may be relatively more aggressive implying that bank management has not been
successful in meeting this challenge.
A set of banking condition ratios provide information on the structure of Asian banking.
The ratios are the density of deposits, the Herfindahl-Hirschman index of concentration,
the average levels of equity-to-assets, intermediation, and non-performing loans/total
loans in each country. A priori the coefficient on the relationship between deposit
density and efficiency is expected to be positive because greater density implies easier
access to banking products and services. The magnitude of this coefficient is one of the
largest and most significant in the vector of environmental variables. The average level
of equity-to-assets is an indicator of the state of regulation in each country. We find a
large and significant relationship between this variable and bank efficiency, which we
interpret as meaning that a strengthening of regulations would lead to lower bank
efficiency. This finding suggests that the cost of compliance with prudential regulations
in Asia is relatively high for banks, which has adverse implications for systemic
stability.
9
The Herfindahl-Hirschman index of deposit market concentration is negative and
significantly related to efficiency, which implies that banks are more efficient in less
concentrated markets. Though not an unexpected finding, one possible implication is
that competition is relatively less intense when concentration is lower and it is this
feature that allows banks to generate higher profit efficiency. The intermediation ratio
measures the cost of producing loans in terms of the amount of required deposits. We
find a positive and significant ratio between the average level of intermediation in Asian
banking systems and bank efficiency. The final banking condition indicator is the
average ratio of non-performing loans-to-total loans which is a proxy for asset quality in
the country. In accordance with much of the established literature we find that an
improvement in asset quality leads to higher levels of bank efficiency.
The final four variables are the capitalisation and liquidity of each bank, year and its
quadratic term. The positive and highly significant coefficient for the relationship
between bank capitalisation and bank efficiency implies that risk averse banks lose less
of their potential profit to inefficiencies. We find that more liquid banks (banks with
fewer loans per unit of deposits) are significantly more profit efficient. Our
interpretation of this relationship is that relatively more liquid banks have greater
diversity in their asset portfolios which has enabled them to lose a smaller proportion of
their potential profit to inefficiencies compared with less liquid, more loan-intensive
institutions. The negative and significant coefficient on the year variables indicates the
level of profit efficiency in Asian banking has declined over time. This finding could be
construed as supporting the argument in the established literature that financial
liberalisation increases financial fragility.
6.2
Time varying efficiency and ownership
We are particularly interested to quantify the relationship between bank efficiency and
bank ownership. Table 4 shows estimates of alternative profit efficiency for the
different bank ownership types between 1990 and 2002. Our first general observation is
that in the initial stages of financial liberalisation banks became less efficient and started
to lose a larger percentage of potential profit to inefficiencies. The mean annual
efficiency fell from 0.7149 to 0.6671 between 1991 and 1993. Thereafter efficiency
begins to rise from 0.6839 in 1994 to 0.7105 in 1996, which means that on average
Asian banks were losing less than 29% of their potential profit to inefficiencies
immediately prior to the financial crisis. However, the level of mean efficiency in 1996
is slightly less than that achieved in 1991. Although banks were becoming more
efficient in the deregulated environment, their efficiency had not surpassed previous
levels recorded under a more heavily regulated environment. From 1998 to 2000, Asian
banks lost more than half of their potential profit to inefficiencies. There has been a
subsequent recovery in 2001 and 2002 but the level of profit efficiency is considerably
lower than it was prior to the crisis.
In general, the trend in bank efficiency is similar over time for all types of ownership.
Prior to the 1997 financial crisis, privatised banks, foreign banks, and company-owned
banks improved their efficiency levels during the deregulatory period. Indeed, foreign
banks and privatised banks were the most profit efficient banks in Asia in 1997 with
efficiency levels of 0.7585 and 0.7408, respectively. Whereas company-owned banks
10
had improved their efficiency they were nevertheless the least efficient group between
1990 and 1995. For all other banks (except the widely-held banks) efficiency levels
deteriorated after financial liberalisation though we note that efficiency appears to have
converged in 1996 and ranged from 0.6485 (commercial banks) and 0.7742 (companyowned banks).
Table 4 here
Bank efficiency turns sharply downwards between 1997 and 1998 for all types of bank
except the foreign banks, which managed to improve their efficiency from 0.7585 to
0.7665. We observe that the decline in efficiency is less severe for foreign banks,
financial-owned banks, and widely-held banks (in rank order). In 1998, financial-owned
banks and widely-held banks were 0.6248 and 0.5959 mean profit efficient. The most
severely affected banks were family-owned banks (0.3131), privatised banks (0.3200)
and company-owned banks (0.3560). Indeed, the collapse of the privatised banks is the
most spectacular; in 1996 privatised banks lost less than 25% of potential profit to
inefficiencies which increased to 68% in 1998.
The recovery of the privatised banks, however, is as sharp as their earlier decline. From
a minimum profit efficiency of 0.3200 in 1998, the privatised banks have become the
most efficient banks in Asia in 2002 achieving a mean profit efficiency of 0.7705.
Indeed, the privatised banks are currently more efficient than at any time during the
1990s. Yet, for all other types of bank the recovery from the financial crisis has been
slow. Foreign bank and widely-held bank efficiency has improved only marginally. For
financial-owned banks and family-owned banks the situation is worse as they are
continuing to lose an increasing proportion of potential profit to inefficiencies. In 2001,
family-owned banks lost around 65% of potential profits which is far greater than the
mean for all banks of approximately 47%.
6.3
Tests of differences in mean efficiency
In Table 5 we show the mean profit efficiencies of banks organised under different
ownership forms in the five Asian countries. In addition, we report the results of a onetailed t-test of the difference of mean efficiencies. For example, we test whether the
mean profit efficiency of commercial banks is equal to the mean of non-commercial
banks and so forth. The general implication of this exercise is that foreign ownership
yields a significantly higher level of mean profit efficiency irrespective of the host
country. State ownership on the other hand tends to result in significantly lower levels
of profit efficiency though not in every country.
Table 5 here
In each country (except the Philippines) foreign-owned banks are on average
significantly more profit efficient than domestic banks. During the financial
restructuring that took place following the 1997 financial crisis, a number of domestic
banks were acquired by government bodies, cleaned up and eventually sold to new
owners. Some of the new owners are foreign banks. Therefore, we have identified 32
observations where foreign banks have acquired formerly domestic banking assets and
we discuss the difference in mean efficiencies of all foreign banks, old foreign banks,
11
and new foreign banks. Banks that are foreign owned throughout the period are found to
be more efficient than domestic banks (0.6984 c.f. 0.6410). However, the institutions
that have been acquired by foreign banks are much less efficient. On average, these
institutions lost over 65% of their potential profit to inefficiencies between 1998 and
2002. Nevertheless, the mean efficiency of new foreign banks increases from 0.1513 in
1998 to 0.4540 in 2001, which is comparable with some of the other ownership forms
but is lower than the old foreign bank efficiency. Foreign acquisition of former
domestic assets has been successful for some institutions; the maximum efficiency of
the new foreign group equals 0.7178 in 2001.
We find that widely-held banks are more efficient than non-widely held banks in Korea
and Thailand but they are less efficient in Indonesia. Whilst financial-owned banks are
more efficient than non financial-owned banks in Korea and Malaysia, company-owned
banks are more efficient than non company-owned banks only in Korea.
We note that the profit efficiency of state banks is significantly less than non state banks
in Korea, Malaysia and Thailand. A similar finding is made for listed banks in every
country except Malaysia. There is mixed evidence for family-owned banks. In Korea,
family-owned banks have significantly lower efficiency than non family-owned banks
whereas the opposite is found in Thailand.
Our results show that on average Malaysian banks are slightly more efficient than
Korean banks and Indonesian banks (0.6829 c.f. 0.6720 and 0.6507, respectively). The
least efficient banks are in the Philippines (0.5830) and Thailand (0.4885). In Indonesia,
Korea and Malaysia, commercial banks are significantly more profit efficient than noncommercial banks
7.
Conclusions
We estimated alternative profit efficiency for a sample of Asian banks that are
characterised by different ownership forms. We find that indicators of the macro
economic environment, the structure of Asian banking sectors and firm-specific
variables are more important determinants of bank efficiency than bank ownership.
Specifically, we find capital regulation to exert the largest effect on bank efficiency.
The density of the environment is another important predicator of bank efficiency. We
find that relatively more liquid banks have higher efficiency levels, which we believe
reflects a more diversified portfolio of assets.
The period between 1990 and 2002 is one of financial liberalisation in Asia. In the
initial stage of liberalisation, bank profit efficiency falls but by 1996 average efficiency
for banks organised under the different types of ownership had increased. Indeed, it
appears that there was a convergence of bank efficiency immediately prior to the
financial crisis. At the time, the most efficient institutions were foreign-owned and
privatised banks. The effect of the financial crisis was to increase the loss of potential
profit due to inefficiencies to an average of nearly 55% in 1999. Family-owned,
privatised and company-owned banks were the most severely affected with familyowned (and financial-owned) institutions remaining in dire straits in terms of potential
profits being lost to inefficiencies at the start of the new millennium.
12
The collapse of privatised bank efficiency is surprising. The efficiency of privatised
banks had improved substantially prior to the crisis but it plummeted thereafter.
However, the recovery of the privatised banks is quite spectacular. By 2002, privatised
banks were the most profit efficient in Asia and their speed of recovery has been
unusually fast especially in the light of the slower recovery of foreign banks and
widely-held banks which are among the most efficient banks in the region.
There are several policy implications arising from the estimated efficiencies, however, it
is difficult to apply general policy recommendations because we find that the bank
efficiency of institutions of the same ownership differs across countries. Nevertheless,
the sale of domestic banking assets to foreign owners has had a positive effect on the
efficiency of acquired institutions. Indeed, the foreign bank sector is one of the strongest
performing sectors in Asian banking. Similarly, privatisation has proved to be
successful in raising bank efficiency although privatised banks were very vulnerable to
the financial crisis which is a cause for concern.
Generally speaking, there is quite substantial evidence to show the public ownership of
banking assets results in lower levels of efficiency which tentatively supports the
arguments for bank privatisation. We would add a recommendation that ownership be
as widely dispersed as is possible given the relatively good performance of widely-held
banks. However, caution needs to be exercised because banks with stock exchange
listings are among the least efficient in the region which suggests that capital market
discipline is relatively weak in South East Asia. Our final note is to confirm the findings
in the literature that family-owned banks perform relatively weakly.
13
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17
Table 1: Number of banks; by country and ownership, 1990-2002
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Indonesia
Korea
Malaysia
Philippines
Thailand
12
0
0
5
2
27
6
0
16
15
56
20
1
20
18
67
29
3
24
18
73
30
25
26
20
76
30
38
29
21
75
30
41
31
22
64
30
40
35
22
49
20
39
30
19
50
19
39
30
18
41
18
33
26
18
35
17
30
22
18
2
10
0
7
14
627
259
289
301
225
Commercial bank
State bank
Foreign bank
Family-owned
Company-owned
Financial-owned
Widely-held
Listed bank
Crisis bank
Privatised bank
17
12
1
1
13
0
62
18
2
22
16
8
25
26
40
4
110
30
17
31
27
15
38
37
62
5
133
44
20
33
34
20
50
43
72
5
160
52
29
34
39
31
56
50
79
5
176
52
34
35
42
39
61
55
81
5
179
54
38
34
39
41
63
57
80
6
171
54
39
30
33
42
65
60
68
7
138
50
41
18
22
34
55
53
43
7
138
56
45
15
21
32
53
51
41
7
118
60
41
12
16
28
46
50
37
7
107
62
34
10
14
28
42
48
33
7
38
32
11
5
4
13
16
14
22
5
1547
576
351
285
313
331
571
545
671
70
Total
19
64
115
141
174
194
199
191
157
156
136
122
45
1713
6
6
Source: BankScope
18
Table 2: Means & standard deviations of outputs, inputs and netputs, 1990-2002a
Indonesia
Korea
Malaysia
Philippines
Thailand
59
712
147
95
213
St.
Dev.
149
607
193
103
256
Commercial bank
State bank
Foreign bank
Family-owned
Company-owned
Financial-owned
Widely-held
Listed banks
Crisis banks
Privatised banks
192
409
65
128
257
154
287
313
334
933
192
209*
OP
1990-1996
1997-2002
118
117
123
148
113
St.
Dev.
29
11
21
123
7
348
541
198
183
423
196
396
421
497
585
123
118
128
123
116
130
122
118
113
111
301
417*
123
123
p1
1.28
1.06
0.73
1.44
0.78
St.
Dev.
0.68
0.82
0.28
0.49
0.33
59
19
36
31
11
117
22
21
11
9
1.15
1.15
0.90
1.29
1.39
0.96
1.17
1.02
1.11
0.82
26
78*
1.21
1.01*
p2
1012
13621
2535
978
5064
St.
Dev.
2024
12180
3144
1077
4814
0.64
0.64
0.53
0.61
0.79
0.58
0.57
0.46
0.70
0.39
3497
8580
1058
2477
4471
2854
5098
2729
6682
17177
0.66
0.60*
3385
4080*
Loans
507
7086
1278
495
1256
St.
Dev.
1245
6471
1886
575
1998
6455
10445
4859
3411
7607
3859
7624
6190
9505
9413
1646
3687
534
665
2513
1555
1336
2856
2927
9735
5967
7876*
1378
2133*
OEA
189
978
1911
2827
3230
566
6772
2852
45518
12782
29
583
40
64
210
St.
Dev.
253
1060
426
235
478
3425
5362
2157
1177
4478
2795
3274
4436
5035
5563
1333
1278
646
3766
300.9
1555
992
1695
1645
1474
20156
20993
1431
46773
963
10520
2503
8398
25198
20269
143
109
41
112
206
96
231
259
274
728
2962
4254*
761
2274*
5667
28289*
138
152
OBS
St. Dev.
Z1
113
1194
331
217
464
St.
Dev.
253
1060
426
235
478
570
933
426
351
644
363
694
704
838
774
354
765
135
274
422
331
529
583
585
1444
570
933
426
351
644
363
694
704
838
774
515
736*
343
419*
515
736*
Z2
a
Number of observations: 1713; Number in thousand USD except p2.
* Denotes significant difference between the two period means at the 1% level of significance.
Source: BankScope and author’s calculation.
19
Table 3: Parameter Estimates: Alternative Profit Function; 1990-2002
Variable
Constant
Time
Time 2
Ln Q1
Ln Q2
Ln Q3
LnP1/P2
LnQ1 2
LnQ1 lnQ2
LnQ1 lnQ3
LnQ2 2
LnQ2 lnQ3
LnQ3 2
LnP1/P2 2
LnZ1/Z2
LnZ1/Z2 2
LnZ1/Z2 LnQ1
LnZ1/Z2 LnQ2
LnZ1/Z2 LnQ3
LnZ1/Z2 LnP1
LnP1/P2 lnQ1
LnP1/P2 lnQ2
LnP1/P2 lnQ3
Cos (x1)
Sin (x1)
Cos (x2)
Sin (x2)
Cos (x3)
Sin (x3)
Cos (x1+x1)
Sin (x1+x1)
Cos (x1+x2)
Sin (x1+x2)
Cos (x1+x3)
Sin (x1+x3)
Cos (x2+x2)
Sin (x2+x2)
Cos (x2+x3)
Sin (x2+x3)
Cos (x3+x3)
Sin (x3+x3)
Cos (x1+x1+x2)
Sin (x1+x1+x2)
Cos (x1+x1+x3)
Sin (x1+x1+x3)
Cos (x1+x2+x2)
Sin (x1+x2+x2)
Cos (x1+x2+x3)
Sin (x1+x2+x3)
Cos (x1+x3+x3)
Sin (x1+x3+x3)
Cos (x2+x2+x3)
Sin (x2+x2+x3)
Cos (x2+x3+x3)
Sin (x2+x3+x3)
Parameter
0
1
11
1
2
3
1
11
12
13
22
23
33
11
1
11
11
12
13
11
11
12
13
a1
b1
a2
b2
a3
b3
a11
b11
a12
b12
a13
b13
a22
b22
a23
b23
a33
b33
a112
b112
a113
b113
a122
b122
a123
b123
a133
b133
a223
b223
a233
b233
Coefficient
-35.037
0.009
0.002
2.875
12.328
1.125
-0.051
-0.326
0.083
0.115
-1.041
-0.057
-0.135
-0.002
-0.183
-0.003
0.090
0.030
-0.007
-0.056
0.187
-0.091
0.003
4.563
3.452
11.064
-0.556
3.822
-1.160
-0.074
0.470
1.037
0.204
1.582
0.187
1.871
0.141
-0.663
0.397
0.470
-0.568
0.112
0.137
-0.029
0.439
0.393
0.364
-0.140
-0.423
0.466
-0.697
0.076
0.119
0.214
0.383
Std-error
1.019
0.029
0.002
0.784
0.887
0.807
0.136
0.071
0.033
0.024
0.085
0.021
0.063
0.003
0.100
0.003
0.019
0.018
0.007
0.018
0.034
0.032
0.012
1.248
0.811
0.907
0.689
1.703
0.567
0.222
0.269
0.341
0.240
0.336
0.284
0.205
0.261
0.211
0.242
0.250
0.233
0.171
0.159
0.154
0.125
0.155
0.146
0.200
0.214
0.137
0.161
0.120
0.115
0.114
0.129
T-ratio
-34.393
0.305
0.924
3.668
13.896
1.394
-0.373
-4.606
2.489
4.691
-12.235
-2.739
-2.154
-0.606
-1.830
-1.062
4.823
1.637
-1.057
-3.111
5.473
-2.805
0.241
3.656
4.258
12.200
-0.807
2.245
-2.045
-0.332
1.745
3.046
0.848
4.707
0.659
9.135
0.540
-3.151
1.636
1.882
-2.437
0.656
0.862
-0.187
3.521
2.536
2.494
-0.699
-1.976
3.413
-4.319
0.633
1.028
1.875
2.975
20
Constant
Commercial
State
Foreign
Family
Company
Financial
Widely
Listed
Crisis
Privatised
GNP per capita
Population density
Deposit density
Herfindahl
Avg ETA
Intermediation
NPL/TL
Capitalisation
Liquidity
Year
Year2
s2  v2 + 2
  2 / s2
Log-likelihood
δ0
δ1
δ2
δ3
δ4
δ5
δ6
δ7
δ8
δ9
δ10
δ11
δ12
δ13
δ14
δ15
δ16
δ17
δ18
δ19
δ20
δ21
-24.849
-3.996
1.823
-0.354
1.107
0.826
-0.603
-1.251
3.351
1.746
-0.086
-3.029
5.280
6.490
-1.482
-10.102
0.454
-1.765
3.174
-10.015
-0.158
-24.849
7.2312
0.9713
5.501
0.525
0.621
0.498
0.590
0.533
0.482
0.463
0.377
0.403
0.702
0.573
0.656
0.769
0.128
1.245
0.051
0.304
0.251
1.070
0.018
5.501
0.580
0.003
-4.517
-7.613
2.937
-0.711
1.875
1.549
-1.253
-2.702
8.896
4.337
-0.122
-5.282
8.052
8.441
-11.581
-8.112
8.959
-5.802
12.662
-9.360
-8.997
-4.517
12.459
324.360
-1818.075
21
Table 4: Average Profit Efficiencies; by Bank Ownership, 1990-2002
Ownership
Commercial
State
Foreign
Family
Company
Financial
Widely
Listed
Crisis
Privatised
Average by year
1990
0.7570
0.6935
0.8548
0.7684
1991
0.7494
0.7938
0.6380
0.7444
0.5829
0.7866
0.7022
0.7234
0.7430
0.6857
0.7149
1992
0.7118
0.6642
0.5773
0.6648
0.5330
0.7404
0.6899
0.7272
0.7359
0.6411
0.6686
1993
0.7119
0.7575
0.6319
0.6086
0.5403
0.7061
0.6658
0.6968
0.6894
0.6629
0.6671
1994
0.6715
0.7327
0.6123
0.6953
0.5639
0.6967
0.7055
0.6952
0.7589
0.7075
0.6839
1995
0.7024
0.7838
0.6910
0.6671
0.6410
0.6899
0.7126
0.6645
0.7551
0.7739
0.7081
1996
0.6485
0.7290
0.7273
0.6469
0.7742
0.6983
0.7033
0.6495
0.7597
0.7685
0.7105
1997
0.6173
0.5847
0.7585
0.6087
0.6257
0.6997
0.6392
0.6605
0.6413
0.7408
0.6576
1998
0.3608
0.4965
0.7665
0.3131
0.3560
0.6248
0.5959
0.4303
0.5046
0.3200
0.4769
1999
0.3444
0.4344
0.6146
0.4186
0.3432
0.6090
0.5614
0.4046
0.4822
0.3360
0.4548
2000
0.4238
0.4907
0.5969
0.3087
0.3847
0.5423
0.5988
0.4511
0.5523
0.5587
0.4908
2001
0.4730
0.5651
0.6343
0.3504
0.4303
0.5502
0.5911
0.4864
0.6253
0.6341
0.5340
2002
0.4663
0.5076
0.5229
0.4692
0.7705
0.5473
Mean
0.5875
0.6393
0.6590
0.5479
0.5366
0.6556
0.6514
0.6087
0.6589
0.6333
0.5875
22
Table 5: Mean profit efficiency; by country and ownership type
Commercial
State
Foreign
Family
Company
Financial
Widely
Listed
Crisis
Privatised
Indonesia
0.6852b
0.6550
0.7134a
0.6984
0.6956
0.7047
0.6343c
0.5943c
0.6774
0.4492 c
Korea
0.6880b
0.6164c
0.7017b
0.5764c
0.7057a
0.6958b
0.7053a
0.6934b
0.6687c
0.6686
Malaysia
0.7294a
0.3462c
0.7315a
0.7099
0.7185
0.7236b
0.6877 c
0.6896
0.7831a
0.7099
Note: (a) significantly greater at 1% level of significance
(b) significantly greater than at 10% level of significance
(c) significantly less than at 1% level of significance
(d) significantly less than at 10% level of significance
Philippines
0.5887c
0.5962
0.5364c
0.5952
0.5859
0.5946
0.5866
0.5720d
0.5921
0.5821
Thailand
0.4952
0.4313c
0.5079a
0.5464a
0.4877
0.4318
0.5102b
0.4519c
0.4849
0.5373
Table A1: Environmental Variables
Variable
Constant
Commercial
State
Foreign
Family
Company
Financial
Widely
Listed
Crisis
Privatised
GNP per capita
PD
DD
HHI
Average ETA
Intermediation
NPL/TL
Liquidity
Capitalisation
Year
Year2 (c)
Param
δ0
δ1
δ2
δ3
δ4
δ5
δ6
δ7
δ8
δ9
δ10
δ11
δ12
δ13
δ14
δ15
δ16
δ17
δ18
δ19
δ20
δ21
Definition
Variable = 1 for commercial banks, 0 = other
Variable = 1 for state-owned banks, 0 = other
Variable = 1 for foreign-owned banks, 0 = other
Variable = 1 for family-owned banks, 0 = other
Variable = 1 for company-owned banks, 0 = other
Variable = 1 for financial-owned banks, 0 = other
Variable = 1 for widely-owned banks, 0 = other
Variable = 1 for listed banks, 0 = other
Variable = 1 for crisis banks, 0 = other
Variable = 1 for privatised banks, 0 = other
Log of gross national product in 1993 prices/population
Log of population density (population per square kilometre)
Log of deposit density (deposits per square kilometre)
Log of Herfindahl Hirschman Index
Log of average equity-assets; proxy for capital regulation
Log of loans/deposits
Log of non-performing loans/total loans
Ratio of customer loans-customer deposits for each bank
Log of ratio of equity/assets for each bank
Time trend
Quadratic term of time trend
24
Appendix A2: Descriptive statistics of environment variables, 1990-2002
Variables
GNP a
Real 1993
prices
(.000 USD)
Mean
Median
St. Dev.
Min
Max
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
1644
12356
4368
1312
2655
1428
12945
4551
1243
2852
870
2783
474
361
480
609
7059
2770
714
1509
3939
17702
5071
2057
3291
1990-1996
1997-2002
3038*
4691*
1243
3085
3434
4303
609
1358
12945
17702
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
102
462
67
241
117
103
462
67
240
117
4
12
4
17
4
93
440
58
207
109
110
484
74
273
123
1990-1996
1997-2002
175
179
103
109
132
135
58
66
462
484
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
70262
6393992
259610
110888
280862
61099
5887206
268245
103084
278454
48124
2753858
61928
47945
88726
17154
2304675
103883
32275
108861
186896
11923347
336510
198303
395006
1990-1996
1997-2002
755172*
1475374*
69562
263284
1590521
3156877
17154
66672
5887206
11923347
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
890
815
809
853
1023
909
697
812
786
988
273
241
129
123
91
558
577
677
750
907
1271
1140
1066
1093
1142
1990-1996
1997-2002
786*
975*
812
998
779
976
187
203
558
677
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
1.70
1.81
2.29
2.76
1.96
2.34
1.75
2.25
2.77
2.01
1.77
0.26
0.12
0.10
0.20
-4.04
1.42
2.11
2.56
1.51
2.51
2.27
2.53
2.86
2.18
1990-1996
1997-2002
2.31*
1.75*
2.33
2.29
0.25
1.60
1.75
-4.04
2.77
2.86
Indonesia
Korea Rep.
Malaysia
Philippines
Thailand
0.21
0.43
0.28
0.07
0.22
0.24
0.46
0.26
0.08
0.24
0.11
0.08
0.10
0.12
0.11
-0.07
0.24
0.14
-0.15
0.04
0.30
0.49
0.43
0.25
0.37
1990-1996
0.24*
0.27
0.15
-0.15
1997-2002
0.22*
0.22
0.14
-0.07
Denotes significant difference between the two means for the periods 1990-1996 and 1997-2002 at the
1% level.
0.49
0.48
PD
Population
density
DD
Density of
demand
HHI
Herfindahl
Hirschman
Index
(Share of deposit)
Ave ETA
Average
Equity/ Assets
Intermediation
Loan/Deposit
Source: BankScope, Asian Development Bank database and own calculation.
25