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

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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.

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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

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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 deregulation-induced 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

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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].

( )UVxY itititit −+= βexp [1] itU = itZ δ + itW [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.

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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, σ2

u); 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]. itTE = exp ( )− itU = exp ( )it itZ W− −δ [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]:

2 Following Berger and Mester (1997), 10% is cut off each end of the [0,2π] interval so that the zi span [0.1 x 2π, 0.9 x 2π] in order to reduce approximation problems near endpoints. The formula for zi 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)).

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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-balance-sheet 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]; εi 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, τ, β, ψ, θ, φ, κ, Ω, ϖ, 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

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are either public commercial banks or specialised government institutions. The majority of banks are commercial banks and their ownership is classified as being foreign-owned, 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-balance-sheet 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.

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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 company-owned 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.

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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

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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 (company-owned 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 one-tailed 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,

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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 non-commercial 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 family-owned (and financial-owned) institutions remaining in dire straits in terms of potential profits being lost to inefficiencies at the start of the new millennium.

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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.

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18

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 12 27 56 67 73 76 75 64 49 50 41 35 2 627 Korea 0 6 20 29 30 30 30 30 20 19 18 17 10 259 Malaysia 0 0 1 3 25 38 41 40 39 39 33 30 0 289 Philippines 5 16 20 24 26 29 31 35 30 30 26 22 7 301 Thailand 2 15 18 18 20 21 22 22 19 18 18 18 14 225 Commercial bank 17 62 110 133 160 176 179 171 138 138 118 107 38 1547 State bank 12 18 30 44 52 52 54 54 50 56 60 62 32 576 Foreign bank 2 17 20 29 34 38 39 41 45 41 34 11 351 Family-owned 6 22 31 33 34 35 34 30 18 15 12 10 5 285 Company-owned 6 16 27 34 39 42 39 33 22 21 16 14 4 313 Financial-owned 8 15 20 31 39 41 42 34 32 28 28 13 331 Widely-held 1 25 38 50 56 61 63 65 55 53 46 42 16 571 Listed bank 1 26 37 43 50 55 57 60 53 51 50 48 14 545 Crisis bank 13 40 62 72 79 81 80 68 43 41 37 33 22 671 Privatised bank 0 4 5 5 5 5 6 7 7 7 7 7 5 70 Total 19 64 115 141 174 194 199 191 157 156 136 122 45 1713 Source: BankScope

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Table 2: Means & standard deviations of outputs, inputs and netputs, 1990-2002a

OP St. Dev. p1 St.

Dev. p2 St. Dev. Loans St.

Dev. OEA St. Dev. OBS St. Dev. Z1 St.

Dev. Z2 St. Dev.

Indonesia 59 149 118 29 1.28 0.68 1012 2024 507 1245 189 566 29 253 113 253 Korea 712 607 117 11 1.06 0.82 13621 12180 7086 6471 978 6772 583 1060 1194 1060 Malaysia 147 193 123 21 0.73 0.28 2535 3144 1278 1886 1911 2852 40 426 331 426 Philippines 95 103 148 123 1.44 0.49 978 1077 495 575 2827 45518 64 235 217 235 Thailand 213 256 113 7 0.78 0.33 5064 4814 1256 1998 3230 12782 210 478 464 478 Commercial bank 192 348 123 59 1.15 0.64 3497 6455 1646 3425 1333 20156 143 570 354 570 State bank 409 541 118 19 1.15 0.64 8580 10445 3687 5362 1278 20993 109 933 765 933 Foreign bank 65 198 128 36 0.90 0.53 1058 4859 534 2157 646 1431 41 426 135 426 Family-owned 128 183 123 31 1.29 0.61 2477 3411 665 1177 3766 46773 112 351 274 351 Company-owned 257 423 116 11 1.39 0.79 4471 7607 2513 4478 300.9 963 206 644 422 644 Financial-owned 154 196 130 117 0.96 0.58 2854 3859 1555 2795 1555 10520 96 363 331 363 Widely-held 287 396 122 22 1.17 0.57 5098 7624 1336 3274 992 2503 231 694 529 694 Listed banks 313 421 118 21 1.02 0.46 2729 6190 2856 4436 1695 8398 259 704 583 704 Crisis banks 334 497 113 11 1.11 0.70 6682 9505 2927 5035 1645 25198 274 838 585 838 Privatised banks 933 585 111 9 0.82 0.39 17177 9413 9735 5563 1474 20269 728 774 1444 774 1990-1996 192 301 123 26 1.21 0.66 3385 5967 1378 2962 761 5667 138 515 343 515 1997-2002 209* 417* 123 78* 1.01* 0.60* 4080* 7876* 2133* 4254* 2274* 28289* 152 736* 419* 736*

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.

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Table 3: Parameter Estimates: Alternative Profit Function; 1990-2002

Variable Parameter Coefficient Std-error T-ratio Constant α0 -35.037 1.019 -34.393

Time τ1 0.009 0.029 0.305 Time 2 τ11 0.002 0.002 0.924 Ln Q1 β1 2.875 0.784 3.668 Ln Q2 β2 12.328 0.887 13.896 Ln Q3 β3 1.125 0.807 1.394

LnP1/P2 ψ1 -0.051 0.136 -0.373 LnQ1 2 θ11 -0.326 0.071 -4.606

LnQ1 lnQ2 θ12 0.083 0.033 2.489 LnQ1 lnQ3 θ13 0.115 0.024 4.691

LnQ2 2 θ22 -1.041 0.085 -12.235 LnQ2 lnQ3 θ23 -0.057 0.021 -2.739

LnQ3 2 θ33 -0.135 0.063 -2.154 LnP1/P2 2 ψ11 -0.002 0.003 -0.606 LnZ1/Z2 φ1 -0.183 0.100 -1.830

LnZ1/Z2 2 φ11 -0.003 0.003 -1.062 LnZ1/Z2 LnQ1 κ11 0.090 0.019 4.823 LnZ1/Z2 LnQ2 κ12 0.030 0.018 1.637 LnZ1/Z2 LnQ3 κ13 -0.007 0.007 -1.057 LnZ1/Z2 LnP1 Ω11 -0.056 0.018 -3.111 LnP1/P2 lnQ1 ϖ11 0.187 0.034 5.473 LnP1/P2 lnQ2 ϖ12 -0.091 0.032 -2.805 LnP1/P2 lnQ3 ϖ13 0.003 0.012 0.241

Cos (x1) a1 4.563 1.248 3.656 Sin (x1) b1 3.452 0.811 4.258 Cos (x2) a2 11.064 0.907 12.200 Sin (x2) b2 -0.556 0.689 -0.807 Cos (x3) a3 3.822 1.703 2.245 Sin (x3) b3 -1.160 0.567 -2.045

Cos (x1+x1) a11 -0.074 0.222 -0.332 Sin (x1+x1) b11 0.470 0.269 1.745 Cos (x1+x2) a12 1.037 0.341 3.046 Sin (x1+x2) b12 0.204 0.240 0.848 Cos (x1+x3) a13 1.582 0.336 4.707 Sin (x1+x3) b13 0.187 0.284 0.659 Cos (x2+x2) a22 1.871 0.205 9.135 Sin (x2+x2) b22 0.141 0.261 0.540 Cos (x2+x3) a23 -0.663 0.211 -3.151 Sin (x2+x3) b23 0.397 0.242 1.636 Cos (x3+x3) a33 0.470 0.250 1.882 Sin (x3+x3) b33 -0.568 0.233 -2.437

Cos (x1+x1+x2) a112 0.112 0.171 0.656 Sin (x1+x1+x2) b112 0.137 0.159 0.862 Cos (x1+x1+x3) a113 -0.029 0.154 -0.187 Sin (x1+x1+x3) b113 0.439 0.125 3.521 Cos (x1+x2+x2) a122 0.393 0.155 2.536 Sin (x1+x2+x2) b122 0.364 0.146 2.494 Cos (x1+x2+x3) a123 -0.140 0.200 -0.699 Sin (x1+x2+x3) b123 -0.423 0.214 -1.976 Cos (x1+x3+x3) a133 0.466 0.137 3.413 Sin (x1+x3+x3) b133 -0.697 0.161 -4.319 Cos (x2+x2+x3) a223 0.076 0.120 0.633 Sin (x2+x2+x3) b223 0.119 0.115 1.028 Cos (x2+x3+x3) a233 0.214 0.114 1.875 Sin (x2+x3+x3) b233 0.383 0.129 2.975

21

Constant δ0 -24.849 5.501 -4.517 Commercial δ1 -3.996 0.525 -7.613

State δ2 1.823 0.621 2.937 Foreign δ3 -0.354 0.498 -0.711 Family δ4 1.107 0.590 1.875

Company δ5 0.826 0.533 1.549 Financial δ6 -0.603 0.482 -1.253 Widely δ7 -1.251 0.463 -2.702 Listed δ8 3.351 0.377 8.896 Crisis δ9 1.746 0.403 4.337

Privatised δ10 -0.086 0.702 -0.122 GNP per capita δ11 -3.029 0.573 -5.282

Population density δ12 5.280 0.656 8.052 Deposit density δ13 6.490 0.769 8.441

Herfindahl δ14 -1.482 0.128 -11.581 Avg ETA δ15 -10.102 1.245 -8.112

Intermediation δ16 0.454 0.051 8.959 NPL/TL δ17 -1.765 0.304 -5.802

Capitalisation δ18 3.174 0.251 12.662 Liquidity δ19 -10.015 1.070 -9.360

Year δ20 -0.158 0.018 -8.997 Year2 δ21 -24.849 5.501 -4.517

σs2 ≡ σv

2 + σ2 7.2312 0.580 12.459 γ ≡ σ2 / σs

2 0.9713 0.003 324.360 Log-likelihood -1818.075

22

Table 4: Average Profit Efficiencies; by Bank Ownership, 1990-2002

Ownership 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Mean Commercial 0.7570 0.7494 0.7118 0.7119 0.6715 0.7024 0.6485 0.6173 0.3608 0.3444 0.4238 0.4730 0.4663 0.5875 State 0.7938 0.6642 0.7575 0.7327 0.7838 0.7290 0.5847 0.4965 0.4344 0.4907 0.5651 0.6393 Foreign 0.6380 0.5773 0.6319 0.6123 0.6910 0.7273 0.7585 0.7665 0.6146 0.5969 0.6343 0.6590 Family 0.7444 0.6648 0.6086 0.6953 0.6671 0.6469 0.6087 0.3131 0.4186 0.3087 0.3504 0.5479 Company 0.6935 0.5829 0.5330 0.5403 0.5639 0.6410 0.7742 0.6257 0.3560 0.3432 0.3847 0.4303 0.5076 0.5366 Financial 0.7866 0.7404 0.7061 0.6967 0.6899 0.6983 0.6997 0.6248 0.6090 0.5423 0.5502 0.5229 0.6556 Widely 0.7022 0.6899 0.6658 0.7055 0.7126 0.7033 0.6392 0.5959 0.5614 0.5988 0.5911 0.6514 Listed 0.8548 0.7234 0.7272 0.6968 0.6952 0.6645 0.6495 0.6605 0.4303 0.4046 0.4511 0.4864 0.4692 0.6087 Crisis 0.7430 0.7359 0.6894 0.7589 0.7551 0.7597 0.6413 0.5046 0.4822 0.5523 0.6253 0.6589 Privatised 0.6857 0.6411 0.6629 0.7075 0.7739 0.7685 0.7408 0.3200 0.3360 0.5587 0.6341 0.7705 0.6333 Average by year 0.7684 0.7149 0.6686 0.6671 0.6839 0.7081 0.7105 0.6576 0.4769 0.4548 0.4908 0.5340 0.5473 0.5875

Table 5: Mean profit efficiency; by country and ownership type Indonesia Korea Malaysia Philippines Thailand Commercial 0.6852b 0.6880b 0.7294a 0.5887c 0.4952 State 0.6550 0.6164c 0.3462c 0.5962 0.4313c Foreign 0.7134a 0.7017b 0.7315a 0.5364c 0.5079a Family 0.6984 0.5764c 0.7099 0.5952 0.5464a Company 0.6956 0.7057a 0.7185 0.5859 0.4877 Financial 0.7047 0.6958b 0.7236b 0.5946 0.4318 Widely 0.6343c 0.7053a 0.6877 c 0.5866 0.5102b Listed 0.5943c 0.6934b 0.6896 0.5720d 0.4519c Crisis 0.6774 0.6687c 0.7831a 0.5921 0.4849 Privatised 0.4492 c 0.6686 0.7099 0.5821 0.5373

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

24

Table A1: Environmental Variables Variable Param Definition Constant δ0 Commercial δ1 Variable = 1 for commercial banks, 0 = other State δ2 Variable = 1 for state-owned banks, 0 = other Foreign δ3 Variable = 1 for foreign-owned banks, 0 = other Family δ4 Variable = 1 for family-owned banks, 0 = other Company δ5 Variable = 1 for company-owned banks, 0 = other Financial δ6 Variable = 1 for financial-owned banks, 0 = other Widely δ7 Variable = 1 for widely-owned banks, 0 = other Listed δ8 Variable = 1 for listed banks, 0 = other Crisis δ9 Variable = 1 for crisis banks, 0 = other Privatised δ10 Variable = 1 for privatised banks, 0 = other GNP per capita δ11 Log of gross national product in 1993 prices/population PD δ12 Log of population density (population per square kilometre) DD δ13 Log of deposit density (deposits per square kilometre) HHI δ14 Log of Herfindahl Hirschman Index Average ETA δ15 Log of average equity-assets; proxy for capital regulation Intermediation δ16 Log of loans/deposits NPL/TL δ17 Log of non-performing loans/total loans Liquidity δ18 Ratio of customer loans-customer deposits for each bank Capitalisation δ19 Log of ratio of equity/assets for each bank Year δ20 Time trend Year2 (c) δ21 Quadratic term of time trend

25

Appendix A2: Descriptive statistics of environment variables, 1990-2002

Variables Mean Median St. Dev. Min Max

GNP a Indonesia 1644 1428 870 609 3939Real 1993 Korea Rep. 12356 12945 2783 7059 17702

prices Malaysia 4368 4551 474 2770 5071(.000 USD) Philippines 1312 1243 361 714 2057

Thailand 2655 2852 480 1509 3291

1990-1996 3038* 1243 3434 609 12945 1997-2002 4691* 3085 4303 1358 17702

PD Indonesia 102 103 4 93 110Population Korea Rep. 462 462 12 440 484

density Malaysia 67 67 4 58 74 Philippines 241 240 17 207 273 Thailand 117 117 4 109 123

1990-1996 175 103 132 58 462 1997-2002 179 109 135 66 484

DD Indonesia 70262 61099 48124 17154 186896Density of Korea Rep. 6393992 5887206 2753858 2304675 11923347

demand Malaysia 259610 268245 61928 103883 336510 Philippines 110888 103084 47945 32275 198303 Thailand 280862 278454 88726 108861 395006

1990-1996 755172* 69562 1590521 17154 5887206 1997-2002 1475374* 263284 3156877 66672 11923347

HHI Indonesia 890 909 273 558 1271Herfindahl Korea Rep. 815 697 241 577 1140Hirschman Malaysia 809 812 129 677 1066

Index Philippines 853 786 123 750 1093(Share of deposit) Thailand 1023 988 91 907 1142

1990-1996 786* 812 779 187 558 1997-2002 975* 998 976 203 677

Ave ETA Indonesia 1.70 2.34 1.77 -4.04 2.51Average Korea Rep. 1.81 1.75 0.26 1.42 2.27

Equity/ Assets Malaysia 2.29 2.25 0.12 2.11 2.53 Philippines 2.76 2.77 0.10 2.56 2.86 Thailand 1.96 2.01 0.20 1.51 2.18

1990-1996 2.31* 2.33 0.25 1.75 2.77 1997-2002 1.75* 2.29 1.60 -4.04 2.86

Intermediation Indonesia 0.21 0.24 0.11 -0.07 0.30Loan/Deposit Korea Rep. 0.43 0.46 0.08 0.24 0.49

Malaysia 0.28 0.26 0.10 0.14 0.43 Philippines 0.07 0.08 0.12 -0.15 0.25 Thailand 0.22 0.24 0.11 0.04 0.37

1990-1996 0.24* 0.27 0.15 -0.15 0.49 1997-2002 0.22* 0.22 0.14 -0.07 0.48

Denotes significant difference between the two means for the periods 1990-1996 and 1997-2002 at the 1% level. Source: BankScope, Asian Development Bank database and own calculation.