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Working Papers Series
Deregulation and Efficiency:
The Case of Private Korean Banks*
By: Jonathan Hao, William Curt Hunter
and Won Keun Yang2
Working Papers Series
Research Department
WP 99-27
Deregulation and Efficiency:
The Case of Private Korean Banks*
Jonathan Hao1
William Curt Hunter1
Won Keun Yang2
March 1999
1
Federal Reserve Bank of Chicago, 230 S. La Salle Street, Chicago, IL 60604
Korea Deposit Insurance Corporation, TaeWon B/D Samsung-Dong, KangNam-Gu,
Seoul, Korea 135-090.
2
*The views expressed in this paper are those of the authors and not necessarily those of
the Federal Bank of Chicago, the Board of Governors of the Federal Reserve System, the
Korean Ministry of Finance and Economy or Korea Deposit Insurance Corporation. The
authors acknowledge the helpful comments received from seminar participants at the
University of Iowa, the University of Minnesota, and the Federal Reserve Bank of Dallas,
and the World Bank.
Abstract
This paper examines the productive efficiency of a sample of private Korean banks
over the 1985 to 1995 time period. The goal of the analysis is to identify the key
determinants of Korean bank efficiency (inefficiency) following the program of
deregulation initiated by the government in the early 1980s and augmented in the early
1990s. Using the stochastic frontier cost function approach, efficiency scores were
determined for each bank in the sample. A second stage efficiency regression was then
estimated to identify the key determinants of operating efficiency. In general, the results
show that banks with higher rates of asset growth, fewer employees per million won of
assets, larger amounts of core deposits, and lower expense ratios were more efficient. In
addition, banks which branched nationwide were found to be more efficient. The financial
deregulation of 1991 was found to have had little or no significant effect on the level of
sample bank efficiency.
Deregulation and Efficiency: The Case of Private Korean Banks
1.
Introduction
From the early 1960s through the early 1980s, Korean banking institutions
essentially served as agents of the government channeling investment funds to selected
sectors under the country’s economic development policy. The policy was designed to
accelerate South Korea’s transition from an agrarian economy to a modern industrialized
state. By most accounts, the country was very successful in achieving its industrialization
goals. Measured by any international standard, the economic development of South
Korea over the last three decades has been exceptional. The policies supporting rapid
industrialization and export growth placed South Korea among the world’s fastest
growing newly industrialized countries.1
The government’s extensive involvement in the banking and financial markets
during the period from 1960 to 1980 led to serious imbalances in the financial markets and
in the industrial structure of the economy. As overall financial repression intensified, the
deadweight costs associated with excessive regulation adversely impacted the efficiency of
the financial system and resource allocation more generally. Restrictions on bank lending
which favored loans to chaebol groups, i.e., large family controlled industrial
conglomerates, as well as export and strategic industries, caused small and medium sized
firms to turn to the informal sector for financing. The repression encouraged the growth
of the informal credit market at the expense of the banking sector and more efficient
resource allocation. An additional and perhaps more important implication of excessive
government involvement in the banking system was the erosion of effective credit
evaluation and risk assessment policies. As has been well documented, Korean banks had
little discretion in allocating funds and therefore, little incentive to screen and monitor the
activities of corporate customers. As a result, the banking sector became increasingly
vulnerable to unbridled corporate expansion. When the economy experienced the recent
downturn (due, in part to the weakening of the Japanese yen against the dollar, and the
fact that many chaebols and related firms either went bankrupt or sustained financial
difficulties) Korean banks suffered immensely. The subsequent ballooning of nonperforming loans on bank balance sheets and the resulting erosion of equity capital
resulted in the collapse of numerous Korean banks.
While much of the blame for the ultimate collapse of the Korean growth miracle
might be directed towards the unholy alliance of the government, the banks, and the
chaebol, the adverse side effects of the alliance did not go unnoticed. Beginning in the
early 1980s the government, in response to mounting public pressure, undertook a series
of steps to liberalize the financial system.2 Key among the steps were: reprivatization of
the banking industry, removal of interest rate ceilings and entry restrictions, reduction of
government directed lending, expanded product deregulation, and reduction of restrictions
on foreign exchange transactions, among others. Additional reforms were implemented in
1991 to further liberalize the financial system: interest rates were further deregulated,
greater autonomy was given to bank managements, bank security holdings and maturities
on loans were liberalized, and further liberalization of foreign exchange transactions and
foreign investment was undertaken. Only recently have the effectiveness of these
liberalization efforts been examined.
Gilbert and Wilson (1998) recently examined the effectiveness of the Korean
liberalization efforts of the early 1980s. These authors examined changes in productivity
among Korean banks during the 1980-1994 period using Malmquist indexes of
productivity. By using Malmquist indexes of productivity, Gilbert and Wilson were able
to decompose productivity changes among the newly privatized Korean banks into
changes in technical efficiency and changes in technology. The authors found that
between 1980 and the mid-1990s, as Korea was privatizing banks and deregulating its
financial industry, banks dramatically changed their mix of inputs and outputs. These
changes, when combined with technological developments, led to significant
improvements in productivity and enhanced the potential output of the Korean banking
sector.
As noted above, we believe that the Korean financial repression, while contributing
to the growth miracle, also increased the deadweight costs associated with excessive
governmental interference in the financial system. Gilbert and Wilson are sympathetic to
this view as they conclude that, “whatever positive effects government control of the
financial system may have had on growth of the Korean economy in the 1960s and 1970s
must be weighed against the negative effects on the productivity of Korean banks.”
In this paper we examine the productive efficiency of a sample of private Korean
banks over the 1985 to 1995 time period. Our goal is to identify the key determinants of
Korean bank efficiency (inefficiency) following the program of deregulation initiated by
the government in the early 1980s and augmented in the early 1990s. Thus, we expand on
the work of Gilbert and Wilson by identifying the key determinants of efficiency and by
investigating the relationship between the macroeconomic performance of the Korean
economy and banking industry efficiency. In section 2 of the paper, we set the stage for
our analysis by briefly reviewing the recent history of the Korean banking system. In
section 3, we examine whether the government’s program of financial liberalization
enhanced the productive efficiency of our sample banks. In contrast to Gilbert and
Wilson, in section 4 we measure the efficiency of our sample banks directly from the
banks’cost functions. This approach allows us to estimate a second stage efficiency
regression to identify the key determinants of operating efficiency (inefficiency). In
addition, we investigate whether the form of ownership was a key determinant of bank
efficiency and examine our sample on a disaggregated basis in an effort to identify other
key characteristics correlated with efficiency. A conclusion follows in section 5. Finally,
in section 6 we discuss the efforts of the Korean government to restructure the banking
system following its recent collapse. In particular, we comment on the ongoing efforts of
the government to merge and close weak and failed banks in light of our findings
regarding the measured efficiency (inefficiency) of our sample banks.
2.
Brief History of the Korean Banking System
The Korean banking system has undergone numerous transformations since the
early 1950s. Modifications began with the creation of the central bank under the Bank of
Korea Act of 1950 and a formalization of the commercial banking sector under the
provisions of the General Banking Act of 1950. Fundamentally, both Acts established the
present objectives of the Korean financial system. These objectives included economic
progress through sound banking operations, protecting depositors, preserving a sound
credit system, and price stability. However, despite these guidelines, the central bank and
the existing banking institutions failed to properly exercise their roles during the 1950s.
This was largely due to the fact that during this period all banks were essentially
government-controlled and exhibited little autonomy. The reign of government control
ended briefly as the government divested its ownership interest in the commercial banks in
the late 1950s.
Up until about 1960, Korea continued to exist primarily as an agrarian state. After
a military coupe in 1961, the new regime embarked on a series of five-year industrial
economic development plans. Under these plans, the financial and banking sectors were
used as a conduit for the regime’s subsequent mix of import substitution policies and
export promotion. Development plans evoked direct government authority over the
country’s financial resources, placing the entire Korean banking industry under tight
government regulations. Once again, the government seized private commercial banks by
acquiring a major portion of their equity capital, appointing their top managers, and setting
their budgets. In 1962, the central bank was placed under government control through
revisions to the Bank of Korea Act.
With the inception of the first five-year economic plan, the Korean government
sought to increase project financing by creating specialized banks that operated outside the
authority of the central bank. Government policymakers set quantitative credit targets to
channel funds to favored light industries such as cement, steel and fertilizers. While
specialized banks provided long-term credit, commercial banks were directed by the
government to supply short-term working capital. Commercial banks even lacked the
autonomy to set their own interest rates on deposits and loans, rather they were set in
accordance with the government’s overall economic plans. Real interest rates on ordinary
and economic development policy loans were frequently lower than the estimated average
real rates of return and in some cases negative (See SaKong, 1993).
Well into the 1970s, subsequent five-year development plans increased government
intervention into the banking and financial sectors. However, during this period the
government recognized that Korea could no longer maintain its economic
competitiveness by focusing on light manufacturing. Consequently, the government’s
focus shifted from aiding domestic light industry towards aiding heavy industrial products
such as machinery, electronics, chemicals, autos, and shipbuilding. During this time,
commercial banks were instructed to allow easy credit access and favorable loans rates to
these industries. This required additional sources of funding that existing commercial
banks were unable to meet. Subsequently, the government established specialized banks
to fill the gap. Toward the latter part of the 1970s, policy loans, i.e., loans which
supported government programs, accounted for nearly 80 percent of domestic credit
extended during that period. During the 1970s, tightly regulated non-bank financial
institutions were introduced in an effort to diversify financing sources and to attract funds
into the organized market.
The industrial policy of the Korean government during this period gave rise to the
chaebol groups. The development strategy bolstered the expansion of existing firms into
targeted sectors through preferential access to bank credit at below-market rates. These
firms not only expanded rapidly into many areas of specialization but also into many which
were not explicitly targeted by government policy. As a result, these firms grew into
economic conglomerates and dominated the Korea economy. These firms also held equity
investments in the commercial banks.
Although the economy was growing at a rapid pace under this strategy, some
government policymakers recognized that privatization and deregulation of the banking
sector was imperative. Market mechanisms provide banks with the incentive to exert selfdiscipline to effectively allocate financial resources, which is necessary to sustain economic
growth. The government began to re-privatize the banking system near the end of the
1970s and undertook an additional series of financial reforms in the early 1980s. With
revisions to the General Banking Act in 1982 and the launch of a new five-year economic
plan in the early 1980s, direct government controls over banking practices were eased, and
permissible banking activities were expanded. For example, permissible banking activities
were expanded to include a wide variety of fee driven non-interest income activities
including sales of commercial bills and government and public bonds under repurchase
agreements. The government also eliminated policy preference loans and further steps
were taken to liberalize interest rates.3
The General Banking Act was revised again in 1991, 1993, and 1994. These
revisions gave commercial banks further autonomy in their business activities and
management. For example, banks were allowed to act as leading underwriters for
government and public bonds. In 1991, a four-stage plan for the full liberalization of
interest rates was announced to effectively set the price mechanism of interest rates.
Through interest rate deregulation, the competitiveness of domestic financial services
industry could be strengthened to cope with continued global financial liberalization.
As is evident from the recent collapse of the Korean banking system, the
liberalization initiatives were, in a larger sense, proven ineffective. In the years leading up
to the crisis, chaebols suffered from heavy financial pressure due to low earnings on their
highly leveraged investment projects. Despite the deterioration of corporate financial
performance, bank lending to the chaebols and corporate debt/equity ratios continued to
grow. By the end of 1997, the debt/equity ratio of the 30 largest chaebols reached an
average of 600 percent.
With a mounting domestic debt and growing number of large corporate failures,
Korean banks are currently bearing the consequences of widespread corporate insolvency.
As such, the country’s current economic crisis demands a serious evaluation of both the
financial reforms and the collusive links among the Korean government, the chaebol, and
the privatized banking industry. As of late 1998, most bank stocks were trading well
under $1 per share. Twelve small merchant banks and five small commercial banks were
closed by the Korean government following the imposition of an International Monetary
Fund rescue package. In addition, the government is currently engaged in a major
restructuring of the banking system as the crisis continues. These more recent
developments are discussed in section 5 of the paper.
3.
Data and Empirical Methodology
Our sample data was taken from the annual balance sheets and income statements
of 19 private Korean banks from 1985 to 1995 (See Table 1).4 Nine of the 19 banks in
our sample are national banks headquartered in the main financial district in Seoul with
branch networks across the nation. Their main business focus is short-term loans and their
main sources of funding are retail deposits and borrowing from the central bank. The rest
are local banks which are headquartered in major metropolitan areas and provinces and
also have branch offices in their province. Although both the size of these banks and the
markets which they serve vary in our sample, studies have shown that if a banking office
has an output below the level of diseconomies of scale, it can operate as efficiently as a
branch of a larger organization. Therefore, bank size and market concentration do not
prevent a bank from achieving efficiency in operating costs (See Gilbert, 1984). All
financial variables were measured in 1990 constant won. The data used in calculating an
operating efficiency index for each sample bank in each year and the data used in
examining the determinants of efficiency were provided by the Korea Institute of Finance.
The data used in the correlation analysis which associates macroeconomic performance
with the efficiency index were taken from the “World Tables” published by the World
Bank.
Bank Efficiency
Our study of efficiency provides for a better understanding of market
competitiveness and profitability. Such an analysis, in turn, can provide policymakers with
information which may prove valuable in the design of public policy. The methodology
allows us to identify best practice banks and thus might be useful in decisions regarding
merging and closing banks. Rather than concentrating on traditional scale and scope
analysis of productive efficiency, we concentrate on management efficiency. This focus
results from recent research in banking which indicates that management’s ineffectiveness
in managing resources accounts for a significantly higher percentage of costs in banking
compared to scale and scope efficiencies (Berger et al., 1993). Furthermore, instead of
comparing the operating performance of our sample banks with a set of superior-operated
banks by using financial ratios, we use production theory and econometric procedures to
extract information on managerial efficiency.
The stochastic frontier approach was used to calculate a measure of production
efficiency for each bank in our sample (see Aigner et al., 1977 and Meeusen and Broeck,
1977). This approach uses a parametric technique to estimate the characteristics of “bestpractice” banks from bank cost functions. These best-practice banks represent institutions
which produce their financial products and services at the lowest cost using the most
efficient mix of productive inputs or factors of production. Individual bank efficiency
indices were measured by computing the deviations of costs from the cost frontier
estimated from the sample data. This inefficiency factor captures both allocative
inefficiencies from failing to react optimally to relative prices of inputs, and technical
inefficiencies resulting from employing excessive amount of the inputs to produce outputs.
In this framework, systematic deviations of cost from the frontier or best-practice levels
are associated with poor management while random deviations can be attributed to
uncontrollable factors that affect total costs, such as weather, luck, labor strikes, or
machine performance.
The stochastic frontier cost function approach maintains that managerial or
controllable inefficiencies only increase costs above best-practice levels and that random
fluctuations or uncontrollable factors can either increase or decrease costs. Therefore, the
model assumes that inefficiencies follow an asymmetric half-normal distribution, while
random fluctuations follow the typical assumption of a symmetric normal distribution.
To calculate each bank’s efficiency index, we first fitted a stochastic frontier cost
function to characterize the efficient frontier for the sample banks. The form of the cost
function is a standard translog cost function:
ln~TC~=~alpha~+~sum from {j = 1} to 3 beta_j ~ln~Y_j~+~1 over 2 ~sum
from {j = 1} to 3 sum from {k = 1} to 3beta_jk~ln~Y_j~ln~Y_k~+~sum
from {n = 1} to 3 gamma_n~ ln~w_n#+~1 over 2~ sum from {n = 1} to 3
sum from {p = 1} to
3gamma_np~ln~w_n~ln~w_p~+~ _i~ln~Z~+~1 over 2~
(1)
where TC is the total cost of inputs used to produce the bank’s various outputs. TC
includes all labor costs, physical capital expenses, and allocated interest expenses. Thus,
we use the intermediation approach to the analysis of bank production which requires that
the output metric be defined in terms of dollars of loans and deposits rather than by the
number of accounts and that interest expense be included in total cost. Allocated interest
equals the product of the ratio of investments to earning assets times total interest
expense. The allocation of interest was necessary because securities are specified as
output and many banks incur substantial interest costs in financing their securities
portfolio. The Yj are three output quantities included in the cost function: total loans and
securities, demand deposits, and fee income. Total loans are comprised of all retail loans,
which include residential real estate, agricultural, personal, credit card and other loans, all
commercial, industrial, and security loans and investments. Fee income is used to proxy
other bank outputs. It is equal to the service charges and fees received on transaction and
nontransaction accounts. The prices of inputs, Wn , used in the production of bank assets
are the wage rate, interest for borrowed funds, and the price of physical capital. The wage
rate is calculated by dividing total salaries and fringe benefits by the number of full-time
equivalent employees. The interest for borrowed funds is calculated by taking the ratio of
total interest expense to the sum of total funds. The price of physical capital equals the
ratio of total expenses of premises and fixed assets to total assets. The cost function also
includes the variable Z, equity capital for each bank, to adjust for increased costs of funds
due to financial risk. The composite error terms, u and v, capture cost inefficiency and
random error. The u is assumed to be normally distributed with truncation below zero.
The v, on the other hand, is assumed to be independently, identically and normally
distributed. Finally, ln denotes the natural logarithm. Standard homogeneity and
symmetry restrictions were imposed in estimating the parameters of the cost function.
Table 2 presents summary statistics for the variables used to estimate the cost
function in equation (1). The average equity capital to total assets ratio is around 5.4
percent and compares favorably with the standard suggested by the FDIC Improvement
Act of 1991 for U.S. banks. This suggests that the banks in our sample had adequate
levels of equity capital to provide the necessary cushion for unanticipated asset portfolio
changes.5
We estimate the above cost equation to get estimates of ln u. The variable ln u is
used to derive the cost inefficiency measure. The inefficiency measure (INEFF ) is an
exponential transformation of the raw estimate of ln u. INEFF has a minimum value of 1
for the most efficient bank; all other banks are above 1 (See DeYoung, 1997).
INEFF~=~exp(ln~u).
(2)
We measure efficiency (EFF) by comparing the inefficiency index of each bank with the
index of the most efficient bank. This gives a good measure of relative efficiency in the
sample. The efficiency measure is bounded between 0 and 1. EFF is 1 for the most
efficient bank, and close to 0 for the least efficient bank.
4.
Efficiency and Its Determinants
Average estimated cost efficiency scores for the entire sample of banks for each of
the 11 years are presented in Table 3. The grand mean efficiency score for the 207
observations was 0.8897 with a standard deviation of 0.08439. The highest efficiency
index in the sample was 1 while the lowest index was 0.5411. Both the efficiency average
and standard deviation of nationwide banks were similar to regional banks. The overall
mean is well within the range estimated for other countries, including the U.S.6 Studies
that have used stochastic econometric methodologies have found inefficiency on the order
of 20 to 30 percent in U.S. banking (See Mester, 1996 and Berger and Mester, 1997).
The average bank in our sample would have increased its efficiency level about 11.03
percent had it been able to operate on the efficient frontier. In other words, about 11.03
percent of costs are avoidable on average relative to a best-practice bank.
Table 3 describes statistics for estimated EFF for each of 11 years in our sample.
A nonparametric sign test applied to this data shows that there is no inter-temporal
improvement in either the mean or standard deviation of cost efficiency index over the
sample period. Given the results reported in Gilbert and Wilson (1998) and the fact that
our sample period began in 1985, the results of this test suggest that the bulk of the
efficiency gains reported by Gilbert and Wilson were probably realized between 1980 and
1985— the time period immediately following the deregulation which began in 1980.
We examine the sources of efficiency by estimating a second stage efficiency
regression. In this regression, the relationship between our efficiency index, EFF, and a
set of economic, structural, and financial variables is explored. The second stage
regression model is specified as follows:
EFF~=~f(AGE,~lnTA,~ GROW, ~STA, ~STA2,~ BTD,~\ETA,~ DDTD, ~NINTOP,
~NATION,#
~STA*NATION, ~BTD*NATION,~EC,~REFORM)~+~epsilon.
(3)
As noted earlier, the efficiency measure is bounded between 0 and 1. Therefore, the
function used to specify equation (3) is required to be a monotonic increasing function that
projects from the real line to the [0, 1] interval. We therefore employ the logistic
functional form. The function is defined as
f(x) ~=~{e^x} over {1~+~e^x},
(4)
and we estimated equation (3) using nonlinear Ordinary Least Squares.
The independent variables included in the model are defined as follows. AGE
accounts for the efficiency difference between new and established banks. One might
expect a positive coefficient on AGE as established banks should have developed good
operative strategies to attain a higher level of efficiency. This follows the concept of
“learning by doing.” However, given that Korean banks have undergone periods of
nationalization followed by periods of privatization, it is not clear that older banks will
necessarily be more efficient than younger banks. The variable lnTA is the natural
logarithm of total assets and is included to control for the impact of scale bias on
efficiency. GROW is the growth rate of bank assets over the previous 12 months. This
variable provides a standard measure for bank performance. Many studies have found that
rapid asset growth does not always lead to improved performance. However, it is quite
possible that more efficient banks grow faster by the very fact that they are efficient.
Thus, we have no a priori expectations regarding the sign on the GROW variable. The
variables STA and BTD are the ratios of salaries-to-assets and branches-to-deposits,
respectively. They provide measures of the impact of overhead expenses on efficiency.
Since they capture expense behavior, we expect these variables to have negative
coefficients. STA2, the square of STA, is also included to capture nonlinear effects. ETA
is the ratio of total employees-to-total assets. This ratio is used to measure the effect of
labor force size on efficiency. Since labor unions in Korea are quite strong and wield
much control in the banking sector, we expect this variable to have a negative impact on
bank efficiency. This is because unions can cause rapid increases in wages even when not
justified by increases in worker productivity. The unions may also prevent banks from
reducing their labor forces when it is clearly called for. DDTD is the ratio of demand
deposits-to-total deposits and is included to capture the impact of deposit mix on
efficiency. Having a higher proportion of demand deposits increases the level of efficiency
because banks can utilize this source of financial capital (core deposits) without incurring
high interest cost. NINTOP is noninterest income over operating profits. This ratio
measures the impact of output mix on efficiency. The coefficient of NINTOP could be
positive or negative depending on the bank’s expertise and strategic objective. We would
expect it to be positive if a bank has the technical ability to offer noninterest income
product lines, i.e., fee based services, which permit the bank to achieve a higher level of
efficiency from its resources (especially its human capital). We would expect it to be
negative if the bank human capital resources and expertise is oriented more towards
traditional commercial and industrial lending activities. Finally, NATION is included to
capture the possible difference in efficiency between the nationwide and regional banks. It
is equal to 1 if the bank is national and 0 if it is regional. To allow for the possibility that
the effects of STA and BTD on the level of efficiency are different for nationwide banks,
each of these two variables was interacted with the NATION variable. Since they are
overhead expense variables, we expect the interaction terms to have negative coefficients.
EC, equity capital, is included to adjust for different risk levels among the sample banks.
Finally, an indicator variable, REFORM, is included in the model to capture any effects of
the 1991 deregulations.
Second Stage Regression Results
Table 4 presents summary statistics for the variables employed in the logistic
regression model. The average age of the sample banks is 36 years. The average growth
rate of bank assets was 16.44 percent and the average demand deposits-to-total assets was
38.05 percent. Banks with nationwide operations represented 47.4 percent of the sample
while regional banks represented 52.6 percent.
The results of the second stage efficiency regression are presented in Table 5. As
can be seen in this table, growth (GROWTH), the square of the ratio salaries-to-assets
(STA2), the ratio of the number of employees-to-total assets (ETA), the ratio of demand
deposits-to-total deposits (DDTD), the nationwide banking indicator (NATION), the
interaction variable for salaries-to-assets with nationwide banking (STA*NATION), and
the interaction variable for branches-to-deposits with nationwide banking
(BTD*NATION) all had a statistically significant impact on bank efficiency. The results
imply that banks with higher rates of growth enjoyed higher levels of efficiency. As noted
above, some studies have reported finding a negative relationship between asset growth
and efficiency. We interpret our finding as being consistent with a positive demand side
effect of efficient operations, i.e., more effective service levels and/or better combinations
of prices and quality. The coefficient estimate on the STA2 variable has a negative sign.
Given that STA is not statistically significant, this result is difficult to interpret. It is quite
possible that this variable is picking up elements of the tradeoff between capital and labor
in production.
The coefficient estimate for ETA accords with our a priori expectations. The
larger the number of bank employees per million won the less efficient is the bank.
Similarly, the coefficient on the variable, DDTD, measuring the source of bank funding,
accords with our a priori expectations regarding the efficiency benefits of using cheap
funding sources on the balance sheet. Nationwide banking franchises were found to be
significantly more efficient than regional franchises and likely reflects better access to
inputs. As expected, the interaction terms involving the ratios salaries-to-total assets and
branches-to-total deposits and nationwide banking had significantly negative coefficient
estimates. Thus, although nationwide franchises were more efficient, the positive effects
were offset when nationwide banks paid higher salaries relative to total assets (or
employed more employees relative to assets) and under took large investments in branches
to attract deposits. Finally, the financial deregulation of 1991 had no statistically
significant effect on the level of efficiency. This is most likely due to the fact that most of
the improvements in efficiency may have been realized during the years preceding 1985,
the beginning point of our analysis. That is, immediately following the major reforms
undertaken in the early 1980 and 1981. It is also quite possible that the reforms
undertaken in 1991 may take longer to produce visible results, or that they simply will not
have any impact on bank efficiency.
Auxiliary Findings
Reliable data on the percentage of chaebol and foreign equity ownership in our
sample banks was not available for the years examined in this study. Similarly, reliable
data on the level of nonperforming loans was not available. However, some reliable data
on each of these variables has become available recently as a result of the ongoing
financial crisis in Korea. Using chaebol and foreign equity ownership data and
nonperforming loans data for the year 1996, we computed the correlation between these
ownership characteristics and the average efficiency scores of our sample banks.7 The
results of this auxiliary analysis produced some interesting findings.
The nationwide banks that improved their efficiency scores following the 1991
deregulation (a total of 6 banks) had lower bad loans ratios, higher foreign equity
ownership, and higher chaebol equity ownership than those who did not have increasing
efficiency scores. Conversely, the 5 regional banks that improved their efficiency levels
following the 1991 deregulation, had lower bad loans ratios, and lower foreign and
chaebol ownership percentages.
Of the 6 nationwide banks that improved their efficiency levels after the financial
reforms instituted in 1991, 3 improved by a statistically significant amount with a
confidence level of 10 percent. The specific banks were the Cho Hung Bank, Korea First
Bank, and Hanil Bank. Comparing those banks that improved their efficiency levels after
the 1991 deregulation, the nationwide banks were more efficient than the regional banks.
However, the differences between these efficiency improving banks were not statistically
significant.
We also examined the correlation between the average efficiency scores of our
sample banks and some indicators of the macroeconomic performance of the Korean
economy. In this analysis, the correlations were computed using data which was available
for the years 1985 to 1993. The level of broad money, i.e., non-demand deposits and
currency, was found to be positively correlated with the average efficiency score of the
sample banks. Similarly, imports of nonfactor services was positively correlated with the
efficiency. The level of real long-term government debt was found to be negatively
correlated with the average efficiency score of our sample banks. Curiously, the level of
real exports of goods and nonfactor services was found to be negatively correlated with
the average efficiency score of our sample banks. This might be related directly to the
negative consequences to the banking sector of the government policy encouraging export
related lending. Finally, the efficiency index is positively correlated with the level of
foreign equity ownership but negatively correlated with the level of government
ownership.
5.
Conclusion
In this paper we extend the analysis of Gilbert and Wilson (1998) who examined
the impact of banking deregulation on the productive efficiency of Korean private banks
during the 1980 and 1994 period. While Gilbert and Wilson report on improvements in
productive efficiency following the 1980s deregulation, they did not attempt to identify the
key determinants of the efficiency gains. Using the stochastic cost frontier approach, we
compute efficiency scores for a sample of 19 top Korean banks over the 1985 to 1995
period. Using these efficiency scores, we fit a second stage efficiency regression. We
found that banks with faster growth rates, operating nationwide and which made extensive
use of core deposits in funding their assets were most efficient. As might be expected
given the strength of Korean labor unions, banks with fewer employees per million won in
assets were more efficient. We also examined the correlation between banking sector
average efficiency and indicators of macroeconomic performance. We found that average
bank efficiency was positively correlated with foreign equity ownership in the banks, and
broad measure of money. Average efficiency was negatively correlated with the level of
long-term private sector debt and the level of real goods exports.
6.
Epilogue8
Following the Korean economic crisis, the country’s unemployment rate reached
its highest level in 31 years and during the first half of 1998, the country’s GDP shrunk 5.3
percent- the largest drop in Korean history. In 1998, the GDP growth was estimated to be
-5.5%. This dire macroeconomic situation is expected to worsen as the IMF’s rescue
program continues. Against this backdrop, the short term prospects for the Korean
banking sector appear bleak. With nonperforming loans approaching as much as 30 to 40
percent of GDP and expected to rise further before falling, future prospects for the Korean
economy depend significantly on the ability of the government to recapitalize and
restructure the banking and financial systems. The prospects also depend on the country’s
ability to break the collusive links among government officials, the chaebol, and the
banking industry. To this end, the government has committed to complete a significant
amount of the needed restructuring of the financial sector by the end of 1998.
To date, of the 26 commercial banks in existence at the end of 1997, two banks—
Korea First Bank and Seoul Bank— have been nationalized and are being prepared for sale
to foreign investors. Twelve banks that failed to meet the 8 percent BIS capital adequacy
standard at the end of 1997 were asked to submit rehabilitation plans and were subjected
to asset quality diagnostic reviews. The plans of five of these 12 banks were deemed
infeasible and these banks had their licenses suspended and have in the process of being
acquired by five banks deemed be stronger (with the addition of public support) under
purchase and assumption transactions. The remaining undercapitalized banks received
conditional approval to operate and most have found merger partners. The nine healthy
banks not involved in mergers, including the five involved in the P&As, continue to
operate under strict supervision to insure that they do not become distressed.
Regarding the disposition of the banks included in our original sample as noted
above, as of December 1998, two of these banks— Korea First Bank (average efficiency
score of 0.8455) and Bank of Seoul (average efficiency score of 0.9598) were
nationalized. On December 31, 1998, the Korean government sold Korea First Bank to a
U.S. consortium. This was the nation’s first ever sale of a commercial bank to a foreign
firm. The Commercial Bank of Korea (average efficiency score of 0.8945) and the Hanil
Bank (average efficiency score of 0.8749) are merging on a voluntary basis but with some
governmental assistance. The Kookim Bank (average efficiency score of 0.8728) acquired
the Dae Dong Bank, a failed bank not included in our original sample. The Kookim Bank
has subsequently become involved in a merger transaction with Korea Long-Term Credit
Bank. Two banks— Chung Chong Bank (average efficiency score of 0.9003) and Kyungki
Bank (average efficiency score of 0.8785) have been closed and sold in purchase and
assumption transactions. Two banks— Shinhan Bank (average efficiency score of 0.9442)
and KorAm Bank (average efficiency score of 0.9311) are acquiring failed banks in
purchase and assumption transactions. KorAm is acquiring Kyungki Bank, one of the
failed banks in our sample. Of the banks that received conditional approval to operate,
Chungbuk Bank (average efficiency score of 0.7853) will be merging with Cho Hung bank
(average efficiency score of 0.9329) which has already merged with Kangwon bank
(average efficiency score of 0.8756).
The impact of chaebol bankruptcies on the Korean banking sector cannot be
overstated. For example, the failure of Korea First Bank was linked to the failure of its
key chaebol borrowers: Kia motors, Hanbo Iron and Steel, Sammi, New Core, Sinho, and
Tongil. Similarly, the Bank of Seoul was adversely impacted by the failure of its main
chaebol customers: DaeNong, ChungGu, HanshinGongYoung, and Jindo. More
generally, these bank failures can be traced to the failure of chaebol’s active in
construction and real estate. Following the financial crisis, the Korean government passed
a series of acts to support corporate restructuring in connection to bank restructuring and
recapitalization. The fundamental goals were to restore the creditworthiness of the
chaebols and lower their debt service requirements to bring them in line with their
projected cash flow. One of the key initiatives was to promote debt/equity conversion. A
recent amendment to the Bank Act allowed banks to hold corporate equity up to 15
percent or higher subject to approval.
In addition, in a series of policy measures supporting corporate restructuring,
Corporate Restructuring Vehicles (CRVs) were proposed. One main function of CRVs
was to purchase debt from financial institutions and convert it into equity. In addition,
CRVs’function extended to the management of converted equity. The forms of CRVs
included trusts, partnerships, funds for qualified investors, and closed-end mutual funds. In
an initial effort, 4 equity funds were created by the Ministry of Finance. Their funding
came from 25 financial institutions, and they are to be managed by experienced
international asset managers.
Furthermore, several banks deemed to be most healthy have been identified as lead
banks in corporate restructuring for the 64 large chaebol groups deemed to be in financial
distress. These banks include: Commercial Bank of Korea, Cho Hung Bank, Hanil Bank,
Korea Exchange Bank, and Bank of Seoul. These banks have created internal Workout
Units which will address their chaebol bad loan problem. These bank workout units will
be assisted by external financial advisors retained under the World Bank’s technical
assistance loan.
On January 13, 1998, Korean government officials and 5 top chaebols agreed on a
restructuring plan aimed at improving management practices. One area focused on
reducing moral hazard by requiring chaebols and creditor financial institutions to eliminate
cross guarantees among companies within chaebol groups. Other areas were designed to
improve operational efficiencies in order to raise the corporate sector's competitiveness in
the global markets. These included business restructuring focusing on core competence,
improving capital structure, enhancing corporate transparency and strengthening the
supervisory role of government and creditor financial institutions.
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Table 1
Sample Commercial Banks
Nationwide Banks
1.
2.
9.
Regional Banks
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Daegu Bank
Pusan Bank
Kwangju Bank
Chungbuk Bank
Chung Chong Bank
Kangwon Bank
Kyungki Bank
Kyongnam Bank
Jeonbuk Bank
Bank of Cheju
Cho Hung Bank
Kookmin Bank
3.
Hanil Bank
4.
Korea First
Bank
Commercial Bank of
5.
Korea
6.
Bank of Seoul
7.
Shinhan Bank
8.
Korea Exchange Bank
KorAm Bank
Table 2
Variables Used in Translog Cost Function
Maximum
(in million won)
Median
Minimum
494057.1
Standard
Deviation
483723.8
1726681
248635
26926.88
Total Loans
3058934
2886696
11838321
1639590
140895.5
Demand Deposits
959666.2
888602.2
3253754
586063.4
52046.96
Fee Income
41233.81
45658.52
174336.1
16257.95
1378.908
Wage Rate
11.77934
2.406335
18.77872
11.12292
8.402332
Interest for Borrowed Funds
0.072518
0.054909
0.614058
0.060771
0.033664
Price of Physical Capital
0.288544
0.109935
0.68766
0.263128
0.121245
Equity Capital
446920.2
417487
1470846
276738.4
19819.69
Variable
Mean
Total Costs
Table 3
Cost Efficiency (EFF)
Year
N
Mean
Std Dev
Minimum
Median
Maximum
1985
19
0.8729
0.1039
0.6888
0.9128
0.9906
1986
17*
0.8599
0.099
0.6892
0.8731
0.9901
1987
19
0.8595
0.06928
0.728
0.8489
0.9967
1988
19
0.8841
0.09555
0.5411
0.8966
0.9982
1989
19
0.9114
0.07246
0.7283
0.9327
0.9933
1990
19
0.9237
0.0942
0.5916
0.9604
1.0000
1991
19
0.9024
0.078801
0.6309
0.9193
0.9894
1992
19
0.8904
0.06121
0.7598
0.9117
0.9621
1993
19
0.9161
0.05828
0.7218
0.9278
0.9852
1994
19
0.9018
0.08299
0.6655
0.9264
0.9976
1995
19
0.8611
0.08907
0.6504
0.8689
0.9754
* Two banks have missing data in this year.
Table 4
Variables Employed in the Logistic Regression Model
Variable
Mean
Efficiency Index
Age
(in million won)
Median
Minimum
Maximum
0.8897
36.21053
Standard
Deviation
0.08439
19.99408
1
98
0.9115
29
0.5411
14
Total Assets
8264394
8635184
37211919
3837055
310788.7
Growth Rate of Bank Assets
0.164434
0.142156
1.27533
0.146509
-0.08987
Salaries-to-Assets
0.008651
0.003409
0.017676
0.008617
0.002461
Employees-to-Total Assets
0.000843
0.00055
0.002552
0.000695
0.000108
Branches-to-Deposits
Demand Deposits/Total Assets
0.00007
0.380456
0.000032
0.089305
0.000177
0.704221
0.000061
0.373751
0.000027
0.19958
Noninterest Income/Op. Profits
1.200807
0.831106
5.57
1.032252
-0.84176
Nation
0.473684
0.500506
1
0
0
446920.2
417487
1470846
276738.4
19819.69
0.363636
0.482201
1
0
0
Equity Capital
Reform
Table 5
Efficiency Correlates - Logistic Regression Parameter Estimates and Simple
Correlation Coefficients with Efficiency Score
Independent
L
o
g
i
s
t
i
c
R
e
g
r
e
s
s
i
o
n
P
a
r
a
m
e
t
e
r
S
i
m
p
l
e
C
o
r
r
e
l
a
t
i
o
n
C
o
e
f
f
i
c
i
e
n
t
s
Variable
Parameter
Estimates
(Significan
(Standard error)
________________________________________________________________________
___
Intercept
2.955104
(3.16625)
AGE
0.00292957
(0.0044518)
0.04749 (0.4969)
lnTA
-0.184281
-0.00833 (0.9052)
(0.16449)
GRO
W
1
.
4
7
5
7
9
9
(
0
.
5
8
5
8
1
)
*
*
0
.
1
5
3
7
5
(
0
.
0
2
8
1
)
STA
BTD
-38.282822
(174.5844)
0.05042 (0.4706)
STA2
16758.81
(7845.4)**
-0.04294 (0.539)
-104.190239 (4761.8)
ETA
1307.6
(404.1
3254)*
**
-0.10891 (0
DDTD
3.084042
(0.89821)***
0.19854 (0.0041)
NINTOP
(0.09461)
NATION
0.088441
-0.0301 (0.6668)
2.9350
16
(0.828
99)***
0.02263 (0
STA*NATION
-162.216092
(60.05065)***
0.03973 (0.5698)
BTD*NATION
-16480.83
(9103.9)*
-0.01357 (0.8462)
EC
3.2292
4E-7
(3.199
0.02188 (0
75E-7)
REFORM
0.029437
(0.205)
0.02433 (0.7278)
Adj R-Sq
0.1436
Coefficients with ***, ** and * are statistically different from zero at the 1%, 5%, 10%
levels of significance.
Endnotes
1
For a discussion of the South Korean growth miracle, see for example,
Park (1998).
2
In the early 1950s, banks were owned by the government. After a brief
period of privatization in the late 1950s, banks were once again
nationalized in the early 1960s. Near the end of the 1970s and into the
early 1980s, the government again privatized the banking system. An
additional series of financial reforms took place in the early 1980s and were
augmented again in the 1990s.
3
Beginning in 1984, banks were permitted to vary
their lending rates within a limited range
depending on the creditworthiness of
borrowers and to increase competition,
openness, and efficiency, the government
further lowered both entry barriers for bank
and non-bank financial institutions and
restrictions upon foreign bank branches.
New commercial banks and investment and
mutual savings companies were established
as a result of the policy change.
Discriminatory restrictions were also reduced
to allow for equal treatment between foreign
and domestic banks. Foreign banks were
able to access the central bank rediscount
window for financing, and engage in trust
activities.
4
There were a total of 26 commercial banks operating in the country during
the period of our study. The 7 banks not included in the sample either had
missing and unreliable data or were not deemed to be true private banks.
5
It should be noted that trust account assets are included in the computation
of the capital ratio. If these assets are deleted, the average capital-to-assets
ratio of our sample banks is about 9.4% percent, a number which compares
favorably with the B.I.S. standard of 8 percent.
6
The average efficiency for our sample of Korean banks also compares
favorably with estimates for the banks in the U.K., Germany, Sweden,
Spain, and Canada, among others. See, Berger and Humphrey (1997).
7
This analysis assumes that the level of nonperforming loans and the
percentages of chaebol and foreign equity ownership in the banks as of
1996 fairly characterizes the percentages in previous years.
8
This section draws directly from Claessens, Ghosh and Scott (1998) and
from personal correspondence with Yung Chul Park, Chairman of the
Hanil/CBK Merger Committee and officials at the Korean Institute of
Finance and the Korean Ministry of Finance.
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