Manuscript

Bad Loans and Accounting Discretion
Kaoru HOSONO*
Faculty of Economics, Gakushuin University, 1-5-1 Mejiro, Toshima-ku, Tokyo 171-8588,
Japan

Masaya SAKURAGAWA**
Department of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345,
Japan

ABSTRACTWhy did Japan’s non-performing loan problems and the banking crisis last more than adecade? We provide theoretical and empirical analyses that investigate whether a lax
enforcement of capital adequacy requirements, accompanied with discretionary accounting
practices, promoted Japanese banks to supply loans to almost insolvent firms and consequently
prolonged the non-performing loan problem in Japan. Following the findings derived from thedeveloped model, we construct a number of measures from accounting variables that are
expected to be correlated with bad loans. Our proposed accounting measures, the difference
between the risk-based capital ratio and the market-valued capital ratio, and the subordinateddebt ratio, are found to be useful in uncovering evidence supporting that Japanese banks had theperverse incentive of extending bad loans in an attempt to inflate regulatory capital in the 1990s.

JEL Classification Code: G21 G28
Key Words: bad loans, capital requirements, accounting discretion*

Corresponding author: Tel. +81-3-5992-4909, Fax. +81-3-5992-1007,
email kaoru.hosono@gakushuin.ac.jp** Tel. & Fax. +81-3-5427-1832, email masaya@econ.keio.ac.jp
This is a greatly revised version of the original paper entitled, “Soft budget problems in theJapanese credit markets.”1

Bad Loans and Accounting Discretion
1. Introduction

Why did Japan’s non-performing loan problems and the banking crisis last more than adecade? According to Hutchison and McDill (1999), the average duration of a banking crisis is
3.9 years that is smaller than the Japan’s case by 10 years ! Finland and Sweden went throughmore serious asset market collapses than Japan and yet needed only four years to solve the badloan problems. Korea were hit by a serious Asian currency crisis but also solved the bad loan
problem in four years.1
Our argument is that an inadequate enforcement of capital adequacy requirements was oneof important sources of the long-lasting non-performing loan problem in Japan. Capital
adequacy requirements constitute a core element of prudential regulation that is intended toinduce sound risk management of bank asset portfolios. Nonetheless, the regulatory authorities
allowed banks to engage in accounting discretion and to overstate bank capital. In response,banks had a strong incentive to conceal non-performing loans by extending additional loans toalmost insolvent firms. It is obvious that the extended loans became further non-performing
loans.
There are a number of studies that found the evidence of the accounting discretion undercapital regulations by Japanese banks, including Shimizu and Horiuchi (1998), Ito and Sasaki(2002), Fukao (2002), and Shrieves and Dahl (2003).2 There are also a number of studies thatfound the evidence of bad loans made by Japanese banks, including Sekine et al. (2002), Hori

1

In Sweden the crisis began in 1991 and ended in 1994. In Korea it began in 1997 and was almost
over in 2000.
2
Shimizu and Horiuchi (1998) found the evidence that Japanese banks issued subordinated debt inorder to maintain the capital ratio above the minimum requirement. Fukao (2002) reports thatJapanese banks issued subordinated debt for the purpose of cross-holding with life insurancecompanies within the same business group, keiretsu to overstate the “supplementary” Tier 2
regulatory capital. Ito and Sasaki (2002) found the evidence that Japanese banks issued subordinateddebt in order to compensate for the latent losses of stocks, both of which constituted components ofTier 2 capital. Shrieves and Dahl (2003) found that banks sold stocks to realize capital gains when
the increase in loan loss provisions decreased “core” Tier I regulatory capital, and argued thatJapanese banks regarded Tier 1 regulatory capital as a crucial regulatory constraint.
2and Osano (2002), Caballero et al. (2003), Peek and Rosengren (2005), and others.3 The former
literature revealed the evidence of accounting discretion that was rooted on capital requirements
by Japanese banks, while the latter found the evidences of the continuation of bad loans. To ourknowledge, however, there are few studies that investigated the relationship between accounting
discretion and bad loans.
The purpose of this paper is to provide theoretical and empirical analyses that investigate
whether a lax enforcement of capital adequacy requirements, accompanied with discretionary
accounting practices, promoted banks to supply loans to almost insolvent firms andconsequently prolonged the non-performing loan problem in Japan.
As stated above, bad loans are often associated with accounting discretion and difficult to
detect because reliable data is limited. Data on accounting discretion is not available, either. In
order to work out this difficulty, we construct a theoretical model in an attempt to derive testable
implications from observable data on the relationship among bad loans, capital adequacy
requirements, and accounting discretion.
The capital requirements, when it is subject to accounting discretion, provide banks with theperverse incentive to extend bad loans to almost insolvent firms. Continuing loans to bad firms
becomes a tool for inflating regulatory capital although it finally makes damages to the bank.
The market evaluation to the bank declines, while the bank has ample regulatory capital that is
sufficient to meet the minimum capital requirements. Recapitalization to poorly-capitalizedbanks also provides them with the perverse incentive. Recapitalization by issuing subordinateddebt, if it is issued to insiders, may not play a disciplinary role, but rather may work as a tool ofsoftening bank’s capital constraint. Consequently, subordinated debt and the continuation of bad
3

Sekine et al. (2002) found the evidence that the loan supply grew more at firms with high bankdebt to assets ratios after 1993, and that this tendency was pronounced among the construction andthe real estate sectors. Using data on banks and firms for the 1998 year, Hori and Osano (2002)
found the evidence that banks provided more (short-term) loans to borrowing firms with small
Tobin’s q when they were tied with banks under the main-bank relationship. Caballero et al. (2003)
quantified the amount of subsidized lending for the publicly traded firms and found that the level ofsubsidized lending increased markedly during the 1990s, and that the subsidies were far morecommon for non-manufacturing firms than for manufacturing firms. Peek and Rosengren (2005),
using the data on individual banks and firms over the 1993-1999 period, conduct the systematic
analysis to detect the misallocation of credit in Japan, and found that banks supplied more loans tofirms with low profitability and high debt-asset ratio.

3

loans can serve as complementary device for capital watering.
Following the theoretical findings, we construct a number of measures from accounting
variables that are expected to be correlated with bad loans. The first measure is themarket-valued capital as a proportion of bank assets that is expected to be correlated with thebank asset quality to the extent that the stock market incorporates the information on financial
conditions of individual banks accurately. The second measure, which we believe to be mostappropriate for account discretion, is the difference between the risk-based capital ratio (RBC)
and the market-valued capital as a proportion of bank assets. The theoretical finding predicts
that the divergence between the two ratios reflects the perverse incentive of banks to extend badloans. The third measure is subordinated debt as a proportion to risk-weighted bank asset. The
theoretical finding predicts that recapitalization by issuing subordinated debts to insiders works
as a tool of softening the bank capital constraint. The fourth measure is the distance of thereported RBC ratio from the minimum requirement level that is motivated by the idea that more
severely capital-constrained banks have a greater incentive of extending bad loans.
Using these measures of accounting discretion as explanatory variables, we estimate theshare of bad loans in total loans, because we can safely regard that the share of bad loans iscontrolled by banks and thus we can work out the identification problem associated with theloan supply function. Given the assumption that accounting variables are “manipulated”, banks
choose the loan portfolio and accounting variables simultaneously [e.g., Shrieves and Dahl
(2003)]. In order to avoid such an endogeneity problem, we estimate coefficients not only by
OLS but also by GMM.
We find that the RBC ratio is not correlated with the banks’ bad loans. Capital requirements
do not seem to have worked well to discipline banks’ behavior. On the other hand, themarket-valued capital ratio is correlated with the banks’ bad loans. The stock market seems tohave incorporated the information on financial conditions of individual banks to some degree.
Our proposed accounting measures, the difference between the risk-based capital ratio (RBC)
and the market-valued capital ratio, and the subordinated debt ratio, are found to be useful in
uncovering evidence supporting that banks had the perverse incentive of extending bad loans in
an attempt to inflate regulatory capital. The estimation using the distance of the reported RBC

4

ratio from the minimum requirement level suggests evidence that banks extended bad loans
beyond the minimum requirement. Furthermore, we find a different result between major banks
and regional banks, suggesting the too-big-to-fail policy with regard to the regulation andsupervision in Japan 4.
The remainder of this paper is organized as follows. Section 2 reviews the banking problem
in the 1990s. Section 3 sets up the model. Section 4 conducts the theoretical analysis. Section 5reports our empirical method and results. Section 6 concludes.

2. Overviews of the Japanese banking system in the 1990s

2.1 Basel capital standards and the manipulation of regulatory capital

We briefly explain how the regulatory authorities helped Japanese banks to manipulate
regulatory capital while requesting them to keep the Basel capital standards. The risk-based
capital ratio (hereafter the RBC ratio) is defined as the regulatory capital divided byrisk-adjusted bank assets. The regulatory capital consists of Tier 1 “core” capital and Tier 2“supplementary” capital. Tier 1 capital is comprised mainly of stock issues and disclosed
reserves, including share premiums and retained earnings, while Tier 2 capital is comprised ofundisclosed reserves, including unrealized capital gains on securities, provisions for generalloan losses, and subordinated debt with maturities exceeding five years. Tier 2 capital cannot
exceed the amount of Tier 1 capital as a contribution to total capital. All the banks that operateinternationally have to meet the minimum requirement level of 8 % of the RBC ratio. Otherwise
they have to withdraw from international business.
Tier 1 capital is defined in a consistent manner for all countries, but Tier 2 capital, thedefinition of which depends on national discretion, is easier to manipulate than Tier 1 capital.5
At the beginning of the 1990s, when the stock market bubble collapsed but stock prices were4

As an evidence of a too-big-to-fail policy, we point out the fact that the government recapitalized
all the major banks and only three regional banks in March 1998.
5
It was true at least until 1998 when the value of deferred taxes was permitted to count as Tier 1
capital.
5still relatively high, Japanese banks were allowed to count unrealized capital gains on securities
as Tier 2 capital.6 Japanese banks were also allowed to count subordinated debt as Tier 2 capitaleven though this was held by keiretsu-affiliated life insurance companies who also issued
subordinated debt to these banks. Such mutual holding of subordinated debt has increased
further since 1996 when the regulatory authorities started to impose risk-based capital adequacy
requirements, the so-called “solvency margin” standards, on life insurance companies.7 In 1997,
when the financial crisis happened, regulatory authorities changed accounting standards
concerning latent capital gains on securities, allowing Japanese banks that incurred unrealized
capital losses on securities to count stocks at acquisition cost. In 1998, banks were allowed tocount unrealized capital gains on land assets as capital base. Banks were able to inflate theircapital base because a large proportion of the land they held had been acquired long before theprice hike in the late 1980s. The value of deferred taxes was also permitted to count as Tier 1
capital.8
Figure I reports the RBC ratio for major banks as of March 1997. Almost all banks
recorded RBC ratios above 8 %. Surprisingly, Hokkaido Takushoku Bank and Long-Term
Credit Bank of Japan also recorded levels above 8 % although both of these banks eventually
failed within two years of March 1997. Only Nippon Credit Bank, which failed in 1998,
recorded the RBC ratio short of 8 %. Note that these three failed banks are placed at the first to
the third left columns of Figures I and II.
Since accounting manipulations were allowed, regulatory capital considerably diverged
from true economic capital, which is typically defined by the market-valued capital that is thenumber of stocks multiplied by end-of-fiscal-year stock prices. Figure I reports themarket-valued capital ratio that is defined as the market-valued capital divided by the sum of themarket-valued capital and total debt, denoted by MVC hereafter. Almost all the major banks
6

The Ministry of Finance allowed Japanese banks to count 45 % of their latent capital gains as partof tier 2 capital in 1990. This is a special rule applied to Japanese banks, but not to banks in the
United States or United Kingdom.
7
Fukao (2002) points out that life insurance companies held 6,689.6 billion yens of subordinateddebt issued by banks at the end of March 2002 while banks held 1,360.2 billion yens of subordinateddebt issued by 14 life insurance companies at the same time.
8
The deferred tax accounting plays a role in helping banks to inflate the regulatory capital since2000 (e.g. Skinner(2005)).
6

displayed the MVC ratios that were smaller than RBC ratios. Notably, the MVC ratios of thethree failed banks displayed even lower values than those of the other surviving banks. The
stock market seemed to evaluate the bank risk despite the widespread belief that poor disclosureof banks prevented market participants from accurately assessing bank performance. There are anumber of papers, including Yamori (1999), Peek and Rosengren (2001), Bremer and Pettway(2002), and Brewer et al. (2003), that found evidence suggesting that the Japanese stock market
were able to price the riskiness of Japanese banks, despite poor disclosure requirements andregulatory distortions,
Let us now look at the components of the capital base in detail. Figure II reports the Tier 1
capital and the major components of Tier 2 capital as a proportion of risk-adjusted assets for the
major banks as of March 1997. Almost all the major banks reported Tier 1 capital ratios above
4 %. Among the components of Tier 2 capital, subordinated debt accounted for a dominantportion. Subordinated debt constituted 2.3% of risk assets on average, about a quarter of total
regulatory capital (see Table 1). The proportions of subordinated debt were high especially at
Hokkaido Takushoku Bank and Long-Term Credit Bank of Japan.
Subordinated debt is, in case of bank insolvency, senior to equity but junior to any otherdebt including other bonds and insured deposits, and admitted as a component of Tier 2 capital
under the special rule of the Basel Accord. Subordinated debt is, in principle, expected to play a
disciplinary role on banks. Those banks that take on excessive risk will see the price of theirsubordinated debt falling, and hence will be forced to shrink their lending to satisfy capital
adequacy requirements (e.g., Calomiris, 1999). Recently a number of papers have foundstatistically significant relationship between the subordinated debt spread and various measuresof bank risk in the U.S. and European bond markets, including Flannery and Sorescu (1996),
Jagtiani et al (1999), De Young et al (2001), Sironi (2003), and others.
The situation in Japan was at odds with this view. In the 1990s, Japanese banks issued
subordinated debt to restore capital bases undermined by asset price deprecation andnon-performing loans (e.g., Horiuchi and Shimizu, 1998; Ito and Sasaki, 2002). However,subordinated debt was not fairly priced to reflect banks’ default risk. The purchasers wereassociated life insurance companies and the government, who never sold it in the market.

7Furthermore, the government often repaid subordinate-debt-holders on behalf of insolvent
banks.9 This observation suggests that subordinated debt did not play a disciplinary role, but
was used as a tool of softening banks’ capital constraints.

2.2 Perverse bank loan portfolios in the 1990s

Before formally analyzing the impact of the discretionary implementation of capital
regulations on bank portfolios, we briefly review the trend of Japanese banks’ portfolios in the
1990s. Although Japanese banks were burdened with huge amounts of non-performing loans,they did not shrink total loans outstanding until 1998. Figure III presents Japanese banks’corporate loans outstanding by industry. While Japanese banks shrank their lending to the
manufacturing sector, the most profitable sector, they increased their lending to the real estate
and the construction sector, which were suffering from the persistent falls in land prices.10 11.
To examine the financial health of these industries, we estimate how many years it would
take borrowing companies to repay their debts by calculating the sum of total borrowing andcorporate bonds outstanding divided by operating profits. Calculating and comparing the
average estimated years of debt repayment in the 1990s with those in the 1980s by industry, we
find that they rose sharply from 15 to 36 years for the real estate sector and from 8 to 14 years
for the construction sector, while it rose moderately from 6 to 9 years for the manufacturingsector.12
This shift in bank loan portfolios is inconsistent with the behavior of profit-motivated banks,suggesting that Japanese banks continued to extend loans to unprofitable firms and industries
even though it was unlikely that those loans would be recovered. Smith (2003) suggests the9

As a matter of fact, the case of Hyogo Bank, a regional bank that failed in 1995, is the last one
when creditors of subordinated debt were not protected. Since then, creditors of subordinated debt offailed banks have been protected.
10
Hoshi (2000) first pointed out that Japanese banks increased the share of loans to the real estateindustry after the collapse of the real estate bubble until 1997.
11
Accordingly, while the loan share to the manufacturing sector was almost constant about 15%
over the 1990s, loan shares to the real estate sector and the construction sector rose from 11% to
13% and 5% to 6%, respectively. See Hosono and Sakuragawa (2002) in detail.
12
We construct these figures using the data from the Financial Statement Statistics of Corporations
published by Ministry of Finance.
8

perverse behavior of Japanese banks by finding evidence that Japanese banks charged lower
interest rates than did foreign banks on syndicated loans, and varied pricing to a less degree
across risks than did foreign banks.
This tendency was especially pronounced among three major banks that later failed, i.e.,
Hokkaido Takushoku Bank, Long-Term Credit Bank of Japan, and Nippon Credit Bank. Figure
IV reports the sum of loans to the real estate, the construction, and the finance sector, summarilyreferred to as “real estate-related bad loans” or simply “bad loans” hereafter, as a proportion of
total loans. Long-Term Credit Bank of Japan and Nippon Credit Bank both sharply show higher
bad loan shares than surviving banks. Notably, bad loan shares of these two banks rose sharply
just before their failure.

3. ModelFollowing Rajan (1994), Berglof and Roland (1995), Aghion et al. (1999) and Mitchel(2001), we rely on a simple model of asymmetric information. There are two dates, date 0 anddate 1, with one bank and many potential borrowers. At date 0, the bank is endowed with capital

A and has access to insured deposits provided at zero interest rate.13 Assume that depositors
are repaid at date 1. The bank is run by a manager and in what follows we use the terms “bank”
and “manager” interchangeably.
The bank potentially makes two types of loans. One type is a safe loan that needs I units offunds at date 0 and returns X (  I ) with certainty at date 1. The other is a risky loan that thebank inherited and initially (before date 0) needed I units of funds. The continuation of thisloan additionally needs I units at date 0, and returns YH with probability p andYL ( YH ) with probability 1  p at date 1. When the bank does not make the additional loan,
the investment terminates and the bank receives Z by liquidating the borrower’s asset througha fire sale. The bank invests the other I units of funds in the government bond with zerointerest rate. Assume that the bank’s continuation/liquidation decision is public information, but

13

Strictly, we assume risk-insensitive, flat-rate deposit insurance pricing, and normalize the deposit
insurance premium to be zero.
9that the liquidation is costly, such that Z  I . The bank collects deposits 2  I  A at date 0
and is obliged to repay the total deposits 3  I  A at date 1.
At date 0, the manager receives a signal about the return of the risky loan. Suppose forsimplicity that the signal the manager receives is perfectly correlated with the performance ofthe risky loan. If the signal is “good”, the final return is YH with certainty while if the signal is“bad”, the return is YL with certainty.14 On the basis of that signal, the manager decides
whether to continue or terminate the risky loan. Importantly, the signal is observable but notverifiable to outsiders. Thus, even if the stock market detects the bank’s bad loan, the regulator(the government) cannot punish the bank for extending the bad loan only on the basis of thestock market information. The court cannot verify the causal relationship between the bad loans
and the stock market depreciation.
This situation is closely related to the accounting rule adopted here. First, the manager does
not lose his job even if he is observed in the market to have chosen a loan portfolio that turned
out to deteriorate the bank’s final earnings. Second, the manager does not lose his job even if heis found not to have disclosed latent gains/ losses from loans in progress. In other words, thebank is not forced to disclose true earnings on the basis of market value accounting. The
government forbearance policy takes the form of allowing banks to engage in the historic costaccounting.
We impose two restrictions on the parameters. First, we assume that YL  I  Z  YH . The
first inequality says that when the signal is bad, the bank earns more by terminating the risky
loan, while the second inequality says that when the signal is good, the bank earns more bycontinuing that loan. Second, we assume that ( X  I )  (YL  2 I )  A  0 , which says that,conditional on the signal being bad, the bank’s final equity value is positive even if the risky
loan is continued. This assumption allows us to focus on the possibility of the bank’s moral
hazard behavior even when the bank never faces the risk of insolvency.
The bank manager does not only benefit from holding the stock of the bank but also enjoys
a private benefit as a result of managing the bank. Formally, the manager maximizes the

14

Although the assumption of perfect accuracy of signal may be a little restrictive, nothing essentialchanges even when the signal is imperfect and the extent of the accuracy is high.
10expected date-1 value of(1)~
U   × max( E , A)  (1   ) × B , with 0    1 ,~where E represents the bank’s final earnings net of the cost of capital, and B stands for theprivate benefit that the manager enjoys by retaining his job.15 The weight  may be related tothe manager’s share of the bank’s stock, the degree of shareholding with affiliated firms, and thegovernment’s forbearance policy. The second term includes not only the manager’s salary but
also non-monetary benefits, such as perks or the satisfaction derived from controlling the bank.

~

We assume that the manager receives the private benefit B  B (  0) when retaining his job~

until date 1 and receives B  0 when losing his job. This term is meant to capture a situation
where the manager is not effectively disciplined to behave in the interest of outside shareholders
and may have an incentive to extend bad loans and hence worsen the bank’s profitability.
Finally, we assume that the manager is fired and loses private benefits at date 0 when thedisclosed risk-based-capital (RBC) ratio is short of the target ratio of 100× k %, which may beequal to or greater than the level of the minimum capital requirement of 8% for internationallyactive banks. The bank’s target ratio may be greater than the minimum requirement for anumber of reasons. The regulator might request banks to hold more capital beyond theminimum requirement in fear of a possible bank panic, and banks also may have an incentive ofobeying the regulator16. In addition, banks may take a buffer-stock behavior. Banks may have an
incentive of holding capital beyond the minimum requirement against possible adverse shocks
in the future. Actually, the fact that Hokkaido Takushoku Bank and Long-Term Credit Bank ofJapan recorded levels above 9 % just when they went bankrupt suggest that at least these banks
targeted more than 9 %.17 Although the decision to fire the manager is formally made by the15

The objective function that motivates non-profit maximizing banks is also used in Rajan (1994),

Aghion et al (1999), and Mitchell (2001).
Readers may wonder why there was a fear of bank panic when there was a government safety net.
However, deposit insurance protected deposits only partially until 1995. Even after the introductionof a blanket guarantee in 1996, depositors chose banks sensitively according to bank risk (e.g.,
Murata and Hori, 2006; Hosono, 2006).
17
Rigorously speaking, it may be better to assume that the manager faces double requirements of
8 % and 100× k %, but that assumption will complicate the analysis. One important implication ofthat extension is that there emerges a positive relationship between the RBC ratio and the bad loan
16

11

board of directors, the regulator may influence the decision indirectly through its pressure onbanks.18

4. Theoretical analysis
In this section we conduct a formal analysis based on the model developed in Section III.
We do this by first establishing a benchmark case and then introducing various aspects of themodel.

4.1 Minimum capital requirements

As a benchmark, it is useful to examine a world in the absence of any capital requirement.
The manager does not worry about losing his job and cares only about the bank’s final earnings.
When the signal is good, the manager continues the risky loan, and when the signal is bad, themanager terminates it.
Now we analyze the portfolio choice in the presence of the minimum capital requirement.
Having received the signal at date 0, the manager has to take into account his private benefit
from staying in that position in deciding whether to terminate or continue the risky loan.
When the bank follows the “termination strategy”, the bank incurs the loss I  Z as aresult of liquidating the borrower’s asset. The other I units are invested in the government
bond. At date 0, the bank writes off the loan loss and reports the risk based capital (RBC) ratioas ( A  Z  I ) I , where the numerator represents the sum of the initial capital and thedisclosed loan loss and the denominator states that only I units of loans are outstanding.
On the other hand, when the bank follows the “continuation strategy”, following the market
value accounting, the bank would have to make provisions against the expected loan loss, andhence in the face of a bad signal, the bank would have to report 2 I  YL as loan-loss

share across banks. The detailed argument regarding that relationship is made in the subsection C of
the next section (empirical implications) and Appendix.
18
Rajan (1994) develops a bank manager’s preference under which the manager attempt tomanipulate the disclosed earnings in order to raise his evaluation in the labor market. However, theobservation that the stock market detected the performance of bad banks suggests that the Rajan’s
idea does not seem to fit the Japanese evidence.
12

provisions. However, the manager who feels that the truthful reporting may endanger his
position attempts to behave as if the received signal is good. Additionally, the practice ofhistorical cost accounting helps the bank to hide the bad loan. As a result, in continuing the risky
loan, the bank reports the RBC ratio as A 3I . Note that we implicitly assume YH  2 I .
The RBC ratio under the continuation, A 3I , is greater than that under the termination( A  Z  I ) / I if

3( I  Z )  2 A holds. This inequality is likely to hold if either the bankcapital A or the liquidation value Z is small.. We assume that this inequality holds
throughout this paper. It follows that the manager is given the option of overstating the RBC
ratio by extending the bad loan.
Since our goal is to analyze the mechanism underlying the continuation of bad loans, inwhat follows we concentrate on the conditions under which the bank continues the risky loan
conditional on the signal being bad. Since the manager is expected to behave differently
depending on the severity with which capital regulations are enforced, we continue the analysis
by distinguishing banks in terms of their initial capital level.
First of all, we examine the behavior of a well-capitalized bank that can meet the target
RBC ratio either by continuing or terminating the risky loan, so thatmin[{ A  ( Z  I )} I , A 3I ]  k . This inequality is more likely to be met when either A or
Z is relatively high. Since the capital regulation does not distort the portfolio choice, themanager cares only about the bank’s final earnings in deciding whether or not to continue therisky loan. In the face of a good signal, the manager continues the risky loan, while in the faceof a bad signal, the manager terminates it.

Proposition 0: If the signal is bad, the well-capitalized bank terminates the risky loan.

Next we examine the behavior of a bank that is still fairly well-capitalized but can meet thetarget only by continuing the risky loan, so that ( A  Z  I ) I  k  A 3I . This inequality islikely to be met when either A or Z is relatively low. Having received a bad signal, themanager may face the trade-off between the bank’s equity value and his private benefit in thedecision. Conditional on the signal being bad, the manager obtains  ( X  Z  2 I ) under the13termination, and  ( X  YL  3I )  (1   ) B under the continuation. If the loan loss is written
off by the termination and the RBC ratio falls below the target ratio k , the manager will lose
his private benefits. We obtain the following.

Proposition 1: If the signal is bad, the fairly well-capitalized bank continues the risky loan if
the following inequality is met:

(1   ) B   ( Z  I  YL ) .

(2)

The L.H.S. of inequality (2) represents the private benefit from staying at the manager’s
position in the utility term, and the R.H.S. the cost of continuing the bad loan in the utility term.
The cost of continuation ( Z  I  YL ) is positive (by assumption), and only the
non-profit-maximizing bank with  less than unity will extend the bad loan. The smaller or Z , or the greater B , the manager is more likely to continue the risky loan although outside
shareholders would want the manager to terminate it.
Proposition 1 is closely related to the fact that it is difficult to evaluate the true bank capital.
In terms of the model, the bank can manipulate the regulatory capital by continuing the risky
loan for two reasons. First, the regulator has no tool to verify the bank’s loan quality. Second,
the regulator allows the bank to engage in discretionary accounting. A forbearance policy on thepart of the government will soften the bank’s capital constraint, which in turn will soften the
borrowing firm’s budget constraint and ultimately result in a non-performing loan. Very often
the government does not force banks to use market value accounting possibly because thegovernment fears possible disastrous consequences of the disclosure of banks’ true balance
sheets.
Finally we examine the behavior of a poorly-capitalized bank that can attain the target RBC
ratio neither by continuing nor terminating the risky loan, so thatmax[{A  ( Z  I )} I , A 3I ]  k . This inequality is most likely to apply when either A or

Z is very low. If the signal is bad, the manager would obtain  ( X  Z  2 I ) under thetermination strategy and  ( X  YL  3I ) under the continuation strategy. Since the bankcannot meet the requirement either by continuing or terminating the risky loan, the manager has

14

no incentive to continue the bad loan.

Proposition 2: If the signal is bad, the poorly-capitalized bank terminates the risky loan.

Propositions 0, 1, and 2 jointly imply a nonlinear relationship between the portfolio choice
and levels of bank capital. At low or high levels of bank capital, the bank’s profitability is more
important to the manager than his private benefit. Only for intermediate levels of bank capital,
the bank manager places more weight on his private benefit than on the bank’s profitability.

4.2 Recapitalization by subordinated debt

We have thus far assumed that the bank can raise funds only by collecting deposits.
However, as reviewed in Section II, Japanese banks typically relied heavily on subordinateddebt to meet the minimum capital requirements. Accordingly we extend the basic model toallow the bank to issue subordinated debt as another means of raising funds.
Suppose that at date 0, having received the signal, the bank decides whether to issue
subordinated debt to outside investors at date 0. Let p denote the date-0 price of subordinateddebt and D the amount issued. The bank raises the fund pD , promising to repay D at date
1. Note that the date-1 price is normalized to be unity. Assume that D is fixed. Assume finallythat the bank invests the raised cash in the government bond.
Under the assumption that the bank is solvent even when the risky loan fails, given by( X  I )  (YL  2 I )  A  0 , it is easy to see that p  1 .19 The subordinated debt does not
influence the bank’s final earnings and works only as a buffer to relax the original minimum
capital requirement. By issuing subordinated debt, the bank can raise the RBC ratio up to

19

The bank is always solvent to the creditors of subordinated debt under the assumed parameter
space ( X  I )  (YL  2 I )  A  0 . This can be proved as follows. At date 1 the bank is obliged to
repay (3I  A) to the depositors. Creditors of subordinated debt are senior to equityholders, but
junior to depositors, and so only if A  2 X  YL  D0  3I  D creditors of subordinated debt are
fully repaid. If A  2 X  YL  3I , A  2 X  YL  D0  3I  D automatically holds because
creditors are satisfied with D 0  D .
15

{ A  ( Z  I )  D} I under the termination strategy, and up to ( A  D) 3I under thecontinuation strategy.
Let us now consider the role of subordinated debt in the strategy of the fairly
well-capitalized bank. The manager determines the portfolio according to whether{ A  ( Z  I )  D} I exceeds the target ratio of k . If { A  ( Z  I )  D} I  k , the manager
does not have any incentive to issue subordinated debt. As Proposition 1 suggests, the manager
continues the bad loan. If, conversely, the amount of subordinated debt D is large enough tomeet { A  ( Z  I )  D} I  k , the manager may have an incentive to issue subordinated debt
because this may provide the bank with the opportunity to meet the target capital requirement.
In the face of a bad signal, the manager obviously prefers to terminate the loan.

Proposition 3: Suppose that { A  ( Z  I )  D} I  k holds. If the signal is bad, the fairly
well-capitalized bank issues subordinated debt and terminates the risky loan.

The fairly well-capitalized bank, when allowed to issue subordinated debt, is likely toterminate the bad loan, which is in sharp contrast with Proposition 1. The option to issue
subordinated debt diminishes the managerial incentive to continue the bad loan and rectifies theperverse effect of capital requirements on the loan portfolio.
We next turn to the case of the poorly-capitalized bank. Unlike when the bank can raise
funds only by collecting deposits, now the bank may be able to attain the target RBC ratio by
issuing subordinated debt. The poorly-capitalized bank can attain the target RBC ratio if theamount thus raised is large enough to satisfy max[{ A  ( Z  I )  D} I , ( A  D) 3I ]  k .
Since it is tedious to analyze all possible cases, we focus on the interesting case when thebank can meet the target only by a combination of issuing subordinated debt and continuing therisky loan, such that ( A  Z  I  D ) I  k  ( A  D) 3I . When the signal is bad, themanager would obtain the utility  ( X  Z  2 I ) under the termination and ( X  YL  3I )  (1   ) B under the continuation. We obtain the following:
Proposition 4: Suppose that ( A  Z  I  D ) I  k  ( A  D) 3I . If the signal is bad, the16

poorly-capitalized bank issues subordinated debt and continues the risky loan if(1   ) B   ( Z  I  YL ) {equation (2)}.

Comparing Propositions 2 and 4, we see that even the poorly-capitalized bank is likely toextend the bad loan when allowed to issue subordinated debt. Since the inequality( A  Z  I  D) I  k  ( A  D) 3I needs 2( A  D)  3( I  Z ) to be met, Proposition 4 islikely to hold when A , Z and D are small. It is plausible to think that D is small if A
is small since by regulation Tier 2 capital should be less than Tier 1 capital. Interestingly, whenbanks are allowed to recapitalize by subordinated debt, banks that are initially fairly-capitalized
tend to terminate the bad loan, whereas those that are initially poorly-capitalized tend tocontinue it.
Recapitalization by subordinated debt, together with the continuation of the bad loan,
provides the manager with room to meet the target RBC ratio, which may strengthen theperverse incentive to continue the bad loan. When the accounting discretion is allowed,
subordinate debt and the continuation of bad loans can serve as complementary devices forcapital watering rather than substitutes.
We briefly discuss the case when the bank becomes insolvent when the risky loan fails, that
is, X  3I  YL  A  0 . In this case, unless subordinated debt is government guaranteed, themarket value of subordinated debt will reflect the insolvency risk, and the decline in the price ofthe subordinated debt p may contribute to diminishing the managerial incentive to continue
the bad loan.

4.3 Empirical implications

The theoretical analyses above suggest a number of testable implications on the relationshipbetween bad loans (as a proportion of total loans) and suitable measures of accounting
discretion. To derive definitive empirical implications between them, we need to argue on thesignal that the bank received and the type of the bank. First, given that land prices declined andthe quality of loans deteriorated during the 1990s, we assume that Japanese banks received the17bad signal. Next, from the overview in the Section II, we also assume that Japanese banks werea poorly-capitalized bank.
It is useful to define the RBC ratio by{ A  (1  d )( Z  I )  D} (1  2d ) I ,(3)

where d is a dummy taking on zero when the risky loan is liquidated, and one when continued.
The RBC ratio depends on the initial capital A , the continuation/termination decision of thebad loan, and the amount of subordinated debt D . The bad loan share is defined by

2d (1  2d ) , which takes zero when the risky loan is liquidated, and 2/3 when continued.
We first examine the relation between the bad loan share and the market-valued capital ratio.
Letting Q denote the bank’s stock price per unit of capital evaluated at date 0, themarket-valued capital-asset ratio is

AQ, where the bank asset, the
AQ  (3I  A)  D

denominator, is the sum of the loan asset funded by bank equity, AQ , deposits, 3I  A , andsubordinated debt D . If the market evaluates the continued risky project at the average, thestock price will be quoted by Q 
becomesYa  X  3I  A, and the market-valued capital-asset ratioA

Ya  X  3I  A, where note that Ya  pYH  (1  p )YL . If the market detects theYa  X  Dcontinued risky project to be a bad loan almost completely, the market-valued capital ratio will
fall and be close to

YL  X  3I  A. On the other hand, if the bank liquidates the bad loan, its
YL  X  D

market-valued capital ratio will be

Z  X  2I  A, which should be smaller thanZX IDYL  X  3I  A
under the assumption of YL  Z  I . We obtain the following.
YL  X  D
Proposition 5: The bank’s market-valued capital ratio is larger under termination than undercontinuation, given that the banks’ continuation of the bad loan is revealed to the stock market.

If either A or Z is small, and D is also small, satisfying 2( A  D )  3( I  Z ) , the RBC
ratio is larger under continuation than under termination. Together with this, Proposition 518

directly leads to the following.

Proposition 6: If either A or Z is small, and D is also small, the divergence between the
RBC ratio and the market-valued capital ratio is larger under continuation than under
termination, given that the bank’s continuation of the bad loan is revealed to the stock market.

Importantly, the bad loan and the related accounting discretion leads to the divergence
between the RBC ratio and the market-valued capital ratio.20
The relationship between the bad loan share and the RBC ratio may not be monotone. The
model’s direct implication is that the bad loan share is zero at less than k , but jumps to somepositive level at k , and stays at that value at more than k . If the effect of the minimum
requirement is also taken into account, the relationship will be more complicated and needdetailed investigation. If the bank’s target is close to the minimum requirement level of 8 %, asFigure V1 illustrates, the bad loan share will be highest just above 8 %, and tends to decline as
the RBC ratio rises since banks that achieve more than 8 % can afford to decrease bad loans.

(Figure V1, V2, V3 should be placed around here.)

However, the bank may target a greater RBC ratio than the minimum requirement for somereasons stated in Section III. Actually, the RBC ratios of many samples seem to fall into theinterval of [0.08, k ] . Although the target RBC ratio is not in general observable, the following
figures will justify the importance of this argument.21 As for major banks, the share of thebank-year samples that display the RBC ratio more than 8% but less than 9% is 30.2% as afraction of the total samples examined in the empirical analysis (172, Table I), those of the RBC
20

Strictly speaking, even in the absence of accounting discretion, the RBC ratio and themarket-valued capital ratio do not in general coincide with each other. Both ratios coincide only
when (i) the risk weight for bank assets is equal to the market price of each asset, and (ii) all theitems in assets and liabilities are evaluated in market terms. However, Proposition 5 never loses its
generality because the divergence is greater when there is accounting discretion than not. We arethankful to Tsutomu Watanabe for pointing out this.
21
For example, Watanabe (2005) regarded the average of the realized RBC ratios for the 1992-1994
period as the target RBC ratio on the ground that Japanese banks did not find great difficulty inmeeting the capital requirements over that interval.
19

ratio that is more than 9% but less than 10% constitute 38.4% and those of the RBC ratio that isover 10% constitute 30.8%, respectively. Then, as Figure V2 illustrates, the relation may not bemonotone. In particular, we derive the positively sloped portion by extending the basic model.
See Appendix for the detailed analysis.
The relation between the RBC ratio and the bad loan share is mixed, depending on wheretarget RBC ratios lie. Furthermore, the negative correlation, even if it would be observed, does
not necessarily support the cosmetic hypothesis. The negative correlation is expected to arise
also when capital requirements work well. If banks are well disciplined by capital requirements,
as Figure V3 illustrates, banks with greater RBC ratios tend to display smaller bad loan shares(e.g. Gerard and Pyle (1991), Giammarino et al (1993), and others). Unfortunately, there are few
data of banks whose RBC ratio is less than 8 % (only 0.5% in our sample) and the result would
make interpretation difficult. Overall, it follows that, without any other measures added, thecorrelation between the bad loan share and the RBC ratio is suggestive of the evidence ofaccounting discretion only if it is positive.
The above argument allows us to posit the following three hypotheses in order to test our“accounting discretion hypothesis”. The first hypothesis, based on Proposition 5, is that thecorrelation between the market-valued capital ratio and the bad loan share is negative, given thatthe banks’ behavior of rolling over bad loans is revealed to the stock market (Hypothesis 1). The
second one, based on Proposition 6, is that the correlation between the difference between the
RBC ratio and the market-valued capital ratio and the bad loan share is positive (Hypothesis 2).
The third one, based on Proposition 4, is that the correlation between subordinated debt and thebad loan share is positive (Hypothesis 3).
We derive other testable implications from the theoretical findings. The theoretical analysis,
as a whole, implies that the bank is more likely to extend the bad loan to the extent that the bankcapital A or the liquidation value of the bad loan Z is small. The bank capital A plays adisciplinary role of prudential management. The forth hypothesis is that the correlation between
the bank’s capital and the bad loan share is negative (Hypothesis 4). A change in the liquidation
value Z may be closely associated with changes in land prices, implying that banks has more
perverse incentive of extending bad loans as land prices decline. The fifth hypothesis is that the20correlation between land prices and the bad loan share is negative (Hypothesis 5).

5. Empirical Analysis

5.1 Data
Our main source for banks’ balance sheet data is the Nikkei Financial Statement Data ofBanks (CD-ROM version, 2000). This data set covers all Japanese banks, including city banks,
long-term credit banks, trust banks, and regional banks. Our sample consists of those banks thatwere subject to the Basel capital standards. Banks are divided into major banks (city banks,
long-term credit banks and trust banks) which operate nation-wide and regional banks which
operate in and around the prefecture where their head office is located.
The sample period is from March 1991 to March 1999, i.e. the period following thecollapse of the bubble in land prices. When two or more banks are involved in a merger or
acquisition, we exclude these banks for that year and the following year from our sample
because of the lag structure in the estimated equation.
Data on the RBC ratio and its components are collected from each bank’s financial
statements. For stock price data, we use the Kabuka (Stock Price) CD-ROM, 2002, and Kabuka
Soran (List of Stock Prices), both published by Toyo Keizai Shimposha. For land prices, we use
the posted price index for land for commercial use for the prefecture where a bank’s head-office
is located. This land price index is published by the Ministry of Land, Infrastructure andTransport.

5.2 Estimation methods

We test the empirical implications of the theoretical hypotheses by estimating therelationships between the bad loan share and measures relevant to the discretionary accounting
controlling for possible other determinants including bank characteristics variables, the recovery
rate of bad loans, and macroeconomic shocks.

21

The accounting discretion hypothesis implies that accounting variables are “manipulated”,
and as the theoretical model suggests, it is natural to think that banks choose the loan portfolio
and accounting variables simultaneously.22 We try to avoid such an endogeneity problem byusing the following two methods. First, we apply OLS to the following equation:(4)

Bad Loan i ,t  1 Fundamenta ls i ,t 1   2 Account i ,t 1  f i  Yeart   i ,t ,where one-year lagged values of the explanatory variables are used. Secondly we apply adynamic panel GMM to the following Equation:(5)

Bad Loan i ,t   0 Bad Loan i ,t 1   1 Fundamenta ls i ,t 1   2 Account i ,t
 f i  Yeart   i ,t ,where the current values of the accounting discretion measures are used as explanatory variables
and their one-year lagged values as well as two- and more- year lagged values of the dependent
variables are used as instrumental variables (e.g., Arellano and Bond, 1991).
We explain variables used in the estimation. As a dependent variable, we use loans to thereal estate, the construction, and the finance sector as a proportion of total loans, as a measure ofbad loans, denoted by Bad Loan .23 Several reasons justify our choice of bad loans. First, realestate loans are inherently risky because real estate prices tend to move in the same direction
and it is therefore difficult for banks to diversify away the credit risk associated with changes inreal estate prices. Second, the profitability of real estate loans declined after the collapse of theasset bubble in the early 1990s. Third, as recent bank disclosure reports have shown, these threesectors accounted for a major fraction of disclosed non-performing loans.24 Fourth, as Caballero
et al. (2003) point out, during the 1990s the amount of subsidized lending increased markedly
for the real estate and the construction sector. Finally, we include loans to the finance sector
because Japanese banks often used their financial subsidiaries as dummy companies to lend to22

Watanabe(2005) , in estimating the effects of tightening capital regulation on the loan growth,
proposes an approach using appropriate instruments in order to avoid the simultaneity that will
happen between the loan growth and accounting variables
23
We do not use the growth rate of bad loans as the dependent variable in order to avoid theidentification problem associated typically with the loan supply function.
24
According to the Nihon Keizai Shinbun (June 13, 2001), among the total of non-performing loans,real estate accounted for 32.8 %, construction for 9.6 %, and finance for 7.1 %.
22

real estate companies and these subsidiaries belonged to the finance sector. In addition, thischoice of the dependent variable has an advantage that we work out the identification problem
associated with the loan supply function because the bad loan share is controlled only by banks.
We have access to the data for disclosed non-performing loans by individual banks but do notuse it because of its low reliability. It was widely recognized that, over the sample period, theweak bank governance by the financial authority allowed banks to understate the amount of
non-performing loans.
We next turn to the explanatory variables. Fundamentals consist of the bank characteristics
variables including ROA , the operating profit as a proportion of total assets, and ASSET , thelogarithm of total assets as well as PLAND , the rate of change in prefectural land priceindexes.
Since the bank’s true capital is likely to be positively related to the past bank’s earnings andthat the bank’s earnings is likely to be correlated over time, Hypothesis 4 predicts that thecoefficient on ROA is expected to be negative. Bank size measured by ASSET may affect theshare of bad loans via several routes. Large banks can diversify their loan portfolios and avoid
the concentration of loans to particular industries, and particularly real estate-related industries.
On the other hand, larger banks that are tempted to anticipate the government’s “too-big-to-fail”
policy may be more inclined to extend bad loans. The coefficient on ASSET is ambiguous.
To control for other unobserved bank characteristics, we estimate a fixed bank effect model by
including a bank dummy, f i .25
As the definition of bad loans implies, PLAND should capture the profitability (including
the recovery rate) of bad loans. Thus profit-motivated banks are supposed to shift away fromreal estate-related loans as land prices decline. On the other hand, as Hypothesis 5 suggests,
banks may be more likely to extend bad loans as land prices fall. Therefore, the coefficient on
PLAND is expected to be negative to the extent that banks deviate from the profit motive.
Finally, macroeconomic variables that may affect a bank’s loan portfolio are all captured bya year dummy, Year .

25

We have tested the null hypothesis that bank dummies are jointly zero and have obtained resultsthat reject the null in most of the equations.
23

5.3 Measures of accounting discretion

Account represents variables relevant to accounting discretion. Following the theoreticalfindings, we construct several measures of accounting discretion. The first variable is the RBC
ratio, denoted by RBC . If there is no accounting discretion and capital requirements work wellto discipline bank managers, the coefficient of RBC is expected to be negative. The literatureon the empirical analysis of capital requirements typically uses the RBC ratio as a fundamental
explanatory variable, including Hall (1993), Peek and Rosengren (1995), Montgomery(2005),
Watanabe(2005), and others.
The second variable is the market-valued capital ratio, denoted by MVC ,. Though thisvariable is not a measure of accounting discretion, we include it to test Hypothesis 1, positingthat the coefficient of MVC is expected to be negative as long as the stock market can see
through the bank asset quality.
The third variable relevant to accounting discretion is the difference between themarket-valued capital ratio and the risk-based capital ratio, denoted by DISCRET , which we
believe to be a most appropriate measure of account discretion. As Proposition 6 predicts, thedivergence between these two variables can be a proxy to the degree of accounting discretion.
Hypothesis 2 predicts that the coefficient of DISCRET is expected to be positive.
The fourth variable is subordinated debt as a proportion to risk-adjusted assets, denoted by
SD. Because almost all subordinated debts were issued for double-gearing in Japan, as we statedabove, this is a direct measure of accounting discretion. Hypothesis 3 predicts that thecoefficient on SD is expected to be positive.
With the above four variables, we can test whether banks tried to manipulate the total RBC
ratio or its Tier 2 capital. We test also to what extent banks were constrained by Tier 1 capitalrequirement. In doing so, we utilize the following three variables. The first variable is Tier 1
divided by risk-adjusted assets, denoted by TIER1. Liquidation of bad loans reduces Tier 1
capital by decreasing earnings. Because banks that are more constrained by Tier 1 capital are
more likely to extend bad loans, the coefficient on TIER1 is expected to be negative. The second
variable is general loan loss provisions divided by risk-adjusted assets, denoted by LOANLOSS.

24

General loan loss provisions reduce Tier 1 capital by decreasing earnings, while they increase
Tier 2 capital. Banks that are more severely constrained by Tier 1 capital requirement are likely
to understate LOANLOSS and at the same time to extend bad loans. The coefficient on
LOANLOSS is expected to be negative. The third variable is unrealized capital gains on
securities divided by risk-adjusted assets, denoted by GAIN. A realization of capital gains on
securities improves Tier 1 capital by increasing earnings, while it reduces Tier 2 capital under
the Japan-specific rule that allows banks to count 45% of unrealized capital gains on securities
as a part of Tier 2 capital. Banks with a larger GAIN are less constrained by Tier 1 capital, but
may be more constrained by Tier 2 capital. The coefficient on GAIN is expected to be negative(positive) to the extent that banks that are more constrained by Tier 1 (Tier 2) capital extend badloans.
Finally, we use dummy variables for the minimum capital requirements: REQ0 for the RBC
ratios less than 8%, REQ1 for those equal to or more than 8% but less than 9%, REQ2 for thoseequal to or more than 9% but less than 10%.We set the benchmark as the RBC ratios of 10% ormore. The coefficient on each of dummy variables measure the average difference of Bad Loanfrom those banks with RBC ratios equal to or more than 10% .The construction of thosedummies was basically intended to capture the notion that the closer the bank’s RBC ratio
relative to the minimum requirement was, the more likely the bank would extend bad loans inorder to mitigate their capital constraint. This idea is based on the premise that the bank’s target
RBC ratio is close to the minimum requirement level of 8%. If that was the case, thecoefficients of the dummy variables are expected to be positive, as Peek and Rosengren (2005)
point out. However, if the banks’ targets were on average greater than 10%, in terms of Figure
V2, they are expected to be negative. The coefficients on those dummy variables provide somevaluable information on banks’ target RBC ratio as long as the accounting discretion hypothesis
was valid.
Table I reports descriptive statistics of bank characteristics. For all banks, the averagevalue of Bad Loan is over a quarter of the total loans. The average value of RBC is over 9%,
while that of MVC is less than the average value of RBC. The difference between the two ratios,DISCRET , results in 2.55%, which suggests that the degree of accounting discretions were25

substantial. Turning to the components of regulatory capital, we see that the average value of
TIER2 is about a third of RBC. The average values of SD and GAIN suggest that these items
occupy a substantial portion (about 15% for each item) of the RBC ratio. On the other hand,
LOANLOSS is very small.
Table 1 also shows descriptive statistics by bank type. The assets of major banks were about
ten times as large as those of the regional banks. The averages of ROA were almost the sameacross the bank type. However, Badloan , was higher for major banks: that was about a thirdfor major banks and a quarter for regional banks.
The levels of RBC were almost the same, but its compositions were substantiallydifferent across the bank type. Notably, major banks displayed a lower TIER1 and a higher
TIER2, and in particular a higher SD than regional banks did. For major banks, SD accounts fora dominant share of Tier 2 capital, but not for regional banks. On the other hand, regional banks
displayed a lower MVC , resulting in a higher DISCRET .

(Table I should be placed around here.)

Table II reports the pair-wise correlations. For all banks, MVC is positively but only weakly
correlated with RBC. Note that the correlation should be strongly positive if there were nodiscretionary accounting practices. MVC is negatively correlated with DISCRET and withSD, which is consistent with our accounting discretion hypothesis. RBC is positively correlatedwith DISCRET , suggesting that RBC is a disguised measure of bank capital. Finally,

DISCRET is positively correlated with SD.
For major banks, MVC is negatively correlated with RBC , suggesting that discretionary
accounting practices were prevailing. MVC is strongly and negatively correlated withDISCRET and with SD, while RBC is positively correlated with DISCRET and SD.
Finally, DISCRET is strongly and positively correlated with SD, suggesting that
subordinated debt was a major tool for accounting dressing for major banks.
For regional banks, MVC is, unlike major banks, positively correlated with RBC. MVC is
negatively correlated with DISCRET and SD. RBC is positively correlated with DISCRET

26

but not as strongly as for major banks. RBC is negatively correlated with SD, unlike majorbanks. The correlation between DISCRET and SD is positive but the coefficient is smaller
than major banks. Though regional banks also seem to have engaged in discretionary accounting(given a sizable DISCRET ), the accounting tools available for them seem to have been
limited relative to major banks. Overall, these statistics suggest that regulatory authorities haveexercised greater forbearance toward major banks than regional banks by allowing the former torecapitalize using subordinated debt.

(Table II should be placed around here.)

5.4 Baseline Results

Table III presents the estimation results for all banks. For OLS estimates, White’sheteroskedasticity-consistent standard errors are reported in parentheses. For GMM estimates,
we use DPD package for OX (Doornik, et al., 2002) and report finite sample corrected standard
errors.

(Table III should be placed around here.)

Columns 1 to 4 show OLS estimation results. In all of the specifications, the coefficients on
ROA are negative and significant, which is consistent with Hypothesis 4. The coefficients on
PLAND are also negative and significant, which is consistent with Hypothesis 5. These results
suggest that banks had the perverse incentive of extending unprofitable loans.
In Column 1, the coefficient on RBC is negative but not significant, which seems to showthat capital requirements did not work well. The coefficient on MVC is negative andsignificant, which is consistent with Hypothesis 1, suggesting that stock market participants saw
through the market value of bank assets. In Column 2, the coefficient on DISCRET is positiveand significant, which is consistent with Hypothesis 2. In Column 3, the coefficient on SD ispositive and significant, which is consistent with Hypothesis 3. Looking at the other27

components, TIER1 is negative and significant, while neither GAIN nor LOANLOSS issignificant. In Column 4, none of the RBC dummies (REQ0, REQ1, and REQ2) are significant.
The OLS estimations are consistent with all of the five hypotheses, supporting the accounting
discretion hypothesis. The coefficient on TIER1 suggests that banks were constrained by Tier 1
capital requirement, but the coefficient on GAIN or LOANLOSS does not.
Columns 5 to 8 show GMM estimations. The coefficients on PLAND are again negative,
though the coefficient of only one specification (Column 7) is significant. The coefficients on
ROA are insignificant. In Column 5, the coefficient on RBC is not significant. The coefficient on
MVC is negative but not significant. In Column 6, the coefficient on DISCRET is positive andsignificant. In Column 7, the coefficient on SD is positive but only marginally significant (thep-value is 10.3%). The coefficient on GAIN is positive and significant, while the coefficients on
LOANLOSS and TIER1are insignificant. The GMM estimations are consistent with three of thefive accounting discretion hypotheses. No result shows that banks were constrained by Tier 1
capital requirement, but rather the coefficient on GAIN shows that banks that extended more badloan chose to account for unrealized capital gains of securities rather than to sell them,suggesting that they were constrained more by Tier 2 capital than Tier 1 capital. This finding issomewhat different from Shrieves and Dahl (2003) who reported that Japanese banks conductedaccounting manipulation in order to meet Tier 1 capital requirement. In Column 8, thecoefficients on REQ1 and REQ2 are negative and significant, showing that banks extended badloans as their RBC ratios rose beyond the capital requirement. This result contradicts with theargument for a disciplinary role of capital requirements. Our result suggests that banks set theirtargets at 10% or more and tried to inflate regulatory capital by extending bad loans toward theirtargets. 26

5.5 Estimation Results by Bank Type26

Our result contradicts also with the findings of Peek and Rosengren (2005). The difference of
estimated results might come from the difference of the data sets. Our sample includes only banks
that were subject to the minimum capita requirements, but Peek and Rosengren (2005)’s sample
includes domestically-operated banks, who were subject to the minimum capital regulations of 4%.
28

Descriptive statistics presented in Table II suggest that the government exercised greater
forbearance toward major banks than regional banks. In order to deal with the possible
heterogeneity between major and regional banks, we conduct estimations by dividing the fullsample into major banks and regional banks.
Table IV represents estimations for major banks. The coefficients on ROA are negative andsignificant for OLS, while they are insignificant for GMM. The coefficients on PLAND are
negative and significant both for OLS and GMM, which is consistent with Hypothesis 5. The
coefficients on RBC are positive for both OLS and GMM and significant for OLS, suggesting
the perverse response of major banks to capital requirements. The coefficients on MVC are
negative and significant only for OLS, which is consistent with Hypothesis 1. The coefficientson DISCRET are positive and significant for both OLS and GMM, which is consistent with
Hypothesis 2. The coefficients on SD are positive and significant for both OLS and GMM,
which is consistent with Hypothesis 3. The estimation results as a whole suggest that theaccounting discretion has been made particularly by major banks. RBC dummies are negativeand insignificant for OLS, but negative and significant for GMM. This result is consistent with
our hypothesis that major banks set their targets at a higher level than the minimum requirement(Figure V2).
The result on LOANLOSS for OLS suggests that major banks were constrained by Tier 1
capital, but any other results on LOANLOSS (for GMM), TIER1 and GAIN (for OLS and GMM)
do not. The coefficients on GAIN suggest that major banks tried to overstate Tier 2 capital rather
than Tier 1 capital.
Table V represents estimations for regional banks. The coefficients on ROA are positive forall specifications, and significant for only two specifications of the GMM estimations. The
positive coefficient is inconsistent with Hypothesis 4. The coefficients on PLAND are mixed
and not significant for any specification, which is inconsistent with Hypothesis 5. The
coefficients on RBC are not significant for OLS or GMM. The coefficients on MVC are negative
for both, and significant only for OLS, which is consistent with Hypothesis 1. The coefficientson DISCRET are positive for OLS and GMM, and significant only for OLS. The coefficients on
SD are positive and significant for OLS, but negative and significant for GMM. The estimations

29

for regional banks as a whole do not seem to support the accounting discretion hypothesis. The
contrasting results between major and regional banks suggest that the Japanese regulatory
authorities pursued a “too-big-to-fail.” The coefficients on RBC dummies are insignificant forany specification. No coefficient on LOANLOSS, TIER1 and GAIN suggest that regional banks
were constrained by Tier 1 capital.

6. Conclusions

In this paper we provide a theoretical and empirical analysis to explain the hypothesis that alax enforcement of capital adequacy requirements, accompanied with discretionary accounting
practices, promoted banks to supply loans to almost insolvent firms and consequently prolonged
the non-performing loan problem in Japan. We found empirical evidence to support that the
government responded to the perverse behavior of banks by allowing the discretionary
enforcement of minimum capital requirements, which softened the banks’ capital constraints
and contributed to the increase in bad loans.
How the accounting problem was crucial was revealed by the financial reform, so-called,“Takenaka Plan”, that started in the end of 2002 and was made to accelerate the disposal of
non-performing loans. Takenaka Plan was remarkable in that it was the first one in Japan that
attempted to restore the confidence in the Japanese banking sector by requesting banks to
improve bank governance. Particularly, Takenaka Plan strongly requested banks to improve thetransparency of financial information by stopping accounting discretion in meeting minimum
capital requirements. By 2005, non-performing loans drastically declined and the financial
reform was successful.27 Findings of this study and the financial reform taken by the Japanese
government tell us how the lax accounting practice weakens bank governance and leads to27

Sakuragawa and Watanabe (2007a) (2007b), using event study methodology, study how the stock

market evaluates the Japanese financial reform, so-called, “Takenaka Plan”. Their estimates showthat market participants seem to perceive that the supervisory policy and the bank governancegradually improved over time.

30

serious consequences of the banking problem.

31

Appendix: The positive relationship between the RBC ratio and the bad loan share

We extend the original model in two respects in order to derive the above relationship. First,
the bank potentially makes one safe loan and two risky loans, each of which needs I units offunds at date 0. Second, the manager is fired and loses private benefits with 100 % when thedisclosed risk-based-capital (RBC) ratio is short of the minimum capital requirement of 8% ,and with 100× q % when it is short of the target ratio of 100× k % (k  0.08) .
Focus on the case whenA  2( Z  I )A Z  I A
A  2( Z  I ) 0.08 , where
is
I
3I
5I
I

the disclosed RBC ratio when the bank terminates the both of the risky loans,
one when the bank terminates only one of the risky loan, andA Z  I
is theI

A
is the one when the bank
5I

continues both risky loans. Accordingly, the bank manager receives the expected utility of ( X  2 Z  3I ) ,  ( X  Z  YL  4 I )  p(1   ) B , and  ( X  2YL  5I )  (1   ) B ,respectively. The following is established.

Proposition 2’: If the signal is bad, the poorly-capitalized bank continues both of the riskyloans ifmin{ p,1  p}  (1   ) B   ( Z  I  YL ) ,(2’)

while it continues only one of the risk loan ifp(1   ) B   ( Z  I  YL )  (1  p)(1   ) B .

(2”)

When B is high, the inequality (2’) is likely to be met, and when B is low, inequalities(2”) are likely to be met. There may be a case when some banks with low B terminate only
one risky loan, having the RBC ratio that is more than 8% but less than 100× k % and the badloan ratio of 2/3, and the other banks continue both risky loans, having the RBC ratio that ismore than 100× k % and the bad loan ratio of 4/5. When B differs among banks, there
emerges a positive relationship between the RBC ratio and the bad loan share across banks.

32

Acknowledgements

We appreciate Toni Braun, George G. Kaufman, Masahiro Hori, Takeo Hoshi, Kiyoshi
Mitsui, Shinichiro Odaka, Kazuo Ogawa, Ralph Paprzycki , Yuri Sasaki, Yosuke Takeda,
Tsutomu Watanabe, and Wako Watanabe for helpful and valuable comments.

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36

Figure1

Figure I
The risk-based capital ratio (RBC) and the market-valued capital ratio (MVC) for Japan’s majorbanks as of March 1997. Market-valued capital is the number of stocks multiplied by theend-of-fiscal-year stock price. MVC is its ratio of the market-valued capital to the sum of themarket-valued capital and total debt. Source: Financial statement of banks and Kabuka [Stock
Price] CD-ROM 2002 published by Toyo Keizai Shimposha.

Figure2

0.12

0.1

0.08
Subordinate debt
Loan loss provisions
Unrealized capital gains on securities
Tier 1

0.06

0.04

0.02

Ho

Lo
ng
-T

kk
aid
o

Ta
k
e r N ip ushmpo
Cr on kued C r B aite d nkBa it
B
Ch nk o ankfuYa o T J ap
su ru
an
s
da
t
Tr B aus nk
Sa t Bku an
ra k
D a Ba
iw nk
a
As Ba
ah nk
i
M To Ban
its ka kuii
Tr B a
In
us nk
du
t
st
ria S an Ba
D a l B wa nk
i- I ank Bachni K of J k
an ap
gy an
o
Ba
Su Su Fuji nk
m mit BitaoM omo mo nk
its
ub Tru Ban
ish st ki
B
To Tru anst ky
N i o T Ba
pp runon st kTr B a
us nk
tB
an
k

0

Figure II
Components of the risk based capital (RBC) ratio of Japan’s major banks as of March 1997. The
major components of capital as defined by the Basel capital standards as a proportion ofrisk-adjusted asset are depicted. Source: Financial statements of banks.

Figure3

Manufacturing
100

Construction
Wholesale

90

Finance80

Real Estate

Trillion Yen

70
60
50
40
30
20
10

19
80
19
80
19
81
19
82
19
83
19
83
19
84
19
85
19
86
19
86
19
87
19
88
19
89
19
89
19
90
19
91
19
92
19
92
19
93
19
94
19
95
19
95
19
96
19
97
19
98
19
98
19
99
20
00
20
01
20
01
20
02

0

Figure III
Loans outstanding of domestically-licensed Japanese banks, by industry of borrowing firms.
Overdrafts before March 1993 were not included in the original data source and hence estimatedby the authors to obtain consistent time series data. Source: Bank of Japan, www.boj.or.jp

Figure4

Figure IV
Share of bad loans in total loans: failed major banks and the average of surviving major banks.
Bad loans are defined as the sum of loans outstanding to the real estate, construction, andfinancial industries. Source: Financial statements of banks.

Figure5

Figure V 1: Target is near 8%
Bad Loan Ratio

RBC
8%

Ratio

Figure V 2 Target exceeds 8%
Bad Loan Ratio

RBC
8%

Figure V 3

k%

Ratio

Discipline Hypothesis

Bad Loan Ratio

RBC
8%

Tables

TABLE I
Descriptive statistics: 1991-1999

Bad loan share (Bad Loan)
Return on assets (ROA)
Logarithm of assets(ASSET)
RBC ratio(RBC)
RBC<8% Dummy (REQ0)
8%<=RBC<9% Dummy (REQ1)
9%<=RBC<10% Dummy (REQ2)
Market-valued capital ratio(MVC)
RBC ratio - Market-valued capital ratio(DISCRET)
Tier1
Tier2
Unrealized capital gains on securities(GAIN)
Loan loss provisions (LOANLOSS)
Subordinate debt(SD)No. of obs.

All banks
Mean Std. Dev.
0.25900.07850.00580.002615.3559
1.1055
0.09390.01030.01040.10160.36010.48040.41370.49290.06840.02350.02550.02400.06080.01200.03320.00960.01480.00900.00340.00130.01460.0112
672

Major banks
Regional banks
Mean Std. Dev. Mean Std.Dev.
0.3450 0.0904
0.2294 0.0453
0.0058 0.0020
0.0058 0.0039
14.8390 0.5587
16.8584 0.9127
0.0932 0.0090
0.0961 0.0130
0.0120 0.1090
0.0058 0.0762
0.3800 0.4859
0.3023 0.4606
0.4240 0.4947
0.3837 0.4877
0.0638 0.0186
0.0817 0.0304
0.0294 0.0176
0.0143 0.0343
0.0629 0.0114
0.0548 0.0119
0.0304 0.0079
0.0413 0.0095
0.0151 0.0083
0.0140 0.0107
0.0034 0.0010
0.0036 0.0017
0.0116 0.0082
0.0233 0.0139
172

37

500

TABLE II
Correlation Matrices
A.All Banks
MVC
RBC
REQ0
REQ1
REQ2
DISCRET
TIER1
TIER2
GAIN
LOANLOSS
SD

MVC

RBC

REQ0

1.000
0.178
-0.082-0.087-0.040-0.907
0.109
0.053
0.402
-0.055-0.2521.000-0.253-0.608
0.018
0.254
0.638
0.271
0.213
0.249
0.011

1.000
-0.077-0.086-0.028-0.113-0.129-0.102-0.040-0.022REQ1

1.000-0.630-0.175-0.369-0.188-0.256-0.111
0.072

REQ2

DISCRET

TIER1

TIER2

GAIN

LOANLOSS

1.000
0.048
-0.0400.069
0.140-0.064-0.041

1.000
0.166
0.064
-0.304
0.161
0.253

1.000
-0.5680.019
0.093-0.521

1.000
0.204
0.149
0.663

1.000
-0.156-0.579

1.000
0.108

38

SD

1.000

B.Major Banks
MVC
RBC
REQ0
REQ1
REQ2
DISCRET
TIER1
TIER2
GAIN
LOANLOSS
SD

MVC

RBC

REQ0

1.000
-0.105-0.1250.039
0.031-0.9260.072-0.2340.579-0.071-0.5741.000-0.390-0.520-0.155
0.473
0.709
0.481
-0.094
0.270
0.349

1.000
-0.050-0.060-0.037-0.258-0.211-0.096-0.114-0.056REQ1

1.000-0.519-0.232-0.271-0.372-0.060-0.087-0.181REQ2DISCRET

TIER1

TIER2

GAIN

LOANLOSS

1.000-0.086-0.2960.158
0.101-0.071
0.038

1.000
0.205
0.390
-0.549
0.165
0.641

1.000
-0.277-0.0390.040-0.1671.000-0.080
0.317
0.684

1.000
-0.178-0.767

1.000
0.206

39

SD

1.000

C.Regional Banks
MVC
RBC
REQ0
REQ1
REQ2
DISCRET
TIER1
TIER2
GAIN
LOANLOSS
SD

MVC

RBC

REQ0

1.000
0.350
-0.067-0.127-0.065-0.8770.329-0.0730.356-0.101-0.3951.000-0.221-0.662
0.110
0.142
0.722
0.104
0.424
0.220
-0.3831.000-0.086-0.095-0.043-0.096-0.116-0.111-0.012
0.006

REQ1

1.000
-0.672-0.205-0.456-0.101-0.348-0.1230.287

REQ2

DISCRET

TIER1

TIER2

GAIN

LOANLOSS

SD

1.000
0.125
0.033
0.077
0.156
-0.060-0.067

1.000
0.022
0.131
-0.160
0.219
0.221

1.000
-0.6130.023
0.175-0.6481.000
0.451-0.0030.495

1.000-0.135-0.5271.000-0.0391.000

40TABLE III
The determinants of bad loans for all banks

Estimation
Equation No.
Badloan

OLS
1

GMM
3

2

4

6
0.546 **
(0.077)-0.122(0.396)

7
0.509 **
(0.091)-0.060(0.516)8
0.555 **
(0.079)0.051(0.466)Return on assets(ROA)-0.773 *(0.469)-0.802 *(0.464)-1.100 **(0.463)-0.812 *(0.458)50.548 **
(0.078)-0.175(0.422)Rate of increase in land prices(PLAND)-0.025 **(0.011)-0.025 **(0.011)-0.027 **(0.011)-0.023 **(0.011)-0.014(0.013)-0.012(0.011)-0.021 *(0.011)-0.017(0.011)

Logarithm of assets(ASSET)-0.052 **(0.013)-0.054 **(0.013)-0.017(0.013)-0.052 **(0.013)-0.034 **(0.017)-0.028(0.017)-0.051 **(0.017)-0.038 **(0.019)RBC ratio(RBC)-0.028(0.124)0.340(0.230)

RBC<8% Dummy (REQ0)-0.001(0.004)-0.013(0.012)

8%<=RBC<9% Dummy (REQ1)

0.002(0.003)-0.012 **(0.006)9%<=RBC<10% Dummy (REQ2)

0.001(0.002)-0.008 **(0.004)Market-valued capital ratio(MVC)
RBC ratio - Market-valued capital ratio(DISCRET)-0.134 **(0.052)-0.116(0.108)0.119 **
(0.050)0.181 **
(0.090)Tier1-0.301 **(0.144)-0.012(0.195)

Unrealized capital gains on securities(GAIN)-0.297(0.217)-1.864(1.188)0.509 **

1.054 **
(0.461)0.079(1.402)
0.507

Loan loss provisions(LOANLOSS)

41

Subordinate debt(SD)No. of obs.
No. of banks
Adjusted R2
AR(2) test
Sargan test

(0.178)

676
93
0.969

676
93
0.969

676
93
0.971

(0.311)

676
93
0.969

649
92

649
92

649
92

649
92

-0.03054.44-0.17152.97-0.00849.58-0.142
53.89

White's heteroskedasticity-consistent standard errors are reported in parentheses.
**, * significant at 5 percent and 10 percent, respectively.
Instrumental variables are two-year and more lagged values of Badloan and one-year lagged values of the explanatory variables.

42

TABLE IV
The determinants of bad loans for major banks

Estimation
Equation No.
Badloan

OLS
1

GMM
3

2

4

5
0.397 *
(0.239)60.434 **
(0.177)70.175(0.284)8-0.137(0.433)Return on assets(ROA)-1.380 *(0.702)-1.322 *(0.689)-1.778 **(0.669)-1.258 *(0.705)0.806(0.780)0.940(0.761)-0.144(0.520)-0.569(0.712)Rate of increase in land prices(PLAND)-0.064 **(0.026)-0.068 **(0.027)-0.070 **(0.025)-0.064 **(0.028)-0.036 **(0.011)-0.038 **(0.012)-0.040 **(0.016)-0.043 **(0.017)Logarithm of assets(ASSET)

0.047(0.030)0.043(0.028)0.057 *
(0.030)0.049(0.030)0.027(0.022)0.031(0.021)-0.012(0.026)0.013(0.025)

RBC ratio(RBC)

0.523 *
(0.278)0.570(0.359)

RBC<8% Dummy (REQ0)-0.004(0.009)-0.037(0.031)

8%<=RBC<9% Dummy (REQ1)-0.008(0.006)-0.003(0.004)-0.016 **(0.007)-0.008 **(0.003)

9%<=RBC<10% Dummy (REQ2)
Market-valued capital ratio(MVC)
RBC ratio - Market-valued capital ratio(DISCRET)-0.186 *(0.109)-0.316(0.258)0.218 **
(0.110)0.394 **
(0.188)Tier1-0.084(0.451)-0.798(0.998)

Unrealized capital gains on securities(GAIN)-0.250(0.457)-3.495 **1.235 **
(0.550)2.803

43Loan loss provisions(LOANLOSS)(1.451)
0.949 **
(0.390)Subordinate debt(SD)No. of obs.
No. of banks
Adjusted R2
AR(2) test
Sargan test

172
23
0.963

172
23
0.963

172
23
0.964

(3.549)0.755 *
(0.440)

172
23
0.961

163
22

163
22

163
22

163
22

-0.2802.74-0.727
3.58

0.170
2.81

1.581
4.79

White's heteroskedasticity-consistent standard errors are reported in parentheses.
**, * significant at 5 percent and 10 percent, respectively.
Instrumental variables are two-year and more lagged values of Badloan and one-year lagged values of the explanatory variables.

44

TABLE V
The determinants of bad loans for regional banks

Estimation
Equation No.
Badloan

OLS
1

2

3

4

5
0.495 **
(0.086)6
0.487 **
(0.088)GMM
70.444 **
(0.102)80.497 **
(0.083)Return on assets(ROA)

0.232(0.551)0.163(0.543)0.022(0.546)0.008(0.559)1.057 *
(0.608)1.107 *
(0.613)0.816(0.789)0.845(0.629)Rate of increase in land prices(PLAND)-0.010(0.008)-0.011(0.008)-0.006(0.009)-0.010(0.008)0.004(0.012)0.007(0.012)-0.005(0.015)0.006(0.012)Logarithm of assets(ASSET)-0.016(0.017)-0.015(0.017)-0.007(0.018)-0.017(0.018)-0.020(0.025)-0.026(0.023)-0.052 **(0.026)-0.027(0.024)

RBC ratio(RBC)

0.031(0.128)-0.078(0.374)

RBC<8% Dummy (REQ0)-0.003(0.004)0.005(0.009)8%<=RBC<9% Dummy (REQ1)

0.003(0.003)0.001(0.002)-0.003(0.006)-0.005(0.003)

9%<=RBC<10% Dummy (REQ2)
Market-valued capital ratio(MVC)
RBC ratio - Market-valued capital ratio(DISCRET)-0.161 **(0.051)-0.208(0.136)0.150 **
(0.049)0.166(0.148)Tier1-0.196(0.153)-0.060(0.362)

Unrealized capital gains on securities(GAIN)-0.2970.597

45

Loan loss provisions(LOANLOSS)
Subordinate debt(SD)No. of obs.
No. of banks
Adjusted R2
AR(2) test
Sargan test

(0.533)-1.397(1.103)-1.371 **(0.664)(0.215)2.923(1.878)0.403 **
(0.181)

504
70
0.943

504
70
0.943

504
70
0.943

504
70
0.942

486
70

486
70

486
70

486
70

-0.24649.42-0.181
49.58

0.718
47.17

0.362
51.34

White's heteroskedasticity-consistent standard errors are reported in parentheses.
**, * significant at 5 percent and 10 percent, respectively.
Instrumental variables are two-year and more lagged values of Badloan and one-year lagged values of the explanatory variables.

46