Wijantini—The Indirect Costs of Financial Distress in Indonesia
Gadjah Mada International Journal of Business
May-August 2007, Vol. 9, No. 2, pp. 157–186

THE INDIRECT COSTS
OF FINANCIAL DISTRESS IN INDONESIA*
Wijantini
This paper presents quantitative estimates of the indirect cost of
financial distress and its determinants. In order to measure the cost,
this study estimates the annualized changes in industry-adjusted
operation profit and sales from a year before the onset of distress to
the resolution year. Using those approaches, the median of indirect
financial distress cost is estimated between three and 11 percent
annually. To the extent that the direct cost of financial distress
reduces reported operating income, the estimated costs are overstated. The simple regressions analysis suggest that the indirect cost
of financial distress significantly increases with size, leverage,
number of creditors, and poor industry performance, but is not
related to degree of bank loan reliance. The findings provide a weak
support for the financial distress theory which suggests that conflicts
of interest render the costs of financial distress.
Keywords: conflicts of interest; indirect cost of financial distress; industry factor

*)

Acknowledgement: This paper is based, in part, on my thesis completed at the University of
Birmingham, UK. I am indebted to my supervisor, Dr. T.A Adedeji for his valuable comment.
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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Introduction
The existence of total financial
distress costs is a critical argument in
corporate finance issues, such as optimal capital structure, firm valuation,
and risk management. The initial work
of Modigliani and Miller (1958, 1963)
trigger seminal arguments on the importance of these costs. It is deeply
embedded in most of the theoretical
works of the authorities in this field
(Kraus and Litzenberger 1973; Scott
1976; Castanias 1983; White 1983).
The objectives of this paper are,
first, to estimate the indirect costs of
financial distress in Indonesia. Capital
structure theories give contradictory
suggestions on whether the costs of
financial distress are trivial (Modigliani
and Miller 1958, 1963) or non-trivial
(Myers and Majluf 1984). The estimates of indirect costs of financial
distress obtained are used to determine
which of these contradictory theoretical views is more relevant to Indonesia. Second, it purports to compare the
estimates of indirect costs of financial
distress obtained for Indonesia with
similar estimates that were reported
for the US. Estimates of the costs of
financial distress that have been reported in the literature were obtained
mainly with U.S. data. The results of
comparison are beneficial for assessing the relevance of the estimates to a
developing economy like Indonesia.
Finally, the other objective is to test the
firm characteristics, which previous
studies suggest to be the determinants
of cross-sectional variation in the costs
158

of financial distress in the U.S., on the
firms in Indonesia, and to examine
whether the impacts of the firm characteristics in Indonesia are similar to
those reported in the U.S.

Brief Literature Review
Financial distress is a situation
where firms cannot service their current debts. Financially distressed firms
have to meet more costs than do normal firms. The costs may reduce firm
value and conventionally consist of
both direct and indirect costs. If firms
at this state reorganize under court
supervision and opt for liquidation,
they may incur even higher direct costs
than if they reorganize privately
(Gilson, John, and Lang 1990). The
values of their assets may go down
progressively while waiting for liquidation. In addition, they will also indirectly be burdened by the costs imposed by customers, suppliers, and
capital providers as a result of financially distressed condition and nonoptimal managerial actions during the
period of distress. Firms’ bad performance leads managers to lose time in
formulating and communicating reorganization plans to their stakeholders.
Hence, the total indirect costs of financial distress are potentially great and
occur whether or not the firm actually
defaults (Chen and Merville 1999).
Previous studies tried to find how
high the costs of financial distress were,
especially those related to the use of
the costs in the capital structure theory.
Some empirical studies estimate the

Wijantini—The Indirect Costs of Financial Distress in Indonesia

costs of financial distress as any reduction in the value of output in the real
world relative to the hypothetical best
world. Critiques appear to the measurement due to the lack of distinction
between ex-ante and ex-post distress
costs. The importance of ex-ante distress cost should be addressed if it is to
be applied in such a theory. Other
studies divide the costs into three types,
which are associated with the behavior
of managers of failing firms who attempt to avoid or delay filing for bankruptcy. They can result from overinvestment, under-investment, or the
delay effect, all causing additional expenses. Financial distress also happens as a result of a mismatch between
the currently available liquid assets of
a firm and its current obligations under
its financial contracts. To solve such
mismatch problem, firms are supposed
to restructure the assets and/or restructure the financing contracts. Restructuring the asset means that firms may
convert illiquid assets to liquid ones,
whereas restructuring the financial
contracts relates to debt restructuring.
In other words, the costs of financial
distress are costs related to corporate
liquidity policy and leverage policy.
When the costs are high, firms may
maintain a larger fraction of their as-

sets as liquid assets and/or incur debt
cautiously.
Economic researchers often find
difficulty measuring the “pure” costs
of financial distress. The difficulties
come from an inability to distinguish
whether the poor performance of a
firm in financial distress is caused by
the financial problem per se or is caused
by factors which originally push the
firm into financial distress, e.g., economic problems or fraud. Andrade and
Kaplan (1998) offer the “pure” measurement of financial distress by using
sample with positive operating income
as evidence that the sample is not economically distressed firms, but firms
which suffer from negative earnings
after paying debt interest. The authors
claim that their sample contains purely
financially distressed firms, and for
this reason they call their measurement ‘costs of financial distress’. Measuring the costs of financial distress is
done by comparing the estimated capital value of the distressed firm at the
end of the year before the onset of
distress to the capital value realized
through the resolution of distress. Table
1 summarizes previous research on the
costs of financial distress in various
sample, methods, and results.

159

160

Southern District of New York

reorganising firms under new code in

Lang (1990)

Gilson, John and

of exchange offers for publicly traded debt. An estimate of exchange
offer-related costs was obtained in circular distributed to bondholders. The circular provided an estimate of out of pocket costs including
payment made to the exchange and information agent and related
legal, accounting, brokerage and investment banking fees.

A sample of 169 listed financial

distress*** companies 1978 – 1987, 80

of themprivately restructuring their debt

and 89 firms reorganising under court

supervision.

Measuring the costs of private workouts by estimating the direct costs

wealth caused by the litigation.

book value of the firm.

ranged between 2.8% and 7.5% of the

firm. Legal fee for bankruptcy filing

0.65%and 0.32%of the book value of the

restructuring private debt, was about

offers, the most used method for

The mean and median cost of exchange

changes was around 9% of firm value.

the outstanding equity of each company to estimate the changes in

The indirect cost implied by stock price

in equity value and multiplying the abnormal returns by the value of

under the new Code.

billion compared to $35.6 billion per year

costs under previous Code were $23.2

indirect costs of financial distress by calculating the abnormal changes

The study used a market model to measure Texaco and Pennzoil’s

parameter values from both before and after the new Code took over.

Calculating the upper bound expressions suggested by model, using

costs were higher than before. Bankruptcy

compared to 88 liquidating and 33

Cutler and Summers It used Texaco-Pennzoil case in 1984 –
(1988)
1988.

(1983)

White, Michelle J.

and 1.7%.

to 100% with mean and median of 7.5%

liquidating value was in range from 0.12%

She suggested that new Code bankruptcy

fees to the liquidation values of the firms.

firms filing under old bankruptcy act

western district of Oklahoma

McConnell (1982)

Direct costs of bankruptcy were measured by dividing administrative

The percentage amount of the costs to total

petition date.

by identifying prices of traded securities.

rose to 5.3% of market value prior to the

the market value of the firms at various points before the year of filing

1% of market value seven years prior and

Direct costs of bankruptcyaveraged about

Findings

to reflect the value of time they spent administering the bankruptcy to

filing fees. They do not include payments to managers or employees

to all parties for legal fees, professional services, trustees’ fees and

Direct costs of bankruptcy were measured by dividing the payments

Method(s)

90 liquidating** and 96 reorganising

86 bankrupt firms in 1963 – 1978 from

1933 and 1955

Ang, Chua and

(1977)

11 US railroad firms in bankruptcy* pro-

Warner, Jerold B

ceedings under Bankruptcy Act between

Sample Size

Author(s)

Table 1. Summary of Empirical Studies on Financial Distress, Bankruptcy and Liquidation Cost

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

uity, 3.1% of the book value of debt plus
the market value of equity and 2.8% of
the book value of total assets

bankruptcy filing to market value of equity, book value of debt plus
market value of equity and book value of total asset all measured at

ingbankruptcywith26 firms fromNYSE

and 73 from the AMEX, 1979 - 1986

The sample consists of 16 bankrupt
trucking firms from 1970 - 1985

(1990)

GuffeyandMoore
(1991)

more likely to experience performance losses than other firms.

*** Financial Distress: A situation where a firm’s cash flow is insufficient to service its current debts.

* Bankruptcy: The court supervised process for breaking and rewriting debt contracts.
** Liquidation: The sale of a firm’s assets and distribution of the proceeds to claimants.

1972 – 1991.

sales growth and median stock returns,

performance firms by testing whether firms with high leverage were

come as proxies of firm performance between normal firms and poor

firms, 1,368 of which were experiencing

poor performance with negative median

High leveraged firms lose 26% market

It compared sales growth, stock returns and changes operating in-

The sample consisted of 46,799 public

(1994)

total assets.

of the five years up to the year of petition.

financial distress.

claimed this finding as an indirect cost of

competitors in industry downturns. They

share compared to their less leveraged

industry is 9.12 % of the book value of

to the book value of assets of the year prior to the petition year for each

Opler and Titman

The average direct cost of the trucking

administrative, professional and minor costs for each firm compared

The direct costs were estimated by dividing the total of legal,

the fiscal year-end prior to the bankruptcy filing

were 20.6% of the market value of eq-

and other professional and administrative fees associated with

The average direct costs of bankruptcy

Findings

Weiss, Lawrence A.

Method(s)
The direct costs of bankruptcy was estimated by dividing all the legal

Sample Size

The sample consists of 99 firms declar-

Author(s)

Continous from Table 1

Wijantini—The Indirect Costs of Financial Distress in Indonesia

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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

The Indirect Costs of
Financial Distress
Explanatory Variables
Figure 1 presents the explanatory
variables of financial distress costs.
The dependent variable in this model
is the indirect costs of financial distress. The total costs of financial distress are defined as the reduction in
value due to a perceived inability to
honor future fixed payments and the
potential for subsequent bankruptcy
proceedings (Branch 2002). The independent variables are grouped according to the construct’s organizational
characteristics, conflicts of interest, and
industry factors. First, the organizational characteristics refer to the inter-

nal characteristics of distressed companies. This construct consists of two
independent variables: size of company and leverage. Second, the conflicts of interest refer to potential problems raised between principals and
agents during the period of distress.
These involve three independent variables: time in distress, capital structure
complexity, and degree of bank loans.
However, size and leverage can also be
proxies for information asymmetry
which has a positive association with
the conflicts of interest. Finally, the
industry factors refer to market conditions which may affect the indirect
cost of financial distress. The variable
is the illiquid market.

Figure 1. Factors Affecting the Indirect Costs of Financial Distress
Organizational
Characteristics

Size
Laverage

Time in
Distress

Complexity of
Capital
Structure

Conflict of
Interest

Degree of
Bank
Loans

Indirect Cost of
Financial Distress

Illiquid
Market

Source: Author’s classification based on various studies.
162

Industry Factors

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Hypotheses Development

H1: Size of a firm is positively related
to the indirect cost of financial
distress

Size of Company and the
Indirect Cost of Financial
Distress

Leverage and the Indirect Cost
of Financial Distress

In theory, small firms have bigger
problems in accessing capital because
of the asymmetric information between
insiders and outsiders. The difficulties
become severe when the likelihood of
liquidation arises. However, managing large firms during the period of
financial distress may be costly since
its more complicated internal organization requires implicit contracts which
may be difficult to enforce during difficult times (Noveas and Zingales
1995).
Financial distress theory suggests
that conflicts of interest positively affect the extent of costs. Bigger size
may represent higher level and more
complex conflicts of interest, making
it more difficult for claimants to agree
over resolving the distress. Complexity also relates to the time spent in
financial distress. The costs increase
with time because the value of firms
declines as claimants expend resources
arguing over a fair resolution of the
distress (Helwege 1996; Andrade and
Kaplan 1998). Moreover, bigger companies may positively relate to bigger
bank loans received by distressed firms.
The number of bank creditors is also
more likely to increase with the amount
of loans. Given the possibility of higher
conflicts in distress resolution as the
number of creditors increases, the following hypothesis is tested:

In arguments which began with
the seminal work of Modigliani and
Miller (1958, 1963), it is specifically
expected that financial distress costs
prevent firms from using high leverage. The reason behind this is that
capital providers of higher-leverage
firms will increase their required rates
of return due to the higher expected
cost of financial distress. The trade-off
between expected distress costs and
expected tax shield benefits yields an
internal solution for optimal capital
structure.
Opler and Titman (1994) give
evidence that there is a positive relationship between financing structure
and firm performance in industry downturns. They reveal that more highly
leveraged firms tend to lose market
share and experience lower operating
profits than do their competitors in
industry downturns. This indirectly
suggests a positive relationship between leverage and lost market shares
since one of the measurements of financial distress costs is by calculating
the changes in corporate performance.
Prior studies applied changes in sales,
investment, and operating income from
the year before the onset of distress to
the resolution year as the measures of
the costs of financial distress (Altman
1984; Chen and Marville 1999;
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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Andrade and Kaplan 1998, among others).
Managers estimating the expected
costs of financial distress believe that
higher leverage leads to a higher probability of distress, and may positively
influence costs. In Miller and
Modigliani’s influential model, leverage is recognized as a proxy for distress cost. However, it is unclear
whether the leverage itself directly affects the realized distress costs or this
is endogenous to agency problems.
Higher leverage may correlate to time
in distress, capital structure complexity, and the ease of restructuring. In
other words, higher leverage may increase the conflicts between claimants
and affect the indirect cost of financial
distress. This leads to the second hypothesis to be tested.
H2: There is a positive relationship
between leverage and the indirect
cost of financial distress

Capital Structure Complexity
and the Indirect Cost of
Financial Distress
In financial distress theory, it is
the bargaining problem which mainly
creates inefficiency. As a firm’s capital structure attracts more securities
and becomes more complex, it adds
problems owing to higher conflicts of
interest and agency problems. Bulow
and Shoven’s model (1978) explains
the potential conflicts of interest among
various claimants. The complexity of
claimants makes it more difficult for
distressed firms to agree on restructur164

ing values. Stone (1977) suggests that
the complexity of the financial structure, such as the number of issues and
nature of claims, may explain bankruptcy costs. Bargaining opportunities are expected to slow down the
restructuring process as the number
and types of claimants involved increase. Furthermore, Modigliani and
Miller’s seminal works reveal that the
conflicts of interest and free-rider problems are factors related to firms’ borrowing ratios. They suggest that higher
leverage leads to higher agency costs
on account of holdout problems. Holdout problems are associated with the
higher number and more complicated
types of creditors.
Most publicly listed companies in
Indonesia utilize bank loans extensively, and rely less on capital markets
in funding their capital. Previous studies commonly used the number of securities as the proxy for capital complexity. Since this proxy may not apply to Indonesian sample, we apply the
number of different creditors as the
proxy for the complexity of capital
structure. Thus, we expect that the
number of bank lenders increases with
conflicts of interest and accordingly
with the indirect cost of financial distress.
Moreover, one specific factor
which may affect the costs of financial
distress is the condition of banks that
lend out money at the onset of distress.
If the main bank is faced with serious
problems of liquidity and subsequently
liquidated, taken over, or merged with
another bank, it may affect the rela-

Wijantini—The Indirect Costs of Financial Distress in Indonesia

tionship between debtor and lender,
leading to higher indirect cost of financial distress. The following hypothesis
will examine the association between
the number of bank lenders and the
indirect cost of financial distress.
H3: There is a positive relationship
between the number of banks lending to a distressed firm and the
indirect cost of financial distress.

The Degree of Bank Debt
Reliance
Gilson, John, and Lang (1990)
find that firms with greater reliance on
bank debt are more likely to resolve
financial distress through out-of-court
resolution. They also suggest that these
firms restructure sooner (11 months)
than do those which restructure under
formal bankruptcy (21 months). They
suggest that banks lead their clients out
of default more quickly, meaning that
the presence of bank debt improves a
firm’s ability to restructure. Andrade
and Kaplan (1998) included a variable
which measures the ratio of debt, and
their findings support Gilson, John and
Lang’s (1990) result. Their cross-sectional results indicate that a greater
fraction of bank debt reduces the costs
of financial distress by 10 percent significance. However, two other proxies, the presence of public junk bonds
and a buyout sponsor, have no effect
on the costs of financial distress. In a
study analyzing junk bond defaults,
Helwege (1999) finds a contradictory
result, which is the greater the fraction
of debt owed to banks, the slower the
renegotiation process.

Under easier bargaining conditions, distressed firms may resolve their
problems quicker; hence, ease of restructuring correlates with time in distress. Previous studies suggest that time
in distress has a positive association
with the costs of financial distress. The
basic argument is that time in distress
relates to the costs of financial distress
because the claimants might expend
the firm’s resources over time. The
quicker the problems of a distressed
firm are resolved, the better will be the
value of the firm. Similar theory suggests that bargaining and coordination
problems may slow down the restructuring process (Giammarino 1989;
Gertner and Scharfstein 1991, among
others). Moreover, negotiations may
also be more difficult when there are
wider information asymmetries among
the claimants.
Jensen (1991) argues that the costs
of financial distress have a positive
relationship with the length of time in
distress. Jensen points out that some
bankruptcy resolutions may help distressed firms to accelerate their distress resolution, for instance, offering
pre-packaged bankruptcies or a facilitator in exchange offer. However,
Haugen and Senbet (1978) argue that
under a well-functioning market, with
a large number of buyers, price-takers
and rational sellers and creditors, claimants’ bargains are nearly costless in a
competitive market; therefore, the overall firm value is not affected. If distressed firms fail to repay their scheduled debts, they may avoid the costs of
financial distress by “switching” the
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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

ownership from equity-holders to debtholders or conducting a merger with
another firm. In order to avoid problems from market impediments, they
suggest that the firms make simple
provisions to incorporate charters and
bond indentures when they issue debt
capital.
Andrade and Kaplan (1998) support Haugen’s idea, and claim that
there is no association between time in
distress and the costs of financial distress. However, they provide details of
the period of distress for their sample,
and report the average time in distress
of 44 months, measured from the beginning of the year of distress onset to
the month of distress resolution, varying from 24 months to more than 60
months. Helwege (1999) also shows
no significant effect of firm value or
lost growth opportunities on the time
in default. She mentions that this reflects the lack of a clear relationship
between time-in-default and decreases
in firm value as one of the measurements of financial distress costs.
In an early study of bankruptcy
cost, Warner (1977) reports no relationship between the length of time
spent in bankruptcy proceedings and
firm value. Hence, high-market-value
firms do not incur higher costs of bankruptcy than do low-market-value firms
simply because they stay longer in
distress. His research does not directly
examine the relationship between time
in distress and the costs of financial
distress. Several studies present evidence of how long bond defaults or
bankruptcy cases last. Altman and
166

Eberhart (1994) and Betker (1998) report that time in default is generally
between two and two-and-a-half years.
Altman (1993) and Hotchkiss (1995)
estimate the time range of 1.5-2.5 years.
Gilson, John, and Lang (1990) suggest
that firms with more bank debt, less
complex classes of debt, and fewer
tangible assets tend to conduct private
workouts. They estimate that the median of informal resolution is only 11
months, compared to the median of
formal restructuring of 21 months. In
contrast, Helwege (1999) reports that
bank debt is associated with slower
restructuring. This is consistent with
Asquith, Gertner, and Scharfstein‘s
(1994) view that banks do not facilitate
the resolution process, and even appear to slow down renegotiations. Her
analysis shows that firm size, lawsuits,
and the presence of contingent claims
are significant factors lengthening the
default time.
Moreover, Gilson, John, and Lang
(1990) suggest that the costs of financial distress of firms which restructure
privately are lower than those of firms
which file under bankruptcy chapters
in the USA. Under private renegotiation, the distressed firms significantly
reduce legal fees because the procedural demand and legal complexity in
bankruptcy processes increase legal
costs. They also show that shareholders are systematically better off when
the debt is restructured privately.
Hoshi et al. (1990) show that financial distress is costly for firms where
significant conflicts among creditors
are likely. The closed financial links in

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Japanese main-bank relationships may
reduce the costs of financial distress.
In addition, by taking a sample of
highly leveraged transaction firms in
the U.S., Andrade and Kaplan (1998)
provide evidence that a greater fraction of bank debt reduces costs. Their
study suggests that a higher proportion
of bank debt improves a firm’s ability
to renegotiate or restructure. The problems are especially severe for firms
that issue publicly traded bonds. In the
U.S., the financial markets offer stronger market structures than do those in
Indonesia. Hence, without systemic
crisis and more sophisticated capital
markets, U.S. firms have more choices
in resolving their financing problems.
Even though the Indonesian distressed firms prefer to resolve privately,
this is not associated with higher reliance on bank debt as it is in the U.S.
Rajan and Zingales (1998) suggest that
firms in less developed markets are
more likely to rely on bank loans as the
main source of funding. Referring to
current judicial systems in Indonesia,
the informal mechanism will not work
properly unless there is an easy resort
to the court should there be a breakdown in negotiations (Tomasic 2001).
Without the legal threat, firms are less
likely to resolve promptly. Therefore,
higher reliance on bank debt may not
reduce the time or the costs of distress.
Further, the Asian systemic crisis also
affects the banking industry, and the
banks have also encountered distress
problems. This condition leads to an
additional issue: resolving corporate
distress due to banks’ collapses. A

higher degree of bank reliance may be
positively associated with the number
of bank creditors; hence, it may increase conflicts among banks. Given
the issues above, the following hypothesis is tested.
H4: There is a positive relationship
between the degree of bank debt
reliance in distressed firms and
the indirect cost of financial distress

Industry Performance and the
Indirect Cost of Financial
Distress
There are debates over bankruptcy
law reform regarding the time allowed
for selling the assets of distressed firms.
Some scholars argue that insolvent
firms should be forced into immediate
cash liquidation (Baird 1986). This
may refer to U.K. bankruptcy law, of
which some studies point out premature liquidation as one of the disadvantages. Nevertheless, others object to
this contention, arguing that premature liquidation may fail to maximize
the proceeds for the liquidating
claimholders (Aghion and Bolton
1992). They argue that problems associated with raising capital and the lack
of competition for distressed firms’
assets will lead the liquidating firms to
dispose of assets at a discount.
Shleifer and Vishny (1992) consider the scenario where a firm responds to financial distress by selling
assets. They identify three factors determining the market liquidity of the
firm’s assets. The first is the number of
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potential buyers in the market; the second is the characteristics of the assets
being sold. If the assets are industryspecific, an inside buyer is likely to
value the assets more highly than an
outsider. However, even if the inside
buyer is more likely a higher bidder,
the selling firm may sell the assets to an
outsider when the industry itself is in
trouble. When firms encounter trouble
in repaying debts, and attempt to sell
their assets, the highest valuation of
these assets are likely given by other
firms in the same industry. The third is
the financial condition of the industry.
If the industry where the firm operates
is distressed, it will affect the liquidity
of the assets; a poor financial condition
in an industry will increase the liquidity premium of assets. The premium
may be reduced if the assets are used in
other industries. However, the industry outsiders who may not know how
to manage them will encounter agency
costs of hiring specialists to run the
assets, and fear for overpayment since
they have no knowledge of the assets’
values. When there is no industry buyer
to buy the assets, and the only buyers
are industry-outsiders, they will charge
significant fees for managing and acquiring the assets. Consequently, the
prices of the assets will be depressed.
This type of cost can be classified
under the indirect cost of financial
distress. Thus, the total costs of financial distress are likely to be higher
among firms with illiquid assets.
Among empirical studies, Kruse
(2002) supports Shleifer and Vishny’s
(1992) asset liquidity model that the
168

prices which distressed firms receive
for their assets are based on industry
conditions. In particular, the distressed
firm is forced to sell assets for less than
their full values to industry outsiders
when other firms in the same industry
are also experiencing difficulties. He
conducted his analysis by applying the
logistic regressions of the probability
of assets sales by poorly performing
firms. The study controlled other factors which were previously identified
to be related with the probability of
assets sales by poorly performing firms.
The study defined distressed firms as
firms suffering from a dramatic decline in operating performance. The
findings confirm a positive relation
between an industry’s growth rate and
the likelihood of assets sales by firms
in this industry. In addition, the results
indicate that firms operating in fastergrowing industries are receiving the
reservation prices for their assets.
Pulvino (1998) also agrees with
the model of Shleifer and Vishny
(1992) that discount assets are sold in
depressed industries where the assets
are industry-specific. He used commercial aircraft transactions to test the
relationship, and finds that financially
constrained airlines liquidate aircrafts
at discount to fundamental values, and
are more likely to sell used aircrafts to
industry outsiders. Moreover, airlines
with high spare debt capacity tend to
buy more used aircrafts than do airlines with low spare debt capacity,
particularly when aircraft prices are
depressed. In addition, Pulvino also
supports Vishny and Schleifer’s model

Wijantini—The Indirect Costs of Financial Distress in Indonesia

that the prices which sellers accept for
their assets depend on the costs of
raising capital. Airlines with high leverage ratios and low current ratios
receive lower prices for their assets
than do more conservatively financed
airlines. This indicates that buyers consider a higher discount rate for riskier
assets.
Brown (2000) also finds similar
evidence from Real Estate Investment
Trusts (REITs). His study shows asset
illiquidity in an industry downturn and
significant financial distress costs for
highly leveraged firms during the
downturn. Moreover, owner-manager
entities may be particularly large because lenders’ incentives to reorganize to avoid a foreclosure sale in a
depressed market are limited. Kim
(1998) measures asset liquidity in the
contract drill industry by focusing on
the depth of buyers’ market and trading volumes, and finds that the characteristics of assets matter. He claims
that drilling rigs are less liquid than oilwells. Moreover, his study also indicates that managers generally sell liquid assets before illiquid ones.
When firms have difficulties meeting debt repayments and sell assets or
are liquidated, the highest valuation of
these assets is likely given by other
firms in the industry. However, these
firms are likely to have troubles meeting their debt payments when the assets are put up for sale, for this is when
the shock causing the seller’s distress
is industry-or economy-wide. When
systemic crisis attacks the East Asian
countries, the industry buyers are un-

likely to be able to raise funds for
buying the distressed assets. If the industry buyers cannot buy the assets
and industry outsiders encounter significant costs of acquiring and managing the assets, the assets in liquidation
will be sold at depressed prices. The
poor financial condition of an industry
will increase the liquidity premium in
such sales. Although the premium may
be reduced when the assets are usable
in other industries, asset-restructuring
costs are likely to be high if the market
for used assets is illiquid. The following hypothesis will then be tested:
H5: There is a negative relationship
between industry performance and
indirect cost of financial distress

Sample Description
Identifying Financially
Distressed Firms
To be included in the sample, firms
must satisfy several criteria. Panel A in
Table 2 describes the screening procedures used to collect the financial distress sample firms. First, they had an
interest coverage ratio of between 0
and 1 for at least one year between
1997 and 2002. The interest coverage
ratio was calculated from Datastream
by dividing operating profit before interest expense, income taxes, depreciation and amortization by interest
charges. In this case, the interest charges
(Datastream code number: 2408) represent the aggregate value of interest
paid less interest received. The sample
contains non-financial firms only, and
169

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Table 2. Sample Selection
Panel A:
Sample Selection Process
Public listed firms in Jakarta Stock
Exchange in 1997-2002

n

Year

Onset Distress

%

1997

7

24.2

1998

16

55.2

1999

3

10.4

2000

3

10.4

2001

0

0

2002

0

0

Total

29

100.00

311

Firms in financial or insurance industries (42)
Firms with interest coverage (EBITDA/
Interest) not between 0 and 1
(229)
Firms with an incomplete or missing
series of annual reports due to lack
of data or being private

Panel B:
Sample Distribution by Year

(5)

Firms without auditor confirmation
of debt renegotiation

(6)

Total firms remaining in sample

29

40 firms meet this criterion. Other reasons, for instance, incomplete data or a
missing series of annual reports (one
firm) and four firms in the sample
going private in the year before the
onset of distress, reduce the number of
firms in the sample to 35. The onset
year is the year when firms for the first
time have an interest coverage ratio of
between 0 and 1, and conduct debt
restructuring (Wijantini 2006).
An interest coverage ratio of between 0 and 1 does not mean that firms
will necessary become financially distressed, which is having difficulties
fulfilling the covenants in their debt
contracts. Debt payment can be made
from other sources than operating income for firms have many options to
obtain cash needed to avoid default,
including utilizing cash reserves, reducing inventory levels, extending
trade creditors, drawing upon bank

lines of credit, restructuring debt payments prior to default, raising equity,
and selling assets (Whitaker 1999).
Therefore, the following additional
criteria should be considered to determine the onset of distress. The auditor
disclosure in the notes to financial statements must indicate that the firms are
negotiating with their creditors to restructure their debts in order to avoid a
default. Debt restructuring is defined
as an exchange of financial claims
which a firm makes to avoid defaulting
on its debt, including exchanges such
as maturity extensions (Gilson 1990).
After this screening, six firms were not
supported by restructuring news, and
the remaining sample contains 29 financially distressed firms.
Panel B of Table 2 offers sample
distribution annually. Most of the firms
(16) plunged into financial distress for
the first time in 1998 (55.2 percent).

170

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Seven firms renegotiated their loans
with their creditors in 1997, and the
remaining firms in the sample rescheduled their debts for the first time in
1999 and 2000.

Research Design
All hypotheses are examined by
regressing an estimate of the indirect
cost of financial distress (CFD) on size
(SIZE), leverage (LEV), industry performance (DLOW), number of creditors (COMPLEX), and bank debt reliance (BANK). Due to data availability, this paper does not apply time in
distress variable as a proxy for conflicts of interest. The following regression equation is applied:
CFDt = 0 +  1 LSIZEt + 2 LEVt +
3 COMPLEXt +
4 BANKt +
5 DLOWt + t
Each firm’s estimated indirect cost
of financial distress (CFDt) is calculated from the changes in operating
and sales performances. The procedure used to measure this variable is
described later. SIZEt is the market
value of outstanding total capital at the
onset of distress as a proxy for company size. The log value of SIZEt
(LSIZE) is included in the analysis
because the association between SIZE
and CFDt was previously identified as
t
a non-linear relationship. LEVt is the
ratio of total debt to total capital at the
onset of distress. DLOWt is 1 if the

industry’s return on sales is in the low
quartile (below 25th percentile) over
the period when indirect cost of financial distress is calculated, 0 otherwise.
The industry’s return is equal-weighted
returns to firms in the same industry
over the period when the indirect cost
of financial distress is calculated.
COMPLEXt is the number of firm’s
creditors at the onset of distress. BANKt
is the portion of bank loans to total debt
at the onset of distress.

Measuring the Indirect Costs of
Financial Distress
To measure the indirect cost of
financial distress, this study applies
changes in operating profit and sales,
adjusted to industry from a year before
the onset of distress year to the year of
resolution (Opler and Titman 1994;
Andrade and Kaplan 1998). After conducting data collection, we find that
some firms were still in distress at the
end of 2002. These firms had their
costs measured by annualizing the
changes in operating profit and sales
from a year before the onset of distress
to the end of 2002. The main reason
that this study includes such firms is to
increase the number of firms in the
sample. We present their cost estimations separately in different categories.
The above approach refers to the
seminal works of Miller and
Modigliani, illustrating that company
value may decrease accordingly when
there is a higher possibility of financial
distress. In their model, higher leverage causes a higher probability of fi171

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

nancial distress. Value in a year before
the onset of distress represents the true
value while value at the distress resolution represents the reduction due to
financial distress.
If the value at the end of distress
resolution is less than the value one
year before the onset of distress, it
reflects the extent of financial distress
costs, which refer to the drop in value
due to the financial distress. It may
also represent the indirect cost of financial distress which we believe to be
the biggest portion of financial distress
costs since the predicted direct cost of
financial distress in Indonesia is very
low.
Furthermore, the costs were estimated by industry-adjusted operating
profit and sales, with the following
procedures. First, the changes in each
firm’s performance were computed.
Then the changes in the median industry firms’ performance for all firms in
the same industry were calculated for
each year for each firm in the sample,
and this number was then subtracted
from the changes in performance. For
those firms having a resolution year,
the annualized changes were from a
year before the onset of distress year to
the resolution year, while for those
firms that were still in distress, the
average changes from a year before the
onset of distress year to the end of 2002
were calculated.
We try to estimate the changes in
value of financially distressed firms by
applying the comparable company
method (Kaplan and Ruback 1995).
However, the bias in the results makes
172

the approach untrustworthy. For instance, for those 11 firms which had an
exit year, the median (mean) estimated
costs of financial distress were 0.8
(14.8) with a standard deviation of
27.8. Under turbulent conditions, the
comparable company’s approach may
lack precision due to future uncertainty in the company and industry.
Hence, we do not report the results of
the estimation.

Results and Discussion
To interpret the results of the costs
estimation, three assumptions are required (Andrade and Kaplan 1998).
First, it assumes that a change is permanent and translated into a permanent drop in firm performance. Second, for firms having a distress resolution year, it assumes that the study has
accurately identified the start and end
years of the distress. For the firms
which were still in distress in 2002, the
estimate may understate the costs, since
the firms’ operating profits may deteriorate further. Finally, the study attempts to capture firms which suffered
from financial distress through sample
screening, even though it is very difficult to purify the screening from economic shock.
Table 3 presents the annualized
estimation of financial distress costs in
Indonesia. The results are presented in
five categories based on the year in
distress. Panel A presents eight companies which were financially distressed in 1997 and 1998, and resolved
their debt renegotiation by 2002. The

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Table 3. The Estimated Indirect Costs of Financial Distress
Panel A:Firms which were financially distressed in 1997 and 1998 and exited from the distress
by 2002
The Indirect Costs of Financial Distress (CFDop) are estimated by annualised changes of industry adjusted operating profit
(EBITDA/Total Sales) from a year before the onset of distress to the exit year. CFDs are estimated by annualised changes
of industry-adjusted sales from a year before the onset of distress to the exit year. Negative (positive) signs indicate lower
(higher) adjusted performance at the exit year, therefore showing the costs (value creation) estimation.

No.

Company

1
2
3
4
5
6
7
8

Astra Graphia
Charoen Pokphand
Fast Food Indonesia
Kedawung Setia Ind’l
Lionmesh Prima
Modern Photo Film
Prima Alloy Steel
Semen Cibinong

Industry Classification Onset
(Datastream)
Distress
Year

Exit
CFDop
Distress
Year

CFDs

Diversified Industry
Farming and Fishing
Food Processing
Household Products
Building Materials
Photography
Autoparts
Building Materials
MEAN
MEDIAN
QUARTILE 1
QUARTILE 3
ST. DEVIATION
N

2000
2000
2002
2000
2002
2001
2000
2001

-0.29
-0.53
0.20
-0.22
-0.05
0.03
-0.07
0.19
-0.09
-0.06
-0.24
0.07
0.25
8

1998
1998
1998
1997
1998
1998
1997
1998

-0.10
-0.13
-0.02
-0.04
-0.04
0.00
-0.03
-0.31
-0.08
-0.04
-0.11
-0.03
0.10
8

Panel B:Firms which were financially distressed in 1997 and 1998, exited from the distress
during 1998-2002 and became financially distressed again by 2002
No.

Company

Industry Classification
(Datastream)

Second Onset
Distress Year

1

Kedawung Setia Ind’l

Household Products

2001

173

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Continued from Table 3
Panel C: Firms which were in financial distress in 1997 and 1998 but still in financial distress
by 2002
The industry-adjusted performance is calculated as follows. First, the median change each performance of all firms in the
same industry was calculated for each year for each firm in the sample. Then this number was subtracted from the change
each firm’s performance. The Indirect Costs of Financial Distress (CFDop) were estimated by annualised changes of
industry-adjusted operating profit (EBITDA/Total Sales) from a year before the onset of distress to 2002. CFDs are measured
by annualised industry adjusted sales changes from a year before the onset of distress to 2002. Sales data for 2002 are directly
collected from hardcopies of the annual report while EBITDA data sources are from Datastream. Negative (positive) signs
indicate lower (higher) adjusted performance at the exit year, therefore showing the costs (value creation) estimation.

No.

Company

Industry Classification
(Datastream)

Onset
Distress
Year

CFDop

CFDs

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Apac Citra
Argha Karya Prima
Davomas Abadi
Dharmala Intiland
Indomobil Sukses
Intraco Penta
Panasia Indosyntex
Primarindo Asia
Surabaya Agung
Surya Hidup Satwa
Surya Semesta
Texmaco Jaya
Trias Sentosa Tbk
United Tractors
Zebra Nusantara

Textiles and Leather
Chemical. Adv. Materials
Food Processors
Real Estate Development
Automobile
Retailers. Multidept
Textiles and Leather
Clothing and Footwear
Paper
Farming and Fishing
Building Materials
Textiles and Leather Goods
Chemical. Adv. Materials
Commercial Vehicles
Railroads, freight

1997
1998
1998
1998
1997
1998
1997
1998
1998
1998
1998
1997
1998
1997
1998

0.02
-0.04
-0.03
-0.23
-0.01
0.00
-0.04
0.01
-0.17
-0.09
-0.41
-0.03
0.04
n/a
-0.01

0.68
-0.12
-0.20
n/a
-0.18
0.02
-0.03
-0.04
-0.04
-1.12
-0.26
-0.32
-0.48
n/a
-0.09

-0.07
-0.03
-0.08
0.00
0.12
14

-0.17
-0.12
-0.26
-0.04
0.39
13

MEAN
MEDIAN
QUARTILE 1
QUARTILE 3
ST. DEVIATION
N
n/a = data are not available

174

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Continued from Table 3
Panel D. Firms which were financially healthy in 1998 but became financially distressed during
1999-2002
The Indirect Costs of Financial Distress (CFDop) are estimated by average changes of the adjusted industry EBITDA / Total
Sales changes from a year before the onset of distress to 2002. CFDs are estimated by average changes of the adjusted
inflation and industry sales changes from a year before the onset of distress to 2002. Negative (positive) signs indicate the
lower (higher) adjusted performance at the exit year, therefore showing the costs (value creation) estimation.

No.

Company

Industry Classification
(Datastream)

Onset
Distress
Year

CFDop

CFDs

1
2
3

Keramika Indonesia
Multi Agro Persada
Sunson Textile

Building Materials
Electronic Equipment
Clothing and Footwear

1999
1999
2000

-0.34
0.06
0.06

-0.14
1.99
0.02

Panel E. Firms which were financially healthy in 1997 and 1998 but became financially
distressed during 1999-2002 and exited from the distress by 2002
The Indirect Costs of Financial Distress (CFDop) are estimated by annualised changes of industry adjusted operating profit
(EBITDA/Total Sales) from a year before the onset of distress to the exit year. CFDs are estimated by annualised changes
of industry-adjusted sales from a year before the onset of distress to the exit year. Negative (positive) signs indicate the lower
(higher) adjusted performance at the exit year; therefore showing the costs (value creation) estimation.

No.

Company

1
2
3

Intikeramik Alamsari
Nipress Tbk
Pioneerindo Gourmet

Industry Classification Onset
Exit
(Datastream)
Distress Distress CFDop CFDs
Year
Year
Building Materials
Electrical Equip.
Hotels and Catering

1999
2000
2000

2001
2001
2002

0.10
0.03
-0.07

-0.07
-0.36
-1.20

175

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Continued from Table 3
Panel F: The Indirect Costs of Financial Distress: Firms with an exit year and Firms
still in distress in 2002
For firms with an exit year, the indirect costs of financial distress (CFDop) are estimated by changes of industry-adjusted
operating profit (EBITDA/Total Sales) from the onset of distress year to the exit year. CFDs are estimated by annualized
changes of industry-adjusted sales from the onset of distress year to the exit year. For firms still in distress by 2002. CFDop*
is estimated by annualized changes of the adjusted industry EBITDA / Total Sales from a year before the onset of distress
to 2002. CFDs* are estimated by annualized changes of the adjusted industry sales from a year before the onset of distress
to 2002. Negative (positive) signs indicate the lower (higher) adjusted performance at the exit year, therefore showing the
costs (value creation) estimation.

Firms with the exit year

Firms still in distress in 2002

Name of Company

CFDop

CFDs Name of Company

CFDop* CFDs*

Astra Graphia
Charoen Pokphand
Fast Food Indonesia
Kedawung Setia Ind’l
Lionmesh Prima
Modern Photo Film
Prima Alloy Steel
Semen Cibinong
Intikeramik Alamsari
Nipress Tbk
Pioneerindo Gourmet

-0.10
-0.13
-0.02
-0.04
-0.04
0.00
-0.03
-0.31
0.10
0.03
-0.07

-0.29
-0.53
0.20
-0.22
-0.05
0.03
-0.07
0.19
-0.07
-0.36
-1.20

Apac Citra
Argha Karya Prima
Davomas Abadi
Dharmala Intiland
Indomobil Sukses
Intraco Penta
Panasia Indosyntex
Primarindo Asia
Surabaya Agung
Surya Hidup Satwa
Surya Semesta
Texmaco Jaya
Trias Sentosa Tbk
Zebra Nusantara
Keramika Indonesia
Multi Agro Persada Tbk
Sunson Textile

0.02
-0.04
-0.03
-0.23
-0.01
0.00
-0.04
0.01
-0.17
-0.09
-0.41
-0.03
0.04
-0.01
-0.34
0.06
0.06

0.68
-0.12
-0.20
n/a
-0.18
0.02
-0.03
-0.04
-0.04
-1.12
-0.26
-0.32
-0.48
-0.09
-0.14
1.99
0.02

MEAN
MEDIAN
QUARTILE 1
QUARTILE 3
ST. DEVIATION
N

-0.06
-0.04
-0.09
-0.01
0.10
11

-0.22
-0.07
-0.33
-0.01
0.40
11

MEAN
MEDIAN
QUARTILE 1
QUARTILE 3
ST. DEVIATION
N

-0.07
-0.03
-0.09
0.01
0.14
17

-0.02
-0.11
-0.22
-0.02
0.64
16

176

Wijantini—The Indirect Costs of Financial Distress in Indonesia

Table 4. Descriptive Statistics and Pearson [Spearman] Correlation Coefficients for Variables
In panel A, CFDop is the indirect costs of financial distress estimated by measuring annualized changes of operating profit
from the onset of distress to the resolution year for 11 firms and annualized industry-adjusted changes of operating profit
from the onset of distress to 2002 for 17 firms. In panel B, CFDs are estimated indirect costs of financial distress by measuring
annualized industry-adjusted changes of sales from the onset of distress to the resolution year for 11 firms and annualized
industry adjusted changes of sales from the onset of distress to 2002 for 16 firms. LEV is the ratio of total debt to total capital
at the onset of distress. COMPLEX is the number of the firm’s creditors at the onset of distress. BANK is the portion of bank
loan to total debt at the onset of distress. DLOW is 1 if the industry return was in the low quartile (below 25th percentile) over
the period when costs of financial distress are calculated, 0 otherwise. Industry performance is equal-weighted return to firms
in the same industry over the period when costs of financial distress are calculated. LSIZE is the log value of market value
of outstanding total capital at the onset of distress. Spearman coefficients are in parentheses.
* Significant at the 10 percent level; ** Significant at the 5 percent level; *** Significant at the 1 percent level

Panel A: CFD is estimated with Operating Profit Approach
Item

CFDop

LEV

COMPLEX

BANK

DLOW

LSIZE

CFDop

1.000
[1.000]

LEV

0.332*
[0.381**]

1.000
[1.000]

COMPLEX

0.341*
[0.348*]

0.131
[0.337*]

1.000
[1.000]

BANK

-0.113
[-0.255]

0.103
[0.110]

0.221
[0.172]

1.000
[1.000]

DLOW

0.429**
[0.211]

0.189
[0.039]

-0.146
[-0.162]

0.016
[0.034]

1.000
[1.000]

LSIZE

0.346*
[0.346*]

0.088
[0.376**]

0.601***
[0.616***]

0.154
[0.122]

-0.124
[-0.088]

1.000
[1.000]

Mean
St. Dev

-0.065
0.123

0.808
0.170

12.679
9.051

0.660
0.240

0.285
0.460

20.142
1.405

177

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Continued from Table 4
Panel B: CFD is estimated with Sales Approach
Item

CFDop

LEV

COMPLEX

CFDs

1.000
[1.000]

LEV

0.087
[0.126]

1.000
[1.000]

AFFILI

-0.134
[-0.086]

-0.377*
[-0.306]

COMPLEX

0.347*
[0.133]

0.112
[0.307]

1.000
[1.000]

BANK

-0.034
[-0.105]

0.070
[0.083]

0.197
[0.146]

1.000
[1.000]

DLOW

0.351*
[0.212]

0.151
[0.000]

-0.199
[-0.229]

-0.058
[-0.038]

1.000
[1.000]

LSIZE

0.123
[0.092]

0.066
[0.357*]

0.592***
[0.601***]

0.124
[0.093]

-0.180
[-0.174]

1.000
[1.000]

Mean

0.099

0.803

12.44

0.650

0.259

20.103

St. Dev

0.554

0.171

9.137

0.238

0.446

1.415

operating profit and sales approach
provides results that show a median
(mean) of the costs of between four
percent (eight percent) and six percent
(nine percent). We thoroughly checked
them in the years after their exit year
until the end of year 2002 whether the
companies renegotiated their restructured loans. Panel B shows that one
company (Kedawung Setia Industrial)
failed to fulfill its debt agreement, and
renegotiated with its creditors for a
second time. The next category (Panel
C) lists firms which were in financial
distress in 1997 and 1998, and were
identified to be still in distress in 2002.
For these firms, we calculated the annualized changes in each firm’s performance from a year before the onset
of distress to the end of 2002. The sales
178

BANK

DLOW

LSIZE

approach estimates higher annualized
costs of financial distress, with a median (mean) of 12 percent (17 percent),
than operating profit estimation, with a
median (mean) of three percent (seven
percent). Panel D and E mainly classify firms which were financially
healthy before 1998, and became distressed after 1998. Finally, in Panel F,
we summarize all cost estimation into
two major categories: firms which had
a resolution year and firms which were
still in distress in 2002. The overall
results of the operating profit approach
indicates that the median (mean) values of indirect financial distress cost
measured by the annualized drop in
industry-adjusted EBITDA/Sales are
between three percent (six percent)
and four percent (seven percent) annu-

Wijantini—The Indirect Costs of Financial Distress in Indonesia

ally. The sales approach shows a wider
range of the costs estimation with a
standard deviation of more than 40
percent; the median (mean) values of
the costs are between seven percent
(two percent) and 11 percent (22 percent) per year.
Panels A and B of Table 4 present
Pearson and Spearman’s Rho correlation coefficients. Both operating profit
and sales approach confirm that the
indirect cost of financial distress is
positively correlated with COMPLEX.
It supports the fifth hypothesis that a
higher number of creditors may cause
higher conflicts of interest in restructuring problem loans. Accordingly, this
may raise the indirect cost of financial
distress. Furthermore, the panels also
show that poor industry performance
(DLOW) has an effect on the costs.
Low industry performance during the
time of distress positively contributes
to the costs. The result supports Shleifer
and Vishny’s (1992) prediction that
the costs of financial distress may be
higher if the firm’s industry performs
poorly. Moreover, both panels also
show a significant correlation between
size of company (LSIZE) and the number of creditors (COMPLEX). Greater
size is positively associated with the
number of bank lenders. The high association between them may cause a
multicollinearity problem in regression results. Thomas (1997) is concerned that the multicollinearity will
present larger standard errors, and
hence the estimation results will lack
precision. However, unless the
multicollinearity is perfect, there is no

violation against the classical assumptions. Even with a high degree of
multicollinearity, the Ordinary Least
Square estimators retain unbiased estimates.
Table 5 presents the results of
both full and simple regressions on
each determinant of the indirect cost of
financial distress. Regression (1) shows
that poor industry performance
(DLOW) significantly affects the costs
with a p-value of 0.0077. However, the
evidence presented here must be carefully assessed along with its limitations. For instance, regression specification tests (RESET) indicate that the
equation has been misspecified in some
way or other (Thomas 1997). Regression (2) and (3) present no significant
evidence that size, leverage, complexity of capital structure, degree of bank
loans, and industry performance affect
the estimated indirect cost of financial
distress.
In simple regressions analysis presented in Regressions (4) to (8), they
demonstrate supports for most of the
hypotheses. Regression (4) shows that
the cost has a positive relationship
with the size of firms (p-value=0.07).
Meanwhile, Regression (5) supports
the view that higher leverage positively affects the costs with pvalue=0.08. Regression (6) substantiates the financial distress theory about
the existence of conflicts of interest in
distress resolution which may increase
the costs of financial distress. The association between the number of creditors, as a proxy for higher conflicts,
and the costs is positive and significant
179

Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

Table 5. Regressions of the Indirect Costs of Financial Distress on Firm
Characteristics
All regressions except Regression (2) and (3) apply the indirect cost of financial distress (CFD) measured as changes of
industry adjusted operating profit on firm characteristics. Regressions (2) and (3) apply the CFD measured as changes of
industry adjusted sales on firm characteristics for full samples. All regressions except Regressions (2) and (3) consist of 28
financially distressed firms while Regressions (2) and (3) consist of 27 financially distressed firms. LSIZE is log value of
SIZE measured by market value of outstanding total capital at the onset of distress. LEV is the ratio of total debt to total capital
at the onset of distress. COMPLEX is the number of firm’s creditors at the onset of distress. BANK is the portion of bank
loan to total debt at the onset of distress. Dlow is 1 if the industry return was in the low quartile (below 25th percentile) over
the period when costs of financial distress are calculated, 0 otherwise. Industry performance is equal-weighted return to firms
in the same industry over the period that costs of financial distress are calculated. p-values are in parentheses.
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Intercept

-0.508
[0.1423]

0.95745
[0.6117]

-0.217
[0.7025]

-0.550
[0.1044]

-0.130
[0.2498]

0.005
[0.8836]

0.103
[0.1541]

0.032
[0.2198]

LSIZE (+)

0.022
[0.2023]

-0.062
[0.5134]

LEV (+)

0.152
[0.1984]

0.349
[0.5871]

0.343
[0.5881]

COMPLEX (+) 0.004
[0.1617]

0.022
[0.1388]

0.017
[0.1674]

BANK (+)

-0.125
[0.1376]

-0.107
[0.8148]

-0.11
[0.8085]

Dlow (+)

0.125***
[0.0077]

-0.403
[0.1177]

-0.39
[0.1229]

Adj R2

0.39

0.09

0.11

0.120

0.110

0.116

0.012

0.184

F ratio

4.106***
[0.0087]

1.272
[0.3126]

1.518
[0.2313]

3.557*
[0.0705]

3.240*
[0.0834]

3.441*
[0.0750]

0.334
[0.5679]

5.883**
[0.0225]

AR

2.213
[0.1354]

0.39227
[0.6809]

0.62256
[0.5466]

2.119
[0.1420]

0.713
[0.4998]

2.289
[0.1231]

0.253
[0.7779]

0.420
[0.6613]

Normality

3.743

9.996 *** 9.196**

6.527**

9.344***

10.999***

19.331*** 2.294

Chi^2(2)

[0.1539]

[0.0067]

[0.0101]

[0.0382] [0.0093]

[0.0041]

[0.0001]

[0.3176]

Xi^2

2.299*
[0.0899]

0.267
[0.9714]

0.351
[0.9157]

0.958
[0.3984]

0.510
[0.6066]

0.305
[0.7397]

0.412
[0.6665]

33.167***
[0.0000]

RESET

5.345*
[0.0310]

1.157
[0.2947]

0.051
[0.8225]

0.362
[0.5524]

0.860
[0.3624]

0.060
[0.8082]

0.342
[0.5638]

0.030*
[0.0705]
0.241*
[0.0834]
0.004 *
[0.0750]
-0.058
[0.5679]
0.115**
[0.0225]

*** Significant at the 1% level, ** Significant at the 5% level and, * Significant at the 10% level.

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Wijantini—The Indirect Costs of Financial Distress in Indonesia

Table 6. Cross-Sectional Determinants of the Costs of Financial Distress
Panel A: Andrade and Kaplan (1998) Results

Coefficient
St. Errors
Adj. R2
N

Log HLT
Value
(-)

Default

-0.163**
0.068
0.14
30

0.270
0.275

(-)

Time In
Distress
(+)

Log # of
Securities
(-)

Bank Debt/
Total Debt
(+)

Industry
Return
(+)

0.002
0.007
0.01

-0.351**
0.160
0.12

-0.811*
0.474
0.06

-0.324
0.256
-0.00

Panel B: Current Sample Results

Coefficient
St. Errors
Adj. R2
N

LSIZE
(+)

LEV
(+)

COMPLEX
(+)

BANK
(+)

DLOW
(+)

0.030*
0.016
0.12
28

0.241*
0.134
0.11

0.004 *
0.002
0.12

-0.058
0.100
0.01

0.115**
0.047
0.18

* Statistically significant at the 10% level.
**Statistically significant at the 5% level.
*** Statistically significant at the 1% level.
In Andrade and Kaplan’s study (1998), the costs of distress are estimated as the difference between the value of total predistress capital and the total capital realized during distress. Pre-distress figures correspond to the last fiscal year before
distress onset. The estimated pre-distress value of total capital for each company is calculated as [product of median industry
(net capital/ EBITDA) and company EBITDA] plus company cash balances at pre-distress year-end. Industry medians are
based on the universe of firms in the same Value Line industry classification as the company. EBITDA is earnings before
interest, taxes, depreciation and amortization. Value of total capital realized during distress is the present value of all
payments to capital made from distress onset up to resolution (inclusive) discounted back to the pre-distress year. Payments
to capital include cash interest and debt principal repaid, dividends paid, equity repurchased and total value received by
capital at distress resolution, net proceeds from new equity and debt issues. HLT value is the capital value of the HLT when
the HLT is completed. HLT is Highly Leveraged Transactions. Default equals 1 if the firm defaulted on its debt and 0
otherwise. Time In Distress is the number of months between the onset of distress and the resolution of that distress. Number
(#) of securities is the number of different debt and preferred stock securities in the post-HLT capital structure. Bank Debt
to total debt is as measured in the year before financial distress. Industry returns dummy variables equal 1if the industry return
was in the third quartile from the onset of distress until resolution and 0 otherwise. In the present study, the CFD is estimated
as the annualized changes of industry adjusted operating profit from the onset of distress year to the exit year for 11 firms
while for the other 16 firms, the costs are estimated as annualized changes of the adjusted industry operating profit from a
year before the onset of distress to 2002. LSIZE is log value of SIZE measured by market value of outstanding total capital
at onset distress the log value of SIZE is included in the analysis because the association between SIZE and CFD is previously
identified as a nonlinear relationship. LEV is the ratio of total debt to total capital at the onset of distress. COMPLEX is the
number of firm’s creditors at the onset of distress. BANK is the portion of bank loan to total debt at the onset of distress. Dlow
is 1 if the industry return was in the low quartile (below 25th percentile) over the period when costs of financial distress are
calculated, 0 otherwise. Industry performance is equal-weighted return to firms in the same industry over the period when
costs of financial distress are calculated.
 Source: Andrade and Kaplan (1998). The Journal of Finance Vol. 53. No. 5. page 1485.
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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

at p-value= 0.07. Regression (7) provides no evidence of a positive association between the bank loan reliance
and costs. Finally, Regression (8)
shows the effect of industry performance on costs. The result indicates
that poor performance in the industry
positively affects costs (p-value= 0.02).
In other words, there is a tendency that
the difficulty of selling assets at fair
values can increase costs when competing firms, as potential buyers, are
also in financial trouble. Again, the
results presented here must be carefully assessed along with its limitations. A significant problem with these
simple regressions is the omission of
relevant variables from the relationship. The estimators will be biased
unless the omitted variables are orthogonal to other independent variables (Thomas 1997; Ryan et al. 2002,
among others).
In Table 6, we examined the crosssectional determinants of the costs on
firm characteristics found in prior research. The work of Andrade and
Kaplan (1998) was used as the benchmark since its approach is the closest to
the one applied in this study. No study
on the costs estimation has so far been
conducted in Indonesia. Under different legal and financial market circumstances, we agree that the tables convey few comparisons for each study.
However, it may be highlighted that
both studies provide evidence that the
size of firm and complexity affect costs.
The number of securities is used as a
proxy for capital structure complexity
in Andrade and Kaplan’s research while
182

this study applies the number of creditors as the proxy for complexity. Their
research offers evidence that costs are
negatively related to the size of firm. It
indicates that there are important fixed
costs to restructuring in the American
system, while in Indonesia we predict
that low fixed costs and size are more
positively correlated to the degree of
conflicts of interest. A high correlation
coefficient between size and the number of creditors (COMPLEX) supports
the consistency of the view that complexity increases the indirect cost of
financial distress.

Conclusions
This research studies sample of
Indonesian financially distressed firms
which survived in 1997-2002. Most of
the firms turned out to be financially
distressed due to the Asian crisis. It
clarifies the factors which may contribute to the costs by classifying its
explanatory variables. More importantly, it presents quantitative estimates
of the indirect cost of financial distress
and its determinants. In order to measure the cost, this study estimates the
annualized changes in industry-adjusted operation profit and sales from a
year before the onset of distress to the
resolution year. Some firms were still
negotiating their loans until the end of
the sample period (2002); for such
firms, the cost estimated the annualized changes until 2002. Using those
approaches, the median of indirect financial distress cost is estimated between three and 11 percent annually.

Wijantini—The Indirect Costs of Financial Distress in Indonesia

To the extent that the direct cost of
financial distress reduces reported operating income, the estimated costs are
overstated. The average time in distress for firms in the sample is divided
into two categories. 17 firms (61 percent) were still in distress by the end of
2002, giving an average time in distress of more than four years. 11 firms
(39 percent) obtained debt renegotiation agreements by 2002 with an average time in distress of 2.6 years. The
simple regressions analysis suggest that
the indirect cost of financial distress
significantly increases with size, leverage, number of creditors, and poor
industry performance, but is not related to group affiliation, political connection, and degree of bank loan reliance. Therefore, the findings provide a
weak support for the financial distress
theory which suggests that conflicts of
interest render the costs of financial
distress.

The Limitations of the Study
The main shortcoming of this
study is the small size of sample and
the lack of data in the sample period.
The sample contains only 28 financially distressed firms. The small
sample reduces confidence and limits
the possibility of drawing general conclusions from the results. The sample

period of 1997-2002 offers both advantages and disadvantages to the aims
of the study. The systemic crisis beginning in mid-1997 offers a bigger sample
of financially distressed firms than a
normal period would; nevertheless, it
also offers disadvantages since it creates a more complex condition in resolving financial distress.
In order to minimize the uncertainty effect on firm performance, we
prefer to estimate the costs on the basis
of accounting information which we
consider to be able to provide more
reliable data than does stock market
performance during the sample period. However, accounting information may have some inherent shortcomings for the purpose of the study;
for instance, it does not reflect investors’ perceptions regarding distress issues.
In particular, the study measures
the ex-post indirect costs of financial
distress for the surviving firms in Indonesia. Ideally, the costs of financial
distress apply to both liquidated and
surviving firms in the sample. Therefore, the estimated costs could have
been higher if the defunct firms are
included. Moreover, the measurement
does not consider the effect of option
values, economic factors on the costs,
for example, the shift of the demand
and supply

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Gadjah Mada International Journal of Business, May - August 2007, Vol. 9, No. 2

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