Global COE Hi-Stat Discussion Paper Series 108

Research Unit for Statisticaland Empirical Analysis in Social Sciences (Hi-Stat)

Institutional Change andCorporate Financing in Indonesia:
Estimating the Effects of Social andPolitical Factors on Capital Structure

Hi-Stat Discussion Paper

Hidenobu Okuda
Yasushi Take

December 2009

Hi-Stat
Institute of Economic Research
Hitotsubashi University
2-1 Naka, Kunitatchi Tokyo, 186-8601 Japan
http://gcoe.ier.hit-u.ac.jp

Institutional Change and Corporate Financing in Indonesia:
Estimating the Effects of Social and Political Factors on Capital Structure

Hidenobu Okuda*
Yasushi Take**

December 21, 2009

Abstract
This study investigates the factors determining the capital structure of Indonesianlisted companies before and after the implementation of economic reform policies
subsequent to the 1997-1998 Asian financial crisis. The estimation analysis of the panel
data for the period 1994-1997 and 2000-2006 reveals several factors that determined
substantive change in the financing activities of these listed companies. The capital
structure of Indonesian companies had not been explained sufficiently by thestandardized theory of corporate financing, which had not considered the effects of thespecific social and political elements as well as business conglomerates, before the Asianfinancial crisis. However, the capital structure of Indonesian companies became fitted
more to the corporate financing theory, after the influence of social and political factorsof corporate attributes weakened substantially following the post-crisis reform policies.
This significant change is considered to result from institutional change caused by thefinancial and corporate reforms in the post-financial crisis era.

Keywords: Corporate Finance, Capital Structure, Ethnic network, Indonesia
JEL Categories: G32, G34, G38* Corresponding author; Department of Economics, Hitotsubashi University; hokuda@econ.hit-u.ac.jp**
Graduate School of Economics, Hitotsubashi University.

11. Introduction
Stable economic growth requires a sound and efficient institutional structure. However,in developing countries where formal economic institutions are not sufficiently developed,
informal institutions and codes of economic behaviors play important roles thatcompliment the formal institution (North, 1990). While these functions of informal
institutions have an economic rationality to a certain extent, they are criticized as the
major cause of the collusion between banks and companies as well as political influenceon economic activities.
It was generally recognized that any weaknesses in corporate finance, such as collusion
between banks and companies to facilitate excessive borrowing, were critical factors that
aggravated the Asian financial crisis in Indonesia. The Asian Development Bank (1999)
and Hill (2000) offer comprehensive views of the Indonesian financial sector. Claessens
et al. (2000) and Hanazaki & Liu (2003) investigated the background and impact of the
Asian financial crisis using econometric analysis.
To achieve a sustainable system, Indonesia promoted structural reforms in corporate
financing via the Indonesian Bank Reconstruction Agency (IBRA) and the Jakarta
Initiative. Public funds were injected into the banking sector, to dispose of nonperforming claims in the course of management reorganization in the wake of resignationand consolidations. In the corporate sector, where excessive borrowing and over investing
had become serious problems, many large conglomerates faced a financial crisis and had
to restructure their business groups. In order to tighten the management disciplines ofbanks and companies, and thereby improve the financial system as a whole, thegovernment implemented a series of banking reforms and corporate governance reforms
in response to the crisis of 1997-98.
Governments have often conducted major economic reforms after an economic crisis.
However, the effects of reform are limited since the social code of behaviors and theinformal institutional framework are not addressed by the reform and survive long after
the change of formal institutions (North, 1990). In the case of Indonesia, some studies
suggested that the reform policy was not effective in changing the companies’ behavior.
Sato (2003) conducted case studies of specific business groups to clarify their ownership
structures.
While the effectiveness of economic reforms has important policy implications, theauthors have found no formal econometric study examining how Indonesian corporate
financing changed as a result of the financial reforms implemented in response to thecrisis1. This study analyzes the financing structure of listed companies in Indonesia before
and after the Asian financial crisis, examining whether their corporate financing activities
changed after the reform policies were implemented. To this end, several types of debt
ratios for companies listed on the Jakarta Stock Exchange are estimated, the applicabilityof standardized theories of corporate finance to Indonesian corporate financing is
examined, and the influence of Indonesia’s unique social and political factors on
corporate financing is investigated. The study covers the thirteen years period from 1994
to 2006, a span that includes both pre-crisis years (FY 1994－FY 1997) when the1

Taridi (1999) was a pioneering study investigating the capital structure of listed companies in Indonesia
before the Asian financial crisis. Among the few formal empirical studies on ASEAN countries are Mieno(2006), Suto (2003), and Wiwattanakantang(1999).

2

economy was flourishing under the old regime, and post- crisis years (FY 2000‐FY
2005) when the economy was recovering from chaos through a series of economic
reforms.
This study is, first and foremost, a fact-finding endeavor to track the changing
corporate financing behavior of Indonesian listed companies during the period from 1994
to 2006. Specifically, this study focuses on four questions. First, did the financing
behavior of listed companies change as a result of the reforms implemented after the
Asian financial crisis? Second, if so, what were the major differences in corporate
financing pre- and post-crisis? Third, how did the post-crisis reforms modernize thefinancial behavior of listed companies? Finally, based on the financial activities of thelisted companies identified, what are the implications for future corporate financing
policies in Indonesia?
This study consists of six sections. Section 2 presents theoretical views for analyzing
the financing activities of listed companies in Indonesia, based on the adjusted
Modigliani-Miller theory (trade off theory) and agency cost theory. Section 3 describes
the characteristics of listed companies in Indonesia and the reform policies conducted in
the Asian-post-crisis period. Section 4 describes the methodology adopted to perform
econometric analysis and the data set used for estimation. Section 5 analyses inregression the determinants of the capital structure of listed companies, using the panel
data of individual listed companies. Section 6 summarizes the discussion of previous
sections, and based on our study results discusses the policy tasks for the consolidation ofIndonesia’s corporate financing system.
2. Analytical Scope of Listed Companies in Indonesia
2. 1 Adjusted Modigliani-Miller Theory and Agency Cost Approach
According to the Modigliani and Miller (1958) theory (hereinafter referred to as the“MM theory”), corporate value does not depend on capital structure; thus, corporate
financing has no impact on corporate value when several conditions exist together: acomplete capital market, perfect information, no corporate tax, no transaction cost, andno economic externality. However, the full set of preconditions of the MM theory is not
likely to exist in the real world; therefore, an adjusted MM theory is required. According
to the trade-off approach, companies choose the optimal capital structure that minimizes
the cost of capital so as to maximize the value of the company, in consideration of a riskof bankruptcy and the impact of corporate tax. The higher the company’s debt ratio is, thelower its average capital cost becomes. However, when the debt ratio is high, the risk ofbankruptcy also becomes high, resulting in a higher risk premium. The optimal debt ratio
is associated with maximum corporate value2.
According to the agency cost approach, determinants of corporate value (which are thedeterminants of optimal corporate capital structure) are also affected by agency cost,
taking into account asymmetric information. Since Jensen and Meckling (1976), two of
the types of conflicts of interest that generate agency cost have received priority:
relationships between shareholders as principals and management executives as agents;
and relationships between creditors as principals and shareholders as agents.

2

See Myers and Majluf (1984) for details.

3

The agency cost due to the relationship between shareholders and management
executives arises from the executives’ pursuit of personal profits and the shareholders’desire to maximize corporate value. This issue could be solved by raising the corporate
debt ratio and by decreasing management access to free cash flows. Meanwhile, theagency problem between creditors and shareholders arises from the shareholders’ desire
to receive good dividends by appropriating borrowed money or by making management
undertake high risk/high return investments using the limited liability system. In the caseof the latter conflict, lowering the corporate debt ratio is one solution to enhance
corporate value.
One of the characteristics of listed companies in Indonesian is their highly
concentrated ownership structure. Therefore, we can equate management executives andmajor shareholders in our description of the principal-agency relationship for listedcompanies in Indonesia. Shareholders have ultimate control over management, so theconflicts of interest between management executives and major shareholders are limited(Sato, 2003). Even the largest major companies are controlled by small numbers ofshareholders or tycoon families; therefore, the agency cost problem between management
executives and major shareholders is very serious. The public-offering ratio is not very
high, and therefore control over management by major shareholders is typical, even in thecase of listed companies.
The existing studies show that information disclosed by companies listed in Indonesia
is relatively low. As a result, there is high asymmetric information between outside
creditors and management executives (major shareholders), and the agency cost is also
consequently high. Therefore, a serious agency cost problem related to fund-raising islikely between outside creditors and management executives (major shareholders), or
between small shareholders and management executives (major shareholders).
Where there is a serious agency cost problem between creditors as principals andmanagement executives as agents (major shareholders), the agency cost becomes high if
funds are raised by borrowings. Therefore, high-profit companies with high retained
earnings tend to reduce external borrowing. A company’s capacity to provide collateral isalso critical as a factor determining agency cost. The larger the fixed assets that are used
as collateral, in comparison to debt, the more the company’s agency cost is reduced.
Therefore, companies with large collateral tend to have a high optimal debt ratio. When
financing by means of borrowed funds, a company’s market visibility is another criticalfactor. The higher the market visibility is, and the more widely corporate management is
known, the lower asymmetry of information is. When the business scale, the sales
volume, and the asset size are larger, the agency cost between creditors and the company
is lower and the optimal debt ratio is higher.
2.2 Informal Codes of Business Behaviors and Networks
2.2.1 Business Conglomerates and Foreign Joint Ventures
In developing countries where financial and legal systems are underdeveloped, there isconsiderable constraint on financial activities. Consequently, a tendency has arisen to
expand activities by borrowing funds externally through the development of quasi
markets where information sharing is easy and the agency cost problem is considerably
negligible. With such quasi markets, the company is likely to enjoy an advantage in
mitigating the agency cost of differentiating its financing activities.
4

For example, a company within a business group can raise funds from a bank in thesame group at a relatively low cost, so the optimal debt ratio is high. This results fromthree factors: the asymmetry of information between the companies and a bank in thesame business group is low; companies within the group enjoy favorable loan terms ascompared with companies on the outside; and companies within the group can count on
more cooperation from a bank, especially if they experience financial difficulties.
It is often said that one of the reasons why business conglomerates are formed indeveloping countries is their advantage in financing risk money with the aid of internal
capital markets. Funds from internal capital markets act as internal funds for companies
within the group, allowing business risks to be absorbed into the funds. In particular, thecore business in a group is expected to function as the borrower of external funds, so its
dependence on debt is apt to be higher than the optimal level for a non-consolidated
company. Foreign companies may take different financing routes compare to othercompanies. A foreign company is generally owned and managed by its parent company
and a local partner. The management information of a foreign company’s local subsidiaryis shared with the parent company in its home country and so the agency cost problem isnegligible between the two. Accordingly, fund raising through the parent company bears
an agency cost that is as low as that achieved through internal funding. Thus, the capital
expenditures of foreign companies are often funded through investment by the parent
company.
2.2.2 Informal Business Networks Based on Socio-Political Networks
The agency cost of external borrowings may be affected by political and social factors,
such as the ethnic connections or family relationships of management executives (major
shareholders) as well as a “revolving door” or other relationships with the government.
Generally, the asymmetry of information between outside investors and the managers of acompany is increased in developing countries where information disclosure and legal
systems are less robust than in advanced countries; thus, the political and social factors
can mitigate or prevent impediments. In reality, the power of contracts is perceived to behigh when the contracting parties share the same social and cultural background, because
there is a shared code of conduct that leads to significant social penalties (“loss of face”)
for contractual defaults (debt defaults) when contractors share the same social andcultural backgrounds.
One example of these factors at play is the difference between ethnic Chinesecompanies and non- ethnic Chinese local companies. There are common cultural andsocial rules for ethnic Chinese companies and ethnic Chinese banks3. Conversely, thecultural and social rules differ between ethnic Chinese companies and non-Chinesebanks; therefore, they may have difficulty maintaining a relationship of mutual trust. If an
ethnic Chinese company is financed by a non-Chinese bank, the loan terms might be lessadvantageous.4 In any case, when an ethnic Chinese company borrows money externally,

3

Okuda (2004) show that social and cultural background may affect the information production conductedby banks in Malaysia.
4
Several studies survey if there is a trusting relationship between Chinese companies and non-Chinesebanks. Andrew (2008) points out this issue. See Sato (2003) for the relationship between Chinesecompanies and the government of Indonesia.

5its agency cost may differ from that borne by a non-ethnic Chinese local company, due tothe disparity of social, cultural, and political background rules.
The agency cost arising in regard to creditors also depends on whether the company isgovernment-linked. If a company is recognized in the market as being supported or
guaranteed implicitly by the government, the risk for creditors in financing that company
is mitigated. In the case of government-linked companies, information sharing throughthe government may minimize the asymmetry of information when dealing withgovernment-linked banks. In any case, government-linked companies may have anagency relationship with creditors different from that experienced by the private sector ingeneral, so their capital structure can have characteristics that are different from thestructure typically seen in private companies.
2.3 The Effects of Reform Policies after the Asian Financial Crisis
After the Asian financial crisis, a wide range of financial and corporate reform policies
were implemented. First, public funds were injected for the liquidation of the failed banks
that had been severely affected by the Asian financial crisis, those banks’ non-performing
loans were settled by the IBRA, and the external debt problems of individual companies
were solved with the help of the Jakarta Initiative. These measures dismantled the special
ownership structure between banks and business conglomerates, that is, the endemic
collusion between banks and business conglomerates that were deemed to haveaggravated the financial crisis (Claessens, 2000)5.
Second, for maintaining healthy bank management, the prudential regulations forbanks were made more stringent, the monitoring power of the monetary authority overbanking activities was enhanced, and the previously low enforcement capability wasstrengthened. Under the tightened regulations, the responsibility of bank managers cameto be critically linked to the sound banking operations, and it became difficult for bankmanagers to exploit their private benefit and direct the profit to a specific company.
Third, in parallel with the reform of the banking sector, corporate governanceregulations for listed companies were tightened, and legal mechanisms to handle
problems such as bankruptcy were developed. The reforms include the improvement of
information-disclosure, which was necessary to strengthen the corporate governance ofstockholders in the capital market, and the modernization of bankruptcy laws, which wasnecessary to strengthen the corporate governance of external creditors.
The restructuring of capital structures and reform of the financial systems instituted
new management disciplines to prevent collusion between banks and private companies,
and thereby exercised considerable influence over corporate financing. If these measures
successfully modernized the country’s corporate financing, analysis would show that the
influences of social and political factors on the funding of listed companies would be
weaker after the Asian financial crisis. On the other hand, if the measurements were noteffective in changing financing attitudes, social and political factors would still berecognizable in the post-crisis data.
3. Listed Companies in Indonesia
3.1 Corporate Attributes and the Classification Method of Listed Companies
5

It was recognized that the enterprise that falls into the excess indebtedness had received the financing
from the bank in the same business conglomerates.

6

The advantages to this approach to analyzing the listed companies include thefollowing1. First, the available financial data are far more refined than those of unlistedcompanies, so that an in-depth analysis based on the framework of economics becomes
possible. Second, consistent long-term control of the corporate data of various industries
leads to a comprehensive overview of corporate finance profiles. The method of thisstudy and the knowledge provided by previous case studies are complementary
approaches, which in combination are expected to greatly expand and deepen theunderstanding of this field. Third, more than half of the major private companies includedin the top thousand companies by sales ranking are listed on the Indonesian stock market.
This means that the presence of major private companies reflects an importance that is
not to be undervalued in the corporate sector or in Indonesia’s economy, despite theirlimited number (Sato, 2004). Accordingly, a thorough analysis of the financing activities
of listed companies is an essential process for studying issues of consolidating corporate
finance.
According to the discussion in the previous section, we classified the listed companies
into several groups based on their corporate attributes. First, in the classification ofownership structure, the major shareholders of each company are categorized as Pribumi(so-called “native” Indonesian or ethnic Malay), the ethnic Chinese, the foreign joinventure, the ethnic Indian, or government controlling companies, on the basis of theirfamily names. Therefore, the attribute of the shareholders who have the largest number ofshares becomes the corporate ownership attribute. When a company’s holding company
is the largest shareholder, the ownership structure is classified as Pribumi, the ethnic
Chinese, the foreign join-venture, the ethnic Indian, or government controlling companies,
on the basis of the family name of the holding company’s largest shareholder.
Second, when a company belongs to a business conglomerate, its importance andcentrality are classified on the basis of three standards. A company is classified as a “corecompany” within the conglomerate only when: the directors are not professional
managers but family members who own the business conglomerate (or its holding
company); the scale of the company is significantly large within the businessconglomerate; and the industry of the company is central to the conglomerate. Companies
that satisfy only two of these three standards are classified as a “major company” within
the business conglomerate.
Third, the impact of the Asian financial crisis is undeniable as a special factor affecting
the financing of listed companies in Indonesia. Companies that underwent reconstruction
after the crisis may, in contrast to other companies, have been supported in various ways
to reduce their debts. Consequently, they enjoyed an advantage over unsupported
companies in regard to debt reduction, which results in a difference in capital structure
attributable to policy factors. In particular, their proportion of bank borrowing usedmainly for short-term funding is relatively low compared to that of other companies; infact, it was greatly reduced during the time when these companies were undergoingreconstruction. A company belonging to the same business conglomerate both before andafter the Asian financial crisis was classified as a “non-restructured company.” A
company belonging to a different business conglomerate after the Asian financial crisis
was classified as a “restructured company.”
3.2 The Fund-raising Structure of Companies with Different Corporate Attributes
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When we looked at the ownership attributes of listed companies, ethnic Chinesecompanies accounted for the largest share both before and after the Asian financial crisis.
According to the number of companies, the share of the total number of listed companies
occupied by ethnic Chinese companies, the foreign joint venture companies, Pribumi
companies, government controlling companies, and ethnic Indian companies were 64%,
20%, 10%, 5%, and 2%, respectively. According to the asset size of companies, the shareof total assets of all listed companies occupied by ethnic Chinese companies, the foreign
joint venture companies, Pribumi companies, government controlling companies, andethnic Indian companies were 42%, 27%, 23%, 6%, and 2%, respectively. The averaged
asset sizes of the ethnic Chinese and Pribumi companies were smaller than those offoreign joint venture and government controlling companies.
The financial characteristics of listed companies are summarized according to different
ownership attributes in Table 3-1. The ratios of debt to total assets (debt ratios) of listedcompanies tended to increase before the Asian financial crisis, while it decreased after thecrisis6. The debt ratios of the ethnic Chinese companies and the ethnic Indian companies
were almost always higher than those of Pribumi companies, and the debt ratios offoreign joint venture companies were similar to those of the ethnic Chinese companies.
After the Asian financial crisis, the long debt ratios and the ratio of bank borrowing
substantially decreased, and these ratios fluctuated widely for the government controllingand Pribumi companies.
(Table 3-1) Comparison of Listed Companies by Ownership Attributes
The ratios of before-tax profit to total assets (profit ratio), which represented thecompanies’ capability to earn profits, gradually decreased after the Asian financial crisis,
then it turned to recover after 2004. The profit ratio of foreign joint venture companies
and government controlling companies were higher than those of other companies, andthe before-tax profit ratios of ethnic Chinese companies and Pribumi companies were atsimilar levels.
The ratios of fixed assets to total assets (fixed asset ratio), which represented thecompanies’ ability to provide collateral, of ethnic Indian companies were the highest, andthose of Pribumi companies were the lowest. The fixed assets ratio did not differ so muchamong government controlling companies, ethnic Chinese companies, and foreign joint
venture companies.
The difference in the financial characteristics between core companies and non-corecompanies belonging to business conglomerates are summarized in Table 3-2. There wasa tendency for the debt ratios and long-term debt ratios of core companies to be higher
than those of non-core companies, while the bank borrowing ratios of core companies
were lower than those of non-core companies. The fixed asset ratios of core companies
were higher than those of non-core companies. These tendencies did not change before
and after the Asian financial crisis. While the profit ratios of non-core companies werehigher than those of core companies before the Asian financial crisis, the difference in the
profit ratios between core and non-core companies disappeared after the crisis.

6

After the Asian financial crisis, some listed companies had the amount of the debts exceeding their assets.
Those companies are excluded from the sample of data for econometric study in the following sections.

8

(Table 3-2) Comparison of Core and Non-core Companies
The comparison of restructured and non-restructured companies is summarized inTable 3-3. There was no significant difference in debt ratios, long-term debt ratios, andshort-term debt ratios between restructured and non-restructured companies before the
Asian financial crisis. Since the restructured companies’ finances were remedied throughdebt reduction, the debt ratios of these companies became lower than those of nonrestructured companies after the financial crisis. However, as the Indonesian economy
recovered, the difference in the debt ratios between restructured and non-restructured
companies disappeared until 2003, and the debt ratio of non-restructured companies
became lower than those of restructured companies.
(Table 3-3) Comparison of Restructured and Non-restructured Companies
Before the Asian financial crisis, there was no significant difference in profit ratios
between restructured and non-restructured companies. After the crisis, the profit ratios ofrestructured companies became lower than those of non-restructured companies.
Meanwhile, as the economic recovery progressed, the difference in the profit ratios
between restructured and non-restructured companies ended.
4. Methodology
We used the following method to analyze the hypotheses described in Section 2. First,
we estimated the capital structure of the listed companies in Indonesia by using a fixedeffect unbalanced panel model. The objectives were to the estimate effects of the several
economic variables, corporate tax and business-risk, explained by the trade off approach;and the creditworthiness and ability to provide collateral explained by the agency costs
theory. The characteristics of each company are contained by the fixed effects in theestimation. Second, we regressed the fixed effects (obtained by the first estimation) to thedummy variable estimators representing unique characteristics of the Indonesiancompanies. Regression of the fixed effects enables us to observe how the characteristics
of each company affect its capital structure. We also analyzed the pre-crisis and postcrisis differences at both of the above steps of analysis (first-step regression and secondstep regression).
4.1. Empirical Model for Debt-Ratios and Economic Variables
We estimated three types of debt-ratio. The empirical model is expressed as equation(1), where DRkit is type k debt-ratio for i-th company at time t－1 ,  i is the fixed-effectfor i-th company, X ijt 1 is the explanatory variables for i-th company at time t－1 ,  j
are the coefficient of X ijt 1 , and  it is the random error term for i-th company at time t.
The explanatory variables include the followings; REit-1 is the free cache flow for i-th
company at time t－1, TAXit-1 is the rate of corporate tax for i-th firm at time t－1, FIXit-1
is the ability to provide collateral for i-th company at time t － 1, SIZEit-1 is thecreditworthiness for i-th company at time t  1 , RISKit-1 is the business-risk for i-th
company at time t－1. AF is the dummy variable for the post-crisis period, BM is thedummy variable for the mini-boom period since 2004, YD1996~YD2005 are the year
9

dummies. We used cross terms of AF (or MB) and each variable (except year dummies)
to observe the change of economic structure from pre-crisis to post-crisis (or from premini-boom to post-mini-boom) period. To rule out simultaneity between the explanatory
variables and the dependent variables, the values of REit-1, TAXit-1, FIXit-1, SIZEit-1, and
RISKit-1 are one period prior time to DRkit.
(1) DRijtt   i   j 1  j X ijt 1  AF   j 1  j X ijt 1  BM   j 1  j X ijt 1  k 1  k YDk   it
m

m

m

n

(1) Dependent Variables
We estimated by using three types of debt-ratio as independent variables; TDR =thetotal debt ratio (total liabilities/total assets), LDR = the long-term debt ratio (Long-term
liabilities/total assets), SDR =the short-term debt ratio (short-term liabilities/total assets).
The total debt ratio shows the rate of liabilities to all capital. It is the most basic index
for capital structure. It is essential to observe the total debt ratio to analyze how corporate
tax and business risk affect a company’s capital structure, because these two variables
affect any debt.
There is a difference between short-term debt and long-term debt. Short-term debt likeaccounts payable and notes are used for short-term objectives like cash flow. Long-term
debt is used for long-term objectives like capital expenditures (e.g., investments financed
by long-maturity instruments). Because both lender and borrower are firms, there is lessasymmetrical information when short-debt like accounts payable is used, than when otherfinancial devices are used. On the other hand, there is more asymmetrical information
when long-term debt is used. The agency cost associated with long-term debt has astronger effect than that associated with short-term debt.
We predicted that the short-term bank debt ratio would be different from the total debt
ratio and long-term debt ratio, because banks are the most important creditors and have asuperior ability to get information about borrowers.
(2) Explanatory Variables
The following explanatory variables and their definitions apply to equation (1).
RE: The rate of retained earnings is defined as (retained earnings) / (total assets). We
used it as a proxy of free cash flow. While profit rates like return on assets are frequently
used in other studies, we used the rate of retained earnings because it seems more stable
than profits rates. Free cash flow incurs less agency cost than other financial sources. The
greater the company’s free cash flow, the less agency cost incurs. It was expected that thesign of RE would be negative.
TAX: The rate of corporate tax is defined as ((profits before tax – profits after tax)/
total assets). We used it as a proxy of the effect of corporate tax. Although the corporate
tax rate of each individual firm is often used in other studies, corporate tax rates do notinclude deferred tax assets and tax-premiums. Considering this point, we calculated thetax rate as described and used it as a proxy. A high rate of corporate tax makes a firm
increase its debt ratio in order to reduce the tax payment. Therefore, it was predicted thatthe sign of the rate of corporate tax would be negative.
FIX: The ratio of fixed assets is defined as (tangible fixed assets)/(total assets). We
used it as a proxy of the ability to provide collateral. Tangible fixed assets are easy topledge as collateral and thus decrease agency costs of borrowing. The more tangible the10firm’s assets, the greater its ability to issue secured debt and the less information it has toreveal about future profits. Therefore, it is predicted that the sign of the ratio of fixed
assets would be positive.
SIZE: The firm’s size is defined as the natural logarithmic of total assets. We used it asa proxy of the creditworthiness in the market. The more visible the company is, thelower its agency costs and the more debt it can issue. It was predicted that the sign of afirm’s size would be positive.
RISK: The business risk is defined as the deviation of the absolute values of theoperating losses divided by total assets, from 1994 to 1997 and 2000 to 2003 7 . The
volatility of a company’s stock price or profits is often used as a proxy of business risk.
However, due to the characteristics of the stock market in Indonesia, there is a tendency
for well-performing listed companies to have a wide fluctuation in their stock price or
profits. To avoid this problem, we determined the business risk from the level of losses.
In other words, the more business risk the firm has, the greater the risk of bankruptcy andthe creditors suffering losses. It was predicted that the sign of company’s business risk
would be negative.
YD1996 ~YD2003: Year dummy variables were created for each year. We used thisdummy to control the change in macroeconomic environments.
AF: The crisis dummy variable is defined as 0 if the year is 1998 or earlier, and 1 if theyear is 1999 or later. We used this dummy to observe the change after the financial crisis.
BM: The mini-boom dummy variable is defined as 0 if the year is 2004 or later, and 1
if the year is 2003 or earlier. We used this dummy to observe the change after the miniboom since 2004.
4.2 Empirical Model for Fixed Effects and Corporate Attributes
We regressed the fixed effects ̂ i , which were obtained by equation (1), on
independent variables and the corporate specific attributes explained in Section 2 as
explanatory variables. We calculated ̂ i from the estimation results of three different
types of debt ratios; the total debt ratio, the long-term debt ratio, and the short-term debt
ratio.
The empirical model is expressed as equation (2), where C is the constant term, Aij isthe dummy variable for the corporate attributes of i-th company,  j is the coefficient of
Aij ,  j is the coefficient of the cross term of Aij and the post crisis dummy variable AC,
ID j is the dummy variable for each industry,  j is coefficient of ID j , m is the numberof corporate attributes, n is the number of industries, and  i is a random error term.
m

m

n

j 1

j 1

j 1

(2) ˆ i   it  C    j Aij  AC    j Aij   j ID j   i
We used the following dummy variables for the ownership structure, the core company
of a business conglomerate, and the post-crisis restructuring, which are all explained in7

We calculated it by including data from times when the firm’s retained earnings were negative.

11Section 3. In addition, we used the dummy variables for industries as control variables.
The categorization of industries was based on ECFIN (2003).
Ownership attributes: According to the classification in Section 3, we used the dummy
variables for the ownership structure, including dummy variables for Pribumi, the ethnic
Chinese companies (EthnicChinese), the foreign join-venture companies (Foreign), theethnic Indian companies (EthnicIndian), or government controlling companies(Government). The value of each ownership structure is 1 if the firm fits its category, or 0
if the firm is not identified by the category8.
Core company of a business conglomerate: According to the classification in Section
3, we used the dummy variables for the core business companies (Core). The value ofcore business companies is 1 if the firm fits its category, or 0 if the firm is not identified
by the category.
Post-crisis restructuring: According to the classification in Section 3, we used thedummy variables for the restructured companies (Restructured). This categorization of acompany as restructured or not depends on whether it changed its business group after the
Asian financial crisis. Specifically, if the company belonged to the same business groupin 2003 as it did in 1997, it is classified as non-restructured; otherwise, it is considered a
restructured company. The value of restructured companies is 1 if the firm fits its
category, or 0 if the firm is not identified by the category.
4.3 Data Description
We analyzed the listed companies that were not financial companies. The data related
to financial statements includes values from 1994 to 2005, and the data related tocorporate attributes is as of 2003.
The financial statement data from 1994 to 1995 and 2003 to 2005 are based on theIndonesia Financial Market Directory (1996, 1997, 2003, 2004 ， and 2005 editions),
published by the ECFIN. The data from 1996 to 1997 was taken from the JETRO-IDE
database of the Institute of Developing Economies, Japan External Trade Organization9.
Data from 1998 to 1999 was omitted because of the Asian financial crisis. Samples
whose retained earnings were negative were excluded as abnormal values. In order toavoid simultaneity, we used the explanatory variables for a period prior to the dependent
variables.
Table 4-1 shows the basic statistics of dependent and explanatory variables and thecorrelation coefficients between them. There is no especially high correlation coefficient.
(Table 4-1) Basic Statistics and Correlation Matrix
5. Estimation Results
5.1 Estimated Results of Debt Ratios
Table 5-1 shows the estimation results of equation (1), which represents the effects ofeconomic factors on the capital structure of listed companies. For the total debt ratio,
long-term debt ratio, and short-term debt ratio, according to the Hausman test, the fixed
effect model was selected. Most of the coefficient estimators were statistically significant
8

The categorization incorporates information on the business status of listed companies obtained through aseriesof interview at P. T. Nomura Indonesia, a local subsidiary of Nomura Securities Co.Ltd.
9This database was created by Yuri Sato and Miki Takeda of Institute of Developing Economies, Japan
External Trade Organization.

12and followed their expected signs. The adjusted R-square values were higher than thosein the previous works examining capital structure of ASEAN companies, and the Fvalues were large enough. Overall, we obtained satisfactory results for the cost function
estimation.
(Table 5-1) Estimation Results of Debt Ratios
Before the Asian financial crisis, the estimation results of debt ratios were not wellconsistent with the corporate financing theory explained in Section 2. The coefficients ofmany explanatory variables had the sign contrary to the theoretical expectation, or they
were statistically insignificant. This observation suggests that corporate fund tapping
activities in Indonesia before the Asian financial crisis differed from those predicted bystandardized corporate financing theory.
In the estimation of total debt ratio before the Asian financial crisis, only thecoefficient estimate of the rate of retained earnings (RE) was statistically significant andconsistent with the theoretically expected sign, that is, negative (-0.077). However, thecoefficient of corporate tax (TAX) was a significantly negative value (-0.468), which wasinconsistent with the theoretical expectation. The coefficient estimates of other variables,i.e., the business risk (RISK), the firm’s creditworthiness (SIZE), and the fixed assets ratio(FIX) were statistically insignificant.
The estimated results of the long-term debt ratio were more consistent with thetheoretical expectation. The coefficient of the business risk (RISK) was significantly
negative (-0.098), the coefficient of the rate of retained earnings (RE) was significantly
negative (-0.078), and the coefficient of the firm’s creditworthiness (SIZE) was
significantly positive (0.085), all of which were consistent with the expectation of
corporate financing theory.
The estimation result of short-term debt was not consistent with the theoretical
expectation at all10. The coefficient estimates of the business risk (RISK) was significantly
positive (0.103), while the coefficient of the corporate tax (TAX) was significantly
negative (-0.285), the coefficient of the fixed assets ratio (FIX) was significantly negative(-0.097), and the coefficient of the firm’s creditworthiness (SIZE) was significantly
negative (-0.064). These results were all opposite to the theoretical prediction.
After the economic reforms in the post Asian financial crisis, corporate fund tapping
activities in Indonesia changed into theoretically expected post-crisis activities. The
estimation results of the debt ratio, long-term debt ratio, and short-term debt ratio, proved
to be much more consistent with the expectation of corporate financing theory. Thissuggests that the economic reforms modernized the corporate fund raising activities inIndonesia, which were explainable by economic rationality under the modernizedinstitutional frameworks. We found that the strengthened prudential regulation
implemented after the crisis and the modernized bankruptcy law had the affect of making
10

The estimation result of short-term bank borrowing ratio was not well consistent with the corporate
financing theory both pre- and post-crisis periods. In the estimation of short-term bank borrowing ratio (seeTable A1 in the appendix), the coefficients of most explanatory variables have the sign opposite to thetheoretical expectation, or they were statistically insignificant. This observation suggests that the short-term
fund raising activities of listed companies were influenced temporally by ad hoc factors during the entire
study period.

13

the fixed assets ratio consistent with the corporate financing theory.
In the estimation of the debt ratio, the coefficient of the post-crisis dummy and thecross term of corporate tax (AF*TAX) had a significantly positive values (0.486) and thecoefficient of post-crisis dummy and fixed assets (AF*SIZE) had a significantly positive
values (0.124). This implies that, after the Asian financial crisis, the influence of tax and
fixed assets ratio on debt ratios became consistent with the standard theory of corporate
financing11. The coefficient of the post-crisis dummy and the rate of retained earnings(AF*RE) had a significantly negative value (-0.112), while the coefficient of the postcrisis dummy and the firm’s creditworthiness (AF*SIZE) had a significantly positive
values (0.034). This implies that, after the Asian financial crisis, the theoretically
expected influence of retained earnings and the firm’s creditworthiness was enhanced.
Moreover, the coefficient of the mini-boom dummy and tax (BM*TAX) had asignificantly positive value (0.468), and the coefficient of mini-boom dummy and theretained earnings ratio (BM*RE) had a significantly negative value (-0.123). Thissuggests that the theoretically expected influence of tax and the retained earnings weremore strengthened.
In the estimation of the long-term debt ratio, the coefficient of the cross term of postcrisis dummy and corporate tax (AF*TAX) was significantly positive (0.182), and thecoefficient of the cross term of the post-crisis dummy and the firm’s creditworthiness(AF*SIZE) was significantly positive (0.077). This implies that, after the Asian financial
crisis, the influence of tax and fixed assets ratio on long-term debt ratios was consistent
with the expectation of corporate financing theory. Furthermore, the coefficient of themini-boom dummy and tax (BM*TAX) had a significantly positive value (0.153), which
implies that the theoretically expected influence of tax was stronger.
Similar to the estimation of debt and long-term debt ratio, in the estimation of shortterm debt ratio, the coefficient of the cross term of the post-crisis dummy and corporatetax (AF*TAX) was significantly positive (0.266), the coefficient of the cross term of the
post-crisis dummy and the retained earnings (AF*RE) was significantly negative (-0.121),
and the coefficient of the cross term of post-crisis dummy and the firm’s creditworthiness(AF*SIZE) was significantly negative (0.074). This observation suggests that, after the
post-crisis economic reforms, the influence of these economic factors on the short-term
debt ratio was consistent with the expectation of corporate financing theory. Moreover,the coefficient of the mini-boom dummy and tax (BM*TAX) had a significantly positive
value (0.285) and the coefficient of the mini-boom dummy and the firm’s
creditworthiness (BM*SIZE) had a significantly positive value (0.043). This suggests that,after the mini-boom since 2004, the theoretically expected influence of tax and the firm’s
creditworthiness was further enhanced.
The coefficients of dummy variables for the years from 1996 and 1997 were positive,
and those for the years after 2001 were negative. Although most of these coefficientswere not statistically significant enough12, this shift suggests that listed companies tended
to decrease their debts after the Asian crisis.
11

After the Asian financial crisis, the total coefficient estimate of tax became positive (-0.468+0.486>0)
and the total coefficient estimate of fixed assets ratio became positive (-0.054+ 0.124>0), too, as
theoretically expected.
12
The coefficient of the dummy variable for the year 1997 was significantly positive for all types of debtratio.

14

5.2. Estimation Results of Companies’ Fixed Effects
The estimation results of companies’ fixed effects by using dummy variables for thecompany’s attribute as explanatory variables are summarized in Table 5-2. While thevalue of adjusted R2 was not high, the selection of explanatory variables was not at fault
in the sense that the values of F-tests are statistically significant enough.
(Table 5-2) Estimation Results of Companies’ Fixed Effects
Before the Asian financial crisis, the ownership attributes affected all types of debtrates. The coefficient estimates of the dummy variables representing the companies’
ownership attributes, such as the ethnic Chinese dummy (EthnicChinese), government
controlling dummy (Government), the foreign joint venture dummy (Foreign), the ethnic
Indian dummy (EthnicIndian) had significant effects on the debt ratio, long-term debt
ratio, and short-term debt ratio. This suggested that, in the pre-crisis period, the fundraising structures of listed companies were affected strongly by the social and political
networks they possessed.
In the estimation of debt ratio, the coefficient estimate of the ethnic Chinese dummy,
the foreign joint venture dummy, and the ethnic Indian dummy were positive (0.061,
0.107, 0.098, respectively) and statistically significant. In the estimation of long-term
debt ratio, the ethnic Chinese dummy, the government controlling dummy, and the ethnic
Indian dummy were positive (0.039, 0.054, 0.172, respectively) and statisticallysignificant. In the estimation of short-term debt ratio, the coefficient estimate of theforeign joint venture dummy was positive (0.099) and statistically significant. Theseobservations suggested that, compared to the Pribumi companies, the ethnic Chinese, thegovernment controlling, the foreign joint venture, and the ethnic Indian companies had
some social, political or economic networks that were used for tapping external debt
funds at lower agency cost. These results supported the commonly cited stories that theethnic Chinese and Indian companies had strong financial ties to their ethnic business
communities, that the government controlling companies had implicit financial support,
and that foreign joint ventures tapped their needed funds from abroad at low cost. On theother hand, the Pribumi companies without strong business or political networks had
more difficulty in raising debt from external creditors at low agency cost.
After the economic reforms in the Asian post-financial crisis period, the effect of thecorporate ownership attributes became very weak drastically in the estimation of debt
ratio as well as long-term debt ratio. The coefficient estimates of cross terms of the postcrisis dummy variable and corporate ownership attributes had the opposite signs fromthose before the Asian crisis occurred. In the mini-boom period after 2003, the influenceof corporate ownership attributes became weaker.
In the estimation of debt ratio, the coefficient estimates of the cross terms of the miniboom dummy and the ethnic Chinese dummy (AC*EthnicChinese) was negative (-0.050)
and statistically significant. In the estimation of long-term debt, the coefficient estimatesof the cross terms of the economic reform dummy and the ethnic Chinese(AC*EthnicChinese), the government controlling dummy (AC*Government), and theforeign joint venture dummy (AC*Foreign) were all negative (-0.053, -0.111, -0.122,
respectively) and statistically significant. Moreover, the coefficient estimates of the crossterms of the mini-boom dummy and the ethnic Chinese (BM*EthnicChinese), the15government controlling dummy (BM*Government), and the foreign joint venture dummy(BM*Foreign) were statistically significant and negative (-0.052, -0.111, -0.032,
respectively).
Before the Asian financial crisis, the core companies in the business conglomerates
tended to borrow funds more eagerly than other companies. In the estimation of debt ratio,
long-term debt ratio, and short-term debt ratio, the coefficient estimate of the corecompanies (Core) was statistically significant and positive (0.038, 0.020, 0.017,
respectively) in the pre-crisis period. This was consistent with the frequently citedunderstanding that the core companies functioned as the window through which businessconglomerates tapped external funds and redistributed them among companies belonging
to the conglomerates13.
After the post-crisis economic reforms, the business conglomerates normalized theirfund raising structure by reducing the external debt, especially the short-term debt. In theestimation of the debt ratio and short-term debt ratio, the coefficient estimates of the corecompany dummy that were crossed with the after-crisis dummy (AC*Core) were
statistically significant and negative (-0.054 and -0.048, respectively). This implied thatthe core companies more aggressively decreased their debt ratio than other companies,
especially in reducing their short-term debt ratio.
However, the business conglomerates retained the special function of the corecompanies to raise long-term debt funds from external creditors. Meanwhile, in theestimation of the long-term debt ratio, the coefficient estimates of the cross term of theafter-crisis dummy and the core company dummy in the long-term debt ratio wasinsignificant. Moreover, in the mini-boom after 2003, in the estimation of the long-term
debt ratio, the coefficient estimates of the cross term of the mini boom dummy and thecore company dummy (BM*Core) was significantly positive (0.036). These observations
suggested that the core business of each business conglomerate is still responsible forborrowing long-term external funds after the Asian financial crisis, and that, as thedemand for investment funds recovered in the mini boom, the business conglomerates
expanded the special function of core companies to raise long-term debt funds fromoutside.
6. Concluding Remarks

The modernization and the rationalization of corporate activity are important policy
tasks for sustainable economic development, which requires the modernization of
institutional frameworks in developing economies. The wide-ranging economic reforms
pursued by the Indonesian government after the Asian financial crisis gives us aninteresting example for examining how the development of formal economic systems
help change the economic behaviors of private companies. This study is the first attempt
to investigate the influence of institutional changes on companies’ corporate financing
activities by clarifying the factors determining the capital structure of Indonesian listedcompanies before and after the implementation of reform policies subsequent to the
Asian financial crisis. The estimation analysis of the panel data for the period 1994-1997

13

The coefficient estimate of the cross term of the post crisis reform dummy and the restructure companies
dummy was a significantly negative value (-0.022) in the estimation of the debt ratio.

16and 2000-2006 reveals several factors that determined substantive change in the financing
activities of these listed companies.
Our investigation makes three contributions to this area of study. First, we found thatthe capital structure of Indonesian companies had not been explained sufficiently by thestandard theory of corporate financing, which had not considered the effects of its
specific social and political elements, as well as business conglomerates, before the Asianfinancial crisis. The estimation results prove that differences in corporate attributes had
some influence on companies’ fund raising activities. These observations suggested thatthe formal economic system that is assumed in the standard theory of corporate financing
did not function well enough, and an informal code of common practices had ameasurably large influence on the corporate capital structure in an Indonesian listedcompany before the Asian financial crisis.
Second, we found that the corporate financing behaviors of Indonesian listedcompanies changed after the economic reforms during the post-crisis period. Ourestimation results show that the earlier significant differences in capital structure between
companies possessing different socio-economic backgrounds, such as the ethnic Chinesecompanies, government controlling companies, and foreign joint venture companies, andthe ethnic Indian companies, almost disappeared after the reforms. The post-crisis
financing activities of listed companies in Indonesia are explainable by economic
rationality. Any particular skew or constraint peculiar to Indonesia that was seen before
the Asian financial crisis is no longer discernible in major explanatory variables, such as
the profit yearnings ratio, collateral capacity, or corporate tax effects. These facts suggestthat the fund raising activities of listed companies in Indonesia are becoming rational as aresult of the post-crisis economic reforms that were designed to ensure the soundmanagement of banks and the consolidation of corporate governance. The restructuringof capital structures and the reforms of Indonesian financial systems succeeded inbuilding an institutional framework in which Indonesian companies could conduct fundraising activities based on economic rationality, not influenced by their social andpolitical factors.
Our third contribution illustrates the limitation of reforms. The estimation results
demonstrate that the agency cost incurred by information asymmetry was a critical
determinant in corporate financing in Indonesia even after the Asian financial crisis andcollateral providing capacity has the most significant impact on determinants of longterm debt ratio. Poor capacity to provide collateral and low transparency to outside
creditors could become serious constraints on a company’s borrowing even though its
other corporate operational characteristics were equal to those of competitors. Only
companies with a high collateral providing capability are able to borrow long-term
external funds.
Another limitation of reform involves the companies’ membership in a businessconglomerate. For companies having a strong influence over the other members of theirgroup, there is a tendency to have a higher long-term debt ratio and a lower short-term
debt ratio than other companies. This tendency suggests that core companies within abusiness group can still function as a conduit of long-term external funds to othermembers of their group; they raise long-term funds by taking advantage of their relatively

17

low agency cost in tapping funds from outside creditors, and redistribute the those funds
to other companies within the group14.
To solve these persistent problems, it is necessary to promote corporate information
disclosure for the benefit of external investors and creditors. Furthermore, it is essential tobuild a legal framework for smooth liquidation of collateral and speedy reconstruction of
failed companies. Despite the implementation of reform policies after the Asian financial
crisis, there is still a desperate need for enhancing information disclosure and the legal
infrastructure (Sato [2004]). In tandem with solution of these problems, the developmentof capital markets such as stock and debenture markets is required to meet the demand oflarge-scale long-term debts.

14

The mechanism of the existence of the internal capital market and the re-capital distribution in thefinancial clique could not be pursued in the present study where only the listed company was analyzed. It
will be necessary to analyze the funding action of a financial clique system enterprise including non-listedcompanies to analyze this problem further.

18

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20

（Table 3-1）Comparison of Listed Companies by Ownership Attributes
（%）
1994

1995

1996

1997

2000

2001

2002

2003

2004

2005

Total debt ratio
Pribumi

35.8

42.1

53.9

64.9

41.0

31.9

32.8

30.1

46.7

47.2

Ethnic Chinese

46.3

49.1

52.7

69.0

48.7

45.0

43.7

46.0

47.8

48.3

Government controlling

44.9

43.5

45.1

58.3

48.2

47.3

45.5

57.8

44.4

42.6

Foreign joint venture

45.6

53.4

53.0

65.8

46.6

44.8

43.3

45.1

45.6

46.3

Ethnic Indian

59.2

61.3

61.2

68.3

42.8

47.3

48.1

57.0

55.6

57.8

Pribumi

22.8

27.2

30.6

46.2

30.1

26.6

27.7

16.8

31.0

27.9

Ethnic Chinese

33.0

34.8

33.3

45.1

29.6

29.5

28.1

29.8

29.0

30.4

Government controlling

20.7

25.0

22.7

25.1

34.7

35.6

33.0

31.0

22.3

21.2

Foreign joint venture

33.9

40.9

42.1

49.6

30.0

31.5

27.6

29.4

28.4

29.0

Ethnic Indian

35.6

30.9

31.4

27.8

28.9

31.9

32.3

34.3

30.9

26.8

Pribumi

15.1

16.4

21.8

25.7

20.7

16.8

17.3

17.8

20.9

20.2

Ethnic Chinese

10.6

11.7

15.2

20.9

13.9

10.6

11.1

13.8

14.2

15.6

Government controlling

33.0

28.0

39.8

41.0

25.3

28.8

35.9

30.6

33.7

26.1

Foreign joint venture

─

1.4

0.9

1.3

22.1

27.0

28.6

32.6

36.6

34.0

Ethnic Indian

─

─

─

─

─

─

─

─

─

─

11.7

13.1

14.5

21.9

14.9

8.5

5.8

1.5

3.0

2.9

16.3

16.9

16.4

22.8

9.9

13.1

11.6

11.2

7.7

12.8

Short-term debt ratio

Long-term debt ratio

Short-term bank borrowing ratio
PribumiEthnic Chinese
Government controlling

7.4

7.3

6.1

12.7

7.8

13.8

12.2

6.7

2.1

7.1

Foreign joint venture

16.2

19.3

20.0

26.3

11.0

13.3

9.4

10.7

─

25.5

Ethnic Indian

21.7

12.8

11.4

3.7

─

─

─

─

─

─

Pribumi

7.8

7.2

6.5

7.4

6.5

5.20

2.5

8.9

6.8

6.8

Ethnic Chinese

9.6

7.6

5.7

8.6

5.6

6.0

5.6

6.4

6.1

6.1

Before-tax profit ratio

Government controlling

8.4

8.9

5.3

14.8

12.6

6.6

9.6

14.0

14.5

14.5

Foreign joint venture

15.2

16.8

8.9

17.8

15.2

12.9

11.2

14.8

15.1

15.1

Ethnic Indian

8.5

7.5

5.8

7.2

3.3

-4.7

1.3

1.1

0.4

0.4

Surplus ratio
Pribumi

8.5

18.7

11.5

14.1

14.1

11.9

20.1

18.2

17.7

17.7

Ethnic Chinese

11.2

16.8

13.9

17.3

17.5

19.5

21.2

20.6

21.9

21.9

Government controlling

16.4

17.5

12.7

22.2

21.4

22.1

16.9

25.9

27.1

27.1

Foreign joint venture

22.1

33.9

18.6

27.3

30.6

31.6

35.3

33.1

32.5

32.5

Ethnic Indian

15.2

17.2

12.1

13.1

10.9

7.8

13.0

13.9

13.2

13.2

Pribumi

37.5

39.2

34.3

31.3

28

30.2

28.9

32.8

34.9

36.7

Ethnic Chinese

38.0

40.2

40.6

40.7

39.9

39.2

41.0

39.3

39.5

38.4

Government controlling

44.9

47.8

58.1

54.5

39.8

34.1

35.3

39.6

52.5

53.4

Foreign joint venture

31.8

45.1

41.8

41.4

31.1

31.4

34.5

34.7

38.3

36.2

Ethnic Indian

35.4

44.3

56.3

52.4

39.6

46.5

46.0

55.1

53.5

50.8

Fixed asset ratio

21

（Table 3-2）Comparison of Core and Non-core Companies
1994

Total debt ratioCore
Non-core
Short-term debt ratioCore
Non-core
Long-term debt ratioCore
Non-core
Short-term bank borrowing ratioCore
Non-core
Before tax profit ratioCore
Non-core
Surplus ratioCore
Non-core
Fixed asset ratioCore
Non-core

1995

1996

1997

2000

2001

2002

2003

2004

2005

46.7

50.5

54.2

69.6

50.3

46.6

44.8

46.6

49.2

49.6

43.5

47.8

49.7

63.2

42.8

38.9

38.7

42.5

43.9

44.6

31.7

34.3

33.6

44.3

29.8

29.9

28.0

28.7

28.3

29.4

32.5

36.8

36.1

45.8

30.4

30.0

28.4

28.7

29.8

29.0

15.1

16.4

21.8

25.7

20.7

16.8

17.3

17.8

20.9

20.2

10.6

11.7

15.2

20.9

13.9

10.6

11.1

13.8

14.2

15.6

15.0

15.5

15.3

21.6

8.8

12.3

10.2

9.7

4.8

9.0

17.1

18.5

19.3

25.1

13.4

13.1

11.0

11.1

11.6

17.4

38.3

40.9

42.4

42.0

40.8

38.7

41.6

41.1

41.8

40.7

34

43.1

39.8

39.0

30.4

32.4

32.4

32.4

35.7

35.2

8.7

8.2

6.4

─

9.3

6.6

7.4

7.8

8.7

8.8

14.5

12.7

6.5

─

13.1

10.3

8.1

5.6

9.6

8.6

11.3

18.3

12.5

8.6

17.8

19.2

21.5

23.9

22.4

24.4

18.4

25.9

19.0

14.1

21.5

21.4

20.6

25.7

24.8

23.3

（Table 3-3）Comparison of Restructured and Non-restructured Companies
1994

Total debt ratio
Restructured
Non-restructured
Short-term debt ratio
Restructured
Non-restructured
Long-term debt ratio
Restructured
Non-restructured
Short-term bank borrowing ratio
Restructured
Non-restructured
Before tax profit ratio
Restructured
Non-restructured
Surplus ratio
Restructured
Non-restructured
Fixed asset ratio
Restructured
Non-restructured

1995

1996

1997

2000

2001

2002

2003

2004

2005

42.9

51.2

51.6

69.8

42.4

34.5

36.9

44.0

49.0

50.4

46.3

49.1

52.9

66.7

48.5

45.7

43.7

45.2

46.3

46.3

29.6

37.5

34.1

45.1

27.9

27.3

27.3

27.2

30.9

31.0

32.6

34.5

34.5

44.7

30.7

30.7

28.5

29.1

28.2

28.5

13.3

14.8

18.0

24.9

15.2

8.9

10.9

16.8

18.1

19.4

13.5

14.8

20.1

23.9

18.6

15.6

15.8

16.1

18.1

17.8

15.0

18.2

15.7

24.2

14.5

11.0

6.9

8.0

9.6

16.8

15.8

15.9

16.7

22.1

9.8

13.0

11.3

10.7

6.0

10.3

13.3

14.8

18.0

24.9

15.2

8.9

10.9

16.8

18.1

19.4

13.5

14.8

20.1

23.9

18.6

15.6

15.8

16.1

18.1

17.8

13.2

13.5

5.9

─

8.3

6.7

5.3

3.7

6.4

6.4

10.0

8.7

6.6

─

11.7

8.9

8.5

7.6

10.0

9.7

13.3

14.8

18.0

24.9

15.2

8.9

10.9

16.8

18.1

19.4

13.5

14.8

20.1

23.9

18.6

15.6

15.8

16.1

18.1

17.8

22

(Table 4-1) Basic statistics and correlation matrix

Statistics

Correlation Matrix
Debt ratios

DA1
DA2
DA3
DA4
RISK
TAX
RE
FIX
SIZE

Mean
0.549
0.188
0.361
0.157
0.090
0.013
0.155
0.400
5.591

Std
0.219
0.171
0.190
0.143
0.308
0.156
0.207
0.242
0.556

DA1
1.000
0.549
0.657
0.399
0.025
-0.073-0.218-0.009
0.266

DA2

DA3

DA4

RISK

TAX

RE

FIX

SIZE

1.000
-0.269-0.210-0.059-0.055-0.205
0.217
0.466

1.000
0.649
0.083
-0.034-0.066-0.207-0.1141.000
0.096-0.015-0.035-0.091-0.1751.000
0.000-0.050-0.020-0.1351.000
0.012-0.042-0.0071.000
0.335-0.1081.000-0.0191.000

23

(Table 5-1) Estimation Results of Debt Ratios
Total debt-ratio（TDR ）Long-term debt ratio（LDR ）Short-term debt-ratio (SDR )Short-term bank debt ratio（SBDR ）coefficent t-value
P-valuecoefficent t-value
P-valuecoefficent t-value
P-valuecoefficent t-value
P-value
RISK
0.001
0.024
0.981
-0.098-2.2960.022 **
0.103
2.023
0.043 **
0.062
1.608
0.109
TAX t-1-0.468-4.3340.000 ***
-0.153-1.7730.077 *
-0.285-2.7790.006 ***
-0.087-1.101
0.271
RE t-1-0.077-2.2070.028 **
-0.078-1.9760.049 **
0.022
0.466
0.641
0.028
0.923
0.356
FIX t-1-0.054-1.487
0.137
0.020
0.585
0.559
-0.097-2.4460.015 **
-0.038-1.2450.214
SIZE t-1
0.036
1.619
0.106
0.085
4.643
0.000 ***
-0.064-2.9300.003 ***
0.012
0.385
0.700
AF*RISK
0.115
0.920
0.358
-0.107-1.082
0.280
0.214
1.809
0.071 *
0.247
2.108
0.036 **
AF*TAX t-1
0.486
4.324
0.000 ***
0.182
2.027
0.043 **
0.266
2.493
0.013 **
0.087
1.047
0.296
AF*RE t-1
-0.112-2.1120.035 **
-0.007-0.1450.885-0.121-2.0580.040 **
-0.021-0.3770.706
AF*FIX t-1
0.124
2.298
0.022 **
0.077
1.663
0.097 *
0.056
1.008
0.314
0.068
1.171
0.242
AF*SIZE t-1
0.034
1.706
0.088 *
-0.026-1.601
0.110
0.074
3.788
0.000 ***
0.004
0.149
0.881
BM*RISK-0.003-0.011
0.991-0.170-0.751
0.453
0.146
0.541
0.588
0.506
1.212
0.226
BM*TAX t-1
0.468
4.333
0.000 ***
0.153
1.771
0.077 *
0.285
2.780
0.006 ***
0.115
0.663
0.508
BM*RE t-1
-0.123-2.0170.044 **
-0.041-0.7460.456-0.104-1.6050.109-0.140-1.0240.306
BM*FIX t-1
0.016
0.259
0.796
0.030
0.580
0.562
-0.012-0.1870.852-0.041-0.316
0.752
BM*SIZE t-1-0.018-0.8530.394-0.045-2.6770.008 ***
0.043
2.127
0.034 **
0.023
0.379
0.705
YD1996
0.009
0.631
0.528
0.022
1.795
0.073 *
-0.005-0.3270.744-0.011-0.895
0.371
YD19970.164
10.5380.000 ***
0.058
4.558
0.000 ***
0.112
7.442
0.000 ***
0.056
4.164
0.000 ***YD2001-0.224-2.0380.042 **
0.152
1.667
0.096 *
-0.454-4.1770.000 ***
-0.080-0.611
0.541
YD2002-0.246-2.2220.027 **
0.139
1.514
0.131
-0.464-4.2400.000 ***
-0.092-0.6980.485
YD2003-0.223-2.0070.045 **
0.149
1.613
0.107
-0.452-4.1190.000 ***
-0.088-0.6690.504
YD2004
0.126
1.124
0.262
0.298
3.247
0.001 ***
-0.254-2.3240.020 **
-0.124-0.331
0.741
YD2005
0.135
1.208
0.227
0.303
3.312
0.001 ***
-0.251-2.2960.022 **
-0.072-0.192
0.848
The number of
1137
1100
1100
684
The number of individuals
235
233
233
208
Adjusted R-square
0.662732
0.623827
0.561545
0.145489
F-statistics （A,B=Ai,B）
5.8182 ***4.3464 ***4.8027 ***4.8009 ***Hausman's test
Fixed
Fixed
Fixed
Fixed
note) *, **, and *** singnificant at 10, 5, and 1percent level, respectively.

24

(Table 5-2) Estimation Results of Company’s Fixed Effects
Total debt-ratio（TDR ）Long-term debt ratio（LDR ）coefficent t-value
P-valuecoefficent t-value
P-value
C
0.217
9.418
0.000 ***
-0.319-18.7960.000 ***
Ethnic Chinese
0.061
2.915
0.004 ***
0.039
2.490
0.013 **
Government
0.046
1.311
0.190
0.054
2.131
0.033 **
Foreign
0.107
4.794
0.000 ***
0.017
1.004
0.315
Ethnic Indian
0.100
1.881
0.060 *
0.172
4.476
0.000 ***
Core
0.038
4.732
0.000 ***
0.020
3.408
0.001 ***
AF*Ethnic Chinese-0.028-1.2680.205-0.041-2.5170.012 **
AF*Government-0.005-0.1070.915-0.099-2.8540.004 ***
AF*Foreign-0.022-1.0480.295-0.019-1.2020.230
AF*Ethnic Indian-0.075-0.8760.381-0.122-1.9720.049 **
AF*Core-0.054-2.7090.007 ***
-0.012-0.805
0.421
AF*Restructured-0.022-1.8380.066 *
-0.013-1.5250.128
BM*Ethnic Chinese-0.050-1.9070.057 *
-0.053-2.7350.006 ***
BM*Government-0.065-1.1680.243-0.111-2.7890.005 ***
BM*Foreign-0.033-1.2740.203-0.032-1.6890.092 *
BM*Ethnic Indian-0.030-0.2480.804-0.113-1.317
0.188
BM*Core
0.026
1.013
0.311
0.036
1.966
0.050 **
BM*Restructured-0.006-0.432
0.666
0.000
0.048
0.962
Industory
Construction-0.056-1.1560.248-0.067-1.7400.082 *
Communicati-0.026-0.606
0.544
0.004
0.143
0.886
Hotel/Travel
0.010
0.316
0.752
0.052
2.163
0.031 **
Manufacturin
0.017
0.943
0.346
-0.028-2.1940.028 **
Mining-0.054-1.7770.076 *
-0.000-0.0100.992
Transportatio-0.002-0.087
0.931
0.061
2.965
0.003 ***
Retail0.050
1.939
0.053 *
-0.114-6.1340.000 ***
Real Estate
0.007
0.337
0.737
-0.035-2.1150.035 **The number of observations
1137
1100
Adjusted R square
0.079466
0.150402
F-statistics
4.92263 ***8.78213 ***note) *, **, and *** singnificant at 10, 5, and 1percent level, respectively.

25

Short-term debt-ratio (SDR )coefficent t-value
P-value
0.632
32.9530.000 ***
0.018
1.014
0.311
-0.011-0.368
0.713
0.099
5.215
0.000 ***
-0.070-1.620
0.105
0.017
2.582
0.010 ***
0.015
0.813
0.417
0.094
2.382
0.017 **
-0.009-0.500
0.617
0.048
0.685
0.493
-0.048-2.9370.003 ***
-0.009-0.910
0.363
0.004
0.175
0.861
0.050
1.104
0.270
-0.012-0.541
0.589
0.088
0.905
0.366
-0.008-0.4060.685-0.007-0.640
0.522
0.041
0.945
0.345
-0.028-0.8040.421-0.034-1.238
0.216
0.041
2.836
0.005 ***
-0.054-2.2060.028 **
-0.041-1.7650.078 *
0.160
7.606
0.000 ***
0.051
2.752
0.006 ***
1100
0.134875
7.85346 ***Short-term bank debt ratio（SBDR ）coefficent t-value
P-value
0.112
4.920
0.000 ***
0.024
1.282
0.200
-0.070-2.1990.028 **
0.042
2.014
0.044 **
-0.116-2.8190.005 ***
-0.017-2.5640.011 **
0.002
0.115
0.908
0.052
1.115
0.265
-0.035-1.591
0.112
0.000
0.000
1.000
-0.054-2.4180.016 **
-0.003-0.271
0.786
0.013
0.298
0.766
-0.036-0.4310.667-0.186-1.342
0.180
0.000
0.000
1.000
0.092
1.120
0.263
-0.042-1.9180.056 *
-0.132-2.2320.026 **
0.000
0.000
1.000
-0.034-1.0260.305-0.001-0.0670.946-0.052-1.3160.189-0.074-2.6060.009 ***
0.009
0.344
0.731
0.004
0.192
0.847
684
0.091759
3.76012 ***Appendix(Table A-1) Estimation Results of Short-term Bank Borrowing Ratio and Company’s Fixed Effects

RISK
TAX t-1
RE t-1
FIX t-1
SIZE t-1
AF*RISKAF*TAX t-1
AF*RE t-1
AF*FIX t-1
AF*SIZE t-1
BM*RISKBM*TAX t-1
BM*RE t-1
BM*FIX t-1
BM*SIZE t-1
YD1996
YD1997
YD2001
YD2002
YD2003
YD2004
YD2005The number of observations
Adjusted R-square
F-statistics （A,B=Ai,B）
Hausman's test

Short-term bank debt ratio（SBDR ）coefficent
t-valueP-value
0.063
1.636
0.103
-0.090-1.143
0.254
0.025
0.831
0.406
-0.037-1.207
0.228
0.008
0.259
0.796
0.250
2.130
0.034 **
0.089
1.064
0.288
-0.028-0.501
0.617
0.076
1.303
0.193
0.007
0.294
0.769
0.733
19.0130.000 ***
0.099
1.259
0.209
-0.150-1.0550.292-0.048-0.374
0.708
0.028
0.448
0.654
-0.010-0.849
0.396
0.056
4.126
0.000 ***
-0.100-0.7660.444-0.115-0.109-0.147-0.096-0.870-0.821-0.387-0.251C
Ethnic Chinese
Government
Foreign
Ethnic IndianCore
AF*Ethnic Chinese
AF*Government
AF*Foreign
AF*Ethnic Indian
AF*CoreAF*Restructured
BM*Ethnic Chinese
BM*Government
BM*Foreign
BM*Ethnic Indian
BM*CoreBM*Restructured
Industory
Construction
Communicatio
Hotel/Travel
Manufacturing
MiningTransportation
RetailReal Estate

0.385
0.412
0.699
0.802

The number of observations
Adjusted R square
F-statistics

683
0.999946
4.7538 ***Fixednote) *, **, and *** singnificant at 10, 5, and 1percent level, respectively.

26

Short-term bank debt ratio（SBDR ）coefficent
t-valueP-value
0.134
5.896
0.000 ***
0.023
1.200
0.230
-0.070-2.2130.027 **
0.040
1.950
0.052 *
-0.116-2.8250.005 ***
-0.017-2.4950.013 **
0.004
0.174
0.862
0.052
1.136
0.256
-0.032-1.472
0.141
0.000
0.000
1.000
-0.056-2.5080.012 **
-0.004-0.322
0.748
0.013
0.295
0.768
-0.036-0.4270.669-0.179-1.296
0.196
0.000
0.000
1.000
0.087
1.062
0.289
-0.041-1.9080.057 *
-0.1320.000-0.035-0.001-0.054-0.0760.010
0.006-2.2400.025 **
0.000
1.000
-1.0750.283-0.0680.946-1.3630.173-2.6600.008 ***
0.380
0.704
0.262
0.794
683
0.09172
3.75478 ***