FUNDMOBILIZATIONAND
IN THAILAND
Asian
Economic
JournalNo.
[AsianEconomic
Journal2006,
1998,Vol.
Vol.20
12INVESTMENT
No.1,3]95–122

95

Fund Mobilization and Investment
Behavior in Thai Manufacturing Firms
in the Early 1990s*
Fumiharu Mieno
Received 18 November 2004; accepted 21 November 2005

This paper investigates capital structure and investment behavior in Thailand in
the early 1990s. Various features of ﬁnancial markets are considered, and thepossibility of applying the ‘pecking order hypothesis’ to developing countries isdiscussed. By estimating the determinants of the capital structure and the investment functions, three major results are obtained. First, the lower debt ratio oflisted ﬁrms is realized by an increase in the capital surplus gained by initial public
offering. Second, ﬁrms’ participation in the securities market accommodates agency
costs both in the equity and bank-loan markets. Third, ‘ﬁnancial conglomerate’
ﬁrms are inactive investors and are dependent upon informal ﬁnancial transactions,whereas foreign ﬁrms borrow less and invest more.
Keywords: capital structure, investment, ﬁnancial system, Thailand.
JEL classification codes: E22, G32, O16.

I. Introduction
The purpose of this paper is to investigate features of capital structure and theireffects on investment behavior in Thai manufacturing ﬁrms, including non-listed
ﬁrms, in the ﬁrst half of the 1990s. After the ﬁnancial crisis of 1997, thefundraising behavior of Thai ﬁrms, particularly their excess dependence on debt
ﬁnancing, was criticized in academic and policy research. Most studies cite thevulnerability of high debt ﬁnancing as a major cause of the ﬁnancial crisis anddiscuss ways of diversifying ﬁrms’ fundraising behavior by using the capital
market through equity ﬁnancing or issuing bonds (e.g. Claessens et al., 1998;
World Bank, 1998).
However, the existing published empirical studies have not completely elucidated Thai ﬁrms’ capital structures and their effects on investment behavior both
before and after the crisis. Observing the corporate ﬁnancial structure in the* Graduate School of International Cooperation Studies, Kobe University, 2-1 Rokkodai, Nadaku, Kobe 657-8501, Japan. Email: fmieno@kobe-u.ac.jp. I would like to thank Juro Teranishi,
Hidenobu Okuda, Hiro Lee, and an anonymous referee for insightful comments on earlier versionsof the paper. The research for this paper was supported by Japan Society for the Promotion of
Science’s Grant-in-Aid for Scientiﬁc Research No. 15730160. The author is solely responsible forany errors that remain.
doi: 10.1111/j.1467-8381.2006.00226.x

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early 1990s, Amano and Mieno (1998) identify several characteristics, including
the ‘estranged’ relationship between banks and manufacturing ﬁrms in ﬁnancialgroups. Wiwattanakantang (1999) examines the determinants of the capital structures of ﬁrms listed on the Stock Exchange of Thailand (SET) in 1994, focusing
on ﬁrm ownership and business group afﬁliation. She ﬁnds that the concentration of shares is negatively correlated with the debt ratio, and that ﬁrms owned
by single families have relatively high debt ratios.1
Several cross-country comparative studies refer to Thai corporate ﬁnancial
structure. Singh and Hamid (1992) point out that the debt ratios in developing
countries (including Thailand) were generally high in the 1980s. Conversely,
Claessens et al. (1998) assert that excessive dependence on indirect ﬁnanceamong Asian countries in the 1990s was a major cause of the ﬁnancial crisis.2
Although previous studies have brought some issues to light, unresolved
issues remain. The ﬁrst relates to sample selection problems. Most existingstudies, including Wiwattanakantang (1999) and Claessens et al. (1998), cover
only some of the companies listed on SET. However, in Thailand (as in mostdeveloping countries), only a limited number of major ﬁrms participate inorganized securities markets. Moreover, their listing behavior might depend on
aspects of ownership, such as business group afﬁliation or nationality, suggesting that ﬁrms’ listing behavior is itself a kind of fund mobilization. Accordingly,
restricting analysis to listed ﬁrms might induce sample-selection bias. Second,most studies focus only on the debt ratio (leverage). However, in developing
countries, the share of formal debt composition in total liabilities is generally
low, and informal ﬁnancial transactions represent a large share of total liabilities.
Because informal ﬁnancial transactions are signiﬁcant in developing economies
and their agency cost structures might differ from bank loans or bond issues, it
is important to focus on these transactions.
The present paper aims to overcome the limitations of the existing studies.
First, in relation to the dataset, both listed and non-listed ﬁrms in those manufacturing sectors that have driven Thai industrialization are covered. Second, in
addition to the debt ratio, bank borrowing and informal borrowing compositions
are examined. Total bank loans and their decomposition into short-term andlong-term loans are evaluated. Third, a neoclassical-type investment function
is estimated to examine the effect of fund-mobilizing methods on equipment
investment.3

1. In relation to this argument, Wiwattanakantang (2001) and Suehiro (2000) examine thecorporate governance structure of Thai ﬁrms. Suehiro presents a skeptical, suspicious view of linear
causality between the governance structure and corporate performance.
2. Booth et al. (2001) stress that simple application of the general theory of the determination of
the capital structure is not rational for developing countries.
3. Amano and Mieno (1998) attempt to estimate a Tobin’s-Q type investment function for Thaimanufacturing ﬁrms to investigate their investment behavior in relation to subsidies. However, stableestimation results are not obtained.

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This paper proceeds as follows. Section II summarizes ﬁrms’ fundraising andinvestment behavior in Thailand and examines its determinants. Aggregated data
and descriptive measures are presented in Section III, followed by empiricalinvestigations of the capital structure and investment behavior using ﬁrm-level
micro data in Sections IV and V, respectively. Section VI concludes the paper.
II.

Determinants of Bank Loans and Investment

II.1 Agency costs, fundraising and investment
Myers (1984) and Myers and Majluf (1984) point out the difference between
capital costs in internal ﬁnance and debt ﬁnance arising from agency costs. They
also present a notion of ﬁrms’ preferences in fundraising methods, known as
the ‘pecking order hypothesis’, in the context of which the model is simpliﬁed
to allow only two types of method: equity and debt. Based on this hypothesis,
a series of empirical studies on developed countries, following the pioneering
work of Fazzari et al. (1988), reveal that the capital costs for investment depend
upon the fundraising method. Speciﬁcally, the lower the agency costs associatedwith the fundraising method, the lower are the capital costs. Recently, therelevant discussions have been further developed to form the ﬁeld of comparative ﬁnancial systems. Allen and Gale (2000) compare ﬁnancial systems
in developed countries, focusing on the determinants of bank-based or marketbased features, and discuss possible explanations from the viewpoint of agency
costs, informational asymmetry and treatment of risk.4
Taking into account features of ﬁnancial markets in developing economies,
the following modiﬁed determining mechanisms should be considered in ananalysis of capital structure and average capital cost. First, ﬁrms face restrictions
on using particular methods because of factors such as the absence of the bondmarket and limited access to the capital market, particularly for non-listed ﬁrms.
Second, under this environment, the composition of each method is determinedin equilibrium where all transaction costs, or agency costs, are equal. Third,
investment is determined by the minimum average capital cost given the
expected earnings of the investment.
When the pecking order hypothesis is applied to developing countries, more
subtle factors should be taken into account. Several methods of fund mobilization are absent, or at least underdeveloped, and some methods are available only
to particular ﬁrms. First, corporate debt and equity markets work only forﬁrms that participate in organized capital markets where they exist. Second, the
4. In regard to developing economies, Herring and Chatusripitak (2000) discuss why they lackbond markets and, consequently, have bank-oriented systems from the perspective of the features ofa market-based debt contract and an equity contract. They also point out that the absence of a bondmarket creates instability and inefﬁciency in other markets because of the failure of correct pricingof risk in the market place.

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market for bank loans works effectively only in places where banks provide
information efﬁciently and agency costs are sufﬁciently low to make transactions feasible. These two issues are raised as crucial problems for the analysis
of developing economies.
Underdevelopment of capital markets and firm behavior when going public
Capital markets do not function effectively as sources of fundraising in mostdeveloping countries. Although there are organized capital markets in whichinvestors place funds in most developing countries, the role of the capital market
in mobilizing funds for ﬁrms is limited in many countries. For company owners,
participation in the capital market is the only alternative, given its merits as asource of ﬁnance and its disadvantages, which are a result mainly of diluting
control rights originally assigned to the owners or their families. Hence, forﬁrms, the choice of equity ﬁnance as a fundraising method is made in twostages: participation in the market (initial public offering (IPO)); and issuing
new bonds or equity. Furthermore, it is noteworthy that the IPO itself could
represent important fundraising behavior as it gains ﬁrms a stock premium.
Two types of informal credit channel
In developing countries, loan–debt ratios are not necessarily high, and a largepart of debt composition consists of informal factors or funds from internal
capital markets. Allen and Gale (2000) point out that it is inevitable that internalﬁnance will become dominant when there are serious agency costs and information asymmetries. They insist that ﬁrms generally prefer internal cash to externalﬁnance because of the existence of agency costs, and that shareholders mightallow managers to retain cash in hand as a second-best optimal strategy even if
their interests are not perfectly aligned. Moreover, ﬁrms exert ﬁnancial functions
to provide and receive funds in order to allocate their surpluses most efﬁciently.
In some particular cases, the transactions could be more stylized to form aninternal capital market between business groups.5
In our empirical observations, informal ﬁnance is classiﬁed into two forms.
The ﬁrst is credit from the usual trade ﬁnance, which is approximately equal toaccounts payable and deferred payments in the balance sheet. The second
is credit from an internal capital market of related parties such as owners,
managers, afﬁliated ﬁrms and subsidiaries. The latter is considered to be closer
to self-ﬁnance rather than debt because the agency costs are close to zero. It is
referred to as ‘quasi self-ﬁnance’.
In sum, this paper examines six signiﬁcant fundraising methods: (i) self-ﬁnance;(ii) quasi self-ﬁnance; (iii) bank borrowing; (iv) informal debt; (v) equity ﬁnance;
5. Moreover, Herring and Chatusripitak (2000) discuss the possibility that when a bond market isabsent, ﬁrms have an incentive to afﬁliate with a bank to create an internal ﬁnance chain andvirtually assure their long-term debt. In such cases, the business groups grow to become ﬁnancial
conglomerates.

FUND MOBILIZATION AND INVESTMENT IN THAILAND

99

and (vi) stock premiums gained by IPO. The function of long-term credit is also
analyzed by discomposing (iii), bank borrowing, into short-term and long-termborrowing. The pecking order or the level of agency costs, in the sense of Myers(1984), is expected to be such that (i) < (iii) < (v) and (i) < (iv) < (v). The agency
costs of (ii) and (vi) are thought to be close to that of (i) or zero. The difference
between the agency costs of (iii) and (iv) is unclear. Short-term borrowing andlong-term borrowing are thought to be equivalent to (iii) in relation to agency
costs.
II.2 Corporate ownership and the capital market in Thailand
This subsection examines how the unique features of the ﬁnancial system andﬁrms in Thailand can be combined with the above discussions on agency costs
and comparative ﬁnancial system issues to create an analytical framework.
Business groups in Thailand
The ﬁrst factor that might inﬂuence the capital structure of Thai ﬁrms is therelationship between ﬁrms and business groups. Most Thai business groups
originated from export merchants dealing in primary products such as sugar, rice
and wooden products. These groups have been operating since the late 1940s.
Thai business groups usually comprise a core (or parent) company and many
afﬁliated companies owned by owner-families, family-owned holding companies and cross-holdings (Suehiro, 1989).
Suehiro (1989) classiﬁes Thai business groups into three categories based on
their origins and major businesses: the ﬁnancial conglomerates, the industry
group, and the agribusiness group.6 Suehiro ﬁnds that ﬁnancial conglomerates
generally limit their business activities to the ﬁnance and commerce sector andare wary of engaging in manufacturing. The industry group and the agribusinessgroup are generally excluded from commercial banking and credit channels.
Hence, they tend to establish joint ventures with foreign capital to expand theirbusinesses.
Commercial banks emerged in Thailand after World War II and were formed
as a part of, and have grown simultaneously with, the ﬁnancial conglomerates(which have developed their businesses primarily in non-manufacturing sectors).
Before the mid-1980s the share of commercial bank loans for the manufacturingsector was negligible, and before the ﬁnancial crisis of 1997 their ownershipwas concentrated among particular families, although ownership gradually
diversiﬁed after commercial banking laws were amended in 1979.
Considering the development process of industries and the ﬁnancial systemfrom a historical perspective, the unique features of the Thai ﬁnancial system are
6. The ﬁnancial conglomerates group centers on the commercial banks. The industry group
includes those that have been expanding mainly in the textile and apparel industry, and the footwear
industry since the 1960s. The agribusiness group is based on exporters of agro-products.

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observed. First, given that the bond market has remained virtually non-existentand the equity market underdeveloped, the role of banks’ intermediation isbiased and limited because bank loans are directed almost exclusively to theﬁnancial conglomerates. Although commercial banks have grown rapidly sincethe 1960s, their information-processing functions have remained inefﬁcient andunstable. Instead, banks have behaved as part of the internal ﬁnancial tools ofsome non-manufacturing sectors. Second, it is highly possible that self-ﬁnanceand internal ﬁnancial transactions were the most common form of fund-mobilization in the manufacturing sector amongst ﬁrms without afﬁliated banks. Thismight have been the result of prohibitively high agency costs for external ﬁnancecaused by imperfect functioning of banks outside their own business groups.
In the context of the history of the banking sector in Thailand, two factors forcommercial banks should be considered. First, bank loans might not play asigniﬁcant role in ﬁrms’ fund mobilization because banks are merely ﬁnancial
entities for each ﬁnancial conglomerate and have limited capability for ﬁnancial
intermediation.7 Second, the availability of bank loans for individual ﬁrms might
depend upon the features of the business groups to which the ﬁrms belong.
Foreign firms
Foreign ﬁrms have played a signiﬁcant role in Thailand’s economic development. In the context of establishing new local ﬁrms, the most popular form is a
joint venture in which both foreign multinational corporations and local partners
invest. The Alien Business Law typically limits the foreign ﬁrm’s share to 50
percent. The following possibilities in relation to the fundraising behavior of
foreign ﬁrms are considered. First, these ﬁrms might be able to retain links with
their parent companies in the form of intra-ﬁrm credit and capital increases.
Second, foreign ﬁrms are more accessible to the local branches of foreign banksfrom the same country because informational asymmetries are reduced by links
to the parent companies and foreign banks in the home countries.
Firms’ participation in the securities market
The Securities Exchange of Thailand (the SET from 1991) was established in
1975. However, it was not until 1992 when comprehensive reforms to the capital
market were implemented to relax rules on listing, which activated transactionsin the Thai securities market. The number of listed ﬁrms peaked at 454 in 1996,
just before the ﬁnancial crisis. However, even in the early 1990s, the number oflisted ﬁrms was less than half that of major ﬁrms. In Thailand not all major ﬁrms
use the securities market for fund mobilization, and participation in the market isa matter of choice for individual ﬁrms.
Underdevelopment of the securities market is related to two importantfeatures of ﬁrms’ capital structure. First, their afﬁliation to business groups

7. This implies that informal ﬁnance or alternative methods might be widely used.

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101

might inﬂuence their participation in the securities market. By listing on themarket, individual ﬁrms can diversify their methods of fund mobilization throughequities and bonds. However, they have to release their control rights because of
the rules and the regulations of the listing code. Hence, whether ﬁrms list isdetermined by factors such as the availability of alternative fundraising methods
and ﬁrms’ attitudes to giving up control rights. Group-afﬁliated ﬁrms might
hesitate to participate in the securities market to retain control rights. Financial
conglomerate ﬁrms might be more reluctant to participate because they might
have internal fund channels with commercial banks.
Second, listing might have indirect effects on ﬁrms’ capital structures in thedeveloping ﬁnancial markets, where bank loans are unevenly distributed. Listing
realizes the disclosure and diffusion of company information, which reduces theagency problem in ﬁnancial markets overall. Therefore, it might also stimulatebank lending in the indirect ﬁnancial market.
II.3 The macroeconomic environment in the 1990s
Based on these features of corporate ownership and capital markets, the Thaiﬁnancial market experienced tremendous environmental changes from the early
to mid-1990s under ﬁnancial liberalization. This time-speciﬁc factor might haveinﬂuenced the ﬁrms’ fund mobilization behavior in our analysis.
Financial liberalization in Thailand began with a gradual relaxation ofoperative regulations in the late 1980s. After 1990, the reform was extended tocover various banking operations to enhance competition between the ﬁnancial
institutions. After 1993, the reforms continued with the relaxation of foreign
capital regulations, particularly the regulations governing capital inﬂows throughcommercial banks. After the offshore market (Bangkok International Banking
Facilities (BIBF)) was founded in 1992, the inﬂow of foreign capital in the formof borrowed funds, particularly short-term capital ﬂows, increased rapidly. Net
capital inﬂows surged from 262 billion baht in 1991 to 518 billion baht in 1995.
It is widely believed that ﬁrms expanded their borrowings in terms of foreign
currency and undertook unproductive investments.
The macroeconomic environment is likely to have inﬂuenced the corporateﬁnance structure. First, the role of commercial bank loans in ﬁrms’ fundraisingmight have strengthened during this period, as reﬂected in the inﬂow of foreign
capital through the banking sector from the offshore market.8 Second, booming
securities markets might have activated equity ﬁnance. The extent of the boom
can be gauged from the fact that 30–40 ﬁrms implemented IPO every year in the
period from 1988 to 1996.

8. Claessens et al. (1998) point out the trend towards increasing debt ratios in the 1990s and argue
that this was a major reason why Thailand was vulnerable to the ﬁnancial distress that occurred in
1997.

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III.

102

Descriptive Measures

III.1 The data
This section describes the trends in ﬁrms’ capital structures and investment
behavior using the present study’s dataset. The sample data used for analysis are
ﬁrm-level ﬁnancial data on 320 major manufacturing ﬁrms, including listed andnon-listed ﬁrms, from 1991 to 1995. There are a total of 748 observations.9 The
information on ﬁrm proﬁles is based on Manager Information Services (1996),
which covers 992 manufacturing ﬁrms. The ﬁnancial data on each ﬁrm are fromthe database provided by the same information services company, which covers
2164 manufacturing ﬁrms. Matching the two sets of information has produced
data on 685 ﬁrms. The data on 320 large-sized ﬁrms, deﬁned as those ﬁrms
possessing total assets over 1 billion baht, are used because information on thebusiness-group afﬁliations of smaller ﬁrms is virtually unavailable, and mostsmall ﬁrms are non-listed ﬁrms.10 This group of large-sized ﬁrms comprises 111
listed ﬁrms and 209 non-listed ﬁrms.
The procedure used to identify afﬁliation to business group and foreign ownership is as follows. Suehiro (1989, 2001) classiﬁes the 65 major Thai businessgroups and their associated ﬁrm afﬁliations primarily on the basis of group or
ﬁrm histories and ownership. He also classiﬁed business groups into three types:
ﬁnancial conglomerates, industry groups and agribusiness. Based on thisclassiﬁcation, the afﬁliations of the 320 ﬁrms to 27 major business groups are
conﬁrmed. The business groups are also classiﬁed into two categories: ﬁnancial
conglomerates and manufacturing groups, where manufacturing groups consistof industry groups and agribusiness from Suehiro’s (1989) classiﬁcation.
Foreign ﬁrms are deﬁned as those in which more than 40 percent of the shares
are owned by foreign ﬁrms, based on Suehiro (2000) and various company
directories.11
III.2 Distribution of the samples
Tables 1 and 2 present the characteristics of the distribution of the samples.
According to Table 1, the largest numbers of ﬁrms are in the manufacturinggroups and foreign ﬁrms, followed by ﬁnancial conglomerates. The table seems

9. This indicates that the dataset used in the present study is unbalanced panel data.
10. The deﬁnition of ‘large ﬁrms’ follows the criteria adopted by the Industrial Financial Corporation of Thailand in 1998. In 1996, the total number of listed ﬁrms was 454, and between 120 and 140of them could be regarded as manufacturing ﬁrms according to the industrial classiﬁcation in ‘Financial Day 2000’. This means that the sample covers more than 78 percent of all listed manufacturingﬁrms and non-listed manufacturing ﬁrms of a similar size.
11. The Alien Business Act of the early 1990s does not allow foreigners to hold more than 50
percent of the shares in a Thai company. Hence, the investment shares of multinational corporations
are usually between 40 and 49 percent at most.

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103

Table 1 Number of samples and firms
Total

Samples
1991
1992
1993
1994
1995
Total
Firms
Full Panel
4 years
3 years
Total

Financialconglomerate

Foreignowned

Others

19
20
20
20
21
100

66
64
66
67
62
325

200
214
220
225
212
1071

285
298
306
312
295
1496

106
109
109
110
109
543

18
2
1
21

52
15
2
69

178
34
18
230

248
51
21
320

104
4
3
111

Listedto support the suggestion of Suehiro (1989) that private capital formation
resulted in segregation between ﬁnancial conglomerates, which developed
primarily in service sectors, and ﬁrms in the industry group, which developed
only in manufacturing sectors.
For 1994, the total number of ﬁrms in the sample is 312, which includes 110
listed ﬁrms. This implies that the samples cover the great majority of the listedﬁrms because the total number of listed ﬁrms in 1994 was 389 and the numberof ﬁrms in manufacturing sectors is thought to be 150–170. However, the numberof listed ﬁrms as a proportion of representative large-sized ﬁrms is no more than
35.2 percent. Table 2 indicates that listed ﬁrms have a relatively high share insome of the light industries, such as textiles and garment and wooden products,
whereas their share is relatively low in the heavy industries, such as fabricatedmetal and machinery, although this tendency is less marked than for lightindustries. According to the classiﬁcations for business group and ownership
nationality, there appear to be more listed ﬁrms among non-group ﬁrms, andfewer among ﬁnancial conglomerates and foreign ﬁrms.
III.3 Capital structure
Table 3 summarizes the balance sheets of the ﬁrms in 1994 by business groupand ownership type. Comparing listed and non-listed ﬁrms, the debt ratio of
the former (55.3 percent) is much lower than that of the latter (70.9 percent).
However, there is little difference in the bank-borrowing ratios (denominated bytotal assets). This implies that the difference in the debt ratios is a result of thedifference in other liabilities, such as debt from afﬁliated ﬁrms and deferredpayments. Equities are higher for listed ﬁrms, evidently because of different
capital reserves, rather than differences in paid-in capital or retained earnings.

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Table 2 Distribution of firms by type of business group
Industrial classification

Food processing
Textile and garment
Wooden products
Pulp and paper
Chemical products
Non-ferrous metal
Primary metal
Fabricated metal and machinery
Total

Financialconglomerate

Manufacturinggroup

Foreign owned

Listed(%)

Listed(%)

Listed
(%)

13
0
0
2
0
1
0
3
19

2
0
0
1
0
0
0
0
3

(15)
—
—
(50)
—
(0)
—
(0)
(16)

14
13
0
7
11
7
0
14
66

8
9
0
0
5
1
0
1
24

(57)
(69)
—
(0)
(45)
(14)
—
(7)
(36)

9
6
1
2
15
3
1
27
64

3
3
1
1
2
3
0
4
17

(33)
(50)
(100)
(50)
(13)
(100)
(0)
(15)
(27)

Others

Total

Listed
(%)
34
23
7
12
20
16
0
26
138

11
13
3
6
7
10
0
11
61

(32)
(57)
(43)
(50)
(35)
(63)
—
(42)
(44)

Listed
(%)
70
42
8
23
46
27
1
70
287

24
25
4
8
14
14
0
16
105

(34)
(60)
(50)
(35)
(30)
(52)
(0)
(23)
(37)

Notes: Based on the sample of 1994. —, no data.

104

FUND MOBILIZATION AND INVESTMENT IN THAILAND
Table 3

105

Capital structure classified by type of business group and ownership nationality
All firms

Listed ﬁrms
Debt
Bank borrowing
Short-termLong-term
Quasi self-ﬁnance
Borrowings from managers and employees
Borrowings from afﬁliated companies
OthersTrade accounts and note payable
OthersEquityPaid-in capital
Retained earnings
Capital surplus and others
Non-listed ﬁrms
Debt
Bank borrowing
Short-termLong-term
Quasi self-ﬁnance
Borrowings from managers and employees
Borrowings from afﬁliated companies
OthersTrade accounts and note payable
OthersEquityPaid-in capital
Retained earnings
Capital surplus and others

Foreignowned(%)

Non-group(%)

Financialconglomerate
(%)

55.3
42.6
24.5
18.1
0.7
0.0
0.6
10.6
5.3
6.7
44.8
13.8
20.0
10.9

55.7
50.0
45.2
4.8
0.0
0.0
0.0
6.8
3.4
2.3
46.8
16.5
16.4
14.0

48.8
32.9
20.7
12.2
2.2
0.0
2.2
9.9
4.9
8.8
51.2
12.9
25.9
12.4

56.4
44.1
24.5
19.6
0.4
0.0
0.4
10.9
5.4
6.5
43.6
13.9
19.1
10.5

70.9
42.4
22.0
20.4
7.9
0.9
7.1
20.7
13.0
7.6
30.4
13.8
17.6
−1.0

81.8
23.2
11.8
11.4
13.6
1.0
12.6
45.0
10.6
34.4
18.2
12.2
6.7
−0.7

65.5
32.3
20.3
11.9
13.3
0.7
12.7
19.9
12.6
7.3
34.5
11.8
20.2
2.5

72.4
48.8
23.7
25.1
4.9
0.9
4.0
18.8
13.4
5.4
29.6
14.9
17.4
−2.7

(%)

Among non-listed ﬁrms included in ﬁnancial conglomerates, the bankborrowing ratio is unexpectedly below average, and higher in other liabilities,
resulting in a higher debt ratio. By contrast, among listed ﬁrms included inﬁnancial conglomerates, the ratio of other liabilities is lower, and that in bankborrowing is higher. For foreign ﬁrms, the debt ratio is approximately averagefor listed and non-listed ﬁrms, but the bank-borrowing ratio is lower.12
Table 4 reports capital structures by year, calculated from a 5-year full-panel
sample. For listed ﬁrms, structures hardly changed, except for a slight increase
12. This might suggest that foreign-owned ﬁrms depend on credit channels with parent multinational ﬁrms in the form of capital increases and intra-ﬁrm credit.

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Table 4 Capital structure classified by years (percent except number of samples)

Listed ﬁrms
Number of samples
Debt
Bank borrowing
Short-termLong-term
Quasi self-ﬁnance
Borrowings from managers and employees
Borrowings from afﬁliated companies
OthersTrade accounts and note payable
OthersEquityPaid-in capital
Retained earnings
Capital surplus and others
Non-listed ﬁrms
Number of samples
Debt
Bank borrowing
Short-termLong-term
Quasi Self-ﬁnance
Borrowings from managers and employees
Borrowings from afﬁliated companies
OthersTrade accounts and note payable
OthersEquityPaid-in capital
Retained earnings
Capital surplus and others

1991

1992

1993

1994

1995

84
58.5
44.7
21.6
23.1
1.3
0.1
1.2
12.5
5.8
6.7
41.5
13.8
16.1
12.2

84
57.1
45.1
23.2
21.9
1.1
0.1
1.0
10.9
5.4
5.5
43.4
13.7
17.4
12.8

84
57.1
35.8
21.4
14.4
1.6
0.7
0.9
19.7
7.1
12.6
42.9
13.7
17.3
14.3

84
55.6
43.4
24.1
19.2
0.4
0.0
0.4
11.8
5.3
6.5
44.4
13.5
19.9
14.3

84
60.7
47.7
24.7
23.0
0.8
0.0
0.8
12.1
5.2
6.9
40.3
12.1
19.0
13.6

90
77.7
48.2
19.2
29.0
3.9
0.7
3.2
25.6
15.2
10.4
23.1
14.1
10.4
1.8

90
77.9
50.2
22.3
27.9
4.6
0.5
4.1
23.1
14.4
8.7
22.7
13.1
10.3
2.1

90
78.2
50.4
21.4
29.0
4.1
0.8
3.3
24.0
16.4
7.6
22.2
12.7
11.4
2.5

90
71.5
48.2
22.4
25.7
4.9
1.0
3.9
18.4
13.7
4.7
29.5
14.1
16.9
2.7

90
69.7
45.9
22.2
23.6
3.6
0.4
3.2
20.2
12.5
7.7
31.4
13.6
18.0
3.4

in retained earnings from 1991 to 1995. For non-listed ﬁrms, there was a sharp
decline in the debt ratio after 1994, which was reﬂected by the increase inretained earnings. This implies that non-listed manufacturing ﬁrms had decreased
their debt ratios by increasing their dependence on self-ﬁnancing when theeconomy was expanding. In addition, it is noteworthy that the bank-borrowing
ratio for non-listed ﬁrms exhibited a stable declining trend for long-term borrowing, implying that the term composition of bank loans changed to a more
short-term basis. This suggests that non-listed ﬁrms were not dependent on thebank loan market for fundraising and that they reduced their dependence on debt
and bank lending, despite the expansion of the real economy and increased

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Table 5 The Level of equipment investment classified by year
(percent except where noted)

Listed ﬁrms
Fixed asset /TA
Rate of change
Investment/TA
Average TAa
Rate of change
Non-listed ﬁrms
Fixed asset/TA
Rate of change
Investment/TA
Average TAa
Rate of change

1991

1992

1993

1994

1995

43.5
—
—
2462
—

43.1
14.1
6.15
2838
15.3

38.4
−0.9
− 0.38
3155
11.2

40.0
24.0
9.21
3760
19.2

38.2
13.4
5.37
4465
18.7

40.6
—
—
2040
—

37.9
24.8
10.1
2729
33.8

37.6
13.3
5.1
3119
14.3

49.3
52.8
19.9
3637
16.6

48.7
23.9
11.8
4559
25.3

Notes: TA, total assets; —, no data. a Millions of baht.
Table 6 The level of equipment investment classified by business group andownership nationality (percent except where noted)

Listed ﬁrms
Fixed asset/TA
Investment/TA
Average TAa
Non-listed Firms
Fixed-asset/TA
Investment/TA
Average TAa

All firms

Financialconglomerate

Foreignowned

Others

38.7
5.3
3488

23.9
1.8
3206

35.6
6.9
3211

45.1
7.3
2549

43.2
10.9
3328

19.3
2.8
2024

46.5
10.7
3663

49.0
15.7
2779

Notes: TA, total assets. a Millions of baht.

inﬂows of foreign capital through the banking sector following ﬁnancial
liberalization of the 1990s.13
III.4 Equipment investment
Tables 5 and 6 report ﬁxed-asset ratios and equipment investment ratios (denominated by total assets) by type of business group and by year, respectively.
The ﬁxed assets of non-listed ﬁrms are generally greater than those of listed
ﬁrms. By business-group classiﬁcation, the ratio is higher for non-group ﬁrms
13. This ﬁnding is in a sharp contrast to the assertion that Thai ﬁrms became more dependent on
debt ﬁnance during the 1990s (e.g. Claessens et al., 1998).

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and foreign ﬁrms, and lower for ﬁnancial conglomerates. The time-series trend
is not clear, except for the sharp increase in 1994, when the Bangkok Offshore
Market began to operate.
There is no clear difference between the equipment investment ratios of listed
and non-listed ﬁrms. The trend in this ratio is very similar to that in the ﬁxedassets ratio. The ratio tends to increase, particularly after 1994.
III.5 Effects of initial public offering behavior
Table 7 reports the trend of changes in capital structure and equipment investment between the pre-IPO and post-IPO years. The data cover only the 77 ﬁrms
that ﬂoated on the SET between 1992 and 1995. Three interesting facts areobserved. First, in the year of IPO, debt ratios and bank-borrowing ratios
declined sharply, and capital surplus consequently increased. Second, one year
prior to IPO, debt ratios and bank-borrowing ratios were lower than average andretained earnings were above average. This suggests that ﬁrms’ efforts to satisfy
the IPO requirements set by the SET or the Securities and Exchange Committee
reduced ﬁrms’ dependence on debt ﬁnance. Third, bank-borrowing ratios
recovered slightly in the post-IPO period.
Importantly, long-term borrowing sharply declined in the year of IPO, and it
continued on its downward trend in the post-IPO period. By contrast, short-termborrowing increased following IPO. This suggests that increased cash ﬂow on

Table 7 Change of capital structures and equipment investment before andafter IPO (percent except where noted)
Period (0 = the period of IPO)
Number of samples
Debt
Bank borrowing
Short-termLong-term
Quasi self-ﬁnance
Borrowings from managers and employees
Borrowings from afﬁliated companies
OthersTrade accounts and note payable
OthersEquityPaid-in capital
Retained earnings
Capital surplus and others
Fixed asset/ TA
Investment / TA
Average TAa

−2
12
73.3
55.5
23.0
32.5
2.9
0.0
2.8
14.9
8.2
6.8
33.0
24.8
8.3
0.5
66.4
2.5
2703

−1
23
60.7
43.0
24.9
18.1
3.5
0.3
3.2
14.2
6.2
8.0
39.3
20.8
10.7
7.8
30.3
−15.6
2622

0
33
52.2
37.4
24.3
13.1
2.0
0.2
1.8
12.7
6.4
6.4
47.8
17.9
11.4
19.9
45.3
29.1
2449

Notes: IPO, initial public offering; TA, total assets. a Millions of baht.

1
40
54.8
39.4
27.3
12.1
1.4
0.1
1.3
14.1
6.7
7.4
45.2
16.7
11.0
17.9
41.2
7.3
2553

2
43
52.2
36.6
27.5
9.0
2.1
0.0
2.0
13.5
5.6
7.9
47.8
15.8
12.9
20.3
31.2
6.2
2617

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109

the equity side at going public substituted primarily for long-term borrowing on
the debt side.
It is noteworthy to observe that the shift in the capital structure towards
equity ﬁnance occurred only during the IPO period and the year preceding it,
seemingly caused by raising cash as capital increased. Despite the prosperity ofthe securities market on the surface during this period, Tables 4 and 7 give noclear evidence that listed ﬁrms continuously used the securities market as asource of equity ﬁnance, such as in the form of an increase in capital.14
There is a clear trend in equipment investment. Investment was evidently
restricted in the pre-IPO period and increased when the ﬁrm ﬂoated. The investment rates in periods 1 and 2 are consistent with those reported in Tables 6
and 7, which show that listed ﬁrms had lower investment rates (at around
6 percent) than non-listed ﬁrms.
IV. Estimation of the Capital Structure
In this section, the determinants of capital structure are empirically investigated.
Five types of debt are considered for dependent variables. In addition tobasic control factors, cash-ﬂow factors and ﬁrm attributes are introduced as
independent variables.
IV.1

Model and variables

Dependent variables
The dependent variables used for estimation are as follows:• Debt ratio = debt/total assets15• Bank-borrowing ratio = bank borrowing/total assets• Other liabilities = (debt − bank borrowing)/total assets16• Borrowing/liability = bank borrowing/total liabilities• Short-term borrowing ratio = short-term borrowing/total assets• Long-term borrowing ratio = long-term borrowing/total assets
In this context, bank borrowing = short-term borrowing ratio + long-termborrowing ratio, and total liabilities = bank borrowings + other liabilities. Otherliabilities consists mainly of deferred payments, notes payable and other liabilities
that could be interpreted as informal ﬁnancial transactions.

14. In the short run, inefﬁcient IPO pricing is a crucial motive for listing. The widely-known
underpricing problem might give the ﬁrms incentive for listing for gaining stock premiums. The longrun underperformance bias after IPO also implies such behavior by ﬁrms. Although the stock market
was booming in Thailand in the 1990s, the ﬁrms’ performance after IPO had a declining trend (Kimet al., 2004), suggesting that the IPO boom during the period was caused by such motivations.
15. In actual calculations, ‘quasi self-ﬁnance’ compositions are deduced from debt.
16. Please refer to footnote 9.

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Control variables
For control variables, the variables that have been shown to affect agency costs
in previous studies are introduced. First, the non-debt tax shield is known to bea primary inﬂuence on tax saving through debt. Debt incurs tax saving becauseinterest expenses are treated as deductions from taxable income. However, themagnitude of the effect depends on the scope for accounting for it, or on
the residual of the total tax shield minus the non-debt tax shield. Therefore, thetax-saving effect through debt is inﬂuenced by the non-debt tax shield. Many
previous studies have identiﬁed the inﬂuence of the tax-saving shield on ﬁrms’
debt ﬁnance and use the depreciation rate to proxy the non-debt tax shield.
However, this proxy is not available in our dataset. The non-debt tax shield isdirectly calculated by following the method presented in Titman and Wessels(1988). Corporation tax, T, is T = τ(OI − I − NDT ), where τ is the tax rate, OI is
operating income, I is interest expenses, and NDT is the non-debt tax shield.
Hence, the non-debt tax shield is:
NDT = OI − I − (T/τ).

(1)

Previous studies have obtained positive correlations between cash ﬂow andthe debt ratio. According to the pecking order hypothesis, a ﬁrm prefers
cash ﬂow to debt, because the agency costs are lower than that of debt. Somestudies adopt retained earnings in the balance sheet as a proxy for cash ﬂow
itself. Because retained earnings are a stock variable, it differs from cash ﬂow,
which is available to ﬁrms at any time. Many studies deal with this problem byusing the proﬁt rate as the proxy. In the present study, both proxies are used.17
The other problem, as mentioned in Section II, is whether it is appropriate totreat cash ﬂow as only on the equity side for developing economies. Taking
ownership and the governance structure into account, some liability items, suchas borrowing from managers and employees and borrowing from afﬁliated ﬁrms,
could be considered as being similar to self-ﬁnance. These are regarded as typesof self-ﬁnance and we treat quasi self-ﬁnance as being deﬁned in terms of thefollowing explanatory variables:
Quasi self-ﬁnance = (borrowing from managers and employees+ borrowing from afﬁliated ﬁrms)/ Total assets(2)

Third, the coefﬁcient of variation for proﬁt and total assets are introduced asa risk factor and a proxy for ﬁrm size, respectively. Although the theoreticaljustiﬁcation might be rather weak, these variables are found to be statisticallysigniﬁcant in many studies. Arguably, the higher the risk and the smaller thesize, the lower is the debt ratio.

17. As a result, there is little difference between the two variables in the context of estimation. We
adopt retained earnings as a variable because the proﬁt ratio does not ﬁt the estimation model andcauses some inconsistent results.

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111

The differences in technology between industries are controlled. In industries
in which technology is highly speciﬁc (so that informational asymmetries areserious), the agency costs associated with debt ﬁnance are generally thought tobe relatively high. R&D expenses and advertising expenditures are appropriate
proxies for such technology speciﬁcity. In addition, in an economy such as
Thailand where heavy industries are at the initial growth stage, the magnitude of
the information asymmetries might differ between the heavy and light industries. For our analysis, industry dummies (at the International Standard Industrial
Classiﬁcation two-digit level) are used given data availability.
Determinants
Three features of Thai corporate ﬁnancial structure are highlighted. The ﬁrst is
the relationship between ﬁrm age and mobilization methods. It is generally
considered that ﬁrms begin their operations mainly with their own resources andgradually expand their external ﬁnance because the problem of information
asymmetry is serious at the initial stage. If a ﬁnancial market functions well,information problems will weaken as transaction experiences accumulate. Thiseffect on Thai ﬁrms is examined by introducing the ﬁrms’ ages with logarithmic
form as an explanatory variable.
The second feature is the relationship between a ﬁrm’s IPO behavior and its
capital structure. On the one hand, a major incentive for ﬁrms to participate inorganized securities markets is to diversify their ﬁnancial resources towards
equity ﬁnance. This means that listing has a negative effect on the debt ratio. On
the other hand, ﬁrms’ listing behavior might induce disclosure, which might
reduce the agency costs of ﬁnancial transactions as a whole. This might promote
debt ﬁnance. Furthermore, if the agency costs of bank borrowing and otherforms of informal borrowing differ, their ‘pecking order’ preference might change
in the way that debt composition changes. This hypothesis can be tested byintroducing a dummy variable for listed ﬁrms.
The third feature is the effect of ﬁrms’ attributes in relation to business-groupafﬁliation and foreign ownership. For example, given the close and longstanding relationship between manufacturing ﬁrms in the ﬁnancial conglomerates
group and commercial banks, these ﬁrms have easy access to bank loans. In
contrast, foreign ﬁrms might have easy access to equity ﬁnance and intra-ﬁrm
credit through their inner fund channels with parent multinational corporations.
Hence, the dummy variables for ﬁnancial conglomerates and foreign ﬁrms areincluded in the estimation.
VI.2

Estimation results

The estimation results are summarized in Table 8. Because panel data withvarious dummy variables are used, it might be necessary to consider the individual and time effects in the estimation. If such effects are non-trivial, the OLS
estimation will be inefﬁcient. To deal with this problem, the estimations usingDependent variables
Debt ratio

Debt ratio

Bank borrowing Other liabilities

0.6183***(28.725)0.0043***(2.990)−0.4429***(−6.810)0.0042(0.195)−0.0312(−1.545)0.6125***(18.596)0.0021(1.310)−0.2646***(−4.419)−0.0021(−0.084)−0.0325*(−1.824)0.4592***(13.926)
0.0038**(2.328)−0.2592***(−4.307)−0.0384(−1.531)−0.0301*(−1.680)

0.1540***(5.271)−0.0017(−1.196)−0.0009(−0.017)0.0335(1.555)−0.0027(−0.176)

0.7828***(16.419)0.0049**(2.132)−0.3631***(−4.271)−0.0829**(−2.317)−0.0256(−1.011)

0.1976***(6.727)−0.0017(−1.269)−0.1170**(−2.394)−0.0010(−0.045)−0.0062(−0.429)

0.2619***(9.401)0.0055***(3.955)−0.1391***(−2.701)−0.0397*(−1.855)−0.0243(−1.584)−0.5281***−0.5052***(−17.121)(−16.399)
Dummy for ﬁnancial−0.0039−0.0275
conglomerate(−0.171)(−0.748)
Dummy for foreign ﬁrms
−0.0483***−0.0620**(−3.381)(−2.748)
Dummy for listed ﬁrms
−0.1436***−0.1455***(−11.987)(−7.536)−0.2712***(−8.761)−0.0927**(−2.522)−0.0720***(−3.188)−0.0528***(−2.733)−0.2367***(−9.010)0.0646*(1.980)0.0105(0.522)−0.0929***(−5.409)−0.1617***(−3.690)−0.1059**(−1.989)−0.0947***(−2.895)
0.0987***(3.529)−0.1209***(−4.772)−0.0742**(−2.255)−0.0318(−1.572)
0.0138(0.796)−0.1458***(−5.511)−0.0195(−0.628)−0.0404**(−2.117)−0.0663***(−4.065)

Control variables
Constant
Total assetsa
Variation of proﬁt
Retained earning
Non-debt tax shielda
Determinant factors
Quasi self-ﬁnanceBank borrowing /liability

Short-term loan Long-term loan

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Table 8 Estimation results for capital structure (all firms)

112

(continued )Dependent variables

Industry dummy
Food processing
Textiles and garment
Wooden products
Chemical products
Non-ferrous metal
Primary metal
Fabricated metal andmachinery
Adjusted R 2
Number of samples
Estimation method

Debt ratio

Debt ratio

0.0824***(3.627)−0.0269(−1.092)−0.0382(−1.006)
0.0331***(1.369)−0.0111(−0.420)−0.0344(−0.368)
0.0071(0.307)
0.343
748
OLS

0.0784**(2.184)−0.0322(−0.823)−0.0409(−0.661)
0.0362(0.942)−0.0094(−0.221)−0.0232(−0.149)
0.0072(0.199)
0.344
748
REM

Bank borrowing Other liabilities−0.0075(−0.210)−0.0749*(−1.909)−0.1132*(−1.827)−0.0625(−1.625)−0.0636(−1.502)0.0095(0.061)−0.0698*(−1.919)
0.226
748
REM

0.0864***(2.709)0.0430(1.233)0.0726(1.319)0.0993***(2.907)0.0548(1.456)−0.0337(−0.244)0.0776**(2.405)
0.139
748
REM

Bank borrowing/liability−0.1037**(−1.993)−0.1149**(−2.023)−0.1570*(−1.750)−0.1412**(−2.535)−0.1163*(−1.895)
0.0376(0.167)−0.1457***(−2.769)
0.194
748
REM

Short-term loan Long-term loan

0.0417(1.298)0.0263(0.748)−0.0721(−1.298)−0.0179(−0.519)−0.0618(−1.629)0.1455(1.043)0.0159(0.488)
0.110
748
REM

−0.0489(−1.611)−0.1010***(−3.049)−0.0417(−0.798)−0.0444(−1.367)−0.0015(−0.043)−0.1361(−1.037)−0.0852***(−2.775)
0.207
748
REM

FUND MOBILIZATION AND INVESTMENT IN THAILAND

Table 8Notes: t-statistics are given in parentheses. *, ** and *** indicate signiﬁcance at the 10%, 5% and 1% level, respectively.
a
The units of ‘total assets’ and ‘non-debt tax shield’ are billion baht. REM, random effect model.

113

ASIAN ECONOMIC JOURNAL

114

the random effect model (variance component model) are implemented.18 The
ﬁrst and second rows of Table 8 compare the results of the estimation using OLS
with the results using the random effect model in the case where the debt ratio isa dependent variable. Although the signiﬁcance of coefﬁcients in some control
variables is different, the effects on determinant factors are basically the same.
The coefﬁcient on total assets is positive but statistically insigniﬁcant when
the dependent variable is the debt ratio, whereas it is positive and signiﬁcant in
the bank borrowing equation, and negative and insigniﬁcant in the other liabilities
equation. The positive effect on total assets is signiﬁcant at the 1 percent level inthe long-term loans equation, which suggests that large ﬁrms tend to be more
dependent on formal bank loans than on informal borrowing, probably becauseof their capacity for repayment. The coefﬁcient on the risk factor, variation of
proﬁt, is negative and signiﬁcant in most of the equations, which is consistent
with results from previous studies. In addition, the results for the non-debt tax
shield are consistent with prevailing knowledge, presenting a negative effect inall equations, but signiﬁcant at the 10 percent level only in the debt ratio andbank borrowing equations.
With regard to the results of the industrial dummy benchmarked by the pulp
and paper industry, the ratios of bank borrowing, particularly of long-termborrowing, are found to be lower both in light industry groups (textiles andgarment and wooden products), where there is a large proportion of listed ﬁrms,
and in heavy industry groups (chemical products and metal and machinery),where the proportion of listed ﬁrms is lower.19
Cash flow and quasi self-financeThe coefﬁcient on retained earnings used as a proxy for cash ﬂow is small andinsigniﬁcant when the dependent variable is the debt ratio. It is negative in thebank borrowing (but insigniﬁcant), borrowing-liability ratio, and long-term loan
equations. In addition, it is positive but insigniﬁcant in the other liabilities
equation. The negative correlation between cash ﬂow and bank loans, andbetween cash ﬂow and borrowing-liability ratio, is consistent with the pecking
order hypothesis. That is, ﬁrms with large cash ﬂows tend to use them rather
than use bank loans because the agency costs of the former are lower. At thesame time, ﬁrms with large cash ﬂows tend to use informal ﬁnancial transactions
instead of bank loans.
18. In our estimation, the ﬁxed effect model was unavailable because of the complete
multicollinearity between the explanatory dummy variables (e.g. ﬁnancial conglomerate dummy,
listed dummy and industrial dummies) and time and ﬁrm individual dummies.
19. This common trend results from different reasons. The low ratio of long-term borrowing inlight industries, where ﬁrms are inclined to participate in the securities market, seems to result
from a diversiﬁcation of fund mobilization. By contrast, in heavy industries, where many ﬁrms are
non-listed, the low ratio might result from a high dependence on the internal funds as an investment
source.

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115

The results clearly show that quasi self-ﬁnance is negatively correlatedwith all the debt indicators: debt ratio, bank borrowing and other liabilities. The
results suggest that quasi self-ﬁnance resembles self-ﬁnance with low agency
costs. Furthermore, ﬁrms’ preference order for quasi self-ﬁnance is before otherliabilities. In other words, quasi self-ﬁnance is similar to genuine self-ﬁnance.
Firm age and fund mobilization
Table 9 provides the results of the estimations when ﬁrm age is included as an
explanatory variable, with the samples divided into listed and non-listed ﬁrms.
The sample size is considerably smaller because information on the year of
establishment is unavailable for approximately half of the sample ﬁrms. According to the estimation results, age has a negative and signiﬁcant effect on bankborrowing for non-listed ﬁrms, and a positive and signiﬁcant effect on otherliabilities for listed ﬁrms. The coefﬁcients on ﬁrm age have opposite signs
between listed and non-listed ﬁrms when the dependent variable is the debt
ratio, but neither is statistically signiﬁcant.
Contrary to the conventional understanding, non-listed older ﬁrms actively
utilize informal ﬁnancial transactions and are inactive in bank loan transactions.
Although the relationship between age and bank loan transactions is insigniﬁcant for listed ﬁrms, it is observed that older ﬁrms rely on informal ﬁnancialtransactions. This suggests that the manufacturing ﬁrms tended to utilize informal
ﬁnance, such as internal or trade ﬁnance, during their initial growth process
because information processing by banks and, thereby, loan markets did notwork perfectly in Thailand in the 1990s.
Participation in organized capital markets
The results in Table 8 reveal that the dummy for listed ﬁrms signiﬁcantly affects
the debt ratio, which is consistent with the descriptive observations in Section
III. The magnitude of the negative effect of the listing dummy is greater in theother liabilities equation than in the bank borrowing equation. In addition,
the sign of the coefﬁcient on the listing dummy in the borrowing/liability
equation is positive and signiﬁcant at the 1 percent level.
In our framework, the results can be interpreted as follows. Participation in
the capital market reduces the agency costs of equity ﬁnance, thereby making
the agency costs of bank borrowings and informal ﬁnance relatively higher.
However, the effect on the agency costs is weaker for bank borrowing than for
informal ﬁnance, causing an increasing divergence in the agency costs for these
forms of fundraising. The result is an increase in the share of bank borrowings indebt composition. In short, ﬁrms’ IPO behavior has the effect of activating thebank loan markets. This suggests that ﬁrms’ participation in organized capital
markets has the ‘by-product effect’ of reducing informational asymmetries throughthe disclosure of information not only in the securities market, but also in bankloan markets. In other words, the listing behavior of ﬁrms creates an externality
regarding information.

Dependent variables
Debt ratio

Control variables
Constant
Total assetsa
Variation of proﬁt
Retained earning
Non-debt tax shielda
Determinant factors
Quasi self-ﬁnanceDummy for ﬁnancial conglomerate
Dummy for foreign ﬁrms
Log of ﬁrm age

Bank borrowing

Other liabilities

ListedNon-listed

ListedNon-listed

ListedNon-listed

0.4393***(4.419)0.0033(1.121)−0.1062−0.0621(−0.977)−0.0009(−0.024)0.7594***(10.245)0.0031(1.415)−0.1742**0.0058(0.124)−0.0557**(−2.121)0.3488***(3.391)0.0059**(2.005)−0.2702−0.0269(−0.420)−0.0085(−0.230)0.6505***(9.343)0.0058***(2.669)−0.2015**−0.0038(−0.081)−0.0383(−1.380)

0.0860(0.962)−0.0028(−1.281)0.2048−0.0288(−0.584)
0.0022(0.083)0.1053(1.425)−0.0018(−0.803)0.01960.0121(0.259)−0.0201(−0.764)−0.3974***(−3.028)0.5274***(5.350)−0.0184(−0.543)0.0295(1.135)−0.5028***(−10.596)−0.0583(−1.050)−0.0981**(−2.510)−0.0414*(−1.875)−0.1475(−1.128)0.4315***(4.209)−0.0399(−1.135)−0.0080(−0.300)−0.2275***(−4.544)−0.1101**(−2.139)−0.0964***(−2.650)−0.0761***(−3.576)−0.2891***(−2.985)0.0896(0.984)0.0192(0.619)0.0386*(1.687)−0.2900***(−6.099)
0.0538(0.973)0.0032(0.081)0.0345(1.569)ASIAN ECONOMIC JOURNAL

Table 9 Estimation results for capital structure, listed and non-listed firms

116Dependent variables
Debt ratio

Industrial dummy
Food processing
Textiles and garment
Wooden products
Chemical products
Non-ferrous metal
Primary metal
Fabricated metal and machinery
Adjusted R2
Number of samples
Estimation method

Bank borrowing

Other liabilities

ListedNon-listed

ListedNon-listed

ListedNon-listed−0.0301(−0.399)−0.1114(−1.502)−0.2034(−1.655)−0.0060(−0.080)−0.0540(−0.659)
0.0116(0.144)
—
0.345
219
REM

0.0460(0.668)−0.0845(−0.876)——0.0113(0.160)−0.1534*(−1.667)−0.0188(−0.284)
—
0.353
369
REM

0.0463(0.593)−0.0638(−0.828)−0.1259(−0.986)
0.0335(0.431)−0.0302(−0.354)0.0418(0.500)
—
0.334
219
REM

−0.0544(−0.853)−0.0060(−0.067)——−0.1236*(−1.887)−0.1806**(−2.132)−0.0928(−1.515)
—
0.298
369
REM

−0.0796(−1.154)−0.0512(−0.750)−0.0848(−0.752)−0.0397(−0.575)−0.0211(−0.280)−0.0304(−0.414)
—
0.045
219
REM

0.1029(1.498)−0.0755(−0.786)——
0.1334*(1.890)0.0298(0.325)0.0732(1.109)
—
0.154
369
REM

FUND MOBILIZATION AND INVESTMENT IN THAILAND

Table 9 Estimation results for capital structure, listed and non-listed firms

Notes: t-statistics are given in parentheses. *, ** and *** indicate signiﬁcance at the 10%, 5% and 1% level, respectively.
a
The units of ‘total assets’ and ‘non–debt tax shield’ are billion baht. REM, random effect model; —, not applicable.

117

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118

Business-group affiliation and foreign ownership
The estimated coefﬁcient on the foreign ﬁrm dummy suggests that the effects on
debt ratios and bank borrowing are relatively low. Foreign ﬁrms tend to rely lesson debt ﬁnance and more on equity ﬁnance. This ﬁnding is consistent with thefact that many foreign ﬁrms have been established by direct investment, with
their capital being formed by multinational ﬁrms.
Unexpected results are obtained with respect to the effect of the ﬁnancial
conglomerate dummy. Firms afﬁliated to this business group have average debt
ratios. However, with regard to debt composition, the coefﬁcient on this dummyis negative and signiﬁcant when the dependent variable is bank borrowing andpositive and signiﬁcant when it is other liabilities. It is difﬁcult to imagine thatsuch ﬁrms face stricter credit restrictions than other ﬁrms because commercial
banks are overwhelmingly the major suppliers of credit in Thai ﬁnancial markets.
Hence, their high dependence on other liabilities suggests that group-afﬁliatedﬁrms tend to access commercial bank credit not through formal bank loans, but
through informal channels redirected by afﬁliated ﬁrms or owner-families.
Short-term and long-term loans
Table 8 also presents the estimation results when the dependent variables
are short-term and long-term loans. The coefﬁcients of the control variables
are almost the same as those of the bank borrowing equation. With regard toﬁrm ownership, the foreign ﬁrm dummy is negative and signiﬁcant at the
1 percent level for long-term borrowing, whereas it is negative but not statisticallysigniﬁcant for short-term borrowing.
The coefﬁcient on the ﬁnancial conglomerate dummy is not signiﬁcant in thelong-term loans equation, but is negative and signiﬁcant in the short-term loans
equation. Firms afﬁliated with ﬁnancial conglomerates depend less on shortterm bank loans, which can be substituted by informal credit. The coefﬁcient on
the listing dummy is not signiﬁcant for short-term borrowing, but is negativeand signiﬁcant at the 1 percent level for long-term borrowing. This suggests that
listed ﬁrms would be able to substitute the funds raised from the capital market
for long-term loans.
V. Estimation of Equipment Investment
V.1 Model and variables
In this section, the impact of ﬁrm ownership and capital structure on ﬁrms’
investment behavior is examined by estimating a simple investment function.
Given data availability and accuracy, the following reduced-form equation basedon the neo-classical-type investment function is estimated:
INV = α 0 + α 1ROA + α 2CAC + α 3FIXASSET + α 4DR + α 5BU+ α 6LONG + α 7FCD + α 8FOD + α 9LIST + α 10IND,(3)

FUND MOBILIZATION AND INVESTMENT IN THAILAND

119

where
INV = equipment investment = log (ﬁxed assets/ﬁxed assets in the previousyear);ROA = return on assets = proﬁt before tax/total assets;
CAC = capital cost = interest expenses/debt;
FIXASSET = ﬁxed assets = log (ﬁxed assets);
DR = debt ratio = debt/total assets;
BU = bank borrowing = bank borrowing/total assets;
LONG = long-term loans = long-term loans/total assets;
FCD = ﬁnancial conglomerate dummy;
FOD = foreign dummy;
LIST = listing dummy;
IND = industrial dummy (vector).
The ﬁrst four variables are typical control variables for an investment function. IND controls for differences in technology. An estimation of Equation (3)allows one to examine the effects of ﬁrm characteristics and indicators of thecapital structure (e.g. debt ratio, bank borrowing and long-term borrowing) on
credit restrictions and the agency costs associated with investment.
Unfortunately, because our dataset does not include depreciation, the investment level is crudely measured. The estimation of a Tobin’s Q-type investment
function was attempted but not succeeded. Our estimation follows Suto (2003),
who dealt with similar data availability problems to estimate investment functions for Malaysian ﬁrms.
V.2 Estimation results
The estimation results are presented in Table 10. Of the control variables, thecoefﬁcients on return on assets are either not signiﬁcant or negative and signiﬁcant. The coefﬁcients on the capital cost and ﬁxed assets have the expected
negative signs, with the latter being highly signiﬁcant. The estimation results
could be seen as reasonable.
Our ﬁndings on the effect of the capital structure are noteworthy. The coefﬁcient on the debt ratio itself is not signiﬁcant. However, when bank borrowing is
included as an independent variable, the coefﬁcient on the debt ratio is stillinsigniﬁcant, but that on bank borrowing is positive and highly signiﬁcant. Thissuggests that debt itself does not promote investment, but bank borrowing does
so strongly. When long-term loans is included in the estimated equation, thecoefﬁcient on bank borrowing becomes insigniﬁcant, but that on long-term loans
is positive and signiﬁcant at the 1 percent level. This implies that long-termloans promote investment, probably more effectively than bank borrowing
overall.
The coefﬁcient on the ﬁnancial conglomerate dummy is negative andsigniﬁcant at the 10 percent level in two of the three cases. Investment byforeign ﬁrms, indicated by the coefﬁcient on the foreign dummy, is slightly

ASIAN ECONOMIC JOURNAL
Table 10120

Estimation results for investment functions

Adjusted least squares
Control variables
Constant
Return on assets
Capital costa
Log of ﬁxed asset at last period
Determinant factors
Debt ratio

Coefficient

Coefficient

Coefficient

0.113

0.119

0.131

4.1122***(11.767)−0.4872*(−1.932)−0.0121(−1.445)−0.1938***(−11.515)

4.3368***(12.121)−0.4348*(−1.726)−0.0093(−1.114)−0.2048***(−11.875)

4.5856***(12.717)−0.3574(−1.424)−0.0103(−1.241)−0.2174***(−12.487)

0.0706(0.825)−0.1543(−1.302)0.3486***(2.736)−0.1232*(−1.719)0.0685(1.516)
0.0337(0.881)−0.1053(−1.469)
0.0777*(1.720)0.0229(0.599)−0.1152(−0.976)
0.0639(0.441)0.5340***(4.023)−0.1307*(−1.829)0.0803*(1.791)0.0455(1.185)−0.1436***(−2.786)−0.1188**(−1.990)−0.0554(−0.499)
0.0743(1.037)−0.1444***(−2.813)−0.1214**(−2.040)−0.0520(−0.471)0.0570(0.795)−0.1512***(−2.964)−0.1130*(−1.912)−0.0881(−0.800)
0.0339(0.475)0.0283(0.515)
0.0619(0.921)0.1925(0.678)0.0378(0.687)0.0632(0.944)0.1438(0.507)0.0145(0.265)0.0223(0.331)0.1684(0.598)Bank borrowing
Long-term loans
Dummy for ﬁnancial conglomerate
Dummy for foreign ﬁrms
Dummy for listed ﬁrms
Industrial dummy
Food processing
Textile and garment
Wooden products
Pulp and paper

Chemical products
Non-ferrous metal
Primary metal

Notes: t-statistics are given in parentheses. *, ** and *** indicate signiﬁcance at the 10%, 5% and
1% level, respectively. a The units of ‘capital cost’ are thousand baht.

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121

above average. No signiﬁcant differences in investment between listed andnon-listed ﬁrms are found.
VI. Concluding Remarks
This paper has examined the capital structure and investment behavior of ﬁrms
in Thailand in the early 1990s. Five important results are obtained. First, there
are serious information problems between manufacturing ﬁrms and ﬁnancial
institutions. The intimate and long-term relationship between them is not formedin the process of their mutual transactions. Rather, ﬁrms become self-reliant interms of fund mobilization during their initial growth process.
Second, the debt ratio depends upon whether ﬁrms are listed on the securities
exchange. The debt ratios of listed ﬁrms are higher than those of non-listed
ﬁrms. For both types of ﬁrm, there was no evidence that debt ratios increased in
the early 1990s. This ﬁnding contrasts with the results of Claessens et al. (1998)
and the World Bank (1998).
Third, the low debt ratios of listed ﬁrms are simply a reﬂection of increased
capital accounts generated by initial public offerings in the form of stock premiums or capital surpluses. By contrast, listed ﬁrms’ ratios of other liabilities
in debt composition are much lower than those of non-listed ﬁrms, whereasbank-borrowing ratios hardly differ. Listing on the stock exchange seems to
reduce the agency costs of equity ﬁnance. More importantly, however, it also
seems to widen the disparity in the agency costs associated with bank borrowing
and informal borrowing, leading ﬁrms to prefer bank borrowing. This might bea result of the enhanced disclosure of information required by the capital market,
which represents an externality effect of listing by ﬁrms.
Fourth, in contrast to the a priori expectation, ﬁrms in the ﬁnancial
conglomerates groups depend more on informal ﬁnance and less on bank loans,particularly on short-term loans. They are also relatively inactive investors.
Although foreign ﬁrms also depend less on bank loans, their investment ratios
are higher. This suggests that capital and credit transfers from parent multinational ﬁrms reduce capital costs, thereby promoting investment.
Lastly, a clear relationship between capital structure and investment is foundfor bank loans and long-term loans, but not for the debt ratio. Bank loans,particularly long-term loans, weaken credit restrictions, and lower capital costs
promote investment. Moreover, in listed ﬁrms long-term loans as a proportion of
total loans is very low. The long-term loans of listed ﬁrms are evidently replacedby cash or credit from the capital market. Such substitution, however, does notpromote ﬁrms’ equipment investment.
In terms of its role in fund mobilization, Thailand’s capital market was not a
substitute for, but a complement to, the indirect ﬁnancial market in the early
1990s. However, bank loans, particularly long-term loans, promoted investment,
whereas equity ﬁnance did not. This paper has identiﬁed some key features of
the capital structure and their effects on investment behavior in Thai manufacturing

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122

ﬁrms. The mechanisms behind these features require more investigation, which
remains a task for future research.
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