An Empirical Study on Capital Structure and Financing DecisionEvidences from East Asian Tigers
Dr. Jung-Lieh Hsiao and Ching-Yu Hsu, National Taipei University, Taiwan
Dr. Kuang-Hua Hsu, Chaoyang University of Technology, Taiwan
ABSTRACT
In general, managers make financial decisions of corporations by two ways which includes internal
financing and external financing. The internal financing is the using of retained earnings. The external financing is
the usage of equity, debt, hybrid securities. Based on these two kinds of financial behaviors, the capital structures of
companies could be shaped differently. As a consequence, it is an important issue for managers how to minimize
financial costs and maximize shareholders’ equity. According to mention above, several theories explaining
financing behaviors have been developed. There are the Modigliani-Miller theorem, the trade-off theory, the pecking
order theory and the market timing theory. In the present study, we re-examine the model developed by Kayhan and
Titman (2007) to provide evidences about the broad patterns of financing activity in Asian emerging markets,
including Hong Kong, Korea, Singapore and Taiwan. The empirical results show that the companies from all
countries rebalance their leverage following equity issuances, results are more in line with the dynamic trade-off
theory rather than the equity market timing or pecking order hypothesis of capital structure.
Key Words: Capital structure, Market timing, Pecking order theory, Trade-off theory.
INTRODUCTION
The capital structure refers to the way that a corporation finances its assets through some combination of
financing sources. The first choice is internal financing which is the using of retained earnings. The second choice is
external financing which is the usage of equity, debt, hybrid securities. Based on different kinds of financial
decisions, the companies could shape different capital structures. Eventually, it is an important issue for managers
how to minimize financial costs and maximize shareholders’ equity by financial decision and the setting of capital
structure.
The Modigliani-Miller theorem (Modigliani and Miller, 1958), the first relevant theory of capital structure,
states that the value of a firm is irrelevant to how that firm is financed in a perfect market. However, the real world
reflects the firm’s value is relevant with its bankruptcy costs, agency costs, taxes, information asymmetry and so on.
That is why a company’s value is affected by the capital structure it employs. Therefore, since Modigliani and
Miller’s irrelevance proposition, researchers have investigated firms’ decisions about how to finance their
operations.
According to the Modigliani-Miller theorem, two traditional theories of capital structure, the Trade-off
Theory and the Pecking Order Theory, are developed. These theories guide most of the capital structure studies. The
Trade-off Theory considers firms have a target capital structure that is determined by the marginal benefits of debt
(tax advantage of debt) and costs associated with debt (bankruptcy costs and agency costs) (Jensen and Meckling,
1976; Myers, 1977). In other words, Trade-off Theory implies that firms adjust their capital structure in response to
the temporary shocks that cause their leverage to deviate from the target. The Pecking Order Theory, due to
asymmetric information (Myers and Majluf, 1984; Myers, 1984), when a manager finance by external funds,
investors would see this behavior as the firm is overvalued. Therefore, invertors tend to sell their stocks and the
value of the firm will fall. For this reason, firms follow a financing hierarchy; descends from internal funds, to debt,
to external equity.
Recently, a new theory, the market timing theory of capital structure which was first introduced by Baker
and Wurgler (2002), develops a different kind of view about capital structure. The Market Timing Theory suggests
that managers are able to identify certain time periods during which equity issuance is less costly due to the high
valuation of company’s stock. In other words, firms are more likely to issue equity when their market values are
high, relative to book and post market values, and to repurchase equity when their market values are low. As a
consequence, current capital structure is strongly related to historical market values. This result provides the theory
that capital structure is the cumulative outcome of past attempts to time the equity market.
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248
However, Hovakimian (2005), Flannery and Rangan (2006), Alti (2006), Kayhan and Titman (2007)
disagree with Baker and Wurgler on the persistence of the effect on capital structure because the importance of
historical average market-to-book ratios in leverage regressions is not influence the past equity market timing.
Kayhan and Titman (2007) make the point that the significance of the historical market-to-book series in leverage
regressions may be due to the noise in the current market-to-book ratio. Specifically, Kayhan and Titman
decompose the external finance weighted average market-to-book ratio into the mean market-to-book ratio, the
covariance between the market-to-book ratio, and the financing deficit. They show that the persistence result of
Baker and Wurgler is mainly driven by the persistence of the average market-to-book ratio rather than the
covariance between the market-to-book ratio and the financing deficit.
Kayhan and Titman (2007) is one of the newly research for the comprehensively study how cash flows,
investment expenditures , and stock price, histories affect company’s debt ratios. But that research only focus on the
United States. It is curious about whether the Eastern countries follow their findings; therefore, this research reexamines the models of Kayhan and Titman (2007) to provide evidences about the broad patterns of financing
activity in this case.
In order to examine financing decision in Asian countries, we select the samples including Japan,
Singapore, Korea, Taiwan, and Hong Kong. The term Four Asian Tigers or East Asian Tigers refers to the
economies of Hong Kong, Korea, Singapore, and Taiwan. These regions were noted for maintaining high growth
rates and rapid industrialization between 1960s and 1990s. In the early 21st century, the original four Tigers are at
fully developed status. In additional, Japan emerged as the most developed nation in Asia. Due to their economical
levels and developments are similar, we draw these five countries in Asia.
According to already mentioned, we will check three purposes of our study: (1) What drives capital
structure developments? Which kinds of theories will the short-term capital structure be fitted to? (2) Are the effects
persistent? Does the capital structure have long-lasting effects? (3) Does the capital structure revise? We tend to
estimate whether the effect of trade-off, pecking order and timing variables on the debt ratio is later reversed.
METHODOLOGY
Data
Our sample is drawn from the database of Standard & Poor’s Compustat Global (Global Vantage) files in
four countries in Asia, including Japan, Singapore, Korea, and Hong Kong. The observed period is from 1993 to
2007. For comparability of results for each country, we translate sales figures in local currencies to US dollars, using
respective yearly average exchange rates.We restrict the sample to exclude financial firms (SIC 6000–6999) and
regulated firms (SIC 4000–4999) since their accounting and reporting environments differ from those in other
industries. Besides, following Baker and Wurgler (2002), we eliminate firms with book value of assets less than $10
million. Our sample is further restricted to include firms that have at least four years of data due to our long-horizon
analysis.
Book leverage is defined as the ratio of book debt to total assets, where book debt is defined as total assets
minus book equity, and book equity is equal to total assets less total liabilities and preferred stock plus deferred
taxes. Even though, Baker and Wurgler (2002) reclassify convertible debt as equity. However, global Vantage does
not provide detailed data on convertible debt. Following recent capital structure studies, i.e. Alti (2006), convertible
debt is included in debt in our study. In addition, we drop observations where this ratio is greater than one for
individual firm-year observations. Market leverage is the ratio of the book value of debt to the sum of the book value
of debt and the market value of equity.
Net debt and net equity issues that are used both in market timing and financial deficit variables are
calculated using balance sheet items. We define net equity issues as the change in the book value of equity minus the
change in retained earnings; Baker and Wurgler (2002) also use this approach. Net debt issues are then defined as
the change in total assets net of the change in retained earnings and net equity issues.
The Model
1. What drives capital structure developments? Which kind of theories will the short-term capital structure be fitted
to?
Stage 1: Predict the target leverage:
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Lt = α 0 + β1M / Bt −1 + β 2 PPEt −1 + β 3 EBITDt −1 + β 4 R & Dt −1 + β 5 ( R & Ddummy )t −1
+ β 6 SEt −1 + β 7 SIZEt −1 + ε t
(1)
(1) Leverage deficit
Ldef t −4 = Lt − 4 − LTt− 4
(2) Change in target
∆T arg et t −4 = LTt − LTt− 4
Stage 2: Estimate the regression model
Lt − Lt − 4 = α 0 + β1 FDd [t ,t − 4 ] + β 2 FD[t ,t − 4 ] + β 3 YT[t ,t − 4 ] + β 4 LT[t ,t − 4 ] + β 5 r[t ,t − 4 ]
+ β 6 EBITD[t ,t − 4 ] + β 7 Ldef t − 4 + β 8 ∆T arg et t − 4 + ε t
(2)
In this study, we select two-stage regression. The first-stage regression is estimated using a Tobit
specification where the predicted value of the leverage ratio is restricted to be between zero and 100. In the secondstage regression we estimate the coefficients with standard OLS regressions. Because of the overlapping intervals,
we use a bootstrapping technique to determine the statistical significance of the estimated coefficients. That is to
say, since the standard errors violate the assumption that the errors are independently and identically distributed,
standard regression models are not appropriate to determine the significance of the parameter estimates. Therefore,
we use bootstrapping to estimate standard errors that are robust to heteroskedasticity, correlation that arises as a
result of multiple observations for each firm, and autocorrelation that we induce by including observations in
overlapping periods.
2. Are the effects persistent? The capital structure has long-lasting effects?
Lt − Lt −8 = α 0 + β 1 FDd [t − 4,t −8] + β 2 FD[t − 4,t −8] + β 3YT[t − 4,t −8] + β 4 LT[t − 4,t −8] + β 5 r[t − 4,t −8]
+ β 6 EBITD[t − 4,t −8] + β 7 FDd [t ,t − 4 ] + β 8 FD[t ,t − 4 ] + β 9YT[t ,t − 4 ] + β 10 LT[t ,t − 4 ]
(3)
+ β 11 r[t ,t − 4 ] + β 12 EBITD[t ,t − 4 ] + β 13 Ldef t −8 + β 14 DT arg et t −8 + ε t
The equation is specified for the change in leverage from t-8 to t, and this is twice as long as equation (1).
We tend to check whether the proxy variables over a four year period t-8 to t-4 still affect the change in leverage
over a eight year period running from t-8 to t. In the other words, if the capital structure has long-lasting effects, we
call this the test for “persistence”.
3. Does the capital structure revise?
Lt − Lt − 4 = α 0 + β 1 FDd [t − 4,t −8] + β 2 FD[t − 4,t −8] + β 3YT[t − 4,t −8] + β 4 LT[t − 4,t −8] + β 5 r[t − 4,t −8]
+ β 6 EBITD[t − 4,t −8 ] + β 7 FDd [t ,t − 4 ] + β 8 FD[t ,t − 4 ] + β 9YT[t ,t − 4 ] + β 10 LT[t ,t − 4 ]
(4)
+ β 11 r[t ,t − 4 ] + β 12 EBITD[t ,t − 4 ] + β 13 Ldef t −8 + β 14 DT arg et t −8 + ε t
We have a tendency to test whether the direction of the effects switches sign from equation (2) to (4). That
would indicate whether the effect of pecking order and timing variables on the debt ratio is later reversed. It is a
method to check non-persistence of the capital structure.
We select two-stage regression, Tobit model and OLS mode in this study. We also employ bootstrapping
technique to determine the statistical significance of the estimated coefficients.
EMPIRICAL RESULTS
The Table 1 shows the summary statistics for leverage, net equity issues, debt issues and changes in
retained earnings for each country for the overall period from 1988 to 2007. First, we observe the mean of book
leverage is higher than the mean of market leverage in Singapore and Taiwan and the mean of book leverage is
lower than the mean of market leverage in Hong Kong and Korea. Second, the average of net equity issues, debt
issues and changes in retained earnings are positive in all countries. Besides, unlike other countries, the mean of net
equity issues is lower than the mean of net debt issues for Singapore.
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250
Table 2 reports the regression results of book leverage change in book and market leverage between year t
and t-3 on YT and LT. Table 3 reports the regression results of book leverage change in book and market leverage
between year t and t-3 on EQUALWMB. The results of the estimation appear to be similar for the whole sample of
firms. Therefore we discuss them together. We observe that a significantly positive coefficient of FDd. In addition,
the proxy variables of pecking order, FD and EBITD, are not significant totally. This is to say, companies just follow
pecking order theory partly when they finance. Besides, we find a significantly negative coefficient for the stock
return in all countries. This relationship is in accordance with market timing, which indicates that firms use
relatively more equity after periods of a stock price increase. This outcome would also be consistent with the
empirical evidence of KT for the US and evidence of Bie and Haan(2007) for the Netherlands. However, the
market-to-book based timing measures YT and LT are not found to be significant in all countries. This implies that
the market timing behavior of firms addresses changes rather than levels of stock market valuation in East Asian
tigers. Finally, a significantly negative coefficient of Ldef and a significantly positive coefficient of ΔTarget, which
implies financial decisions are all followed with trade-off theory in East Asian tigers.
Table 3 reports the regression results of change in book and market leverage between year t and t-6 on YT
and LT. Since the pages constraint, we reserve the reports for the regression results of change in book and market
leverage between year t and t-6 on EQUALWMB. Unlike proxy variables of pecking order and market timing, a
significantly negative coefficient of Ldef and a significantly positive coefficient of ∆Target, which implies financial
decisions are all followed with trade-off theory in East Asian tigers. As a consequence, the capital structures of these
four countries do not have long-lasting effects.
The empirical results show that unlike proxy variables of pecking order and market timing, a significantly
negative coefficient of Ldef and a significantly positive coefficient of ∆Target, which implies the financial decisions
are all followed with trade-off theory in East Asian tigers. As a consequence, the effects of history do not reverse in
these four countries.
CONCLUSIONS
In finance, capital structure refers to the way a corporation finances its assets through some combination of
sources. Based on many kinds of financial decisions, firms could shape different capital structures. According our
findings above, firms from all countries rebalance their leverage following equity issuances, results are more in line
with the dynamic trade-off theory rather than the equity market timing or pecking order hypothesis of capital
structure. In other words, firms have a target capital structure, determined by the marginal benefits of debt and costs
associated with debt. Thus, this implies that firms adjust their capital structure in response to the temporary shocks
that cause their leverage to deviate from the target in East Asian Tigers, which are highly developed countries in
Asia. This outcome would be consistent with the previous empirical evidence of the US, the Netherlands and G7.
REFERENCES
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Bie, T., Haan, L. (2004). Does market timing drive capital structures? A panel data study of Dutch firms, Working Paper, De Nederlandsche Bank,
Netherlands.
Chen, L., Zhao, X. (2004). Understanding the role of the market-to-book ratio in corporate financing decisions. Working Paper. Michigan State
University, East Lansing.
Flannery, M.J., and Rangan, K.P. (2006). Partial adjustment and target capital structures, Journal of Financial Economics, 79, 469-506.
Frank, M., and Goyal, V. (2003). Testing the pecking order theory of capital structure, Journal of Financial Economics, 67, 217-248.
Greene, W. H. (2008). Econometric analysis, 6th Edition , Prentice Hall.
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Huang, R., and Ritter J.R. (2006). Testing the market timing theory of capital structure, Working paper.
Kayhan, A., and Titman S. (2007). Firms' histories and their capital structure, Journal of Financial Economics, 83, 1-32.
Korajczyk, R.A., and Levy A. (2003). Capital structure choice: Macroeconomic conditions and financial constraints, Journal of Financial
Economics, 68, 75-109.
Mahajan, A., and Tartaroglu, S. (2008). Equity market timing and capital structure: International evidence, Journal of Banking and Finance, 32,
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1421-1460.
Welch, I. , (2004), Capital structure and stock returns, Journal of Political Economy, 112, 106–131.
The Business Review, Cambridge * Vol. 13 * Num. 1 * Summer * 2009
251
Table 1 Summary statistics for leverage, net equity issues, debt issues and changes in retained earnings
Hong Kong
Korea
Singapore
Taiwan
Number of firms
81
358
148
560
Book leverage
Mean
0.40
0.56
0.47
0.45
SD
0.20
0.20
0.17
0.16
Market leverage
Mean
0.43
0.70
0.43
0.40
SD
0.25
0.28
0.21
0.21
Net equity issues
Mean
0.02
0.03
0.02
0.03
SD
0.26
0.15
0.19
0.14
Net debt issues
Mean
0.01
0.03
0.02
0.017
SD
0.27
0.21
0.23
0.95
Newly retained
Mean
0.02
0.01
0.02
0.01
earnings
SD
0.25
0.11
0.18
0.14
Table 2 The regression of change in book and market leverage between year t and t-3 on YT and LT
Hong Kong
Korea
Singapore
Taiwan
Panel A. Book Leverage
Coefficient/SD
0.05***/0.02
0.03***/0.01
0.05***/0.01
0.06***/0.02
FDd [t ,t − 3 ]
Coefficient/SD
0.06***/0.03
-0.02*/0.02
0.05***/0.02
-0.03***/0.06
Coefficient/SD
0.10/0.24
0.19***/0.06
-0.03//0.08
-0.05/0.11
Coefficient/SD
0.03/0.09
-0.11*/0.11
-0.02/0.03
0.10***/0.04
Coefficient/SD
-0.01**/0.01
-0.01***/0.01
-0.01***/0.01
-0.01***/0.01
Coefficient/SD
0.06**/0.04
-0.05***/0.03
-0.11***/0.04
-0.08***/0.02
Ldeft −3
Coefficient/SD
-0.60***/0.07
-0.66***/0.03
-0.89***/0.0
-0.82***/0.03
∆T arg ett −3
Coefficient/SD
0.35***/0.09
0.38***/0.07
0.55***/0.13
0.82***/0.03
729
81
2693
358
1356
173
2937
560
0.03*/0.02
0.02**/0.01
0.05***/0.01
0.05***/0.02
Coefficient/SD
0.09***/0.02
-0.10***/0.04
0.08***/0.02
-0.04***/0.06
Coefficient/SD
-0.01/0.13
0.41***/0.12
0.01/0.08
0.09*/0.14
Coefficient/SD
0.14***/0.06
-0.05/0.18
-0.04**/0.05
0.15***/0.04
Coefficient/SD
-0.04***/0.01
-0.04***/0.01
-0.08***/0.01
-0.07***/0.01
Coefficient/SD
0.13***/0.06
0.03/0.05
0.02/0.03
0.07***/0.03
Ldeft −3
Coefficient/SD
-0.67***/0.06
-0.84***/0.03
-0.76***/0.03
-0.78***/0.03
∆T arg ett −3
Coefficient/SD
0.44***/0.06
0.58***/0.06
0.40***/0.04
0.69***/0.03
719
81
2693
358
1354
173
2804
560
FD [t ,t − 3 ]
YT [t ,t − 3 ]
LT [t ,t − 3 ]
r [t ,t − 3 ]
EBITD [t ,t − 3 ]
observations
clusters
Panel B. Market Leverage
Coefficient/SD
FDd [t ,t − 3 ]
FD [t ,t − 3 ]
YT [t ,t − 3 ]
LT [t ,t − 3 ]
r [t ,t − 3 ]
EBITD [t ,t − 3 ]
observations
clusters
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252
Table 3 Do the effects of history persist? Regression of change in book and market leverage between year t and t-6 on YT and LT
Hong Kong
Korea
Singapore
Taiwan
Panel A. Book Leverage
Coefficient/SD
0.02/0.02
0.03***/0.01
0.02*/0.01
-.02**/0.01
FDd [t −3,t − 6 ]
Coefficient/SD
-0.04**/0.03
-.03*/0.03
-0.01/0.04
0.06**/0.05
Coefficient/SD
-0.07/0.02
.10*/0.11
0.05/0.12
-0.11/0.18
Coefficient/SD
-0.07/0.13
-.22**/0.21
0.03/0.19
-0.14***/0.07
Coefficient/SD
0.01/0.01
-.07***/0.01
-0.01*/0.01
0.01/0.01
Coefficient/SD
-0.08/0.10
-.06*/0.06
0.01/0.06
0.03/0.06
Coefficient/SD
0.04**/0.02
0.02***/0.01
0.03**/0.01
-0.01/0.01
Coefficient/SD
0.13***/0.04
-0.03/0.03
0.07***/0.04
0.15***/0.05
Coefficient/SD
0.36***/0.35
0.18***/0.09
-0.03/0.17
-0.31***/0.21
Coefficient/SD
0.15***/0.19
-0.08/0.16
-0.07*/0.10
0.02/0.09
Coefficient/SD
-0.01/0.01
-0.01***/.0.01
-0.01***/0.01
-0.01**/0.01
Coefficient/SD
0.25***/0.11
0.04/0.06
-0.09***/0.09
-0.18***/0.07
Ldeft −6
Coefficient/SD
-0.92***/0.06
-0.86***/0.03
-1.09***/0.04
-0.99***/0.06
∆T arg ett −6
Coefficient/SD
0.67***/0.10
0.67***/0.07
0.63***/0.10
0.96***/0.06
observations
clusters
497
73
1958
341
878
148
1340
536
Panel B. Market Leverage
Coefficient/SD
FDd [t −3,t − 6 ]
0.01/0.02
0.02**/0.01
0.02/0.02
-0.03***/0.01
Coefficient/SD
-0.02/0.03
0.10***/0.06
0.06***/0.05
0.06/0.06
Coefficient/SD
0.25**/0.21
-0.33***/0.20
0.01/0.13
-0.07/0.27
Coefficient/SD
-0.06/0.11
0.39***/0.35
-0.15***/0.12
-0.19***/0.10
Coefficient/SD
0.01/0.01
0.01***/0.01
0.01/0.01
0.02***/0.01
Coefficient/SD
0.01/0.11
0.01/0.09
0.04/0.05
0.06/0.09
Coefficient/SD
0.02/0.02
0.01/0.01
0.03**/0.01
-0.02/0.01
Coefficient/SD
0.14***/0.04
-0.07***/0.05
0.04/0.04
0.04/0.07
Coefficient/SD
0.13/0.27
0.29***/0.18
0.01/0.21
0.01/0.32
Coefficient/SD
0.22***/0.15
-0.16/0.23
0.03/0.11
0.01***/0.11
Coefficient/SD
-0.05***/0.01
-0.07***/0.01
-0.05***/0.01
-0.08***/0.01
Coefficient/SD
0.37***/0.12
0.15***/0.09
-0.05/0.07
-0.03/0.07
Ldeft −6
Coefficient/SD
-0.84***/0.05
-0.97***/0.02
-1.03***/0.03
-1.01***/0.03
∆T arg ett −6
Coefficient/SD
0.78***/0.06
0.74***/0.06
0.78***/0.05
0.99***/0.04
481
69
1958
341
878
148
1170
432
FD [t −3,t − 6 ]
YT [t − 3,t − 6 ]
LT [t − 3,t − 6 ]
r [t − 3,t − 6 ]
EBITD
[t −3,t − 6 ]
FDd [t ,t − 3 ]
FD [t ,t − 3 ]
YT [t ,t − 3 ]
LT [t ,t − 3 ]
r [t ,t − 3 ]
EBITD [t ,t − 3 ]
FD [t −3,t − 6 ]
YT [t −3,t − 6 ]
LT [t − 3,t − 6 ]
r [t − 3,t − 6 ]
EBITD
[t −3,t − 6 ]
FDd [t ,t − 3 ]
FD [t ,t − 3 ]
YT [t ,t − 3 ]
LT [t ,t − 3 ]
r [t ,t − 3 ]
EBITD [t ,t − 3 ]
observations
clusters
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