This paper applies Within3SLS to estimate simultaneous equations for panel data of Japanese manufacturing firms to investigate the relationship between investment and fund raising. A negative interrelationship between current leverage and investment is detected.

Hongfei Zhu

English

Research Papers in Economics

     
 
 
  
  
Volume 29, Issue 1 
  
The Relationship Between Investment and Fund Raising: An Empirical study 
to Japanese Manufacturing Firms 
  
 
 
Hongfei Zhu  
Graduate School of Economics, Nagoya University 
Abstract 
This paper applies Within3SLS to estimate simultaneous equations for panel data of Japanese manufacturing firms to 
investigate the relationship between investment and fund raising. A negative interrelationship between current leverage 
and investment is detected.
I would like thank Jiro Nemoto, Ryuhei Okumura, Nobuyoshi Yamori, Kei Tomimura, ZhongHua Cong and Banntane scholarship. Any 
remaining errors are my own responsibility. 
Citation: Hongfei Zhu, (2009) ''The Relationship Between Investment and Fund Raising: An Empirical study to Japanese Manufacturing 
Firms'', Economics Bulletin, Vol. 29 no.1 pp. 357-367. 
Submitted: Oct 23 2008.   Published: March 20, 2009. 
 
     1 Introduction
According to the Modigliani-Miller Theorem (MM Theorem), corporate in-
vestment behavior is independent of the capital structure in a perfect market.
However in an imperfect market, investment behavior can be restricted by
nancing. In the area of corporate nance theory, there are two opposed the-
orems about the relation between investment behavior and nancing. One is
the pecking order hypothesis which suggests that investment is nanced rst
by retentions, then by debts and by equities only as a last resort because of
hierarchy costs. The other one is the trade o hypothesis which insists that
capital structure decision is a static trade-o between the tax advantage of
debt and costs for bankruptcy risk.
As discussed above, empirical researches also draw two opposed conclu-
sions. Recently, there are more empirical literatures to support the pecking
order hypothesis. Tong and Green (2005) support the pecking order hy-
pothesis over the trade-o hypothesis using Chinese listed companies'data.
However in their paper the relation between investment and nancial leverage
is inconclusive. Baskin (1989) and Allen (1993) nd that there is a positive
interrelation between nancial leverage and investment in the US and Aus-
tralia respectively. However as mentioned by Adedeji (1998), pecking order
hypothesis does not make a denitive prediction about the interrelation be-
tween investment and nancial leverage. In his paper, the results obtained
show that there is no signicant interaction between nancial leverage and
investment. While investment has a positive inuence on nancial leverage,
nancial leverage does not have a signicant inuence on investment. The
interrelations between them are complicated. For instance, higher leverage
can increase bankruptcy risk and push ahead investment projects. Adversely,
as a fund raising method, debt can arise with increasing investment. It is
noted that Adedeji (1998) uses 3SLS to estimate his model with cross section
data. This paper applies the method of Within 3SLS summarized by Bal-
tagai (2001) to estimate the simultaneous equation models using Japanese
manufacturing rms' panel data from 1994 to 2005. As it is well known,
the Japanese investment behavior is slackening in growth after the Bubble
economy collapses. Therefore, it is important to investigate how corporate
nance aects investment behavior.
In section 2, I introduce my model and the method. Section 3 presents
results and section 4 concludes. Data set is described in the appendix.
12 The Model and Method
In this section, just as suggested by Adedeji (1998), simultaneous equations
are used to investigate the interrelations between investment and leverage.
Benito and Young (2007) indicate that a rm can adjust nancial pressure
through dividends, new equity issuance and real investment decision, using
the UK listed rms' data. Although Adedeji (1998) considers investment,
leverage, dividends as dependent variables in his simultaneous equations, I
do not consider the dividends and new equity issuance as dependent vari-
ables in my model for a technique puzzle. I nd that there are so many
observations of dividends are zero in my samples that they can not be ig-
nored1, which means that the distribution of dividends is truncated at zero
from left side. It is necessary to apply Tobit model if dividend is used as
a dependent variable. In addition, the capital market system of Japan is
dierent from United Kingdom and US. Just mentioned by Hirota (1999)
and Hosono (2003), the UK is similar to the US and they are described as
market-oriented economies. Dividends often uctuate with protability. On
the other hand, Japan is described as a bank-oriented economy, whose stock
market is rigid comparatively. I nd that Japanese rms' dividends are per-
sistent, in other words, dividends of current term are dependent on those of
previous term and independent of the other variables such as protability,
investment and so on. The managers and shareholders prefer stability of
dividends. I call it a permanent dividends system peculiar to the Japanese
capital market. Therefore a dynamic Tobit model is necessary if a lagged
dependent variable is included as a regressor when unobserved heterogeneity
is present. It is dicult to assume the distribution of unobservable individual
eect2, when the maximum likelihood method is used. Similar to dividends,
the new equity issuance is a dummy variable. If the new equity issuance is
used as a dependent variable, a logit model or a probit model is necessary to
be applied in simultaneous equations.
The simultaneous equation models are described as follows. I suggest
that the rm can control the current aggregate investment and leverage si-
multaneously, according to the other exogenous variables.
1I nd that there are 17.0% observations of dividends are zero in the Chemistry industry.
Other industries, 26.0% in Electrical appliances, 16.1% in Food, 30.5% in Machinery, 22.1%
in Metal, 21.9% in Motor, 17.1% in Pottery, 35.7% in Steel, 36.9% in Textile.
2Although a semiparametric approach is suggested by Honore and Kyriazidou (2000)
without assumptions on the distribution of the unobserved eect and a more single method
is demonstrated by Loudermilk (2007) to solve dynamic Tobit model, their equations
are single equations. Up to this point, there is no explicit method can be applied in
simultaneous equations.
2(I=K)i;t = 0+1Levi;t + 2Levi;t 1 + 3Reti;t 1 + 4ROAi;t + 5qi;t
+ 6NEDi;t + 7Divi;t + 8GDt + i + i;t
(1)
Levi;t = 0+1(I=K)i;t + 2Reti;t 1 + 3ROAi;t + 4ri;t + 5Baddebti;t
+ 6NEDi;t + 7Divi;t +  i + i;t
(2)
Model (1) represents three fund raising methods for investment according
to the pecking order theorem, previous term's retention, current term's debt
and new equity issuance. Model (2) represents variables which aect leverage.
The variables are described in the following and the data set description
is shown in the Appendix in detail. The subscript i denotes rms and t de-
notes time. Ii;t is net investment and Ki;t is tangible capital. Levi;t is current
leverage. In my model, (I=K)i;t and Levi;t are endogenous variables. Levi;t 1
is previous term's leverage. Increasing Levi;t 1 can reduce or push ahead the
investment project. Reti;t 1 is previous term's retention per capital. Increas-
ing Reti;t 1 can relax current nancial distress and accelerate the investment.
ROAi;t is current income per asset. qi;t is Tobin's q, which denotes the in-
vestment opportunity. NEDi;t is a dummy variable for new equity issuance.
As a last resort, new equity issuance can increase investment and reduce the
leverage because of the increment of net assets. Divi;t is dividend per equity.
Interest ri;t denotes borrowing cost. The variables described above only rep-
resent the properties of the money demand side. As one of the properties
of the money supply side, Baddebti;t is the ratio of bad performing loans of
banks. Increasing Baddebti;t can cause credit crunch of bank and reduce the
rm's leverage. As is well known, 40 trillion Japanese yen Government Bond
was issued in 1998 and government expenditure expanded since 1998. GDt is
a dummy variable and applied to test whether government expenditure sup-
press the private investment, which is called crowding out. i and  i denote
the unobservable individual specic eects, i;t and i;t denote the remainder
disturbances.
In this paper I apply the method summarized in chapter 7 of Baltagai
(2001) to estimate panel data simultaneous equations. Firstly, the variance-
covariance matrix across equation (1) and (2) is necessary to be estimated,
using the method of Within 2SLS and Between 2SLS respectively. Subse-
quently, apply Within 3SLS to estimate the simultaneous equations.
The instrumental variable set is described in the following and the sub-
script i is omitted for simplication. (I=K)t 3, (I=K)t 2, (I=K)t 1, Levt 3,
Levt 2, Rett 2, Divt 1, ROAt 1, qt 1, rt 1 are in the instrumental variable
3set. The other exogenous variables NEDt, Baddebtt, GDt and constant term
are leaved in the set.
The estimation processes are programmed using matrix computation.
3 Results
In this paper, model (1) and model (2) are estimated using Japanese manufac-
turing rms' nancial statements data from Nihon Keizai Shimbun's NEEDS
database. The rms are classied into nine industries3.
The results are represented in Table 1-3. The upper half of each Table
represents the estimation of model (1) and the lower half represents the
model (2). The Comparison of the main results with the previous evidence
is represented in Table 4.
Signicant negative interrelationship between investment and current lever-
age can be detected in Chemistry, Food, Metal, Pottery, and Textile indus-
tries. Although, as represented in Table 4, Benito and Young (2007) also
nd a negative relation between investment and leverage, their model is a
single equation. They only conclude that leverage has a negative inuence
on investment. Adedeji (1998) applies simultaneous equations and concludes
that leverage does not have a signicant inuence on investment, While in-
vestment has positive inuence on leverage.
According to the upper half of each Table 1-3, we can see that the pre-
vious term's leverage does not have a unique inuence on the investment.
As one of the fund raising methods, previous term's retention has a positive
eect on investment behavior. Current return does not have a unique inu-
ence on investment. Tobin's q has a signicant positive eect on investment
in Electrical appliances, Machinery, and Motor industries. As another one
of the fund raising methods, new equity issuance has a signicant positive
eect on investment in Food and Pottery industries. Opposite to Benito and
Young (2007), Adedeji (1998), the positive relation between investment and
dividends can be detected in the electrical appliances, and Steel industries.
The crowding out can be detected explicitly in Chemistry, Metal, and Steel
industries.
According to the lower half of each Table 1-3, we can see that increasing
previous term's retention can relax current nancial distress. The increase of
current ROA can also relax current nancial distress in Electrical appliances,
Metal, Pottery, and Steel industries. The decrease of interest cannot stimu-
3Chemistry (80), Electrical appliances (71), Food (69), Machinery (80), Metal (58),
Motor (30), Pottery (41), Steel (35), Textile (33). The numbers of samples in each industry
are represented in the parentheses.
4late corporate borrowing in any industry, just as we know the policy of zero
interest installed by Japan Bank could not stimulate corporations to borrow
for investment. Corporate borrowing is restricted by bad performing loans
of banks in Pottery and Steel industries. New equity issuance increases net
assets and decreases leverage. Opposite to Adedeji (1998), Benito and Young
(2007), Tong and Green (2005), the negative relationship between dividends
and leverage is detected in Pottery and Steel industries.
4 Conclusions
This study applies Within3SLS to estimate simultaneous equations for panel
data and concludes a negative interrelationship between current leverage and
investment. In addition, it is detected explicitly that the previous term's re-
tention can relax current nancial distress and accelerate the investment.
New equity issuance can also contribute to investment behavior. Japanese
corporate borrowing was reduced after the Bubble collapse in spite of de-
creasing interest. Japanese corporate borrowing is restricted because of bad
performing loans, which is the most important reason why investment be-
havior was slackening in growth after the Bubble economy collapsed. Finally,
the relation of dividends and investment as well as the relation between div-
idends and leverage is detected to be opposite to previous research for UK,
China etc, because of a dividend system which is peculiar to Japanese capital
market.
Appendix
The subscript i is omitted for simplication.
Net investment It can be calculated using the formula It = Kt   Kt 1 +
Kt 1. The physical depreciation rate  employs the results calculated by
Hayashi (1991) for nonresidential buildings, structures, machinery, trans-
portation equipment, instruments tools and land respectively.
Kt is tangible capital.
Levt uses the ratio of total debt and net asset to net asset.
Rett 1 uses the ratio of previous term's retention to the Kt.
ROAt uses the ratio of current income to net asset.
qt uses the ration of market value to book value.
NEDt employs 1 if new equity is issued in current term, and 0 for other-
wise.
5Divt is the total of interim dividend per equity and term-end dividend
per equity.
GDt employs 0 from 1994 to 1997 and 1 from 1998 to 2005.
rt is calculated by formula (payment for interest + amortization of bond
premium)/( short-term loans + commercial paper + long-term loans + bond
+ convertible bond).
Baddebtt employs the ratio of bad performing loans of main bank4.
References
Adedeji,A. (1998) \Does the Pecking Order Hypothesis Explain the Dividend
Payout Ratios of Firms in the UK?" Journal of Business Finance and
Accounting 25, 1127-55.
Allen,D.E. (1993) \The Pecking Order Hypothesis: Australian Evidence"
Applied Financial Economics 3, 101-112.
Baltagi,B.H. (2001) Econometric Analysis of Panel Data, 2nd ed, John Wiley
& Sons.
Baskin,J. (1989) \An Empirical Investigation of the Pecking Order Hypoth-
esis" Financial Management 18, 26-35.
Benito,A. and Young,G. (2007) \Financial Pressure and Balance Sheet Ad-
justment by Firms"Oxford Bulletin economics and statistics 69, 581-602.
Hayashi,F. and Inoue,T. (1991) \The Relation between Firm Growth and Q
with Multiple Capital Goods:Theory and Evidence Panel Data on Japanese
Firms" Econometrica 59, 731-753.
Hirota,S.I. (1999) \Are Corporate Financing Decisions Dierent in Japan?
An Empirical Study on Capital Structure" Journal of Japanese and Inter-
national Economies 13, 201-229.
Honore,B.E. and Kyriazidou,E. (2000) \Estimation of Tobit Type Models
with Individual Specic Eects" Econometric Reviews 19, 341-366.
Hosono,K. (2003) \Growth Opportunities, Collateral and Debt Structure:
the Case of Japanese Machine Manufacturing Firms" Japan and the World
Economy 15, 275-297.
4The denition of main bank is very complicated. The rm may borrow the money
from more than a bank. In this paper, according to Japan Company handbook, The
highest percent loan lender is consider to be the main bank
6Loudermilk,M.S. (2007) \Estimation of Fractional Dependent Variables in
Dynamic Panel Data Models with an Application to Firm Dividend Policy"
Journal of Business & Economic Statistics 25, 462-472.
Tong,G. and Green,C.J. (2005) \Pecking Order or Trade-o Hypothesis? Ev-
idence on the Capital Structure of Chinese Companies" Applied Economics
37, 2179-89.
Toyo Keizai Inc (2000) Japan Company Handbook.
7Table 1: 3SLS estimation for Chemistry, Electrical appliances, Food industry
Chemistry Electrical appliances Food
Levt  2:43E   2( 4:38)  1:26E   2( 3:21)  2:33E   2( 3:82)
Levt 1 7:89E   3(2:66)  2:78E   3( 1:71)  6:30E   4( 0:703)
Rett 1 0:167(1:89)  1:97E   3( 0:06)  0:336( 0:153)
ROAt 0:440(2:41)  6:68E   2( 3:00) 0:184(4:36)
qt 4:90E   3(1:34) 1:06E   2(4:36) 3:57E   3(0:615)
NEDt 6:27E   3(0:554) 1:14E   2(0:970) 6:97E   2(3:19)
Divt  3:02E   3( 1:26) 7:81E   3(3:56) 2:17E   3(0:462)
GDt  2:77( 3:29)  1:06E   2( 1:25)  2:28E   3( 0:377)
(I=K)t  19:6( 1:93)  5:77( 1:46)  37:9( 2:86)
Rett 1 1:93(0:325)  1:09( 1:74)  13:9( 1:68)
ROAt 22:6(1:79)  2:71( 6:60) 7:27(2:92)
rt 19:7(1:49)  10:4( 1:07)  2:66(0:129)
Baddebtt  4:73( 0:595)  2:43( 0:81)  3:07( 0:436)
NEDt  0:391( 0:546)  6:43E   2( 0:245) 2:85(2:37)
Divt  0:215( 1:39) 2:55E   2(0:486) 9:34E   2(0:412)
Note: The t value is represented in the parentheses
   denotes significant at 0:01 level
  denotes significant at 0:05 level
 denotes significant at 0:10 level
8Table 2: 3SLS estimation for Machine, Metal, Motor industry
Machine Metal Motor
Levt 6:97E   4(0:06)  3:15E   2( 3:88) 3:74E   2(1:26)
Levt 1 3:60E   3(0:621)  6:70E   5( 0:044) 9:28E   3(0:471)
Rett 1  1:74( 0:386) 7:64E   2(0:241) 0:683(4:80)
ROAt 8:08E   2(0:989)  0:225( 1:87)  0:239( 2:14)
qt 1:32E   2(2:11) 1:30E   3(0:208) 1:11E   2(1:90)
NEDt 1:13E   2(0:313) 2:43E   3(0:113)  2:24E   3( 0:127)
Divt 3:83E   3(0:656) 7:47E   3(0:895)  6:54E   3( 2:10)
GDt 1:09(0:346)  3:11E   2( 1:69)  1:02E   2( 0:760)
(I=K)t  13:4( 0:955)  25:5( 4:69) 5:50(1:14)
Rett 1  2:38( 1:69)  0:704( 0:886)  7:99( 4:32)
ROAt  2:34( 0:766)  7:64( 2:46) 0:727(0:516)
rt 74:8(1:21)  1:00E   2( 0:150) 0:204(0:026)
Baddebtt  10:5( 0:703) 0:291(1:17) 2:18(0:079)
NEDt 0:188(0:127)  6:43E   2( 0:245)  0:280( 1:31)
Divt  2:25E   2( 0:088) 2:55E   2(0:486) 7:76E   2(2:41)
Note: refer to Table 1.
Table 3: 3SLS estimation for Pottery, Steel, Textile industries
Pottery Steel Textile
Levt  0:100( 2:22)  4:41E   2( 1:34)  4:03E   2( 5:88)
Levt 1 1:18E   2(0:632) 4:69E   2(2:01)  9:70E   4( 0:143)
Rett 1 0:725(3:17) 7:89E   2(0:738) 0:390(3:75)
ROAt 3:39E   2(0:111)  0:294( 1:42)  7:37E   2( 0:666)
qt  3:23E   3( 0:199) 1:52E   2(0:998)  3:75E   2( 1:15)
NEDt 6:75E   2(2:50)  9:80E   3( 0:045)  3:35E   2( 0:831)
Divt 9:25E   3(1:19) 1:44E   2(1:84) 2:40E   2(1:28)
GDt  1:27E   2( 0:477)  2:95E   2( 1:96)  4:18E   3( 0:209)
(I=K)t  3:54( 5:18) 30:3(3:41)  21:5( 6:59)
Rett 1  3:39( 5:51)  11:2( 5:54)  7:03( 5:57)
ROAt  3:49( 7:01)  8:20( 3:41) 0:195(0:122)
rt 7:91(2:14)  27:7( 1:50)  9:85( 0:533)
Baddebtt  3:91( 3:09)  19:2( 2:54) 7:91(1:11)
NEDt  0:223( 1:91) 0:367(0:694)  0:797( 0:989)
Divt  9:22E   2( 3:23)  0:427( 2:19) 0:243(0:953)
Note: refer to Table 1.
9Table 4: Comparison of the main results with the previous evidence
Tong and Green Benito and Young Adeedeji Zhu
(2005) (2007) (1998) (2009)
Sample rms China UK UK Japan
Investment and Leverage ? - + -
Leverage and Dividends + + + -
Investment and Dividends ? - - +
Investment and Protability ? + ?
Leverage and Protability - -
Note: + denotes signicant positive relation. - denotes signicant negative
relation. ? denotes inconclusive. Blank means that the relation is not dis-
cussed in the literature.
10

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The Relationship Between Investment and Fund Raising: An Empirical study to Japanese Manufacturing Firms

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