1246
support the hypotheses tested. Future research that includes more companies and years is needed to provide a robust set of results.
The hypothesized relationship between cash flowvoting rights and cost of equity is not supported. The comparison between Claessens 1998b sample and the samples
under study provides an insight why this is so. Table 4.5 indicates that even the minimum voting rights found in the samples in this study is quite close to the mean of
28 in Claessens 1998b study. Seventy five percent of companies in the samples have ultimate controlling party with voting rights above 3638. Similarly the mean
cash flow rights in all samples in this study are almost twice that reported in Claessens 1998b. 75 of the companies have ultimate controlling party with cash flow rights
above 28. Similar pattern is observed in Fan and Wong 2002 whose study includes 177
Malaysian companies. The mean voting rights is 31 whilst the mean cash flow rights is reported to be 26. As in Claessens et al 1998b study the reported mean CFVR is
85. Further both Claessens et al 1998b and Fan and Wong 2002 capped the voting rights at 50. They stopped analyzing the voting rights of the ultimate controlling party
once the voting rights breaches 50. So the maximum voting rights for the companies in the sample is 50.
Certainly the off setting effect of increasing cash flow rights and increasing voting rights is complex and merit more research. Previous research such as Claessens
1998b found that at a higher level of control the tendency to expropriate, which is expected in information asymmetry situations, is higher. However the insignificant result
in this study suggests that even though the disparity between cash flow and voting rights exists, at higher level of control and even higher level of cash flow, market does not price
the disparity because the ultimate controlling party is not expected to expropriate or inhibit information as the cash consequence of his action is more significant.
1247
Finally the lack of significant association between cash flowvoting rights disparity and the cost of equity, could be due to the effective presence of a substantial
shareholder. As found, substantial shareholders‘ voting rights, SSVR, is fairly consistent in showing negative association with cost of equity.
The significant negative relationship with cost of equity suggests that a lower percentage holding of substantial shareholder poses information risk. This is consistent
with the theory in general, as an increase in voting rights afford the substantial shareholder more bargaining power for inclusion in the decision making process such as
being a member of the board of directors. Therefore this increase the chance of more information flow to the public, information which otherwise would be in the proprietary
control of the ultimate controlling party. This result contributes towards the ‗information argument‘ Fan Wong β00β. That is the presence of others other than the controlling
party increase the likelihood that proprietary knowledge of the company is shared to the others and decrease the likelihood that it is concentrated to certain individual which
leads to opacity of information. The wider the set of informed individuals the greater the likelihood that information ‗leaks‘ to the public and thus reduce the company‘s
information risk. Previous researches Jung and Kwon 2002, Koh 2003 and Chung, Firth and
Kim β004 associate substantial shareholder‘s voting rights with earnings quality measure. The cost of equity effect, that is the information risk effect, has never been
examined. The finding that substantial shareholders‘ shareholding is priced is a new and significant contribution not only in the Malaysian context but also elsewhere. Thus not
only substantial shareholder is an important mechanism, it is also perceived as such by the market.
The hypothesis that there is a cost of equity effect of earnings quality is largely supported. There is nothing new in this finding except that this study examines
1248
companies in an emerging market. Therefore even in an emerging market investors are sophisticated and do price earnings quality with low earnings quality being perceived as
information risks. Whilst there have been many studies on Malaysian companies that examine
earnings quality, especially abnormal accruals in relation to many variables such as board characteristics, managerial ownership, etc. there has never been any Malaysian
studies that prove that abnormal accruals are priced. The consequence of this is that the preparer may gain in manipulation of accounts but they stand to lose in terms of higher
required return by investors. This research has looked at one dimension of the ultimate controlling party and
that is the cash flowvoting rights disparity. However the ability and potential to inhibit information may be explained by another layer of control and that is control obtained by
direct possession of knowledge regarding the operations. This is achieved by direct involvement with operation or close relationship with those in direct involvement. This
research has not differentiate the ultimate controlling party who are and are not in executive position. In the same line of argument this research has not separated out the
substantial shareholders who are in actual fact a partner of the ultimate controlling party and the substantial shareholders who are really an outsider. Obviously the presence of
the former may impair its monitoring role and thus may not ‗leak‘ information to the public.
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1252
THE EFFECT OF MANAGERIAL OWNERSHIP ON THE COST OF DEBT: EMPIRICAL EVIDENCE FROM JAPAN
Akinobu Shuto, Kobe University Norio Kitagawa, Kobe University
First version: June 2009
Abstract: We examine the effect of managerial ownership on interest rate spread on
corporate bonds for Japanese firms. First, we find that managerial ownership is positively associated with interest rate spread after controlling for other aspects of the Japanese
ownership structure, cross-shareholding and stable shareholdings by financial institutions. Second, by employing factor analysis to measure the agency cost of debt based on
financial variables, we find that managerial ownership has a higher correlation with interest rate spread when the agency cost of debt at the time of bond issue is larger. Our
results suggest that prospective bondholders use managerial ownership information to anticipate a firm‘s future agency cost of debt, and estimate it to be higher when the
current agency cost of debt at bond issue is larger. Further, our results indicate that accounting information is useful for estimating the agency cost of debt and increasing the
efficiency of bond contracts.
Keyword: managerial ownership; agency cost of debt; bond yield spread. Data Availability: Data are publicly available from sources identified in the paper.
1253
I. Introduction
This study examines the effect of managerial ownership on the cost of debt. Specifically, it investigates the relationship between managerial ownership and the cost
of debt as measured by the interest rate spread on corporate bonds for Japanese firms. Agency theory predicts that the shareholdings of managers help align the
managers‘ interests with those of the shareholders Jensen and Meckling 1976. This incentive alignment effect is expected to have a greater impact as managerial ownership
increases. This suggests that as managerial ownership increases, corporate performance also increases Morck et al. 1988. On the other hand, however, the theory also suggests
that managerial shareholdings lead to a conflict between shareholders and bondholders Jensen and Meckling 1976; Myers 1977. In particular, limited liability shareholders
ma y have an incentive to expropriate bondholders‘ wealth through investments and
financial decisions aimed at reducing the value of the firm‘s outstanding debt. For example, owner-managers by levered firms may have an incentive to invest in
projects that are riskier than those specified by bondholders. This is commonly called the
―risk-shifting problem.‖ Further, owner-managers have an incentive to conduct wealth
transfers by financing activities such as changes in the dividend policy and the issuance of additional debt. In an efficient market, rational bondholders should recognize owner-
managers‘ incentives to increase shareholder wealth at the expense of their wealth and should accordingly adjust the required yield.
Some empirical investigations support the prediction of agency theory. Ortiz-
Molina 2006 and Bagnani et al. 1994 empirically tested the implication of the risk- shifting problem
. Ortiz-Molina 2006 provides evidence that managerial ownership is
1254 positively correlated with the yield spread of corporate bonds. Bagnani et al. 1994
indicate that an increase in managerial ownership increases the cost of debt measured by bond return premia when managerial ownership is low. Consistent with the implication of
the theory, these results suggest that bondholders obtain price protection against the potential agency cost of debt. Furthermore, the authors argue that the relation between
shareholdings by managers and the cost of debt is nonmonotonic, and they provide some evidence in support of their argument.
Our study is also related to the studies focusing on the effect of the corporate governance structure on the cost of debt. Anderson et al. 2003 investigate the impact of
the founding family ownership structure on the agency cost of debt and indicate that family ownership is associated with a lower cost of debt financing. Bhojraj and Sengupta
2003 explore the link between governance mechanisms and bond yields and ratings. They reveal that the cost of debt on new debt issues is negatively associated with the
percentage of shares held by the institutions and the fraction of the board comprising non- officers i.e., stronger external control of the board. Overall results indicate that
corporate governance mechanisms could affect the cost of debt by mitigating agency costs.
The first research objective of this study is to examine the relationship between managerial ownership and the cost of debt for Japanese firms. Following the empirical
implication of the theory, we hypothesize that managerial ownership is positively associated with the interest rate spread. In addition to managerial ownership, we explore
the effect of other ownerships in the Japanese corporate ownership structure on the cost
1255 of debt because it is often argued that Japanese ownership structures have unique
characteristics as compared to those of other countries. We control the effect of two institutional ownerships: cross-shareholding and stable
shareholding by financial institutions. Cross-shareholding, which refers to mutually exchanging equity shares in a pair of firms, has been a common practice in Japan. Further,
stable shareholding by financial institutions, mainly represented by the main bank, is a unique practice and was a grave concern during the 1990s in Japan. We examine the
functioning of these Japanese ownership structures in a bond market setting. We find support for the hypothesis that managerial ownership has a positive
association with interest rate spread. The results suggest that prospective bondholders in Japan perceive managerial ownership as a structure that increases the potential conflict
between shareholders and bondholders, and they incorporate this perception in the pricing of new corporate bond issues. Moreover, we find that stable shareholding is positively
associated with interest rate spread, while cross-shareholding exhibits no significant correlation in this regard. The findings are consistent with the argument that stable
shareholdings by financial institutions play an active role in reducing managerial opportunism and mitigating the wealth transfer problem between bondholders and
shareholders. The second research objective of this study is to examine the effect of the potential
agency cost of debt of bond-issuing firms at the time of issue on the relation between managerial ownership and the cost of debt. As predicted by the theory, managerial
shareholdings may induce opportunistic behavior by firm managers aimed at increasing
1256 their benefits at the expense of bondholders‘ wealth. Our first result is consistent with the
implication of the theory. If firm managers have already engaged in moral hazard behaviors or have a wide
range of options for this purpose at the time of bond issue, bond investors would estimate a higher future agency cost of debt and default risk for the firm because prospective
bondholders consider that such managers exhibit a high probability to conduct actions that transfer the wealth of bondholders to them after bond issue, which results in an
increase of the interest rate spread. Therefore, we hypothesized that managerial ownership has a higher correlation with the interest rate spread when the agency cost of
debt at issuing bonds is already larger. To measure the agency cost of debt of bond issuing firms, we reduce six financial
variables related to the agency cost of debt to a single index by using factor analysis. Our results indicate that managerial ownership has a stronger effect on interest rate spread
when the agency cost of debt is larger, which supports our hypothesis. Further, we conduct some analyses to verify the validity of our hypothesis because
a part of our results is not consistent with the results of prior studies. Bagnani et al. 1994 indicate that managerial ownership is nonmonotonically related to the cost of debt.
They advocate that at high ownership levels, managerial ownership is negatively correlated to the cost of debt because of two reasons: the first reason is that large
shareholdings by managers could induce firm managers to be more concerned about the
nonsystematic risk of firms, which reduces the risk-shifting problem. The second reason
is that when managerial ownership is high, managers can become entrenched and their risk choice is not dependent on the preference of shareholders. Both arguments assume
1257 that at high ownership levels, the positive effect of managerial ownership on managerial
risk-taking can be weaker, and as a result, managerial ownership is expected to be nonlinearly associated with the cost of debt.
To address the possibility of this nonlinear relationship, we perform regression analyses by employing the quadratic form regression model. The result does not indicate
that the relation between managerial ownership and interest rate spread is nonmonotonic, as indicated by Bagnani et al. 1994. The result reveals that managerial ownership is
positively and linearly associated with interest rate spread. In the subsequent section, we present possible explanations as to why our results differ from those of Bagnani et al.
1994. To ensure the robustness of our results, we conduct further analyses such as those
on bond rating and the potential endogeneity problem and those conducted using the Fama and Macbeth 1973 approach. We find that our results are robust under these
additional analyses. This study makes several contributions to the literature on finance and accounting,
and the understanding of practice of the Japanese bond market. First, our results suggest that Japanese bond investors use managerial ownership information to anticipate a firm‘s
future agency cost of debt, and that they incorporate this prediction in determining the bond yield spread. In addition, the results indicate that bond investors estimate a firm‘s
future default risk to be higher when the agency cost of debt at issuing bond is already larger. Therefore, our results indicate that managerial ownership is an important
determinant of bond yield spread in the processes of the Japanese bond market.
1258 Second, this study contributes to prior studies by clarifying that the agency cost of
debt at the time of bond issue affects the anticipation of the future potential agency cost of debt that reflects the interest rate spread. While prior studies consider managerial
opportunistic behaviors arising from the conflict between bondholders and shareholders only from the perspective of the risk-shifting problem Ortiz-Molina 2006; Bagnani et al.
1994, this study develops hypotheses based on inclusive opportunistic behaviors by managers and constructs a composite measure for the degree of the agency cost of debt.
These procedures contribute to the verification of the validity of theoretical hypothesis based on the agency cost of debt, and they discriminate the alternative hypotheses.
Further, these results support the utility of accounting information in debt contracting because they suggest that prospective bondholders use financial information
to anticipate the potential agency cost of debt in decision making for bond investments.
Although we already know that accounting information provides ex post benefits to bondholders through accounting-based debt covenants in the debt contracting process
Watts and Zimmerman 1986, our results indicate the ex ante role of accounting information in the debt contracting process. This acts as evidence suggesting that
accounting information plays an important role in increasing the efficiency of bond contracts.
Finally, this is the first study that examines the effect of Japanese corporate ownership on the cost of debt in the Japanese bond market. It is often advocated that the
Japanese ownership structure is quite different from that of other countries. Previous studies have investigated the impact of the Japanese ownership structure on firm
performance Prowse 1992; Lichtenberg and Pushner 1994; Morck et al. 2000. Our
1259 study contributes to these studies by resolving the functioning of the Japanese ownership
structure in a bond contract setting. Further, it should be noted that in our result, managerial ownership has a strong
effect on the interest rate spread after controlling for other aspects of ownership structure, cross-shareholding and stable shareholding by financial institutions, which are often
emphasized as characteristics of the Japanese ownership structure. Although previous studies examining the Japanese ownership structure generally focus on the findings
related to the unique aspects of ownership structure, such as cross-shareholding and main banks, our results reveal that the empirical implication of the traditional agency theory on
managerial ownership is supported by the analyses for the Japanese bond market, which is consistent with the findings of analyses for US firms Ortiz-Molina 2006; Bagnani et al.
1994. The remainder of this paper is organized as follows. Section II describes the
theoretical background and develops the hypotheses. Section III explains the research model for testing our hypotheses. Section IV outlines the sample selection procedure and
describes the variables used in this analysis. Section V reports the empirical results on the relation between managerial ownership and interest rate spread. Section VI summarizes
the results of additional analyses. Finally, Section VII concludes the study with a summary.
II. Hypothesis development
Managerial ownership and the cost of debt
1260 Our first research objective is to examine the effect of managerial ownership on the
cost of debt. Prior studies indicate that shareholdings held by managers create a conflict of interest between shareholders and bondholders Jensen and Meckling 1976; Myers
1977. This conflict induces owner-managers to take investment and financing decisions that benefit them at the expense of the bondholders. With respect to the investment
decisions, owner-managers have an incentive to transfer wealth to shareholders from bondholders by taking excessive risk, which is referred to as risk-shifting or asset
substitution. Consequently, according to the theory, it is expected that as managerial ownership increases, firm managers become more likely to make investment decisions
involving higher risks that are consistent with the interests of the shareholders, at the expense of the bondholders.
The other source of conflicts of interest between shareholders and bondholders involves financing decisions such as dividend policy and the issuance of new debt.
Owner-managers have an incentive to distribute cash funds themselves when firms are financed partially by debt Myers 1977. For instance, firm managers may forgo positive
net present value projects, and instead, pay dividends to shareholders or repurchase shares. Furthermore, managers could sell existing business assets and distribute the
proceeds to shareholders by dividends or share repurchase. In the extreme case, such managerial behaviors could sell off all business assets through a discretionary dividend
policy, leaving the bondholders with an ―empty corporate shell.‖ Finally, it is often argued that the issuance of additional debt also transfers wealth
from the original bondholders to the managers and consequently creates costs that reduce the value of the firms Watts and Zimmerman 1986. In practice, the owner-managers can
1261 issue additional corporate bonds after the original bond is issued. The issuance of new
debt dilutes the value of existing debt. The dilution is particularly strong if the new debt is either secured or senior to the original debt Tirole 2006.
Since rational bondholders know that their interests might conflict with the interests of owner-managers, they would demand a higher interest rate on corporate
bonds as a compensation for the added risk on the risk-shifting and discretionary financing behaviors by owner-managers. This higher interest rate is the way bondholders
obtain price protection against the possibility that owner-managers will take actions that benefit shareholders but harm bondholders.
196
Thus, this argument leads to our first hypothesis that shareholdings of managers increase the cost of debt.
Hypothesis 1: Managerial ownership is positively associated with the cost of debt.
The effect of the potential agency cost of debt on the relation between managerial ownership and the cost of debt
Our second research objective is to examine the effect of the potential agency cost of debt of bond issue firms at the time of issue on the relation between managerial
ownership and the cost of debt. In the development of the first hypothesis, we assume that owner-managers take investment and financing decisions that benefit them at the
expense of bondholders, and that bondholders use managerial ownership information to predic
t a firm‘s future agency cost of debt.
196
Another way to reduce conflicts of interest between bondholders and shareholders is to write bond covenants that restrict the owner-
managers‘ behaviors to harm bondholders‘ wealth Smith and Warner 1979. However, McDaniel 1986 indicates that while the use of bond covenants
reduces the agency cost of debt, the protection offered by these covenants cannot totally eliminate the conflicts between bondholders and shareholders.
1262 If firm managers have already engaged in opportunistic behavior that increases the
agency cost of debt or have a wide range of options for this purpose at the time of bond issue, prospective bondholders are likely to anticipate a higher future agency cost of debt
and default risk for the firm. The behaviors of managers, such as highly risky investment, excessive dividend payment, and frequent insurance of debt before the corporate bond
issue, would make prospective bondholders more sensitive to firms‘ future agency costs
of debt arising from shareholding by managers. The bondholders would consider that such managers have a high incentive in transferring the wealth of bondholders to them
after the bond issue. In reality, although it is difficult for the bond inventors to completely grasp the
agency cost of debt, they can estimate it by using accounting information in financial statements to a certain extent. Prior studies indicate that some financial variables are
useful in measuring the potential conflict between bondholders and shareholders Long and Malits 1985; Titman and Wessels 1988; Prowse 1990; Hwang and Kim 1998; Ahmed
et al. 2002. We expect that prospective bondholders can grasp the agency cost of debt by observing financial variables at the time of bond issue and incorporate their estimation in
the pricing of new corporate bond issues. Therefore, we expect that the shareholding of managers has a stronger effect on the
cost of debt when the potential agency cost of debt at issuing bonds is larger.
Hypothesis 2: Managerial ownership has a higher correlation with the interest rate spread when the agency cost of debt at the time of bond issue is larger.
1263 The alternative hypotheses
We should note that some prior studies reveal the possibility that managerial ownership is nonlinearly associated with the cost of debt, which suggests the existence of
alternative hypotheses. Bagnani et al. 1994 and Ortiz-Molina 2006 argue that at low ownership levels, managerial ownership is positively correlated to the cost of debt due to
the risk-shifting problem, which is consistent with our first hypothesis. However, they also advocate that at high ownership levels, managerial ownership has a negative
correlation with the cost of debt. Consequently, it is expected that the relation between managerial ownership and the cost of debt is nonmonotonic. The aforementioned studies
present two possible explanations about the negative relation between managerial ownership and the cost of debt at high ownership levels. First, as managerial
shareholding increases, the firm managers would be more concerned with the nonsystematic risk of the firms because their wealth is less diversified Saunders et al.
1990, which reduces the risk-shifting problem. Second, at high ownership levels, managers can become entrenched because they
can use their control of votes to protect their position, and thus, their decisions regarding risk-taking are not dependent on the preferences of the shareholders Morck et al. 1988.
Both theoretical considerations suggest that managerial ownership is not positively associated with the cost of debt at high ownership levels.
The empirical results remain mixed and inconclusive. Bagnani et al. 1994 indicate that the relation between managerial ownership and bondholder returns is
nonmonotonic according to their hypothesis. On the other hand, Ortiz-Molina 2006 provides evidence that although the shareholdings of managers, including stock option
1264 holdings, are nonlinearly associated with yield spread, managerial ownership does not
have a nonmonotonic relationship with yield spread. Overall, with respect to the empirical investigation on the effect of managerial ownership, only the findings of
Bagnani et al. 1994 indicate a nonlinear effect of managerial ownership on the cost of debt.
With regard to the reason for the inconclusive results mentioned above, numerous points about the validity of their hypothesis development on nonmonotonic relationships
can be considered. While this study develops hypotheses based on the inclusive implication of the theory of agency cost of debt, they discuss the effect of managerial
ownership only from the perspective of the risk-shifting problem and do not consider other managerial behaviors such as financing decisions. This lack of consideration may
reduce the validity of their hypothesis because the expected effect of managerial ownership related to financing decisions does not clearly suggest that the relation
between managerial ownership and the cost of debt is nonmonotonic. Further, with respect to the managerial entrenchment effect that the aforementioned
studies depend upon in their hypotheses development, we can derive an opposite prediction about the relation between managerial ownership and the cost of debt. Prior
studies provide evidence that entrenched managers decrease firm performance because of their opportunistic behaviors Morck, Shleifer, and Vishny 1988; McConnell and Servaes
1990; Short and Keasey 1999.
197
Since such opportunistic behaviors decrease firm values and increase the default risks of the firms, we also expect that managerial
ownership increases the bond yield spread, following the implication of the managerial
197
With regard to Japanese firms, prior studies have clarified the entrenchment effect from some perspectives: firm performance Teshima 2004, earnings management Teshima and Shuto
2008, and accounting conservatism Shuto and Takada 2008.
1265 entrenchment effect, which implies a positive association between managerial ownership
and the cost of debt.
Thus, this leads to an empirical question whether there is a nonmonotonic relation
between managerial ownership and the cost of debt. Hence, in Section VI, we conduct an additional examination assuming that there is a nonmonotonic relation between
managerial ownership and interest rate spread and compare the obtained results with those of prior studies.
III. Research design
Research model to test hypothesis 1 To test hypothesis 1, we examine the association between managerial ownership
and bond yield spread by estimating the following model:
SPREAD = C +
1
MO +
2
CROSS +
3
FSTABLE +
4
MARGIN +
5
DER +
6
INCR +
7
LNASIZE +
8
BSIZE +
9
MATURE +
10
BCFIRM +
11
RISKP + YEAR + ε,
1 where
SPREAD = the interest rate spread on the first straight bond issued of the fiscal year;
the spread is the difference between the interest rates on the bond issued by the firm and on government bonds
MO = the fraction of the shares owned by directors at the end of fiscal year t
1266 CROSS
= the fraction of the shares owned by cross-shareholders at the end of fiscal year t
FSTABLE = the fraction of stable shareholdings by financial institutions at the end of
fiscal year t MARGIN
= the operating income divided by net sales at the end of fiscal year t DER
= the debt equity ratio at the end of fiscal year t INCR
= the interest coverage ratio at the end of fiscal year t LNASIZE
= the natural log of total assets at the end of fiscal year t BSIZE
= the log of the issue size MATUR
= the number of years till maturity BMCOMP
= an indicator variable that takes the value of one if a bond management company is established, and zero otherwise
RISKP = the risk premium the average values of SPREAD
on RI‘s A bonds for the month of issue
We use the interest rate spread on straight bond issues SPREAD to measure the cost of debt. As a proxy for managerial ownership MO, we use the ratio of the shares
owned by the directors on the board. The ratio of the shares owned by all directors should be used in this study because prior studies such as Aoki 1990 and Milgrom and Roberts
1992 argue that the Japanese corporate governance system functions more through consensus than through a CEO-dominated system, as is the case in the US. Further, they
argue that Japanese board members make decisions as a group. Teshima and Shuto 2008 examine the effect of managerial ownership on the earnings management behavior
1267 for Japanese firms. They also use the ratio of the shares owned by all directors as a proxy
for managerial ownership.
198
If the relationship between managerial ownership and the cost of debt is similar to the prediction of hypothesis 1, the coefficient of MO would be
expected to be positive. Institutional ownership could also influence managerial behavior, and for Japanese
firms, the influence of cross-shareholding CROSS and stable shareholdings FSTABLE by financial institutions is noticeable Prowse 1990; Lichtenberg and Pushner 1994;
Isagawa 2007. The stable shareholdings by financial institutions, mainly represented by main banks, would have a positive effect on the cost of debt. Since the stable
shareholders, including main banks, have superior information and ability to monitor the inefficient behaviors of firm managers,
the cost of debt of firms with a high number of stable shareholders is expected to be lower.
Shareholders that are cross-owned are also expected to have an incentive to monitor firm managers because they share a relationship with the firms as trade partners
Osano 1996; Isagawa 2007. Further, cross-shareholding strengthens the stability of firm
management by decreasing the threat of a hostile takeover, permitting managers to develop operations according to a long-term perspective. The perspective may be
consistent with the interests of the bondholders, and it may lower the cost of debt.
199
In contrast, we can also predict that cross-shareholding would have a negative effect on the
cost of debt. It is often argued that cross-shareholding enhances managerial
198
Further, prior studies examining executive compensation for Japanese firms usually employ total cash compensation data of the board directors as a proxy for executive compensation and
present significant results Kaplan 1994; Joh 1999; Shuto 2007. This is consistent with the above argument.
199
Anderson et al. 2003 examine the relation between founding family ownership and the cost of debt, and argue that the family‘s strong interest in the firm‘s long-term survival could mitigate
the divergence of interests between bondholders and shareholders.
1268
entrenchment Prowse 1992; Sheard 1994; Isagawa 2007
, and the increased agency costs associated with managerial opportunism may increase the cost of debt. Therefore,
while the coefficient on FSTABLE is expected to be negative, the expected sign on CROSS
cannot be predicted. Following Sengupta 1998 and Shuto et al. 2009, we set the control variables for
the cost of debt.
200
The cost of debt can be explained in the following terms: 1 characteristics of the issuer, 2 characteristics of the issued bonds, and 3 market
conditions. For the variables controlling the characteristics of the issuer, we employ the
operating income divided by net sales MARGIN, debt equity ratio DER, interest coverage ratio INCR, and natural log of the total assets LNASIZE. Firms with a higher
profit margin and interest coverage ratio are expected to enjoy a lower SPREAD. Further, asset-rich firms are expected to have a lower SPREAD because of their solvency.
Therefore, the expected signs of the coefficients on these control variables MARGIN, INCR
, and LASSET are all negative. In contrast, we expect that the firms with a higher debt equity ratio have a higher SPREAD because the debt equity ratio reflects the default
risk of the firm. The coefficient on DER is expected to be positive. As a proxy for the characteristics of issued bonds, we use the log of the total
amount of the bond BSIZE, the number of years till maturity MATURE, and the dummy variable BMCOMP that takes the value one if the bond management company
that monitors the bond on behalf of the bondholders is established, else, its value is zero. Following the economies of scale in underwriting, the issue size would be negatively
200
Sengupta 1998 examines the effect of disclosure quality on the bond interest rate for US firms, and Shuto et al. 2009 investigate the bond yield spread for Japanese firms.
1269 related to SPREAD. Bonds with a longer maturity period are expected to have a higher
SPREAD because of their greater default risk exposure. Bonds that are monitored by a
bond management company would enjoy a lower SPREAD because the establishment of the bond management company is expected to contribute toward protecting the
bondholder. The expected signs of the coefficients of BSIZE and BMCOMP are negative, and the expected sign of the coefficient of MATURE is positive.
Finally, we use risk premium RISKP as a control variable proxy for market conditions. RISKP denotes the average values of SPREAD on bonds that are rated as A by
Rating and Investment Information Inc. RI for the month of issue of the bonds.
201
We expect the sign of the coefficient of RISKP to be positive because this variable is
expected to capture the time series variation in the risk premium over the business cycle.
Research model to test hypothesis 2 To measure the potential conflict between bondholders and shareholders i.e., the
agency cost of debt, we construct a composite measure of the degree of the agency cost of debt. Specifically, we reduce the following six financial variables related to the agency
cost of debt into a single index by using factor analysis:
ACD 1 = RD expendituresales
ACD 2 = 1
– fixed assetstotal assets ACD
3 = cash and marketable securitiestotal assets
201
Sengupta 1998, p.464 calculated this variable on the basis of the interest rate of εoody‘s
AAA bonds. However, we could not calculate the average SPREAD for the month of issue because there were insufficient issued bonds with the AAA rating to calculate RISKP in our
sample. Following Shuto et al. 2009, we then used SPREAD on RI‘s A bonds to compute
RISKP.
1270 ACD
4 = common dividendstotal assets ACD
5 = the standard deviation of ROA net incometotal assets for the past five years ACD
6 = the standard deviation of leverage total debttotal assets for the past five years
These financial variables are expected to capture the severity of potential agency conflict between shareholders and bondholders. The first three variables ACD 1, ACD 2,
and ACD 3 are widely used in prior studies and are expected to measure the extent to which firm managers with risk-shifting incentives can engage in wealth-transferring
investment policies that cannot be easily detected by the bondholders Long and Malits 1985; Titman and Wessels 1988; Prowse 1990; Hwang and Kim 1998.
ACD 1 is the measure of the research and development intensity of the firms. ACD
β is the proportion of the firm‘s assets not involved in fixed plant and equipment. These assets can be regarded as sources for the potential agency cost of debt because firm
managers with risk-shifting incentives are likely to have a wide range of options for discretionary behavior and use these assets for other risky investments. ACD 3 measures
the short-
term liquidity of the firm‘s assets. C ash and marketable securities are expected
to be another source of agency conflicts because of the risk-shifting incentives of managers because managers can substitute these assets for risky assets with relative ease.
The last three variables ACD 4, ACD 5, and ACD 6 are generally based on the definition of Ahmed et al. 2002 who employ proxies for bondholder-shareholder
conflicts over dividend policy. ACD 4 is the level of dividends, measured as a percentage of the assets. If a firm pays a high level of dividend, then the bondholders are more likely
1271 to be concerned about the firm‘s dividend policy. Paying a high level of dividend is a
typical moral hazard problem, and it possibly indicates more severe bondholder- shareholder conflicts over dividend policy.
ACD 5 is the proxy for the firm‘s operating uncertainty measured by the standard
deviation of its return on assets. Watts 1993 and Ahmed et al. 2002 argue that greater uncertainty about future profits implies a greater risk that excess dividends based on
temporarily inflated earnings may be paid to shareholders. Thus, greater uncertainty in this regard is likely to increase bondholder-shareholder conflicts over dividend policy.
Finally, we calculate ACD 6, as measured by the standard deviation of leverage total debttotal assets, for grasping the moral hazard behaviors of managers on debt
financing decisions. Firm managers can issue other debt instruments after the original debt is issued. The issuance of additional debt transfers wealth from the original debt
holders to the managers, and in the process, creates a cost that reduces the value of firms Watts and Zimmerman 1986. We use the volatility of leverage to measure the agency
cost of debt on debt financing decisions because the frequent issuance of additional debt is likely to increase it.
Prior studies assume that each of these variables can be proxy for the potential agency cost of debt and obtain the results that are consistent with their assumption. In
practice, however, it is likely that rational bondholders estimate the agency cost of debt of issuer firms by considering various types of moral hazard behaviors of managers
simultaneously and take investment decisions. Focusing on a single variable does not
completely capture the conflict between bondholders and shareholders, the agency cost of debt. Therefore, to comprehensively estimate the agency cost of debt of issuer firms, we
1272 construct a composite measure of the degree of the agency cost of debt by using factor
analysis to reduce the above six financial variables into a single index.
Insert Table 1 about here
Factor analysis assumes that attribute measures are intercorrelated and that they exert load on a single factor. Panel A of Table 1 reveals that the correlations among the
six financial variables are all positive and most of the correlations are significant as expected. Panel B of Table 1 shows that a single factor loaded by these six attribute
measures justifies around 33.5 of the cumulative variance. Panel C of Table 1 reports the factor loadings, all of which have positive signs as expected. Overall, the results
suggest that our factor analysis provide useful composite measures for the degree of the agency cost of debt.
202
To test hypothesis 2, we estimate the following models by using a calculated composite measure of the agency cost of debt ACD:
SPREAD = C +
1
MO +
2
MOACD +
3
CROSS +
4
FSTABLE +
5
MARGIN +
6
DER +
7
INCR +
8
LNASIZE +
9
BSIZE +
10
MATURE +
11
BCFIRM +
12
RISKP + YEAR + ε,
2 where
ACD = the agency cost of debt, computed using factor analysis based on six financial
variables: 1 RD expendituressales, 2 1 – fixed assetstotal assets, 3
cash
202
Although we also conduct factor analysis on a year-by-year basis for our sample and calculate the ACD by each year 1996
–2003, the results are generally consistent with those of the body.
1273 and marketable securitiestotal assets, 4
common dividendstotal assets, 5 the
standard deviation of ROA net incometotal assets for the past five years, and 6 the standard deviation of leverage total debttotal assets for the past five years.
The positive negative coefficient of MOACD provides evidence that the association between managerial ownership and interest rate spread is greater smaller
when the agency cost of debt at issuing corporate bonds is larger smaller. Therefore, the expected sign of the coefficient of MOACD for supporting hypothesis 2 is positive.
IV. Sample selection and descriptive statistics
Sample selection The sample of Japanese firms was selected on the basis of the following criteria:
i The firms issued straight bonds from April 1997 to March 2004.
ii Banks, securities firms, insurance firms, and other financial institutions are
eliminated from this study. iii
The fi rms‘ financial year ends in εarch.
iv The financial statements, stock prices, and bond issue data necessary
for this study are available from the respective databases mentioned below.
The data on bond issues during the sample period are collected from the Bond database
issued by I-N Information Systems Ltd. This database provides detailed security-specific information on corporate bonds, including interest rate spread, total
1274 amount of the bond, number of years till maturity, and credit rating. We collected data
regarding managerial ownership, financial statements, and stock prices from Nikkei NEEDS - Financial QUEST
of Nikkei Media Marketing. The other corporate ownership variables, cross-shareholdings and stable shareholdings, were obtained from the NLI
Research Institute, the Data Package of Cross-Shareholding and Stable Shareholding. Cross-shareholders include all domestic companies listed on the Japanese stock markets
at the end of the fiscal year. The stable shareholdings are defined as the fraction of the shares that are owned by stable shareholders at the end of the fiscal year. Stable
shareholders include financial institutions, trust banks, and other financial institutions i.e., brokerage companies and securities finance companies.
203
Bond information must be matched with corporate ownership and financial statement data. If the firm issues the bond for fiscal period t,
then corporate ownership and other financial statement data for the period t
– 1 are matched with the bond. The
accounting data is based on consolidated financial statements.
204
In order to ensure that the results are not sensitive to extreme values, observations in the highest and lowest one
percent of SPREAD and of each accounting variable were omitted. The final sample
consisted of 643 firm-year observations.
Descriptive statistics Table 2 presents descriptive statistics for the variables used in this study. It shows
that the mean median yield spread of a corporate bond over a government bond having
203
These also include parent companies.
204
We also conducted robustness tests by using unconsolidated financial statements because consolidated financial statements were not required for primary financial statements under the
Securities and Exchange Law of Japan before March 2000 Shuto 2009. The results based on unconsolidated financial statements data are consistent with those of the analyses of the body.
1275 the same characteristics is about 0.61 0.51, with a standard deviation of 0.425. For
our sample, the mean median percentage of managerial ownership MO is 0.007 0.001, which exhibits fair skewness distribution. This value is lower than that of prior
studies that have examined the managerial ownership of Japanese firms Teshima 2004; Shuto and Takada 2008; Teshima and Shuto 2008.
Insert Table 2 about here
In our opinion, the lower value arises from the fact that our sample is restricted to firms that issue corporate bonds. Since it is likely that the firms that issue bonds are
relatively large and mature, the managerial ownership of these firms is expected to be smaller.
205
Further, we can observe that the value of managerial ownership in the sample of Ortiz-Molina 2006 for US firms is considerably smaller than that of prior studies.
The value of cross-shareholding ownership CROSS is 12.6, whereas that of stable shareholding ownership FSTABLE is 16.
Insert Table 3 about here
Table 3 indicates the correlations matrix for the variables on the analysis of cost of debt. The lower left-hand portion of the table reports the Pearson correlations, and the
205
Prior studies that examine Japanese firms indicate that managerial ownership is negatively correlated with firm size, which support our consideration. For example, Shuto and Takada
2008, which examines Japanese firms from 1990 and 2005, indicate that managerial ownership is negatively and significantly correlated with firm size The coefficient of spearman correlation =
– 0.438, p-value = 0.000. In our sample, Table 3 also indicates that MO is negatively correlated with LNASIZE.
1276 upper right-hand portion presents the Spearman rank-order correlations. The Pearson
correlations reveal that MO is positively correlated with SPREAD 0.16, as expected. Table 3 also shows that MO is positively correlated with ACD 0.13, and that ACD is
positively correlated with SPREAD 0.30. The results suggest that managerial ownership is positively associated with the agency cost of debt for the fiscal year immediately
preceding the bond issue, and that the agency cost of debt is positively associated with interest rate spread.
V. Main results
Managerial ownership and interest rate spread We estimate regression model 1 to test hypothesis 1, the results of which are
summarized in Table 4. The reported t-statistics are based on the heteroscedasticity- corrected covariance matrix by White 1980. In model 1, the coefficient of MO is
1.829 and significantly positive at the less than 0.01 level, as expected. This result holds after controlling for the other ownership structure, characteristics of the issuer,
characteristics of the issued bonds, and market conditions. Thus, managerial ownership has an incremental explanatory power for the cost of debt when the other ownership
structure and control variables are given. The result suggests that prospective bondholders interpret an increase in managerial ownership as an increase in the conflict
of interest between bondholders and shareholders. This supports our first hypothesis.
Insert Table 4 about here
1277 Further, we find that the coefficient on FSTABLE is significantly negative at the
less than 0.01 level. The result is consistent with our prediction that stable shareholdings by financial institutions have a favorable impact on the cost of debt through efficient
monitoring. This finding indicates that firms facing stronger external and effective
monitoring by financial institutions are rewarded with lower yield spreads. The coefficient on CROSS is not significant, which suggests that cross-shareholdings have no
impact on the cost of debt in the presence of other ownerships and control variables. With respect to control variables, they have their expected signs, except for INCURE and
MATUR , and are statistically significant at conventional levels.
Agency cost of debt, managerial ownership, and interest rate spread Table 5 shows the regression result of model 2 to test hypothesis 2. To support
hypothesis 2, we expect the coefficient of MOACD to be positive in the model. In model 2, the coefficient of MOACD is 3.839 and significantly positive at the less than 0.01
level, as hypothesized. We also find that the coefficient on MO is no longer positive. The result indicates that managerial ownership has a stronger effect on interest rate spread
when the agency cost of debt at the time of corporate bond issue is larger. This finding is consistent with hypothesis 2. We observe that our control variables have their expected
signs, except for MATUR, and that most of the variables are statistically significant at conventional levels.
Insert Table 5 about here
1278 Overall, the evidence from Section V suggests that prospective bondholders use
managerial ownership information to anticipate a firm‘s future agency cost of debt and default risk, and then they incorporate this prediction in the pricing of new corporate
bond issues. Further, bond investors are likely to estimate a firm‘s future agency cost of debt and default risk higher when managers have already engaged in an action that
transfers wealth from the bondholders to the shareholders or when managers have a wide range of options for this purpose at the time of bond issue.
VI. Additional analyses
The nonlinearity of managerial ownership and the cost of debt As discussed in Section II, some prior studies suggest the possibility that
managerial ownership is nonmonotonically related to the cost of debt Bagnani et al. 1994; Ortis-Molina 2006. To address the possibility of the nonlinearity of managerial
ownership and the cost of debt, we estimate the following model.
SPREAD = C +
1
MO +
2
MO
2
+
3
CROSS +
4
FSTABLE +
5
MARGIN +
6
DER +
7
INCR +
8
LNASIZE +
9
BSIZE +
10
MATURE +
11
BCFIRM +
12
RISKP + YEAR + ε,3
where MO
2
= the square of the fraction of the shares owned by directors
1279 Although a piecewise regression model is used in the prior studies Bagnani et al.
1994; Ortis-Molina 2006, we use the quadratic form mentioned above. Short and Keasey 1999 argue that the empirical application of the piecewise regression model has a
drawback: it allows the coefficients of the managerial ownership variables to change only at predetermined levels of ownership. Since there is no theoretical guidance for the
choice of the turning points on the piecewise regression model, we test the relationship between managerial ownership and the cost of debt using the quadratic form, which
allows the turning points to be determined endogenously.
Insert Table 6 about here
Table 7 indicates the regression results. It shows that while the coefficient of MO is significantly positive, the coefficient of MO
2
is not significant. It also reveals that the explanatory power adjusted R² of model γ is 0.56β, which is slightly lower than that
of model 1 in Table 1 0.563. These results suggest that MO
2
has no incremental explanatory power for interest rate spread and is not consistent with the assumption that
the relation between the cost of debt and managerial ownership is nonmonotonic. In addition to the discussion regarding Section II, we can suggest two possible
reasons for our results being different from those of Bagnani et al. 1994. First, as stated above, Bagnani et al. use a piecewise regression model to test the hypothesis. Second, we
also indicate the possibility of sample selection biases because they obtained the sample from the list of Fortune 500 companies, which comprises only those firms whose
revenues are extremely high.
1280 The effect of bond rating on the relation between managerial ownership and the cost of
debt Our results are consistent with hypothesis 2 indicating that the association between
managerial ownership and interest rate spread is greater when the agency cost of debt at the time of corporate bond issue is larger. To verify the robustness of the results, we
estimate the regression model using the bond rating instead of ACD because the bond rating is often assumed to reflect an agency cost of debt and a firm‘s default risk
Sengupta 1998; Bhojraj and Sengupta 2003; Shuto et al. 2009. Further, Bhojraj and Sengupta 2003 argue that the influence of corporate
governance mechanisms would be more critical when dealing with debts of poor quality than otherwise. For high-
risk firms, bondholders would rely more on the firm‘s governance structure because traditional measures of past profitability and leverage may
not be very informative about future cash flows. Thus, we expect that the ownership structure should have a greater effect on bond yield spread for poorly rated bonds than on
high-quality bonds. In particular, we estimate the following regression model:
SPREAD = C + β
1
MO + β
2
MORATE + β
3
CROSS + β
4
FSTABLE + β
5
MARGIN + β
6
DER + β
7
INCR + β
8
lnASIZE + β
9
BSIZE + β
10
MATURE +
β
11
BCFIRM + β
12
RISKP + YEAR + ε,4
1281 where RATE takes the value 1 through 10, representing the bond ratings of AAA, AA
+
, AA, AA
–
, A
+
, A, A
–
, BBB
+
, BBB, and BBB
–
, respectively.
206
We expect the coefficient on MORATE to be negative in model 4. The result of the regression with the interaction term is given in Table 7. In model 4, the coefficient
of MORATE is positive and statistically significant at the 0.05 level, as expected. The result reveals that managerial ownership has stronger effects on bond yield spread for
lower rated bonds, which is consistent with the results of the previous section and the implication of the theory.
Insert Table 7 about here
Endogeneity of managerial ownership and the cost of debt Our results suggest that shareholding of managers increase the cost of debt because
rational bondholders use managerial ownership information to anticipate a firm‘s future agency cost of debt and default risk. While interpreting the results, we should consider
the joint determination of managerial ownership and the cost of debt. Firm managers may
consider the cost of capital of the firms when deciding whether or not to hold stocks of their firms
. If MO and SPREAD are jointly determined, the estimated results are biased
and difficult to interpret. To solve this simultaneity problem, we use a simultaneous equation model in which the shareholding of managers and the interest rate spread are
jointly determined. Specifically, we consider the following system of equations:
206
The bond rating used in this analysis is from Rating and Investment Information Inc RI, the most comprehensive and popular database on bond ratings in Japan.
1282
SPREAD = C + β
1
MO + β
2
CROSS + β
3
FSTABLE + β
4
MARGIN + β
5
DER +
β
6
INCR + β
7
lnASIZE + β
8
BSIZE + β
9
MATURE + β
10
BCFIRM +
β
11
RISKP + YEAR + ε
5 MO = C +
β
1
SPREAD + INSTRUMENTS + ε6
We estimate model 5 by conducting a two-stage regression. In the first stage, we regress MO on all exogenous variables from models 5 to 6. The estimation of this
regression requires the construction of a set of variables INSTRUMENTS associated with managerial ownership. We use two variables as the instruments: sales growth and 1
– fixed assetstotal assets. In the second stage, we estimate model 5 instead of MO using the fitted value from the first stage. This value is labeled as MOFIT.
207
Insert Table 8 about here
The results of the estimation of the second-stage regression are summarized in Panel A of Table 8. These results are consistent with those in the previous section: The
coefficient of MOFIT is positive and statistically significant. We also test hypothesis 2
207
Using the Hausman 1978 test, we also assess whether the two variables MO and SPREAD are jointly determined. To conduct this test, we run the second-stage regression, while including
both the actual variables and the predicted value from the first-stage regression. The test rejects the null hypothesis that the coefficient of the predicted value is zero p-value = 0.000, which
implies that the simultaneity problem does exist.
1283 by using a two-stage regression.
208
Panel B indicates that the coefficient of MOACD is significantly positive, which supports our second hypothesis. These results suggest that
our findings do not merely reflect the simultaneity between managerial ownership and interest rate spread.
Robustness of the results Finally, we describe the analyses conducted further to verify the robustness of our
results. First, we conduct a regression analysis on a year-by-year basis for our sample and estimate the t-value based on the approach used by Fama and Macbeth 1973. Since
these empirical analyses are based on eight years of pooled cross-sectional data in which the same firm can appear multiple times in the sample, these observations may not be
independent. This procedure may involve cross-sectional and autocorrelational problems. It is well known that the Fama and Macbeth 1973 approach can solve these problems
and provide a better inference on the estimates.
Insert Table 9 about here
The results are summarized in Table 9. Panel A summarizes the results for
hypothesis 1. We are mostly able to obtain the same results: the coefficient of MO is
208
Specifically, we consider the following system of equations:
SPREAD = C +
1
MO +
2
MOACD +
3
CROSS +
4
FSTABLE +
5
MARGIN +
6
DER +
7
INCR +
8
LNASIZE +
9
BSIZE +
10
MATURE +
11
BCFIRM +
12
RISKP + YEAR + ε7
MO = C + β
1
SPREAD + INSTRUMENTS + ε6
1284 significantly positive. With respect to the test of hypothesis 2, the regression results are
summarized in Panel B of Table 9, which provides evidence supporting hypothesis 2 that the coefficient of MOACD is significantly positive. Our results are robust under the
Fama and Macbeth 1973 approach. Finally, we also examine the relationship between managerial ownership and the
cost of equity capital. If managerial ownership reflects the bondholder-shareholder conflict in our research setting, it is expected that managerial ownership would not be
positively associated with the cost of equity capital because we cannot correctly predict how the severity of bondholder-shareholder conflict affects the cost of equity capital.
209
We use the cost of equity capital measured using the three-factor model based on the study by Fama and French 1993.
210
With regard to control variables, we added the logarithm of the market value of equity MV and capital asset pricing model CAPM
beta estimated using data from 60 months preceding the most recent month of April BETA to model 1 and deleted the variables of the characteristics of the issued bonds
from the model. Our untabulated result shows that the coefficient of MO is negative and not significant, which is consistent with our prediction.
VII. Conclusion
Agency theory predicts that shareholdings of managers create a conflict of interest between shareholders and bondholders Jensen and Meckling 1976; Myers 1977.
209
If the incentive alignment effect on managerial ownership dominates in this setting, we can expect that managerial ownership is negatively associated with the cost of equity capital because
the effect has a potential to increase the shareholder value of firms and decrease the cost of equity capital.
210
For details on the estimation method of the cost of equity capital, see Appendix.
1285 δimited liability shareholders may have an incentive to expropriate bondholders‘ wealth
by taking investment and financial deci sions aimed at reducing the value of the firm‘s
outstanding debt. Rational bondholders would demand a higher interest rate to compensate for the added risk on owner-
managers‘ behaviors. To test the implication of the theory, we investigate the relationship between
managerial ownership and the cost of debt, as measured by the interest rate spread on corporate bonds for Japanese firms. We find that managerial ownership is positively
associated with interest rate spread on corporate bonds, as expected. We also find that stable shareholding has a significantly positive association with the interest rate spread,
while cross-shareholding is not significantly correlated with it. Further, we expect that the effect of managerial ownership on the cost of debt
strengthens when the potential agency cost of debt of firms at the time of bond issue is larger. By employing factor analysis to measure the current agency cost of debt, we find
that managerial ownership has a higher correlation with interest rate spread when the potential agency cost of debt at the time of bond issue is larger. The results are robust
with respect to additional analyses, including the possibility of a nonlinear relationship, bond ratings, endogeneity problems, and the Fama and Macbeth 1973 approach.
Consequently, our results suggest that prospective bondholders in the Japanese market anticipate a firm‘s future agency cost of debt by using managerial ownership
information and incorporate this prediction in the pricing of new corporate bond issues. Further results suggest that the prospective bondholders estimate a higher firm‘s future
agency cost of debt because of managerial behavior that benefits the managers at the expense of bondholders‘ wealth when the current agency cost of debt at the time of bond
1286 issue is already larger. Our results also suggest that prospective bondholders perceive
stable shareholdings of financial institutions to be mitigating the wealth transfer problem between bondholders and shareholders.
Overall, our results suggest that managerial ownership is an important determinant of bond yield spread in the Japanese bond market. The results also suggest that bond
investors focus on the current agency cost of debt at the time of bond issue to determine the interest rate in the bond contract. Further, the results show that accounting
information is useful in estimating the agency cost of debt. Finally, we find that agency theory on the conflict between shareholders and
bondholders applies to the practice of the Japanese bond market after controlling for the unique Japanese ownership structure, cross-shareholding, and stable shareholding of
financial institutions. While previous studies generally focus on the findings related to the unique ownership structure in Japan, our results indicate that the empirical implication of
the traditional agency theory on managerial ownership is also supported by analyses for the Japanese bond market. Our study may be useful for reconsidering the functioning of
the unique ownership structure of Japan in the bond market.
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1291
TABLE 1 Factor analysis results on measuring agency cost of debt
Panel A: Pearson correlation matrix ACD
1 ACD
2 ACD
3 ACD
4 ACD
5 ACD
6 ACD
1 1.000
ACD 2
0.247 1.000
ACD 3
0.018 0.615
1.000 ACD
4 0.128
0.102 0.149
1.000 ACD
5 0.225
0.282 0.090
0.011 1.000
ACD 6
0.201 0.115
0.183 0.158
0.315 1.000
Panel B: Total variance explained Component
Eigenvalue of
Variance Cumulative
1 2.008
33.460 33.460
2 1.183
19.721 53.181
3 0.999
16.650 69.831
4 0.852
14.200 84.030
5 0.656
10.929 94.959
6 0.302
5.041 100.000
Panel C: Component Matrix Factor loadings Loading
ACD 1
0.476 ACD
2 0.783
ACD 3
0.682 ACD
4 0.330
ACD 5
0.557 ACD
6 0.533
Note: Table reports the results from computing the agency cost of debt ACD measure using factor analysis based on following six
financial variables: ACD 1 = RD expendituressales
ACD 2 = 1 fixed assetstotal assets
ACD 3 = cash and marketable securitiestotal assets ACD 4 = common dividendstotal assets
ACD 5 = the standard deviation of ROA net incometotal assets for the past five years ACD 6 = the standard deviation of leverage total debttotal assets for the past five years
Principal components method is used for extraction method Statistically significant at the 0.01 level of significance using a two-tailed t-test
Statistically significant at the 0.05 level of significance using a two-tailed t-test
1292
TABLE 2 Descriptive statistics
Mean Median
Max Min
SD Skewness
Kurtosis N
SPREAD 0.606
0.510 1.990
0.050 0.425
0.833 2.945
643 MO
0.007 0.001
0.405 0.000
0.031 8.969
99.797 643
CROSS 0.126
0.120 0.486
0.000 0.088
0.475 3.059
643 FSTABLE
0.160 0.138
0.690 0.000
0.131 1.522
5.968 643
MARGIN 0.043
0.037 0.332
-0.032 0.042
3.533 21.700
643 DER
4.059 3.026
33.479 0.514
3.949 3.427
19.761 643
INCR 7.521
3.069 230.670
-1.230 17.315
7.061 67.591
643 LNASIZE
13.689 13.735
16.532 11.028
1.227 0.017
2.378 643
BSIZE 23.336
23.026 25.734
21.640 0.740
0.527 3.209
643 MATUR
7.398 7.000
20.000 2.000
3.870 1.764
6.388 643
BCFIRM 0.229
0.000 1.000
0.000 0.420
1.292 2.671
643 RISKP
0.711 0.560
1.318 0.175
0.350 0.334
1.566 643
ACD 0.000
0.030 4.397
-2.012 1.000
0.365 3.602
589
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
CROSS = fraction of the shares that are cross-owned by non-financial companies cross-shareholdings.
FSTABLE = fraction of the stable shareholdings by financial institutions
MARGIN = the operating income divided by net sales
DER = the debt equity ratio
INCR = the interest coverage ratio
LNASIZE = the natural log of the total assets
BSIZE = the log of the issue size
MATUR = the years to maturity
BMCOMP = an indicator variable that takes the value of one if a bond management company is established, and zero otherwise
RISKP = the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue
ACD = the agency cost of debt, computed using factor analysis based on six financial variables; 1 RD expendituressales, 2 1
fixed assetstotal assets, 3 cash and marketable securitiestotal assets, 4
common dividendstotal assets, 5 the standard
deviation of ROA net incometotal assets for the past five years, 6 the standard deviation of leverage total debttotal assets for
the past five years
1293
TABLE 3 Correlations matrix
SPR EAD
MO CRO
SS FSTA
BLE MAR
GIN DER
INCR LNA
SIZE BSIZE
MAT UR
BCF IRM
RIS KP
ACD SPREAD
1 0.34
0.13 0.01
-0.31 0.03
-0.02 -0.40
-0.41 -0.46
-0.19 0.54
0.32 MO
0.16 1
0.18 0.05
0.04 -0.31
0.30 -0.67
-0.46 -0.25
-0.16 0.06
0.22 CROSS
0.08 -0.10
1 0.20
-0.04 -0.17
0.05 -0.26
-0.24 -0.03
-0.19 0.07
0.12 FSTABLE
0.01 -0.14
0.04 1
0.06 -0.17
0.06 -0.25
-0.10 0.00
-0.04 0.10
0.03 MARGIN
-0.13 0.31 -0.11
0.03 1
-0.36 0.58
-0.08 0.12
0.21 0.15 -0.07 -0.06
DER 0.05
-0.06 -0.22 -0.22
-0.21 1
-0.67 0.53
0.16 0.04
0.27 -0.03 -0.54 INCR
0.01 0.31 -0.15
-0.06 0.62
-0.11 1
-0.40 -0.13
-0.13 -0.27 -0.02
0.46 LNASIZE
-0.36 -0.12 -0.24
-0.23 -0.10
0.39 -0.09
1 0.65
0.31 0.19 -0.05 -0.35
BSIZE -0.37
-0.05 -0.22 -0.09
0.06 0.09
0.01 0.68
1 0.34
0.21 -0.02 -0.19 MATUR
-0.40 -0.11 -0.06
-0.05 0.06
0.00 -0.12
0.37 0.33
1 0.02 -0.08 -0.33
BCFIRM -0.10
0.01 -0.18 -0.07
0.06 0.16
-0.11 0.19
0.22 0.12
1 -0.12 -0.34
RISKP 0.54
-0.01 0.05
0.12 -0.05
-0.01 -0.03
-0.02 -0.01
-0.07 -0.14
1 0.06
ACD 0.30
0.13 0.10
0.08 -0.01
-0.43 0.38
-0.36 -0.16
-0.39 -0.32
0.05 1.
Note: Spearman Pearson correlations are above below the diagonal.
SPREAD = the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the
interest rate on the bond issued by the firm and that on government bonds MO
= fraction of the shares owned by directors CROSS
= fraction of the shares that are cross-owned by non-financial companies cross-shareholdings. FSTABLE
= fraction of the stable shareholdings by financial institutions MARGIN
= the operating income divided by net sales DER
= the debt equity ratio INCR
= the interest coverage ratio LNASIZE
= the natural log of the total assets BSIZE
= the log of the issue size MATUR
= the years to maturity BMCOMP
= an indicator variable that takes the value of one if a bond management company is established, and zero otherwise RISKP
= the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue ACD
= the agency cost of debt, computed using factor analysis based on six financial variables; 1 RD expendituressales, 2 1 fixed assetstotal assets, 3
cash and marketable securitiestotal assets, 4 common dividendstotal assets, 5
the standard deviation of ROA net incometotal assets for the past five years, 6
the standard deviation of leverage total debttotal assets for the past five years
CEC = the cost of equity capital measured using the three factor model based on Fama and French 1993
MV = the logarithm of the market value of equity
BETA = CAPM beta estimated using 60 months of data prior to the most recent April
1294
TABLE 4 Regression results on the relationship between managerial ownership and bond
spreads
Dependent variable = SPREAD Independent
variable Expected
sign Model 1
Coefficient t
-value Constant
3.359 7.804
MO +
1.829 4.164
CROSS +
0.065 0.488
FSTABLE –
-0.247 -2.978
MARGIN –
-1.380 -3.203
DER +
0.012 3.278
INCR –
0.001 0.871
LNASIZE –
-0.069 -4.401
BSIZE –
-0.087 -3.821
MATUR +
-0.025 -7.599
BCFIRM +
0.079 2.179
RISKP +
0.500 8.558
Adj. R
2
0.563 N
643
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
CROSS = fraction of the shares that are cross-owned by non-financial companies cross-shareholdings.
FSTABLE = fraction of the stable shareholdings by financial institutions
MARGIN = the operating income divided by net sales
DER = the debt equity ratio
INCR = the interest coverage ratio
LNASIZE = the natural log of the total assets
BSIZE = the log of the issue size
MATUR = the years to maturity
BMCOMP = an indicator variable that takes the value of one if a bond management company is established, and zero otherwise
RISKP = the risk pre
miumμ the average values of SPREAD on RI‘s A bonds for the month of issue Indicator variables for the year Year are included but not reported.
t -statistics are provided in parentheses.
They are based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
1295 TABLE 5
Result of the differential effect of the agency cost of debt on the relationship between managerial ownership and bond spreads
Dependent variable = SPREAD Independent
variable Expected
sign Model 2
Coefficient t
-value Constant
3.118 7.279
MO +
-1.131 -1.652
MOACD +
3.839 4.666
CROSS +
0.102 0.768
FSTABLE –
-0.175 -2.053
MARGIN –
-1.496 -3.567
DER +
0.032 5.389
INCR –
-0.002 -1.602
LNASIZE –
-0.105 -6.485
BSIZE –
-0.055 -2.420
MATUR +
-0.025 -7.370
BCFIRM +
0.018 0.464
RISKP +
0.475 8.073
Adj. R
2
0.607 N
589
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
ACD = the agency cost of debt, computed using factor analysis based on six financial variables; 1 RD expendituressales, 2 1
fixed assetstotal assets, 3 cash and marketable securitiestotal assets, 4
common dividendstotal assets, 5 the standard
deviation of ROA net incometotal assets for the past five years, 6 the standard deviation of leverage total debttotal assets for
the past five years CROSS
= fraction of the shares that are cross-owned by non-financial companies cross-shareholdings. FSTABLE
= fraction of the stable shareholdings by financial institutions MARGIN
= the operating income divided by net sales DER
= the debt equity ratio INCR
= the interest coverage ratio LNASIZE
= the natural log of the total assets BSIZE
= the log of the issue size MATUR
= the years to maturity BMCOMP
= an indicator variable that takes the value of one if a bond management company is established, and zero otherwise RISKP
= the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue Indicator variables for the year Year are included but not reported.
t -statistics are provided in parentheses. They are
based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
Statistically significant at the 0.1 level of significance using a two-tailed t-test
1296 TABLE 6
Regression results on the
nonlinear
relationship between managerial ownership and bond spreads
Dependent variable = SPREAD Independent
variable Expected
sign Model 3
Coefficient t
-value Constant
3.356 7.795
MO 1.939
2.019 MO
2
-0.364 -0.119
CROSS +
0.065 0.491
FSTABLE –
-0.245 -2.951
MARGIN –
-1.383 -3.238
DER +
0.012 3.272
INCR –
0.001 0.874
LNASIZE –
-0.068 -4.269
BSIZE –
-0.087 -3.812
MATUR +
-0.025 -7.587
BCFIRM +
0.079 2.180
RISKP +
0.500 8.552
Adj. R
2
0.562 N
643
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
MO
2
= square of the fraction of the shares owned by directors CROSS
= fraction of the shares that are cross-owned by non-financial companies cross-shareholdings. FSTABLE
= fraction of the stable shareholdings by financial institutions MARGIN
= the operating income divided by net sales DER
= the debt equity ratio INCR
= the interest coverage ratio LNASIZE
= the natural log of the total assets BSIZE
= the log of the issue size MATUR
= the years to maturity BMCOMP
= an indicator variable that takes the value of one if a bond management company is established, and zero otherwise RISKP
= the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue Indicator variables for the year Year are included but not reported.
t -statistics are provided in parentheses.
They are based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
1297
TABLE 7 Result of the differential effect of bond ratings on the relationship between
managerial ownership and bond spreads
Dependent variable = SPREAD Independent
variable Expected
sign Model 4
Coefficient t
-value Constant
3.104 6.915
MO +
0.489 1.194
LOWRATEMO +
2.029 2.420
CROSS +
0.103 0.769
FSTABLE –
-0.227 -2.627
MARGIN –
-1.570 -2.750
DER +
0.013 2.700
INCR –
0.003 2.230
LNASIZE –
-0.068 -4.231
BSIZE –
-0.078 -3.437
MATUR +
-0.021 -6.289
BCFIRM +
0.048 1.145
RISKP +
0.465 7.360
Adj. R
2
0.596 N
520
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
LOWRATE = an indicator variable that takes the value of one if
RI‘s bond ratings are A or BBB, and zero otherwise i.e. AAA or AA.
CROSS = fraction of the shares that are cross-owned by non-financial companies cross-shareholdings.
FSTABLE = fraction of the stable shareholdings by financial institutions
MARGIN = the operating income divided by net sales
DER = the debt equity ratio
INCR = the interest coverage ratio
LNASIZE = the natural log of the total assets
BSIZE = the log of the issue size
MATUR = the years to maturity
BMCOMP = an indicator variable that takes the value of one if a bond management company is established, and zero otherwise
RISKP = the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue
Indicator variables for the year Year are included but not reported. t
-statistics are provided in parentheses.
They are based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
1298
TABLE 8 The results from the estimation of the second-stage regression on MO
Panel A: The test of hypothesis 1 Dependent variable = SPREAD
Independent variable
Expected sign
Model 5 Coefficient
t -value
Constant 1.945
3.842 MOFIT
+ 22.255
5.387 CROSS
+ 0.830
4.148 FSTABLE
– 0.635
3.607 MARGIN
– -4.310
-6.368 DER
+ 0.017
3.824 INCR
– -0.009
-3.313 LNASIZE
– -0.034
-1.949 BSIZE
– -0.079
-3.310 MATUR
+ -0.011
-2.775 BCFIRM
+ 0.016
0.439 RISKP
+ 0.550
9.348 Adj. R
2
0.569 N
626 Panel B: The test of hypothesis 2
Dependent variable = SPREAD Independent
variable Expected
sign Model 7
Coefficient t
-value Constant
4.317 8.914
MOFIT +
-39.172 -5.128
MOACD 40.940
5.534 CROSS
+ 0.126
0.929 FSTABLE
– -0.393
-3.923 MARGIN
– -3.265
-6.088 DER
+ 0.037
6.469 INCR
– -0.003
-1.910 LNASIZE
– -0.178
-7.904 BSIZE
– -0.057
-2.501 MATUR
+ -0.021
-6.076 BCFIRM
+ 0.099
2.390 RISKP
+ 0.450
7.697 Adj. R
2
0.627 N
586
Note:SPREAD = the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
ACD = the agency cost of debt, computed using factor analysis based on six financial variables; 1 RD expendituressales, 2 1
fixed assetstotal assets, 3 cash and marketable securitiestotal assets, 4
common dividendstotal assets, 5 the standard
deviation of ROA net incometotal assets for the past five years, 6 the standard deviation of leverage total debttotal assets for
the past five years CROSS
= fraction of the shares that are cross-owned by non-financial companies cross-shareholdings. FSTABLE
= fraction of the stable shareholdings by financial institutions MARGIN
= the operating income divided by net sales DER
= the debt equity ratio INCR
= the interest coverage ratio LNASIZE
= the natural log of the total assets BSIZE
= the log of the issue size MATUR
= the years to maturity BMCOMP
= an indicator variable that takes the value of one if a bond management company is established, and zero otherwise RISKP
= the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue Indicator variables for the year Year are included but not reported.
1299
t -statistics are provided in parentheses. They are
based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
TABLE 9 Regression results on the relationship between managerial ownership and bond
spreads: Fama and Macbeth 1973 approach
Panel A: The test of hypothesis 1 Dependent variable = SPREAD
Independent variable
Expected sign
Model 1 Coefficient
t -value
Constant 3.016
4.740 MO
+ 2.317
3.182 CROSS
+ 0.237
2.207 FSTABLE
– -0.278
-3.011 MARGIN
– -1.122
-2.636 DER
+ 0.015
2.591 INCR
– 0.001
0.647 LNASIZE
– -0.058
-2.458 BSIZE
– -0.076
-2.070 MATUR
+ -0.026
-5.644 BCFIRM
+ 0.060
1.841 RISKP
+ 0.217
1.631 Adj. R
2
0.424 N
643 Panel B: The test of hypothesis 2
Dependent variable = SPREAD Independent
variable Expected
sign Model 2
Coefficient t
-value Constant
2.875 4.465
MO +
-13.468 -1.511
MOACD +
14.918 2.550
CROSS +
0.349 2.137
FSTABLE –
-0.253 -2.190
MARGIN –
-0.866 -2.374
DER +
0.039 5.192
INCR –
-0.005 -1.489
LNASIZE –
-0.102 -5.452
BSIZE –
-0.046 -1.379
MATUR +
-0.024 -5.254
BCFIRM +
0.005 0.134
RISKP +
0.194 1.538
Adj. R
2
0.476 N
589
Note: SPREAD
= the interest rate spread on the first straight bond issued of the fiscal year; the spread is the difference between the interest rate on the bond issued by the firm and that on government bonds
MO = fraction of the shares owned by directors
CROSS = fraction of the shares that are cross-owned by non-financial companies cross-shareholdings.
FSTABLE = fraction of the stable shareholdings by financial institutions
MARGIN = the operating income divided by net sales
DER = the debt equity ratio
INCR = the interest coverage ratio
LNASIZE = the natural log of the total assets
BSIZE = the log of the issue size
1300
MATUR = the years to maturity
BMCOMP = an indicator variable that takes the value of one if a bond management company is established, and zero otherwise
RISKP = the risk premiumμ the average values of SPREAD on RI‘s A bonds for the month of issue
t -statistics are provided in parentheses.
They are based on White‘s 1λ80 heteroskedasticity-consistent standard errors and covariance.
Statistically significant at the 0.01 level of significance using a two-tailed t-test Statistically significant at the 0.05 level of significance using a two-tailed t-test
Statistically significant at the 0.1 level of significance using a two-tailed t-test
Appendix
Estimation method for the equity cost of capital To calculate a firm‘s estimated equity cost of capital ECC, we estimate the following
equation.
, ,
, , , ,
, ,
ˆ ˆ
ˆ
t i t
f t RMRF i t
M f
t SMB i t
t HML i t
ECC R
R R
SMB HML
,1 where R
m
– R
f
is the monthly return of the market portfolio in excess of the risk-free rate. HML and SMB are the monthly returns to the book-to-market and size factor
mimicking portfolios, as described in Fama and French 1993. First, we calculate each factor‘s average monthly return over a period of 60 months before month m. And then,
we estimate the expected annual factor returns, R
m
– R
f
, HML, and SMB, by compounding the resulting average monthly returns over a period of 12 months before
the beginning of the fiscal year. Second, we estimate the betas associated with the firm‘s return to each of the three factors by estimating the following monthly time series
regression, as described in Fama and French 1993. We estimate the following equation by considering the period of the latest 60 months preceding the beginning of the firm‘s
fiscal year.
m i
m i
HML m
i SMB
m f
m M
i RMRF
i m
f m
i
HML SMB
R R
R RET
, ,
, ,
, ,
, ,
2
1301
FINANCING ALTERNATIVES AND INCENTIVES FOR RENEWABLE ENERGY, FROM THE VIEW POINT
OF TURKEY’S MEMBERSHIP TO THE EU
Cem Berk, Marmara University
Summary In this paper we discuss the approaches to financing conventional energy sources and renewable
energy projects from the standpoint of EU-Turkey relation, by focusing on how these transactions differ from more conventional oil trade at the other part of the world. Main features of
conventional energy sources and renewable energy are analysed, from the strategic point of view
and Turkey‘s regional position to the surrounding oil and gas producing countries. Strategic alignment and future oriented advantage of the increasing interest for Caspian and Mediterranean
oil transfers to EU countries, has been critically evaluated. The incentives and tax-breaks used in EU including Turkey have been studied to illustrate principles and insure understanding.
Attention is also given to different financing instruments and -methods. Finally, quantitative analysis and model on the energy incentives in Turkey are also presented in the paper.
1. Introduction Global warming will result in major environmental, social and economic problems. These
negative consequences of are already occurring, and others are inevitable even if the emission of atmospheric greenhouse gases could be stabilized at present levels. In the light of global warming,
the political leaders of many countries have accepted that there is an urgent need to reduce greenhouse gas emission on a worldwide scale. At the same time, there is a potential for reducing
such emissions by economies in energy use, energy efficiency and by energy generation from alternative, non-carbon-based sources.
Turkey as an emerging market will continue its effort to increase diversifies energy sources and
the energy requirements. At present, most of Turkey‘s home-produced energy is generated from lignite and poor-quality coal; these are problematic in terms of carbon dioxide emission, so there
is the possibility that Turkey‘s contribution to anthropogenic atmospheric carbon dioxide will grow over the coming years. More positively, Turkey has great potential for generating energy
from renewable sources. For example, there is considerable possibility of using more hydropower. In addition, many regions of the country are suitable for wind power, and it has been calculated
that Turkey could meet a large part of its energy needs from wind farms that could be located along its western seaboard. There are, however, potential barriers to the implementation of such a
strategy. Apart from the financial investment that will be needed, there will need to be public support too.
211
See Appendix 1 for Turkish Energy Sector Details Historically, feed-in laws have been the primary mechanism used to support renewable energy
RE development in both Europe and the US, where there is a track record of some two decades of experience. At present, they are being applied in 16 EU member countries.
212
Green pricing programs allow electricity customers to express their willingness to pay for renewable energy
development through direct payments on their monthly utility bills. 2. Energy Market and
–policy
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Kilinc, Stanistreet, Boyes; Incentives and disincentives for using renewable energy: Turkish students‘ ideas; Renewable and Sustainable Energy Reviews;β008.
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European PV Association Position Paper On a Feed-in Tariff for Photovoltaic Solar Electricity;; p.3; 2005.
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The attributes of energy policy may include legislation, international treaties, incentives to investment, and guidelines for energy conservation, taxation and other public policy techniques.
Frequently the dominant issue in the energy policy is the risk of supply-demand mismatch. Current energy policies also address environmental issues. Some governments state explicit
energy policy, but, declared or not, each government practices some type of energy policy. The main elements intrinsic to an energy policy are:
The energy self-sufficiency
Energy pricing
The goals for future energy intensity,
Ratio of energy consumption to GDP
Environmental externalities
The diversification of energy recourses
The national policy drive province, state and municipal functions
The incentives accelerating energy sustainability and
Security of supply. Gas is an important input for electricity generation in the energy industry and therefore wholesale
natural gas and electricity markets are vertically interrelated. The same is true for wholesale and retail electricity markets since retailers buy electricity from wholesalers. Vertical integration is
widespread among European energy firms. Moreover, the merger activity appears to be accelerating as competition opportunities expand, incentive regulation diffuses more widely, and
regulators have become less hostile to mergers. As a result, the vertically integrated firm can increase profits by raising both its end-user market share and price. Collaborative incentives,
however, not only encourage cooperation but may also enhance free riding. Indeed, rewards based on aggregate profits hinder the identification of individual performances. As a consequence,
individuals have more incentives to avoid hoping that the others will compensate.
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3. Developing Energy Project
The use of non-conventional renewable energy system technologies have received strong incentives in developed countries, especially after the third conference of the parties of Kyoto
Protocol. One of the main reasons for these incentives was the existence of a climate change, with global consequences, and with anthropogenic causes mainly related to the use of fossil fuels. As
this impact was not included in the fuel prices, the governments that signed the protocol is obligated to give economic incentives for clean technologies, and especially for RE.
Kyoto protocol was a compromise between the industrialized countries and Russia who decided to reduce the CO2 emissions a 5.4 with respect to the 1990 emissions, for 2010. EU- countries
like Denmark 29 of RE on its energy matrix Germany 9.4, Spain 3.4 and Holland 4 are clear examples where strong incentives for RE were applied, with successful results.
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If properly regulated and supported, the expansion of renewable energy could make unquestionable contributions in many areas. But if only left to the market forces, the expected
effects may never occur or may even become problems to the society. As sites for renewable energy projects become scarcer and energy demand continues to grow, a derived demand for sites
could be explained on the basis of the trade-off between their distance and their productivity. In particular, in a competitive market the change from one isoprofit to another by means of
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Micola, Estanol, Bunn; Incentives and Coordination in Vertically Related Energy Markets; Journal of Economic Behavior Organization; 2008
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Valencia M. Leonardo; New scenario of the non-conventional renewable energies on Chile after the incentives created on the ‗‗Short δaw I‘‘; Renewable Energy;β008.
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relocating a project should be associated to a corresponding increase or decrease in the price of the site, whereas sites lying over the same isoprofit should have similar prices. Of course such
market will often be influenced by the multiple use of land, in which the implementation of a renewable energy project is just one of the possible uses explaining demand. Same isoprofit
should have similar prices. Of course such market will often be influenced by the multiple use nature of land, in which the implementation of a renewable energy project is just one of the
possible uses explaining demand. Technologies, especially wind energy, but also small-scale hydro power, energy from biomass,
and solar thermal applications, are economically viable and competitive. The others, especially photovoltaic, depend only on increasing demand and thus production volume to achieve the
economy of scale necessary for competitiveness with central generation. This should be seen against the rapidly improving fiscal and economic environment being created in the EU both by
European legislation itself swinging into full implementation and the
εember States‘ own programmes and support measures, which despite the short-term macro-economic background,
are accelerating rapidly at the time of publication. In this context, the generation of energy from renewable sources is beginning to gather strength
throughout the world, motivating leaders to implement policies aimed at increasing the number of projects according to this line of thinking.
Source: Zulunga, Dyner; Incentives for renewable energy in reformed Latin-American electricity markets: the Colombian case; Journal of Cleaner Production; 2006
Although the reduction of poverty is perhaps the most important concern in the developing countries, there is significant environmental interest associated with the use of new energy
sources which will help to reduce the environmental impacts that have been caused by traditional forms of energy based on the combustion of fossil fuels. From simulations carried out for the
Colombia market, it is less efficient to promote renewable energies through fiscal policies such as income tax exemption, while other kinds of policies such as direct subsidies have a major effect
as far as accelerating the process of technology diffusion. Therefore, it remains for the government to set the appropriate incentives in order to efficiently exploit renewable energy
resources. Although in the process of Turkish market, renewable energy did not occupy a prominent place,
there now seems to be a new international trend to develop these resources, which will begin to