资本结构的决定因素【外文翻译】

外文文献翻译译文一、外文原文原文：The Determinants of Capital Structure Choice The basic approach taken in previous empirical work has been to estimate regression equations with proxies for the unobservable theoretical attributes. This approach has a number of problems. First, there may be no unique representation of the attributes we wish to measure. There are often many possible proxies for a particular attribute, and researchers, lacking theoretical guidelines, may be tempted to select those variables that work best in terms of statistical goodness-of-fit criteria, thereby biasing their interpretation of the significance levels of their tests. Second, it is often difficult to find measures of particular attributes that are unrelated to other attributes that are of interest. Thus, selected proxy variables may be measuring the effects of several different attributes. Third, since the observed variables are imperfect representations of the attributes they are supposed to measure, their use in regression analysis introduces an errors-in-variable problem. Finally, measurement errors in the proxy variables may be correlated with measurement errors in the dependent variables, creating spurious correlations even when the unobserved attribute being measured is unrelated to the dependent variable.This study extends empirical work on capital structure theory in three ways. First, it extends the range of theoretical determinants of capital structure by examining some recently developed theories that have not, as yet, been analyzed empirically. Second, since some of these theories have different empirical implications with regard to different types of debt instruments, we analyze separate measures of short-term, long-term, and convertible debt rather than an aggregate measure of total debt. Third, a technique is used that explicitly recognizes and mitigates the measurement problems discussed above.This technique, which is an extension of the factor-analytic approach tomeasuring unobserved or latent variables, is known as linear structural modeling. Very briefly, this method assumes that, although the relevant attributes are not directly observable, we can observe a number of indicator variables that are linear functions of one or more attributes and a random error term. There is, in this specification, a direct analogy with the return-generating process assumed to hold in the Arbitrage Pricing Theory. While the identifying restrictions imposed on our model are different, the technique for estimating it is very similar to the procedure used by Roll and Ross to test the APT.Our results suggest that firms with unique or specialized products have relatively low debt ratios. Uniqueness is categorized by the firms' expenditures on research and development, selling expenses, and the rate at which employees voluntarily leave their jobs. We also find that smaller firms tend to use significantly more short-term debt than larger firms. Our model explains virtually none of the variation in convertible debt ratios across firms and finds no evidence to support theoretical work that predicts that debt ratios are related to a firm's expected growth, non-debt tax shields, volatility, or the collateral value of its assets. We do, however, find some support for the proposition that profitable firms have relatively less debt relative to the market value of their equity.Determinants of Capital StructureIn this section, we present a brief discussion of the attributes that different theories of capital structure suggest may affect the firm's debt-equity choice. These attributes are denoted asset structure, non-debt tax shields, growth, uniqueness, industry classification, size, earnings volatility, and profitability. The attributes, their relation to the optimal capital structure choice, and their observable indicators are discussed below.A. Collateral Value of AssetsMost capital structure theories argue that the type of assets owned by a firm in some way affects its capital structure choice. Scott suggests that, by selli secured debt, firms increase the value of their equity by expropriating wealth from their existing unsecured creditor. Arguments put forth by Myers and Majluf also suggest thatfirms may find it advantageous to sell secured debt. Their model demonstrates that there may be costs associated with issuing securities about which the firm's managers have better information than outside shareholders. Issuing debt secured by property with known values avoids these costs. For this reason, firms with assets that can be used as collateral may be expected to issue more debt to take advantage of this opportunity.Work by Galai and Masulis, Jensen and Meckling, and Myers suggests that stockholders of leveraged firms have an incentive to invest suboptimally to expropriate wealth from the firm's bondholders. This incentive may also induce a positive relation between debt xatios and the capacity of firms to collateralize their debt. If the debt can be collateralized, the borrower is restricted to use the funds for a specified project. Since no such guarantee can be used for projects that cannot be collateralized, creditors may require more favorable terms, which in turn may lead such firms to use equity rather than debt financing.The tendency of managers to consume more than the optimal level of perquisites may produce the opposite relation between collateralizable capital and debt levels. Grossman and Hart suggest that higher debt levels diminish this tendency because of the increased threat of bankruptcy. Managers of highly levered firms will also be less able to consume excessive perquisites since bondholders (or bankers) are inclined to closely monitor such firms. The costs associated with this agency relation may be higher for firms with assets that are less collateralizable since monitoring the capital outlays of such firms is probably more difficult. For this reason, firms with less collateralizable assets may choose higher debt levels to limit their managers' consumption of perquisites.The estimated model incorporates two indicators for the collateral value attribute. They include the ratio of intangible assets to total assets (INTITA) and the ratio of inventory plus gross plant and equipment to total assets (IGPITA). The first indicator is negatively related to the collateral value attribute, while the second is positively related to collateral value.B. Non-Debt Tax ShieldsDeAngelo and Masulis present a model of optimal capital structure that incorporates the impact of corporate taxes, personal taxes, and non-debt-related corporate tax shields. They argue that tax deductions for depreciation and investment tax credits are substitutes for the tax benefits of debt financing. As a result, firms with large non-debt tax shields relative to their expected cash flow include less debt in their capital structures.Indicators of non-debt tax shields include the ratios of investment tax credits over total assets (ITCITA), depreciation over total assets (DITA), and a direct estimate of non-debt tax shields over total assets (NDTITA). The latter measure is calculated from observed federal income tax payments (T), operating income (OI), interest payments (i), and the corporate tax rate during our sample period (48%), using the following equation:NDT=OI-i-T/0.48which follows from the equalityT = 0.48(OI- i-NDT).These indicators measure the current tax deductions associated with capital equipment and, hence, only partially capture the non-debt tax shield variable suggested by DeAngelo and Masulis. First, this attribute excludes tax deductions that are not associated with capital equipment, such as research and development and selling expenses. (These variables, used as indicators of another attribute, are discussed later.) More important, our non-debt tax shield attribute represents tax deductions rather than tax deductions net of true economic depreciation and expenses, which is the economic attribute suggested by theory. Unfortunately, this preferable attribute would be very difficult to measure.C. GrowthAs we mentioned previously, equity-controlled firms have a tendency to invest suboptimally to expropriate wealth from the firm's bondholders. The cost associated with this agency relationship is likely to be higher for firms in growing industries, which have more flexibility in their choice of future investments. Expected future growth should thus be negatively related to long-term debt levels. Myers, however,noted that this agency problem is mitigated if the firm issues short-term rather than long-term debt. This suggests that short-term debt ratios might actually be positively related to growth rates if growing firms substitute short-term financing for long-term financing. Jensen and Meckling, Smith and Warner, and Green argued that the agency costs will be reduced if firms issue convertible debt. This suggests that convertible debt ratios may be positively related to growth opportunities.It should also be noted that growth opportunities are capital assets that add value to a firm but cannot be collateralized and do not generate current taxable income. For this reason, the arguments put forth in the previous subsections also suggest a negative relation between debt and growth opportunities.Indicators of growth include capital expenditures over total assets (CEITA) and the growth of total assets measured by the percentage change in total assets (GTA). Since firms generally engage in research and development to generate future investments, research and development over sales (RDIS) also serves as an indicator of the growth attribute.D. UniquenessTitman presents a model in which a firm's liquidation decision is causally linked to its bankruptcy status. As a result, the costs that firms can potentially impose on their customers, suppliers, and workers' by liquidating are relevant to their capital structure decisions. Customers, workers, and suppliers of firms that produce unique or specialized products probably suffer relatively high costs in the event that they liquidate. Their workers and suppliers probably have jobspecific skills and capital, and their customers may find it difficult to find alternative servicing for their relatively unique products. For these reasons, uniqueness is expected to be negatively related to debt ratios.Indiators of uniqueness include expenditures on research and development over sales (RDIS), selling expenses over sales (SEIS), and quit rates (QR), the percentage of the industry's total work force that voluntarily left their jobs in the sample years. It is postulated that RDIS measures uniqueness because firms that sell products with close substitutes ark likely to do less research and development since their innovationscan be more easily duplicated. In addition, successful research and development projects lead to new products that differ from those existing in the market. Firms with relatively unique products are expected to advertise more and, in general, spend more in promoting and selling their products. Hence, SEIS is expected to be positively related to uniqueness. However, it is expected that firms in industries with high quit rates are probably relatively less unique since firms that produce relatively unique products tend to employ workers with high levels of job-specific human capital who will thus find it costly to leave their jobs.It is apparent from two of the indicators of uniqueness, RDIS and SEIS, that this attribute may also be related to non-debt tax shields and collateral value. Research and development and some selling expenses (such as advertising) can be considered capital goods that are immediately expensed and cannot be used as collateral. Given that our estimation technique can only imperfectly control for these other attributes, the uniqueness attribute may be negatively related to the observed debt ratio because of its positive correlation with non-debt tax shields and its negative correlation with collateral value.E. Industry ClassificationTitman suggests that firms that make products requiring the availability of specialized servicing and spare parts will find liquidation especially costly. This indicates that firms manufacturing machines and equipment should be financed with relatively less debt. To measure this, we include a dummy variable equal to one for firms with SIC codes between 3400 and 4000 (firms producing machines and equipment) and zero otherwise as a separate attribute affecting the debt ratios.F. SizeA number of authors have suggested that leverage ratios may be related to firm size. Warner and Ang, Chua, and McConnell provide evidence that suggests that direct bankruptcy costs appear to constitute a larger proportion of a firm's value as that value decreases. It is also the case that relatively large firms tend to be more diversified and less prone to bankruptcy. These arguments suggest that large firms should be more highly leveraged.The cost of issuing debt and equity securities is also related to firm size. In particular, small firms pay much more than large firms to issue new equity (see Smith) and also somewhat more to issue long-term debt. This suggests that small firms may be more leveraged than large firms and may prefer to borrow short term (through bank loans) rather than issue long-term debt because of the lower fixed costs associated with this alternative.We use the natural logarithm of sales (LnS) and quit rates (QR) as indicators of size.5 The logarithmic transformation of sales reflects our view that a size effect, if it exists, affects mainly the very small firms. The inclusion of quit rates, as an indicator of size, reflects the phenomenon that large firms, which often offer wider career opportunities to their employees, have lower quit rates.G. VolatilityMany authors have also suggested that a firm's optimal debt level is a decreasing function of the volatility of earning. We were only able to include one indicator of volatility that cannot be directly affected by the firm's debt level. It is the standard deviation of the percentage change in operating income (SIGOI). Since it is the only indicator of volatility, we must assume that it measures this attribute without error. H. ProfitabilityMyers cites evidence from Donaldson and Brealey and Myers that suggests that firms prefer raising capital, first from retained earnings, second from debt, and third from issuing new equity. He suggests that this behavior may be due to the costs of issuing new equity. These can be the costs discussed in Myers and Majluf that arise because of asymmetric information, or they can be transaction costs. In either case, the past profitability of a firm, and hence the amount of earnings available to be retained, should be an important determinant of its current capital structure. We use the ratios of operating income over sales (OIIS) and operating income over total assets (OIITA) as indicators of profitability.Measures of Capital StructureSix measures of financial leverage are used in this study. They are long-term, short-term, and convertible debt divided by market and by book values of equity.'Although these variables could have been combined to extract a common "debt ratio" attribute, which could in turn be regressed against the independent attributes, there is good reason for not doing this. Some of the theories of capital structure have different implications for the different types of debt, and, for the reasons discussed below, the predicted coefficients in the structural model may differ according to whether debt ratios are measured in terms of book or market values. Moreover, measurement errors in the dependent variables are subsumed in the disturbance term and do not bias the regression coefficients.Data limitations force us to measure debt in terms of book values rather than market values. It would, perhaps, have been better if market value data were available for debt. However, Bowman demonstrated that the cross-sectional correlation between the book value and market value of debt is very large, so the misspecification due to using book value measures is probably fairly small. Furthermore, we have no reason to suspect that the cross-sectional differences between market values and book values of debt should be correlated with any of the determinants of capital structure suggested by theory, so no obvious bias will result because of this misspecification.There are, however, some other important sources of spurious correlation. The dependent variables used in this study can potentially be correlated with the explanatory variables even if debt levels are set randomly. Consider first the case where managers set their debt levels according to some randomly selected target ratio measured at book value.' This would not be irrational if capital structure were in fact irrelevant. If managers set debt levels in terms of book value rather than market value ratios, then differences in market values across firms that arise for reasons other than differences in their book values (such as different growth opportunities) will not necessarily affect the total amount of debt they issue. Since these differences do, of course, affect the market value of their equity, this will have the effect of causing firms with higher marketbook value ratios to have lower debt/market value ratios. Since firms with growth opportunities and relatively low amounts of collateralizable assets tend to have relatively high market value/book value ratios, a spurious relation might exist between debt market value and these variables, creating statisticallysignificant coefficient estimates even if the book value debt ratios are selected randomly.Similar spurious relations will be induced between debt ratios measured at book value and the explanatory variables if firms select debt levels in accordance with market value target ratios. If some firms use book value targets while others use market value targets, both dependent variables will be spuriously correlated with the independent variables. Fortunately, the book and market value debt ratios induce spurious correlation in opposite directions. Using dependent variables scaled by both book values and market values may then make it possible to separate the effects of capital structure suggested by theory, which predicts coefficient estimates of the same sign for both dependent variable groups, from these spurious effects.Source:Sheridan Titman; Roberto Wessels The Journal of Finance, V ol. 43, No. 1. (Mar., 1988), pp. 1-19.二、翻译文章译文：资本结构的选择的决定因素用以往用过的基本方法来评估回归方程，而此方程夹杂着难以窥测的代理性理论因素。

资本结构决定因素以中国企业为案例【外文翻译】XXX titled "XXX Structure: Evidence from XXX's n-making process in regards to their capital structure。

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中英文对照外文翻译(文档含英文原文和中文翻译)The effect of capital structure on profitability : an empirical analysis of listed firms in Ghana IntroductionThe capital structure decision is crucial for any business organization. The decision is important because of the need to maximize returns to various organizational constituencies, and also because of the impact such a decision has on a firm’s ability to deal with its competitive environment. The capital structure of a firm is actually a mix of different securities. In general, a firm can choose among many alternative capital structures. It can issue a large amount of debt or very little debt. It can arrange lease financing, use warrants, issue convertible bonds, sign forward contracts or trade bond swaps. It can issue dozens of distinct securities in countless combinations; however, it attempts to find the particular combination that maximizes its overall market value.A number of theories have been advanced in explaining the capital structure of firms. Despite the theoretical appeal of capital structure, researchers in financial management have not found the optimal capital structure. The best that academics and practitioners have been able to achieve are prescriptions that satisfy short-term goals. For example, the lack of a consensus about what would qualify as optimal capital structure has necessitated the need for this research. A better understanding of the issues at hand requires a look at the concept of capital structure and its effect on firm profitability. This paper examines the relationship between capital structure and profitability of companies listed on the Ghana Stock Exchange during the period 1998-2002. The effect of capital structure on the profitability of listed firms in Ghana is a scientific area that has not yet been explored in Ghanaian finance literature.The paper is organized as follows. The following section gives a review of the extant literature on the subject. The next section describes the data and justifies the choice of the variables used in the analysis. The model used in the analysis is then estimated. The subsequent section presents and discusses the results of the empirical analysis. Finally, the last section summarizes the findings of the research and also concludes the discussion.Literature on capital structureThe relationship between capital structure and firm value has been the subject of considerable debate. Throughout the literature, debate has centered on whether there is an optimal capital structure for an individual firm or whether the proportion of debt usage is irrelevant to the individual firm’s value. The capital structure of a firm concerns the mix of debt and equity the firm uses in its operation. Brealey and Myers (2003) contend that the choice of capital structure is fundamentally a marketing problem. They state that the firm can issue dozens of distinct securities in countless combinations, but it attempts to find the particular combination that maximizes market value. According to Weston and Brigham (1992), the optimal capital structure is the one that maximizes the market value of the firm’s outstanding shares.Fama and French (1998), analyzing the relationship among taxes, financing decisions, and the firm’s value, concluded that the debt does not concede tax b enefits. Besides, the high leverage degree generates agency problems among shareholders and creditors that predict negative relationships between leverage and profitability. Therefore, negative information relating debt and profitability obscures the tax benefit of the debt. Booth et al. (2001) developed a study attempting to relate the capital structure of several companies in countries with extremely different financial markets. They concluded thatthe variables that affect the choice of the capital structure of the companies are similar, in spite of the great differences presented by the financial markets. Besides, they concluded that profitability has an inverse relationship with debt level and size of the firm. Graham (2000) concluded in his work that big and profitable companies present a low debt rate. Mesquita and Lara (2003) found in their study that the relationship between rates of return and debt indicates a negative relationship for long-term financing. However, they found a positive relationship for short-term financing and equity.Hadlock and James (2002) concluded that companies prefer loan (debt) financing because they anticipate a higher return. Taub (1975) also found significant positive coefficients for four measures of profitability in a regression of these measures against debt ratio. Petersen and Rajan (1994) identified the same association, but for industries. Baker (1973), who worked with a simultaneous equations model, and Nerlove (1968) also found the same type of association for industries. Roden and Lewellen (1995) found a significant positive association between profitability and total debt as a percentage of the total buyout-financing package in their study on leveraged buyouts. Champion (1999) suggested that the use of leverage was one way to improve the performance of an organization.In summary, there is no universal theory of the debt-equity choice. Different views have been put forward regarding the financing choice. The present study investigates the effect of capital structure on profitability of listed firms on the GSE.MethodologyThis study sampled all firms that have been listed on the GSE over a five-year period (1998-2002). Twenty-two firms qualified to be included in the study sample. Variables used for the analysis include profitability and leverage ratios. Profitability is operationalized using a commonly used accounting-based measure: the ratio of earnings before interest and taxes (EBIT) to equity. The leverage ratios used include:. short-term debt to the total capital;. long-term debt to total capital;. total debt to total capital.Firm size and sales growth are also included as control variables.The panel character of the data allows for the use of panel data methodology. Panel data involves the pooling of observations on a cross-section of units over several time periods and provides results that are simply not detectable in pure cross-sections or pure time-series studies. A general model for panel data that allows the researcher to estimate panel data with great flexibility and formulate the differences in the behavior of thecross-section elements is adopted. The relationship between debt and profitability is thus estimated in the following regression models:ROE i,t =β0 +β1SDA i,t +β2SIZE i,t +β3SG i,t + ëi,t (1) ROE i,t=β0 +β1LDA i,t +β2SIZE i,t +β3SG i,t + ëi,t (2) ROE i,t=β0 +β1DA i,t +β2SIZE i,t +β3SG i,t + ëi,t (3)where:. ROE i,t is EBIT divided by equity for firm i in time t;. SDA i,t is short-term debt divided by the total capital for firm i in time t;. LDA i,t is long-term debt divided by the total capital for firm i in time t;. DA i,t is total debt divided by the total capital for firm i in time t;. SIZE i,t is the log of sales for firm i in time t;. SG i,t is sales growth for firm i in time t; and. ëi,t is the error term.Empirical resultsTable I provides a summary of the descriptive statistics of the dependent and independent variables for the sample of firms. This shows the average indicators of variables computed from the financial statements. The return rate measured by return on equity (ROE) reveals an average of 36.94 percent with median 28.4 percent. This picture suggests a good performance during the period under study. The ROE measures the contribution of net income per cedi (local currency) invested by the firms’ stockholders; a measure of the efficiency of the owners’ invested capital. The variable SDA measures the ratio of short-term debt to total capital. The average value of this variable is 0.4876 with median 0.4547. The value 0.4547 indicates that approximately 45 percent of total assets are represented by short-term debts, attesting to the fact that Ghanaian firms largely depend on short-term debt for financing their operations due to the difficulty in accessing long-term credit from financial institutions. Another reason is due to the under-developed nature of the Ghanaian long-term debt market. The ratio of total long-term debt to total assets (LDA) also stands on average at 0.0985. Total debt to total capital ratio(DA) presents a mean of 0.5861. This suggests that about 58 percent of total assets are financed by debt capital. The above position reveals that the companies are financially leveraged with a large percentage of total debt being short-term.Table I.Descriptive statisticsMean SD Minimum Median Maximum━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ROE 0.3694 0.5186 -1.0433 0.2836 3.8300SDA 0.4876 0.2296 0.0934 0.4547 1.1018LDA 0.0985 0.1803 0.0000 0.0186 0.7665DA 0.5861 0.2032 0.2054 0.5571 1.1018SIZE 18.2124 1.6495 14.1875 18.2361 22.0995SG 0.3288 0.3457 20.7500 0.2561 1.3597━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Regression analysis is used to investigate the relationship between capital structure and profitability measured by ROE. Ordinary least squares (OLS) regression results are presented in Table II. The results from the regression models (1), (2), and (3) denote that the independent variables explain the debt ratio determinations of the firms at 68.3, 39.7, and 86.4 percent, respectively. The F-statistics prove the validity of the estimated models. Also, the coefficients are statistically significant in level of confidence of 99 percent.The results in regression (1) reveal a significantly positive relationship between SDA and profitability. This suggests that short-term debt tends to be less expensive, and therefore increasing short-term debt with a relatively low interest rate will lead to an increase in profit levels. The results also show that profitability increases with the control variables (size and sales growth). Regression (2) shows a significantly negative association between LDA and profitability. This implies that an increase in the long-term debt position is associated with a decrease in profitability. This is explained by the fact that long-term debts are relatively more expensive, and therefore employing high proportions of them could lead to low profitability. The results support earlier findings by Miller (1977), Fama and French (1998), Graham (2000) and Booth et al. (2001). Firm size and sales growth are again positively related to profitability.The results from regression (3) indicate a significantly positive association between DA and profitability. The significantly positive regression coefficient for total debt implies that an increase in the debt position is associated with an increase in profitability: thus, the higher the debt, the higher the profitability. Again, this suggests that profitable firms depend more on debt as their main financing option. This supports the findings of Hadlock and James (2002), Petersen and Rajan (1994) and Roden and Lewellen (1995) that profitable firms use more debt. In the Ghanaian case, a high proportion (85 percent)of debt is represented by short-term debt. The results also show positive relationships between the control variables (firm size and sale growth) and profitability.Table II.Regression model results━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Profitability (EBIT/equity)Ordinary least squares━━━━━━━━━━━━━━━━━━━━━━━━━━━━━Variable 1 2 3SIZE 0.0038 (0.0000) 0.0500 (0.0000) 0.0411 (0.0000)SG 0.1314 (0.0000) 0.1316 (0.0000) 0.1413 (0.0000)SDA 0.8025 (0.0000)LDA -0.3722(0.0000)DA -0.7609(0.0000)R²0.6825 0.3968 0.8639SE 0.4365 0.4961 0.4735Prob. (F) 0.0000 0.0000 0.0000━━━━━━━━━━━━━━━━━━━━━━━━━━━━ConclusionsThe capital structure decision is crucial for any business organization. The decision is important because of the need to maximize returns to various organizational constituencies, and also because of the impact such a decision has on an organization’s ability to deal with its competitive environment. This present study evaluated the relationship between capital structure and profitability of listed firms on the GSE during a five-year period (1998-2002). The results revealed significantly positive relation between SDA and ROE, suggesting that profitable firms use more short-term debt to finance their operation. Short-term debt is an important component or source of financing for Ghanaian firms, representing 85 percent of total debt financing. However, the results showed a negative relationship between LDA and ROE. With regard to the relationship between total debt and profitability, the regression results showed a significantly positive association between DA and ROE. This suggests that profitable firms depend more on debt as their main financing option. In the Ghanaian case, a high proportion (85 percent) of the debt is represented in short-term debt.译文加纳上市公司资本结构对盈利能力的实证研究论文简介资本结构决策对于任何商业组织都是至关重要的。

lodging companies出处：International Journal of Contemporary Hospitality Management 作者：Erdinc Karadeniz, Serkan Yilmaz Kandir, Mehmet Balcilar andYildirim Beyazit Onal原文Determinants of capital structure:evidence from Turkish lodging companiesBy Erdinc Karadeniz, Serkan Yilmaz Kandir, Mehmet Balcilar and Yildirim BeyazitOnalIntroductionCap ital structure refers to the composition of a firm’s liabilities and owners’ equity. Capital structure decisions are related to the magnitudes of liabilities and owners’equity. Capital structure decisions are one of the three financing decisions –investment, financing, and dividend decisions – finance managers have to make (Van Horne and Wachowicz, 1995).Capital structure of a firm determines the weighted average cost of capital (WACC).WACC is the minimum rate of return required on a firm’s investments an d used as the discount rate in determining the value of a firm. A firm can create value for its shareholders as long as earnings exceed the costs of investments (Damodaran, 2000).A number of theoretical and empirical studies investigated the optimal capital structure of a firm. These studies pointed out the importance of the relationships among capital structure, cost of capital, capital budgeting decisions, and firm value.Lodging companies are capital intensive, as they require huge capital at both investment and operating stages. Since assets of lodging companies mostly consist of fixed assets share of long-term debt and owners’ equity becomes rather high. Furthermore, because of the structure of the industry, lodging companies are highly sensitive to systematic risks. Therefore, lodging companies face high operating andfinancial risks (Andrew and Schmidgall, 1993). All these make it important to determine the composition of capital structure and the factors affecting leverage decisions and debt ratio.The trade-off and pecking order theoriesThe relationship between capital structure decisions and firm value has been extensively investigated in the past few decades. Over the years, alternative capital structure theories have been developed in order to determine the factors that affect capital structure decisions. Modigliani and Miller (1958) is a milestone among capital structure studies. In their first proposition, Modigliani and Miller (1958) state that market is fully efficient when there are no taxes. Thus, capital structure and financing decisions affect neither cost of capital nor market value of a firm. In their second proposition, they maintain that interest payments of debt decrease the tax base, thus cost of debt is less than the cost of equity. The tax advantage of debt motivates the optimal capital structure theory, which implies that firms may attain optimal capital structure and increase firm value by altering their capital structures. Bankruptcy and financial distress costs (Myers, 1977) and agency costs (Jensen and Meckling, 1976) constitute the basics of trade-off theory. Trade-off theory asserts that firms set a target debt to value ratio and gradually move towards it. According to this theory, any increase in the level of debt causes an increase in bankruptcy, financial distress and agency costs, and hence decreases firm value. Thus, an optimal capital structure may be reached by establishing equilibrium between advantages (tax advantages) and disadvantages (financial distress and bankruptcy costs) of debt. In order to establish this equilibrium firms should seek debt levels at which the costs of possible financial distress offset the tax advantages of additional debt.Data and methodologyWe investigate the determinants of capital structure decisions of lodging companies using a panel data on five companies traded in the ISE. Although there are eight lodging companies traded in the ISE, there of these companies are excluded from the study since these are traded only after 2000 and including would substantially reduce the number of observations. The sample period of the data set spans the period1994-2006. There are totally 65 observations and all data are expressed in local currency (Turkish lira). We specify a dynamic fixed effects panel data model to investigate the factors that affect the capital structure of lodging companies. Various estimation techniques, including the Arellano-Bond System GMM method, are used for the estimation. In the theoretical model specified to test the capital structure decisions of the lodging companies in Turkey the dependent variable is specified as the debt ratio. The debt ratio is defined as the book value of liabilities divided by the book value of total assets. This variable measures the share of liabilities in total assets of a company and is widely used in capital structure studies. Explanatory variables are specified as follows:. growth opportunities defined as the market value divided by the book value of the firm, often referred as market-to-book ratio;. share of fixed assets (tangibility) defined as the net fixed tangible assets divided by total assets;. effective tax rates defined as the corporate tax divided by taxable income;. non-debt tax shields defined as the depreciation divided by total assets;. firm size defined as the net sales adjusted by the inflation rate, where the inflation rate is computed as the annual percentage change in the wholesale price index;. profitability (return on assets-ROA) calculated by dividing net profit by total assets; . free cash flows computed by adding interest payments and depreciation to earnings before taxes;. net commercial trade position (inter-enterprise debt) defined as the difference between commercial receivables and liabilities divided by total assets.Empirical findingsIn this section, we present the various estimation results and discuss the implications of the empirical findings. The specification of the debt ratio equation introduces correlation between the errors and the lagged first-differenced endogenous variable. This correlation is handled using instrumental variables (IVs). Anderson and Hsiao (1982) proposed using lagged past differences or levels of endogenous variables as instruments (Anderson-Hsiao IV approach). These IVs are proposedwithin the framework of the GMM, since they may not be highly correlated with the first-differenced dependent variable. Alternatively, Arellano and Bond (1991) suggested that first differences of the endogenous variable be instrumented with lags of its own levels. This is known as the Arellano-Bond GMM approach. Blundell and Bond (1998) pointed out that lagged levels are often poor instruments for first differences. They proposed using all information on both endogenous and exogenous variables. This is known as the Arellano and Bond system (Arellano-Bond System GMM approach) method and provides more efficient and unbiased estimates in small Samples。

外文翻译Capital Structure and Firm Performance Material Source: Board of Governors of the Federal Reserve SystemAuthor: Allen N. BergerAgency costs represent important problems in corporate governance in both financial and nonfinancial industries. The separation of ownership and control in a professionally managed firm may result in managers exerting insufficient work effort, indulging in perquisites, choosing inputs or outputs that suit their own preferences, or otherwise failing to maximize firm value. In effect, the agency costs of outside ownership equal the lost value from professional managers maximizing their own utility, rather than the value of the firm.Theory suggests that the choice of capital structure may help mitigate these agency costs. Under the agency costs hypothesis, high leverage or a low equity/asset ratio reduces the agency costs of outside equity and increases firm value by constraining or encouraging managers to act more in the interests of shareholders. Since the seminal paper by Jensen and Meckling (1976), a vast literature on such agency-theoretic explanations of capital structure has developed (see Harris and Raviv 1991 and Myers 2001 for reviews). Greater financial leverage may affect managers and reduce agency costs through the threat of liquidation, which causes personal losses to managers of salaries, reputation, perquisites, etc. (e.g., Grossman and Hart 1982, Williams 1987), and through pressure to generate cash flow to pay interest expenses (e.g., Jensen 1986). Higher leverage can mitigate conflicts between shareholders and managers concerning the choice of investment (e.g., Myers 1977), the amount of risk to undertake (e.g., Jensen and Meckling 1976, Williams 1987), the conditions under which the firm is liquidated (e.g., Harris and Raviv 1990), and dividend policy (e.g., Stulz 1990).A testable prediction of this class of models is that increasing the leverage ratio should result in lower agency costs of outside equity and improved firm performance, all else held equal. However, when leverage becomes relatively high, further increases generate significant agency costs of outside debt – including higher expected costs of bankruptcy or financial distress – arising from conflicts between bondholders and shareholders.1 Because it is difficult to distinguish empiricallybetween the two sources of agency costs, we follow the literature and allow the relationship between total agency costs and leverage to be non-monotonic.Despite the importance of this theory, there is at best mixed empirical evidence in the extant literature (see Harris and Raviv 1991, Titman 2000, and Myers 2001 for reviews). Tests of the agency costs hypothesis typically regress measures of firm performance on the equity capital ratio or other indicator of leverage plus some control variables. At least three problems appear in the prior studies that we address in our application.First, the measures of firm performance are usually ratios fashioned from financial statements or stock market prices, such as industry-adjusted operating margins or stock market returns. These measures do not net out the effects of differences in exogenous market factors that affect firm value, but are beyond management’s control and therefore cannot reflect agency costs. Thus, the tests may be confounded by factors that are unrelated to agency costs. As well, these studies generally do not set a separate benchmark for each firm’s performance that would be realized if agency costs were minimized.We address the measurement problem by using profit efficiency as our indicator of firm performance. The link between productive efficiency and agency costs was first suggested by Stigler (1976), and profit efficiency represents a refinement of the efficiency concept developed since that time.2 Profit efficiency evaluates how close a firm is to earning the profit that a best-practice firm would earn facing the same exogenous conditions. This has the benefit of controlling for factors outside the control of management that are not part of agency costs. In contrast, comparisons of standard financial ratios, stock market returns, and similar measures typically do not control for these exogenous factors. Even when the measures used in the literature are industry adjusted, they may not account for important differences across firms within an industry –such as local market conditions – as we are able to do with profit efficiency. In addition, the performance of a best-practice firm under the same exogenous conditions is a reasonable benchmark for how the firm would be expected to perform if agency costs were minimized.Second, the prior research generally does not take into account the possibility of reverse causation from performance to capital structure. If firm performance affects the choice of capital structure, then failure to take this reverse causality into account may result in simultaneous-equations bias. That is, regressions of firmperformance on a measure of leverage may confound the effects of capital structure on performance with the effects of performance on capital structure.We address this problem by allowing for reverse causality from performance to capital structure. We discuss below two hypotheses for why firm performance may affect the choice of capital structure, the efficiency-risk hypothesis and the franchise-value hypothesis. We construct a two-equation structural model and estimate it using two-stage least squares (2SLS). An equation specifying profit efficiency as a function of the firm’s equity capital ratio and other variables is use d to test the agency costs hypothesis, and an equation specifying the equity capital ratio as a function of the firm’s profit efficiency and other variables is used to test the net effects of the efficiency-risk and franchise-value hypotheses. Both equations are econometrically identified through exclusion restrictions that are consistent with the theories.Third, some, but not all of the prior studies did not take ownership structure into account. Under virtually any theory of agency costs, ownership structure is important, since it is the separation of ownership and control that creates agency costs (e.g., Barnea, Haugen, and Senbet 1985). Greater insider shares may reduce agency costs, although the effect may be reversed at very high levels of insider holdings (e.g., Morck, Shleifer, and Vishny 1988). As well, outside block ownership or institutional holdings tend to mitigate agency costs by creating a relatively efficient monitor of the managers (e.g., Shleifer and Vishny 1986). Exclusion of the ownership variables may bias the test results because the ownership variables may be correlated with the dependent variable in the agency cost equation (performance) and with the key exogenous variable (leverage) through the reverse causality hypotheses noted above.To address this third problem, we include ownership structure variables in the agency cost equation explaining profit efficiency. We include insider ownership, outside block holdings, and institutional holdings.Our application to data from the banking industry is advantageous because of the abundance of quality data available on firms in this industry. In particular, we have detailed financial data for a large number of firms producing comparable products with similar technologies, and information on market prices and other exogenous conditions in the local markets in which they operate. In addition, some studies in this literature find evidence of the link between the efficiency of firms and variables that are recognized to affect agency costs, including leverage andownership structure (see Berger and Mester 1997 for a review).Although banking is a regulated industry, banks are subject to the same type of agency costs and other influences on behavior as other industries. The banks in the sample are subject to essentially equal regulatory constraints, and we focus on differences across banks, not between banks and other firms. Most banks are well above the regulatory capital minimums, and our results are based primarily on differences at the margin, rather than the effects of regulation. Our test of the agency costs hypothesis using data from one industry may be built upon to test a number of corporate finance hypotheses using information on virtually any industry.We test the agency costs hypothesis of corporate finance, under which high leverage reduces the agency costs of outside equity and increases firm value by constraining or encouraging managers to act more in the interests of shareholders. Our use of profit efficiency as an indicator of firm performance to measure agency costs, our specification of a two-equation structural model that takes into account reverse causality from firm performance to capital structure, and our inclusion of measures of ownership structure address problems in the extant empirical literature that may help explain why prior empirical results have been mixed. Our application to the banking industry is advantageous because of the detailed data available on a large number of comparable firms and the exogenous conditions in their local markets. Although banks are regulated, we focus on differences across banks that are driven by corporate governance issues, rather than any differences in-regulation, given that all banks are subject to essentially the same regulatory framework and most banks are well above the regulatory capital minimums.Our findings are consistent with the agency costs hypothesis – higher leverage or a lower equity capital ratio is associated with higher profit efficiency, all else equal. The effect is economically significant as well as statistically significant. An increase in leverage as represented by a 1 percentage point decrease in the equity capital ratio yields a predicted increase in profit efficiency of about 6 percentage points, or a gain of about 10% in actual profits at the sample mean. This result is robust to a number of specification changes, including different measures of performance (standard profit efficiency, alternative profit efficiency, and return on equity), different econometric techniques (two-stage least squares and OLS), different efficiency measurement methods (distribution-free and fixed-effects), different samples (the “ownership sample” of banks with detailed ownership data and the “full sample” of banks), and the different sample periods (1990s and 1980s).However, the data are not consistent with the prediction that the relationship between performance and leverage may be reversed when leverage is very high due to the agency costs of outside debt.We also find that profit efficiency is responsive to the ownership structure of the firm, consistent with agency theory and our argument that profit efficiency embeds agency costs. The data suggest that large institutional holders have favorable monitoring effects that reduce agency costs, although large individual investors do not. As well, the data are consistent with a non-monotonic relationship between performance and insider ownership, similar to findings in the literature.With respect to the reverse causality from efficiency to capital structure, we offer two competing hypotheses with opposite predictions, and we interpret our tests as determining which hypothesis empirically dominates the other. Under the efficiency-risk hypothesis, the expected high earnings from greater profit efficiency substitute for equity capital in protecting the firm from the expected costs of bankruptcy or financial distress, whereas under the franchise-value hypothesis, firms try to protect the expected income stream from high profit efficiency by holding additional equity capital. Neither hypothesis dominates the other for the ownership sample, but the substitution effect of the efficiency-risk hypothesis dominates for the full sample, suggesting a difference in behavior for the small banks that comprise most of the full sample.The approach developed in this paper can be built upon to test the agency costs hypothesis or other corporate finance hypotheses using data from virtually any industry. Future research could extend the analysis to cover other dimensions of capital structure. Agency theory suggests complex relationships between agency costs and different types of securities. We have analyzed only one dimension of capital structure, the equity capital ratio. Future research could consider other dimensions, such as the use of subordinated notes and debentures, or other individual debt or equity instruments.译文资本结构与企业绩效资料来源: 联邦储备系统理事会作者：Allen N. Berger 在财务和非财务行业，代理成本在公司治理中都是重要的问题。

资本结构层次因素甲，乙爱德华光加代？，赫伯特木村一Universidade圣保罗，圣保罗，巴西bUniversidade Presbiteriana麦肯齐，圣保罗，巴西文章资讯摘要：文章历史：我们分析了时间，固件，行业和国家一级的资本结构决定因素的影响。

收到2019年2月3日第一，我们使用阶层线性模式，以评估这些水平的相对重要性。

接受2019年8月16日我们发现，时间和企业一级公司的杠杆解释78％。

第二，我们包括随机拦截可在线二○一○年八月二十日和随机系数以分析公司的直接和间接的影响力/行业/国家characteristicsonfirmleverage.Wedocumentseveralimportantindirectinfluences ofvariablesatindus - JEL分类：尝试和国家层面的杠杆公司决定因素，以及在一些结构上的差异F30金融行为与发达国家和新兴国家的公司。

G32 2019埃尔塞维尔B.诉保留所有权利。

关键词：资本结构层次分析企业层面的决定因素行业水平的决定因素国家一级的决定因素1。

导言等，2019;。

曼西和里布，2019年;。

德赛等，2019）的比较与跨国公司的国内企业融资政策这些研究对资本结构的优势主要basedontheargumentthatglobalfactorsmightinfluencefinancial重点是分析某些公司特征- 例如，利润杠杆。

如果，一方面，它很容易找到研究，分析能力，有形性，大小等- 作为杠杆的决定因素。

在阿迪，公司/作为国家的资本结构影响因素的特点，tion，资本结构可能各不相同的时间（例如，Korajczyk和ontheotherhand，theliteratureoftenneglectstheroleofindustry。

利维，2019年），尽管常常相对稳定云集帽虽然大多数研究包括资本结构虚拟需求面实证结构（莱蒙等。

中文3400字原文：The interaction of corporate dividend policy and capital structure decisions under differential tax regimes1、The interaction of capital structure and dividend policyFirm values are normalized with respect to the firm with zero debt and zero dividend payout. The panels in the figure indicate that the combined net impact of corporate dividend and capital structure policies on firm value is directly affected by the pertinent tax rates at the time.We next discuss the implications of the model for dividend and capital structure policies under several historical tax regimes. Three representative tax regimes (1979–1981, 1988–1990, 1993–2002) were chosen for analysis out of the ten that were in existence at some time during the three decades since 1979. The three representative tax regimes exhibit distinctly different set of tax rates both in terms of absolute values and relative to each other. For this reason, these three contrasting regimes provide a suitable setting to test the value implications of our model. If our model provides a reasonable representation of firms’ capital structure and dividend policy decisions, the three contrasting tax regimes would be the ideal environment to observe the fit between the model’s predictions and the empirical o bservations.2、Years 1979–1981The application of the model using the tax rates from the period 1979–1981 reveals a subtle effect. The table and the figure depict normalized firm value, VD,Π/V0,0, as a function of the leverage D and the dividend payout π. The gain from leverage is positive only when the firm is at a relatively high payout ratio (above approximately 40%), with the maximum gain occurring at full (100%) payout. Interestingly, at a dividend payout level lower than 40%, increasing leverage lowers firm value.The reversal of the leverage effect at lower payout ratios is driven by the relative levels of tax rates. During the years 1979–1981, the top marginal tax rate for personalincome was very high in comparison to the tax rate for corporate income (70% and 46% respectively). In a tax rate environment such as this, high taxes paid by the bondholders for their interest income proceeds exceed the benefit from the tax deductibility of interest payments at the firm level. Since debt financing can be assumed to have zero NPV, this additional burden is borne by the shareholders. At high levels of dividend payout on the other hand, the taxation of the dividend income makes dividend payout even more disadvantageous compared to paying interest. In other words, now it would be more beneficial for the firm to borrow and pay interest rather than dividends. The benefit reaped from the tax deductibility of interest payments tilts the balance in favor of debt financing, and makes leverage more attractive.Another noteworthy observation about the 1979–1981 tax rate environment is the steep loss in firm value at very low debt levels in response to increasing dividend payout. According to our model, it was possible for an all-equity firm to experience losses in value up to 58%. The firm could mitigate this loss by maintaining a higher debt level.The tax regime that made the interesting features discussed above possible is not a short-term anomaly confined to the years 1979–1981. Indeed, the entire period between the Great Depression and the late 1970s was characterized by a similar tax rate environment. Our model indicates that optimal policies to maximize firm value under such tax regimes required zero debt and zero dividend payout. This prescription interestingly comports with the observed leverage policies of the time, when numerous prominent companies such as IBM and Coca Cola had little, if any, debt before the 1980s. However, if a firm would need to maintain high dividend payout levels, it would be better off by carrying a relatively high debt level at the same time. Traditional electric utility companies are examples that appear to fit this mold.3、Years 1988–1990 (and 1991–1992)The situation during the years 1988–1990 is unique because during that time the top marginal tax rates on ordinary income (thus on dividend and interest income) were nominally the same as the tax rate on capital gains at 28%. In the following 2 years(1991–1992), the two tax rates remained very close (at 31.0% and 28.9% respectively). The result of the convergence in tax rates is visible in Fig. 2 for the1988–1990 and 1991–1992 panels. There is little if any moderating influence of the dividend payout on the leverage-firm value relation. The maximum theoretical gain from leverage is close to 50% regardless of the level of dividend payout. As discussed and anticipated on the comparative statics for our model, the influence of the dividend payout ratio vanishes due to the near-zero tax rate differential (τpd−τpg) during the years 1988–1992.4、Years 1993–2002In contrast to the reversal effect observed under the tax regime during 1979–1981, and similar to the situation during 1988–1992, the gain from leverage is always positive under the 1993–2002 tax regimes. The details of the gain from leverage relation and the effect of the dividend payout for the years 1993–1994 and the year 2002 are available. As a departure from the previous tax regimes discussed above, throughout this decade-long time interval, the gain from leverage is significantly more pronounced for high payout firms. Although at low or zero debt levels increased dividend payout reduces the firm value, the negative impact of the dividend payout weakens as the debt level increases.In contrast to the maximum potential gain from leverage during 1988–1992 that reached up to 50%, the tax rate changes throughout the 1990s significantly reduced the maximum potential gain. the maximum potential gain was near 30% in 1993, and by 1998, approximately 20%,remaining at that level through 2002.5、Summary and empirical implicationsThe nature of the combined impact of financial leverage and dividend policy on firm value over the years 1979–2002 is found to be wide ranging as a direct result of the tax rate changes. We discussed above three distinct tax regime environments in detail. In the first interval 1979–1981, low leverage and low dividend payout leads to higher firm value. However, given a high dividend payout, the firm is better off by carrying a high debt level. That suggests a simultaneous increase or decrease in leverage and payout for firms. It is less likely to find firms with low leverage and highpayout (which results in the minimum possible firm value). The empirical implication of the model for the 1979–1981 time interval is a positive association between leverage and payout.The same logic applies throughout the years following the 1979–1981 time interval up to 1987 and again after 1992. During the years 1979–1987, the tax rate were such that at low debt levels, firm value declined with increasing dividend payout ratios. Similarly, from 1993 until 2002, firms would suffer losses in value if they chose to increase dividend payout while maintaining low debt levels. In contrast, during the 1988–1992 time interval, there was no penalty for having a high dividend payout for a firm with a low debt level. Dividend payout was truly irrelevant during that time and would not be expected to systematically vary between firms that carry various levels of debt.The breakdown in the interaction of dividend payout and capital structure during the 1988–1992 time period as implied by our model provides an opportunity to test the model empirically. If our model is a reasonable representation of the dividend payout-capital structure interaction under varying tax rate environments, we would expect a positive association between dividend payout and debt levels during the years 1979–1987 and 1993–2002 During the years 1988–1992, the association between dividend payout and leverage is expected to be weaker. We conduct several empirical tests in Section 5 to examine the validity of these predictions.It is worth noting that, to the extent firms have shifted their distributions to their shareholders from dividends to stock repurchases over time, our empirical analysis, which only uses dividend payout data, will not be able to pick up this trend. Indeed, during the three decades under study there was a shift in firms’ attitudes toward share repurchases vis-à-vis dividend payout. We do not pursue stock repurchases empirically in this study due to data limitations. However, note that the model derived in this paper is implicitly capturing the valuation effect of repurchases via the capital gains term .Variable pay is an expanding field within compensation driven by the emerging trends of pay for performance and competitive advantage. Funding these new programs and developing the processes supporting long-term effectiveness iscritical.In this paper we develop a valuation model that ties together capital structure and dividend payout polices while incorporating differential tax rates on dividend distributions and capital gains. As such it is an extension of the original Miller and Modigliani (1961) dividend policy model and of the Miller (1977) model. We numerically and graphically demonstrate the implications of this new model under ten different tax regimes in effect since 1979 and derive the implications of the model for firm value as a function of debt ratio and dividend payout ratio.Our analysis indicates a wide range of firm values depending on the particular set of tax rates applicable at the time. In the first interval, 1979–1981, when the tax regime featured a high rate on dividend income in comparison to the rates on corporate income and personal capital gains, increasing financial leverage would lead to losses in firm value, if the dividend payout was relatively small. At dividend payout ratios below 40%, the loss in firm value in response to increased debt ratio could potentially reach 23%. During the same time period, if the firm maintained a dividend payout ratio in excess of 40%, the firm value could almost double, if an all equity firm decided to take on debt. During the 1988–1990 time period, when the tax rates on dividend income and capital gains were both 28%, an all-equity firm (without regard to its dividend payout level) could increase in value by as much as50% as it took on more debt. Under the tax regimes prevailing after 1998, the maximum potential gain for a non-dividend paying all-equity firm was roughly 20%, whereas a firm with a high dividend payout could be worth 50% more if it were to boost its debt financing.Using the analysis of the valuation model under a diverse set of tax regimes, we develop several predictions for empirical testing. The results of the empirical tests are strongly supportive of the basic predictions of our analysis in a static setting. The interaction between dividend policy and financial leverage decisions is significantly influenced by the prevailing tax rates. The more dynamic predictions of the model remain for subsequent examination.By design, our tax-based model abstracts from the well-known and important contributions of previous studies on bankruptcy/financial distress costs, agencyconsiderations, and signaling theories. However, the insights gained from our extended tax-based model could contribute in a significant way to the understanding of corporate financial policy in both research and policy dimensions. It is a well established notion within the trade-off theory of corporate capital structure that a range of debt levels exists, in which debt financing has a positive impact on firm value. Over this range, our model has the potential to provide a valuable insight into the effect of dividend policy on capital structure.In the near future, another major change in the U.S. tax environment is possible, especially if the JGTRRA is allowed to expire by the Congress. The ability of the model in this paper to easily incorporate the new levels of marginal tax rates on four types of income makes it a useful tool for corporate decision makers in analyzing dividend and debt decisions. For purposes of research, the model can be used to gain insights into the evolution of dividend policy over the past three decades.Source: Ufuk Ince and James E. Owers. 2003 “The interaction of corporate dividend policy and capital structure decisions under differential tax regimes”. Journal of Economics and Finance, August, pp. 29-32.译文：在分税制度股利政策与资本结构下的决策1、互动的资本结构和股利政策公司价值方面进行归一零债务和零股利支出。

第01讲资本成本与资本结构Part 1 核心词汇Part 2 重难点讲解—资本成本（一）普通股成本的估计（二）优先股成本的估计（三）债务成本的估计特殊债券的成本估计（四）加权平均资本成本（WACC）【例题·2017年考题】甲公司为扩大产能，拟平价发行分离型附认股权证债券进行筹资，方案如下：债券每份面值1000元，期限5年，票面利率5%。

每年付息一次。

同时附送20份认股权证。

认股权证在债券发行3年后到期，到期时每份认股权证可按11元的价格购买1股甲公司普通股股票。

甲公司目前有发行在外的普通债券，5年后到期，每份面值1000元，票面利率6%，每年付息一次，每份市价1020元（刚刚支付过最近一期利息）公司目前处于生产的稳定增长期，可持续增长率5%。

普通股每股市价10元。

公司企业所得税率25%。

要求：（1）计算公司普通债券的税前资本成本。

（2）计算分离型附认股权证债券的税前资本成本。

（3）判断筹资方案是否合理，并说明理由，如果不合理，给出调整建议。

『正确答案』（1）令税前资本成本为iAssume Pre－tax cost of capital is i1020＝1000×6%×（P/A，i，5）＋1000×（P/F，i，5）当i＝4%时，等式右边＝1000×6%×4.4518＋1000×0.8219＝1089When i equals 4%, the right side of the equation＝1000×6%×4.4518＋1000×0.8219＝1089 continuing当i＝6%时, 等式右边＝1000×6%×4.2124＋1000×0.7473＝1000When i equals 6%， the right side of the equation ＝1000×6%×4.2124＋1000×0.7473＝1000 列出等式：Write out the equality ：（i－4%）/（6%－4%）＝（1020－1089）/（1000－1089）i＝4%＋[（1020－1089）/（1000－1089）]×（6%－4%）＝5.55%（2）第3年末行权支出＝11×20＝220（元）Exercise expenditure at the end of the third year＝11×20＝220（yuan ）取得股票的市价＝10×（F/P，5%，3）×20＝231.525（元）The market price of the acquired stock＝10×（F/P，5%，3）×20＝231.525（yuan ）行权现金净流入＝231.5325－220＝11.525（元）Net cash inflow when option are exercised＝ 231.5325－220＝11.525（yuan ）令税前资本成本为k，Assume Pre－tax cost of capital is K1000＝1000×5%×（P/A，K，5）＋11.525×（P/F，K，3）＋1000×（P/F，K，5）K＝5%时，等式右边＝1000×5%×4.3295＋11.525×0.8638＋1000×0.7835＝1009.93（元）When K equals 5%, the right side of the equation =……K＝6%时，等式右边＝1000×5%×4.2124＋11.525×0.8396＋1000×0.7473＝967.60（元）When K equals 6%, the right side of the equation =……（K－5%）/（6%－5%）＝（1000－1009.93）/（967.60－1009.93）K＝5%＋[（1000－1009.93）/（967.60－1009.93）]×（6%－5%）＝5.23%（3）该筹资方案不合理，原因是附认股权证债券的税前资本成本低于普通债券的税前资本成本。

外文文献翻译译文原文：Capital Structure around the World: The Roles of Firm andCountry-Specific DeterminantsWe analyze the importance of firm-specific and country-specific factors in the leverage choice of firms from 42 countries around the world. Our analysis yields two new results. First, we find that firm-specific determinants of leverage differ across countries, while prior studies implicitly assume equal impact of firm-specific factors. Second, although we concur with the conventional direct impact of country-specific factors on the capital structure of firms, we show that there is an indirect impact because country-specific factors also influence the roles of firm-specific determinants of leverage.Prior research (e.g. Demirgüç-Kunt and Maksimovic, 1999; Booth, Demirgüç-Kunt and Maksimovic, 2001; Claessens, Djankov and Nenova, 2001; Bancel and Mittoo, 2004) finds that a firm’s capital structure is not only influenced by firm-specific factors but also by country specific factors. In this study, we demonstrate that country-specific factors can affect corporate leverage in two ways. On the one hand, these factors can influence leverage directly. For example, a more developed bond market facilitating issue and trading of public bonds may lead to the use of higher leverage in a country, while a developed stock market has the opposite effect. On the other hand, we show that country-specific factors can also influence corporate leverage indirectly through their impact on firm-specific factors’ roles. For example, although the developed bond market of a country stimulates the use of debt, the role of asset tangibility as collateral in borrowing will be rather limited for firms in the same country. In other words, country-characteristics may explain why in one country a f irm’s tangibility affects leverage, but not in another country. Previous studies have not systematically investigated these indirect effects.International studies comparing differences in the capital structure betweencountries started to appear only during the last decade. An early investigation of seven advanced industrialized countries is performed by Rajan and Zingales (1995). They argue that although common firm-specific factors significantly influence the capital structure of firms across countries, several country-specific factors also play an important role. Demirgüç-Kunt and Maksimovic (1999) compare capital structure of firms from 19 developed countries and 11 developing countries. They find that institutional differences between developed and developing countries explain a large portion of the variation in the use of long-term debt. They also observe that some institutional factors in developing countries influence the leverage of large and small firms differently. Several recent studies on the field have indicated that even among developed economies like the U.S. and European countries, the financing policies and managers’ behavior are influenced by the institutional environment and international operations (see, for example, Graham and Harvey, 2001; Bancel and Mittoo, 2004; and Brounen, De Jong and Koedijk,2006).The literature specifically discusses only the direct impact of country characteristics on leverage. In an analysis of ten developing countries, Booth et al. (2001) find that capital structure decisions of firms in these countries are affected by the same firm-specific factors as in developed countries. However, they find that there are differences in the way leverage is affected by country-specific factors such as GDP growth and capital market development. They conclude that more research needs to be done to understand the impact of institutional factors on firms’ capital structure choices. The importance of country-specific factors in determining cross country capital structure choice of firms is also acknowledged by Fan et al. (2006) who analyze a larger sample of 39 countries. They find a significant impact of a few additional country-specific factors such as the degree of development in the banking sector, and equity and bond markets. In another study of 30 OECD countries, Song and Philippatos (2004) report that most cross-sectional variation in international capital structure is caused by the heterogeneity of firm-,industry-, and country-specific determinants. However, they do not find evidence to support the importance of cross-country legal institutional differences in affecting corporateleverage. Giannetti (2003) argues that the failure to find a significant impact of country-specific variables may be due to the bias induced in many studies by including only large listed companies. She analyzes a large sample of unlisted firms from eight European countries and finds a significant influence on the leverage of individual firms of a few institutional variables such as creditor protection, stock market development and legal enforcement. Similarly, Hall et al. (2004) analyze a large sample of unlisted firms from eight European countries. They observe cross country variation in the determinants of capital structure and suggest that this variation could be due to different country-specific variables.A remarkable feature of existing studies on international capital structure is the implicit assumption that the impact of firm-specific factors on leverage is equal across countries (see for example Booth et al., 2001; Giannetti, 2003; Song and Philippatos, 2004; and Fan et al., 2006). By reporting the estimated coefficients for firm-specific determinants of leverage per country, these papers, on the one hand, acknowledge that the impact of firm-level determinants does differ in terms of signs, magnitudes and significance levels. On the other hand, in the analysis of country-specific determinants of corporate leverage, these papers also make use of country dummies in pooled firm-year regressions, thus forcing the firm-specific coefficients to have the same value. With an extremely large number of firm-year observations, it is more likely for this procedure to produce statistically significant results for many country-specific variables. But, utilizing an alternative regression framework where a single average capital structure for each country is used as an observation, one hardly finds strong evidence on this issue. As an additional contribution of our paper, we show the invalidity of this implicit assumption. Our analysis without imposing such restriction thus provides a more reliable analysis on the importance of country-specific variables.The study encompasses a large number of countries (42 in total) from every continent for the period 1997-2001. We construct a database of nearly 12,000 firms (about 60,000 firm-year observations). All types of firms –large and small –are included as long as a reasonable amount of data is available. We analyze the standard firm-specific determinants of leverage like firm size, asset tangibility, profitability,firm risk and growth opportunities. Besides, we incorporate a large number of country-specific variables in our analysis, including legal enforcement, shareholder/creditor right protection, market/bank-based financial system, stock/bond market development and growth rate in a country’s gross domestic product (GDP).Firm-specific and country-specific determinants are the two major types of variables that we take into account when analyzing the impacts on firm s’ leverage choice. The firms in our sample cover 42 countries that are equally divided between developed and developing countries. Data for leverage and firm-specific variables are collected from COMPUSTAT Global database. We exclude financial firms and utilities. Data on country-specific variables are collected from a variety of sources, mainly World Development Indicators files and Financial Structure Database of the World Bank. Few country-specific variables are taken from previous studies including La Porta et al. (1998), Claessens and Klapper (2002) and Berkowitz et al. (2003). Our sample period covers the years 1997-2001. The selection of a time-period involves a trade-off between the number of countries that can be included in the study and the availability of enough firm-specific data. Whenever needed, we resort to some other sources to collect any missing data. It is still impossible to obtain data for each and every variable from all 42 countries during this time period. The final sample consists of 59,225 observations on 11,845 firms. Even though we aim to keep the number of countries high enough and also maintain a reasonable number of firms, our dataset has unavoidably a limited number of firms in a few countries.Analyzing the direct impact of country-specific factors on leverage, the evidence suggests that creditor right protection, bond market development, and GDP growth rate have a significant influence on corporate capital structure. In measuring the impact indirectly, we find evidence for the importance of legal enforcement, creditor/shareholder right protection, and macro-economic measures such as capital formation and GDP growth rate. It implies that in countries with a better legal environment and more stable and healthier economic conditions, firms are not only likely to take more debt, but also the effects of firm-level determinants of leverage are also reinforced. Overall, the evidence provided here highlights the importance ofcountry-specific factors in corporate capital structure decisions. Our conclusion is that country-specific factors do matter in determining and affecting the leverage choice around the world, and it is useful to take into account these factors in the analysis of a country’s capital structure. If the limitations of data, especially the number of countries, can be overcome, one might find even more significant results with respect to the impact of country-specific factors.We first make a detailed comparative analysis of the impact of various firm-specific factors. We find across a large number of countries that the impact of some factors like tangibility, firm size, risk, and profitability and growth opportunities is strong and consistent with standard capital structure theories. Our study shows that, in terms of firm-specific determinants of leverage, capital structure theories do explain the corporate leverage choice in a large number of countries. Using a model with several firm-specific explanatory variables, we find a relatively large explanatory power of leverage regressions in most countries. However, a few determinants remain insignificant, and in some countries one or two coefficients are significant with an unexpected sign. Performing a simple statistical test, we reject the hypothesis that firm-specific coefficients across countries are equal. It indicates that the often-made implicit assumption of equal firm-level determinants of leverage across countries does not hold.In the analysis of the direct impact of country-specific factors, we observe that certain factors like GDP growth rate, bond market development and creditor right protection significantly explain the variation in capital structure across countries. Moreover, we find considerable explanatory power of country-specific variables beyond firm-specific factors. We then proceed to measure the indirect impact of country-specific variables. The results consistently show the importance of country factors as we document significant effects of these via firm-specific determinants. For example, we observe that in countries with a better law enforcement system and a more healthy economy, firms are not only likely to take more debt, but the effects of some firm-level determinants of leverage such as growth opportunities, profitability and liquidity are also reinforced. Our findings indicate that the conventional theorieson capital structure developed using listed firms in the United States as a role model, work well in similar economies with developed legal environment and high level of economic development. The indirect impact analysis also indicates that firm-specific variables are significantly influenced by several country-specific variables but in different ways.Capital structure theories have been mostly developed and tested in the single-country context. Researchers have identified several firm-specific determinants of a firm’s leverage,based on the three most accepted theoretical models of capital structure, i.e. the static trade-off theory, the agency theory and the pecking-order theory. A large number of studies have been conducted to date investigating to what extent these factors influence capital structures of firms operating within a specific country. In this paper, we examine the role of firm-specific determinants of corporate leverage choice around the world. We analyze a large sample of 42 countries, divided equally between developed and developing countries. Our main objective is to verify the role of various country-specific factors in determining corporate capital structure. We distinguish two types of effects: the direct effect on leverage and the indirect effect through the influence on firm-specific determinants of corporate leverage.We find that the impact of several firm-specific factors like tangibility, firm size, risk, growth and profitability on cross-country capital structure is significant and consistent with the prediction of conventional capital structure theories. On the other hand, we also observe that in each country one or more firm-specific factors are not significantly related to leverage. For some countries, we find results that are inconsistent with theoretical predictions.Several studies analyzing international capital structure assume cross-country equality of firm-level determinants. We show that this assumption is unfounded. Rather, it is necessary to conduct an analysis of country-specific factors by including countries as observations and avoid a specification using a pooled regression method. We conduct regressions using country-specific factors to explain coefficients of country dummies as well as firm-specific determinants.Source:Abe de Jong, Rezaul Kabir, 2007.9 “Capital Structure around the World: The Roles of Firm and Country-Specific Determinants”. ERIM Report Series Reach in Management.September.pp.58-63.译文：世界各地的资本结构：公司和国家因素在其中的影响我们从世界42个国家中分析了公司在选择财务杠杆所需要考虑的公司特有因素和国家因素的重要性。

Capital Structure and Firm Performance1. IntroductionAgency costs represent important problems in corporate governance in both financial and nonfinancialindustries. The separation of ownership and control in a professionally managed firm may result in managersexerting insufficient work effort, indulging in perquisites, choosing inputs or outputs that suit their ownpreferences, or otherwise failing to maximize firm value. In effect, the agency costs of outside ownership equalthe lost value from professional managers maximizing their own utility, rather than the value of the firm. Theory suggests that the choice of capital structure may help mitigate these agency costs. Under theagency costs hypothesis, high leverage or a low equity/asset ratio reduces the agency costs of outside equity andincreases firm value by constraining or encouraging managers to act more in the interests of shareholders. Sincethe seminal paper by Jensen and Meckling (1976), a vast literature on such agency-theoretic explanations ofcapital structure has developed (see Harris and Raviv 1991 and Myers 2001 for reviews). Greater financialleverage may affect managers and reduce agency costs through the threat of liquidation, which causes personallosses to managers of salaries, reputation, perquisites, etc. (e.g., Grossman and Hart 1982, Williams 1987), andthrough pressure to generate cash flow to pay interest expenses (e.g., Jensen 1986). Higher leverage canmitigate conflicts between shareholders and managers concerning the choice of investment (e.g., Myers 1977), the amount of risk to undertake (e.g., Jensen and Meckling 1976, Williams 1987), the conditions under which thefirm is liquidated (e.g., Harris and Raviv 1990), and dividend policy (e.g., Stulz 1990).A testable prediction of this class of models is that increasing the leverage ratio should result in loweragency costs of outside equity and improved firm performance, all else held equal. However, when leveragebecomes relatively high, further increases generate significant agency costs of outside debt –including higherexpected costs of bankruptcy or financial distress –arising from conflicts between bondholders andshareholders.1 Because it is difficult to distinguish empirically between the two sources of agency costs, wefollow the literature and allow the relationship between total agency costs and leverage to be nonmonotonic.Despite the importance of this theory, there is at best mixed empirical evidence in the extant literature(see Harris and Raviv 1991, Titman 2000, and Myers 2001 for reviews). Tests of the agency costs hypothesistypically regress measures of firm performance on the equity capital ratio or other indicator of leverage plussome control variables. At least three problems appear in the prior studies that we address in our application.In the case of the banking industry studied here, there are also regulatorycosts associated with very high leverage.First, the measures of firm performance are usually ratios fashioned from financial statements or stockmarket prices, such as industry-adjusted operating margins or stock market returns. These measures do not netout the effects of differences in exogenous market factors that affect firm value, but are beyon d management’scontrol and therefore cannot reflect agency costs. Thus, the tests may be confounded by factors that areunrelated to agency costs. As well, these studies generally do not set a separate benchmark for each firm’sperformance that would be reali zed if agency costs were minimized.We address the measurement problem by using profit efficiency as our indicator of firm performance.The link between productive efficiency and agency costs was first suggested by Stigler (1976), and profitefficiency represents a refinement of the efficiency concept developed since that time.2 Profit efficiencyevaluates how close a firm is to earning the profit that a best-practice firm would earn facing the sameexogenous conditions. This has the benefit of controlling for factors outside the control of management that arenot part of agency costs. In contrast, comparisons of standard financial ratios, stock market returns, and similarmeasures typically do not control for these exogenous factors. Even when the measures used in the literature areindustry adjusted, they may not account for important differences across firms within an industry – such as localmarket conditions – as we are able to do with profit efficiency. In addition, the performance of a best-practicefirm under the same exogenous conditions is a reasonable benchmark for how the firm would be expected toperform if agency costs were minimized.Second, the prior research generally does not take into account the possibility of reverse causation fromperformance to capital structure. If firm performance affects the choice of capital structure, then failure to takethis reverse causality into account may result in simultaneous-equations bias. That is, regressions of firmperformance on a measure of leverage may confound the effects of capital structure on performance with theeffects of performance on capital structure.We address this problem by allowing for reverse causality from performance to capital structure. Wediscuss below two hypotheses for why firm performance may affect the choice of capital structure, theefficiency-risk hypothesis and the franchise-value hypothesis. We construct a two-equation structural model andestimate it using two-stage least squares (2SLS). An equation specifying profit efficiency as a functi on of the2 Stigler’s argument was part of a broader exchange over whether productive efficiency (or X-efficiency) primarily reflectsdifficulties in reconciling the preferences of multiple optimizing agents –what is today called agency costs –versus “true” inefficiency, or failure to optimize (e.g., Stigler 1976, Leibenstein 1978). firm’s equity capital ratio and other variables is used to test the agency costs hypothesis, and an equationspecifying the equity capital ratio as a function of the firm’s profi tefficiency and other variables is used to testthe net effects of the efficiency-risk and franchise-value hypotheses. Both equations are econometricallyidentified through exclusion restrictions that are consistent with the theories.Third, some, but not all of the prior studies did not take ownership structure into account. Undervirtually any theory of agency costs, ownership structure is important, since it is the separation of ownership andcontrol that creates agency costs (e.g., Barnea, Haugen, and Senbet 1985). Greater insider shares may reduceagency costs, although the effect may be reversed at very high levels of insider holdings (e.g., Morck, Shleifer, and Vishny 1988). As well, outside block ownership or institutional holdings tend to mitigate agency costs bycreating a relatively efficient monitor of the managers (e.g., Shleifer and Vishny 1986). Exclusion of theownership variables may bias the test results because the ownership variables may be correlated with thedependent variable in the agency cost equation (performance) and with the key exogenous variable (leverage)through the reverse causality hypotheses noted aboveTo address this third problem, we include ownership structure variables in the agency cost equationexplaining profit efficiency. We include insider ownership, outside block holdings, and institutional holdings.Our application to data from the banking industry is advantageous because of the abundance of qualitydata available on firms in this industry. In particular, we have detailed financial data for a large number of firmsproducing comparable products with similar technologies, and information on market prices and otherexogenous conditions in the local markets in which they operate. In addition, some studies in this literature findevidence of the link between the efficiency of firms and variables that are recognized to affect agency costs,including leverage and ownership structure (see Berger and Mester 1997 for a review).Although banking is a regulated industry, banks are subject to the same type of agency costs and otherinfluences on behavior as other industries. The banks in the sample are subject to essentially equal regulatoryconstraints, and we focus on differences across banks, not between banks and other firms. Most banks are wellabove the regulatory capital minimums, and our results are based primarily on differences at the mar2. Theories of reverse causality from performance to capital structureAs noted, prior research on agency costs generally does not take into account the possibility of reversecausation from performance to capital structure, which may result in simultaneous-equations bias. We offer twohypotheses of reverse causation based on violations of the Modigliani-Millerperfect-markets assumption. It isassumed that various market imperfections (e.g., taxes, bankruptcy costs, asymmetric information) result in abalance between those favoring more versus less equity capital, and that differences in profit efficiency move theoptimal equity capital ratio marginally up or down.Under the efficiency-risk hypothesis, more efficient firms choose lower equity ratios than other firms, allelse equal, because higher efficiency reduces the expected costs of bankruptcy and financial distress. Under thishypothesis, higher profit efficiency generates a higher expected return for a given capital structure, and thehigher efficiency substitutes to some degree for equity capital in protecting the firm against future crises. This isa joint hypothesis that i) profit efficiency is strongly positively associated with expected returns, and ii) thehigher expected returns from high efficiency are substituted for equity capital to manage risks.The evidence is consistent with the first part of the hypothesis, i.e., that profit efficiency is stronglypositively associated with expected returns in banking. Profit efficiency has been found to be significantlypositively correlated with returns on equity and returns on assets (e.g., Berger and Mester 1997) and otherevidence suggests that profit efficiency is relatively stable over time (e.g., DeYoung 1997), so that a finding ofhigh current profit efficiency tends to yield high future expected returns.The second part of the hypothesis –that higher expected returns for more efficient banks are substitutedfor equity capital –follows from a standard Altman z-score analysis of firm insolvency (Altman 1968). Highexpected returns and high equity capital ratio can each serve as a buffer against portfolio risks to reduce theprobabilities of incurring the costs of financialdistressbankruptcy, so firms with high expected returns owing tohigh profit efficiency can hold lower equity ratios. The z-score is the number of standard deviations below theexpected return that the actual return can go before equity is depleted and the firm is insolvent, zi = (μi +ECAPi)/σi, where μi and σi are the mean and standard deviation, respectively, of the rate of return on assets, andratios for those that were fully owned by a single owner-manager. This may be an improvement in the analysis of agencycosts for small firms, but it does not address our main issues of controlling for differences in exogenous conditions and insetting up individualized firm benchmarks for performance.ECAPi is the ratio of equity to assets. Based on the first part of the efficiency-risk hypothesis, firms with higherefficiency will have higher μi. Based on the second part of the hypothesis, a higher μi allows the firm to have alower ECAPi for a ven z-score, so that more efficient firms may choose lower equity capital ratios.文章出处：Raposo Clara C. Capital Structure and Firm Performance .Journal ofFinance.Blackwell publishing.2005, (6): 2701-2727.资本结构与企业绩效1.概述代理费用不管在金融还是在非金融行业，都是非常重要的企业治理问题。

外文翻译原文The analysis of company's capital and evaluation of factors, which influencecreation of the optimal capital structureMaterial Source: Author: Svetlana Saksonova This is the primary information gathering stage, which is necessary for the effective planning afterwards. At this stage the objective of the financial manager is to determine the existing tendencies of the development of capital structure, as well as its volume, and their influence on the financial stability of the company. Efficiency of the existing financing arrangements can also be considered at this stage. This stage can conditionally be split into three parts –one more concerned with qualitative characteristics and the two other ones concerned with quantifying the results of the analysis.The first (qualitative) stage involves comparing the dynamics of the total capital and its ingredients compared to the dynamics of production and sales, assessing the proportion of the borrowed and equity and the history of this proportion. Borrowed capital is further split into long-term and short-term financial obligations, overdue financial obligations are discovered (if they exist) and the causes for the inabilities of a company to meet financial commitments are analyzed.The second (more quantitative) stage of the analysis uses the system of coefficients of financial stability of a company to asses the capital structure.This stage utilizes well known financial indicators, such as different liquidity ratios.The purpose of these coefficients of financial stability is to show the degree of the possible risk of bankruptcy of a company that is related to the use of borrowed financial resources. Obviously, if the company does not use any borrowed funds the risk of bankruptcy related to the usage of borrowed funds is equal to zero. As the proportion of the borrowed capital grows, the risk of bankruptcy is also growing, because of the increase in company’s liabilities.Therefore, financial coefficients are mostly of interest for the existing andpotential creditors of the company.As a rule, debts to the ordinary creditors are paid, after the payment of taxes, wages and repayment of claims of secured creditors, who provided loans secured by collateral, such as office space or production machinery. The assessment of company’s liquidity helps to make a judgment of the extent to which the ordinary (unsecured) creditor is protected.Another group of financial coefficients helps to determine the dependency of the company on the borrowed capital (how does the company use financial leverage) and therefore to compare the positions of the creditors and owners of the company. The concept of financial leverage states that the successful use of the borrowed capital leads to the increased profits for the owners of the company, since they have the rights to profits obtained by the use of the borrowed capital, which leads to the increase in company’s equity.However, one has to keep in mind that any loans and interest on those loans have to be repaid even in case, if the profits obtained are not enough to cover these payments. The owners of the company always have to cover the claims of the creditors, which can negatively influence the equity of the company. The concept of leverage is therefore a double-edged sword. The positive and negative influence of the financial leverage grows in proportion to the volume of the borrowed capital that the company uses. The risk of the creditor, therefore, also grows in tandem with the risk of the owners. The coefficients in this group include:• Debt to assets ratio is the primary and the most utilized evaluation, which can be made, while evaluating the risk of the creditor. This indicator is calculated by the following formula:Debt to assets ratio = Total Liabilities / Total AssetsThis indicator is calculated for a point in time, but not for a period. It calculates the share of the “other money” in the total amount of claims on the assets of the company. The higher this coefficient, the larger is the probable risk for the creditor. Let us assume, for example, that the results of the computation for the last three years of business operation of Company X are presented (along with several other financial coefficients that will be discussed below) in Table 1.This data indicates that around 50 % of the financial resources at company’s disposal come from the borrowed resources. Naturally, a question arises: whether this is a positive or negative development? This question doesnot have a unanimous answer. Everything depends on the preferences of company’s owners and its management, most importantly, on their attitude to risk. Managers, who are risk averse, will try to achieve lower levels of this indicator and will attempt attracting additional finance by issuing new shares. One the other hand, managers and owners who are risk neutral and have higher tolerance for risk, will attempt to boost the share of borrowed funds in assets, aiming to exploit the positive aspects of financial leverage and increase profits.If a company has a well-developed and positive credit history, creditors will gladly lend money, in spite of the large value of the debt to asset ratio. In practice, this indicator can reach levels as high as 90 %.I f the company is not considered a “reliable borrower” (not necessarily due to a failure to repay obligations, but, for example, due to the fact that the company is newly created), then the debt to asset ratio of 50 % can be considered critical for the company, in a sense, that after that level, the prospective of obtaining additional loan financing is significantly decreased.However, one cannot simply conclude that the coefficient described above is a perfectly correct evaluation of the company’s abilities to repay its debts. The reason for this is that the asset book value (used to calculate the coefficient) does not always correspond to the real economic value of those assets or even the value, for which they can be sold quickly. Apart from that, this coefficient does not provide any insights on the possible changes in profits of the company, which can influence the payments of interest and the repayment of the principal. • Debt to capital ratio is an indicator that is computed based on the proportion between the size of the long-term debt and the size of the capital. This indicator presents the analyst witha clearer picture of risk due to the usage of borrowed funds. In this calculation, capital is defined as the total amount of company’s capital (includi ng common and preferred stock as well as long-term debt), minus the short term liabilities. The coefficient can be computed according to the following formula:Debts to capital ratio = Long-term Liabilities /Total capitalBy definition, capital in this case includes the amount of long-term claims on company’s assets by the creditors as well as the owners but does not include current (short-term) claims. The total amount of those corresponds to what can be called net assets”, if no adjustments have been mad e, such as excluding deferred taxes from the calculation. For example, if deferred taxes have notbeen excluded a calculation of this indicator for the company leads to the results that are summarized in the second line of Table 1.Debt to capital ratio tends to get lower over time, due to the fact that part of the long-term financial liabilities is usually repaid over time. This coefficient gets a large share of attention, because a lot of contracts on lending, whether it’s the private company or a public corporation being financed, contain certain conditions that regulate the maximum share of company’s borrowed capital, which is expressed in terms of the debt to capital ratio.The same characteristics, but in a different ratio, are represented by the indicator of the debt to equity ratio. This indicator is directly related to the previous indicator and can be calculated, with the help of the previous indicator. Consider the following calculation:Let D be the amount of the long-term debt in the company, E – the size of company‘s equity, then DC –debt to capital ratio can be calculated by the following formula:DC = D / (D+E).If we now let, DE to denote debt to equity ratio, such as DE = D/E, then by simple algebraic manipulation, we obtain that:DE = DC / (1 – DC).The value of the debt to equity ratio for Company X is also summarized in Table 1.Using this indicator, one can easily interpret the condition of capital structure. A potential creditor, for example, can clearly see that on January 1st, 2005, company X long term debts are around 22 % of the size of the equity. If the company X has sufficiently high liquidity (that is the ability to repay its short term obligations), then it can be granted additional credit. Note, that if one only had the access to the first ratio considered (debt to assets ratio), it would not have been possible to make that conclusion, because there long-term debtswere not separated from the short-term ones.A number of other ratios can be considered, for example, the previous calculation of the debt to equity ratio can be modified to include current liabilities (short term debts) divided by the total equity of the company. This coefficient represents a yet another way to indicate relative shares in claims of creditors and owners and is also used to determine the dependency of the company on borrowed capital.If the values of this coefficient are significantly higher than the values of the previously described coefficients, then there’s a large share of the short term liabilities in the overall capital structure.Another possible coefficient used in financial ratio analysis is capital to asset ratio, which indicates the share of company’s equity in its assets. The existence of such a variety of coefficients serves to underscore how carefully the rules of financial analysis and conditions that regulate credit access are developed. However, coefficients only serve to provide the first overall idea of the risks and rewards that stem from the usage of the borrowed capital.On the third (also quantitatively oriented) stage of the analysis, the objective of the analyst is to assess the efficiency of capital utilization as a whole, as well as the efficiency of utilizing separate sources of capital. This stage also envisages a set of useful quantitative indicators, which can be calculated and analyzed. These indicators can include:• Capital intensity of production. This indicator aims to show the amount of capital necessary to produce one unit of firm’s output. It is mostly dependent on the natur e of firm’s output (for example, clothes vs. electronics manufacturing). Information about capital intensity is vital for planning firm’s capital requirements in the future.• Capital turnover period.This coefficient is the number of days, in which the company turns over capital that is capital, generates the projected amount of profit. This coefficient can be computed for equity, borrowed capital as well as the total capital of the company. Since every turnover of capital means generating a certain amount of profit, the lower the company manages to make capital turnover period, the more efficient is capital utilization.• Return on equity. This indicator characterizes the amount of earnings generated by a single unit of equity and is one of the most important pieces of information, necessary for decisions on optimizing capital structure.• Return on investment (total capital).This indicator is somewhat equivalent。

How Important is Financial Risk?IntroductionThe financial crisis of 2008 has brought significant attention to the effects of financial leverage。

There is no doubt that the high levels of debt financing by financial institutions and households significantly contributed to the crisis。

Indeed，evidence indicates that excessive leverage orchestrated by major global banks (e。

g。

, through the mortgage lending and collateralized debt obligations）and the so-called “shadow banking system” may be the underlying cau se of the recent economic and financial dislocation。

Less obvious is the role of financial leverage among nonfinancial firms. To date, problems in the U.S. non-financial sector have been minor compared to the distress in the financial sector despite the seizing of capital markets during the crisis。

For example，non-financial bankruptcies have been limited given that the economic decline is the largest since the great depression of the 1930s. In fact，bankruptcy filings of non-financial firms have occurred mostly in U.S。

外文翻译Determinants of Capital StructureMaterial Source: http://journal.fsv.cuni.cz Author:Patrik BAUER The modern theory of capital structure was established by Modigliani and Miller (1958). Thirty-seven years later, Rajan and Zingales (1995,p. 1421) stated: “Theory has clearly made some progress on the subject. We now understand the most important departures from the Modigliani and Miller assumptions that make capital structure relevant to a firm’s value. However, very little is known about the empirical relevance of the different theories.”Similarly, Harris and Raviv (1991, p. 299) in their survey of capital structure theories claimed: “The models surveyed have identified a large number of potential determinants of capital structure. The empirical work so far has not, however, sorted out which of these are important in various contexts.” Thus, several conditional theories of capital structure exist (none is universal), but very little is known about their empirical relevance. Moreover, the existing empirical evidence is based mainly on data from developed countries (G7 countries). Findings based on data from developing countries have not appeared until recently –for example Booth et al. (2001) or Huang and Song (2002). So far, no study has been published based on data from transition countries of Central and Eastern Europe, at least to the extent of this author’s knowledge. The main goal of this paper is to fill this gap, exploring the case of the Czech Republic.1.TheoreticalAccording to Myer s (2001,p.81), “there is no universal theory of the debtequity choice, and no reason to expect one”. However, there are several useful conditional theories, each of which helps to understand the debt-to-equity structure that firms choose. These theories can be divided into two groups –either they predict the existence of the optimal debt-equity ratio for each firm (so-called static trade-off models) or they declare that there is no well-defined target capital structure (pecking-order hypothesis).Static trade-off models understand the optimal capital structure as an optimal solution of a trade-off, for example the trade-off between a tax shield and the costs of financial distress in the case of trade-off theory. According to this theory the optimal capital structure is achieved when the marginal present value of the tax shield on additional debt is equal to the marginal present value of the costs of financial distress on additional debt. The trade-off between the benefits of signaling and the costs of financial distress in the case of signaling theory implies that acompany chooses debt ratio as a signal about its type. Therefore in the case of a good company the debt must be large enough to act as an incentive compatible signal, i.e., it does not pay off for a bad company to mimic it. In the case of agency theory the trade-off between agency costs4 stipulates that the optimal capital structure is achieved when agency costs are minimized. Finally, the trade-off between costs of financial distress and increase of efficiency in the case of free cash-flow theory, which is designed mainly for firms with extra-high free cash-flows, suggests that the high debt ratio disciplines managers to pay out cash instead of investing it below the cost of capital or wasting it on organizational inefficiencies. On the other hand, the pecking-order theory suggests that there is no optimal capital structure. Firms are supposed to prefer internal financing (retained earnings) to external funds. When internal cash-flow is not sufficient to finance capital expenditures, firms will borrow, rather than issue equity. Therefore there is no well-defined optimal leverage, because there are two kinds of equity, internal and external, one at the top of the pecking order and one at the bottom.Existing empirical evidence is based mainly on data from developed countries. For example Bradley et al. (1984), Kim and Sorensen (1986), Friend and Lang (1988), Titman and Wessels (1988) and Chaplinsky and Niehaus(1993) focus on United States companies; Kester (1986) compares United States and Japanese manufacturing corporations; Rajan and Zingales(1995) examine firms from G7 countries; and Wald (1999) uses data for G7 countries except Canada and Italy. Findings based on data from developing countries have appeared only in recent years, for example Booth et al. (2001) or Huang and Song (2002).2. Determinants of Capital Structure2.1 SizeFrom the theoretical point of view, the effect of size on leverage is ambiguous.As Rajan and Zingales (1995, p. 1451) claim: “Larger firms tend to be more diversified and fail less often, so size (computed as the logarithm of net sales) may be an inverse proxy for the probability of bankruptcy. If so, size should have a positive impact on the supply debt. However, size may also be a proxy for the information outside investors have, which should increase their preference for equity relative to debt.”Also empirical studies do not provide us with clear information. Some authors find a positive relation between size and leverage, for example Huang and Song (2002), Rajan and Zingales (1995)7 and Friend and Lang (1988). On the other hand,some studies report a negative relation, for example (Kester, 1986), (Kim – Sorensen, 1986) and (Titman – Wessels, 1988). Moreover, the results are very often weak as far as the level of statistical significance is concerned.2.2 ProfitabilityThere are no consistent theoretical predictions on the effects of profitability on leverage. From the point of view of the trade-off theory, more profitable companies should have higher leverage because they have more income to shield from taxes. The free cash-flow theory would suggest that more profitable companies should use more debt in order to discipline managers, to induce them to pay out cash instead of spending money on inefficient projects. However, from the point of view of the pecking-order theory, firms prefer internal financing to external. So more profitable companies have a lower need for external financing and therefore should have lower leverage.Most empirical studies observe a negative relationship between leverage and profitability, for example (Rajan – Zingales, 1995)8, (Huang – Song, 2002), (Booth et al., 2001), (Titman – Wessels, 1988), (Friend – Lang, 1988)and (Kester, 1986).2.3 TangibilityIt is assumed, from the theoretical point of view, that tangible assets can be used as collateral. Therefore higher tangibility lowers the risk of a creditor and increases the value of the assets in the case of bankruptcy. As Booth et al. (2001, p. 101) state: “The more tangible the firm’s assets, the greater its ability to issue secured debt and the less information revealed about future profits.” Thus a positive relation between tangibility and leverage is predicted.Several empirical studies confirm this suggestion, such as (Rajan –Zingales, 1995), (Friend – Lang, 1988) and (Titman – Wessels, 1988) find. On the other hand, for example Booth et al. (2001) and Huang and Song (2002) experience a negative relation between tangibility and leverage. In this study, tangibility is defined as tangible assets divided by total assets.2.4 Growth OpportunitiesAccording to Myers (1977), firms with high future growth opportunities should use more equity financing, because a higher leveraged company is more likely to pass up profitable investment opportunities. As Huang and Song (2002, p. 9) claim: “Such an investment effectively transfers wealth from stockholders to debt holders.” Therefore a negative relation between growth opportunities and leverage is predicted.Some empirical studies confirm the theoretical prediction, such as (Rajan–Zingales, 1995), (Kim – Sorensen, 1986) or (Titman – Wessels, 1988) report. However, for example, Kester (1986) and Huang and Song (2002) demonstrate apositive relation between growth opportunities and leverage.2.5 TaxAccording to the trade-off theory, a company with a higher tax rate should use more debt and therefore should have higher leverage, because it has more income to shield from taxes. However, for example Fama and French (1998) declare that debt has no net tax benefits. As MacKie-Mason (1990,p. 1471) claims: “Nearly everyone believes taxes must be important to financing decision, but little support has been found in empirical analysis.” As he also points out (MacKie-Mason, 1990, p. 1471): “This paper provides clear evidence of substantial tax effects on the choice between issuing debt or equity; most studies fail to find significant effects. [...] Other papers miss the fact that most tax shields have a negligible effect on the marginal tax rate for most firms. New predictions are strongly supported by an empirical analysis; the method is to study incremental financing decisions using discrete choice analysis. Previous researchers examined debt-equity ratios, but tests based on incremental decisions should have greater power.”As he adds, debt-equity ratios “are the cumulative result of years of separate decisions. Tests based on a single aggregate of different decisions are likely to have low power for effect s at the margin.” (MacKie-Mason, 1990,p. 1472).However, as data to perform similar analysis as (MacKie-Mason, 1990) is not available in the Czech Republic, the average tax rate defined as the difference between earnings before taxes and earnings after taxes, scaled by earnings before taxes, is used as a proxy variable to analyse the tax effects on leverage in this study.2.6 Non-debt Tax ShieldsOther items apart from interest expenses, which contribute to a decrease in tax payments, are labelled as non-debt tax shields (for example the tax deduction for depreciation). According to Angelo –Masulis(1980, p. 21): “Ceteris paribus, decreases in allowable investment-related tax shields (e.g., depreciation deductions or investment tax credits)due to changes in the corporate tax code or due to changes in inflation which reduce the real value of tax shields will increase the amount of debt that firms employ. In cross-sectional analysis, firms with lower investment related tax shields (holding before-tax earnings constant) will employ greater debt in their capital structures.” So they argue that non-debt tax shields are substitutes for a debt-related tax shield and therefore the relation between non-debt tax shields and leverage should be negative.Some empirical studies confirm the theoretical prediction, for example Kim and Sorensen (1986, p. 140) declare: “DEPR9 has a significantly negative coefficient. [...] This is consistent with the notion that depreciation is an effective tax shield, and thus offsets the ta x shield benefits of leverage.” A negative relation between non-debt tax shields and leverage is also found by (Huang – Song, 2002) and (Titman – Wessels, 1988). However, for example Bradley et al. (1984) and Chaplinsky and Niehaus(1993) observe a positive relationship between non-debt tax shields and leverage. Depreciation divided by total assets is used in order to proxy for non-debt tax shields in this study.2.7 V olatilityV olatility may be understood as a proxy for risk of a firm (probability of bankruptcy). Therefore it is assumed that volatility is negatively related to leverage. However, as Huang and Song (2002, p. 9) state based on findings of Hsia (1981): “As the variance of the value of the firm’s assets increases, the systematic risk of equity decreases. So the business risk is expected to be positively related to leverage.”The positive relation between volatility and leverage is confirmed by (Kim–Sorensen, 1986) and (Huang –Song, 2002). Conversely, a negative relation is found by (Bradley et al., 1984) and (Titman –Wessels, 1988).In this study, standard deviation of return on assets is used as a proxy for volatility.2.8 Industry ClassificationSome empirical studies identify a statistically significant relationship between industry classification and leverage, such as (Bradley et al., 1984),(Long –Malitz, 1985), and (Kester, 1986). As Harris and Raviv (1991, p. 333)claim, based on a survey of empirical studies: “Drugs, Instruments, Electronics, and Food have consistently low leverage while Paper, Textile Mill Products, Steel, Airlines, and Cement have consistently large leverage.”译文资本结构的决定因素资料来源:http://journal.fsv.cuni.cz作者：Patrik BAUER 现代资本结构理论的建立始于Modigliani和Miller（1958）。

The Determinants of Capital StructureXuefeng Li 1,a1 School of Economic and Management, Zhengzhou University of Light Industry,Zhengzhou, Henan, Chinaa lxf@Keywords: Capital structure; panel data; fixed effects modelAbstract. In this paper, we use new samples of Shanghai 180 index of China to investigate the determinants of capital structure. With the panel data of 102 listed companies over the span from 2004 to 2006, we analyze the factors which influence the capital structure of these companies. As in other countries, collateral value of asset, firm size, and reputation have positive and significant effects on leverage, profitability, liquidity, non-debt tax shields have negative and significant effects on leverage. Different from those in other countries, leverage in Chinese firms increases with growth opportunity. We also find that Chinese listed firms tend to depend on short-term debt financing.1. IntroductionSince the seminal works of Modigliani and Miller (1958, 1963) , there have been studies on capital structure of firns in such sectors as manufacturing, electriutility, non-profit hospital and agriculture firns. Modigliani and Miller (1958) argue on the basis of the very restrictive assumptions, such as, perfect capital markets, homogenous expectations, no taxes and no transaction costs, that, they draw a conclusion that capital structure is irrelevant to the value of a firm. The literature on capital structure has been expanded by many theoretical and empirical contributions. Much emphasis has been placed on releasing the assumptions made by Modigliani and Miller, in particular by taking into account corporate taxes (Modigliani and Miller, 1963), personal taxes (Miller, 1977), bankruptcy costs, agency costs (Jensen and Meckling, 1976; Myers,1977), and information asymmetries (Myers, 1984).Despite decades of intensive theoretical and empirical research after MM theory, there is a surprising lack of consensus as to what factors determine capital structure. The reason is that the capital structure is not only the company's own decision-making, but closely related to a country's cultural differences, the stage of economic development, the financial system and corporate governance mechanism (Rajan and Zingales (1995) and Wald (1999)).China is a developing country and the development of market economy is far from sufficient. As Chinese listed companies and the enterprises of mature market economies are at different levels of political, social and economic environment, facing different market structure, whether the choice of the capital structure of Chinese listed companies would be differences. The objective of this article is to carry out empirical testing, using panel data methodology, to investigate the determinants of the capital structure of Chinese listed companies.The paper is organized as follows. In Section 2, we provide literature review on the determinants of the capital structure and hypothesis. The method and data are presented in Section 3, while our results are discussed in Section 4. Finally, Section 5 contains some concluding remarks.2. Literature review and hypothesis2011 2nd International Conference on Management Science and Engineering Advances in Artificial Intelligence, Vol.1-6978-1-61275-994-4/10/$25.00 ©2011 IERI MSE2011The famous seminal paper by Modigliani and Miller (1958) set the stage for numerous propositions that have been developed to provide the theoretical underpinnings of this crucial concept. The linkage between capital structure and firm value has engaged the attention of both academics and practitioners. Bradley (1984), Rajan and Zingales (1995), Wald (1999), De Miguel and Pindado (2001) and others show that profitability, firm size, collateral value of assets, growth opportunities, non-debt tax shields an so on affect capital structure.2.1 ProfitabilityAlthough much theoretiacal work has been done since Modigliani and Miller (1958), no consistent predictions have been reached of the relationship between profitability and leverage. Pecking order theory suggests firms will use retained earnings first as investment funds and then move to bonds and new equity only if necessary. In this case, profitable firms tend to have less debt. Rajan and Zindales (1995), Wald (1999) show that leverage is negatively related to profitability. Agency-based models also give the same predictions. However, Long and Maltiz (1985) argue leverage would be positively related to profitability, but the relationship is not statistically significant. In this study, profitability will be defined as earnings before interest and tax (EBIT) scaled by equity (variable: ROE).2.2 LiquidityThe liquidity of the firm also has important effect on the leverage. According to the pecking order theory, firms with high liquidity will borrow less. The firm with more liquidity shows that it can generate abundant funds which can then use to finance its operating and investment activities. Therefore, the property fluidity can have the negative influence to the debt. In this paper, we proxy the liquidity of the firm considering its current ratio which is equal to current assets divided by current liabilities (variable: LIQU).2.3 Collateral value of assetsOn the relationship between collateral value of assets and leverage, theories generally state that collateral value of assets is positively related to capital structure. Trade-off theory suggests that companies use tangible assets as collateral to provide lenders with security in the event of financial distress. If an firm’s tangible assets occupy greater proportion of total assets, these assets can be used as collateral, so firm may more be debt financing. On the contrary, if an enterprise’s intangible assets are high, liabilities ratio will be smaller. Myers (1984), Rajan and Zindales (1995) make sure that collateral is positively correlated with leverage. This paper defines collateral value of assets as the ratio of inventory plus fixed assets to total assets (variable: CVOA).2.4 Non-debt tax shieldsThe tax deduction for depreciation and investment tax credits is called non-debt tax shields (NDTS). DeAngelo and Masulis (1980) maintain that depreciation and investment tax credits are substitutes for the tax benefits of debt financing. Thus, firms with large non-debt tax shields will be expected to issue less debt. Chaplinsky and Niehaus (1993) also find that leverage is negatively correlated with NDTS. While Bradley et al. (1984) find leverage is positively related with NDTS. In this study, we use depreciation scaled by total assets to measure non-debt tax shields (variable: NDTS).2.5 Firm sizeMany studies suggest there is a positive relation between leverage and size. Wald (1999) finds that large firms more often choose long-term debt, while small firms choose short-term debt.. Larger firms may be able to take advantage of economies of scale in issuing long-term debt, and may even have bargaining power over creditors. In the same circumstances, the possibility of bankruptcy for large firms is smaller than small ones, so the larger firms have a stronger capacity of debt and higher debt ratio. Rajan and Zingales (1995) generally find that larger firms are likely to use more debt. This study uses the natural logarithm of sales as a proxy for firm size (variable: SIZE).2.6 Growth opportunityTheoretical studies generally suggest growth opportunities are negatively related with leverage. On th one hand, if management pursues growth objectives, management and shareholder interests tend to coincide foe firms with strong investment opportunities. On the other hand, debt also has its own agency cost. According to the trade-off theory, firms holding future growth opportunity tend to borrow less than firms holding more tangible assets because growth opportunity cannot sever as collateral. Furthermore, according to the pecking order theory, firms expecting high future growth opportunity should use greater equity financing. Myers (1984) considers that high-growth firms may hold more real options for future investment than low-growth firms, so firms with high-growth opportunity may not issue debt in the first place and leverage is expected to be negatively related with growth opportunity. Berens and Cuny (1995) also find that growth opportunity implies significant equity financing and low leverage. Empirical studies such as Rajan and Zingales (1995), and Wald (1999) predominately support the trade-off theory. However, Ferdinand (1999) argues that when companies have relatively high growth opportunity, the need for capital is more and therefore companies are more inclined to take a higher debt ratio. In this paper, we proxy our growth opportunity measurement as total assets growth rate (variable: GROWTH).2.7 The reputation of a firmThe reputation of a firm may affect its leverage capability, because it reduces the conflicts between the company and its lenders. The longer the firm's history of repaying its debt, the better is its reputation, and the lower is its borrowing cost. The company’s reputation is a symbol of strength, if the company has good reputation, the company would occupy more debt. Jensen (1976) concludes that, by fulfilling its payment obligations, a company enjoys a good reputation, which may be sufficient to eliminate conflicts with its creditors. As Myers (1984) points out, the companies that are most concerned about having a reputation for being honest are those that expect to remain in the market for a long time. For them, honesty is the best policy. This study uses the natural logarithm of number of years since listed as a proxy for reputation (variable: REPU)Taking into account the review of the literature, the hypotheses that we propose about the possible determinants of the debt level of Chinese listed companies are as follows:H1. The stronger a company’s profitability, the less its tendency to resort to debt.H2. The higher the liquidity of a firm, the lower its debt level.H3. The larger the collateral values of asset, the lower the need to resort to external financing.H4. The greater the non-debt tax shields of a company, the lower its tendency to resort to debt.H5. The larger the size of a company, the more possibilities there are of obtaining debt financing.H6. The greater a firm’s growth opportunity, the lower its tendency to need external resources.H7. The better the reputation of a firm, the higher its debt level.3. Data and measurement of variablesIn this paper, a new sample we use is Shanghai 180 index shares. Shanghai 180 index shares were launched in 2002. Because of their strong representation, good income, low risk and high liquidity, they are increasingly becoming the capital market focus.We investigate the determinants of capital structure of Shanghai 180 index for the period from 2004 to 2006. All the companies included in the sample fulfill the following two criteria: they were all listed in the market before 2004 and none of them was expelled from Shanghai 180 index during the period 2004-2006. We form our variables using data derived from China Center for Economic Research (CCER) database. The final sample, after considering two criteria, consists of 102 listed firms.The different variables that allow us to test the stated hypotheses are: profitability, liquidity, collateral value of assets, non-debt tax shields, firm size, growth opportunity, and firm reputation. The dependent variable in the regression model is the ratio of leverage, defined as:assets Total debtTotal DAR =(1)The evolution of the leverage ratio for all the sample firms and its decomposition into short-term and long-term leverage are shown in Table 1. Table 1 Descriptive statisticsYear Leverage ratio （%） Short-term leverage （%）Long-term leverage （%）2004 43.56 33.55 10.01 2005 44.37 34.78 9.59 2006 45.48 36.51 8.97 From Table 1, we can see that the leverage ratio is gradually increased, from 43.56 percent in 2004 to 45.48 percent in 2006, and short-term leverage is also gradually increased, form 33.55 percent to 36.51 percent during the period from 2004 to 2006, but long-term leverage rate is gradually reduced, from 10.01 percent in 2004 to 8.97 percent in 2006. From 2004 to 2006, the proportion of short-term leverage accounts for 77 percent, 78 percent and 80 percent of total debt respectively. Short-term leverage rate is much higher than long-term debt rate, showing the Chinese listed companies mainly depend on short-term debt financing. This suggests that Chinese listed companies are mainly equity capital financed. The possible reason is that the bond market in china is very small and quite undeveloped. So, China should accelerate the development of the bond market in order to expand the financing channels of listed firms.Table 2 presents the exogenous variables for the level of debt.Table 2 Summary of determinants of capital structureVariable Sign DefinitionProfitability ROE EBIT/equityLiquidity LIQU current assets/current liabilityCollateral CVOA (inventory plus fixed assets)/total assetsNon-debt tax shields NDTS depreciation/total assetsFirm size SIZE LN (sales)Growth opportunities GROWTH total assets growth rateReputation REP LN (number of years since listed)4. Methodology and empirical evidenceThe described methodology is applied in our study with the purpose of estimating, by means of a balanced panel, the determinant factors of the leverage ratio, using as exogenous variables: profitability, liquidity, collateral value of assets, non-debt tax shields, firm size, growth opportunities, and reputation. We estimate the following model:ti t i t i t i t i t i t i t i i t i REP GROWTH SIZE NDTS CVOA LIQU ROE DAR ,,7,6,5,4,3,2,1,εβββββββα++++++++= (2) The descriptive statistics of the variables of the model are summarized in Table 3.Table 3 Descriptive statistics of leverage and independent variablesVariable Minimum Maximum Mean Std.Dev. DAR 0.023 0.871 0.446 0.173 ROE -0.371 0.516 0.139 0.118 LIQU 0.189 7.801 1.483 1.025 CVOA 0.125 0.926 0.583 0.195 NDTS 0.001 1.253 0.195 0.185 SIZE 19.561 27.675 22.160 1.316 GROW 0.684 9.193 1.642 0.845 REP 0.000 2.773 1.789 0.607In order to estimate the effect of the independent variables on the dependent and to improve our results, we consider the two different econometric approaches—fixed effects model and random effects model.The Hausman specification test is employed to test the fixed effects model versus the random effects model. Using Hausman specification test, we obtain the2χStatistic test value of 24.6, with an associated probability of 0 percent. This test result indicates that the fixed effects model fits better toour specific set of variables and thus prevails over the random effects model.The regression results using the fixed effects model are presented in Table 4.The results regarding our various hypotheses about leverage are as follows.H1 analyses the relationship between profitability and the dependent variable. We measure profitability as earning before interest and tax divided by equity. This variable is significant and negatively related to the endogenous variable. The negative and significant result is consistent withthe predictions of the pecking order theory, showing that firms prefer to use internal sources of funding when profits are high.Table 4 Regression results using the fixed effects modelt-Statistic Prob.Variable Coefficient-3.032 0.003C -0.198-3.481 0.001 ROE -0.032-15.801 0.000 LIQU -0.04016.841 0.000CVOA 0.151-15.269 0.000 NDTS -0.28211.311 0.000SIZE 0.028GROWTH 0.059 23.875 0.0003.837 0.000REP 0.012R2 0.893Adjusted R2 0.890F-statistic 299.993Prob.(F-statistic) 0.000H2 addresses the relationship between liquidity and the leverage. We consider the liquidity of thefirms using the current ratio which is equal to current assets divided by current liabilities. The estimated regression coefficient is negative and statistically significant. The result is consistent with pecking order theory, proving that firms with high liquidity tend to borrow less.H3 relates to the collateral value of corporate assets, which is measured as inventory plus fixed assets divided by total assets. The coefficient of this variable is significant and positively related to leverage. This result is accordant with Myers (1977), Titman and Wessels (1988), Rajan and Zindales(1995), which shows that tangible assets as debt collateral can decrease lender’s risk and thefirms with more tangible assets can require more debt.H4 considers the effect of non-debt tax shields on its leverage level. We define non-debt tax shields as depreciation divided by total assets. This variable is significant and inversely related to the leverage. The result confirms the findings of previous studies such as DeAngelo and Masulis (1980)and Chaplinsky and Niehaus (1993) which testifies that firms with high non-debt tax shields tend to require less debt.H5 addresses the influence of firm size and the level of debt, where size is defined as the natural logarithm of sales. Firm size has a positive and significant impact on leverage. This finding is consistent with Marsh (1982), Rajan and Zingales (1995), and Wald (1999), attesting that the size ofthe firms is a symbol of strength, the larger corporations have the greater debt secured capacity andthe less risks of bankruptcy, leading to a stronger ability in obtaining external financing.H6 analyses the relationship between growth opportunity and the dependent variable. We measure growth opportunity as total assets growth rate. A somewhat puzzling result is the positive relation between leverage and growth opportunity. The finding contradicts the previous prediction.According to Ferdinand (1999), a possible explanation is that firms with high growth opportunity employ more debt in their capital structure.H7 relates to the reputation of the company, which is measured as the natural logarithm of the number of years since listed. The coefficient of this variable is significant and positively related to leverage, which is consistent with Diamond (1989). The main reason is that Chinese listed companies are excellent performance of companies and the possibility of bankruptcy is smaller.5. SummaryIn this study, we conduct our analysis in order to investigate the determinants of the firm’s capital structure. We use the panel data derived by the financial statements of 102 Chinese listed firms which belong to shanghai 180 index shares for the period from 2004 to 2006.The results obtained using fixed effects model and random effects model suggest that the behavior of the sample throughout the study period is consistent with the fixed effects approach.The empirical results indicate that the more collateral value of asset, larger size, higher growth opportunity and best reputation of the corporations allow a greater level of debt. In contrast, inverse relationships exist between the level of debt and profitability, liquidity, and non-debt tax shields. We also find that Chinese listed firms tend to have much lower long-term debt and higher short- term leverage. The proportion of short-term leverage accounts for approximate 80 percent of leverage References[1] J. L.Berens, and C. L. Cuny: The capital structure puzzle revisited, Review of Financial Studies,Vol.8(1995), p. 1185.[2] M.Bradley, G.Jarrell, and E.Kim: On the existence of an optimal capital structure: theory andevidence, Journal of Finance, Vol.39(1984) No. 3, p.857.[3] S.Chaplinsky, and G.Niehaus: Do inside ownership and leverage share common determinants?,Quarterly Journal of Business and Economics ,Vol. 32(1993), p.51.[4] H.DeAngelo, and R. W.Masulis: Optimal capital structure under corporate and personal taxation,Journal of Financial Economics, Vol. 8(1980), p.3.[5] A.De Miguel, and J.Pindado: Determinants of capital structure: New evidence from Spanishpanel data, Journal of Corporate Finance,7(2001), p.77.[6] A.G.Ferdinand: Growth opportunities, capital structure and dividend policies in Japan, Journalof Corporate Finance, Vol. 5(1999), p.141.[7] M.Jensen, and W.Meckling: Theory of the firm: managerial behavior, agency costs andownership structure, Journal of Financial Economics, Vol. 3(1976), p. 305.[8] M.Long, and I. Maltiz: The investment-financing nexus: some empirical evidence, MidlandCorporate Finance Journal, 3(1985), P. 53.[9] ler: Debt and taxes, Journal of Finance, Vol. 32(1977), p. 261.[10] F. Modigliani, and ler: The cost of capital, corporate finance and the theory of investment,American Economic Review, Vol. 48(1958), p. 261.[11] F. Modigliani, and ler: Corporate income taxes and the cost of capital: a correction,American Economic Review, Vol. 53(1963), p. 443.[12] M.Jensen, and W.Meckling: Theory of the firm: managerial behavior, agency costs andownership structure, Journal of Financial Economics, Vol. 3(1976), p. 305.[13] S.C.Myers：The capital structure puzzle, Journal of Finance, Vol. 34 (1984), p. 575.[14] R.G.Rajan, and L.Zingales：What do we know about capital structure: some evidence frominternational data, Journal of Finance, Vol. 50(1995), p. 1421.[15] J. K.Wald: How firm characteristics affect capital structure: an international comparison, Journalof Financial Research, Vol. 22(1999), p.161.。

中文3677字外文翻译原文：Capital structure, dividend policy, and multinational: Theory versusempirical evidence3.1.Factors influencing capital structure and dividend policyIt is important to examine the factors that impact capital structure and dividend policy so that appropriate control variables can be included in the examination of the impact of multinational on capital structure and dividend policy. The list of these control variables must be based on extant theories and empirical evidence related to capital structure and dividend policy. Theories in these areas generally start with the well known results presented in Modigliani and Miller (1958) note that in an efficient markets world with no taxes or bankruptcy costs, the value of a firm is invariant to its capital structure. This theory has since been modified and extended so that capital structure does matter to include not only the impact of taxes and bankruptcy costs, but also the real world costs related to agency problems, asymmetric information, moral hazard, and other frictions and deviations from perfect markets.3.1.1. Operating leverage and other influencesThe operating leverage of a firm reflects its business risk. Firms with higher operating leverage face higher bankruptcy probabilities and should have lower financial leverage. However, higher operating leverage is generally associated with higher levels of fixed tangible assets — indeed the proportion of such assets is widely used in the literature as a measure of operating leverage. A firm's level of fixed assets should be associated positively with leverage as high levels of such assets can be used as collateral for loans (Friend & Lang, 1988; Long & Malitz, 1985). Jensen, Solberg, and Zorn (1992) provide empirical support for the positive impact on leverage of assets available for collateral. The non-debt tax shield variable is also important as firms with high levels of non-debt tax shields are expected to have lower debt levels (Kim & Sorensen, 1986). Due to institutional practices, herding among managers,bankers, and financiers, and their influence of firm risk, capital structure and dividend policy can also be expected to vary with firm size and industry classification.3.1.2. Trade-off theoriesIn the trade-off theory, capital structure decisions of firms depend on benefits and costs of using more debt. Less debt is used if the cost of bankruptcy is higher than the tax shield or other benefits of using debt (Kim & Sorensen, 1986; Graham, 2000). Therefore, the trade-off theory suggests a negative relationship between leverage and bankruptcy costs and a positive relationship between leverage and firm's marginal tax rate(Lasfer, 1995; Cloyd, Limberg, & Robinson, 1997). According to Rozeff (1982), riskier firms pay out lower dividends indicating a negative relationship between dividends, bankruptcy costs, and the amount of debt used by a firm.3.1.3. Impact of agency costsAvailability of free cash flow creates an agency problem since managers can use some of the free cash available for their own benefit, thereby decreasing the value of the firm (Jensen & Meckling, 1976). To protect against this managerial sub-optimal behavior, firms with higher level of cash flow should use higher leverage. The asymmetric information model of Ross (1977) also notes that there should be a positive relationship between use debt and the firm's profitability. Agency theory also indicates that firms with higher growth opportunities will hold less debt controlling for profitability and Stulz (1990)notes that due to the under-investment problem, firms with high growth opportunities should hold less debt. Chang (1992) contends that firms with high profitability use more debt in its capital structure controlling for investment opportunities.The agency issue in dividend payout decisions is similar to capital structure decisions in the presence of agency costs. In agency model of Jensen and Meckling (1976) and Jensen (1986), dividends and debt help control the agency costs of overinvestment if there are conflicts of interests between managers and stockholders. Thus, agency costs predict a positive relation between firm's free cash flow and payment of dividends. According to the signaling hypothesis of Ross (1977),firms with high profitability will also pay out more dividends as costly credible signals.However, firms with higher growth opportunities will pay out less dividends especially when there is an available alternative (debt) as a monitoring technique (Easterbrook, 1984).3.1.4. Pecking order theoryThe pecking order model (Myers & Majluf, 1984) contends that because of transaction costs and information asymmetry, firms finance new investments first with retained earnings, then successively with safe debt, risky debt and finally with equity. According to this pecking order model, more profitable firms should have lower leverage and lower short-term, but not long-term, payout controlling for investment opportunities. In a simple version of the pecking order model, firms with high investment and growth opportunities are predicted to have high leverage (on the condition that investment is more than the internal capital). In a more complex version of pecking order model, firms with high investment and growth opportunity will carry low leverage taking into consideration current as well as future financing costs. In contrast with the agency theory of free cash flow, Myers and Majluf (1984) predict that leverage decreases with the higher level of free cash flow. Pecking order theory also predicts that firms with high future growth opportunities should pay out lower dividends. Shyam-Sunder and Myers (1999) introduce a funding deficit model to test the pecking order hypothesis of firm's capital structure. They argue that, except for firms at or near their debt capacity, pecking order predicts that the deficits will be filled entirely with new debt issues. Therefore, we can expect a positive relationship between funding deficit and leverage assuming that the firms are still below their debt capacity.3.2.Interdependence between capital structure and dividend policyMany of the factors discussed above have been shown to influence not only capital structure but also dividend policy. Easterbrook (1984)documents that dividends exists because they induce firms to float new securities suggesting that firm's dividend decisions linked to firm's financing decisions. Intuitively, it is clear that the firm's payout ratio determines its retention ratio and, thus, its capital structure. Further, given the empirical evidence in support of the pecking order theory, corporatedebt levels should be related to the cash flows retained by a firm and to its dividend policy. Indeed, because of the interdependence between dividend policy and capital structure, empirical studies of capital structure, including those that focus on the impact of firm multinational, are most likely miss-specified unless they include an assessment of dividend policy.There is considerable evidence of this interdependence between dividends and capital structure. For example, consistent with the pecking order hypothesis, Adedeji (1998) suggests that if firms respond to earnings shortages by borrowing to pay dividends because of reluctance to cut dividends, financial leverage may have a positive relationship with dividend payout ratio, and a positive or negative relationship with investments depending on whether firms borrow to finance investments or postpone/reduce the investments. This hypothesized positive relationship between debt and dividend payout is empirically confirmed in Baskin (1989). Thus, according to pecking order hypothesis, corporate capital structure is positively related to its dividend policy.On the other hand, Jensen (1986) hypothesizes that dividends and debt are substitute mechanisms for controlling agency costs of free cash flows. Empirical finding of Agrawal and Jayaraman (1994) supports Jensen's hypothesis. They find that dividend payout ratios of a sample of all equity firms are significantly higher than those of a control group of levered firms. Jensen et al. (1992) posits that firms with high dividend payouts might find debt financing less attractive than equity financing leading to a negative relation between debt and dividends. As noted in the comprehensive survey on payout policy by Allen and Michaely (2002), firms also might not want to pay high dividends when they are obligated to pay high levels of other fixed finance charges.Thus, while the direction of the debt ratio–dividend policy relationship is not clear, it is clear that corporate capital structure is determined simultaneously with its dividend policy. Consequently, any examination of the impact of multinational on capital structure must account for the impact of dividend policy. Recognizing the endogenous nature of some of the variables being tested, some studies do usesimultaneous equation models to study the interdependence between capital structure and dividend payout ratios of U.S. firms. Noronha, Shome, and Morgan (1996) apply three-stage least squares (3SLS) tests to investigate the simultaneity between dividend and capital structure decisions of the U.S. firms for the period of 1986–1988 and find that the debt–dividend simultaneity is observed empirically only for the sub sample in which the monitoring rationale for dividends is appropriate. However, they do not examine the capital structure-dividend policy interdependence for multinational firms.As this brief review shows, capital structure and dividend policy are likely to be determined simultaneously in practice. A study of the relationship between capital structure and firm multinational must therefore include variables that determine both debt ratios and dividend payout ratios. Based on the theoretical and empirical evidences on capital structure and dividend policy, we enumerate the specific variables used here in estimating the relationship between debt, dividends, and firm multinational.3.3.Variables influencing capital structure and dividend policyBus Risk used as a measure of business risk, is calculated as the standard deviation of the ratio of the first difference of EBIT and the average total asset over the past five-years (as in Jensen et al., 1992).Beta is used as an alternative measure of firm risk as a determinant of dividend payout (as in Rozeff, 1982). The degree of operating leverage (DOL) is also used as a measure of business risk and is calculated as the average of the annual percentage change in EBIT divided by the percentage change in sales. Tax Rate (Tax Rate) is used as measure of tax benefits from the interest payments.Agency and under-investment problems indicate that firms with higher growth opportunities (measured by the market-to-book ratio, MTB) will hold less debt controlling for profitability. In addition, Chang (1992) predicts that firms with high profitability (ROA) use more debt in its capital structure controlling for investment opportunities. Firm's uniqueness (UNQ) in term of R&D and advertising expenses ratio proxies also for agency cost because the external stakeholders faces larger costs of monitoring when the more of the investment is in intangibles as such investmentslead to under investment problems and agency costs (Long & Malitz, 1985). Funding deficit (FundDef) is a measure of agency costs. According to Shyam-Sunder and Myers (1999), the funding deficit is:FundDef t = DIV t + X t + ΔW t + R t−C t :Where,C t operating cash flow, after interest and taxesDIV t dividend paymentsX t capital expendituresΔW t net increase in working capitalR t current portion of long-term debtThe agency issue in dividend payout decisions is similar to capital structure decisions in the presence of agency costs. Agency costs predict a positive relation between firm's free cash flow(FreeCFLS) and payment of dividends. According to signaling hypothesis of Ross (1977), firms with high profitability (ROA) will pay out more dividends as costly credible signals. Firms with higher growth opportunities (SalesGR) will pay out lower dividends especially when there is an alternative for using dividend payout as monitoring technique as suggested by Easterbrook (1984). Firm's past five year's sales growth is used for the dividend payout regression (as in Rozeff, 1982).Return on Assets (ROA) is another important variable. Pecking order theory indicates more profitable firms (ROA) should have lower leverage and lower payout controlling for investment opportunities and firms with high future growth opportunity should pay out lower dividends. Highly profitable firms can also use high dividends and high debt levels as signals for the good performance of the company (Ross, 1977). A firm's level of fixed assets (COL) should be associated with higher leverage as high levels of such assets can be used as collateral for loans (Friend & Lang, 1988; Long & Malitz, 1985). Such a measure of assets available for collateral is also used in Jensen etal. (1992). The non-debt tax shield variable (NDTS) is also used in the regression of capital structure determinants as firms with high availability of non-debt tax shield are expected to have lower debt levels (Kim & Sorensen, 1986).Jensen etal. (1992), Noronha etal. (1996), Kwok and Reeb (2000), and Bathala, Moon, and Rao (1994) also take into account NDTS as a determinant of leverage. As Graham (2000) notes, firm size has a negative influence on debt ratios. The natural log of total asset (Lsize) is the measure of firm size. Industry dummies are also added to control for variations across industries.Thus, we have the following variables:(a) Dependent variables:Leverage [Leverage=LTD/(LTD+MVE)]DivPO [dividend payout ratio](b) Independent variables:Fsale (foreign sales ratio as a measure of degree of multinational)M (distinguishing MNCs from DCs and =1 if Fsale > 20% and =0,otherwise)BusRisk: business riskBeta: firm's market beta a measure of equity market riskDOL: degree of operating leverageROA, Return on Assets as a measure of ProfitabilityMTB, market-to-book ratio, as a measure of growth opportunitiesSalesGR, growth rate of the firm, geometric average past 5-yr sales growth rate FreeCFLS, free cash flow divided by total salesCOL, assets that can be used as collateral, measured as PP&E/Total assetsUNQ, uniqueness, measured as (R&D + Adver. Exp)/ total salesNDTS, non-debt tax shields, (Depreciation +Amortization)/Sales× Tax rateFundDef, funding deficitLsize, natural log of total sales as a measure of size.Source: Aggarwal, Raj Kyaw, NyoNyo Aung,2010.―Capital structure, dividend policy, and multinational: Theory versus empirical evidence‖.International Review of Financial Analysis. Vol.19, No.2, January,pp.140-150.译文：资本结构，股利政策，跨国经营：理论与实证研究3.1影响资本结构和股利政策的因素我们更应该注意资本结构,股利政策的影响因素,以便适当的控制变量减少跨国资本结构和股利政策的冲击。

本科毕业论文（设计）外文翻译原文：The Determinants of Capital Structure:Evidence from Chinese ListedCompaniesOne early extension was to allow for the incidence of taxation and financial distress. Since the late 1970s, there have been two new strands of research which originate more from the theory of the firm: the …pecking order‟theory and the …trade-off‟ theory. The pecking order theory argues that firms have a preference of issuing financing instruments due to adverse selection problems (Myers and Majluf, 1984). T he theory suggests that the financial manager tends to use internal capital as the first choice, then issue debt, and equity will only be considered as the last resort as issuance of equity can be perceived by the market as a signal of a poor future for the investment. In contrast, the trade-offtheory emphasizes that an optimal capital structure can be achieved by the trade-offof the various benefits of debt and equity.2.1. The pecking order theoryThe pecking order theory is based on the information asymmetries between the firm‟s managers and the outside investors. Ross (1977) was the first to address the function of debt as a signalling mechanism when there are information asymmetries between the firm‟s management and its investors.He argued that management has better knowledge of the firm than the investors, and that management will try to avoid debt when the firm is performing poorly for fear that any debt default due to poor cash flow will result in their job loss. The information asymmetry may also explain why existing investors may not favor new equity financing, as new investors may require higher returns to compensate for the risks of their investment thus diluting the returns to existing investors. Myers and Majluf (1984) later developed their so-called peckingorder theory of financing: i.e.that capital structure will be driven by firms‟ desire to finance new investments preferably through the use of internal funds, then with low-risk debt, and with new equity only as a last resort. In their theory, there is no optimal capital structure that maximiz es the firm value. The financial managers issue debt or equity purely according to the costs of capital. Subsequent empirical studies provide mixed evidence. Helwege and Liang (1996) found no empirical evidence for such a pecking order. Booth et al. (2001) found evidence supporting the theory in their 10-country empirical study. Frank and Goyal (2003) tested the pecking order theory on a broad cross-section of publicly traded American firms for 1971 to 1998, and concluded that the theory was not supported by the evidence. Whilst large firms exhibited some aspects of pecking order behavior, the evidence was not robust to the inclusion of conventional leverage factors, nor to the analysis of evidence from the 1990s.2.2. The trade-off theoryThe trade-offtheory argues that there is an optimal capital structure that maximiz es the firm value, but the trade-off comes in various forms.2.2.1. TaxShield Benefits and the Financial Distress Cost of DebtOne of the crucial assumptions of the MM (1958) model was that there is no taxation. Later work by Modigliani and Miller (1963), and Miller (1977) add tax effects into the original framework. An implication of this newer work was that firms should finance their projects completely through d ebt in order to maximize corporate value. Clearly this contradicts reality in that debt constitutes only a fraction of firms‟ total capital. Subsequent theoretical work seeks an optimal capital structure which results from a trade-offbetween the benefits of tax shield of debt and the costs of financial distress of debt.According to this line of theory, the benefits of debt arise from its tax exemption, which implies that a higher debt ratio will increase the firm‟s value. But the benefits can be offset by costs o f financial distress, which may destroy the value of the firm. Thus the optimal capital structure is determined by the trade-offbetween the tax-free benefits of debt and the distress costs of debt - see Figure 1. De Angelo and Masulis (1980), Ross (1985) and Leland (1994) have shown that, in the presence of taxation, it is advantageous for a firm with safe, tangible assets and plenty of taxable income to take a high debt-equity ratio to avoid high tax payments. For a firm with poorer performance and more intangi ble assets, it is better to rely on equity financing.One problem with the theories based on consideration of the tax-shield benefits is that they cannot explain why capital structures vary across firms that are subject to the same taxation rates. Empirical evidence from the United States (Copeland and Weston, 1992) shows that the capital structure of corporations did not change much after corporate income tax came into existence. In Australia, where there is no dual income taxation at all, capital structure is roughly the same as in other economies (Rajan and Zingales, 1995). Booth et al. (2001) found that the tax benefits vary in developing countries and play no role in the determination of capital structure choice.2.2.2. Agency Theory and Capital StructureEven if markets are perfect and there is no tax impact, agency theory suggests that the appropriate mix of debt and equity is still an important matter for corporate governance. In general, debt claims provide the holders with a fixed repayment schedule but little in the way of rights to control the company, as long as the repayment schedule (and sometimes certain other terms) is met. However, creditors can have a strong influence over a company if it gets in financial distress but, even if a company is financia lly sound, creditors can influence whether it can obtain additional funding for proposed new projects. For example, a bank that has loaned a company the money for factory expansion can make it easy or hard for the company to borrow more money for a new office building.Conversely, equity claims – in particular, common stock – give shareholders the right to vote for Boards of Directors and on other important corporate issues such as major mergers or plans that would dispose of substantial portions of the compan y‟s assets. Shareholders are also entitled to receive dividends or other distributionswhenever the company pays them or, if the company is liquidated, to receive the net assets of the company after paying all debts and any securities, such as preferred stock, that rank ahead of common shares. These two features, the right to vote and the right to receive dividends and other distributions, are the defining characteristics of common shares.Jensen and Meckling (1976) identify two potential sources of conflict.On the one hand, conflicts between debt-holders and equity-holders arise because the debt contract gives equity-holders an incentive to invest sub-optimally. More specifically the debt contract provides that, if an investment yields large returns well above the face value of the debt, equity-holders will capture most of the gain. If, however, the investment fails, debt-holders bear the consequences because of limited liability. As a result, equity-holders may benefit from …going for broke‟; i.e. investing in very risky projects, even if they are value-decreasing. Such investments result in a decrease in the value of the debt. The loss in value of the equity from the poor investment can be more than offset by the gain in equity value captured at the expense of debt-holders. Equity-holders correctly anticipate equity-holders‟ future behavior. In this case, the debt-holders receive less for the debt than they otherwise would. Thus, the cost of the incentive to invest in value-decreasing projects created by debt is borne by the equity-holders who issue the debt. This effect, generally called the asset substitution effect, is the agency cost of debt financing.On the other hand, conflicts between shareholders and managers arise because managers hold less than 100% of the residual claim. Consequently, they do not bear the entire cost of these activities. Managers may thus invest less effort in managing the firm‟s resources, and may be able to transfer firm resources to their own personal benefit, for example through …empire-building‟ or by consuming …perquisites‟ such as corporate jets, luxurious offices etc.The manager bears the entire cost of refraining from these activities, but captures only a fraction of the gain. As a result, managers overindulge in these pursuits relative to the level that wou ld maximize firm value. This in effciency is reduced the larger isthe fraction of the firm‟s equity owned by the manager. Holding constant the manager‟s absolute investment in the firm, an increase in the debt ratio of the firm increases the manager‟s share of the equity and mitigates the loss from the conflict between the manager and shareholders. Moreover, as pointed out by Jensen (1986), since debt commits the firm to pay out cash, it reduces the amount of …free‟ cash available to managers to engage in the types of pursuits mentioned above. This mitigation of the conflicts between managers and equity-holders constitutes a benefit of debt financing.A number of implications follow from this analysis. First, one wouldexpect bond contracts to include features that attempt to prevent asset substitution, such as interest coverage requirements, prohibitions against investments in new unrelated lines of business, etc. Second, industries in which the opportunities for asset substitution are more limited will have higher debt levels ceteris paribus. Thus, for example, the theory predicts that regulated public utilities, banks, and firms in mature industries with few growth opportunities will be more highly leveraged. Third, it is optimal for firms with slow or even negative growth, and that have large free cash in flows from operations, to have more debt. Large free cash flows without good investment prospects create the resources to consume perquisites, build empires, overpay subordinates etc. Increasing debt reduces the amount of …free cash‟ and increases the manager‟s fractional ownership of the residual claim. According to Jensen (1986) industries with these characteristics include steel, chemicals, brewing, tobacco, television and radio broadcasting, and wood and paper products. The theory predicts that these industries should be characterized by high leverage ratios.2.2.3. Corporate ControlOne limitation of agency theory is that it assumes the agency problem can be mitigated, or eliminated, by a comprehensive contract which postulates all the future contingencies and states the circumstances in which the manager should take what action, as criticised by Hart (1995a, 1995b). But such a comprehensive contract would be very costly to design and/or execute(Williamson, 1988). It may well be optimal to leave the contract incomplete, and to assign the equity-holders the residual controlrights beyond contractual control rights which are assigned to the debt-holders (Aghion and Bolton, 1992). This incomplete contract approach regards equity and debt as contingent state‟ securities. When the firm is financially healthy, it is the equity-holders who have control. But a default of debt repayment will trigger the transfer of control to the debt-holders. Li quidation of the firm and/or managerial sackings are then inevitable. Thus management is constrained by the requirement to ensure a smooth repayment of debt (see table I).Two related models share a common concern with conflicts between shareholders and managers, though they diff er in the specific ways in which the conflicts arise and in the role of debt. Harris and Raviv (1990) postulate that managers always want to continue the firm‟s current operations, even if liquidation of the firm would be the preferred option for investors. But debt can force managers to liquidate firms, because default may well trigger the managers‟ job loss. The optimal capital structure is achieved by trading off improved liquidation decisions against higher investigation costs. A different model by Stulz (1990) is based on the assumption that managers always want to invest available funds so as to expand the size of the firm, even though investors might prefer higher dividend payouts. The optimal capital structure in Stulz‟s model is achi eved by trading off the benefits of debt in preventing investment in bad projects with the costs of debt in preventing investment in good projects. Therefore, unlike in the Modigliani-Miller world, changing the capital structure of the firm changes the alloc ation of power between the insiders and the outside investors, and thus almost surely changes the firm‟s investment policy (La Porta et al., 2000).Source: Jian Chen and Roger Strange, 2006.“conomic Change and Restructuring”. Volume 38, January. pp:11-35译文：资本结构决定因素—以中国企业为案例为应对税收与财务困境的金融压力，早期理论作了相应的扩展。