關(guān)于公司特征如何影響資產(chǎn)結(jié)構(gòu)的實證研究外文翻譯

1、關(guān)于公司特征如何影響資產(chǎn)結(jié)構(gòu)的實證研究外文翻譯 外文題目: How firm characteristics affect capital structure:an empirical study出 處: Managerial Finance作 者:Nikolaos Eriotis原文: How firm characteristics affect capital structure: an empirical study By Nikolaos EriotisIntroduction The various financing decisions are vital for the fin

2、ancial welfare of the firm. A false decision about the capital structure may lead to financial distress and eventually to bankruptcy. The management of a firm sets its capital structure in a way that firms value is imized. However, firms do choose different financial leverage levels in their effort

3、to attain an optimal capital structure. Although theoretical and empirical research suggests that there is an optimal capital structure, there is no specified methodology, yet, that financial managers can use in order to achieve an optimal debt level. However, financial theory does provide some help

4、 in understanding how the chosen financing mix affects the firms value. This paper shed some light on the determinants of the capital structure of the major Greek firms listed on the Athens Stock Exchange ASE. We examine the cross sectional variation in leverage among the Greek firms for the time pe

5、riod 1997-2001. We include variables that are based on different capital structure theories and have never been investigated for the Greek market before, such as the interest coverage ratio and the quick ratio. We also differentiate the firms that heavily use debt capital i.e. a debt ratio more than

6、 50 per cent using a dummy variable. Thus, the conclusions of this paper are expected to enlighten the darksome scientific area of the capital structure determination for the Greek firms. The paper is organized as follows. In the next session, we review some of the theoretical and empirical literatu

7、re concerning the determinants and effects of leverage. In section 3, we describe our data and we justify the choice of the variables used in our analysis. The fourth section presents the result of the empirical analysis and a discussion of the conclusions that can be derived from the results. Final

8、ly, we summarize our findings in the last section.Theoretical backgroundModigliani and Miller 1958 were the pioneers in theoretically examining and algebraically demonstrating the effect of capital structure on firm value. Assuming perfect capital markets, they concluded to the broadly known theory

9、of capital structure irrelevance which means that the capital structure that a firm chooses does not affect its value. Thereafter, many researchers, including Modigliani and Miller, examined the effects of less restrictive assumptions on the relationship between capital structure and the firms value

10、. For example, Modigliani and Miller 1963 took taxation under consideration and they proposed that firms should employ as much debt capital as possible in order to achieve the optimal capital structure. Along with corporate taxation, researchers were also interested in analyzing the case of personal

11、 taxes imposed on individuals. Miller 1977 discerns three tax rates in the tax legislation of the USA that determine the total value of the firm. These are the corporate tax rate, the tax rate imposed on the income of the dividends and the tax rate imposed on the income of interest inflows. Accordin

12、g to Miller, the value of the firm depends on the relative height of each tax rate, compared with the other two.Data and measurement of variables In this paper, we investigate the determinants of capital structure for the firms listed in the ASE market during the period 1997-2001. All the companies

13、included in the sample fulfill the following two criteria; they were all listed in the market in 1996 and none of them was expelled during the period 1997-2001. These criteria were imposed to ensure that the capital structure was not distorted by the effects of a recent official listing. We form our

14、 variables using data derived from the financial statements contained in the ASE database. The final sample, after considering any missing data, consists of 129 firms. This figure represents the 63 per cent of the listed companies on the ASE in 1996. Thus, our sample consists of a significant propor

15、tion of the listed firms in the ASE during the five-year-period 1997-2001. Our dependent variable is the debt ratio variable: DRi,t which is defined as the ratio of total debt divided by the total assets of the firm. Total debt contains both long-term and short-term liabilities. Although the strict

16、notion of capital structure refers exclusively to long-term leverage, we have decided to include short-term debt as well, mainly because Greek firms use either very little ? less than 10 per cent ? or no long-term capital. Banks in Greece are hesitant in providing long-term financing with attractive

17、 terms. Therefore, Greek firms turn to short-term borrowing even when financing their long-term investments. That is why we also consider short-term financing as a measure of gearingThe model In order to combine cross-sectional with time series data and formulate the characteristics of the market, w

18、e use pooling methods for our panel data. The models for panel data are powerful research instruments, which give the researcher the ability to take in to account any kind of effect that the cross-sectional data may have, and finally to estimate the appropriate empirical model. A general model for p

19、anel data that allows the researcher to empirically estimate the relation between dependent and independent variables with great flexibility and formulate the differences in the behavior of the cross-section elements is theoretically as follows5: where yit is the dependent variable, xi the matrix wi

20、th the independent variables and zi a matrix which contains a constant term and/or a set of individual or group specific variables depending on the sample, which may be observed or unobserved.Empirical resultsIn order to estimate the effect of the independent variables on the dependent and to improv

21、e our results we consider the three different econometric approaches presented in the previous section. Under the hypothesis that there are no group or individual effects among the firms included in our sample we estimate the total model. The results are presented in Table I. The diagnostics provide

22、 us with useful results concerning the theoretical model presented in equation 1. All the variables proved to be significant in confidence level of 5 per cent. The power of the model is given by the high F-statistic of 1,352.4. According to adjusted R2 the independent variables explain the 92 per ce

23、nt of the size in the debt ratio. In the analysis of panel data, where cross-section combined with time series data, there might be cross-section effects on each firm or on a set of groups of firms. There are two procedures to deal with those effects and each of them has already presented in the beg

24、inning of section 4. These two approaches are the random and the fixed effects models for panel data. The case where all the effects are uncorrelated with the regressors and can be formulated as constant terms for each individual or group of firms in the known matrix z, is presented in Table II. The

25、 diagnostics from the random effects model suggest that the variable of growth is not statistically significant and does not affect the debt ratio. The adjusted R2 is lower than that of the total model at 83.5 per cent. In random effects model there are three assumptions about the cross-section effe

26、cts. The first is that there exist group or individual effects, the second that those effects are uncorrelated with the independent variables and the third that the effects can be formulated. The case where the major assumption about the effects does not hold i.e. there are no effects has already pr

27、esented in Table I. The next step is to stay consistent with the major assumption, there are effects, and relax the last two restrictions concerning them. The results from the fixed effect model are presented in Table III. According to Table III all the independent variables of our model are statist

28、ically significant at 5 per cent. The F-statistic proves the high explanatory power of the estimated model and the high R2 adjusted indicates that the estimated model explain the 97.2 per cent of the size in the dependent variable. According to our findings there is a contradictory result concerning

29、 the variable of growth. The total and the fixed effects model accept this variable but the random effects model does not. These controversial results indicate that further analysis has to be done. As we mention in section 4 the random effects model assumes that the individual effects are uncorrelat

30、ed with the independent variables. In consequence, the random effects model may suffer from inconsistency as a result of omitted variables, something that does not happen with the fixed effects model. On the other hand, the fixed effects model uses the individual effects as given by the sample. In o

31、rder to see if the individual effects are uncorrelated with the regressors we perform a Hausman test. The test statistic is 565.3 and the critical value of the chi?square table with five degrees of freedom, at 95 per cent, is 11.7, which is lower than the tests value. Hence, the hypothesis that the

32、individual effects are uncorrelated with the regressors can be rejected. The random effects model estimates suffer from inconsistency probably due to omitted variables see section 4. Hence, according to our sample and findings, the appropriate model to explain the market is the one that includes the

33、 GROWTH variable. According to our findings the SIZE of the firm has a positive relation with the debt ratio, something that has been confirmed by Marsh 1982 and Bennett and Donnelly 1993, which found similar results with us. This suggests that larger firms use more debt. The short-term leverage cov

34、erage is an indication of the liquidity of the firm. As we expected there is a negative relation between the debt ratio of the firm and its liquidity. The negative relation confirms that firms finance their activities following the financing pattern implied by the pecking order theory. As we expecte

35、d the negative relation between debt and growth has been confirmed from our data. The statistical significance of the dummy variable and its positive sign indicate that there is a distinction in the capital structure between firms who have debt ratio greater than 50 per cent and those that do not ha

36、ve. According to our results from the fixed effects model these firms use, compared to the market, an extra debt of 19 per cent.Conclusions In this study, we conduct our analysis in order to investigate how some specific firm characteristics determine the firms capital structure. We use the panel da

37、ta derived by the financial statements of 129 Greek firms listed in the ASE. In our calculations we consider the total model, the fixed effects model and the random effects model. Our dependent variable is the debt ratio expressed as total liabilities divided by total assets. The debt ratio includes

38、 both long-term and short-term liabilities mainly because Greek firms use either very little or no long-term debt capital at all. According to the results, the debt ratio of the firm is positively related to its size which is measured by the sales figure. Thus, larger firms employ more debt capital

39、in comparison with smaller firms, a finding which is consistent with the theoretical background mentioned in the second section of the paper. On the other hand, our findings show that the liquidity of the firm is negatively related to its financial leverage. We consider the liquidity of the firms us

40、ing the quick, or acid test ratio which is equal to current assets minus inventories divided by current liabilities. This ratio shows the ability of the firm to deal with its short-term liabilities. Firms with high liquidity tend to use less debt. This finding can be considered as an indication that

41、 firms generally finance their activities following the financing procedure implied by the pecking order theory. Firms with high liquidity maintain a relatively high amount of current assets, which means that they maintain high cash inflows. This means that they also generate high cash inflows. As a

42、 consequence, they are able to use these inflows in order to finance their operating and financing activities. Thus, they do not use much debt capital in comparison with firms that are not so profitable because they prefer to use these funds rather than debt capital; this is an indication of pecking

43、 order financing. This finding is further supported by the result of the negative relation between the interest coverage ratio of the firms and their capital structure. The interest coverage ratio is expressed as net income before taxes divided by interest payments. Thus, firms that maintain a relat

44、ively high interest coverage ratio prefer to use less debt capital. If a firm has a high interest coverage ratio, this means that it has the ability to generate relatively high earnings. The negative relation implies that firms probably prefer to use these earnings to finance their activities and th

45、us use less debt capital; this is also an implication of the pecking order financing. The negative relation between the growth of the firm and its capital structure shows that firms with high growth potential employ less debt in their capital structure. We proxy our growth measurement as the annual

46、change on earnings. Thus, high growth means high variation in earnings which can be interpreted as higher risk. Firms that are risky generally find it difficult to raise debt capital, simply because the lenders will demand higher returns making debt capital more expensive. According to the results o

47、f the dummy variable, we find strong evidence that there is a capital structure differentiation among the firms which heavily use debt capital more than 50 per cent of their total assets and those that use less debt capital. The results and conclusions are consistent with the theoretical background

48、as presented in the second section of the present paper. All the three models conclude in the same remarks except for the situation of the growth variable. The growth variable is not statistically significant in the random effects model, but it is in the other two models. However, the Hausman test i

49、ndicates that the fixed effects model fits better toour specific set of variables and thus prevails over the random effects model. Thus, growth does affect the determination of capital structure.外文題目:How firm characteristics affect capital structure:an empirical study出 處: Managerial Finance作 者: Niko

50、laos Eriotis譯文: 關(guān)于公司特征如何影響資產(chǎn)結(jié)構(gòu)的實證研究簡介 多樣化融資決策對公司的金融福利是至關(guān)重要的。有關(guān)資本結(jié)構(gòu)的錯誤決定可能會導(dǎo)致公司財務(wù)危機(jī)最終破產(chǎn)。企業(yè)的管理是對資本結(jié)構(gòu)進(jìn)行設(shè)置,使得公司的價值最大化。然而,不同的企業(yè)選擇不同的財務(wù)杠桿水平,都是為了達(dá)到最優(yōu)的資本結(jié)構(gòu)。雖然理論和實證研究表明,有一種最優(yōu)的資本結(jié)構(gòu)存在,但卻沒有專門的優(yōu)化方法。但是,財務(wù)管理者能夠以達(dá)到最優(yōu)的債務(wù)水平。然而,金融理論的確提供一些幫助了解選擇融資組合影響公司價值使其最大化的方法。 本文透露一些在希臘雅典上市公司證券交易所ASE上市公司的資本結(jié)構(gòu)的影響因素問題。我們選取了截面數(shù)據(jù)變化在1997-2001.之間。我們將變量, 在希臘市場,根據(jù)不同的資本結(jié)構(gòu)理論進(jìn)行,如興趣覆蓋率和快捷的比率。我們也將分化嚴(yán)重的公司用債務(wù)資本即負(fù)債比率超過50%虛擬變量的使用。因此,本文的結(jié)論將啟示有關(guān)科學(xué)領(lǐng)域一些希臘公司的資本結(jié)構(gòu)確定。 摘要組織如下。 在接下來的一節(jié),我們回顧一下理論和實證文獻(xiàn)和影響因素杠桿作用。在第三節(jié)中,將描述我們的數(shù)據(jù)資料,證明了用于我們分析的選擇變量。 第四部分提供了實證分析的結(jié)果并提出從結(jié)論中提取出的具體的結(jié)果。 最后,我們總結(jié)我們的發(fā)現(xiàn),對比過去