1、外 文 翻 译原文:Capital Structure and Debt StructureIn this study, we provide a number of new insights into capital structure decisions by recognizing that firms simultaneously use different types, sources, and priorities of debt. These insights are based on a novel data set that records the type, source,
2、 and priority of every balance sheet debt instrument for a large sample of rated public firms. The data are collected directly from financial footnotes in firms annual 10-K filings and supplemented with information on pricing and covenants from three origination based datasets: Reuters LPCs Dealscan
3、, Mergents Fixed Income Securities Database, and Thomsons SDC Platinum. To our knowledge, this data set is one of the most comprehensive sources of information on the debt structure of a sample of public firms: It contains the detailed composition of the stock of corporate debt on the balance sheet,
4、 which goes far beyond what is available from origination-based datasets alone.We begin by showing the importance of recognizing debt heterogeneity in capital structure studies. We classify debt into bank debt, straight bond debt, convertible bond debt, program debt (such as commercial paper), mortg
5、age debt, and all other debt. For almost 70% of firm-year observations in our sample, balance sheet debt comprises significant amounts of at least two of these types. Even more striking is the fact that 25% of the observations in our sample experience no significant one-year change in their total de
6、bt but significantly adjust the underlying composition of their debt. Studies that treat corporate debt as uniform have ignored this heterogeneity, presumably in the interest of building more tractable theory models or due to a previous lack of data.In this section, we motivate our empirical analysi
7、s of the relation between debt structure and credit quality by examining hypotheses from the theoretical literature on debt composition and priority.The first group of theories hypothesizes that firms should move from bank debt to non-bank debt as credit quality improves (Diamond, 1991; Chemmamur an
8、d Fulghieri, 1994; Boot and Thakor, 1997;Bolton and Freixas, 2000). The seminal article is Diamonds (1991b) model of reputation acquisition. In his model, firms graduate from bank debt to arms length debt by establishing a reputation for high earnings. More specifically, the main variable that gener
9、ates cross-sectional predictions is the ex-ante probability that a firm is a bad type with a bad project; this ex-ante probability is updated over periods based on earnings performance, and is interpreted as a credit rating. Bad firms have a lower history of earnings, and a higher probability of sel
10、ecting a bad project in the future. High quality firms borrow directly from arms length lenders and avoid additional costs of bank debt associated with monitoring,medium-quality firms borrow from banks that provide incentives from monitoring, and the lowest qualityfirms are rationed.The model by Bol
11、ton and Freixas (2000) explores the optimal mix of bonds, bank debt, and equity. The key distinction between bonds and bank debt is the monitoring ability of banks. If current returns are low and default is pending, banks can investigate the borrowers future profitability, whereas bond holders alway
12、s liquidate the borrower. In their model, high quality firms do not value the ability of banks to investigate, and therefore rely primarily on arms length debt. Lower quality borrowers value theability to investigate by the bank, and thus rely more heavily on bank financing.Two main hypotheses emerg
13、e from this kind of model. First, the lender with monitoring duties (the bank) should be the most senior in the capital structure. The intuition is as follows: a banks incentive to monitor is maximized when the bank appropriates the full return from its monitoring effort. In the presence of senior o
14、r pari passu non-monitoring lenders, the bank is forced to share the return to monitoring with other creditors, which reduces the banks incentive to monitor.Second, the presence of junior non-bank creditors enhances the senior banks incentive tomonitor. This result follows from the somewhat counteri
15、ntuitive argument that a bank has a strongerincentive to monitor if its claim is smaller. Park (2000) describes this intuition as follows: if the project continues, an impaired senior lender will get less than a sole lender simply because his claim is smaller. On the other hand, if the project is li
16、quidated, an impaired senior lender will get the same amount as a sole lender, the liquidation value. Given its lower value in the going concern, a bank with a smaller claim actually has a stronger incentive to monitor and liquidate the firm. The presence of junior debt reduces the size of the banks
17、 claim, which increases the amount of socially beneficial monitoring.The intuition of this latter result is evident if one considers a bank creditor with a claim that represents a very large fraction of the borrowers capital structure. In such a situation, the bank has less of an incentive to liquid
18、ate a risky borrower, given that the banks large claim benefits relatively more from risk-taking than a smaller claim. In other words, a large bank claim is more “equity-like” than a small bank claim given its upside potential. As a result, reducing the size of the senior bank claim by addingjunior
19、debt improves the banks incentive to detect risk-shifting. Alternatively, by holding a small stake in the firm, bank lenders are able to credibly threaten borrowers with liquidation, which makes their monitoring more powerful in reducing managerial value-decreasing behavior.There are at least two wa
20、ys, however, in which the existing theories do not map into our empirical design. First, theories such as Diamond (1993), Besanko and Kanatas (1993), and Park (2000) derive a priority structure as the optimal contract under incentive conflicts, but they do not explicitly derive the comparative stati
21、c of how optimal priority structure should vary across a continuum of incentive conflict severity. A thought experiment close to this is provided by DeMarzo and Fishman (2007), who do examine the comparative statics of debt structure with respect to liquidation values,managerial patience, and manage
22、rial private benefits. However, their predictions are about the mix between long-term debt and lines of credit, rather than priority structure per se.Second, with the exception of DeMarzo and Fishman (2007) and some other recent dynamic contracting work, these theories are static in nature, and ther
23、efore do not predict how debt structure should change with respect to the evolution of stochastic cash flows. In this sense, the theory is more relevant for our random sample cross-sectional results more than our panel results on fallen angels.Indeed, Diamond (1993), Besanko and Kanatas (1993), and
24、Park (2000) are ex-ante models in which moral hazard explains the existence of priority structure; however, they do not consider dynamic deterioration in the firms credit quality. In DeMarzo and Fishman (2007), agents draw down on credit lines when cash flows are insufficient to pay debt coupons. Ho
25、wever, there are no dynamic models to our knowledge that derive both an increase in secured and subordinated debt as a percentage of total debt, i.e. the spreading of the debt structure that we find as credit quality deteriorates.Figure 1 presents our first main result on the relation between credit
26、 quality and debt structure:firms lower in the credit quality distribution spread the priority structure of their debt obligations. While investment grade firms rely uniquely on senior unsecured debt and equity, speculative grade firms rely on a combination of secured bank debt, senior unsecured deb
27、t, subordinated convertibles and bonds, and equity.Table 4 presents estimates of these patterns in a regression context. In Panel A, the left hand side variables are the debt priority class amounts scaled by total debt. The omitted credit quality group is firms rated A or better. As the coefficients
28、 show, speculative grade firms have a much higher fraction of their debt in secured and subordinated obligations. The magnitude is economically significant: secured and subordinated debt as a fraction of total debt is more than 50% higher for firms with a B rating than for firms with a rating of A o
29、r better.In Panel B, the left hand side variable for each regression is the debt priority class amount scaled by total capitalization.: lower credit quality firms use a substantially higher fraction of secured and subordinated debt in their capital structure. Once again, the magnitudes are striking:
30、 the combination of secured and subordinated debt as a fraction of total capital structure is higher by more than 40% for B-rated firms compared to firms rated A or higher. Meanwhile, senior unsecured debt actually decreases in the capital structure despite the fact that total debt increases. Natura
31、lly the decrease in senior unsecured is smaller when scaled by total capitalization than by total debt. This reflects the fact that lower credit quality firms use more total debt and less equity. In other words, as firms move down the credit quality distribution, they replace senior unsecured debt a
32、nd equity with secured bank debt and subordinated debt. This finding is also evident in Panel A of Figure in the introduction.Using a novel data set on the debt structure of a large sample of rated public firms, we show that debt heterogeneity is a first order aspect of firm capital structure. The m
33、ajority of firms in our sample simultaneously use bank and non-bank debt, and we show that a unique focus on leverage ratios misses important variation in security issuance decisions. Furthermore, cross-sectional correlations between traditional determinants of capital structure (such as profitabili
34、ty) and different debt types are heterogeneous. These findings suggest that an understanding of corporate capital structure necessitates an understanding of how and why firms use multiple types, sources, and priorities of corporate debt.We then examine debt structure across the credit quality distri
35、bution. We show that firms of lower credit quality have substantially more spreading in their priority structure, using a multi-tiered debt structure often consisting of both secured and subordinated debt issues. We corroborate these results in a separately collected dataset for firms that experienc
36、e a drop in credit quality from investment grade to speculative grade. Here too, firms spread their priority structure as they worsen in credit quality. The spreading of the capital structure as credit quality deteriorates is therefore both a cross-sectional and within-firm phenomenon. The increased
37、 secured debt used by lower quality firms is generally secured bank debt, whereas the increased subordinated debt is in the form of bonds and convertibles.The spreading of the capital structure as credit quality deteriorates is broadly consistent with models such as Park (2000) that view the existen
38、ce of priority structure as the optimal solution to manager-creditor incentive problems. However, to our knowledge, the existing models do not exactly deliver the dynamics that we find. For example, they do not derive differential priority structures as a function of a continuum of either moral haza
39、rd severity or creditor quality types. Further, these models do not explain why non-bank issues after a firm is downgraded must be subordinated to existing non-bank debt or convertible to equity. Theoretical research suggests that the use of convertibles can mitigate risk shifting by making the secu
40、ritys value less sensitive to the volatility of cash flows (Brennan and Schwartz, 1988) or by overcoming the asymmetric information problem in equity issuance (Stein, 1992).Future research could aim to integrate these ideas about convertible debt into a conceptual framework that links debt structure
41、 and capital structure.We close by highlighting two other avenues for future research. First, our findings suggest that recognition of debt heterogeneity might prove useful in examining the effect of financing on invest mentor the importance of adjustment costs in capital structure studies. Indeed,
42、we have shown that firms frequently adjust their debt structure even when total debt remains relatively stable. This latter fact suggests that adjustment costs are not as large as an examination of total debt implies. An important question related to the adjustment cost literature is whether firms h
43、ave debt composition targets, and if so how that effects the literatures estimates of the speed of adjustment to targets. To address this question would require a longer panel of data than we have available in our sample.Second, we hypothesize that our findings with regard to fallen angels may help
44、explain the difference between bank and non-bank debt recovery rates in bankruptcy (Hamilton and Carty, 1999;Carey and Gordy, 2007). According to Standard & Poors, bank debt recovery rates are 75% whereas senior unsecured bonds recover only 37%. Our findings suggest that one can perhaps trace the ba
45、nk debt recovery premium to the moment when firms move from investment grade to speculative grade debt ratings. It is at this point that banks become secured and increase the use of control-oriented covenants,both of which are likely to increase recovery rates in the event of bankruptcy.Source: Josh
46、ua D. Rauh,Amir Sufi,2010,“Capital Structure and Debt Structure”. Review of Financial Studies,vol.23,no.12, December.PP.4242-4280译文:资本结构和债务结构在这个研究中,我们提供大量的资本结构决策的新见解,认识到公司同时使用不同的债务类型、来源和优先债务。这些观点基于一个数据集,数据集中的债券来源于每一个大样本的公共公司。收集数据直接从公司10年文档中的金融脚注和来源定价和契约基础的信息:路透社LPC分析的固定收益债券数据库。据我们所知该数据集是其中一有个最全面的信息来
47、源的债务融资结构的公共公司,在资产负债表中它包含详细的组成公司债务的股票,远远超过了基础数据单独提高的信息。首先,我们认识到债务资本结构中的异质性研究的重要性表现。我们的债务包括银行债务、直债券债务、可转换债券债务、程序债务(如商业票据)、抵押债务和所有其它债务。我们的样本中有近70%公司年度报表,至少大量包含资产债务表和债务法。更令人惊讶的事实是,观察中有25%的样品没有一年改变他们的全部债务而是明显调整基本组成的欠债。研究表明,治理公司债务忽略了这个异质性,想必在建设更适合的理论模型或由于对以前的数据缺乏兴趣。在本节中,们鼓励通过检查从债务构成和优先的理论文献假设我们之间的债务结构和信贷质
48、量关系的实证分析。第一组理论推测,企业应该从银行债务的非银行债务的信用质量得到改善(黛蒙德,1990;谢姆努尔和法拉,1994;布特和撒克,1997;博尔顿和弗雷克萨斯,2000)。黛蒙德(1991)写的文章具有开创性,他的模型中,企业从银行债务的公平债务毕一直获得高收入而建立了声誉。更确切的说,主要变量是公司可能有一个坏的项目的可能性。这个事前概率出现,改变了以盈利为基础的评级而改用信用评级。坏的公司有一个较低的历史收益,更有可能在未来选择一个坏的项目。高质量的公司直接从公平债权人那获得借款避免支付与监测有关的额外债务费用;中等质量的公司从银行获得借款,最低质量的公司则是被配给。由博尔顿和弗
49、雷克萨斯(2000)提供的模型探讨了债券、银行债务和股权的最佳组合。债券和银行之间的债务主要区别在于银行的监控能力。如果当前的回报很低默认等待,银行可以调查借款人的未来盈利能力,但是债券持有者总是清算借款人资产。在他们的模型中高质量公司不需要值银行调查盈利能力,因此主要依靠长期债务。质量差的借款人注重银行调查,从而在很大程度上依靠银行贷款。两个主要假设摆脱这种模式。首先,拥有监测贷款人的职责(银行)的债务人的资本是资本结构最多的。直觉是:当银行激励监控最大时,银行使用了所有监测的努力。现存的高级或同等地位的非监控贷款,银行被迫分享监测权给其他债权人,从而降低了银行激励监控监测的回报。第二,初级非银行债权人的存在提高了银行高级的激励监视。当银行回报少时有强烈的动力去监督这一结果有点违反常理。帕克(2000)描述这他的研究成果:如果该项目继续,受损的高级贷款人获得将比只有公司只有一个债权人的少,因为他的索取权小了。在另一方面,如果项目被清算,受损的高级贷款人将作为唯一的贷款人得到同样数额清偿价值。鉴于其较低的持续经营价值,银行有较强的激励来监测公司清算。该次级债务的存在降低了银行的要求,还增加了社会的有益监测。