DETERMINANTS OF CAPITAL STRUCTURE IN BUSINESS START‐UPS: THE ROLE OF NONFINANCIAL STAKEHOLDER RELATIONSHIP COSTS

According to the finance literature, nonfinancial stakeholders (NFS), such as customers, suppliers, and employees, take into account their expected liquidation costs when dealing with a firm. In this framework, firms can influence their probability of liquidation by choosing an appropriate capital structure. Also, the literature suggests NFS bargaining power may affect firm financing decisions. In the current article we investigate these ideas for initial financing decisions by business start‐ups, where ex ante failure risk is high and NFS must decide whether to make relationship‐specific investments. We find that start‐ups imposing larger costs on their NFS following liquidation significantly reduce leverage. This effect is strengthened when suppliers have greater bargaining power. We also document a marginally negative effect of NFS liquidation costs on the proportion of bank loans. Finally, business start‐ups rely less on bank loans when customers and suppliers are in a powerful bargaining position.     

DETERMINANTS OF CAPITAL STRUCTURE IN THE UK RETAIL INDUSTRY: A COMPARISON OF MULTIPLE REGRESSION AND GENERALIZED REGRESSION NEURAL NETWORK

Firms need to rely on different financing sources, but the question is how capital structure is determined for a particular industry. Our aim is to undertake an investigation into the factors which determine capital structure in the UK retail industry. Our initial sample consists of 163 (final sample: 100) UK retail companies, using data from 2000 in order to analyse capital structure from 2002 to 2006. Nonlinear models tend to be unduly neglected in capital structure research, and so we apply generalized regression neural networks (GRNNs), which are compared with conventional multiple regressions. We utilize a hold‐out sample for the multiple regressions to make them comparable with the GRNNs. Stability of the data is also confirmed. Our main findings are: net profitability and the depreciation‐to‐sales ratio are key determinants of capital structure based on GRNNs, while two more variables are added in the multiple regressions, namely size and quick ratio; there is strong support for the pecking‐order theory; both root‐mean‐square errors and mean absolute errors are much lower for the GRNNs than those for the multiple regressions for overall, training and testing datasets. The potential benefit of this research to financial managers and investors in the UK retail sector is the identification of the overriding role of net profitability in reducing the financial risk from high levels of gearing. Copyright © 2012 John Wiley & Sons, Ltd.     

EFFECTS OF INFLATION ON CAPITAL STRUCTURE

The purpose of this study is to examine the aggregate capital structure based on several factors that affect the demand for and supply of corporate debt. The main hypotheses are that under inflation the larger the amount of depreciation and the larger the yield differences between corporate and municipal bonds and between corporate bonds and equities, the larger the amount of corporate debt. The empirical tests performed in this study support these hypotheses.     

A MULTIPERIOD MEAN-VARIANCE MODEL OF OPTIMAL CAPITAL STRUCTURE

The continuing interest in the capital structure issue among financial researchers is evidenced by the stream of capital structure models that have appeared in the literature. Much of this research has used a risk-neutral and/or a single-period framework. In this paper, we develop a capital structure model for multiperiod firms and allow for the firm's cash flows to grow over time, for the firm to issue new debt, and for two types of bankruptcy costs to occur. The types of bankruptcy costs that occur are determined by the firm's uncertain operating cash flows and negotiations between the firm and creditors. Risk is priced via the Sharpe-Lintner capital asset pricing model. Multiperiod risk-priced models, we argue, realistically represent actual firms and are thus an important step toward the development of more testable and usable models of capital structure. We execute a demonstration example in which the value of the levered firm achieves a maximum and discuss the steps the firm would take to maximize shareholder wealth within this example. The example illustrates that the value of the firm passes through an interior optimum as the promised debt payment is increased. A simulation of the effect of changes in firm-specific parameters shows that the model exhibits expected and appealing relationships between these parameters and the value of the levered firm.     

THE BALANCED CAPITAL STRUCTURE

At leading companies, financial executives are becoming business partners rather than just scorekeepers. In this environment, capital structure can be a source of competitive advantage, and financial strategy issues are critical: Should your company buy back shares or issue stock, grow internally or join the M & A boom, issue fixed-rate debt or stay floating? These decisions must be addressed one company at a time, balancing the competing priorities of cost, risk, and flexibility. The most important issue, target leverage, depends on the company's desired risk profile, growth plans, and debt cost considerations. But market conditions are also very important: Can the company access the equity market? How will a repurchase announcement be interpreted? Market conditions also affect the raising of debt capital. Rather than maintaining a constant mix of fixed- to floating-rate debt, companies should shift the mix during high- or low-yield environments. Many other financing issues will effectively be decided by market convention. For example, meeting a company's needs with respect to seniority, maturity structure, call flexibility, and financial covenants is often accomplished simply by choosing the market that most closely matches the firm's cost and risk preferences.     

ALL-EQUITY FIRMS AND THE BALANCING THEORY OF CAPITAL STRUCTURE

Despite the benefits of leverage, many firms exist that at some point in their corporate history had no debt. This study provides evidence that the balancing theory of capital structure can predict the behavior of such firms. All-equity firms allow a more precise measurement of firm market value and risk, and provide a less ambiguous relationship between independent variables and dependent variables than the firms used in previous studies. Using a logit function to avoid spurious correlation between the dependent and independent variables, we find that for most years during 1964–88 all-equity firms listed in the Compustat industrial file exhibited a consistently significant negative relationship between the Myers growth option variable and the probability of borrowing. Positively significant but less consistent relationships exist between the risk measures and the nondebt tax shields, and the probability of borrowing. These results do not qualitatively change when the data are aggregated over twenty years or over five-year subperiods. The tests are also conducted by industry according to the one-digit Standard Industrial Classification (SIC) code. Significant relationships are found in the 2000 and 3000 SIC code manufacturing industries.     

TOWARD A MORE COMPLETE MODEL OF OPTIMAL CAPITAL STRUCTURE

Most corporate finance practitioners understand the trade-off involved in making effective use of debt capacity while safeguarding the firm's ability to execute its business strategy without disruption. But quantifying that trade-off to arrive at an optimal level of debt can be a complicated and challenging task. This paper develops a simulation model of capital structure that starts by generating multiple estimates of market rates (LIBOR, currency rates) and corresponding company operating cash flows. To arrive at an optimal capital structure, the model then incorporates the shareholder value effects of alternative financing decisions by directly measuring the costs of financial distress, including the costs of missed investment opportunities and higher working capital requirements.
The model generates both a target credit rating and a lower fallback rating that permits a higher level of debt to maintain investments and dividends when operating cash flows are weak. As the model shows, companies with volatile cash flows and significant investment opportunities can add substantial shareholder value by establishing a fallback credit rating that is one or two notches below the target rating. The model also optimizes the mix of fixed versus floating debt, the maturity structure, and the currency composition. Another distinctive feature of the model is its ability to estimate the expected cost of alternative liability structures that can provide the liquidity insurance necessary to sustain the firm through periods of severe stress. This cost turns out to be quite small relative to the total market capitalization of the average firm.     

AN EMPIRICAL MODEL OF CAPITAL STRUCTURE: SOME NEW EVIDENCE

Using a general autoregressive distributed lag model, we estimate the longrun steady state determinants of corporate capital structure. We find that, in the long run, the leverage ratio is related positively to the corporate tax rate and firm size and negatively to future growth opportunities and stock returns. By contrast, there appears to be no relation between leverage and the corporate tax rate on a short-run year to year basis. Our results suggest that prior empirical evidence on capital structure is of questionable value precisely because of its failure to clearly separate the short-run relationship between leverage and its determinants from its long-run relationship.     

利用外资、引进技术与优化产业结构

当前我国现代化进程已跨上了一个新的发展平台,进入一个关键的历史性转折时期.在这一转折时期,我国在利用外资引进技术方面应作出一番重新思考与定位.本文分析了我国近20年来经济增长的支撑点及我国未来将面临着的资源约束等方面的压力,探讨了国际上新一轮的产业结构调整及经济全球化等对我国的影响,指出了利用外资、引进技术以产业结构优化为主要目标是我国目前利用外资引进技术工作的必然的战略选择;同时提出了在实现这一战略选择过程中须处理好的几个主要问题:优化利用外资引进技术的结构、建立和完善企业和国家的技术创新体系、改变对国内幼稚产业的保护方式等.     

THE EFFECTS OF COMPLEX CAPITAL STRUCTURE ON THE MARKET VALUES OF FIRMS

The familiar Modigliani and Miller risk class model is the basis of a test for differences in value between simple and complex capital structure groups of firms. Cluster analysis, using market risk measures and debt-equity ratio as input, provides the method for obtaining the risk class sample of firms. Crosssectional tests at three annual dates are made on twenty-six simple and twentysix complex capital structure firms. For all periods examined, the complex capital structure firms are valued lower than the simple capital structure firms. Possible explanations for the results include failure of the arbitrage mechanism and the presence of certain costs associated with different types of capital structures.