Prior work on leverage implicitly assumes capital availability depends solely on firm characteristics. However, market frictions that make capital structure relevant may also be associated with a firm’s source of capital. Examining this intuition, we find firms that have access to the public bond markets, as measured by having a debt rating, have significantly more leverage. Although firms with a rating are fundamen-tally different, these differences do not explain our findings. Even after controlling for firm characteristics that determine observed capital structure, and instrumenting for the possible endogeneity of having a rating, firms with access have 35 % more debt. Under the tradeoff theory of capital structure, firms determine their preferred leverage ratio by calculating the tax advantages, costs of financial distress, mispricing, and incentive effects of debt versus equity. The empirical literature has searched for evidence that firms choose their capital structure, as this theory predicts, by estimating firm leverage as a function of firm characteristics. Firms for whom the tax shields of debt are greater, the costs of financial distress lower, and the mispricing of debt relative to equity more favorable are expected to be more highly levered. When these firms discover that the net benefit of debt is positive, they will move toward their preferred capital structure by issuing additional debt and/or reducing their equity. The implicit assumption has been that a firm’s leverage is completely a function of a firm’s demand for debt. In

We empirically examine the trade-off theory of capital structure, allowing for costly adjustment. After confirming that financing behavior is consistent with the presence of adjustment costs, we use a dynamic duration model to show that firms behave as though adhering to a dynamic trade-off policy in which they actively rebalance their leverage to stay within an optimal range. We find that firms respond to changes in their equity value, due to price shocks or equity issuances, by adjusting their leverage over the two to four years following the change. The presence of adjustment costs, however, often prevents this response from occurring immediately, resulting in shocks to leverage that have a persistent effect. Our evidence suggests that this persistence is more likely a result of optimizing behavior in the presence of adjustment costs, as opposed to market timing or indifference.

If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Long-horizon return forecasts give the same strong evidence. These tests exploit the negative correlation of return forecasts with dividend-yield autocorrelation across samples, together with sensible upper bounds on dividend-yield autocorrelation, to deliver more powerful statistics. I reconcile my findings with the literature that finds poor power in long-horizon return forecasts, and with the literature that notes the poor out-of-sample R2 of return-forecasting regressions. (JEL G12, G14, C22) Are stock returns predictable? Table 1 presents regressions of the real and excess value-weighted stock return on its dividend-price ratio, in annual data. In contrast to the simple random walk view, stock returns do seem predictable. Similar or stronger forecasts result from many variations of the variables and data sets. Economic significance

Abstract not found

This paper provides empirical evidence of a strong causal relation between the structure of managerial compensation and investment policy, debt policy, and firm risk. Controlling for CEO pay-performance sensitivity (delta) and the feedback effects of firm policy and risk on the structure of the managerial compensation scheme, we find that higher sensitivity of CEO wealth to stock volatility (vega) implements riskier policy choices, including relatively more investment in R&D, less investment in property, plant and equipment, more focus on fewer lines of business, and higher leverage. At the same time, we find that riskier policy choices in general lead to compensation structure with higher vega and lower delta. Stock-return volatility, however, has a positive effect on both vega and delta. 1

Discount-rate variation is the central organizing question of current asset-pricing research. I survey facts, theories, and applications. Previously, we thought returns were unpredictable, with variation in price-dividend ratios due to variation in expected cashflows. Now it seems all price-dividend variation corresponds to discount-rate variation. We also thought that the cross-section of expected returns came from the CAPM. Now we have a zoo of new factors. I categorize discount-rate theories based on central ingredients and data sources. Incorporating discount-rate variation affects finance applications, including portfolio theory, accounting, cost of capital, capital structure, compensation, and macroeconomics. ASSET PRICES SHOULD EQUAL expected discounted cashflows. Forty years ago, Eugene Fama (1970) argued that the expected part, “testing market efficiency,” provided the framework for organizing asset-pricing research in that era. I argue that the “discounted ” part better organizes our research today. I start with facts: how discount rates vary over time and across assets. I turn

Abstract not found

An investment factor, long in low-investment stocks and short in high-investment stocks, helps explain the new issues puzzle. Adding the investment factor into standard factor regressions reduces the SEO underperformance by about 75%, the IPO underperformance by 80%, the underperformance following convertible debt offerings by 50%, and Daniel and Titman’s (2006) composite issuance effect by 40%. The reason is that issuers invest more than nonissuers, and the investment factor earns a significantly positive average return of 0.57 % per month. Equity and debt issuers underperform matching nonissuers with similar char-acteristics in the post-issue years (e.g., Ritter, 1991; Loughran and Ritter, 1995; and Spiess and Affleck-Graves, 1995, 1999). We explore empirically the investment-based hypothesis of this underperformance. The q-theory of investment and the real options theory imply a negative relation between real investment and expected returns. If the proceeds from equity and debt issues are used to finance investment, then issuers should invest more and earn lower

This paper develops a model in the spirit of Hennessy and Whited (2005) in which the capital structure dynamics associated with transitory debt fully explain the long-horizon leverage paths documented by Lemmon, Roberts, and Zender (2008). The model shows how and why debt serves as a transitory financing vehicle to meet the funding needs associated with random shocks to investment opportunities. It yields a variety of new testable predictions about the time paths of leverage and the link between investment and capital structure dynamics. Although these dynamics also reflect financing frictions, predictable variation in capital structure primarily reflects the attributes of firms ’ investment opportunities–e.g., the volatility and serial correlation of investment shocks, the marginal profitability of investment, and the nature of capital stock adjustment costs–with the linkage between investment attributes and leverage dynamics reflecting firms ’ usage of transitory debt.

This paper studies the effect of top managers on corporate financing decisions. Differences among CEOs account for a great deal of the variation in leverage among firms. After a CEO is forced out, leverage typically declines. Firms that offer higher pay-for-performance to the top executives, adjust leverage to target more rapidly. CEO personal characteristics are not closely connected to corporate leverage choices. To some extent the CEO may be serving as a proxy for an entire management team. The CFO seems to play at least as important a role as the CEO in determining corporate leverage. JEL classification: G32