Testing static tradeoff against pecking order models of capital structure1

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Abstract

This paper tests traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater time-series explanatory power than a static tradeoff model, which predicts that each firm adjusts gradually toward an optimal debt ratio. We show that our tests have the power to reject the pecking order against alternative tradeoff hypotheses. The statistical power of some usual tests of the tradeoff model is virtually nil.

Introduction

The theory of capital structure has been dominated by the search for optimal capital structure. Optimums normally require a tradeoff, for example between the tax advantages of borrowed money and the costs of financial distress when the firm finds it has borrowed too much. A value-maximizing firm would equate benefit and cost at the margin, and operate at the top of the curve in Fig. 1. The curve would top out at relatively high debt ratios for safe, profitable firms with plenty of taxes to shield and assets whose values would escape serious damage in financial distress. This static tradeoff theory quickly translates to empirical hypotheses. For example, it predicts reversion of the actual debt ratio towards a target or optimum, and it predicts a cross-sectional relation between average debt ratios and asset risk, profitability, tax status and asset type.

The empirical literature seems to confirm these two predictions. However, none of these papers has systematically compared the explanatory power of their fitted equations with alternative explanations of financing behavior, and none has checked whether their equations could seem to work even when actual financing is driven by other forces. That is, they have not checked the statistical power of their tests against alternative hypotheses.

We propose an alternative time-series hypothesis based on the pecking order theory of optimal capital structure. In the pecking order theory, there is no well-defined optimal debt ratio. The attraction of interest tax shields and the threat of financial distress are assumed second-order. Debt ratios change when there is an imbalance of internal cash flow, net of dividends, and real investment opportunities. Highly profitable firms with limited investment opportunities work down to low debt ratios. Firms whose investment opportunities outrun internally generated funds borrow more and more. Changes in debt ratios are driven by the need for external funds, not by any attempt to reach an optimal capital structure.

We find that a simple pecking order model explains much more of the time-series variance in actual debt ratios than a target adjustment model based on the static tradeoff theory. Moreover, we show that the pecking order hypothesis can be rejected if actual financing follows the target-adjustment specification. On the other hand, this specification of the static tradeoff hypothesis will appear to work when financing follows the pecking order. This false positive results from time patterns of capital expenditures and operating income, which create mean-reverting debt ratios even under the pecking order. Thus we have power to reject the pecking order but not the static tradeoff specification. We conclude that the pecking order is a much better first-cut explanation of the debt-equity choice, at least for the mature, public firms in our sample. We question the evidence for a well-defined optimal debt ratio as predicted by the tradeoff theory.

We claim two contributions for this paper. The first is methodological, that is our procedures for testing the statistical power of alternative hypotheses about financing behavior. The second is empirical, based on the excellent performance of a simple, time-series pecking order model, at least for our sample of mature, public companies, and the weak performance of target-adjustment models derived from the static tradeoff theory.

We do not claim that the simple pecking order is the whole story, and we concede that more elaborate tradeoff specifications may work better. Actual financing decisions reflect many motives, forces and constraints. However, elaborate models have their own dangers, because variables may proxy for several different effects. A positive t-statistic, against a null hypothesis of a zero coefficient, proves nothing, unless statistical power is demonstrated.

There is evidence in favor of the static tradeoff and optimal capital structure. Several authors, such as Schwartz and Aronson (1967), have documented evidence of strong industry effects in debt ratios, which they interpret as evidence of optimal ratios. Long and Malitz (1985)show that leverage ratios are negatively related to research and development expenditures, which they use as a proxy for intangible assets. Smith and Watts (1992)also document a negative relation between growth opportunities and debt ratios. Mackie-Mason (1990)reports evidence that firms with tax loss carry forwards are less likely to issue debt. This conclusion is consistent with Miller and Modigliani (1966), who detected the positive effects of interest tax shields in the market values of electric utilities.

Bradley et al. (1984)give an excellent review and synthesis of some of the earlier theoretical and empirical literature on optimal capital structure, and conclude that their findings `support the modern balancing [tradeoff] theory of capital structure'. More recently, however, Titman and Wessels (1988), using a latent variables approach, have found only mixed evidence for the role of the factors predicted by the static tradeoff theory.

Other studies provide more direct evidence that firms adjust toward a target debt ratio. Taggart (1977), Marsh (1982), Auerbach (1985), Jalilvand and Harris (1984)and Opler and Titman (1994)find mean reversion in debt ratios or evidence that firms appear to adjust toward debt targets. Marsh (1982), using a logit model, finds that the probabilities of debt and equity issues vary with the deviation of the current debt ratio from the target, which he estimates as the observed average over his sample period. Opler and Titman (1994), who also use a logit model but estimate the target by a cross-sectional model, come to broadly similar conclusions. Taggart (1977)and Jalilvand and Harris (1984)estimate target-adjustment models and find significant adjustment coefficients, which they interpret as evidence that firms optimize debt ratios. Auerbach (1985)also estimates a target-adjustment model, but allows for firm-specific and time-varying targets. He also interprets the significant adjustment coefficients as support for target-adjustment behavior.

However, other evidence is inconsistent with the optimal debt ratios or can be interpreted differently. First, as pointed out by Myers (1984), the negative valuation effects of equity issues or leverage-reducing exchange offers – see Masulis (1980)– do not support the tradeoff story. If changes in debt ratios are movements towards the top of the curve (as in Fig. 1), both increases and decreases in leverage should be value enhancing.2 Second, Kester (1986), Titman and Wessels (1988)and Rajan and Zingales (1995)find strong negative relationships between debt ratios and past profitability. Models based on the tradeoff of the tax benefits of debt and the costs of financial distress predict a positive relation.3

This empirical literature has been guided almost exclusively, though sometimes implicitly, by the assumption of an optimal debt ratio. In Myers's (1984) and Myers and Majluf's (1984) pecking order model there is no optimal debt ratio. Instead, because of asymmetric information and signaling problems associated with external funding, firms' financing policies follow a hierarchy, with a preference for internal over external finance, and for debt over equity. A strict interpretation of this model suggests that firms do not aim at any target debt ratio; instead, the debt ratio is just the cumulative result of hierarchical financing over time. Firms that face a financial deficit will first resort to debt, and will be observed later at higher debt ratios. This reasoning could readily explain the negative relation between past profitability and debt ratios.

A growing literature considers liquidity constraints on real investment as a result of the asymmetric information problems of external equity financing. See for example, Hoshi et al. (1991), Fazzari et al. (1988)and Whited (1992). In this paper, we take real investment as exogenous, because our sample consists of large, public firms, most with investment-grade debt ratings. Firms that can issue debt that is (nearly) default-risk free escape liquidity constraints caused by asymmetric information.

What if our firms have excess debt capacity but systematically operate below their optimal debt ratio? This could explain why they issue debt when they need external funds. However, if they are constantly below target over a 20-year sample period, the concept of an optimal debt ratio has little operational meaning. On the other hand, if many such firms were found to issue equity, the pecking order would be rejected.

The static tradeoff and pecking order theories assume shareholder wealth maximization as the corporate objective. We do not attempt to test any theory based on managerial or organizational objectives.4 Such a theory could predict behavior similar to the pecking order.

But we are not attempting to frame or test a general model of capital structure choices. As Harris and Raviv's (1991) review article demonstrates, the motives and circumstances that could determine those choices seem nearly uncountable. Instead we concentrate on simple specifications of two widely cited theories. It's important to understand why tests of these specifications work, do not work, or appear to work.

Section 2describes the two contending hypotheses. Data, basic tests and results are described in Section 3. Section 4shows how the statistical power of models of financing can be assessed. The standard target adjustment model cannot be rejected when the pecking order drives financing. We can reject the pecking order in a static tradeoff world. This section also comments on the power of certain cross-sectional tests. Section 5concludes and discusses implications for future research.

Section snippets

The pecking order

In its simplest form, the pecking order model of corporate financing says that when a firm's internal cash flows are inadequate for its real investment and dividend commitments, the firm issues debt. Equity is never issued, except possibly when the firm can only issue junk debt and costs of financial distress are high.

Define

.

Ct=operating cash flows, after interest and taxes,
DIVt=dividend payments,
Xt=capital expenditures,
ΔWt=net increase in working capital,
Rt=current portion of long-term debt at

Sample and data

We started with all firms on the Industrial Compustat files. Financial firms and regulated utilities were excluded. Firms are included in the final sample if they have no gaps in data on the relevant funds-flow and balance-sheet variables and if they are not involved in a `major' merger as defined in the Compustat footnotes.

Power

The tests reported so far show that when the target-adjustment and pecking order models are independently tested against a zero null, they both appear to describe the variation in debt ratios, although the pecking order wins the horse race when judged on raw explanatory power (R2). We now investigate the statistical power of these tests. We demonstrate that the target-adjustment model can generate plausible and highly `significant' statistical results even when it is false. The simple pecking

Conclusions

This study reexamines some aspects of the empirical literature on capital structure. Others, for example Titman and Wessels (1988), have attempted to test various models by including all hypotheses jointly in the empirical tests. Instead, we view the theories as contending hypotheses and examine their relative explanatory power. The attention to statistical power is an important methodological point, and we believe our procedure for testing the power of financing hypotheses is original.

Our main

References (31)

  • M. Harris et al.

    The theory of capital structure

    Journal of Finance

    (1991)
  • T. Hoshi et al.

    Corporate structure, liquidity, and investmentevidence from Japanese industrial groups

    Quarterly Journal of Economics

    (1991)
  • A. Jalilvand et al.

    Corporate behavior in adjusting to capital structure and dividend targetsan econometric study

    Journal of Finance

    (1984)
  • M.C. Jensen

    Agency costs of free cash flow, corporate finance and takeovers

    American Economic Review

    (1986)
  • C.W. Kester

    Capital and ownership structurea comparison of United States and Japanese manufacturing corporations

    Financial Management

    (1986)
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    This paper has benefited from comments by seminar participants at Boston College, Boston Unsiversity, Dartmouth College, Massachusetts Institute of Technology, University of Massachusetts, Ohio State University, University of California at Los Angeles and the NBER, especially Eugene Fama and Robert Gertner. The usual disclaimers apply. Funding from MIT and the Tuck School at Dartmouth College is gratefuly acknowledged. We also thank two reviewers, Richard S. Ruback and Clifford W. Smith, Jr., for helpful comments.

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