The Mystery of Zero-Leverage Firms

Strebulaev and Yang (working paper, 2013)

A large percentage of publicly-owned U.S. firms (14% in 2000) have zero or almost-zero leverage, and this phenomenon is not confined to just a few years.  Zero leverage as a corporate policy appears to be persistent, and is not explained either by industry or by firm size.

In addition, many zero-leverage firms pay dividends, so it is not the case that this is driven by growth firms choosing zero leverage to avoid paying out earnings.

Compared to similar firms matched on size and industry, zero-leverage firms that pay dividends:

  • pay higher dividends
  • have higher cash balances

One potential explanation is an agency story where the manager prefers zero leverage, even if the shareholders may not.  This story finds support in the empirical findings that zero leverage is more likely in

  • firms with higher CEO ownership
  • firms with less independent or more CEO-friendly boards
  • family-owned firms.

 

How Stable Are Corporate Capital Structures?

Harry DeAngelo and Richard Roll (2008 JF)

Summary

  • Lemmon, Roberts, and Zender (2008) and others make the argument that the cross-section of corporate capital structure is quite stable over long horizons.  LRZ show that, among a selection of determinants that are believed to be linked to capital structure, firm fixed effects are by far the most powerful predictor.  They also sort firms into leverage quartiles, and show that the high- (low-) leverage portfolios at time t also have the highest (lowest) leverage as much as 20 years into the future.
  • One interpretation, bluntly stated, is that 50 years of capital structure research has been barking up the wrong tree.  Researchers should go “back to the beginning” and rethink their approach.
  • Another interpretation of these findings is that the cross-section is stable over time, and therefore not interesting.  Researchers should confine themselves to explaining within-time variation in capital structure.
  • DeAngelo and Roll (this paper) present compelling arguments that (1) LRZ’s analysis masks variation of the cross-section over time, and so is somewhat biased toward finding stability and (2) capital structure at the firm level is wildly unstable, and the evolution of the cross-section is at least as interesting a research topic as the snapshot at each point in time.

Methods and Findings

  • The sample consists of 15,096 CRSP/Compustat firms over 1950-2008.
  • The authors test for firm-level stability by measuring the length of each firm’s “stable leverage regimes” – i.e. a period of time where the firm’s leverage stays within a narrow band of 0.05, 0.1, or 0.2.
    • Among firms that are in the sample for at least 20 years, only 20% have stable (using the bandwidth definition of 0.05) leverage for a ten-year period, only 4% have stable leverage for a 20-year period, and the median length of firms’ “longest stable regime” is only 6 years.
    • Among firms that are in the sample for the entire 59-year period, 52% have stable leverage (again, bandwidth of 0.05) for some 10-year period, 0% have stable leverage for a 40-year period, and the median length of “longest stable regime” is only 10 years.
  • They then show that, during firm’s stable regimes, leverage tends to be quite low, often less than 0.1.
  • A significant portion of the paper is dedicated to explaining why the results in Lemmon, Roberts, and Zender (2008) and MacKay and Phillips (2005) are misleading.
    • Use a creative specification that allows firm-time fixed effects with firm-time observations.  A textbook application of this would result in one fixed effect for each observation and tells the researcher absolutely nothing.
      • Following Scheffé (1959), they get around this by imposing some additional structure. They assume that firm-time interaction effects are stable over longer periods – they arbitrarily choose 10 years – so that they run regressions with firm-decade fixed effects.
        • Using firm-decade interactions significantly improves R-squared over a specification with firm fixed effects only.
        • ANOVA reveals that
    • DeAngelo and Roll (this paper) use a longer sample than the papers they criticize.  This is important, because if firm leverage changes slowly (this can be represented by adjustment costs to leverage), then the power of firm fixed effects will be overstated in short samples.  The problem is similar if many firms only appear in the sample for a few years.
      • This is also important because, as these authors argue, the LRZ sample begins in 1970 – after economy-wide increases in leverage as firms took advantage of post-war investment opportunities.  Thus, the later sample misses crucial time-series variation in leverage.
  • In another set of analyses, DeAngelo and Roll show that the cross-section varies meaningfully over time.
    • They measure the correlation between several pairs of cross-sections – the pairs {t,t+1}, {t,t+2},…,{t,+40}.
      • The correlation falls quickly from 0.8 for {t,t+1} and approaches zero.
    • They show that firms in one leverage quartile at time t  moves across quartiles a lot in the ensuing years.  LRZ miss this because they look at average leverage of quartile groups.
  • The final part of the paper tests various theories of capital structure: (1) Miller’s (1977) random variation, (2) speed-of-adjustment (SOA) models, (3) flexible target ratio models, and (4) time-varying target (TVT) models.
    • They simulate a model that nests all these as special cases, and see which model(s) appear to best fit the data.
    • The TVT and flexible-target models seem to be the best, while Miller’s random leverage model is not supported.

The authors’ primary conclusion is that the cross-section is far from stable, and that within-firm variation of leverage over the time series is probably a response to the firm’s investment needs.

Comments

  • I liked this paper.  It documents new facts about the variability of firm-level debt ratios over time, and uses creative analysis.
  • The paper also leaves many questions unanswered.  It doesn’t explain why firms have such low leverage during stable regimes (though DeAngelo, Stulz, and Gonçalves currently have a working paper that tries to answer this question).  It doesn’t explain why, if macro factors (post-war environment) are so important, the cross section still changes so much from year to year.
  • Sample-selection bias is an accusation commonly made to papers whose data start after the post-war period.  David, Fama, and French (2000) made a similar criticism of Daniel and Titman’s (1997) argument that firm characteristics matter and risk-factor loadings don’t.  But it is not clear that the post-war decades are relevant for all analyses.
    • Fama’s and French’s three-factor asset pricing model seeks to explain only cross-sectional difference in returns, and is not concerned with how the cross-section changes over time.  High-return stocks in any period have different risk-loadings, but the risk loadings are allowed to change over time in an unspecified manner.  In this case, extending the sample backwards should be safe.
    • But this paper is concerned with how the cross-section varies over time.  Firms’ “wholesale abandonment of conservative capital structure” in the 1950s and 1960s, as they took advantage of (potentially very rare) investment opportunities may not tell us much about how they have managed their debt ratios in the last 40 years.

Do Peer Firms Affect Corporate Financial Policy?

Leary and Roberts, JF (2014)

Many CFOs responding to Graham and Harvey’s survey have indicated that peer firm financial policy plays an important role in their decision-making.  A number of empirical papers have shown that average industry leverage seems to be an important determinant of individual firm leverage.  Intuitively, peer firm leverage might be a signal of optimal capital structure and/or investment opportunities.  If a CFO does not have all the answers, he may try to infer them from peer firms’ decisions.

There are two general reasons why a firm’s capital structure decisions might appear to be related to the decisions of peer firms.  The first reason is that the firms may be subject to common factors.  Exposure to these common factors might have led to the firms selecting to become “peer firms” in the first place.  The second reason is that the firm may respond to the characteristics and/or the actions of its peer firms in a causal manner.  The confoundedness of these two reasons lead to what Manski (1993) calls the “reflection problem.”  This is an endogeneity problem that arises when trying to determine the impact of group behavior on the behavior of individuals within the group.

This paper asks, in addition to the title question, whether firms respond to the actions or to the characteristics of peer firms.

Method:

The basic idea is to regress firm outcome on peer firm characteristics, perfectly controlling for common variation; or, to measure the impact on firm outcome of an exogenous shock to peer firms. This paper regresses peer firm stock returns on market excess returns and on firm fixed effects over rolling 5-year windows, and uses the residuals as the exogenous shock.  They use (lagged) idiosyncratic stock return as the exogenous shock because it is easy to calculate and can be measured each period, unlike other plausibly exogenous shocks such as natural disasters or CEO death.  The inclusion of industry fixed effects is supposed to account for any common factors, rather than for priced return determinants.

Table 3, Panel A shows the results from regressing several capital structure outcomes on own-firm idiosyncratic stock return and characteristics, average peer-firm idiosyncratic stock return and characteristics, and industry and year fixed effects.

  • Columns 1-2 use market leverage and book leverage as dependent variables
  • Columns 3-4 use first-differences of market and book leverage, with no industry fixed effects, to control for unobserved own-firm characteristics in another way.
  • Columns 5-7 use different types of security issuance as dependent variables.

Table 3, Panel B conducts a number of robustness tests to address a number of concerns.

  • Column 1 replaces lagged own-firm idiosyncratic stock return with lagged and contemporaneous own-firm total stock return. The results are similar. This alleviates the concerns that (1) lagged peer-firm are correlated with own-firm idiosyncratic shock and this is what drives the results, and (2) the asset pricing model is misspecified so that the residuals are biased in some way.
  • Column 2 controls for a bevy of additional variables that the previous literature has presented as determinants of capital structure.
  • Column 3 controls for bank fixed effects.
  • Column 4 includes own-firm lagged leverage ratio to account for possible leverage targeting.
  • Column 5 replaces lagged controls with contemporaneous controls to verify that the results are not due to the idiosyncratic shocks affecting characteristics with a lag.
  • Column 6 adds quadratic and cubic polynomials of the peer-firm and own-firm characteristics to control for misspecification of functional form in the baseline regression.

The authors then redefine peer groups, and use shocks to peer-firm customers, that are not own-firm customers and that are in a different industry, as the exogenous shock.

Finally, they perform a double 5×5 sort on peer-firm idiosyncratic equity shock and peer-firm actions (changes in leverage).  For each group, they calculate the own-firm change in leverage.  The differential changes in own-firm leverage across the quintiles of one variable, controlling for the other variable, shed light on whether firms respond to the characteristics or to the actions of their peers.

Results:

  • Firms respond to peer-firms’ financing decisions.
  • Firms respond to peer-firms’ characteristics, but to a lesser degree than to their decisions.
  • Peer firm behavior is a more important determinant than the observable determinants from prior literature.
  • Smaller, younger, and less-successful firms tend to be more influenced by peer firms, while industry leaders appear to be less influenced.

Discussion:

I love that the main findings of the paper can be presented in just one table (table 3)!  The authors use an interesting type of exogenous shock and draw on a variety of finance research to motivate and defend it.  I also love the literature review section(s) of this paper.  It is very well written…or maybe it’s just personal preference for the subject.

This paper is in line with Lemmon, Roberts, and Zender (2008) in questioning the relevance of several decades of capital structure.  If firm peer groups are relatively static, then this could explain the just-mentioned paper’s findings that firm fixed effects are the best determinant of firm capital structure.

Banks as Patient Fixed Income Investors

Hanson, Samuel G., Andrei Schleifer, Jeremy C. Stein, and Robert W. Vishny, “Banks as Patient Fixed Income Investors,” American Finance Association 75th Annual Meeting, Boston (2015).

Purpose:  To introduce a model explaining why asset holdings differ between traditional banks and so-called “shadow banks.”

Findings:

  • Traditional banks have more market share in assets that are illiquid and that are fundamentally safe but have high intertemporal volatility.
    • business loans, MBSs, etc.
  • So-called shadow banks hold assets that are either highly liquid or that have low volatility.
    • equities, Tresauries, etc.

Motivation:

  • Commercial banks’ liability mix is highly homogeneous (mostly customer deposits), both in the cross section and in the time series.
  • Bank assets are far more heterogeneous.
  • Banks’ scale seems to be driven by their ability to attract deposits (liabilities), rather than by their investment opportunities (assets).
  • Banks’ asset portfolio does not appear to be a liquidity buffer; rather, banks hold few Treasury securities and instead hold assets earning a (riskier) spread over Treasuries.
  • Bank risk-taking is not likely to be the result of moral hazard due to deposit insurance.

Model:

  • There are N risky assets
    • Assets are perfectly correlated, differing by their payoff in the bad state of the world.
  • The model has three actors: households, banks, and shadow banks.
    • Households are risk neutral, and invest in bank claims but do not own assets.
    • Banks invest in assets and issue claims on these assets to households. Intermediation is necessary to create safe claims, as no asset is risk-free.
  • The model has three time periods:
    • At time t=0, banks invest in risky assets and issue claims to households.
    • At time t=1, bad news arrives with probability 1-p. Shadow banks must sell assets for less than fundamental value, but traditional banks are not forced to sell.
    • At time t=1, payoffs to asset holdings and household claims are realized. If bad news arrived at time t=2, then the bad state occurs with probability 1-q.
  • Traditional bank intermediation
    • Traditional banks hold assets to maturity, and create safe assets by only issuing claims equal to their asset portfolio payoff in the bad state. The rest of their asset portfolio is financed using costly equity.
  • Shadow bank intermediation
    • A shadow bank is a dual institution–a highly-leveraged institution (HL) and a money-market fund (MMF).
    • The HL purchases risky assets and enters a short-term repo agreement with the MMF.
    • The MMF creates safe assets through its ability to seize the HL’s assets and sell them at fire-sale prices if bad news occurs.

Results:

  • In an interior equilibrium where both types of banks hold an asset type, the marginal benefit of stable funding (the avoidance of fire-sale losses) equals the marginal cost of stable funding (limits on the amount of claims that can be created—money creation).
  • Corner solutions are also possible, where an asset type is held exclusively by one type of institution.
  • Traditional bank asset ownership increases in asset illiquidity and in expected bad-state payoff.
    • High asset illiquidity and bad-state asset payoff diminishes the money-creating advantage of shadow banks.
    • Equities are not suitable for traditional bank ownership (bad-state payoffs are too low) but are suitable for shadow bank ownership (liquidity is high).
  • An increase in the premium households pay for safe assets lowers traditional bank ownership for all (risky) assets.
  • A decrease in the probability of bad news lowers traditional bank ownership for all assets.

Empirical Evidence

  • Banks with stickier liabilities hold more illiquid assets.
    • “Sticky” liabilities mean that depositors are less likely to withdraw them upon bad news.
  • Banks hold very little of either Treasury securities or equities.

Debt and Seniority: An Analysis of the Role of Hard Claims in Constraining Management

Hart, Oliver, and John Moore, “Debt and Seniority: An Analysis of the Role of Hard Claims in Constraining Management,” The American Economic Review, Vol 85, No 3 (1995), 567-585.

  • Assume that managers will always invest in every project (due to empire-building, prestige, resumé-building, etc.)
    • If managers have too much cash flow, they will invest in bad (negative NPV) projects along with good ones.
    • Debt can fix the agency problem by forcing managers to pay out cash flows before investing.
  • The debt overhang problem
    • If managers have too little cash, they will have to forgo investing in good projects.
    • If managers have too much debt, they will not risk losing their job and, again, will forgo investing in good but risky projects.
  • Long-term debt can outperform complicated contracts in solving agency problems.
    • Contracts that attempt to align manager compensation with shareholders’ interests can’t address every agency problem.
    • Long-term debt restricts managers from borrowing against future cash flows to invest in bad projects.

Debt and Taxes

Miller, Merton H., “Debt and Taxes,” The Journal of Finance, Vol 32, No 2 (1977), 261-275.

Purpose:  To argue that, even if debt repayments are tax deductible, a firm’s value is independent of its capital structure.

Arguments:

  • The [potential] direct bankruptcy costs of debt seem too small to be balanced by the tax savings.
    • Corporations do not have as much debt as models suggest they should have – fear of bankruptcy has to be very high for debt levels in the models to match the empirical evidence.
    • The potential indirect costs of bankruptcy are probably not very big, either.
  • Between the 1920s and the 1950s, taxes increased 400% while corporate capital structures changed very little (and change through the end of the 1970s appears unlikely).
  • Investment bankers and corporate financial officers are aware of the tax implications of debt.
  • The only explanation left is that the tax savings of debt are much smaller than researchers generally believe.

Tax Advantages of Debt:

  • If there are no taxes, there are no tax advantages.
  • If there are corporate taxes but no personal income taxes, then the tax advantage of debt is the corporate tax rate multiplied by corporate debt.
  • If there are personal income taxes, and the personal tax on share income is less than the tax on bond income, then investors will prefer that corporations use equity financing over debt financing, thus negating the tax advantages of debt.
    • Corporations holding very little debt and/or paying small dividends will be preferred by shareholders in high tax brackets.
    • Corporations with high leverage and/or high dividends will be preferred by shareholders in low tax brackets.
    • One shareholder class is as good as another, so capital structure is, again, irrelevant.

Measuring investment distortions arising from stockholder-bondholder conflicts

Parrino, Robert, and Michael S. Weisbach, 1999, “Measuring investment distortions arising from stockholder-bondholder conflicts,” The Journal of Financial Economics 53, 3-42.

Purpose:  This paper calculates the expected wealth transfer between stock- and bondholders occurring when a firm begins a new project.  It also estimates how stockholder-bondholder conflict impacts investment decisions, and whether it can explain cross-sectional variation in capital structure.

Findings:

  • There will be underinvestment when the firm is faced with safe projects.
    • Stockholders demand a higher return than the CAPM rate.
      • This effect is stronger for high-leverage firms.
    • Safe projects with low returns benefit bondholders at the expense of equity holders.
  • There will be overinvestment when the firm is faced with risky projects.
    • Stockholders are willing to gamble, and will even invest in negative NPV projects if the potential payoff is high.
      • This effect is also stronger for high-leverage firms.
    • Risky projects with negative expected (but high potential) payoffs benefit equity holders at the expense of bondholders.
  • Longer debt duration is vulnerable to larger agency problems
  • Lower marginal tax rates lead to slightly larger distortions
  • The stockholder-bondholder conflict does exist and there do seem to be empirical investment distortions, but these distortions are too small to be useful in explaining most firms’ capital structure decisions.
    • The distortion is only 0.14% for a firm with 20% debt-to-capital ratio, compared with a 3% noise factor in measuring cost of capital

parrinoweisbach

Motivation:  Managers seek to maximize shareholder value, not necessarily firm value.  The “underinvestment problem” is when managers avoid a positive NPV project that would increase firm value but would lower stockholder value.  The “overinvestment problem” is when managers undertake a negative NPV project that lowers firm value but raises stockholder value.  These agency problems have been widely discussed in the literature for decades, but there is no consensus on their magnitude or on how important they really are.

Data/Methods:  Use numerical simulations to estimate the impact of debt on the investment decisions of a levered firm whose managers seek only to maximize stockholder value.  Compute the stockholder-bondholder wealth transfer accompanying projects with known characteristics.

  • Compustat data for firms from 1981-1995
  • Monte Carlo:  Assume a firm with known cash flows following a random walk without drift for 30 years, after which cash flows are static.  Assume a project financed entirely with equity, whose cash flows similarly follow a random walk without drift for 30 years.  Assume a correlation of 0.5 between firm and project cash flows, run the simulation 5,000 times, and compute the ex ante value of debt and equity each time.
    • Value of debt is the sum of discounted future cash flows to bondholders.
    • Value of equity is the discounted cash flows to stockholders plus a terminal value.

Conclusions:  Distortions in stockholder-bondholder required investment returns vary along several dimensions.  However, for the typical firm they are much smaller than the noise in cost-of-capital measurement.  The effect exists but is too small to explain cross-sectional variation in capital structure.

The Cost of Capital, Corporation Finance, and the Theory of Investment

Modigliani, Franco, and Merton Miller, 1958, “The Cost of Capital, Corporation Finance, and the Theory of Investment,” The American Economic Review, Vol. 48, No. 3, 261-297.

Purpose:  This paper proposes a theory explaining how a firm’s stock price (market value) is impacted by managers’ capital structure decisions.

Motivation:  Previous work regarding the cost of capital treats assets as having known income streams, and adjusts for uncertainty simply by subtracting “risk discounts” from the expected rates of return.  This treatment of risk is inadequate.  A market-value approach—where the cost of capital is the return on an investment that does not affect a firm’s stock price—has promise, but we need a theory describing the impact of a firm’s capital structure on its market value.

Theory:

  • Model 1:  Corporations can only issue common equity
    • Assume perfect markets, no agency problems, and an economy where all assets are owned by corporations that can only finance operations with common equity.  Therefore, the rate of return on one share equals expected return to the share divided by share price.
      • Since there are no agency problems, retained earnings are the same as cash dividends.
    • Assume classes of corporations where each share’s expected return is perfectly correlated with all others in the class.  Then there is one rate of return for each class, and all shares in a class are perfect substitutes (up to a scale factor).
  • Model 2:  Corporations can issue bonds in addition to common equity
    • Assume bonds trade in perfect markets and all corporations and households have a perfect credit rating.  Then all bonds are perfect substitutes (up to a scale factor), and have the same expected rate of return.
    • Market value is independent of capital structure.
      • If an individual values leverage, he can take it on himself by borrowing money to buy more stock in an unlevered company.
    • The expected rate of return on stock in a levered company is the rate of return on a pure-equity company from its same class, plus a premium equal to the debt-to-equity ratio times the spread between the class-specific equity return and the [universal] cost of debt.
  • Model 3:  Corporate interest payments are tax-deductible
    • The debt-vs-equity consideration is important for overall corporate liquidity management due to taxes, timing, market sentiment, investor tax profiles, etc.
    • However, all that matters in project financing is the cost of capital.  A preference for one type of financing over another does not make a project more or less profitable.

Empirical Evidence and Conclusion:

  • Using data from the only two relevant studies:
    • There is no significant relationship between leverage and cost of capital.
    • As leverage increases, expected return to equity increases.
  • The amount of leverage can be important over the life of a corporation, but is irrelevant in determining the profitability of a project.

Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers

Jensen, Michael C., 1986, “Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers,” The American Economic Review 76 (2), 323-329.

Purpose:  This paper develops a theory linking debt, agency costs of free cash flow, and corporate takeovers.

Theory:  Managers seek to maximize their own influence, and not necessarily shareholder return.  They also have discretion over free cash flow, which represents an agency problem for firms with high free cash flows and low growth prospects.  Debt can be used to limit managers’ discretion over cash flows, and so increases in leverage can create value for shareholders beyond the tax implications.

  • Debt holders can force firm reorganization without bankruptcy more quickly and easily than equity holders.  This means higher-leveraged firms tend to be leaner and better managed.
  • Takeover targets should include firms with poor earnings and poor management, or firms with excellent earnings that management does not use to create value.
  • Lack of growth opportunities frequently leads to the undertaking of value-destroying projects.  Firms pursuing diversification and firms in industries with overcapacity often fit in this category.
  • These firms ought to see more takeovers, threats of takeovers, and subsequent debt increases.

Empirical Evidence:

  • Evidence from LBOs and going-private transactions
    • Most firms that are taken private are those with low growth and high potential for free cash flows—hence, high agency costs.  Strip financing (all bond-holders hold equal proportions of debt in each tier of seniority) reduces conflict of interest among bond holders, which gives them more power over the firm.
    • Very few of these transactions have gone into bankruptcy, suggesting that debt holders can force management efficiency and limit suboptimal investments.
  • Evidence from the oil industry
    • During the 1970s, oil prices increased and optimal capacity decreased, so that oil firms were both highly profitable and destined to shrink.  Oil managers continued investing in exploration & discovery projects that returned less than the cost of capital.
    • Around this time, oil companies began to merge and restructure under threat of takeover.  They increased leverage and cut value-destroying investments.

Conclusions:

  • Managers of firms with low growth opportunities can’t be trusted with high cash flow.
    • Leverage can be used to limit the free cash flow agency problem.
  • Firms with high cash flows and low growth opportunities should be prime takeover targets.
  • Acquisitions financed with debt and cash should create more value than similar transactions done with equity.