Operating Leverage and Corporate Financial Policies

Transcription

1 Operating Leverage and Corporate Financial Policies Matthias Kahl McCombs School of Business University of Texas at Austin Jason Lunn Smeal College of Business Pennsylvania State University Mattias Nilsson U.S. Securities and Exchange Commission This version: April 26, 2016 Abstract Using a measure of operating leverage that directly reflects the importance of fixed operating costs in firms cost structures, we show that high fixed cost firms have lower leverage ratios and also much larger cash holdings than low fixed cost firms. High fixed cost firms do not appear to primarily follow conservative financial policies to reduce the probability of financial distress. Instead, these policies allow high fixed cost firms to limit the amount by which they have to cut investment if sales are low. The relationship between operating leverage and financial policies has strengthened considerably over time. We conclude that operating leverage is an important determinant of financial policies and helps explain conservative financial policies. We thank David Brown, Henrik Cronqvist, Mark Garmaise, Yrjö Koskinen, Chris Leach, Mark Leary, Nathalie Moyen, Chris Parsons, Roberto Pinheiro, Jaime Zender, conference participants at the AFA 2012, and seminar participants at the University of Colorado at Boulder for helpful comments and suggestions. All remaining errors are our own. The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees. The views expressed herein are those of the author and do not necessarily reflect the views of the Commission or of the author s colleagues on the staff of the Commission.

2 1. Introduction There is a large literature on capital structure and cash holdings. Several variables found to explain variation in these financial policies include size, tangibility, market-to-book ratios, and profitability (for recent surveys of the capital structure literature, see Frank and Goyal, 2008; Parsons and Titman, 2008; Frank and Goyal, 2009). However, a large fraction of the variation in financial policies between firms is still unexplained. We argue that one factor that is likely to affect financial policies, but has received surprisingly little attention in the empirical literature, is operating leverage, which refers to the mix of fixed and variable operating costs. In this paper, we provide a detailed analysis of how and why operating leverage is related to firms financial policies. High fixed cost firms are exposed to more risk than low fixed cost firms. If sales are high, cash flows are very high, because the increased sales are not associated with much higher costs. However, if sales are low, cash flows are very low, because the fixed costs remain and only the variable costs are reduced. Thus, high fixed costs expose firms to the risk of low cash flows if sales are low. As a consequence, they may adjust their financial policies to reduce this risk. The most common argument in the theoretical literature is that high fixed cost firms have a greater risk of default for a given financial leverage ratio, because fixed costs are another fixed financial obligation that is similar to debt. Hence, high fixed cost firms should have lower leverage ratios than low fixed cost firms. We call this the leverage trade-off hypothesis (see Van Horne (1977)). However, fixed costs can also affect a firm s optimal cash holdings. For example, a high fixed cost firm may want to hold more cash to hedge its higher default risk. We call this the cash adjustment hypothesis. High fixed cost firms may also have more conservative financial policies than low fixed cost firms to preserve their ability to sustain investment when sales and hence cash flows are low. Both this underinvestment hypothesis and the default risk hypothesis imply that high fixed cost firms should have lower leverage ratios and higher cash holdings than low fixed cost firms. We measure the importance of fixed costs by measuring the sensitivity of innovations in growth rates of operating costs to innovations in growth rates of sales. This sensitivity approximates the relative mag- 1

3 nitude of variable operating costs in a firm s cost structure. This approach offers an alternative to the measure of operating leverage sometimes used in the literature, the degree of operating leverage (DOL), which measures the sensitivity of EBIT to sales (Mandelker and Rhee, 1984). One advantage of our measure is that it is unaffected by factors unrelated to cost structure such as fluctuations in operating margins. Moreover, it can be calculated for firms with negative EBIT in the estimation period, which constitute almost half of our sample. Our sample consists of all Compustat firms from 1980 to 2013 (except financial firms and regulated utilities) with at least a ten-year history of positive sales and operating expenses. Consistent with the leverage trade-off hypothesis, high fixed cost firms, which comprise the highest third of firm-years in terms of fixed costs, have 4.1 percentage points or 12% lower book leverage ratios than low fixed cost firms (i.e., the lowest third of firm-years in terms of fixed costs). The results for market leverage ratios are similar. High fixed cost firms also have a 4.7 percentage points or 45% higher probability of having no debt than low fixed cost firms. Consistent with the cash adjustment hypothesis, we find that the relationship between cost structure and corporate cash holdings is particularly strong. High fixed cost firms hold 3.1 percentage points or 30% more cash than low fixed cost firms. These results suggest that operating leverage is an important reason why firms hold large cash reserves. Combining leverage and cash holdings, we also consider net leverage ratios (net debt is gross debt minus cash). We find that high fixed cost firms have 7.7 percentage points or 42% lower net book leverage ratios than low fixed cost firms. These results support a basic prediction shared by the default risk hypothesis and the underinvestment hypothesis. To understand why high fixed cost firms choose more conservative financial policies than low fixed cost firms, we test more unique predictions of the two hypotheses. The underinvestment hypothesis implies that high fixed cost firms hold extra cash reserves and have lower leverage ratios so that they can finance positive NPV investments even if their sales and hence cash flows are low. This suggests that in years with low sales growth high fixed cost firms should not reduce their investment more than low fixed cost firms. Our evidence confirms this prediction. While high fixed cost firms experience a 2

4 much larger decline in their cash flows in years with low sales growth, they make up for this decline by drawing down their cash holdings more and issuing new debt when sales are low. This allows them to reduce their spending on capital expenditures, acquisitions, and net working capital by less than low fixed cost firms. These results support the hypothesis that high fixed cost firms choose more conservative financial policies to preserve their ability to invest when sales are low. In contrast, if high fixed cost firms chose more conservative financial policies mainly to avoid default, they would cut investment when sales are low and draw down their cash holdings instead to repay debt, reducing the probability of financial distress. We also find that even among firms with no debt and hence no possibility of default, high fixed cost firms have much larger cash holdings than low fixed cost firms. These results do not support the argument that high fixed cost firms choose more conservative financial policies primarily to reduce the probability of default. We investigate how high and low fixed cost firms responded to the financial crisis of The financial crisis reduced the cash flows of high fixed cost firms substantially more than those of low fixed cost firms. However, high fixed cost firms did not reduce their spending on total investment (capital expenditures, acquisitions, and increases in net working capital), compared to low fixed cost firms. They compensated for the larger decrease in cash flows by drawing down their cash holdings more than low fixed cost firms. However, they did not use this cash to repay more debt than low fixed cost firms. These results again support the underinvestment hypothesis but not the default risk hypothesis. We also find time-series variation in the relationship between operating leverage and financial policies. Fixed costs have increased over time and the relationship between fixed costs and financial policies has strengthened considerably in the more recent half of our sample. The difference between the book leverage ratios of high and low fixed cost firms has increased from 1.6 percentage points in the first half of our sample ( ) to 4.3 percentage points in the second half ( ). The difference between the cash holdings of high and low fixed cost firms has increased over the same period from 1.2 to 4.1 percentage points and the difference between the book net leverage ratios from 2.6 to 9.0 percentage points. The difference between the likelihood of having no debt for high and low fixed cost firms has in- 3

5 creased from 2.7 to 7.3 percentage points. These results are consistent with the secular increase in competition and idiosyncratic cash flow volatility that has been documented in the literature (see, for example, Comin and Philippon, 2005, and Irvine and Pontiff, 2009). Firms with high operating leverage should be exposed to a larger extent to such a general increase in operating risk. Although operating leverage, like other characteristics linked to a firm s production technology, is fixed in the short-term, firms can adjust it in the long-term. To address the potential endogeneity problem, we run regressions with the earliest available dependent variable as an additional regressor, following Lemmon, Roberts, and Zender (2008). Our results are robust to this change in specification. We also run models with firm fixed effects, although they are in our context likely to give rise to very conservative estimates, because operating leverage is a persistent variable and measured with error. 1 Operating leverage remains a significant determinant of financial policies in these specifications, but its economic magnitude is reduced substantially with firm fixed effects. 2 This is also typical for other determinants of capital structure (Lemmon, Roberts, and Zender, 2008). To summarize, our contribution is threefold. First, we show that operating leverage is an important determinant of a firm s financial policies. Firms with high fixed costs have lower leverage ratios and larger cash holdings than low fixed cost firms. The difference in cash holdings is particularly large in terms of economic magnitude. Second, our evidence suggests that the primary reason why high fixed cost firms follow conservative financial policies is not the desire to reduce the probability of default. Instead, they appear to do so to limit investment cuts if sales are low. Third, the relationship between fixed costs and corporate financial policies has strengthened over time. This could help explain the secular increase in cash holdings that has been documented in the literature (see Bates, Kahle, and Stulz, 2009). Most of the literature on operating leverage focuses on its relationship to the riskiness of stocks or expected stock returns (see, for example, Lev, 1974: Novy-Marx, 2011). In contrast, there are surprisingly 1 The attenuation bias associated with measurement error becomes particularly severe in the presence of firm fixed effects (Griliches and Hausman, 1986). 2 The only exception is one specification with firm fixed effects in which the difference in market leverage ratios between high and low fixed cost firms is not statistically significant. 4

6 few papers that consider the empirical relationship between operating leverage and corporate financial policies. In a univariate analysis of 255 manufacturing firms between 1957 and 1976, Mandelker and Rhee (1984) show that there is a negative relationship between DOL and the elasticity of earnings after interest and taxes with respect to EBIT, which they interpret as financial leverage. 3 One factor that could affect operating leverage is production flexibility. Reinartz and Schmid (2015) analyze a worldwide sample of energy utilities and find that higher production flexibility, measured by average run-up time and ramp-up cost, increases financial leverage. They argue that production flexibility increases financial leverage because of reduced expected costs of financial distress and higher interest tax shields. We add to the literature by conducting a systematic, panel data analysis of the relationship between operating leverage and financial policies. Our results indicate a strong and robust relationship between operating and financial leverage. This adds to the findings in Reinartz and Schmid (2015), who consider only one factor affecting operating leverage (production flexibility) and restrict their analysis to energy utilities. More importantly, we also analyze the relationship between fixed costs and cash holdings, which is especially strong, and consider the relationship between fixed costs and investment policies. In addition, we find strong time-series variation in the relationship between operating leverage and financial policies. In contrast to the literature, our results suggest that concerns about underinvestment, not about default risk are the primary motive behind the conservative financial policies of high fixed cost firms. Operating leverage affects cash flow volatility directly. To ensure that our results are not just due to cash flow volatility, we control for contemporaneous cash flow volatility, which does not affect our results. Moreover, in our comprehensive data set of over 50,000 firm-years, cash flow volatility, unlike fixed costs, is not negatively related to leverage ratios (and indeed in some specifications positively related to it) and is not positively related to cash holdings (and in some specifications negatively related to 3 In a sample of 233 firms for the years 1974 and 1976, Ferri and Jones (1979) find that there is a negative univariate relationship between a measure of tangibility and leverage ratios. They interpret this measure of tangibility as a measure of operating leverage. However, they find only a marginally significant univariate relationship between DOL and leverage for 1976 but no significant relationship for Dugan, Minyard, and Shriver (1994) show that firms for which the trade-off between financial and operating leverage is stronger (ranked above the median of the industry in either operating leverage or financial leverage but below it in the other) differ according to some financial ratios when one uses the O Brien and Vanderheiden (1987) measure of operating leverage but not if one uses the Mandelker and Rhee (1984) approach. 5

7 them). Therefore, the relationship between operating leverage and financial polices is different in nature from that between cash flow volatility and financial policies. Our paper also contributes to the literature on financial conservatism. Graham (2000) finds that U.S. firms are underleveraged. Several explanations for this underleverage puzzle have been proposed, including conflicts between managers and shareholders (Morellec, 2004), underestimates of financial distress costs (Molina, 2005), dynamic capital structure adjustments (Goldstein, Ju, and Leland, 2001; Ju, Parrino, Poteshman, and Weisbach, 2005), and tax shelters (Graham and Tucker, 2006). We show that high fixed costs are an additional reason for financial conservatism and contribute not just to low leverage but also to high cash holdings. The remainder of the paper is structured as follows. Section 2 discusses the hypotheses guiding our analysis. In Section 3, we describe the data and our cost structure measure and discuss some univariate results. Section 4 presents our empirical approach and the main results. Section 5 concludes. 2. Hypotheses Operating leverage has important consequences for optimal financial policies. Higher fixed costs imply that cash flows are more sensitive to sales. If sales are high, cash flows are particularly high, because the increased sales are not associated with substantially increased costs. However, if sales are low, cash flows are particularly low, because the fixed costs remain and only the variable costs are reduced. Thus, high fixed costs expose firms to the risk of low cash flows if sales are low. As a consequence, they should have more conservative financial policies to reduce this risk. One way high fixed cost firms can achieve more conservative financial policies is by having lower financial leverage ratios than low fixed cost firms. We call the hypothesis that high fixed cost firms choose lower leverage ratios, which has been proposed by Van Horne (1977) and Mandelker and Rhee (1984), the leverage trade-off hypothesis. One reason behind a trade-off between operating and financial leverage is that for a given financial leverage ratio, higher fixed costs increase the risk of default. Other reasons behind such a trade-off are discussed below. 6

8 However, firms may want to avoid reducing their leverage, because they would forgo some of the benefits of debt, such as interest tax shields. While the literature has focused on the role of fixed costs for firm s debt policies, firms may also respond to high fixed costs by holding additional cash, which allows them to hedge the higher operational risks generated by their technology. We call the hypothesis that high fixed cost firms choose to hold more cash the cash adjustment hypothesis. However, excess cash is costly due to its lower expected return, increased risk of overinvestment, and substantial tax disadvantages. Hence, high fixed cost firms may be reluctant to hold additional cash. If cash is negative debt, firms can use either more cash or less debt in response to high fixed costs. However, cash may not be just negative debt. For example, Acharya, Almeida, and Campello (2007) argue that cash is better at hedging against future low cash flows than unused debt capacity. They point out that cash is available in all states and hence also when cash flows are low but the firm may have attractive investment opportunities. In contrast, extra debt capacity is less valuable in states where cash flow is low, because then the firm can raise less cash by issuing debt, since the debt is backed by the firm s future cash flows. Therefore, high fixed cost firms may prefer to hold extra cash rather than have lower debt. One reason why high fixed cost firms may reduce their leverage ratio or increase their cash holdings is to reduce the probability of financial distress. We call this the default risk hypothesis. Since fixed costs are fixed obligations similar to debt, for a given amount of debt, high fixed costs increase the probability of financial distress. Such financial distress can be very costly for firms (see, for example, Titman, 1984; Titman and Wessels, 1988). The default risk hypothesis implies that firms with high fixed costs have lower leverage ratios or larger cash holdings that result in lower net leverage ratios (net debt is gross debt minus cash). High fixed cost firms should reduce their debt more than low fixed cost firms following a negative sales shock that increases the probability of financial distress for a given amount of debt. They should also cut investment expenditures more than low fixed cost firms when sales are low to save cash for debt repayment. The default risk hypothesis also implies that high fixed cost firms without debt should not adjust their financial policies. In particular, they should not hold more cash since they cannot default in the ab- 7

9 sence of debt. While the literature focuses on default risk as the primary driver for the relationship between fixed costs and financial policies, firms may also adjust their financial policies to their degree of operating leverage for different reasons. For example, high fixed cost firms may be concerned about their ability to sustain positive NPV investment when sales and hence cash flows are low. Then, a firm could lack the internal funds for even profitable projects and be unable to attract new funding, because new investors understand that the funds they provide are first used to cover the firm s fixed costs or debt obligations (Myers, 1977). To reduce the expected costs of such underinvestment, high fixed cost firms may reduce their leverage ratios or increase their cash holdings. This would allow them to fund more projects if sales are low by issuing additional debt or financing the projects from internal cash. We call this the underinvestment hypothesis. Like the default risk hypothesis, the underinvestment hypothesis implies that high fixed cost firms have larger cash holdings or lower leverage ratios than low fixed cost firms. More specifically, and in contrast to the default risk hypothesis, it suggests that high fixed cost firms do not reduce their investment expenditures more than low fixed cost firms when sales are low. They avoid this investment reduction despite larger declines in their cash flows by drawing down their additional cash holdings or issuing more new debt than low fixed cost firms. The latter is possible because they have lower debt ratios in order to leave some additional debt capacity for years with low sales. Hedging the cash flow risk associated with high fixed costs can also be important even if a firm has no debt and hence no chance of entering financial distress. For example, high fixed cost firms without debt may want to sustain their investment spending if sales and cash flows are low by drawing down their cash holdings. 3. Data, construction of cost structure measure, and descriptive statistics We construct our sample using all U.S. incorporated firm-year observations in the Compustat database from 1980 to 2013 with the relevant data available. We require that each firm has both positive reve- 8

10 nue and operating costs for the ten years preceding each firm-year of interest. This requirement allows us to construct our metric of operating cost structure for each firm-year observation in the time period. Further, we exclude financial firms and regulated utilities because their financial policies are potentially affected by the regulatory environment in which they operate. In addition, we require that leverage ratios and cash holdings are contained in the closed unit interval. All other independent and control variables are winsorized at the first and 99 th percentiles to mitigate the effects of outliers in the data Construction of cost structure measure Following Lev (1974), we develop a measure of operating leverage that is directly linked to a firm s cost structure by estimating the sensitivity of operating costs to changes in sales. 4 We start by generating ex ante expectations of operating costs and sales based on the geometric growth rate over the previous two years: 1/2 1/2 E S i,t = S i,t-1 S i,t-1 S i,t-3 and E X i,t = X i,t-1 X i,t-1 X i,t-3, (1) where S i,t and X i,t represent sales and operating costs, respectively, for firm i in period t. To generate the innovations in growth rates, we calculate the following: μ S i,t = (S i,t E S i,t ) S i,t-1 and μ X i,t =(X i,t E X i,t ) X i,t-1. (2) Finally we run the following regression using seven years of innovations to obtain our measure: μ X i,t = Cost Structure i,t μ S i,t + ϵ i,t, t ϵ [-7, 0]. (3) 4 Lev (1974) runs a time-series regression of costs on physical output or sales and uses the estimated coefficient on output (or sales) as measure of a firm s operating leverage. 9

11 The intuition behind this measure is straightforward. Cost structure captures the sensitivity of operating cost growth to sales growth after accounting for growth trends. We contend that firms with higher proportions of fixed costs to total operating costs will show lower sensitivities and consequently lower estimates of Cost structure. Conversely, higher estimates of Cost structure imply that firms have more variable costs relative to total costs. We include observations with an estimated cost structure below zero among high fixed cost firms, but our results are very similar if we exclude them. We winsorize Cost structure at the 1 st and 99 th percentiles to remove the influence of outliers. Despite this, Cost structure is still a noisy proxy for the true operating cost structure and will measure it with some error. Section 4 describes how we deal with this measurement error. An alternative approach to the above would be to simply run a regression of the logarithm of operating costs on the logarithm of sales during the estimation period, and use the coefficient on the logarithm of sales as our measure of cost structure. For example, Mandelker and Rhee (1984) estimate their EBITbased operating leverage measure in this manner. However, if operating costs and sales follow similar secular growth trends, the coefficient estimates in such an approach would tend to cluster around a value of one (O Brien and Vanderheiden, 1987). By taking into account growth trends, our approach does not suffer from this problem. One advantage of Cost structure is that, unlike EBIT-based measures such as DOL, it is unaffected by factors that are unrelated to a firm s cost structure. For example, fluctuations in profit margins do not affect our measure, but affect EBIT-based measures, even if the mix of fixed and variable costs does not change. Moreover, our measure, unlike EBIT-based measures, does not require that firms have positive EBIT throughout the entire estimation period. Firms with a history of negative EBIT are quite common, constituting almost half of our sample, and ignoring them possibly introduces a sample selection bias. Figure 1 shows the evolution of Cost structure from 1980 to The mean value of Cost structure has declined over time, suggesting that firms have increasingly higher fractions of fixed costs in their cost structures. However, this evolution seems to be mainly driven by firms in the low end of the distribution 10

12 of Cost structure, the firms with the highest fixed costs. The yearly 25 th percentiles have become substantially lower whereas the medians only display a slight decrease and the 75 th percentiles have remained essentially constant over time Descriptive statistics Table A1 in the Appendix presents the full definitions of dependent and control variables. Note that all independent variables (Cost structure and control variables) are lagged one year relative to the dependent variables. Table 1 presents univariate results by comparing the means and medians of the variables across terciles of Cost structure. In particular, a firm-year observation is classified as high (low) fixed cost if it is in the bottom (top) tercile of Cost structure for the whole sample (i.e., across all firm-years). The differences between the means and medians for high fixed cost and low fixed cost firms are significant at the 1% level for all variables except for net working capital. First, we consider net leverage ratios. Net Leverage (BV) is defined as the ratio of total debt net of cash to the sum of the book values of total debt and shareholders equity. We follow Welch (2011) in constructing our leverage variables by using financial capital (debt plus equity) as the denominator. We also consider net market leverage, Net Leverage (MV), which is defined as the ratio of debt net of cash to the sum of the book value of total debt and the firm s equity market capitalization (for details, see Table A1). High fixed cost firms have a mean book leverage ratio of 24.0%, compared to 31.2% for medium and 33.9% for low fixed cost firms. They also have a lower mean market leverage ratio (18.6%) than medium (25.9%) and low fixed cost firms (26.4%). Moreover, high fixed cost firms have a much larger probability of having zero leverage (21.4%) than medium and low fixed cost firms (9.3% and 7.7%, respectively). Finally, high fixed cost firms have much larger cash holdings (mean: 20.4%) than medium and low fixed cost firms (11.3% and 10.4%, respectively). As a consequence of their lower leverage ratios and higher cash holdings, high fixed cost firms have substantially lower net book leverage ratios (mean: -3.4%) than medium fixed cost firms (14.8%) and low 11

13 fixed cost firms (18.5%). They also have much lower net market leverage ratios (1.6% instead of 14.1% and 16.1%, respectively). These results support the idea that high fixed cost firms have more conservative financial policies. They also support both the leverage trade-off and the cash adjustment hypotheses. Firms with higher fixed costs have lower leverage ratios as well as higher cash holdings. The relationship between fixed costs and financial policies is mostly driven by the high fixed cost firms. There is little difference between the financial policies of medium and low fixed cost firms. Table 1 also shows that high fixed cost firms have larger R&D expenditures than other firms. This correlation is not surprising, because R&D expenditures are often of a fixed nature. In contrast, there is no clear relationship between cost structure and capital expenditures. High fixed cost firms have slightly larger capital expenditures than medium fixed cost firms, but slightly smaller ones than low fixed cost firms. Note that capital expenditures are not included in our definition of operating costs. Capital expenditures give rise to physical assets (in particular, net PPE), and one might think that operating costs are mainly driven by the size of a firm s physical assets. However, this is not the case, as high fixed cost firms have smaller net PPE as a fraction of assets than low fixed cost firms. This relationship suggests that fixed operating costs are often not related to physical assets. For example, they include costs of fixed contracts (including labor contracts) as well as R&D expenditures, as mentioned above. High fixed cost firms are also smaller than low fixed cost firms. This relationship could arise because there are some costs that even the smallest firm has to bear (such as having a management team and an accounting department), and some of these costs are fixed. Note that our cost structure measure is by construction not affected by operating margins since they do not enter the estimation. However, one might argue that firms with larger operating margins are less affected by their fixed costs because they have a larger buffer to sustain negative shocks to sales without becoming unprofitable. Perhaps firms with larger operating margins are then misclassified by our measure as being affected substantially by high fixed costs. However, as shown in Table 1, high fixed cost firms actually have lower operating margins (EBITDA/sales) than low fixed cost firms, alleviating this concern. 12

14 4. Empirical results To examine whether a firm s operating leverage is an important determinant of a firm s financial policies, we run panel data regressions of the financial policy variables of interest on our cost structure measure. However, since Cost structure is an estimate that is measured with some error, we do not use this variable directly. Instead, we use two indicator variables that allow us to compare observations at the tails of the distribution of Cost structure: High fixed cost (Low fixed cost) is equal to one if the firm-year observation is in the bottom (top) tercile of Cost structure for the whole sample (i.e., across all firmyears), and is equal to zero otherwise. By focusing on the distributional ranking instead of the point estimates the effect of any measurement error should be mitigated. However, in untabulated results we obtain similar results with the continuous cost structure measure. The regressions we run are of the following generic type: Y it = a jt + β 1 High fixed cost it-1 + β 2 Low fixed cost it-1 + γz it-1 + ε it, (4) where Y it is the financial policy variable of interest, High fixed cost it-1 is an indicator variable for the firmyear having a Cost structure it-1 value in the bottom tercile of the sample, Low fixed cost it-1 is an indicator variable for the firm-year having a Cost structure it-1 value in the top tercile of the sample, Z it-1 is a vector of control variables, and α jt are industry-year fixed effects based on the Fama-French 49 industry classification that are included to control for unobserved time-varying industry factors. Because we have a panel of firms, we estimate standard errors that are robust to clustering at the firm level. There is a large literature on the determinants of leverage ratios and also some literature on the determinants of cash holdings that guide our choice of the set of control variables included in Z (see, for example, Rajan and Zingales, 1995; Opler, Pinkowitz, Stulz, and Williamson, 1999; Frank and Goyal, 2008; Lemmon, Roberts, and Zender, 2008; Parsons and Titman, 2008; Bates, Kahle, and Stulz, 2009; 13

15 Frank and Goyal, 2009). These controls are: firm size (Log(sales)), operating performance (EBITDA/assets), tangibility (NPPE/assets), Market-to-book, R&D expenses (R&D/sales), investment intensity (CAPEX/assets), Acquisition activity, net working capital (NWC/assets), and Cash flow volatility (the standard deviation of EBITDA/assets). Since firms can choose their cost structure over the long-term (even if it is fixed in the short-term), there is a potential endogeneity problem in estimating the relationship between fixed costs and financial policies. In particular, despite the inclusion of the control variables above, it is, of course, still possible that our estimates suffer from an omitted variable bias. The analysis in Lemmon, Roberts, and Zender (2008) suggests that such unobserved firm heterogeneity is likely to be relatively constant over time. The standard way of dealing with this is to include firm fixed effects and only rely on within-firm variation for estimation. Thus, we also estimate versions of Eq. (4) that include firm fixed effects. However, using firm fixed effects is somewhat problematic in our case, because by their very nature fixed costs are stable over time (at least in the short- to medium-term), and therefore the effect of having high fixed costs could be hard to identify separately from the fixed effects. 5 Moreover, the attenuation bias of measurement error affecting our estimates of cost structure can be severely increased in the presence of firm fixed effects (Griliches and Hausman, 1986). As an alternative to including firm fixed effects, we also attempt to control for unobserved firm-specific heterogeneity by adding the initial values of the dependent variables to our set of control variables in Eq. (4). Lemmon, Roberts, and Zender (2008) use this approach to control for the persistence in leverage ratios in part of their analysis. As initial values we use the first recorded valid value of the relevant dependent variable in Compustat. Note that the initial value of the dependent variable precedes our cost structure measure significantly, because we require ten years of past data to estimate cost structure Cost structure and leverage First, we consider the relationship between cost structure and (gross) leverage ratios. Table 2 pre- 5 Zhou (2001) discusses a similar problem for the relationship between ownership structure and performance. 14

16 sents OLS regressions based on the specification in Eq. (4) to test whether, as hypothesized, firms with higher fixed costs follow a more conservative financial policy by having lower leverage ratios. Models (1) to (3) of Table 2 show our results for book leverage ratios. Model (1) indicates that high fixed cost firms have a book leverage ratio that is 4.1 percentage points lower than that of low fixed cost firms. This difference is significant at the 1% level and also economically meaningful and 12% lower than the average leverage ratio of low fixed cost firms. High fixed cost firms have a 2.7 percentage points lower leverage ratio than medium fixed cost firms. Low fixed cost firms have a 1.4 percentage points higher leverage ratio than medium fixed cost firms (both differences are significant at the 1% level). In line with our argument above, we include the initial value of the leverage ratio in model (2) to control for the possibility that persistent unobserved firm heterogeneity explains both a firm s leverage ratio as well as its cost structure. Although the magnitude of the difference between high and low fixed cost firms is reduced somewhat, the difference is still significant (at the 1% level) as well as economically meaningful (3.1 percentage points). As an alternative to including the initial leverage ratio, model (3) includes firm fixed effects to control for unobserved firm heterogeneity. With firm fixed effects, the coefficient on the high fixed cost indicator variable and the difference between it and the coefficient on the low fixed cost indicator variable are still significant (at the 1% level), but they are reduced substantially in magnitude. However, the coefficient on the low fixed cost indicator variable loses its statistical significance in the presence of firm fixed effects. The firm fixed effects results could indicate that unobserved firm heterogeneity explains a large part of the relationship between fixed costs and leverage ratios. However, it could also be that despite using the indicator variable approach to deal with measurement error in Cost structure the fixed effect results suffer from attenuation bias due to remaining measurement error, since firm fixed effects regressions tend to substantially increase such attenuation bias. Models (4) to (6) consider market leverage ratios. The results are similar to those using book leverage ratios, but the difference in leverage ratios between high and low fixed cost firms is slightly smaller. 15

17 Moreover, this difference is not statistically significant in the presence of firm fixed effects. The relationship between fixed costs and leverage ratios is strong although we include cash flow volatility as an independent variable. Cash flow volatility is positively related to book leverage, suggesting that firms with greater cash flow volatility have higher leverage ratios, unlike high fixed cost firms, which have lower leverage ratios. Cash flow volatility is either insignificantly or positively related to market leverage. These results are consistent with the fact that in the literature, there is no consensus on the empirical relationship between cash flow volatility and leverage ratios, with some authors finding positive, others negative or insignificant relationships, as discussed in Parsons and Titman (2008). Therefore, cash flow volatility is not among the list of factors robustly related to leverage in Frank and Goyal (2008, 2009). Table A3 in the Appendix shows that high fixed cost firms achieve their lower leverage ratios by issuing more net equity (equity issues minus share repurchases) than low fixed cost firms. There is no significant difference between the mean net debt issuance of high and low fixed cost firms. Strebulaev and Yang (2013) show that between 1962 and 2009, on average 10.2% of large U.S. firms have no debt and attribute this at least partially to factors related to managerial preferences and corporate governance. Table 3 analyzes the determinants of this especially conservative financial behavior of having no debt at all. In our sample, the incidence of firm-years with zero debt is similar (12.8%) to the one found in Strebulaev and Yang (2013). The dependent variable is an indicator variable Zero leverage that takes on the value of one if a firm has no debt and is otherwise zero. Model (1) is estimated by logit. It shows that high fixed cost firms are significantly more likely to have zero leverage than low fixed cost firms (the difference is significant at the 1% level). The coefficient estimates imply that a low fixed cost firm has an average predicted probability of zero leverage of 10.5%, whereas the average predicted probability for a high fixed cost firm is 15.2% (see Panel B of Table 3). This corresponds to a 45% difference. Model (2) includes the initial dependent variable as a regressor. The results are very similar. Model (3) estimates a logit model with firm fixed effects for firms that at some point switch between having zero and positive leverage. The results are similar, but the economic magnitude of the difference between high 16

18 and low fixed cost firms is smaller. Models (4) to (6) are estimated as linear probability models by OLS. Model (4) shows that high fixed cost firms have a 5.6 percentage points higher probability of having no debt than low fixed cost firms. In the presence of firm fixed effects, the difference in the probability of having no debt between high and low fixed cost firms is still significant at the 1% level, but reduced to 1.9 percentage points. We also find in most specifications that, unlike high fixed cost firms, firms with greater cash flow volatility have a smaller likelihood of having no debt. These results indicate that high fixed costs are associated with not only generally lower leverage ratios, but also with the observations with no debt at all. Hence, fixed costs help understand the puzzling extremely conservative behavior of zero leverage firms. Overall, these results support the leverage tradeoff hypothesis Cost structure and cash holdings We now turn to the relationship between cost structure and cash holdings. As explained above, the cash adjustment hypothesis implies that firms with higher fixed costs should hold more cash. We measure cash holdings by cash and marketable securities scaled by total assets. Table 4 presents the results. Model (1) shows that firms with high fixed costs have 3.1 percentage points larger cash holdings than firms with low fixed costs. This corresponds to a difference of 30% when compared to the low fixed cost firms mean cash holdings (10.4%). The effect is again driven mostly by the difference between high and medium fixed cost firms. High fixed cost firms have 2.3 percentage points larger cash holdings than medium fixed cost firms. Low fixed cost firms have 0.8 percentage points smaller cash holdings than medium fixed cost firms. The other regression specifications confirm these findings. The magnitudes are about 70% smaller if firm fixed effects are included. The relationship between fixed costs and cash holdings is strong although we control for cash flow volatility. Moreover, cash flow volatility is either insignificant or enters negatively, suggesting, perhaps surprisingly, that firms facing greater cash flow volatility have smaller cash 17

19 holdings. Overall, these results support the cash adjustment hypothesis. Firms with higher fixed costs have substantially larger cash holdings. Moreover, the percentage difference in cash holdings between high and low fixed cost firms is between two and three times as large as the percentage difference in leverage ratios. This preference by high fixed cost firms to hold extra cash suggests that cash is not just negative debt, but may be better at hedging the risk of low future cash flows. This supports the arguments in Acharya, Almeida, and Campello (2007). Models (4) and (5) distinguish between the differences in cash holdings between high and low fixed cost firms with and without debt. We report only the specifications with the initial dependent variable as an independent variable. Model (4) indicates that even among firms without debt high fixed cost firms have 3.0 percentage points larger cash holdings than low fixed cost firms. The difference is significant at the 1% level. Therefore, even high fixed cost firms without debt hold additional cash reserves. At least for some firms, having the most conservative possible debt policy (no debt) appears not to be sufficient to hedge the greater operating risk emanating from high fixed costs. This result does not support the default risk hypothesis. Since firms without debt cannot have difficulties making debt payments, their larger cash holdings cannot be motivated by a desire to avoid financial distress. Now we turn to the sources of the higher cash holdings for high fixed cost firms. We analyze how many cents firms save out of every dollar of cash flow, their equity issues, and their debt issues. To analyze this question, we employ an approach very similar to Almeida, Campello, and Weisbach (2004). We run a regression of changes in cash holdings on cash flow and net external financing activity, controlling for firm size and market-to-book ratios. Riddick and Whited (2009) discuss potential problems with this approach arising from measurement error in the market-to-book ratio or Tobin s q (see also, for example, Erickson and Whited, 2000). Therefore, our results should be interpreted with some caution. Table 5 shows the results. Model (1) indicates that high fixed cost firms display a cash flow sensitivity of cash of 0.30, suggesting that they save 30 cents of every dollar cash flow. This is significantly larger than the cash flow sensitivity of cash for low fixed cost firms in model (2) (0.18; the difference is 18

20 significant at the 1% level). High fixed cost firms also save more out of their net financing activity (31%) than low fixed cost firms (14%; the difference is significant at the 1% level). Models (3) and (4) provide separate results for net debt and net equity issuance. High fixed cost firms save more out of their debt issues (10%) than low fixed cost firms (3%). They also save more out of their equity issues (54%) than low fixed cost firms (37%). Both differences are significant at the 1% level. In summary, high fixed cost firms have larger cash holdings than low fixed cost firms because they save more out of their cash flow as well as out of their debt and equity issues than low fixed cost firms Cost structure and net leverage So far, we have analyzed the relationship between fixed costs and leverage and fixed costs and cash separately. Now we combine leverage and cash holdings into net leverage. Net debt is gross debt minus cash holdings. Debt and cash policies are presumably jointly determined. Therefore, endogeneity problems are likely to arise if one separately estimates their determinants in the absence of an instrument for at least one of these financial policies. This problem affects all of the literature on the determinants of capital structure and of cash policies, although these policies are typically not treated in the same paper. Considering net leverage should alleviate this problem. Our separate results for leverage and cash holdings reported above should be interpreted as reduced-form estimates. One other advantage of net leverage is that it represents a simple summary statistic for the overall stance of financial policy and its degree of conservatism. Model (1) in Table 6 indicates that high fixed cost firms have net book leverage ratios that are on average 7.7 percentage points lower than those of low fixed cost firms (the difference is significant at the 1% level). This difference is large (42%) when compared to the average net book leverage ratio of low fixed cost firms (18.5%). Most of this difference comes from the difference in net leverage ratios between high fixed cost and medium fixed cost firms (5.1 percentage points). The difference between medium fixed cost and low fixed cost firms is only 2.6 percentage points. The results are again similar, but slightly smaller in magnitude, if we include the initial dependent variable in the regression. The difference be- 19

21 tween high and low fixed cost firms remains significant at the 1% level in the presence of firm fixed effects, but the economic magnitude is reduced substantially. Models (4) to (6) show similar results for net market leverage ratios. Model (4) indicates that high fixed cost firms have net market leverage ratios that are on average 5.3 percentage points lower than those of low fixed cost firms (the difference is significant at the 1% level). This represents a 33% reduction relative to the average net market leverage ratio of low fixed cost firms (16.1%). Thus, high fixed costs firms pursue a much more conservative financial policy than low fixed cost firms. Sales growth volatility could affect our estimates of the relationship between cost structure and financial policies in that firms with more volatile sales growth are potentially likely to display a lower measured sensitivity between unexpected changes in sales and operating costs. This could happen since we only use a simple extrapolation of recent sales growth to form the expected baseline sales growth when calculating Cost structure. Thus we may attribute effects to operating leverage that are really due to factors driving firm-level sales growth volatility. To address this concern, we control directly for the firmlevel sales growth volatility in Panel A of Table A2 in the Appendix. Doing so has no effect on our results. Finally, we check the robustness of our results to changing the sample distribution we use to classify firms into high versus low fixed cost firms. In Panel B of Table A2, we show that defining cost structure indicator variables based on each separate yearly distribution of Cost structure leads to very similar results to the ones we obtain by classifying the fixed cost categories based on all firm-years Cost structure and financial policies: early period versus late period Previous research has documented a secular increase in firm-level operating risk from the 1970s to the 2000s due to an increased competitive environment and technological shocks. For example, Irvine and Pontiff (2009) show that there has been an increase in idiosyncratic cash flow volatility from the beginning of the 1970s to the mid-2000s, and that this increase mirrors a similar increase in idiosyncratic stock return volatility. They attribute the increase in firm specific risk to an increase in economy wide competi- 20