The Value of Tax Benefits

The Value of Tax Beneﬁts∗

Philipp Immenk¨otter†

Preliminary Version, January 2014

Abstract In this paper, I show that investors discount tax benefits to a larger extent than predicted by asset pricing models. Even though the discount can partly be explained by default costs, financial stability, and information asymmetries, a large fraction of the discount is not related to common factors of capital structure models. This finding indicates that tax benefits play a less important role in the choice of target debt ratios than predicted by the trade-off theory. The results can explain the large cross- sectional dispersion of financing policies and why firms exhibit instable debt ratios. Tax avoidance and earnings management provide a higher utility for managers and shareholders which reduces the present value of future tax benefits.

Keywords: tax shield; leverage; corporate ﬁnancing policy; JEL classiﬁcation: G31; G32; M41

∗I am grateful for valuable comments from Andr´eBetzer, Diane Denis, Dieter Hess, Alexander Kempf, Peter Limbach, Oliver Pucker and participants of research seminars at the University of Pittsburgh, PA, CFR Cologne, Germany, and University of Wuppertal, Germany. †University of Cologne, Corporate Finance Seminar, Albertus Magnus Platz, D 50923 Cologne, Germany, email: [email protected], tel. +49-221-4707875.

1 I Introduction

Since the early work of Modigliani and Miller (1958), various attempts in the research on theoretical and empirical corporate finance have been made to explain how firms choose leverage ratios. Most commonly, tax shields serve as the primary source of benefits from financing policies. In an economy with taxes but no other frictions, an additional dollar of tax benefits increases the value of a firm by the same amount. Incorporating frictions such as default costs into an asset pricing model, Chen (2010) shows that frictions partly offset tax shields but optimal financing policies can still lever the value of a firm though tax shields by 10%. Related studies (Bhamra, Kuehn, and Strebulaev (2010)) come to similar conclusions and argue that optimizing financing policies to maximize tax benefits is a primary concern for financial managers. The empirical literature, however, offers a contrasting view. Van Binsbergen, Graham, and Yang (2010) show that only 3.5% of firm’s assets correspond to tax benefits and Graham (2000) finds that levering up could increase firm values by 15%. Hence, theoretical predictions on the value of corporate tax benefits strongly differ from the empirical findings, which forms a puzzle as to how tax benefits are priced and utilized by shareholders. This paper departs from previous work and studies this problem from a fresh perspective. I identify a discount in the marginal market value of tax benefits that cannot be explained by commonly discussed frictions in models of optimal capital structure. Share prices reflect tax benefits only partially so that the net worth of one dollar of tax benefits is substantially less than predicted by corporate valuation models. In detail, one additional dollar of tax benefits is on average rewarded only by 26.1 cents. In combination with the average level of tax benefits, the fraction of the levered firm value that corresponds to tax benefits is only 1.3%, which is significantly lower than in the previously mentioned studies. The three largest frictions that cause part of the discount of tax benefits are default costs, financial instability, and information asymmetries. In contrast to previous research, I identify the impact of each factor in a unified framework and measure its relative strength.

2 The frictions imposed by default costs are the strongest among these three forces with on average 17.4 cents per dollar of tax benefits. The second strongest friction is the instability of financing policies. Firms that commonly alter their debt ratio have a low marginal value of additional benefits. The same holds for firms that are constrained in their financing decision and cannot access external capital markets easily. The stability of financing policies is responsible for another discount of 9.3 cents per dollar. The weakest of the three forces are information asymmetries between shareholders and management that sum up to only a few cents per dollar of tax benefits. Shareholders who are not well informed about the firm reward tax benefits less in comparison to shareholders of more transparent companies. In combination, the three frictions offset tax benefits considerably, however, a substantial part remains unexplained. Depending on the empirical design, up to one third of the discount cannot be explained by these factors. Even in cases where it is most likely that none of the frictions applies, low marginal values of tax benefits are still observed. Other frictions in form of market inefficiencies such as market timing (Baker and Wurgler (2002)) and behavioral aspects (Malmendier, Tate, and Yan (2011)) that have a significant influence on firms’ financing decisions do not influence the marginal value of tax benefits, neither in economic nor in statistical terms. This study contributes to the literature on corporate capital structure in the following ways. First, the results of the study shed light on the controversy of the importance of target debt ratios that are determined through the tax deductibility of interest payments. While Leary and Roberts (2005) highlight the importance of the target adjustment process, Welch (2004) shows that firms do only little to offset deviations from target debt ratios. DeAngelo and Roll (2012) document a large variation of corporate debt ratios that seems to be inconsistent with target adjustment behavior. For firms with low marginal values of tax benefits, a dispersion and instability of debt ratios becomes plausible as the firm cannot increase its value sufficiently when adhering to a target leverage policy. Only for firms where shareholders attribute a high marginal value to tax benefits, management should follow a

3 strict target that exhausts tax shields. In line with Fama and French (2012), shareholders’ low marginal utility of tax benefits shows that target leverage ratios are rather of second order importance in financing decisions. Second, I emphasize shareholders’ utility in the valuation of corporate tax benefits. The unexplained discount of the value of tax benefits is due to shareholders’ low utility of cash flows through tax benefits which is founded on different economic reasons. Tax avoidance and tax sheltering policies play an important role in the managerial decision making process which cannot be separated from financing decisions (Shackelford and Shevlin (2001)). This effect is further amplified by incentive based compensation of corporate executives that lead managers to focus on tax avoidance (Desai and Dharmapala (2006)). This interaction of tax management and financing decisions leads to a low utility of tax benefits because tax sheltering provides more potential for generating shareholder value than tax shields from interest payments. These results indicate that managerial strategies might not focus on exhausting the full potential for tax benefits so that maximizing tax benefits is not a primary concern when choosing target capital structures. The results presented in this paper do not contradict the trade-off theory of capital structure. My results document the existence of the trade-off between tax benefits and costs of debt financing, however, they show that this trade-off is not able to fully explain corporate financing behavior. Despite low marginal values and low utilities, firms can adhere to dynamic target debt ratios that provide tax benefits, however, their speed of adjusting to the target debt ratios is expected to be rather slow. Simulations by DeAngelo and Roll (2012) show that a high variation in the time series of debt ratios can be consistent with time varying targets and slow speeds of adjustments. The cross-sectional differences in shareholders’ utility of tax benefits make it challenging to identify the targets as well as the target adjustment behavior. My study is structured as follows. In section II, I develop a parsimonious model to establish hypotheses on how a change in tax benefits translates into a change in shareholders’

4 wealth and how frictions materialize into a discount of the marginal value of tax benefits. In a Modigliani and Miller (1958) framework, shareholders utilize tax benefits completely, i.e. each additional dollar of tax benefits is fully reflected in shareholders’ wealth. The stepwise inclusion of new variables such as default costs and information asymmetries identifies the frictions that reduce the marginal value of tax benefits. The resulting econometric model is closely related to value relevance regressions on possibly inefficient markets (Aboody, Hughes, and Liu (2002)) and the estimation of the marginal value of cash holdings by Faulkender and Wang (2006). In section III, I discuss the sample selection of US firms and the choice of variables that are fed into the model. Following Graham (2000), I account for both corporate and personal taxes so that tax benefits equal the benefit of directing one dollar to investors as interest instead of equity gains. Section IV presents the empirical results on the marginal value of tax benefits, the identification of frictions, and its cross-sectional variation. Finally, section V discusses shareholders’ utility of tax benefits and section VI concludes.

II Linking tax beneﬁts and shareholders’ wealth

This section presents a framework for linking tax benefits, shareholder’s wealth, and excess returns. The identification strategy of the empirical part is based on this framework as it shows how the marginal value of tax benefits can be singled out. The model is hold in a parsimonious but general manner to provide empirical applicability.

II.1 A model for shareholder’s value of tax beneﬁts

Consider a representative firm in an economy where interest payments on corporate debt are deductible from corporate taxable income. Besides the existence of a corporate income tax, individuals have to pay taxes upon their personal income from interests, dividends, and capital gains. The economy could either be discrete or continuous in time which does not affect the results of the model. The firm can finance its operations either with debt, equity

5 or a combination of both. Upon this economy, I use a generalization of the Modigliani and Miller (1958) valuation formula which is one of the most general valuation formulas that account for the firm’s financing policy. At time t the value of the levered firm i denoted as

L Vi,t can be split up into three parts:

L U Vi,t = Vi,t + TBi,t − Ci,t . (1)

For the ease of notation, the subscripts i and t are suppressed for the reminder of the paper. Unless otherwise stated, all variables are time and firm-specific. V U denotes the present value of firm’s expected future EBIT after taxes, also referred to as the unlevered asset value which corresponds to a firm that is only financed with equity. TB is the present value of future tax benefits that results from differences in taxation of corporate and personal income. C represents costs associated with the firm’s financing policy and appears in form of default costs (Fischer, Heinkel, and Zechner (1989)), agency costs (Jensen (1986), adverse selection costs (Myers and Majluf (1984)), temporary misvaluations (Baker and Wurgler (2002)), or other factors such as behavioral aspects (Hackbarth (2009)). The three components of V L are not necessarily independent and may contain common factors. For example, indirect default costs such as the loss of future clients affects the present value of operations due to a loss of future business and at the same time the cost of debt capital due to an incline of firm’s default probability. Using annual changes and the accounting identity that the value of company’s assets is the sum of its debt value D and equity value E, V L = D + E, one can rearrange equation (1) to

∆E = ∆TB + ∆V U − ∆D − ∆C, (2) where ∆ denotes the annual change of the respective variable from period t − 1 to t. In an economy without other frictions but personal and corporate taxes, equation (2) yields

6 ∆TB = ∆E. Hence, a change in tax benefits of one dollar results in a change of equity value of one dollar. However, without this assumption, factors that trigger a change in tax benefits affect the other factors of equation (2) which dilute the observed change in E. Suppose there is a factor F which incorporates ∆V U , ∆D, ∆C, as well as all residual effects that lead to a change in equity value that does not stem from a change in tax benefits, then equation (2) reads

∆E = ∆TB + F. (3)

To receive an empirically testable equation without any restrictions on the coefficients, I add linear coefficients βj, j = 0, 1, 2 and an error term ε to the equation. Furthermore, all variables are scaled by last year’s value of equity El to mitigate heteroskedasticity where the subscript l indicates that the variable refers to the value of the prior fiscal year. Equation (3) translates into

∆E ∆TB F = β0 + β1 + β2 + ε . (4) El El El

This equation has the form of a linear regression specification. The left hand variable is the annual return on firm’s equity, while all variables on the right hand side are denoted as percentage of firm’s equity value from the last period. Following the methodology and its interpretation by Faulkender and Wang (2006), the coefficient β1 is the marginal value of one additional dollar of tax benefits for shareholders. Equation (4) has the power to estimate the marginal value of tax benefits but cannot distinguish between economic frictions that cause a variation in the shareholder’s net worth of one dollar of tax benefits. To single out their effect, I separate factors from F and combine them with a cross term of the change in tax benefits ∆TB. For example, let leverage Lev defined as the firm’s debt ratio in market values be a measure for default costs. Adding the

7 cross term ∆TB/El · Lev to the regression leads to

∆E ∆TB F ∆TB = β0 + β1 + β2 + β3 · Lev + ε . (5) El El El El

Now, the estimate of β1 is shareholder’s marginal value of tax beneﬁts under the assumption

that debt issues do not cause default costs. The estimate of β3 is the average discount that emerges due to the friction measured by Lev. Shareholders reward one additional dollar of

tax benefits on average with β1 + β3Lev, where Lev is the mean value of Lev. With this methodology, I am able to determine how shareholders translate different frictions into a discount of tax benefits.

II.2 Identifying frictions

The regression approach (5) is closely related to a value relevance regression under semi- strong information efficiency (Aboody, Hughes, and Liu (2002)). When taking it to the data, one has to find variables that provide a precise measure of the economic forces discussed in the previous section. The left hand variable in the regression is the firm’s annual stock return. Stock returns are subject to variation that stems from observable risk factors which are not directly related to tax benefits. Daniel, Grinblatt, Titman, and Wermers (1997), (DGTW), provide for each firm a benchmark portfolio that is based on the risk factors size, book-to- market, and momentum (Fama and French (1992), Carhart (1997)). These portfolios are constructed by annually sorting all firms into quintiles according to the three risk factors independently which results in 125 portfolios for each calendar year that provide a peer group for each firm year observation. The return on the firm’s respective benchmark portfolio can be used as benchmark return that accounts for the three risk factors. I substitute the dependent variable in the regression with the annual excess return on the firm’s stock over the annual return on the corresponding DGTW-portfolio to rule out variation that is not related to tax benefits. Let R denote the firm’s annual stock return and B the return on the

8 firm’s DGTW-portfolio, then the left hand side of equation (5) is substituted with R − B. The choice of explanatory variables is based on factors that influence tax benefits and stock returns. Variation in ∆TB can stem either from a shift of tax rates or a change in firm’s debt policy. Both factors are correlated with other variables that determine ∆E in equation (2). Therefore, the factor F in equation (5) has to consist of factors that determine changes in the unlevered asset value ∆V U , in debt policy ∆D, and costs of the financing policy ∆C. Following Goldstein, Ju, and Leland (2001), the unlevered asset value of a firm is a function of the present value of firm’s future earnings before interest and taxes. To capture the change in the unlevered asset value, I use the change in earnings before interest and taxes ∆EBIT as it indicates how firm’s profitability has changed within the fiscal year. Further sources for changes in the unlevered asset value are new capital issuances that firms use to finance new projects and acquisitions. These changes in the firm’s investment policy is approximated by the change in firm’s net assets ∆NA. To capture firm’s current financing policy as well as changes during the fiscal year, I include market leverage measures as the firm’s debt ratio Lev as well as the change in interest expenses ∆IE. Leverage as explanatory variable captures costs of debt financing that emerge at the current level of debt as a linear function. Further factors in C are captured with the help of a modified version of the Altman z-score Z (Altman (1968)) and the current level of tax benefits TB. The final regression equation reads

∆TB ∆EBIT ∆NA ∆IE R − B = β0 + β1 + β2 + β3 + β4 El El El El TBl ∆TB + β5 + β6Zl + β7Levl + β8 · Levl + ε . (6) El El

With help of this regression equation, I estimate the marginal value β1 of one additional dollar of tax benefits. Adding various cross terms, such as ∆TB/El · Lev identifies the effect

9 of the factors that diminish or increase the shareholder’s marginal value of tax beneﬁts. For

the remainder of the paper I suppress the scaling factor El for the ease of notation. In the following section, I will alter the speciﬁcation and substitute Lev with other variables that measure other sources of frictions.

III Data, variable deﬁnitions, and summary statistics

In this section, I discuss the sample selection, variable definitions and the summary statistics of the sample. The sampling period ranges from 1981 to 2010 and covers 59,748 firm-year observations from the US economy. All accounting data stems from Compustat, market value of equity is taken from the CRSP, and equity analyst forecast from I/B/E/S. Government and municipal bond returns as well as the Consumer Price Index (CPI) are provided by the Federal Reserve Bank of St. Louis (ALFred).1 Data on marginal corporate tax rates is kindly provided by John Graham.2 I exclude all observations with missing information that is required to construct the test of this paper and all data is deflated to 2010 US dollar using the monthly CPI.

III.1 Estimating marginal tax rates

The central variable in this empirical study is the tax benefit that stems from corporate debt issuance. Modigliani and Miller (1958) define tax benefits as the savings that result from deducting interest payments from taxable earnings and calculate them as the product

of the corporate tax rate τC and the current level of interest bearing debt D. Miller (1977) notes that tax savings at the corporate level can be partly oﬀset by investor’s personal tax

rate τP . Following the approach of Graham (2000), I incorporate personal and corporate taxes and deﬁne the beneﬁt Ben of directing one dollar to investors as interest instead of

1All data obtained from the Federal Reserve Bank of St. Louis can be downloaded from http://alfred.stlouisfed.org/. 2The data is obtained from John Graham’s homepage https://faculty.fuqua.duke.edu/ jgraham/.

10 equity as

Ben = (1 − τP ) − (1 − τC )(1 − τE) . (7)

Equation (7) is the diﬀerence between investor’s after tax income on interest payments and his after tax income on equity gains. Interest payments are taxed at the personal level at the rate τP while equity gains are taxed twice, once at the corporate level at the rate τC and

again at the personal level at the rate τE. Under the assumption of debt being perpetual, the present value of a ﬁrm’s tax shield is

(1 − τP ) − (1 − τC )(1 − τE) TB = rDD (8) (1 − τP )rTB

where D denotes the value of interest bearing corporate debt, rD ﬁrm’s coupon rate so that rDD equals the coupon payments. rTB is the discount factor for the tax shield. If tax shields

are as risky as debt and hence have to be discounted at the same discount rate, rD and

rTB cancel out which simplifies the estimation of the equation significantly. The assumption that debt is perpetual implies that firms keep the amount of debt outstanding constant but not its level of leverage. As the company growths, formula (8) only incorporates the present value of debt that is currently outstanding. Hence, it is more likely that it underestimates than that it overestimates the present value of future tax benefits because additional future debt issues are not accounted for. In the proceeding analysis, I will present an alternative measure of tax benefits that softens the assumption of perpetual debt and only uses benefits that are realized in the current period. Following Green (1993), I calculate the personal tax rate as the implicit tax rate that

results from the diﬀerence in yields on taxable bonds rG and tax exempt bonds rM of the same maturity and risk class:

rM τP = 1 − . (9) rG

11 The implicit personal taxes on interest income vary by definition only in the time dimension but not across firms or investors. For the tax exempt bonds, I use the monthly yield on an index of municipal bonds with a maturity of 20 years. The corresponding taxable bond is the US government bond with the same maturity. From January 1987 up to September 1993 there is no data on a 20 year government bond available. I interpolate missing yields using a linear regression of yields on 20 year government bonds on the yields of government bonds with maturities of 10 and 30 years.3 Longstaff (2011) proposed to estimate implicit personal tax rates with weekly data on a municipal bond swap index (MSI). His procedure matches the maximum Federal individual income tax rate well, however, the sampling period is rather short as the time series of the MSI starts in 2001. Other approaches, e.g. Fortune (1996) and Poterba (1989), use municipal bonds of different maturities to estimate implicit tax rate. I use the 20 year bond because the noise in the 20 year bond yields is smaller than of the short-term yields which leads to more precise estimations of the personal tax rates. The results of this study remain virtually the same if I calculate the personal tax rate from bonds with a maturity of 5 years. I calculate annual yields from monthly yields to be able to match each firm’s annual statement with the corresponding tax rate for the firm’s fiscal year which does not necessarily coincide with the calendar year.

The marginal corporate tax rate τC is the marginal corporate tax rate before financing from the studies Graham (1996b) and Graham (1996a). The tax rates are based on a simula- tion of corporate earnings before financing decisions using firm-specific historic information to forecast future earnings and at the same time accounting for various characteristics of the US tax code, such as the investment tax credit, loss carryforward, and carryback tax opportunities. The result is the tax rate that a firm has to pay on one additional dollar of earnings. Other methodologies to calculate marginal tax rates are available, however, I

3The regression formula for estimating the missing values of the cumulative yield on the government bond with a maturity of 20 years rG is estimated as rG = 0.0218 + 0.4238 r10 + 0.5546 r30 where r10 and r30 are the annual yields on government bonds with a maturity of 10 and 30 years, respectively, calculated from monthly data. The estimated coefficients are based on a data set using 307 monthly observations between 1981 and 2010. The adjusted R2 of this linear regression is 0.9989 and all coefficients are significant at a 0.1% level.

12 choose Graham’s version of the marginal tax rate because Plesko (2003) points out its superior ability in capturing tax attributes. Moreover, it has the best performance in estimating the unobservable tax rate from non-publicly disclosed tax balance sheets using commercial balance sheet data. Dividend payments and long-term capital gains are taxed at the personal level at the rate

τE. Following the clientele hypothesis (Scholz (1992)), investors are sensitive to personal tax rates and dividend yields when choosing equity investments. For example, an investor with a high personal tax rate favors stocks with low payout ratios to avoid tax payments. Therefore, the personal tax rate is estimated with ﬁrm-speciﬁc information as a function of the dividend yield, long-term capital gains, and the personal tax rate. Following Graham

(2000), the personal tax on equity income τE equals

τE = (d + (1 − d)gα)τP . (10)

The payout ratio d is calculated as dividends divided by a three-year moving average of net income. The moving average helps to smooth out temporary deviations and negative earnings. d is restricted to the domain of [0, 1] and replaced with 0 or 1 if the values lie outside of the interval which happens in only 3.2% of the observations. The proportion g of long-term capital gains that is subject to taxation is equal to one but equals 0.4 prior to 1987. α measures the beneﬁts of deferring capital gains and equals 0.25 (Feldstein and Summers (1979)).

The net benefits of a single dollar of interest Ben, the marginal corporate tax rate τC and the tax rate on personal equity income are by definition firm-year specific leading to

59,748 observations while the personal tax on interest income τP is a monthly time series of 360 observations. Table 1 summarizes the descriptive statistics of the tax rates and the net tax beneﬁts. The average net beneﬁt Ben of directing a single dollar to investors as interest rather than equity is 0.207, has a standard deviation of 0.125 and ranges between

13 -0.192 and 0.453. For investors of firms with positive net benefits, it is favorable to issue debt because of low personal taxes and high taxes on corporate income. In contrast, 11.5% of all firms exhibit negative net benefits. For investors of these firms, it is not favorable to issue debt because they pay higher taxes on interest income than on equity income and marginal corporate tax rates are close to zero. The marginal corporate tax rate is on average 0.308 and varies between the observation by 0.127. The highest corporate tax rates of 0.51 were established prior the Tax Reform Act of 1986 and dropped afterwards with a maximum merely below 0.40. 2,139 of the firm- years have a marginal tax rate below 0.01 which can be caused by net losses, carry forwards and backwards. The personal tax on interest income ranges from 0 to 27.5 percent and is higher in the earlier sample period than in recent times. Personal tax on equity income is significantly smaller and amounts on average only 3.2% driven by low payout ratios and the factor α. The presented estimates of personal tax rates correspond to estimates from earlier studies using comparable data (Poterba (1989)).

III.2 Tax beneﬁts and ﬁnancial statement data

The present value of tax benefits as defined in equation (8) is a function of the firm’s current level of interest bearing debt outstanding D. I define D as debt in current liabilities (dlc) plus long-term debt (dltt) where the names in parenthesis identify the respective Com- pustat items. Market leverage Lev equals debt divided by the sum of debt and market value of equity. The market value of equity equals the number of adjusted shares outstanding times the adjusted stock price from CRSP at the end of the firm’s fiscal year. Corporate earnings before interest and taxes EBIT is calculated as earnings before extraordinary items (ib) plus interest (xint) and deferred taxes (txdi) and investment tax credit (itci). Missing information on deferred taxes and investment tax credit are replaced with zero to prevent a drastic decrease in sample size. Net assets NA are total assets (at) less cash and equivalents (che). All variables are scaled by the market value of equity at the beginning of the fiscal

14 year. Following Leary and Roberts (2010), the z-score Z is calculated as the sum of 3.3 times EBITDA (oiadp), sales (sale), 1.4 times retained earnings (re), and 1.2 times working capital (wcap) all divided by market value of equity at the end of the last fiscal year. The original version of the z-score by Altman (1968) is divided by total assets instead of market equity which is altered for consistency with the definition of the other variables. I define the annual stock return R using CRSP data. The DGTW returns B are generated from Compustat and CRSP data with the help of the program code by Rabih Moussawi and Gjergji Cici kindly provided via WRDS. Each June, a firm is sorted into one of 125 portfolios. Each portfolio is formed on an independent sort into quintiles of all CRSP and Compustat firms according to their market capitalization (size), book-to-market value of equity and momentum (historic return). The annual benchmark return is the cumulative return of the corresponding DGTW portfolio within the 12 months of the firm’s fiscal year. Finally, the annual excess return R−B is the annual stock return over the DGTW benchmark. All input variables of the following regressions are trimmed at the 0.5% tails with exceptions of variables that are naturally bounded on either side of its tails, for example, market leverage is not trimmed at the lower tail because it cannot fall below zero. Table 2 summarizes all variables used in the following analyses. Tax benefits are presented in two ways, once as fraction of market equity as it is used in the regression and again as fraction of total assets to compare the estimates with results from other studies. On average tax benefits amount to 11.5% of market equity and 5.3% of total assets while the median values are notably smaller indicating a right skewed distribution. The estimates of tax benefits correspond to gross benefits because no frictions but taxes and the discount rate of debt are included when calculating the marginal values. Despite differences in methodology, the descriptive statistics of tax benefits correspond to results from prior by Graham (2000), Korteweg (2010), and van Binsgergen, Graham, and Yang (2010). The independent variable, the excess return on the DGTW benchmark, has an average of -0.038 and a median of -0.102 picturing as usual a right skewed distribution of excess returns. Market leverage

15 Lev is on average 0.239 with a standard deviation of 0.219 indicating a large variety of ﬁnancing policies. The summary statistics of the remaining variables correspond to the results presented in Faulkender and Wang (2006) and, hence, a discussion is omitted.

IV Empirical results

This section contains the empirical results for the value relevance model presented in section II. I begin by estimating the marginal value of tax benefits for the average firm. Then, I analyze how various frictions materialize into costs that reduce or increase the marginal value of tax benefits. The frictions include default costs, stability of leverage, financial constraints, and flexibility as well as information asymmetries. Finally, I provide an estimate of the implied discount rate that shareholders implicitly use to price marginal tax benefits and conclude that the shareholders’ utility of tax benefits is lower than of other claims.

IV.1 Marginal value of tax beneﬁts in the cross-section

The main focus of the paper is to estimate the marginal value of one additional dollar of tax benefits. The scaling of the explanatory variables in the regressions allows to interpret the estimated coefficients as the marginal value of one additional dollar in the respective explanatory variable. The results obtained from estimating the model (6) are listed in table 3. Columns (1), (2), and (3) provide different approaches to estimate marginal values of tax benefits while column (4) reports a model without any tax variables. For shareholders of the average firm, the marginal value of one additional dollar of tax benefits is 0.261 dollars or equivalently 26.1 cents. 73.9 cents of the dollar are not reflected in the share price either due to friction or investors’ preferences on sources of capital gains. The summary statistics in table 2 document that the gross benefits of debt financing amounts on average to 5.4% of the levered firm value. The estimated discount in the regression model of

16 73.9% results in a net benefit of only 1.41% of firm’s asset value. This estimate is significantly smaller than the net benefits predicted by models of capital structure, such as in Chen (2010) or Bhamra, Kuehn, and Strebulaev (2010). The low estimate of the marginal value raises questions how different frictions are priced on the market that might not be captured in standard asset pricing models. To explore if shareholder’s anticipation of tax benefits depends on the current level of tax benefits, I perform an additional analysis. In column (2), the regression is extended by an interaction term of the change in tax benefits and the level of tax benefits at the beginning of the fiscal year. The estimation results show that the marginal value of tax benefits is declining in the level of tax benefits. For a firm without any tax benefits at the beginning of the fiscal year, the first dollar of tax benefits at the end of the year is rewarded by 44.4 cents. Firms can have zero tax benefits either due to a zero leverage policy or because of an equivalence of taxation between shareholder’s equity and debt income. In either case, there are additional yet unidentified frictions that lead to such a low estimate even though the firm has currently no tax benefits. For the average level of tax benefits, the marginal value is 0.444 − 0.492 · 0.115 = 0.387 and further declining in the level of tax benefits. For the most extreme cases, the marginal value tends to zero and the two coefficients nearly cancel out leading to a zero benefit of an additional dollar of tax benefits. This analysis shows that there is substantial variation in the value of tax benefits across firms, however, it cannot differentiate between the sources of frictions. In specification (1) and (2), the observed present value of the change of tax benefits is one of the independent variables. If all firms in the same DGTW portfolio increase tax benefits in a similar manner, then the benchmark returns should already account for the change in tax benefits and the excess return is only driven by the unexpected part of the change in tax benefits. The same holds if financial markets anticipate changes in tax benefits at the beginning of the fiscal year. To test if the low estimates of the marginal value can be explained by actions of firms in the DGTW portfolios and investors’ expectations at the

17 beginning of the fiscal year, I form estimates of the unexpected part of the change in tax benefits in two ways. For the first estimate, I predict the expected change in tax benefits through a moving average of the change in tax benefits within the last 3 fiscal years. The

excess change over the moving average is the unexpected change in tax beneﬁts ∆TBMA. The

second estimate of the unexpected change in tax benefits ∆TBDGTW is the excess change over the median change in tax benefits of a firm’s DGTW portfolio-year. Columns (3) and (4) report the results of using the new versions of changes in tax benefits as independent variables. The marginal value of unexpected tax benefits is virtually the same as in the original version. The market rewards the expected and unexpected part of tax benefits to a similar extent. One can conclude that the observed discount of tax benefits does not stem from investors’ expectation on the change in tax benefits. Hence, I will use the annual change of tax benefits for the remainder of this study. Column (5) of table 3 shows a benchmark regression of excess returns on all explanatory variables but tax benefits. The correlation between tax benefits TB, interest expenses IE, and leverage lev leads to a small change in the coefficients. All other estimates are comparable between the different approaches. The adjusted R2 indicates that tax benefits identify an additional source of variation in excess returns. The incremental explanatory power is substantial as it increases from 0.170 up to 0.203.

IV.2 Default costs

So far, it has been shown that shareholders materialize the value of tax benefits only partially and that the marginal value exhibits a cross-sectional and within firm variation. However, frictions causing low marginal values are not yet identified. In the literature on trade-off models of optimal financing choices, most commonly default costs serve as friction that offsets tax benefits (Fischer, Heinkel, and Zechner (1989) and Leland (1994)). The valuation formula for tax benefits in equation (8) partly accounts for default costs because future tax benefits are discounted at the same risk adjusted interest rate as debt. Moreover,

18 Graham’s marginal tax rates are based on simulations of earnings before financing decisions to account for the possibility that future earnings might be negative and hence the firm will not have tax benefits in the current period. However, tax benefits might cease before default if corporate earnings before interest and taxes are negative and firms change their financing strategy due to upcoming default. As a result, there is still unidentified part of default costs left in the estimates. Table 4 reports the results of three different approaches to measure default costs. First, an interaction term of leverage and tax benefits measures default costs associated with the amount of debt outstanding. Intuitively, default costs increase with the leverage ratio. Leverage reduces the marginal value of one dollar of tax benefits on average by 0.726·0.239 = 0.174 dollars as shown in column (1). A firm without debt outstanding faces most likely no default costs stemming from coupon payments. For such a firm, the regression yields a value of 0.671 dollars for the first dollar of tax benefits. This estimate is significantly larger than the results of table 3, however, the full discount cannot be attributed to default costs alone because other frictions vanish as well when there is no debt outstanding. Nevertheless, the regression documents a substantial discount that can partly be classified as a discount due to default costs but default costs alone cannot explain shareholder’s perception of tax benefits. Default is more likely for firms with a high earnings volatility. To provide a second measure of default costs, I include an interaction term of the standard deviation of firm’s earnings from the last 12 fiscal quarters into the regression. Earnings are defined as EBIT to receive an earnings measure that excludes financing and taxation choices. Column (2) shows that shareholders attribute a lower marginal value of tax benefits to firms with a high volatility of earnings. A firm with almost constant earnings has only a marginal value of tax benefits of merely below 0.362. Altman’s z-score is a frequently used measure of default risk. It combines various firm characteristics and forms them into a variable that can be used as cross-sectional comparison

19 in default probabilities. A reduction in default risk measured by an increase in the modified version of the z-score ∆Z leads to an increase in the marginal value of tax benefits. One standard deviation of z-score yields a change in the marginal value of tax benefits of 4.515 · 0.017 = 0.076 dollars. All three approaches document a negative effect of default costs on the marginal value of tax benefits. However, none of the approaches can explain the originally observed discount of the marginal value of tax benefits. Column (4) shows that the combination of low leverage, low earnings volatility, and a high z-score leads to a marginal value of tax benefits of 0.744.4 Even in cases where it is most likely that the market does not price default costs of firm’s financing policy, the marginal value of tax benefits is significantly below one dollar. On the other extreme, default costs can completely offset tax benefits only at very high levels of leverage which is the case for only the most extreme observations. Hence, a large fraction of shareholder value is not explained by default costs.

IV.3 Stability in leverage, ﬁnancial constraints, and ﬂexibility

The value generated through financing policies partly depends on the persistence and stability of financing policies. The literature offers contradicting views on the stability of corporate debt ratios. Lemmon, Roberts, and Zender (2008) identify large firm-fixed effects that contribute substantially to explaining cross-sectional variation in debt ratios and conclude that leverage ratios converge over time. In contrast, DeAngelo and Roll (2012) state that “stability is the exception, not the rule, [...] substantial instability is the norm”. If firms commonly adjust their debt ratios to not previously defined targets, then it becomes more complicated for shareholders to estimate the present value of future tax benefits and hence they apply a stronger discount to expected future tax benefits. To test the influence of stability of leverage on the value of tax benefits, stability of leverage is measured by the standard deviation of the firm’s leverage ratio within the last 12 fiscal quarters. On aver-

4For a ﬁrm with leverage and sd(EBIT ) both equal to the 25% percentile and Z as in the 75% percentile, the marginal value is: 0.693 − 0.048 · 0.662 − 0.009 · 0.958 + 4.823 · 0.019 = 0.744

20 age, leverage ratios change from quarter to quarter by 6.3 percentage points (table 2) which indicates that firms adjust their debt ratio rather often. Column (1) of table 5 shows that the stability of leverage ratios influences the marginal value of tax benefits. Shareholders price tax benefits of firms with unstable debt ratios at a higher discount than of firms with persistent financing policies. The average standard deviation of debt ratios reduces the marginal value of tax benefits by 1.484 · 0.063 = 0.093 dollars. Firms that follow a strict target capital structure and readjust deviations from the target immediately are hardly exposed to these costs. Firms with the most stable debt ratios have a standard deviation of their debt ratio less than 2.3%. Shareholders of these firms expect tax benefits to be more persistent and price each dollar of benefits in the range of 48.0 to 51.9 cents. These results highlight the importance of the readjustment process of leverage ratios (Leary and Roberts (2005)). Firms with high speed of adjustments are rewarded by their shareholders through higher values of their tax benefits. The stability of debt ratios is on the one hand endogenous because management has the choice of issuing and substituting capital but on the other hand is exogenously determined by financial constraints. Firms that cannot frequently access capital markets either cannot readjust their debt ratio or they are forced to choose costly financing means. I follow Ko- rajczyk and Levy (2003) and classify a firm in a given firm-year as financially constraint if it meets all of the following criteria. The firm must not distribute funds to shareholders in form of dividends and must not have a net repurchase of debt and equity. At the same time, the market-to-book ratio of firm’s assets (Tobin’s Q) has to be larger than one. With help of the second condition, all firms that face constraints from upcoming default are excluded from the sample of financially constraint firms and it is possible to distinguish between financial constraints and default costs. Firms that are classified as financially constraint face high costs of accessing capital markets and cannot choose freely between different financing means. 11,207 (18.8%) of all firm-years stem from firms that are financially constraint. The definition of financial constraints only focuses on one fiscal year so that firms can change the

21 classification over time. In column (2) of table 5, an indicator variable that equals one if the firm-year is classified as financially constraint is interacted with the change in tax benefits to single out the effect of financial constraints on the marginal value of tax benefits. The regression provides the astonishing results that shareholders do not reward tax benefits of financially constraint firms at all. The estimated coefficient of the interaction term cancels out the marginal value provided by tax benefits. This result is of special importance for studies that test the predictions of trade-off models of optimal capital structure. For at least 18.8% of the sample, it is not possible to readjust leverage to a given target ratio while at the same time shareholders anticipate this inability and do not reward tax benefits at all. Taking a look at financial constraints from the opposite side is to analyze financial flexibility. Firms that can obtain funds timely and inexpensively to pursue investment opportunities and are sufficiently able to react to cash flow shocks are considered as financially flexible (Graham and Harvey (2001)). The literature offers different approaches for measuring this flexibility. I follow Faulkender and Wang (2006) and Almeida, Campello, and Weisbach (2004) and classify a firm as financially flexible if firm’s payout ratio is in the top 25-percentile of the respective calendar year. 14,951 of all firm-year observations are classified as financially flexible. The authors provide additional measures such as firm size and bond ratings, however, the DGTW benchmark returns already account for size effects and the previous analysis of default costs is closely related to bond ratings. Table 5 shows that firm’s financial flexibility provides shareholders with a higher marginal value of tax benefits. The estimated coefficient yields an increase due to financial flexibility of 0.201 for each dollar of tax benefits. In column (4) leverage as a measure of default risk as well as all three measures of stability, constraints, and flexibility are included in the regression. Even though all three measure are related to leverage, there is still an economically and statistically significant effect of stability and financial constraints which shows that the frictions help to explain

22 cross-sectional differences in the marginal value of tax benefits. However, in neither case shareholders fully reward an additional dollar of tax benefits. Even in the most extreme and unlikely scenario that a firm does not face any default costs, is financially unconstrained and has a stable financing policy, there is still a discount of roughly 10% to the first dollar of tax benefits.

IV.4 Information asymmetries

Information asymmetries between stockholders and managers are the driving force in three of the most prominent capital structure theories. Jensen and Meckling (1976) show that agency costs of equity capital can arise due to insufficient monitoring of managers. In the market-timing theory (Baker and Wurgler (2002)), managers exploit temporary misvaluations by timing equity issues and share repurchases and in the pecking order theory (Myers and Majluf (1984)) information asymmetries lead to a preference for external funds. In each theory, shareholders apply a discount to the stock price that arises from the information asymmetries, however, it is not stated how tax benefits are affected. In this section, I will show how information asymmetries lead to a discount of tax benefits. Equity sell-side analysts provide financial markets with timely and price-relevant information on the current and expected financial situation of a firm (Womack (1996)). Since information gathering is costly, shareholders partly rely on the information provided by pro- fessional analysts. If a stock is covered by at least one sell-side analyst, then information asymmetries between stockholders and managers are reduced because analysts provide financial market with timely and relevant information on covered firms. Hence, information asymmetries are measured by a dummy variable that equals one if there is at least one observation from a sell-side analyst in I/B/E/S covering the firm during its fiscal year. On average, 68.6% of all firm years are covered by at least one analyst and the fraction increases from 59.7% in 1983 up to 90.1% in 2010. I exclude all observations prior to 1983 because there are either no or only insufficient observations in the I/E/B/S database each year. The

23 second measure of information asymmetries is the disperson of analysts’ earnings forecasts. If analysts strongly disagree on future earnings, then the dispersion is high and it is most likely that there are high information asymmetries not only between analysts but between management and the market as well. The average forecast dispersion measured as the standard deviation of analysts’ most recent earning per share forecasts for a given firm-year scaled by the firm’s stock price at the beginning of the fiscal year is 0.028. Table 6 explores the relation between shareholders’ value of tax benefits and information asymmetries. Shareholder reward tax benefits from firms with high information asymmetries less. A discount of 10 cent per dollar can be attributed to the fact that the firm is not covered by any analyst and hence it is likely that shareholders are not provided with sufficient information in comparison to other firms on the market. For all firms that are covered, the dispersion of earnings forecast indicates the extent of information asymmetries. Column (2) shows that the forecast dispersion reduces that marginal value of tax benefits. Shareholders place a higher value on a single dollar of tax benefits if analysts agree on the prospects of the firm. The average discount that results from the forecast dispersion is 0.021. Even though the results on information asymmetries are somewhat weaker than in the previous analyses, market prices reveal that information asymmetries serve as a friction for the marginal value of tax benefits.

IV.5 Model-free tax beneﬁts

In this section, I provide an alternative approach for estimating the marginal value of tax benefits that is only based on data from firm’s current fiscal year, i.e the realized interest payments and the marginal tax rate. In the previous sections, tax benefits TB are calculated as the present value of all expected future tax benefits. This calculation puts up assumptions on the future level of debt, its maturity, and the discount rate that shareholders apply to future tax benefits. To circumvent all three assumptions and to exclude that they drive the results, I form an alternative version of tax benefits that only uses information from firm’s

24 current fiscal year. I define the tax benefits TBIE that are realized during the current fiscal year as

TBIE = [(1 − τP ) − (1 − τC )(1 − τE)] · IE (11) which is the difference in taxation of interest payments and equity gains multiplied with firm’s interest expenses IE during the fiscal year. The whole term is scaled by the market value of equity at the beginning of the fiscal year so that the assumptions for the interpretation of marginal values of (6) are fulfilled. Table 7 explores the results of estimating shareholders’ marginal value of this alternative version of tax benefits with the help of the value relevance regression (6). If a firm increases tax benefits by one additional dollar in the current period, then shareholders reward this change with 1.814 dollar. A change in the market value of equity is on the one hand driven by the realized values from the current period but on the other hand driven by the change of expectations on future cash flows. Hence, the change in shareholders’ wealth is larger than the realized tax shield in the current period. Shareholders do not only anticipate the change in the realized tax benefits but a change in the expectation of future tax benefits as well. The estimated marginal value is shareholders’ value of the sum of the change of the recent change in tax benefits and the present value of the change of expected future tax benefits. Depending on maturity and discount rate, the sum exceeds the value of current tax benefits. Same as in the previous analysis, shareholders’ marginal value of tax benefits decreases with the level of tax benefits as well as with the level of debt outstanding reported in column (3) and (5) of table 7. Using the excess change in tax benefit over a three-year-moving-average results in an estimate that is larger than in the original setting. Again, the results reflect the previously established implications.

25 V Further possible explanations

The previous analyses document that shareholders’ marginal value of one additional dollar in tax benefits is substantially smaller than its fundamental value on a frictionless capital market of one dollar. The identification of frictions reveals that default costs generate the largest friction while the frictions stemming from the instability of the financing policies, financial constraints, and information asymmetries are rather small. Even for a firm that is most likely not to be exposed to any of these frictions, shareholders do not fully reward tax benefits and apply a discount that reduces the market value of the generated tax benefits substantially. In this section, I discuss further sources where low marginal values of tax benefits can stem from.

V.1 The dispersion of leverage ratios

A related branch of literature offers a view of financing decisions which is consistent with my results. DeAngelo and Roll (2012) document that for a given firm the difference in leverage ratios over time grows remarkably as the time interval increases. For two observations several years apart, all similarities seem to be vanished and only few firms keep leverage consistently below 50%. Denis and McKeon (2012) analyze large debt issues that drive firms away from target leverage ratios and observe that these firms return to their target debt ratio only in a few cases. Finally, Welch (2004) shows that management does only little to offset deviations in market leverage. These observations can be explained with my results. Instability of debt ratios becomes plausible once the marginal value generated through an additional dollar of tax benefits does not add sufficiently value to the firm. If the management does not persue a financing strategy that is based on tax benefits, then a substantial variation in the time series of the leverage ratio of a firm emerges.

26 V.2 Tax beneﬁts and capital structure theories

Frank and Goyal (2009) summarize empirical determinants that are related to factors from models of financing decisions. A variable that is related to the choice of issuing debt or equity does not necessarily have to be related to the value of tax benefits. In untabulated results, I find neither economically nor statistically significant results for various of their variables, e.g. tangibility of assets, expected inflation, and R&D intensity. Explanations for financing decisions that are based on market inefficiencies such as equity market-timing and behavioral aspects do not yield explanatory power for a cross-sectional variation in the marginal value of tax benefits either. The marginal value of tax benefits is neither related to investor sentiment factors (Baker and Wurgler (2006)) nor hot IPO phases (Alti (2006)). If these factors contribute to the marginal value, then their economic power is of negligible size. Theoretical models of optimal capital structure offer an alternative view on the estimated marginal values. In the structural-equilibrium framework of Bhamra, Kuehn, and Strebulaev (2010) and Chen (2010), management acts in best interest of shareholders and chooses a leverage ratio that maximizes the value of the levered firm through future tax benefits. For an optimally levered firm in such an economy the marginal value of an additional dollar of tax benefits is completely offset by default costs and other frictions because a change in tax benefits cannot further increase the levered firm value. The marginal value of tax benefits equals zero if the firm is optimally levered, positive if the firm is underlevered and negative if the firm is overlevered. The results in column (1) of table 4 show that the marginal value is zero if the firm has a leverage ratio of 0.881 which lies beyond the 95% percentile of the distribution of leverage ratios, hence it is rather an exception than the rule to observe a marginal value of zero. For 95% of all firms, the marginal value of tax benefits is larger than zero and shareholders anticipate a positive although small marginal value of additional tax benefits. If firms target optimal leverage ratios but deviate from targets when facing shocks, lever-

27 age ratios are distributed on the left as well as on the right of the target leverage ratio. The distribution of leverage ratios does not mirror this picture so that one can conclude that if target leverage ratios exist, then the marginal value of tax benefits is still positive for the targets. Moreover, target leverage ratios cannot purely be the result of balancing tax benefits and frictions of debt financing because only in very few cases tax benefits are fully offset by the frictions. This finding does not contradict the validity of trade-off models, it rather tests the precision of the implications. As stated by Miller (1977) and Ju, Parrino, Poteshman, and Weisbach (2005), balancing of default costs and tax benefits can be thought of as an unequally balanced mixture such a “horse-and-rabbit stew”. Bankruptcy costs alone are too small to offset gains through tax shields. Despite the low explanatory power of the pecking order (Chirinko and Singha (2000) and Leary and Roberts (2010)), the theory can help to explain why firms do not exhaust to full potential of tax benefits. Under the assumptions that capital issues are driven by the demand for investments, then the residual amount of financing sources that is left after exhausting internal funds can be insufficient to lever the firm to some optimal debt ratio that provides the maximal amount of tax benefits. The same can hold for firms with insufficient investment and growth opportunities. However, untabluated results do not yield a significant relationship between the marginal value of tax benefits and investment opportunities.

V.3 Shareholders’ utility of tax beneﬁts

The low marginal value of tax benefits indicates that shareholders have a low utility of the value generated through a firm’s financing policy. There are various possible reasons why shareholders can attribute a low utility to tax benefits that are challenging to capture empirically. From managers’ perspective, tax shields do not rank as a top priority among the determinants of financing decisions (Graham and Harvey (2001), Bancel and Mittoo (2004), and Brounen, de Jong, and Koedijk (2004)). In surveys, less than 10% of the executives name

28 investors’ taxes on interest income to be important and less than 50% state that interest tax savings contribute to their decision to issue debt. Financial flexibility, credit ratings, and the level of interest rates are only a few of the factors that are of superior importance. When it comes to the decision of issuing equity, investors’ taxes of equity income range with about 5% among the least important factors. Hence, the management conveys a view that tax benefits are not their primary concern which can translate into a low utility of tax benefits for shareholders because they cannot expect them to be persistent. Anecdotal evidence from recent events show common practices of tax sheltering. As reported in the Wall Street Journal (2013), “Apple [Inc.] used technicalities in Irish and American tax law to pay little or no corporate taxes on at least $74 billion over the past four years”. If firms have the power to minimize their tax rate, then the value that can be saved through minimizing tax payments is by definition substantially larger than the value generated through tax shields. Therefore, tax avoidance and tax sheltering are commonly applied corporate policies. However, tax management and financing decisions are two aspects that can hardly be managed separately because tax avoidance and tax sheltering influence other organizational goals (Shackelford and Shevlin (2001)). Tax avoidance is often attractive to firms due to a compensation structure that is based on high-powered incentives (Desai and Dharmapala (2006)). An exogenous factor that triggers tax avoidance is documented by Black and Hoyt (1989). States and cities have incentives to attract firms by minimizing tax rates even at the cost of social welfare losses. Finally, tax benefits are an indirect way for generating value and can be compared to an opportunity cost that emerges if the company had used different financing resources. They are not explicitly stated in financial statements and have to be calculated by combining corporate and personal tax rates. An inspection of a sample of 300 full text research reports reveals that sell-side equity analysts address tax benefits explicitly only in rare cases. In cases where tax benefits are mentioned, they are usually listed as a side note or implicitly incorporated in a valuation model but not reported explicitly. The reports usually focus on

29 revenue growth, earnings per share, and target share prices but rarely mention the level of tax beneﬁts explicitly. Hence, they are not directly visible to investors which could translate into a low marginal utility.

VI Concluding thoughts

More than half a century after Modigliani and Miller’s seminal paper of 1958, the literature has established tons of implications for optimal corporate financing policies. However, Myers’ capital structure puzzle (Myers (1984)) is still far from being solved. DeAngelo and Roll’s (2012) instability of debt ratios and the variety of corporate financing policies indicates that Modigliani and Miller’s irrelevance theorem of capital structures is not as implausible as it seems due to its restrictive assumptions. This paper attempts to close the gap between theoretical implications on optimal financing policies that are based on tax benefits and and the empirical counterparts of observed financing behavior. Besides commonly addressed frictions such as default costs, financial stability, and information asymmetries, I document that shareholders discount the value tax benefits more strongly than predicted by theory which suggests that they have a low utility of future tax benefits. A low utility of tax benefits can emerge due to the importance of tax incentives for corporate executives (Graham and Harvey (2001)), its visibility for shareholders, and managements’ focus on minimizing tax payments. Further insights on the motives why managers do not exhaust the full potential for tax benefits and why shareholders discount tax benefits stronger than predicted by theory can be gained from different field in financial economics. Cross-border mergers and acquisitions that involve targets or acquirers that operate in countries with extremely low corporate tax rates can give further insights on the relative importance of tax avoidance in comparison to tax benefits from financing policies. As well, debt covenants and the power of creditors in financing decisions can keep firms from levering up to higher debt ratios.

30 Differences in the treatment of future cash flows within a firm can be used to enhance asset pricing models. Usually a unique discount rate is applied to the sum of all future cash flows of a firm. As the market participants reward tax benefits less than operating income, future research could treat cash flow from tax shields differently than operating income. The cross-sectional variation in the marginal value of tax benefits can be exploited by market participants through an identification of firms with the most valuable tax benefits and establishing a trading strategy that exploits possible market inefficiencies.

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35 Table 1: Summary statistics of tax variables. The table reports the summary statistics for the tax variables in our sample. The sample period ranges from 1981 to 2010 and uses data from ALFred, Compustat, and John Graham’s database of marginal tax rates. Ben is defined as (1 − τP ) − (1 − τC )(1 − τE). τC is the marginal corporate tax rate before financing from Graham (1996b). The tax rate on personal interest income τP is calculated as the implicit tax rate that results from difference in yields on taxable and tax exempt bonds. The tax rate on personal equity income equals τE = (d + (1 − d)gα)τP where d is the dividend payout, g equals 1 but prior to 1987 is 0.4 and α is 0.25. Ben, τC and τE are firm-year specific variables while τP is a monthly time series.

mean sd min p25 median p75 max N Ben 0.207 0.125 -0.192 0.183 0.232 0.292 0.453 59,748 τC 0.308 0.127 0.000 0.291 0.348 0.356 0.510 59,748 τP 0.121 0.055 0.000 0.084 0.130 0.161 0.275 360 τE 0.032 0.019 0.000 0.019 0.031 0.041 0.200 59,748

Table 2: Summary statistics of firm characteristics. This tables provides the summary statistics for the variables used in the empirical study constructed with data from Compustat, CRSP, ALFred, and I/B/E/S. The sample consists of 59,742 firm-years from the US economy between 1981 and 2010. ∆ denotes the annual change of a variable. Tax benefits are defined in equation (8). R−B is the excess return on firm’s stock over a DGTW benchmark portfolio. Stock returns are calculated using data from CRSP. Lev is leverage in market values, Z is a modified version of the Altman z-score, IE denotes interest expenses, EBIT earnings before interest and taxes, sd(EBIT ) and sd(Lev) are the standard deviation of the respective variable in the proceeding 12 fiscal firm-quarters, and NA is net assets defined as assets in book values minus cash. AF is analyst coverage and FD is the dispersion of analyst earnings forecast for current fiscal year. All variables but Lev and AF are scaled by the market value of equity at the beginning of the fiscal year and TBassets is scaled by the book value of firm’s total assets the beginning of the fiscal year. Due to missing information or analyst coverage, the number of observations for sd(EBIT ), sd(Lev), and FD is smaller than 59,742.

variable mean sd p25 median p75 TB 0.115 0.191 0.003 0.047 0.143 TBassets 0.053 0.054 0.005 0.046 0.088 ∆TB −0.001 0.094 −0.015 0.000 0.016 R−B −0.038 0.445 −0.311 −0.102 0.134 Lev 0.239 0.219 0.048 0.186 0.377 Z 3.629 4.515 1.330 2.662 4.823 IE 0.000 0.027 −0.004 0.000 0.004 EBIT 0.007 0.233 −0.036 0.005 0.039 ∆NA 0.009 0.436 −0.079 0.017 0.117 sd(EBIT ) 0.036 0.307 0.009 0.019 0.038 sd(Lev) 0.063 0.054 0.023 0.050 0.089 AF 0.686 0.464 0.000 1.000 1.000 FD 0.028 0.059 0.006 0.014 0.030

36 Table 3: Marginal value of tax benefits. This table presents the results of regressing the excess return over the DGTW benchmark on tax benefit and control variables over the sampling period of 1981 up to 2010. ∆ denotes the annual change of a variable. Tax benefits are defined in equation (8), Lev is market leverage, Z is a modified version of the Altman z-score, and IE is interest expense. EBIT is earnings before interest and taxes and NA is total assets less cash. ∆TBMA is the excess change in tax benefits over a 3-year moving average and ∆TBDGTW is the excess change in tax benefits of the change in tax benefits of the respective DGTW portfolio-year. All independent variables but Lev are scaled by the market value of equity at the beginning of the fiscal year. Standard errors are clustered in the firm and in the time dimension (Petersen (2009)). ∗∗∗, ∗∗, ∗ correspond to a significance at the 1% , 5%, or 10% level, respectively, and N denotes the number of observations.

Independent Variables (1) (2) (3) (4) (5) ∆TB 0.261∗∗∗ 0.444∗∗∗ (0.051) (0.069)

TB 0.663∗∗∗ 0.653∗∗∗ 0.793∗∗∗ 0.660∗∗∗ (0.043) (0.042) (0.046) (0.043)

Lev −0.955∗∗∗ −0.965∗∗∗ −0.975∗∗∗ −0.954∗∗∗ −0.634∗∗∗ (0.041) (0.043) (0.041) (0.041) (0.030)

Z 0.015∗∗∗ 0.015∗∗∗ 0.015∗∗∗ 0.015∗∗∗ 0.023∗∗∗ (0.001) (0.001) (0.002) (0.001) (0.001)

∆IE −0.603∗∗∗ −0.559∗∗∗ −0.578∗∗∗ −0.600∗∗∗ −0.931∗∗∗ (0.165) (0.164) (0.173) (0.165) (0.149)

EBIT 0.281∗∗∗ 0.276∗∗∗ 0.297∗∗∗ 0.281∗∗∗ 0.298∗∗∗ (0.019) (0.019) (0.025) (0.019) (0.018)

∆NA 0.158∗∗∗ 0.159∗∗∗ 0.153∗∗∗ 0.159∗∗∗ 0.151∗∗∗ (0.010) (0.010) (0.013) (0.010) (0.008)

∆TB · TB −0.492∗∗∗ (0.121)

∗∗∗ ∆TBMA 0.348 (0.046)

∗∗∗ ∆TBDGTW 0.255 (0.050)

intercept 0.057∗∗∗ 0.058∗∗∗ 0.052∗∗∗ 0.057∗∗∗ 0.025∗∗ (0.011) (0.011) (0.011) (0.011) (0.010)

N 59,742 59,742 35,634 59,742 59,742 adj. R2 0.202 0.203 0.203 0.201 0.170

37 Table 4: Tax benefits and default costs. This table presents the results of regressing the excess return over the DGTW benchmark on tax benefits, control variables, and measures of default costs. ∆ denotes the annual change of a variable. Tax benefits are defined in equation (8), Lev is market leverage, Z is a modified version of the Altman z-score, and IE is interest expense. EBIT is earnings before interest and taxes and NA is total assets less cash. sd(EBIT ) is the standard deviation of EBIT of firm’s last 12 fiscal quarters. All independent variables but Lev are scaled by the market value of equity at the beginning of the fiscal year. Standard errors are clustered in the firm and in the time dimension (Petersen (2009)). ∗∗∗, ∗∗, ∗ correspond to significances at the 1% , 5%, or 10% level, respectively, and N denotes the number of observations.

Independent Variables (1) (2) (3) (4) ∆TB 0.671∗∗∗ 0.362∗∗∗ 0.257∗∗∗ 0.693∗∗∗ (0.139) (0.069) (0.051) (0.148)

TB 0.672∗∗∗ 0.643∗∗∗ 0.665∗∗∗ 0.653∗∗∗ (0.043) (0.037) (0.043) (0.039)

Lev −0.967∗∗∗ −0.946∗∗∗ −0.958∗∗∗ −0.958∗∗∗ (0.042) (0.045) (0.041) (0.045)

Z 0.015∗∗∗ 0.014∗∗∗ 0.015∗∗∗ 0.015∗∗∗ (0.001) (0.002) (0.001) (0.002)

∆IE −0.604∗∗∗ −0.697∗∗∗ −0.586∗∗∗ −0.694∗∗∗ (0.162) (0.251) (0.163) (0.252)

EBIT 0.281∗∗∗ 0.293∗∗∗ 0.282∗∗∗ 0.293∗∗∗ (0.019) (0.022) (0.019) (0.023)

∆NA 0.154∗∗∗ 0.171∗∗∗ 0.159∗∗∗ 0.170∗∗∗ (0.010) (0.015) (0.010) (0.015)

∆TB · Lev −0.726∗∗∗ −0.662∗∗∗ (0.224) (0.242)

∆TB · sd(EBIT ) −1.519∗∗ −0.958 (0.692) (0.651)

∆TB · ∆Z 0.017∗∗∗ 0.019∗∗∗ (0.004) (0.007)

intercept 0.059∗∗∗ −1.519∗∗ −0.057∗∗∗ −0.069∗∗∗ (0.011) (0.692) (0.011) (0.012)

N 59,742 24,722 59,693 24,716 adj. R2 0.203 0.206 0.202 0.207

38 Table 5: Tax benefits and stability of leverage. Sample selection and the definition of the variables is identical to table 3. The dependent variable is the excess return on firm’s stock price over the corresponding DGTW portfolio. sd(Lev) is the standard deviation of firm’s leverage ratio within the last 12 fiscal quarters. All independent variables but Lev are scaled by the market value of equity at the beginning of the fiscal year. The dummy variable Dconstr equals one if a firm-year is classified as financially constraint. A firm-year is called financially constraint if it does exhibit a net repurchase of debt and equity, no dividends are paid, and the market-to-book ratio of assets greater one. Dunconstr equals one if the firm-year is considered as unconstrained with in the case if the firm belongs to the top 25% percentile of the distribution of payout ratios in calendar year. Standard errors are clustered in the firm and in the time dimension (Petersen (2009)) and ∗∗∗, ∗∗, ∗ correspond to significances at the 1% , 5%, or 10% level, respectively. N denotes the number of observations.

Independent Variables (1) (2) (3) (4) ∆TB 0.413∗∗∗ 0.293∗∗∗ 0.241∗∗∗ 0.901∗∗∗ (0.067) (0.048) (0.050) (0.142)

TB 0.653∗∗∗ 0.660∗∗∗ 0.664∗∗∗ 0.661∗∗∗ (0.038) (0.043) (0.043) (0.039)

Lev −0.946∗∗∗ −0.956∗∗∗ −0.957∗∗∗ −0.959∗∗∗ (0.043) (0.041) (0.041) (0.044)

Z 0.015∗∗∗ 0.015∗∗∗ 0.015∗∗∗ 0.015∗∗∗ (0.002) (0.001) (0.001) (0.002)

∆IE −0.626∗∗∗ −0.598∗∗∗ −0.603∗∗∗ −0.628∗∗∗ (0.235) (0.167) (0.165) (0.239)

EBIT 0.283∗∗∗ 0.281∗∗∗ 0.281∗∗∗ 0.283∗∗∗ (0.022) (0.019) (0.019) (0.023)

∆NA 0.172∗∗∗ 0.157∗∗∗ 0.157∗∗∗ 0.169∗∗∗ (0.014) (0.010) (0.010) (0.013)

∆TB · sd(Lev) −1.484∗∗ −1.441∗∗ (0.593) (0.581)

∗∗∗ ∗ ∆TB · Dconstr −0.325 −0.241 (0.076) (0.131)

∗∗∗ ∆TB · Dunconstr 0.201 0.052 (0.063) (0.084)

∆TB · Lev −0.834∗∗∗ (0.233)

intercept 0.067∗∗∗ 0.057∗∗∗ 0.057∗∗∗ 0.068∗∗∗ (0.011) (0.011) (0.011) (0.011)

N 26,766 59,742 59,742 26,766 adj. R2 0.205 0.202 0.202 0.206

39 Table 6: Information asymmetries. The definition of the variables is identical to table 3 but the sample period starts in 1983 due to the availability of analyst forecasts in I/B/E/S. The dependent variable is the excess return on firm’s stock price over the corresponding DGTW portfolio. All independent variables but Lev are scaled by the market value of equity at the beginning of the fiscal year. AF is a dummy variable that equals one if the number of analysts following in the fiscal year is larger than zero. FD is the forecast dispersion of the latest analyst forecasts for a firm-year divided by the market value of equity at the beginning of the fiscal year. Standard errors are clustered in the firm and in the time dimension (Petersen (2009)) and ∗∗∗, ∗∗, ∗ correspond to significances at the 1% , 5%, or 10% level, respectively. N denotes the number of observations.

Independent Variables (1) (2) (3) ∆TB 0.236∗∗∗ 0.472∗∗∗ 0.642∗∗∗ (0.067) (0.066) (0.153)

TB 0.670∗∗∗ 0.829∗∗∗ 0.673∗∗∗ (0.049) (0.064) (0.049)

Lev −0.947∗∗∗ −1.070∗∗∗ −0.957∗∗∗ (0.042) (0.058) (0.044)

Z 0.016∗∗∗ 0.021∗∗∗ 0.016∗∗∗ (0.001) (0.002) (0.001)

∆IE −0.623∗∗∗ −0.816∗∗ −0.624∗∗∗ (0.173) (0.329) (0.172)

EBIT 0.283∗∗∗ 0.346∗∗∗ 0.284∗∗∗ (0.020) (0.038) (0.020)

∆NA 0.150∗∗∗ 0.162∗∗∗ 0.147∗∗∗ (0.010) (0.017) (0.010)

∆TB · AF 0.101∗ 0.073 (0.056) (0.055)

AF 0.022∗∗ 0.022∗∗ (0.009) (0.009)

∆TB · FD −0.730∗ (0.401)

∆TB · Lev −0.635∗∗∗ (0.232)

∗∗∗ ∆TB · Dconstr −0.346 (0.080)

intercept 0.037∗∗∗ 0.055∗∗∗ 0.038∗∗∗ (0.013) (0.015) (0.013)

N 55,808 36,429 55,808 adj. R2 0.199 0.207 0.200

40 Table 7: Tax benefits from the current fiscal year. This table reports the results of regressions of the excess return on firm’s stock over the corresponding DGTW portfolio on a choice of independent variables. TBIE equals personal tax benefits (equation (7)) times interest payments. The definition of the other variables is identical to table 3. All independent variables but Lev are scaled by the market value of equity at the beginning of the fiscal year. Standard errors are clustered in the firm and in the time dimension (Petersen (2009)) and ∗∗∗, ∗∗, ∗ correspond to significances at the 1% , 5%, or 10% level, respectively. N denotes the number of observations.

Independent Variables (1) (2) (3) (4) ∗∗∗ ∗∗∗ ∗∗∗ ∆TBIE 1.814 3.100 5.998 (0.690) (0.654) (1.609)

∗∗∗ ∗∗∗ ∗∗∗ ∗∗∗ TBIE 5.596 5.528 7.146 5.681 (0.586) (0.584) (0.545) (0.595)

Lev −0.855∗∗∗ −0.861∗∗∗ −0.867∗∗∗ −0.860∗∗∗ (0.039) (0.041) (0.038) (0.040)

Z 0.017∗∗∗ 0.017∗∗∗ 0.017∗∗∗ 0.017∗∗∗ (0.001) (0.001) (0.002) (0.001)

∆IE −0.283 −0.227 −0.399∗∗ −0.338 (0.225) (0.231) (0.182) (0.218)

EBIT 0.294∗∗∗ 0.291∗∗∗ 0.302∗∗∗ 0.292∗∗∗ (0.019) (0.019) (0.025) (0.018)

∆NA 0.155∗∗∗ 0.154∗∗∗ 0.154∗∗∗ 0.155∗∗∗ (0.009) (0.009) (0.012) (0.009)

∗∗ ∆TBIE · TBIE −33.699 (13.695)

∗∗∗ ∆TBIE,MA 3.380 (0.514)

∗∗∗ ∆TBIE · Lev −7.162 (2.718)

intercept 0.049∗∗∗ 0.050∗∗∗ 0.046∗∗∗ 0.050∗∗∗ (0.011) (0.011) (0.011) (0.011)

N 59,747 59,747 35,696 59,747 adj. R2 0.190 0.191 0.192 0.191