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Taxable Income As An Indicator of Earnings Quality

Baruch Lev New York University

Stern School of Business (212) 998-0028

[email protected]

and

Doron Nissim Columbia University

Graduate School of Business (212) 854-4249

[email protected]

November 2002 We gratefully acknowledge the helpful comments and suggestions made by Sid Balachandran, Bjorn Jorgensen and seminar participants at Carnegie Mellon University and UCLA.

Taxable Income As An Indicator of Earnings Quality

Abstract

The widening gap during the 1990s between reported and taxable income has been recently noticed. We examine whether this gap is informative regarding the quality, or persistence of reported earnings. We document that our tax-based earnings quality indicator—the ratio of taxable-to-reported income—is positively correlated with various estimates of earnings persistence, derived from regressions of contemporaneous price, future earnings, and future returns on current earnings and control variables. We also find that the ratio of taxable-to-reported income predicts future earnings up to five years ahead, and that the information in taxable income concerning earnings quality is incremental to that in accruals and cash flows. Finally, we document an intriguing phenomenon: investors appear to fully comprehend the quality-related information in taxable income for low earnings quality firms, but not for high quality firms. This finding is consistent with Kahneman and Tversky (1979) well known “prospect theory.” Keywords: earnings quality; taxable income; market efficiency. Data Availability: Data are available from sources identified in the paper.

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I. INTRODUCTION

The recent high-profile cases of failure of reported earnings to reflect economic reality (e.g.,

Enron, Global Crossing, Tyco, WorldCom, and Xerox) focused the attention of investors and

policymakers on the quality of earnings issue. Attempting to identify a benchmark for earnings

quality, several researchers and commentators drew attention to the gap between reported

earnings and taxable income which has increased during the 1990s (e.g., Patrick 2001; Manzon

and Plesko 2002; Desai 2002; Mills et al. 2002). A recent Fortune article (“The Truth Behind

the Earnings Illusion,” 7/22/02) echoes this theme by suggesting that taxable income can be used

as a “reality check” for the validity of reported earnings (henceforth earnings).

Using taxable income as a benchmark for assessing earnings quality is not a novel idea.

Revsine et al. (1998, p. 633), for example, state: “a widening excess of book income over taxable

income…represent[s] a potential danger signal that should be investigated, because…[it] might

be an indication of deteriorating earnings quality.” More recently, several articles in the

financial press pointed out that Enron did not pay income taxes for several years prior to going

bankrupt in 2001, while it had reported high earnings during that period.1 These articles suggest

that Enron’s investors overlooked an important indicator of earnings quality—taxable income.

Academic research has also claimed that tax disclosures contain information about

earnings quality. For example, Mills and Newberry (2001) report that differences between book

and tax income are related to mangers’ incentives to overstate earnings.2 Phillips et al. (2002)

and Joos et al. (2002) report a positive correlation between the deferred portion of the income tax 1 See. e.g., “Tax Dodging: Enron Isn’t Alone,” Business Week, 3/4/02, and “Two Birds, One Stone,” Forbes, 3/4/02. 2 As proxies for incentives to overstate earnings, Mills and Newberry (2001) use firm type (public versus private), financial leverage (proxy for debt covenants), bonus plan thresholds, and past book income. Evidence on the relation between book-tax differences and firm type has also been provided by Cloyd et al. (1996), reporting that public firm managers are less likely than private firm managers to take a conforming book position that would decrease earnings.

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expense and various proxies for earnings management. Focusing on the relative informativeness

of book and tax income, Shevlin (2002) reports that estimated taxable income conveys

incremental information over earnings with respect to contemporaneous stock returns, and calls

for further research of this issue. We pursue this line of investigation, addressing four issues

central to the question of whether taxable income informs on earnings quality.

1. In our primary analysis, we estimate earnings quality from regressions of: (a)

contemporaneous stock prices, (b) future earnings, and (c) future stock returns on reported

earnings and control variables. We then examine the relation between the ratio of taxable

income to earning—our quality indicator—and earnings quality, estimated by the regression

coefficients on earnings. A positive relation would indicate that taxable income informs on

earnings quality. Our empirical tests indeed confirm that taxable income contains useful

information about the quality of earnings.

2. We interpret earnings quality in terms of persistence, and accordingly ask: What is

the duration of earnings prediction facilitated by taxable income? Our empirical analysis

indicates that the quality indicator—taxable income to earnings—predicts future earnings up to

five years ahead.

3. Having documented that the ratio of taxable income to earning helps predict stock

returns in the regression analysis, we next perform a portfolio analysis to assess the extent to

which contemporaneous stock prices fail to impound the earnings quality information in taxable

income. Specifically, we form portfolios based on the ratio of taxable income to earnings and

compute subsequent abnormal (risk-adjusted) portfolio returns. This analysis reveals an

intriguing phenomenon: The stocks of firms with low quality of earnings (low ratios of taxable-

to-book income) appear to be properly priced, as evidence by the absence of subsequent

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abnormal returns, while the stocks of firms with a high quality of earnings (large taxable-to-book

income) are systematically undervalued, as evidenced by the existence of positive abnormal

returns. Thus, investors appear to use the information in taxable income when they suspect

quality of earnings problems, yet ignore at least some of the taxable income information when

valuing firms with high quality of earnings. This behavior is consistent with a well-established

behavioral model—prospect theory—which posits an asymmetry between prospective gains

(high earnings quality, in our context) and prospective losses (low earnings quality): “The value

function is normally concave for gains, commonly convex for losses, and is generally steeper for

losses than for gains.” (Kahneman and Tversky, 1979, p. 263).

4. Finally, the earnings quality research area is an active one, yielding various quality

indicators. In particular, accruals and cash flows have been established as indicators of the

quality of earnings (e.g., Sloan, 1996; Desai et al; 2002). Accordingly, we ask: Is the quality-

related information in taxable income incremental to that in accruals and cash flows? Our

empirical analysis answers this question in the affirmative, and thereby establishes taxable

income as a unique indicator of the quality of earnings.

The potential of book-tax differences to inform about the quality of reported earnings has

been examined previously. The closest to our study are Phillips et al. (2002) and Joos et al.

(2002), reporting a positive association between the deferred portion of the income tax expense

(reflecting temporary book-tax difference) and discretionary accruals. The two studies differ,

among other things, in the estimate of discretionary accruals: Phillips et al. (2002) focus on the

proximity of current to past earnings and other earnings management thresholds, whiled Joos et

al. (2002) focus on the ability of accruals to predict future cash flows. We extend the

contribution of these studies in several directions. First, based on the widely recognized

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interpretation of earnings quality in terms of persistence, or predictability, we focus on the

information in taxable income relevant to the prediction of near- to medium-term future earnings.

Thus, an important feature of our study is the predictability of future earnings by taxable income.

Second, we examine the important question of market efficiency with respect to taxable income:

Namely, to what extent are investors cognizant of the quality-related information in taxable

income?

Third, and a more subtle extension of previous research: We focus on the total difference

between book and tax income, including both temporary and permanent differences, while some

of our predecessors examine the deferred portion of the tax expense only, namely focus on the

temporary book-tax differences. It should be noted that various accounting choices affecting the

quality of earnings, such as most goodwill amortizations, result in permanent book-tax

differences, and will therefore be missed by a focus on deferred taxes, yet captured by the total

book-tax difference. Furthermore, the deferred tax expense, examined previously, may be

affected in different directions by various discretionary accounting choices. For example, a

decrease in the valuation allowance will decrease deferred taxes and increase book income, while

a switch from accelerated to straight-line depreciation will increase deferred taxes and also

increase reported earnings.3 If such offsetting accounting choice (earnings management) effects

on deferred taxes are prevalent, they detract from the ability of deferred taxes to inform about the

quality of earnings. In contrast, all earnings management activities that increase reported

earnings but do not affect current taxable income are captured by our quality indicator, the ratio

of taxable income to earnings. The above does not detract, of course, from the important

3 See Dhaliwal et al. (2002) for investigation of earnings management via the tax expense, and review of prior evidence.

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contributions of previous tax-earnings studies, rather highlights the differences between the

current one and its predecessors.

The paper is organized as follows. Section II motivates the research questions, and

Section III develops the methodology we use. The sample selection criteria are presented in

Section IV, followed by the primary empirical analysis in Section V. Section VI examines the

uniqueness of the quality-related information in taxable income, against widely-used quality

proxies: Accruals and cash flows, while Section VII provides robustness checks on our taxable

income estimates. Section VIII concludes the paper.

II. TAXABLE INCOME AND EARNINGS QUALITY

The concept of “earnings quality” eludes a tight definition, yet most interpretations

associate earnings quality with sustainability or persistence of earnings, thereby suggesting that

reported earnings are of high quality when they are expected to recur in the future.4 We adopt

this interpretation of earnings quality, and conjecture that taxable income informs about the

persistence of reported earnings, and facilitates the prediction of future earnings.5

A priori, taxable income can be expected to provide information on earnings quality

because the tax code does not allow many of the estimates underlying accounting accruals (e.g.,

bad debt and warranty provisions), which are often the vehicle for earnings management.

However, cash flows too abstract from accrual estimates, so whether taxable income contains

incremental quality-related information over cash flows is an empirical question. Our analysis

4 For a comprehensive discussion of “earnings quality,” see Bricker et al. (1995). 5 Our focus on persistence is consistent with Penman and Zhang’s (2002) definition of earnings quality, which equated quality with earnings sustainability.

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answers this question affirmatively (in Section VI). But we would like to point our here, on a

priori grounds, several important differences between taxable income and cash flows related to

the quality of earnings.

Various components of cash flows, and cash flows from operations in particular, can and

are manipulated by management. The most obvious manipulation device is, of course, the

timing of cash flow transactions, such as deferring payments to supplies to next quarter. But

there are many subtler devices to inflate operating cash flows. Selling receivables is one such

device,6 capitalization of expenses or intangibles (including leases) are examples of other

devices.7 In many cases, such as the capitalization of expenses, the impact on earnings and

operating cash flows is in the same direction.8 The fact that cash flow components can, and are

being managed obviously detracts from their ability to inform about the quality of earnings.

Taxable income, in contrast, is more immune to manipulation, and therefore may serve as a more

reliable proxy for earnings quality, since any inflation of taxable income results in a heavy tax

payment.

While taxable income excludes some “soft,” amenable to manipulation accruals, it does

include many accruals that are less likely to be used to manage earnings. For example, under the

FIFO inventory assumption, purchasing inventory for cash does not affect earnings or taxable

6 White et al. (1998, p. 552) provide a real life example. “At June 30, 1994, the $300 million net proceeds from the sale [Delta’s sale of receivables] were reported as operating cash flows in the Company’s Consolidated Statement of Cash Flows and as a reduction in accounts receivable on the Company’s Consolidated Balance Sheet… the Company has substantially the same credit risk as if the receivables had not been sold.” Thus, an increase in operating cash flows was achieved without a real change in accounts receivable. 7 Consider the accounting for internally developed software, for instance. When such software is expensed, it reduces operating cash flows. However, when the software expenditures are capitalized (allowed, under certain circumstances, by SFAS 86), the charge goes to investing cash flows, thereby inflating operating cash flows (see, White et al., 1998, p. 116). 8 A particularly egregious such manipulation is WorldCom’s, which by its most recent admission fraudulently capitalized about $7 billion of expenses, during 1999-2001.

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income if the inventory is still on hand at the end of the year, but it does reduce operating cash

flow. To the extent that taxable income accruals are associated with a higher earnings

persistence than the excluded accruals, taxable income may contain information about the quality

of earnings incremental to operating cash flows (which exclude all accruals), even when the cash

flows are not manipulated.

Finally, there is an additional, subtler reason for taxable income to be informative about

earnings quality, or persistence. Under certain circumstances, outlined by Graham and Smith

(1999), managers may smooth taxable income.9 Such smoothing implies that current taxable

income reflects managers’ estimates of future taxable income, which in turn are related to future

earnings and cash flows. Under these circumstances, for example, a relatively high current

taxable income might indicate managers’ expectations for high subsequent taxable income (and

hence high future earnings). Thus, to the extent that managers smooth taxable income, the latter

provides information on future earnings.10

While the above a priori reasons to expect the ratio of tax-to-book income to inform

about earnings quality seem quite convincing, it should be noted that a low ratio of taxable-to-

9 These circumstances, yielding a convex tax function are: (1) progressive tax schedules, (2) provisions of the alternative minimum tax and the investment tax credit, (3) the asymmetry in the tax treatment of income and losses (delays in obtaining the tax benefits associated with losses and the expiration of unexploited tax losses). This convexity implies that firms will smooth taxable income because the expected value of a convex transformation (income taxes) of a random variable (taxable income) is larger than the value of the transformation applied to the expected value of the variable (the Jensen Inequality). That is, holding the average level (over time) of taxable income constant, the lower the volatility, the lower the income taxes. 10 In this context we provide some preliminary evidence on the smoothness of taxable income compared with that of earnings, operating income, and operating cash flows. For each firm-year observation in our sample, we calculated the standard deviation of the change in each of the four variables over the subsequent five years. To hold scale constant, we deflated the variables by total assets at the end of the current year. The mean (median) of the standard deviations over all firm-year observations is 0.038 (0.026) for taxable income, 0.072 (0.039) for earnings, 0.078 (0.059) for operating income, and 0.140 (0.099) for cash flow. That is, the time-series variability of taxable income is considerably lower than the variability of each of the other three variables, consistent with the argument that firms smooth taxable income and so render its current level informative about future taxable income and earnings. (The differences between the standard deviation of taxable income and the standard deviations of the other three variables are highly significant.)

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book income does not necessarily indicate low quality (manipulated) earnings. For example,

certain book-tax differences, such as from interest on state and municipal bonds, and deductions

from dividend income reduce taxable income while not affecting earnings quality. Furthermore,

some firms may be more efficient than others in deferring taxable income to the future or may

operate in industries where it is easier to defer taxable income (e.g., through depreciation in

capital intensive industries), without adversely affecting the quality of their earnings. Thus, the

extent to which taxable income contains information about earnings quality is an empirical

question, which we address below.

III. METHODOLOGY

We start by deriving an estimate of taxable income, and then present the empirical

specifications of our tests.

Estimating Taxable Income

Our primary estimate of taxable income is based on the current portion of the reported

income tax expense:

Taxable income (TI) = k × current portion of the income tax expense. (1)

The parameter k is assumed to be cross sectionally constant and is measured as the inverse of the

top statutory federal tax rate.11 The income tax expense includes federal (Compustat #63) and

foreign (#64) taxes but excludes state taxes. This approach to estimating taxable income has

been followed in several recent studies (e.g., Manzon and Plesko 2001; Cipriano et al. 2001).12

11 The top statutory corporate federal tax rate was 48% in 1973-1978, 46% in 1979-1986, 40% in 1987, 34% in 1988-1992, and 35% in 1993-2001. 12 To reduce measurement error due to the use of statutory federal tax rates in grossing up current income taxes, Manzon and Plesko (2002) include only federal income taxes in the calculation. We include foreign income taxes too because the dependent variables in our analysis (price, future earnings, and future return) reflect both foreign and

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The estimate of taxable income (1) contains measurement error from several sources.

First, the assumption that k is cross-sectionally constant does not hold in a strict sense. Cross-

sectional variations in the average tax rate (which determines k) may be due to progressive tax

rates (relatively small effect for large firms), as well as to differences between the statutory

federal tax rate and foreign tax rates (potentially large effect for some sample companies). In the

robustness tests (Section VII), we address the latter concern by excluding from the analysis firms

with relatively large amounts of foreign income. The taxable income estimate (1) is also noisy

because the current portion of the income tax expense does not reflect the tax benefits associated

with the exercise of non-qualified employee stock options (quite a large effect for many firms,

see Hanlon and Shevlin (2002) and Desai (2002)), or the benefits from dividends paid on

unallocated ESOP shares (relatively small effect).13 Thus, our estimate of taxable income may

overstate the amount of income actually subject to income taxes. In the robustness tests, we

examine the sensitivity of our findings to this source of measurement error by using an

alternative estimate of taxable income, based on the amount of income taxes actually paid during

the year.14

Models

We relate in the following regression analyses contemporaneous stock prices, future

earnings, and future returns to current earnings and control variables. In conformity with past

domestic income. (The dependent variable in Manzon and Plesko (2001) is the difference between book and tax income.) 13 The tax deduction associated with non-qualified options (ESOP dividends) is equal to the value of the options at the time of exercise (the amount of dividends). Companies account for the tax benefit associated with non-qualified options (ESOP dividends) by increasing contributed capital (retained earnings), instead of reducing the current portion of the income tax expense. See Hanlon and Shevlin (2002) for a detailed discussion of accounting for employee stock options and its implications for alternative estimates of taxable income. 14 Note that our estimate of taxable income pertains to the consolidated entity. As pointed out by Manzon and Plesko (2002), and Mills et al. (2002), the consolidated tax entity is typically different from the financial accounting entity due to differences in IRS consolidation rules.

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empirical research and analytical work (e.g. Ohlson, 1995), we interpret the estimated regression

coefficients on current earnings as proxies for the quality (persistence) of earnings. A high

earnings coefficient from a price-earnings regression, for example, indicates investors’ strong

belief in the persistence of those earnings. We then examine the relation between our earnings

quality indicator—tax-to-book ratio—and the empirical quality proxies—estimated regression

coefficients on earnings.

Contemporaneous Stock Price Analysis

To examine whether taxable income contains information on the quality of reported

earnings, we estimate the following cross-sectional model:

P/A = �

=

99

1ii1iDβ + β2 1/A + β3 B/A + β4 E/A + β5 ATTI/A + ε,

(2)

where P is the market value of common equity at fiscal year-end (Compustat #199 × #25); A is

total assets at year end (#6); Di is a dummy variables that equals one if the firm belongs to

industry i (two digit SIC code) and zero otherwise; B is book value at fiscal year-end

(Compustat’s common equity adjusted for preferred treasury stock and preferred dividends in

arrears, #60 + #227 - #242); E is reported earnings (income before extraordinary items, #18); and

ATTI is estimated after-tax taxable income (i.e., the difference between estimated taxable

income and the current portion of income taxes, or TI × (1-t), where t is the top statutory federal

tax rate). ATTI is the after tax analogue to earnings (E).

The specification of Equation (2) is based on available evidence that earnings and book

value jointly explain cross-sectional variation in share prices (for a review, see Chambers et al.

2001). The variables in (2) are deflated by the book value of total assets to mitigate the effect of

heteroskedasticity, and the industry dummy variables are included in the regression to mitigate

the effect of correlated omitted variables. As the industry dummies span an intercept, Equation

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(2) effectively controls for the information in total assets (the deflator) about market value (the

undeflated dependent variable). Including total assets in (2) captures the average effect of

omitted factors that are correlated with firm size.15

Earnings (E) in Equation (2) serves as a proxy for expected future earnings, which in turn

determine price (P). If taxable income is informative about the quality of reported earnings, the

coefficient that relates earnings to price, β4, should be positively related to the tax-to-book

income ratio ATTI/E. ATTI (after-tax taxable income) is included in Equation (2) to capture this

relationship. To see this, note that Equation (2) can be derived by starting with E and B (book

value) as the only explanatory variables, and then allowing the earnings coefficient to be linearly

related to ATTI/E (i.e., specifying the earnings coefficient as β4 + β5 ATTI/E). The product of

ATTI/E and E equals ATTI, and hence the coefficient on ATTI (i.e., β5) in (2) reflects the

sensitivity of the earnings coefficient (persistence estimate) to changes in ATTI/E, our tax-based

indicator of earnings quality.16 Accordingly, β5 in (2) captures the information in taxable income

about the quality of earnings.17

While variants of Equation (2) are commonly used in accounting research, it is clear that

earnings and book value are not the only determinants of stock prices. If the omitted information

15 Note also that controlling for both total assets and book value implies that variation in total liabilities, and hence in financial leverage, is also captured by the explanatory variables in (2).

16 Specifically, the model P/A =�=

99

1ii1i Dβ + β2 1/A + β3 B/A + (β4 + β5 ATTI/E) E/A + ε is equivalent to

Equation (2). 17 An alternative approach would be to include in Equation (2) pre-tax earnings and taxable income (TI), instead of E and ATTI, respectively. We use the after-tax approach for two reasons. First, price reflects expectations about after-tax, not before-tax earnings. Second, to the extent that firms manage the income tax expense (for example, by decreasing the valuation allowance; see, e.g., Dhaliwal et al. 2002), the before-tax ratio of tax-book income will not reflect the earnings management, while the after-tax ratio will reflect it (higher after-tax income).

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is correlated with the variables in (2), the ATTI coefficient will be biased. To mitigate the effect

of correlated omitted variables, we estimate a change in variables specification:

∆P/A = �

=

99

1ii1iDβ + β2 1/A + β3 ∆B/A + β4 ∆E/A + β5 ∆ATTI/A + ε,

(3)

where ∆ denotes the annual change in the variable (before deflation).

Future Earnings and Returns Analyses

While stock prices reflect investors’ expectations regarding the persistence of current

earnings, prices are also related to firm risk and other factors that may be correlated with our

quality indicator ATTI/E. To examine more directly the information in ATTI/E about the

persistence (predictability) of earnings, we move beyond the contemporaneous relations, (2) and

(3), and examine the predictive ability of taxable income with respect to the next year’s earnings

(FE), by substituting FE for price in Equation (2):

FE/A = �

=

99

1ii1iDβ + β2 1/A + β3 B/A + β4 E/A + β5 ATTI/A + ε,

(4)

and similarly for the changes in Equation (3):

∆FE/A = �

=

99

1ii1iDβ + β2 1/A + β3 ∆B/A + β4 ∆E/A + β5 ∆ATTI/A + ε.

(5)

Focusing on subsequent earnings rather than contemporaneous prices also addresses concerns

with market efficiency. Specifically, if securities are not priced efficiently, Equations (2) and (3)

may not fully capture the implications of taxable income regarding earnings quality. Equations

(4) and (5),however, inform directly on the information in taxable income concerning earnings

persistence.

Finally, we examine a future stock returns model, based on prior research (e.g., Fama and

French 1992), which includes the following determinants of expected returns:

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R = �

=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β5 BETA + β6 VOL + β7 ATTI/P + ε.

(6)

R is the one-year-ahead buy-and-hold stock return (including all distributions to shareholders),

measured from beginning of May of the subsequent year.18 (For securities that delist during the

one-year holding period, proceeds from the issue are invested in the NYSE, AMEX, and

NASDAQ value-weighted index until the end of the holding period.) SIZE is the log of the

market value of equity at the beginning of May of the subsequent year. BETA—systematic

risk—is estimated using monthly stock returns and the CRSP value-weighted returns (including

all distributions) during the five years that end in April of the subsequent year (at least 30

observations are required). VOL—volatility of returns—is the root mean squared error from the

BETA regression, reflecting idiosyncratic volatility (risk). The other variables in (6) were

defined above.

The estimation of BETA and VOL requires considerable prior years’ data, which are

missing for many firms. Moreover, the explanatory power of these variables for expected returns

was found to be negligible (see Fama and French 1992). Thus, to avoid loss of observations, we

also run a circumcised version of regression (6) excluding BETA and VOL:

R = �

=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β5 ATTI/P + ε.

(7)

Below (Section V) we report on portfolio analyses which abstract from the linearity

assumption underlying the regressions (2)-(7). Finally, we investigate the incremental

18 For the future stock returns analysis, we reassign firms to years based on the calendar year in which the fiscal year ends, rather than use the COMPUSTAT year (which includes in the same year all fiscal year-ends between June of that year and May of the following year). We measure stock returns from May of the subsequent year to assure that investors had access to the annual financial report.

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information in our earnings quality signal ATTI/E relative to other indicators of earnings quality:

accruals and cash flows (Section VI).

IV. SAMPLE AND DESCREPTIVE STATISTICS

To construct the sample for the contemporaneous price analysis, (2) and (3), we apply the

following criteria. First, data items #6 (total assets), #18 (income before extraordinary items),

#199 (price per share), #25 (number of shares outstanding), #60 (common equity), and #63

(federal income taxes) should be available on COMPUSTAT’s industrial, full coverage, and

research files. Second, we restrict the sample to positive earnings observations, because: (1) our

indicator of earnings quality is the ratio of after-tax taxable income to earnings, which is

meaningless when earnings are negative, and (2) losses are less permanent than positive earnings

(e.g., Hayn 1995), and hence the estimated coefficients are likely to differ between profits and

losses (see, e.g., Barth et al. 1998).

Although the required data for our tests are available since 1969, we drop the years 1969

through 1972 because the number of observations is substantially smaller than in subsequent

years. To mitigate the effect of influential observations, we delete in the various analyses

observations for which any of the variables (excluding future stock returns) lies outside the

0.5%-99.5% range of its sample distribution.19 The sample selection criteria result in a sample of

89,283 firm-year observations for the price-levels analysis (12,509 different firms; 29 years,

from 1973 through 2001). For the price-changes analysis, the requirement of data availability for

the previous year (to calculate the changes) reduces the number of observations to 79,642.

19 In the price and future earnings analyses, regressions (2)-(5), we obtain similar results when applying the outlier filter only to the independent variables. Consistent with most previous studies, we do not apply the outlier filter to stock returns because they are typically “well-behaved.”

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Similarly, in the future earnings tests, we exclude firm-year observations with missing future

earnings (which in effect excludes all observations from 2001, as well as firms that did not

survive in the subsequent year). The resulting sample includes 82,809 (78,107) observations for

the future earnings-levels (-changes) analysis. For the subsequent returns analysis, we require

that the CRSP number of shares outstanding and closing stock price be available as of the end of

April of the subsequent calendar year, and drop fiscal years 2000 and 2001.20 These

requirements result in a sample of 71,999 observations.

Table 1 presents the distribution of the variables used in the price association analysis.

The variables in Table 1 (and Table 2) are deflated by total assets, as in the regressions. As

shown, reported earnings (mean 0.067) are considerably larger than after-tax taxable income

(mean 0.042), consistent with previous evidence that the gap between book and tax income is

positive and large (e.g., Manzon and Plesko 2002; Desai 2002).

Table 2 provides the Pearson (lower triangle) and Spearman (upper triangle) correlation

coefficients among the deflated variables in (2). The coefficients in both triangles are similar,

indicating that outliers are not likely to affect our inferences. As expected, there is a strong

positive correlation between earnings and taxable income, and both variables are positively

related to price. Consistent with Shevlin (2002), the relationship between price and earnings is

considerably stronger than that between price and taxable income.

20 We cannot use fiscal years after 1999 for this analysis since the CRSP files contain data through December 2001. Recall that for the market efficiency analysis we reassign firms to years based on the calendar year, and we measure stock returns from the beginning of May of the subsequent year through the following April.

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V. PRIMARY EMPIRICAL RESULTS

Price Association Analysis

Panels A and B of Table 3 present summary statistics from the annual cross-sectional

regressions (2) and (3). The statistics reported are the time-series means of the annual cross

sectional coefficients, and the associated t-statistics (the ratio of the mean of the cross-sectional

coefficients to its standard error). Each panel contains three sets of regressions corresponding to

two sub-periods (1973-1986 and 1987-2001), as well as to the full sample period (1973-2001).

For the entire period, the ATTI coefficient is positive and highly significant in both the levels

(Panel A) and changes (Panel B) specifications. For the sub-periods, in the levels specification,

the ATTI coefficient is significant only for the recent (1987-2001) period, while in the changes

specification (Panel B), the ATTI coefficient is significant in both sub-periods but it is

significantly larger in the recent period than the early one, 4.422 vs. 2.255 (t-statistic for the

difference is 7.78).

As discussed in Section III, the ATTI coefficient captures the relationship between the

earnings coefficient and the quality indicator ATTI/E. Thus, the positive ATTI coefficients in

Table 3 imply that the persistence of earnings, as reflected in stock prices, increases with

ATTI/E. We therefore conclude from the price association analysis that taxable income contains

useful information for assessing earnings quality. Moreover, the finding that the ATTI

coefficient is larger in the recent (relative to the early) period confirms widely held beliefs that

the quality of earnings has deteriorated in recent years, making the information in taxable income

about earnings quality increasingly relevant.

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Future Earnings Analysis

Inferences from a contemporaneous price analysis, such as those derived above,

essentially assume market efficiency. To abstract from such an assumption and focus directly on

earnings quality in terms of persistence (predictability), we shift the focus to future earnings—

regressions (4) and (5). Table 4 is identical to Table 3, except that the dependent variable in

Table 4 is next year’s earnings instead of contemporaneous price. The sign, significance and

trend of the ATTI coefficients in Table 4 are similar to those in Table 3, except that now all the

ATTI coefficients are highly significant. As discussed in Section III, the ATTI coefficient (β5)

captures the information in taxable income about the implications of current earnings for next

year’s earnings, namely the information in taxable income regarding the persistence (quality) of

earnings. Furthermore, the larger ATTI coefficient in the recent period implies that the

information in ATTI/E has increased in relevance in recent years. In particular, the t-statistic

associated with the change in the ATTI coefficient between the two sub-periods is 5.50 (1.97) in

the levels (changes) analysis. Note that the evidence from the subsequent earnings analysis

(Table 4) also mitigates concerns that the results of the price analysis reported in the previous

subsection are due to ATTI/E proxying for factors unrelated to earnings quality, such as risk or

long-term growth prospects.

The regressions reported in Table 4 assume that the relationship between the earnings

coefficient and ATTI/E is monotonic and linear, which may not be the case. Moreover, the

dependent variable in (4) and (5) is just next year’s earnings, and hence the regression estimates

do not reveal the implications of taxable income for longer-term future earnings. To examine

these issues we perform the following portfolio analysis. For each sample year t, we rank all

firms within their industries (2-digits SIC) on the value of ATTI/E (after-tax taxable income to

18

earnings). We then use the industry-specific relative ranks (i.e., rank divided by the number of

industry observations) to form cross-sectional quintiles of all the sample firms, and compute for

each quintile the average ratio of earnings to total assets for each of the future years t through

t+5.21 The deflator in each of the years t through t+5 is total assets at the end of year t.

Figure 1 presents the grand mean of earnings for each of the five portfolios described

above in each of the years t through t+5. The grand mean is calculated as the time-series mean

(over the sample years) of average earnings for each portfolio in the current and next five years.

Consistent with ATTI/E proxying for earnings quality, the two lowest earnings quality quintiles

(bottom two curves in Figure1), containing firms with low taxable income to earnings ratios,

exhibit earnings decreases through the third subsequent year, while the two highest quality

quintiles (high ATTI/E) exhibit continuous increases in subsequent earnings through year 5.

Moreover, both the change in earnings in year 1 (the slope of the curve) and the cumulative

change in earnings over the five years have a perfect Spearman correlation with the portfolio

rank; that is, the highest quality (highest ATTI/E) quintile has the largest earnings change,

followed by the second highest quality quintile, etc.22 We conclude that the ratio of taxable

income to earnings indicates multi-year persistence of earnings.

Summarizing the analysis so far, we have documented that taxable income informs about

the persistence of earnings as perceived by investors (contemporaneous regressions), as well as

the quality of earnings in terms of predicting short and intermediate-term future earnings.

21 We rank firms within their industries (rather than using the cross-section sample) to control for specific industry effects on book-tax differences (see Mills and Newberry 2001), as well as to control for other determinants of book-tax differences that are likely to be correlated with industry membership (e.g., capital intensity, see Manzon and Plesko 2002). To improve efficiency, we delete observations from industries with less than five firm-year observations. 22 Note that the overall earnings decline in year 1 (the mean earnings across the five quintiles in year 1 is smaller than in year 0) is partly due to design: All firms in year t are profitable, while in the subsequent five years we allow negative earnings.

19

Future Returns Analysis

Having documented that taxable income contains information about future earnings, we

next examine whether this forward-looking information in taxable income is fully reflected in

current stock prices, or some of it is overlooked by investors. To this end, we run cross-sectional

regressions (6) and (7), which examine the relationship between taxable income (and control

variables) and subsequent stock returns. Regression estimates, presented in Table 5, indicate that

the ATTI coefficient is positive and significant for the total sample period, in each of the sub-

periods (1973 through 1986, and 1987 through 1999), and under both specifications (with and

without BETA and VOL). Moreover, ATTI is generally the most significant explanatory

variable in the regressions. These results suggest that stock prices do not fully impound on a

timely basis the forward-looking information in taxable income. However, in contrast to the

contemporaneous price and future earnings results, we do not observe here a positive trend in the

ATTI coefficient (i.e., the coefficient is not larger in the recent sub-period than in the early one).

Perhaps investor awareness of earnings quality issues has increased over time, offsetting the

negative trend in earnings quality.

As pointed out above, the regression approach used thus far assumes that the relationship

between the dependent variable and the tax-based quality indicator is monotonic and linear,

which may not be the case. In addition, it is difficult to assess from estimated regression

coefficients the economic significance of the information in taxable income. To address these

issues, we perform a portfolio analysis similar to that described in the previous subsection to

examine future stock returns (from May 1 of year t+1 through April 30 of year t+2).

Specifically, in each year, the sample firms are ranked by ATTI/E in their respective 2

digit SIC (industries), and five portfolios are formed from all the sample firms based on the

20

industry-specific relative ranks (i.e., rank divided by the number of observations in the industry).

The data in Table 6 are the time-series means of the cross-sectional (portfolio) means. The table

reports (from left to right) the means of the earnings quality indicator ATTI/E, three measures of

subsequent returns (raw returns, size-adjusted returns, and returns adjusted for both size and

B/P), and five firm and stock return characteristics (SIZE, B/P, E/P, BETA, and VOL). For the

two abnormal return measures (size, and size & B/P adjusted), also reported are the t-statistics

associated with the time-series distribution of the portfolio means. The size-adjusted abnormal

return is calculated by deducting the contemporaneous size-decile return from the firm’s buy-

and-hold return. The abnormal return adjusted for both size and book-to-market is calculated as

the difference between the firm’s raw return and the contemporaneous return on a matched

portfolio based on size (five quintiles) and book-to-market (five quintiles).23 In effect, we

construct 25 benchmark portfolios, and subtract the return on the corresponding benchmark

portfolio from the firm’s raw return.24

The data in Table 6 indicate that the relationship between the ratio ATTI/E and

subsequent abnormal returns is positive and significant for the two quintiles of firms with the

largest ATTI/E values (4 and 5), namely firms with the high earnings quality. For the other three

portfolios, the subsequent abnormal returns are insignificant. The data thus indicate that high

earnings quality firms, as measured by the ratio of taxable income to earnings, are systematically

underpriced by investors, while low earnings quality firms are, on average, properly priced.

These findings hold under both types of risk adjustment (size, and size & B/P). Examination of

the portfolio attributes (the five columns on the right of Table 6) suggests that the observed

23 We measure the decile and quintile benchmark returns using all observations in the intersection of CRSP and COMPUSTAT with available values for SIZE and B/P. 24 We obtained very similar results when controlling for size and book-to-market using 100 (=10×10) portfolios.

21

abnormal returns associated with high values of ATTI/E are not due to inappropriate risk control

by the size and book-to-market adjustments to returns. For example, none of the five

characteristics of the high ATTI/E portfolio, which generates the largest subsequent returns, rank

this portfolio as the riskiest of the five (e.g., portfolio 5 BETA and volatility are not the highest

of the five portfolios).

The significance of the abnormal returns associated with the high ATTI/E portfolio is

also apparent when considering non-parametric statistics: The abnormal return SAR (AR) is

negative in only 3 (4) out of the 27 years examined, and both return measures are never below –4

percent. The magnitude of these returns is also quite substantial: SAR of 3.2% and AR of 2.7%.

Summarizing, high earnings quality firms (indicated by high ATTI/E) are systematically

underpriced, while low earnings quality firms are properly priced,on average. This suggests that

investors use the information in ATTI/E (or information correlated with it) on a timely basis

when evaluating earnings of firms suspected of having quality issues, as indicated by the large

gap between taxable income and earnings. In contrast, for high earnings quality firms, investors

fail to fully incorporate in prices the information in taxable income. This finding is consistent

with Kahneman and Tversky’s (1979) well known “prospect theory” and considerable

subsequent behavioral research indicating that people’s concern with prospective losses (low

earnings quality firms in our context), outweighs the gratification from expected gains. In

Kahneman and Tversky’s expression (p. 279): “A salient characteristic of attitudes to changes in

welfare is that losses loom larger than gains. The aggravation that one experiences in losing a

sum of money appears to be greater than the pleasure associated with gaining the same amount.”

22

VI. UNIQUENESS OF THE INFORMATION IN TAXABLE INCOME

The evidence presented above suggests that the ratio of taxable income to earnings

informs on the quality of reported earnings. Is this information incremental to other indicators of

earnings quality? In particular, we investigate here whether the quality indicator ATTI/E

contains incremental information relative to accounting accruals (Sloan 1996), a commonly used

indicator of earnings quality, and the ratio of cash flow to price, which Desai et al. (2002) argue

subsumes the information in accruals.

We measure the accrual component of earnings (ACC) as:

ACC = (∆CA – ∆Cash) – (∆CL – ∆STD – ∆ITP) – Dep, (8)

where:

∆CA = annual change in current assets (∆#4)

∆Cash = change in cash and cash equivalents (∆#1)

∆CL = change in current liabilities (∆#5)

∆STD = change in debt included in current liabilities (∆#34)

∆ITP = change in income taxes payable (∆#71), and

Dep = depreciation and amortization expense (#14).

Following Sloan (1996), we scale ACC by the average of the beginning and ending of year book

value of total assets. We measure cash flow (C) as the difference between operating income

after depreciation (#178) and accruals.

Given the asymmetry in the relationship between future stock returns and ATTI/E

(Section V), we allow for different coefficients on high and low values of ATTI/E, using dummy

variables. Specifically, using the five portfolios of firms ranked by the size of ATTI/E (Section

V), we specify a dummy variable DHQ for firms in the highest quintile (high tax-to-book firms),

23

and DLQ for firms in the lowest quintile (low tax-to-book firms). We then incorporate these

dummy variables in the following regression of subsequent returns on risk control variables

(size, book-to-price, earnings-to-price, beta, volatility), the tax dummies, and the two quality

proxies: accruals (ACC), and cash flow to price (C/P).

R = �

=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β5 BETA

+ β6 VOL + β7 DHQ + β8 DLQ + β9 ACC + β10 C/P + ε.25 (9)

Table 7 reports summary statistics from four regressions nested in (9). The first

specification (top row) excludes ACC and C/P to establish a benchmark. Consistent with the

portfolio analysis (Section V), the coefficient on DHQ (high earnings quality) is positive and

significant and the coefficient on DLQ is insignificant. The second specification adds ACC—

accrual earnings scaled by total assets. Consistent with prior studies, the coefficient on ACC is

negative and highly significant. However, the magnitude and significance of the coefficients on

DHQ and DLQ remain essentially unchanged, indicating that the information in taxable income

about earnings quality is incremental to that in accruals. As expected, the addition of cash flow

to price (C/P) into the regression (third specification) reduces the magnitude and significance of

the coefficient on DHQ (from 0.019 to 0.014), but the tax coefficient remains significant (t-

statistic of 2.73). Similar results are obtained when both ACC and C/P are included in the

regression (fourth specification). These results indicate that ATTI/E contains information on

earnings quality incremental to that in the accrual and cash components of earnings.26

25 All variables are defined in Table 8. 26 We also reran the contemporaneous price and future earnings regressions (model (2)-(5)) adding accruals (in all regressions) and cash-to-price (in models (4) and (5)) as additional explanatory variables. We found with respect to the ATTI/E variable essentially the same results as those reported in Tables 3 and 4.

24

VII. ROBUSTNESS CHECKS

In Section III we discussed sources of measurement error in the taxable income estimate

(1). In particular, the assumption of constant gross-up parameter, k, may not hold due to

differences between the U.S. tax rate and foreign tax rates, and to the exclusion of some tax

benefits (e.g., on exercise of non-qualified employee stock options) from the current portion of

the income tax expense. To evaluate the robustness of our findings with respect to these error

sources, we rerun the analysis using an alternative estimate of taxable income, and excluding

firms with substantial amounts of foreign income.

An Alternative Estimate of Taxable Income

As discussed above, our primary estimate of taxable income (1) does not reflect

deductions from taxable income that do not affect the current portion of the income tax expense

(primarily the tax benefits associated with the exercise of non-qualified stock options). As a

robustness check, we construct an alternative estimate of taxable income, based on income taxes

paid during the year. Specifically,

Taxable income = k × (income taxes paid + ∆ accrued income taxes). (10)

Income taxes paid (reported by most companies at the bottom of the cash flow statement or in

the notes) is measured as Compustat data item #317. The change (∆) in accrued income taxes

(#305) is the amount reported in the operating section of the cash flow statement as an

adjustment to net income. The parameter k in (10) is assumed to be cross-sectionally constant

and, unlike the primary tax estimate (1), is measured as the inverse of the top statutory federal

tax rate plus two percent average state tax rate (income taxes paid include state income taxes).

Relative to the primary analysis, this taxable income estimate has at least two

shortcomings. First, since the estimate is based on income taxes paid during the year, it includes

25

income tax payments applicable to prior years. Second, the cash flow information required to

calculate this estimate has only been publicly available since 1987. This latter restriction is

important especially for the future returns analysis because the 1990s were characterized by

unusually high stock returns for technology firms, which have relatively large amounts of stock

options.

Table 8 presents summary statistics from the cross-sectional regressions (2) through (6)

for the years 1987 through 2001, using the alternative measure of taxable income (10). As

shown in the table, the ATTI coefficients in the price and future earnings regressions (Panels A

through D) are positive and highly significant, both in the levels and changes specifications.

These results are consistent with the primary analysis and provide support for the inference that

taxable income contains information on the quality of earnings. However, in the future return

regressions of Table 8 (Panel E), the ATTI coefficient is insignificant. This latter result may be

due to the unusually high stock returns of technology firms during the 1990s. Specifically,

technology firms typically issue large quantities of employee stock options, and enjoy large tax

benefits when the options are exercised. These tax benefits, which reduce the ATTI/E ratio, are

particularly large during periods of high stock returns.27 Thus, the high stock returns of

technology firms during the 1990s, which resulted in a low ratio of tax-to-book income,

weakened the generally positive relation between ATTI/E and stock returns.

Excluding Firms with Substantial Foreign Income

We mentioned above that one source of measurement error in our estimate of taxable

income (1) is due to the use of the federal tax rate in converting the current portion of the income

tax expense to estimated taxable income. For many firms, the current portion of the income tax

27 For non-qualified employee stock options, the tax benefits equal the difference between the stock price on the exercise date and the exercise price, which increases with stock prices.

26

expense includes foreign taxes, which are generally taxed at different rates than U.S. rates. To

examine the effect of this potential source of measurement error on our estimates, we rerun

regressions (2) through (6), excluding firms with relatively large amounts of foreign income.

Specifically, we exclude from the analysis firm-year observations for which the ratio of the

absolute value of “Pretax income-foreign” (#273) to the sum of that amount and the absolute

value of “Pretax income-domestic” (#272) is larger than 20%. As data items #272 and #273 are

available only since 1984, the period covered is 1984 through 2001. The results, presented in

Table 9, are very similar to those reported in the primary analysis, indicating that measurement

error in estimated taxable income due to differences between foreign and U.S. tax rates has

negligible effect on our estimates and inferences.

VIII. SUMMARY AND CONCLUSIONS

We investigate in this study the ability of corporate taxable income to convey information

on the quality of reported earnings, defined in terms of persistence. In the primary empirical

analysis we estimate earnings persistence from contemporaneous stock price regressions on

earnings and control variables, as well as from regressions of future earnings on current earnings,

and show that taxable income is positively associated with earnings persistence estimates. We

thus establish that taxable income indeed informs on the quality of earnings. Additional tests

indicate that our quality indicator—the ratio of taxable income to earnings—predicts future

earnings up to five years ahead.

Is this information in taxable income fully impounded in stock prices? Namely, are

prices efficient with respect to the quality related information in taxable income? Our analysis

provides an affirmative answer with respect to low earnings quality firms, and a negative answer

27

regarding high earnings quality firms. Specifically, investors appear to use on a timely basis the

information in taxable income (or correlated information) in assessing the earnings quality of

suspect firms (those having a large gap between book and tax income), yet largely ignore the

useful information in taxable income for high earnings quality firms. The usefulness of the

information in taxable income for high earnings quality firms is demonstrated by subsequent

annual abnormal (risk-adjusted) returns of about 3%. Finally, we ask: Is the information on

earnings quality embedded in taxable income incremental to established quality proxies—

accruals and cash flows? Our analysis answers this question too affirmatively.

From a policy perspective, these findings suggest that public firms be required to disclose

taxable income in financial reports, a modest regulatory requirement. The fact that corporate

taxable income plays an important role in macro-economic statistics adds weight to this

disclosure recommendation. Specifically, in the absence of firm-specific taxable income data,

the Bureau of Economic Analysis (BEA) estimate “corporate profits”, a key indicator in the

National Income and Product Accounts (NIPA), based on aggregate taxable income data

obtained from the IRS. Firm-specific taxable income data may, therefore, improve both investor

and policymakers’ decisions.

28

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Chaney, P.K., and D.C. Jeter. 1994. The effect of deferred taxes on security prices. Journal of Accounting, Auditing, and Finance 9: 91-116.

Cipriano, M., D. W. Collins, and P. Hribar. 2001. An empirical analysis of the tax benefit from employee stock options. Working Paper, University of Iowa, Iowa City, IA.

Cloyd, J. Pratt, and T. Stock. 1996. The use of financial accounting choice to support aggressive tax positions: Public and private firms. Journal of Accounting Research 34 (Spring): 23- 43.

Desai, M. A. 2002. The corporate profit base, tax sheltering activity, and the changing nature of employee compensation. NBER Working Paper #8866.

Desai, H., S. Rajgopal, and M. Venkatachalam. 2002. Value-glamour and accruals mispricing: One anomaly or two? Working Paper, University of Washington, Seattle, WA.

Dhaliwal, D., C. A. Gleason and L. F. Mills. 2002. Last chance earnings management: Using the tax expense to achieve earnings targets. Working Paper, University of Arizona, Tucson, AZ.

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Manzon, G. B., and G. A. Plesko. 2002. The relation between financial and tax reporting measures of income. The Law Review 55: 175-214.

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30

FIGURE 1 Current and Future Earnings

for Portfolio Sorted by a Tax-based Proxy for Earnings Quality

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0.11

0 1 2 3 4 5

year (year 0 is portfolio formation year)

Earn

ings

lowest quality

highest quality

second lowest quality

second highest quality

intermediate quality

Earnings are deflated by total assets in year 0, the portfolio formation year. The figure presents the grand mean (i.e., time-series mean of the cross-sectional means) of deflated earnings in years 0 through 5 for each of the five earnings quality portfolios. The proxy for earnings quality is the within industry (2 digit SIC code) rank of ATTI/E, where ATTI is after-tax estimated taxable income (see Section III for details) and E is earnings (income before extraordinary items).

31

TABLE 1 Descriptive Statistics

Mean STD 5% 25% 50% 75% 95% P/A 1.070 1.211 0.154 0.365 0.671 1.282 3.396 1/A 0.034 0.070 0.000 0.002 0.009 0.032 0.156 B/A 0.491 0.212 0.155 0.336 0.480 0.646 0.850 E/A 0.067 0.051 0.008 0.032 0.055 0.089 0.162 ATTI/A 0.042 0.045 0.000 0.005 0.031 0.065 0.132 The number of observations is 89,283. P is market value of common equity at fiscal year-end. A is total assets. B is book value at fiscal year-end. E is earnings (income before extraordinary items). ATTI is estimated after-tax taxable income (see Section III for details).

32

TABLE 2 Pearson (Lower Triangle) and Spearman (Upper Triangle)

Correlation Coefficients among the Variables in Expression (2)

P/A 1/A B/A E/A ATTI/A P/A 0.09 0.54 0.57 0.42 1/A 0.11 0.34 0.11 -0.03 B/A 0.41 0.19 0.46 0.36 E/A 0.49 0.09 0.42 0.66 ATTI/A 0.41 -0.05 0.36 0.67 The number of observations is 89,283. P is market value of common equity at fiscal year-end. A is total assets. B is book value at fiscal year-end. E is earnings (income before extraordinary items). ATTI is estimated after-tax taxable income (see Section III for details). All correlation coefficients are statistically significant at the 0.001 level.

33

TABLE 3 Contemporaneous Cross-sectional Regressions of Market Value

on Estimated Taxable Income and Control Variables (Expressions 2 and 3)

Panel A: Levels specification

P/A = �=

99

1ii1iDβ + β2 1/A + β3 B/A + β4 E/A + β5 ATTI/A + ε

(2)

Years 1/A B/A E/A ATTI/A Mean R2 Mean N Sub1 1973-86 1.151 0.754 7.885 0.230 0.704 2,978 4.353 6.816 19.525 0.732 Sub2 1987-01 0.178 1.178 8.105 4.269 0.719 3,173 0.442 18.570 18.392 11.959 Total 1973-01 0.648 0.973 7.999 2.319 0.712 3,079 2.520 13.261 27.085 5.178 Panel B: Changes specification

∆P/A = �=

99

1ii1iDβ + β2 1/A + β3 ∆B/A + β4 ∆E/A + β5 ∆ATTI/A + ε

(3)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N Sub1 1973-86 -0.031 1.382 1.055 2.255 0.359 2,674 -0.216 4.107 4.302 11.918 Sub2 1987-01 -0.330 2.023 0.645 4.422 0.301 2,814 -3.286 16.112 7.314 21.634 Total 1973-01 -0.186 1.713 0.843 3.376 0.329 2,746 -2.069 9.416 6.469 13.699 The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). P is market value of common equity at fiscal year-end. A is total assets. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). B is book value at fiscal year-end; E is earnings (income before extraordinary items). ATTI is estimated after-tax taxable income (see Section III for details). ∆ denotes the change in the variable (before the deflation) relative to the previous year.

34

TABLE 4 Cross-sectional Regressions of Next Year’s Earnings on Estimated Taxable Income and Control Variables

(Expressions 4 and 5) Panel A: Levels specification

FE/A = �=

99


(4)

Years 1/A B/A E/A ATTI/A Mean R2 Mean N Sub1 1973-86 -0.058 0.009 0.893 0.209 0.680 2,864 -3.407 2.876 33.144 7.508 Sub2 1987-00 -0.066 0.000 0.670 0.417 0.457 3,051 -5.408 -0.012 19.537 16.293 Total 1973-00 -0.062 0.004 0.782 0.313 0.569 2,957 -6.015 1.559 25.775 11.458 Panel B: Changes specification

∆FE/A = �=

99


(5)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N Sub1 1973-86 -0.059 0.004 -0.091 0.236 0.111 2,691 -3.553 0.491 -3.702 8.696 Sub2 1987-00 -0.103 -0.023 -0.176 0.317 0.115 2,888 -11.037 -2.797 -11.500 10.217 Total 1973-00 -0.081 -0.009 -0.134 0.277 0.113 2,790 -7.897 -1.458 -8.146 12.757 The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). FE is next year’s earnings (income before extraordinary items). A is total assets. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). B is book value at fiscal year-end. E is earnings. ATTI is estimated after-tax taxable income (see Section III for details). ∆ denotes the change in the variable (before the deflation) relative to the previous year.

35

TABLE 5 Cross-sectional Regressions of Next Year’s Stock Return

on Estimated Taxable Income and Control Variables (Expressions 6 and 7)

Panel A: Using all control variables

R = �=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β5 BETA + β6 VOL + β7 ATTI/P + ε

(6)

Years SIZE B/P E/P BETA VOL ATTI/P Mean R2 Mean N Sub1 1973-86 -0.023 0.024 0.261 -0.007 -0.341 0.347 0.158 2,042 -3.411 1.493 2.434 -0.568 -1.311 3.227 Sub2 1987-99 -0.006 0.021 -0.039 0.020 0.034 0.317 0.098 2,383 -1.445 1.223 -0.257 1.129 0.120 1.943 Total 1973-99 -0.015 0.023 0.117 0.006 -0.160 0.333 0.129 2,206 -3.459 1.958 1.230 0.539 -0.838 3.521 Panel B: Excluding BETA and VOLAT

R = �=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β7 ATTI/P + ε

(7)

Years SIZE B/P E/P ATTI/P Mean R2 Mean N Sub1 1973-86 -0.018 0.036 0.234 0.428 0.138 2,408 -2.004 1.863 2.162 3.448 Sub2 1987-99 -0.003 0.024 0.010 0.379 0.085 2,945 -0.512 1.245 0.076 2.201 Total 1973-99 -0.011 0.030 0.126 0.404 0.113 2,667 -1.943 2.248 1.472 3.927 The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). The annual return (R) is measured from May 1 of year t+1 through April 30 of year t+2. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). SIZE (log of market value of equity) is measured at the end of April in year t+1. B is book value at fiscal year-end. P is market value of common equity at fiscal year-end. E is earnings (income before extraordinary items). BETA is estimated using monthly stock returns and the CRSP value-weighted returns including all distributions during the five years that end in April of year t+1 (at least 30 observations are required). VOL is the root mean squared error from the BETA regression. ATTI is estimated after-tax taxable income (see Section III for details).

36

TABLE 6 Annual Buy-and-Hold Portfolio Returns and Other Characteristics for Portfolios Sorted by

a Tax-based Proxy for Earnings Quality Quintile ATTI/E R SAR AR SIZE B/P E/P BETA VOL

1 -0.015 0.184 0.003 0.000 10.753 0.946 0.090 1.112 0.137

0.372 -0.058

2 0.404 0.179 0.003 -0.003 11.472 0.863 0.098 1.073 0.113

0.483 -0.532

3 0.590 0.182 0.005 0.000 11.601 0.830 0.101 1.028 0.102

0.491 0.011

4 0.853 0.199 0.021 0.018 11.642 0.759 0.101 1.076 0.105

2.521 2.271

5 1.346 0.212 0.032 0.027 11.476 0.836 0.094 1.074 0.109 5.489 4.882

The numbers reported in each cell are the time-series mean of the cross sectional means of those variables for each portfolio. For the two abnormal return measures, also reported are the t-statistic associated with the time-series distribution of the cross-sectional means. The proxy for earnings quality used in sorting the portfolios is the within industry (2 digit SIC code) rank of ATTI/E, where ATTI is after-tax estimated taxable income (see Section III for details) and E is earnings (income before extraordinary items). The annual returns (R, AR, SAR) are measured from May 1 of year t+1 through April 30 of year t+2. R is total return, SAR is size-adjusted return, and AR is size and B/P adjusted return (see section V for details). SIZE (log of market value of equity) is measured at the end of April in year t+1. B is book value at fiscal year-end. P is the market value of common equity at fiscal year-end. E is earnings (income before extraordinary items). BETA is estimated using monthly stock returns and the CRSP value-weighted returns including all distributions during the five years that end in April of year t+1 (at least 30 observations are required). VOL is the root mean squared error from the BETA regression.

37

TABLE 7 Cross-sectional Regressions of Next Year’s Stock Return

on Tax-based Proxies for Earnings Quality and Control Variables

R = �=

99

1ii1iDβ + β2 SIZE + β3 B/P + β4 E/P + β5 BETA + β6 VOL + β7 DHQ + β8 DLQ + β9 ACC + β10 C/P + ε

(9)

SIZE B/P E/P BETA VOL DHQ DLQ ACC C/P Mean R2 Mean N -0.015 0.028 0.280 0.005 -0.202 0.019 -0.005 0.127 1,959 -3.509 2.059 2.365 0.427 -0.997 3.774 -0.418

-0.016 0.017 0.296 0.007 -0.137 0.017 -0.007 -0.370 0.132 1,959 -3.815 1.358 2.557 0.568 -0.667 3.222 -0.559 -7.020

-0.016 0.009 0.118 0.005 -0.196 0.014 -0.005 0.146 0.131 1,959 -3.735 0.686 1.022 0.447 -0.959 2.725 -0.438 6.840

-0.017 0.011 0.224 0.007 -0.151 0.015 -0.007 -0.282 0.061 0.133 1,959 -3.861 0.845 2.182 0.545 -0.744 2.936 -0.542 -3.664 1.859

The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). The annual return (R) is measured from May 1 of year t+1 through April 30 of year t+2. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). SIZE (log of market value of equity) is measured at the end of April in year t+1. B is book value at fiscal year-end. P is market value of common equity at fiscal year-end. E is earnings (income before extraordinary items). BETA is estimated using monthly stock returns and the CRSP value-weighted returns including all distributions during the five years that end in April of year t+1 (at least 30 observations are required). VOL is the root mean squared error from the BETA regression. DHQ (DLQ) is a dummy variable that equals one for firms in the top (low) earnings quality quintile. The proxy for earnings quality used in defining DHQ and DLQ is the within industry (2 digit SIC code) rank of ATTI/E, where ATTI is after-tax estimated taxable income (see Sections III and V for details) and E is earnings (income before extraordinary items). ACC is the accrual component of operating income divided by average total assets. C is the cash component of operating income.

38

TABLE 8 Cross-sectional Regressions Using an Alternative Measure of Taxable Income (10)

Panel A: Price – levels specification

P/A = �=

99


(2)

Years 1/A B/A E/A ATTI/A Mean R2 Mean N 1987-01 -0.838 1.213 9.719 1.975 0.719 3,403

-1.354 19.670 24.741 8.595 Panel B: Price – changes specification

∆P/A = �=

99


(3)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N 1987-01 -0.598 2.247 1.240 2.521 0.318 3,081

-2.732 15.990 13.971 11.059 Panel C: Future Earnings - levels specification

FE/A = �=

99


(4)


-6.819 0.493 21.467 13.848 Panel D: Future earnings – changes specification

∆FE/A = �=

99


(5)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N 1987-00 -0.149 -0.012 -0.139 0.165 0.112 3,162

-9.925 -1.570 -6.965 5.717 Panel E: Future stock returns

R = �=

99


(6)

Years SIZE B/P E/P BETA VOL ATTI/P Mean R2 Mean N 1987-99 -0.006 0.010 -0.021 0.022 0.080 0.250 0.116 2,500

-1.364 0.552 -0.129 1.218 0.265 1.449 The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). P is market value of common equity at fiscal year-end; A is total assets. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). B is book value at fiscal year-end. E is earnings (income before extraordinary items). ATTI is estimated after-tax taxable income, measured based on income taxes paid during the year (see Section VIII for details). ∆ denotes the change in the variable (before the deflation) relative to the previous year. FE is next year’s earnings. The annual return (R) is measured from May 1 of year t+1 through April 30 of year t+2. SIZE (log of market value of equity) is measured at the end of April in year t+1. BETA is estimated using monthly stock returns and the CRSP value-weighted returns including all distributions during the five years that end in April of year t+1 (at least 30 observations are required). VOL is the root mean squared error from the BETA regression.

39

TABLE 9 Cross-sectional Regressions Focusing on Firms with Little or No Foreign Income

Panel A: Price – levels specification

P/A = �=

99


(2)

Years 1/A B/A E/A ATTI/A Mean R2 Mean N 1984-01 0.451 1.186 7.802 3.823 0.716 2,709

1.307 20.205 18.435 10.343 Panel B: Price – changes specification

∆P/A = �=

99


(3)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N 1984-01 -0.311 1.989 0.664 4.293 0.308 2,383

-3.443 16.474 7.468 22.059 Panel C: Future Earnings - levels specification

FE/A = �=

99


(4)


-5.478 0.100 19.953 17.095 Panel D: Future earnings – changes specification

∆FE/A = �=

99


(5)

Years 1/A ∆B/A ∆E/A ∆ATTI/A Mean R2 Mean N 1984-00 -0.105 -0.020 -0.172 0.323 0.125 2,446

-10.330 -2.987 -11.964 12.184 Panel E: Future stock returns

R = �=

99


(6)

Years SIZE B/P E/P BETA VOL ATTI/P Mean R2 Mean N 1984-99 -0.004 0.030 0.019 0.014 -0.165 0.361 0.114 1,981

-0.870 1.886 0.142 0.984 -0.666 2.317 The first row reports the mean of the cross sectional coefficient and the second row reports the associated t-statistic (the ratio of the mean cross-sectional coefficient to its standard error). P is market value of common equity at fiscal year-end; A is total assets. Di is a dummy variable that equals one if the firm belongs to industry i (two digit SIC code). B is book value at fiscal year-end. E is earnings (income before extraordinary items). ATTI is estimated after-tax taxable income (see Section III for details). ∆ denotes the change in the variable (before the deflation) relative to the previous year. FE is next year’s earnings. The annual return (R) is measured from May 1 of year t+1 through April 30 of year t+2. SIZE (log of market value of equity) is measured at the end of April in year t+1. BETA is estimated using monthly stock returns and the CRSP value-weighted returns including all distributions during the five years that end in April of year t+1 (at least 30 observations are required). VOL is the root mean squared error from the BETA regression.

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