tax conformity of earnings and the pricing of accruals

ORI GINAL RESEARCH

Tax conformity of earnings and the pricing of accruals

Anıbal Baez-Dıaz • Pervaiz Alam

Published online: 9 March 2012� Springer Science+Business Media, LLC 2012

Abstract The primary purpose of this study is to investigate whether the market prices

discretionary and non-discretionary tax accruals. Previous studies have examined the

persistence of total accruals (Sloan in Account Rev 71(3):289–315, 1996) and the per-

sistence of discretionary and non-discretionary components of total accruals (Xie in

Account Rev 76(3):357–373, 2001). These studies do not investigate the tax components of

accruals. We argue that tax accruals are mispriced more than book accruals because of the

complexity of tax accruals in assessing future earnings. We use a sample of 6,397 firms and

the Mishkin model to investigate whether the market overvalues tax accruals more than

book accruals. Descriptive statistics show that firms are increasingly using more income

decreasing tax accruals than income-increasing book accruals contributing to the growing

divergence between tax and book earnings. Results from the Mishkin test show that the

overpricing of tax accruals is more severe than that for book accruals. Finally, hedge

portfolio tests show that investors can earn excess returns using a hedging strategy based

on tax accruals. Interestingly, excess returns based on a hedging strategy using book

accruals almost disappear.

Keywords Accrual mispricing � Tax conformity � Discretionary accruals �Nondiscretionary accruals

JEL Classification M41

A. Baez-DıazDepartment of Accounting, College of Business Administration, University of Puerto Rico,San Juan, PR, USAe-mail: [email protected]

P. Alam (&)Department of Accounting, College of Business Administration, Kent State University,Kent, OH 44242, USAe-mail: [email protected]

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Rev Quant Finan Acc (2013) 40:509–538DOI 10.1007/s11156-012-0275-2

1 Introduction

The purpose of this study is to examine the nature of the information contained in the tax

and book accrual components of earnings and the extent to which information in these

variables is reflected in stock returns. Sloan’s (1996) pioneering work shows that the

market misprices total accruals. Xie (2001) decomposed total accruals into discretionary

and non-discretionary accruals and found that overpricing of total accruals is primarily due

to the discretionary portion. We contribute to the accruals mispricing literature by dividing

total accruals into book (discretionary and non-discretionary) and tax (discretionary and

tax) accruals. Previous studies have not examined the persistence of (discretionary and

non-discretionary) tax accruals. Our disaggregation of total accruals provides a more

comprehensive understanding of how the stock market interprets managers’ accounting

decisions that affect both book and tax accruals. We argue that the market’s mispricing of

tax accruals is more serious than the mispricing of book accruals because of the complexity

of tax accruals (Chen and Schoderbek 2000; Shane and Stock 2006). We also believe that

book-tax income differences can be better understood if we know how the market prices

book versus tax accruals. We follow Calegari (2000) for decomposing total accruals (TAC)

into discretionary tax accruals (DTA), non-discretionary tax accruals (NDTA), discre-

tionary book accruals (DBA), and non-discretionary book accruals (NDBA).1

The divergence between taxable income and accounting earnings was brought to public

attention in July 1999 when a Treasury Department White Paper cited this growing dis-

crepancy as possible evidence of increased tax-shelter activity (Department of the US

Treasury, Office of Tax Policy 1999). In 2003, the US Treasury issued new tax shelter

regulations, under Section 6011, which require the disclosure of significant tax differences

outside the predictable range.2 The regulations significantly broadened the disclosure

requirements and provide the Internal Revenue Service (IRS) and the Treasury with

information needed to evaluate potentially abusive transactions. Prior studies examine the

divergence between reported earnings and taxable income to investigate earnings man-

agement, debt financing, and tax shelter activities. Generally, these studies suggest that low

divergence between tax and financial accounting rules may increase the quality of reported

earnings (Mills 1998; Mills and Newberry 2001; Mills et al. 2002; Canellos and Kleinbard

2002; Desai 2003; Lev and Nissim 2004; Hanlon 2005). However, there is growing evi-

dence which suggests that it is unlikely that conforming taxable income and accounting

earnings will reduce the amount of tax sheltering by corporations. For instance, Hanlon

et al. (2006) found that increased tax conformity reduces the information content of

earnings because managers would rather report taxable earnings and pay additional taxes

than convey private information about firm performance.

Some studies show that firms increase their tax conformity to minimize chances of IRS

scrutiny (Cloyd 1995; Cloyd et al. 1996; Guenther and Maydew 1997; Northcut and Vines

1998). In addition, current accounting standards allow firms to simultaneously use accruals

with relatively high tax conformity to achieve tax planning goals and those with relatively

1 Book accruals have relatively low tax conformity. They affect reported earnings but do not affect thefirm’s taxable income. Tax accruals have higher tax conformity because the tax code allows similar or equaltreatment when computing the firm’s taxable income. Thus, tax accruals affect both taxable income andreported earnings (Calegari 2000).2 These rules generally became effective for transactions on or after January 1, 2003. Under the regulations,six classes of reportable transactions have been created: (1) confidential transactions, (2) transactions withcontractual protection, (3) loss transactions, (4) transactions with significant tax differences, (5) transactionsinvolving a brief asset holding period and (6) IRS listed transactions.

510 A. Baez-Dıaz, P. Alam

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low tax conformity to accomplish financial reporting objectives (Manzon 1992; Guenther

1994; Guenther and Maydew 1997; Calegari 2000). In many cases, taxable income and

book income are sufficiently similar so that revenues and expenses are recognized in the

same period for both tax and financial reporting purposes (Manzon 1992; Guenther 1994;

Guenther et al. 1997; Calegari 2000). These similarities allow managers to choose either

book or tax accruals to reduce book income in order to minimize political costs, subsequent

IRS audits, and higher tax payments (Guenther 1994; Northcut and Vines 1998). Thus,

high tax conformity does not necessarily suggest better financial reporting and low tax

conformity should not be interpreted as evidence of poor financial reporting. Despite this,

the increasing divergence of book and taxable earnings raises the question of whether

security prices reflect an unbiased estimate of future earnings.

In an efficient market, the participants correctly impound the value of current earnings

components for future earnings. Nevertheless the complexity of accruals impedes a clear

understanding of their implications for future earnings since it is difficult to assess the

intentions of managers when they select different types of accruals. In the case of tax

accruals, this problem is more severe because neither the tax authorities nor the financial

reporting standards require detailed public disclosure of such accruals. Even if these tax

accruals were made available to the market, there is still the possibility that the market may

not fully comprehend the mechanics and consequences of different tax rules behind such

accruals. These complications raise the possibility that stock prices do not fully reflect the

contribution of all earnings components towards future earnings.

It is also possible that investors misprice the impact of these accruals on stock prices if

they accept the accruals at face value without adjusting them for their long-term effects. In

1996, Sloan introduced the accrual anomaly, which is characterized by the US stock

market over-weighting the role of accrual persistence and under-weighting the role of

operating cash flow persistence for future earnings (Zach 2003). As a result, a trading

strategy based on publicly available book accruals earns abnormal returns in the year

following the publication of financial statements. Bartov and Myungim (2004) found that

following a joint strategy of book-to-market ratios and accruals, the mispricing of stocks is

more common among firms held by unsophisticated investors than for firms followed

extensively by institutions and analysts. The accrual anomaly has been examined by other

studies (i.e., Heyns et al. 1999; Xie 2001; DeFond and Park 2001; Fairfield et al. 2003;

Rajgopal et al. 2003; Hanlon 2005; Dopuch et al. 2010). Even though these studies con-

sider the valuation implications of accruals, they do not examine how taxes affect the

extent to which the market uses financial information efficiently.3

We contribute to the ongoing tax conformity research, with particular emphasis on

investigating whether the decomposition of total accruals into book and tax accruals

3 Prior studies suggest that capital market participants are unable to fully capture accounting numbers thatresult from complex tax rules. Nor does the market anticipate and correctly interpret income effects of tax-motivated income shifting. Shaw (1990) reports that the lack of complete disclosure of earning componentsimpairs the analysts’ and investors’ ability to predict the earnings effects of some transactions related totaxes. Chen and Schoderbek (2000) and Chen et al. (2003) examine how investors and analysts assess theincome effects of the deferred tax adjustment caused by the Omnibus Budget Reconciliation Act of 1993.They find evidence indicating that investors and analysts are fixated on reported accounting numbers andinterpret accounting information without regard to the rules used to produce it. These authors suggest thatthe complexity of deferred tax adjustments and disclosures may have contributed to the failure of investorsand analysts to properly interpret the reported earnings. Shane and Stock (2006) report that market pricesand analysts’ earnings per share forecasts fail to reflect unbiased expectations regarding firms’ incentives toshift income from high to low tax rate years. In general, these studies suggest that market prices do not fullyreflect the future earnings implications of current earnings components.

Tax conformity of earnings and the pricing of accruals 511

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provide us a better understanding of why the accrual component of earnings is less per-

sistent than the cash flow component of earnings and why the market overestimates the

persistence of accruals. Thus, this study has two goals. First, we examine whether or not

tax conformity affects the market’s ability to correctly price the accrual components of

earnings. Second, we investigate if a trading strategy based on both publicly available tax

accruals and book accruals information earn abnormal returns in the years following the

publication of the financial statements. We use a sample of 6,397 US firms to perform

empirical analysis. Our evidence demonstrates that firms are increasingly using income

decreasing tax accruals rather than income-increasing book accruals, contributing to the

growing divergence between tax and book accruals. The Mishkin test shows that over-

pricing is more severe for tax accruals than book accruals. In addition, our results show that

a hedge portfolio based on discretionary (non-discretionary) tax accruals yields positive

size adjusted returns even 3 (two) years after portfolio formation. Finally, the hedge

portfolio returns are generally insignificant for book accruals.

2 Research design

2.1 Hypotheses development

The Tax Reform Act of 1986 (TRA86) strengthened the link between tax and book income

by requiring large companies (defined as those with sales in excess of $5 million) to use the

accrual method of accounting for tax purposes (Guenther et al. 1997). Sections 446(a) and

461(a) of the Internal Revenue Code sets forth the general rule for how taxable income is

computed, and how deductions are taken under the accounting method that the corporation

normally uses for its books.4 This furthers the goal of tax accounting to clearly reflect

income by preventing a corporation from using one method to report high income to

shareholders and another method to report low income to the IRS. While both temporary

and permanent tax differences continue under these rules, a predictable relationship

between financial and tax reporting is likely to exist since the underlying business activities

are the same (Plesko 2003).

Empirical research suggests that managers choose book accruals to reduce book income

in order to minimize their political costs (Guenther 1994; Guenther et al. 1997; Northcut

and Vines 1998). Guenther (1994) investigates whether accounting earnings of US cor-

porations are managed in response to changes in the statutory corporate income tax rate.

He finds that reductions in corporate tax rates provide an incentive for managers to

decrease financial statement income in the year prior to the effective date of the Tax

Reform Act of 1986 (TRA86). Furthermore, Guenther et al. (1997) find evidence that

publicly-traded firms that were required by TRA86 to switch from the cash basis to the

accrual basis for tax purposes decided to defer income for financial reporting purposes in

order to maximize their tax savings. Northcut and Vines (1998) investigate whether

political scrutiny of corporate effective tax rates influences accounting policy choices.

They suggest that managers are willing to reduce book income in order to reduce the

probability of higher taxes.

4 I.R.C. 446(a) states: ‘‘Taxable income shall be computed under the method of accounting on the basis ofwhich the taxpayer regularly computes his income in keeping his books’’. I.R.C. 461(a) provides: ‘‘Theamount of any deduction or credit allowed by this subtitle shall be taken for the taxable year which is theproper taxable year under the method of accounting used in computing taxable income’’ (US Tax CodeOn-Line, http://uscode.house.gov/title_26.htm).


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http://uscode.house.gov/title_26.htm

In general, economic theory dictates that managers will choose financial accounting

methods that conform to methods selected for income tax purposes when the expected

benefits exceed the expected costs. Cloyd et al. (1996) and Cloyd (1995) suggest two

potential benefits from tax conformity: (1) it reduces the probability of an IRS challenge by

eliminating the need to report to the IRS a book-tax difference5 which may serve to ‘‘red

flag’’ tax returns for IRS scrutiny, and (2) it also increases the chance of successfully

defending an aggressive position challenged by the IRS.6 On the other hand, Calegari

(2000) suggests that firms adjust debt ratios and discretionary accruals with relatively high

tax conformity (tax accruals) to achieve tax-planning goals and use discretionary accruals

with relatively low tax conformity (book accruals) to accomplish financial reporting

objectives.

Using actual IRS audit adjustment data, Mills (1998) finds that firms with greater tax

differences face larger subsequent IRS audit adjustments. Keating and Zimmerman (2000)

document managers’ reluctance to make income-increasing revisions when the revision has

potential tax ramifications. Hanlon (2005) finds that firms with large tax differences7 (low

conformity) have earnings that are less persistent than firms with small tax differences

(high conformity). Her evidence is consistent with investors interpreting large positive tax

differences (book income greater than taxable income) as a ‘‘red flag’’. In addition, Hanlon

(2005) finds that analysts use the tax differences information in a manner similar to

investors. In summary, the current literature suggests that firms cannot costlessly maximize

financial reporting income and tax savings independently.8

We examine whether the market rationally prices the properties of the accrual and cash

flow components of earnings. In an efficient market, stock prices reflect all publicly

available information. However, prior studies find evidence showing that the market’s

expectations embedded in stock prices consistently deviate from rational expectations

(Sloan 1996; Heynes et al. 1999; Collins and Hribar 2000; DeFond and Park 2001; Xie

2001; Hanlon 2005). Prior studies (Shaw 1990; Chen and Schoderbek 2000; Chen et al.

2003; Shane and Stock 2006) also reveal that lack of complete disclosure of earnings

components impairs the market’s ability to predict the earnings effects of transactions

related to taxes. On the other hand, consistent with Statement of Financial Accounting

Concepts No. 1 (FASB 2000, SFAC No. 1, }34, 37 and 40), non-discretionary book

accruals are less subject to managerial discretion and are intended to improve the pre-

dictive ability of the accounting information. Consequently, non-discretionary book

accruals are more aligned with the financial reporting system and are predicted to have

higher persistence than the other accrual components. Following Sloan (1996), we believe

that cash flow from operations will be most persistent and that it will be underpriced by the

5 The Schedule M-1 of Form 1120-US Corporation Income Tax Return requires a reconciliation of income(loss) per books with income per tax return.6 On the other hand, because tax savings are generally maximized by deferring revenues and by acceleratingexpenses, tax conformity may also impose significant non-tax costs on the firms. Tax conformity may depictthe firm to external parties (i.e., actual and potential investors, lenders, suppliers, etc.) as relatively worse offthan it would be portrayed without conformity, may increase the probability of violating some debt cove-nants, and it may also reduce managers’ compensation tied to book income (Cloyd et al. 1996).7 Hanlon (2005) uses deferred tax asset and liability accounts to classify firms into one of two groups:positive tax differences or negative tax differences. It is important to note that deferred tax accountsrepresent only a subset of total accruals.8 Graham et al. (2008) report that book-tax differences arise because of tax planning, general businessconditions, earnings management, changes in financial accounting rules, changes in sales, and the level ofproperty, plant, and equipment.


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market. Furthermore, based on the findings of Xie (2001), we assume that discretionary tax

accruals and discretionary book accruals will be overpriced and that they will be less

persistent than non-discretionary tax accruals and non-discretionary book accruals,

respectively. Thus, the following hypothesis is proposed in the alternate format:

H1 Ceteris paribus, the market fails to correctly price the persistence of discretionary and

non-discretionary components of book and tax accruals.

The financial consequences associated with the company’s tax accruals may be more

complex for the market to impound in stock prices because of the limited disclosure of

corporate tax information. In addition, book-tax conformity may induce tax conservatism,

which could reduce the information content of earnings (Hanlon et al. 2006). Thus, we

predict that the market’s inability to correctly assess the persistence of accruals is more

severe for tax accruals than for book accruals because of the complexity associated with

tax accruals (Shaw 1990; Chen and Schoderbek 2000; Chen et al. 2003; Shane and Stock

2006). In addition, because non-discretionary book accruals are not influenced by complex

tax rules, market participants are more likely to interpret them correctly. Thus, the fol-

lowing hypothesis is proposed in the alternate format:

H2 Ceteris paribus, the market mispricing of tax accruals is more severe than book

accruals.

Sloan (1996) and Xie (2001) indicate that the mispricing of accruals is corrected when

realized future earnings are lower (higher) than expected, resulting in predictable negative

(positive) abnormal stock returns. If the market mispricing is more severe for the tax

accrual components of earnings then a strategy that exploits this mispricing can be

implemented to generate abnormal returns. A trading strategy that takes a long position in

the stock of firms with high tax accruals and a short position in the stock of firms with low

tax accruals is expected to generate positive abnormal stock returns. This forms the basis

for the next alternate hypothesis:

H3 A trading strategy based on the level of tax accruals generates positive abnormal

stock returns.

Mishkin (1983) provides a methodology to test the rational expectations hypothesis in

macroeconomics (hereafter the Mishkin test). Accounting researchers have used the

Mishkin test to examine the market valuation of the earnings components (e.g., Sloan

1996; Xie 2001; Kao 2007). The Mishkin test and the hedge portfolio test will be used to

examine whether the market rationally values the tax and book components of accruals.

2.2 Variable measurement9

The Center for Research in Security Prices (CRSP) monthly returns file is used to measure

annual buy-and-hold returns (RETURN) for the 12-month period ending three months after

the firm’s fiscal year end. Following Subramanyam’s (1996) and Xie (2001), earnings

(EARN) are defined as earnings before extraordinary items (Compustat data item 18), and

cash flow from operations (CFO) is net cash flow from operating activities reported in the

Statement of Cash Flows (Compustat data item 308).

In order to measure discretionary accruals, the procedure used by Calegari (2000) is

adopted. Discretionary accruals are estimated as the difference between total accruals and

9 All variables used in this study are defined in Table 1.


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estimated non-discretionary accruals. Consistent with previous studies of earnings man-

agement (Healy 1985; Jones 1991; Dechow et al. 1995; Calegari 2000; Fairfield et al.

2003), total accruals (TACi,t) for firm i in year t are computed as follows:

TACi;t ¼ DCAi;t þ DSTDEBTi;t � DCLi;t � DCASHi;t � DEPi;t; ð1Þ

where, DCAi,t is the change in current assets (Compustat data item 4) for firm i between

years t - 1 and t. Similarly, DSTDEBT is the change in the current portion of long-term

debt (Compustat data item 44), DCL is the change in current liabilities (Compustat data

item 5), DCASH is the change in the cash balance (Compustat data item 162), and DEP is

the depreciation and amortization expense (Compustat data item 14). All variables are

deflated by total assets (Compustat data item 6) at the beginning of the year.

To estimate total tax accruals (TTA), certain accrual items that do not have high tax

conformity are removed10:

TTAi;t ¼ TACi;t � DOCAi;t � DTAXRECi;t þ DOCLi;t þ DTAXPAYi;t þ DEPi;t; ð2Þ

where DTAXPAY is the change in income taxes payable (Compustat data item 71) for firm

i between years t - 1 and t. Likewise, DOCL is the change in other current liabilities

(Compustat data item 72), DTAXREC is the change in income taxes receivable (Compustat

data item 161), and DOCA is the change in other current assets (Compustat data item 68).

DTAXPAY and DTAXREC are eliminated because these variables represent income taxes

due or receivable from the government and therefore are not part of the corporation’s

taxable income. DOCL is removed from TTA because it includes deferred income taxes,

estimated claims, reserves, and related party payables, which are not currently deductible

for income tax purposes unless they meet the all-events test. DEP is removed because tax

depreciation and amortization deductions are not affected by the amounts of depreciation

reported on the financial statements. Lastly, DOCA11 is removed because it includes

deferred charges (including deferred taxes), prepaid income taxes, and the cash surrender

value of life insurance policies, which are not currently included in taxable income. In

essence, total tax accruals (TTA) consists of changes in current assets and current liabilities

that are treated relatively similarly for book and tax purposes and therefore do not cause

temporary or permanent differences between book income and taxable income (e.g.,

receivables, inventory, trade accounts payable, etc.).

Total book accruals (TBA), which consist of accruals that have relatively low tax

conformity, are estimated by subtracting total tax accruals (TTA) from total accruals

(TAC).

TBAi;t ¼ TACi;t � TTAi;t; ð3Þ

The modified Jones model is used to estimate non-discretionary tax and non-discre-

tionary book accruals (Dechow et al. 1995; Rees et al. 1996):

TTAi;t ¼ d0 þ d1DADJREVi;t þ d2CFOi;t þ ti;t; ð4Þ

10 Plesko (2007) computes tax accruals by taking the difference between book and taxable income. He thenuses the Jones (1991) model to derive the discretionary and non-discretionary components of tax accruals.11 This item represents current assets that are not included in cash, cash equivalents, receivables orinventory on the balance sheet. It also includes prepaid expenses (e.g., prepaid insurance, advertising, andrent) that cause temporary differences between taxable income and book income (Dyckman et al. 1998).


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TBAi;t ¼ d0 þ d1DADJREVi;t þ d2CFOi;t þ d3GPPEi;t þ ti;t; ð5Þ

where, DADJREV is the change in revenues (Compustat data item 12) minus the change in

receivables (Compustat data item 302) for firm i in year t, CFO is the cash flow from

operations (Compustat data item 308), and GPPE is the gross property, plant, and equip-

ment (Compustat data item 7). All variables are deflated by total assets at the beginning of

the year. GPPE is not included in Eq. 4 because tax accruals do not include depreciation.

The coefficients in Eqs. 4 and 5 are estimated separately for each combination of two-

digit SIC code and calendar year. The predicted values of the Jones model are denoted as

non-discretionary tax accruals (NDTA) and non-discretionary book accruals (NDBA).

Discretionary tax accruals (DTA) and discretionary book accruals (DBA) are the residuals

from Eqs. 4 and 5, respectively. In other words, they are computed as follows12:

DTAi;t ¼ TTAi;t � a0;t;p þ a1;t;pDADJREVi;t þ a2;t;pCFOi;t

� �ð6Þ

DBAi;t ¼ TBAi;t � b0;t;p þ b1;t;pDADJREVi;t þ b2;t;pCFOi;t þ b3;t;pGPPEi;t

� �ð7Þ

where a0,t,p, a1,t,p, a2t,p, b0,t,p, b1,t,p,b2,t,p and b3,t,p are the parameter estimates for year t and

SIC portfolio p from Eqs. 4 and 5. Figure 1 shows the decomposition of total accruals into

total tax and book accruals and then into four components: DTA, NDTA, DBA, and

NDBA.

Discretionary Tax

Accruals (DTA)

Non-discretionary Tax Accruals

(NDTA)

Discretionary Book

Accruals (DBA)

Non-discretionary Book Accruals

(NDBA)

Total Tax

Accruals(TTA)

Total Book

Accruals(TBA)

Total Accruals

(TAC)

Fig. 1 Decomposition of total accruals

12 A similar procedure has been used by DeFond and Jiambalvo (1994), Subramanyan (1996), and Xie(2001).


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2.3 The Mishkin test

The first hypothesis (H1) predicts that firms’ stock returns fail to correctly reflect the

persistence attributable to the accrual components of earnings. Furthermore, H2 predicts

that the mispricing problem is more severe for the tax accrual components than the book

accruals. These predictions are examined using the Mishkin test. The Mishkin test is used

to examine whether the market rationally prices discretionary tax accruals (DTA), dis-

cretionary book accruals (DBA), non-discretionary tax accruals (NDTA), and non-

discretionary book accruals (NDBA) with respect to their 1-year-ahead earnings. The

following regression system is used to test hypothesis H1:

EARNtþ1 ¼ a0 þ a1CFOt þ a2DTAt þ a3NDTAt þ a4DBAt þ a5NDBAt þ ttþ1; ð8Þ

SARtþ1¼b0þb1 EARNtþ1�a�0�a�1CFOt�a�2DTAt�a�3NDTAt�a�4DBAt�a�5NDBAt

� �

þ etþ1; ð9Þ

where as are the persistence coefficients of earnings’ components and a�s are the market’s

valuation coefficients of earnings components.

Following Sloan (1996) and Xie (2001), size-adjusted abnormal returns (SARt) are

calculated as the difference between a company’s annual buy-and-hold return and the

annual buy-and-hold return for the same 12-month period on the market portfolio decile

to which the firm belongs. Therefore, the return variable is both, size-adjusted and

abnormal. The CRSP size decile breakpoints are used to classify each firm into a size

decile according to its market value of equity at the beginning of the calendar year in

which the 12-month return period begins. The rest of the variables are defined as

before.

Equations 8 and 9 are estimated jointly as in Mishkin (1983) using an iterative gen-

eralized nonlinear least squares estimation procedure. Equation 8 is the forecasting

equation that estimates the forecasting coefficients (as) of discretionary accruals and the

other components of earnings for predicting 1-year-ahead earnings. Equation 9 is the

valuation equation that estimates the valuation coefficients (a�s ) that the market assigns to

abnormal accruals and other earnings components. The Mishkin test is applied in two

stages.

In the first stage, Eqs. 8 and 9 are jointly estimated without imposing any constraints on

the forecasting (as) and valuation (a�s ) coefficients to test whether the a�s coefficients are

significantly different from their counterpart as coefficients (s = 1, 2, 3, and 4). In the

second stage, Eqs. 8 and 9 are jointly estimated after imposing the rational pricing con-

straints, aq ¼ a�q. Mishkin (1983) shows that the following likelihood ratio statistic is

asymptotically v2 (q) distributed under the null hypothesis that the market rationally prices

the earnings’ components with respect to their association with 1-year-ahead earnings:

2NLn SSRc=SSRuð Þ

where, q = the number of rational pricing constraints imposed, N = the number of sample

observations, Ln = natural logarithm operator, SSRc = the sum of squared residuals from

the most constrained system in the second stage. SSRu = the sum of squared residuals

from the most unconstrained system in the first stage. A supplemental test is performed by

estimating the Mishkin test after controlling for the growth in net operating assets (Fairfield

et al. 2003).


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2.4 The hedge-portfolio test

Following prior studies (Sloan 1996 and Xie 2001) a trading strategy is designed based on

the results of the Mishkin test performed in the previous section to test Hypotheses H3.

Firms are grouped into portfolio deciles each year based on their ranking of accruals, and

form a hedge portfolio taking a long position in the lowest decile portfolio (most positive)

and a short position in the highest decile portfolio. Portfolio deciles are formed annually

based on the ranking of discretionary tax accruals, non-discretionary tax accruals, dis-

cretionary book accruals and non-discretionary book accruals. The analysis of the trading

strategy is based on the annual abnormal size-adjusted returns for each accrual decile over

the sample period, and the abnormal returns to the hedge portfolio.

An additional test is performed by regressing 1-year ahead size-adjusted abnormal

returns on accrual deciles (ACCtdec). The accrual variable (ACCt

dec) represents accruals

(discretionary tax accruals, non-discretionary tax accruals, discretionary book accruals and

non-discretionary book accruals) for year t divided by total assets at the beginning of the

year ranked into deciles (0–9) each year and scaled by nine so that each observation takes a

value ranging between zero and one. The regression model used is the following:

SARtþ1 ¼ c0 þ c1ACCdect þ etþ1 ð10Þ

Regression in Eq. 10 measures the association of accrual components individually in a

single-variable regression. In order to assess the importance of the accrual components

jointly and individually we perform the following regression.

SARtþ1 ¼ c0 þ c1DTAdect þ c2NDTAdec

t þ c3DBAdect þ c4NDBAdec

t þ etþ1 ð10aÞ

We perform additional tests to control for Fama and French (1992) risk factors and the

Basu anomaly in Eqs. 11 and 12, respectively. Equation 11 shows the relationship of four

Fama–French risk factors in a returns regression.

ERtþ1 ¼ c0 þ c1MRPt þ c2SMBt þ c3HMLt þ c4WMLt þ etþ1 ð11Þ

where, ERt?1 is the excess return (Rpt - Rft) in period t ? 1, Rpt is the monthly calendar-

time portfolio return at month t, and Rft is the risk free return based on 30-day US.

Treasury bill. The other variables are the three Fama–French factors and a momentum

factor: market risk premium (MRP), the size premium (difference between portfolios of

small capitalization versus big capitalization firms, small minus big, SMB), the book to

market risk premium (return differences between high and small book to market firms, high

minus low, HML), and a momentum factor (winners minus losers, WML). Fama and

French (1993, 1996) factors and the momentum factor have been used in previous studies

to control for market anomalies and risk (Carhart 1997; Barber et al. 2001; Jegadeesh

2000; L’Her et al. 2004; Lam et al. 2010). The average abnormal return is captured by the

intercept of Eq. 11.13

Basu (1977, 1983) documented a relationship between price to earnings (P/E) ratio and

future abnormal returns. The earnings of a company with low P/E ratio are not valued as

much as those of a company with a higher P/E ratio. This can be due to expectations of

poor earnings, slow revenue and earnings growth, or negative industry factors, or simply

13 Nguyen et al. (2009) and Vassalou (2003) augment the CAPM and the Fama–French model (1993) with aGDP factor. Nguyen et al. (2009) found that the information about future GDP growth is not priced in equityreturns in the Australian market. On the other hand, Vassalou (2003) using US data reported that premiumrelated to the GDP growth is positive and significant.


123

companies overlooked by the investors. Conversely, high P/E stocks imply high expec-

tations. Basu (1977, 1983) reports that low P/E stocks yield higher average returns than the

high P/E stocks, which seems to indicate that the low P/E stocks are undervalued while the

high P/E stocks are overvalued. Additionally, included in Eq. 12 are size (LnMVtdec), risk

(BETAtdec), and growth (LnBMt

dec) as control variables. Equation 12 controls for the Basu

anomaly and other commonly used controls to examine the association of accrual com-

ponents and size-adjusted returns. The modified model is as follows (Table 1 gives the

definition of variables):

Table 1 Variable definitions

TAC Total accruals scaled by total assets at the beginning of the period

DCA Change in current assets scaled by total assets at the beginning of the period

DSTDEBT Current portion of long-term debt scaled by total assets at the beginning of the period

DCL Change in current liabilities scaled by total assets at the beginning of the period

DCash Change in cash balance scaled by total assets at the beginning of the period

Dep Depreciation and amortization scaled by total assets at the beginning of the period

TTA Total tax accruals scaled by total assets at the beginning of the period

DOCA Change in other current assets scaled by total assets at the beginning of the period

DTAXREC Change in tax receivable scaled by total assets at the beginning of the period

DOCL Change in other current liabilities scaled by total assets at the beginning of the period

DTAXPAY Change in taxes payable scaled by total assets at the beginning of the period

TBA Total book accruals for firm i in year t

DADJREV Change in revenues less change in receivables scaled by total assets at the beginning of theperiod

CFO Cash flow from operations scaled by total assets at the beginning of the period

GPPE Gross property, plant, and equipment scaled by total assets at the beginning of the period

NDBA Total non-discretionary book accruals scaled by total assets at the beginning of the period

DTA Total discretionary tax accruals scaled by total assets at the beginning of the period

NDTA Total non-discretionary tax accruals scaled by total assets at the beginning of the period

DBA Total discretionary book accruals scaled by total assets at the beginning of the period

EARN Income before extraordinary items scaled by total assets at the beginning of the period

SAR Size adjusted abnormal returns computed as the difference between a company’s annual buyand hold return and the annual buy and hold return for 12-month period on the marketportfolio decile to which the firm belong.

ACCdec Accrual for year t scaled by total assets at the beginning of the year ranked into deciles eachyear

MRP Market risk premium

SMB Difference between returns of portfolio of small versus big capitalization firms

HML Difference between returns of high versus low book to market firms

WML Difference between returns of winner versus loser firms

LnMV Firm’s size proxied by the natural logarithm of the firm’s market value

BETA Market model beta estimated using daily returns

LnBM Natural logarithm of the book to market ratio

PE Price to earnings ratio

GrNOA Growth in net operating assets


123

SARtþ1 ¼ c0þ c1ACCdect þ c2LnMVdec

t þ c3BETAdect þ c4LnBMdec

t þ c5PEdect þ etþ1 ð12Þ

2.5 Sample

Table 2 summarizes the sample selection process. The sample comprises all firm years

with available data on the Compustat Annual Industrial and Research files and on the

CRSP stock returns file for NYSE, AMEX, and NASDAQ firms. The sample period is

1986 to 2001. Firm-years, within each industry, with fewer than six observations in any

two-digit SIC code and year combinations were deleted. In addition, firm-years where any

variable in the modified Jones (1991) model has a value that was more than three standard

deviations away from its mean were deleted. This results in 36,516 firm-year observations

with the required financial statement and returns data to perform the Mishkin test. Our

check of the CRSP returns data showed that none of the firms in our final sample had been

delisted. Thus, our returns data is not influenced by delisting bias.14

3 Empirical results

3.1 Descriptive statistics

Table 3 provides descriptive statistics for the variables used in the analysis of the

persistence and pricing of accruals. Mean and median total accruals (TACt), total non-

discretionary accruals (NDACt) and non-discretionary book accruals (NDBAt) are negative

on average because of depreciation and amortization expenses (Subramanyam 1996; Xie

2001; Fairfield et al. 2003). Given that total discretionary accruals (DACt), discretionary

tax accruals (DTAt) and discretionary book accruals (DBAt) are defined as the error term of

the modified Jones (1991) model, their mean and median are close to zero. However, since

the modified Jones model does not have an intercept, the sum of the residuals is not

Table 2 Sample selection process (1986–2001)

Firm-years with all required variables from Compustat 44,861

Less

Missing stock return information from CRSP (6,868)

Compustat and CRSP intersection 37,993

Less

Insufficient data to apply the modified Jones modela (307)

Observations trimmed in order to apply the modified Jones modelb (1,170)

Final Sample (firm-years) 36,516

Firms in the sample 6,397

a Firm-years with fewer than six observations in any two-digit SIC code and year combination was deletedb Firm-years where any variable in the Jones Model has a value that was more than three standardsdeviations away from its mean were deleted (Xie 2001)

14 Beaver et al. (2007) find that tests of market efficiency are sensitive to the exclusion or inclusion ofdelisting returns. Shumway (1997) and Shumway and Walther (1999) recommend that firms with missingdelisting returns should be corrected for the delisting bias. A limitation of our study is that the sample wasidentified using Compustat database which has a survivorship bias. As a result, it is quite possible thatdelisted firms were dropped in the initial sample selection process.


123

necessarily equal to zero (Xie 2001). Finally, discretionary accruals are more variable

(SD = 0.125) than their non-discretionary counterpart (SD = 0.078), but are under-

standably less variable than total accruals (SD = 0.143).

While the mean for earnings (EARNt) and 1-year ahead earnings (EARNt?1) is negative

(-0.020 and -0.030, respectively), their median is positive (0.030 for both).15 The mean

and median for the cash flow from operations is positive (0.036 and 0.065, respectively).

The mean growth in net operating assets is 0.067, the same as Fairfield et al. (2003) but

with higher variation and lower median.

Figure 2 provides time-series plots of mean total tax accruals and book accruals.

Twelve out of sixteen years of the sample report more negative total tax accruals (TTA)

than total book accruals (TBA). Thus, as expected, on average, corporations are using more

income decreasing tax accruals than book accruals. Figure 3 plots discretionary tax

accruals and discretionary book accruals. The figure shows that companies are using more

income decreasing discretionary tax accruals (DTA) than discretionary book accruals

(DBA). A t test comparing the difference between the mean values shows that discre-

tionary tax accruals (DTA) are significantly more negative than the mean value of dis-

cretionary book accruals (DBA) in 7 years.

Table 4 reports the Pearson and Spearman correlations between earnings components

and the variables used in the analysis of the pricing of accruals. It can be seen that current

earnings (EARNt) is positively correlated with each of its components, except non-dis-

cretionary book accruals (NDBAt). The positive correlation is not a surprise since net

income is merely an aggregation of its components. On the other hand, given that one of

the accounting principles is conservatism, it is not surprising that the non-discretionary

Table 3 Descriptive statistics for the sample of 6,397 firms, 1986–2001 (n = 36,516)a

Variable Mean Std Dev Median Minimum Maximum

EARNt -0.0199 0.2333 0.0326 -1.9988 1.7710

EARNt?1 -0.0299 0.4346 0.0315 -50.5351 3.9498

CFOt 0.0362 0.2096 0.0650 -2.4860 1.7099

TACt -0.0366 0.1431 -0.0397 -1.8747 1.3478

DACt 0.0096 0.1247 0.0125 -1.4130 1.2506

NDACt -0.0462 0.0779 -0.0453 -1.1747 1.0636

DTAt 0.0160 0.1112 0.0112 -1.1076 1.2022

NDTAt 0.0159 0.0727 0.0060 -0.9013 1.1682

DBAt -0.0064 0.0829 -0.0007 -1.5053 1.2414

NDBAt -0.0621 0.0542 -0.0534 -1.0264 0.5462

GrNOAt 0.0667 0.2997 0.0000 -5.2023 17.5213

SARt 0.0554 0.6687 0.0078 -8.3196 22.8986

SARt?1 0.0324 0.7168 0.0008 -8.3196 22.8986

a See Table 1 for variable definitions

t = year t and t?1 = one year ahead of year t

15 Compared to previous related studies our median earnings scaled by total assets at the beginning of theperiod are similar. Our sample period runs over 1986–2001. Sloan (1996) reported scaled median earningsof 0.011 over the sample period of 1994–2000, Xie (2001) reported median scaled earnings of 0.048 over thesample period of 1971–1992, and Hanlon (2005) reports median earnings of 0.113 using the sample periodof 1994–2000.


123

book accrual is negatively associated with contemporaneous earnings. Consistent with

prior research (Dechow 1994; Sloan 1996; Subramanyam 1996; Xie 2001; Fairfield et al.

2003) there is evidence of a significant negative correlation between accruals and cash flow

from operations. The Pearson (Spearman) correlation between cash flow from operations

(CFOt) and total accruals (TACt) is -0.20 (-0.28). The relationship between cash flow

from operations and the different components of accruals is also negative and significant.

3.2 Results of the Mishkin test

This section examines whether tax accruals influence investors’ expectations about the

persistence of earnings and its components. A common perception in contemporary

accounting research is that managers opportunistically manipulate accruals such that

extreme accruals tend to reflect greater earnings management resulting in lower earnings

quality (Warfield et al. 1995; Becker et al. 1998; Bartov et al. 2000; Heninger 2001; Klein

Fig. 2 Changes in total tax accruals (TAXACC) and total book accruals (BOOKACC)

Fig. 3 Changes in discretionary tax accruals (DTxACC) and discretionary book accruals (DBoACC)


123

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123

2002; Francis et al. 2004; and Myers et al. 2003). Furthermore, prior studies such as

Chaney and Jeter (1994) report that stock returns are less associated with earnings when

the firm’s tax differences are large or highly variable. These studies assume that earnings

are of lower quality when tax differences are large and that the market prices the shares

accordingly. This stream of work, however, does not examine how tax conformity influ-

ences investors’ expectations about the persistence of earnings and its components. Using

Table 5 Nonlinear generalized least squares estimation (the Mishkin test) of the market pricing of cashfrom operations, tax accruals, and book accruals with respect to their implications for 1-year-ahead earn-ingsa, b (n = 36,516)

Forecasting equation

EARNtþ1 ¼ a0 þ a1CFOt þ a2DTAt þ a3NDTAt þ a4DBAt þ a5NDBAt þ ttþ1 ð16Þ

Valuation equation

SARtþ1 ¼ b0 þ b1 EARNtþ1 � a0 � a�1CFOt � a�2DTAt � a�3NDTAt � a�4DBAt � a�5NDBAt

� �

þ etþ1 ð17Þ

Parameter Forecasting coefficients Valuation coefficients

Estimate Asymptotic SE Parameter Estimate Asymptotic SE Market valuation

Panel A: Market pricing of earnings components with respect to their implications for 1-year aheadearnings

a1 (CFO) 0.9518 0.0101 a�1 (CFO) 0.6565 0.0824 -0.30 = under

a2 (DTA) 0.4798 0.0187 a�2 (DTA) 1.4656 0.1570 0.99 = over

a3 (NDTA) 0.5457 0.0297 a�3 (NDTA) 2.5810 0.2558 2.04 = over

a4 (DBA) 0.4963 0.0251 a�4 (DBA) 1.1332 0.2054 0.64 = over

a5 (NDBA) 0.9481 0.0400 a�5 (NDBA) 1.4021 0.3246 0.45 = over

Null hypotheses Likelihoodratio statisticsc

Marginalsignificance level

Panel B: Test of rational pricing of earnings components

CFO, DAC,NDAC: a�1 ¼ a1

and a�2 ¼ a2 and a�3 ¼ a3


291.45 0.0000

CFO: a�1 ¼ a1 25.59 0.0000

DTA: a�2 ¼ a2 82.29 0.0000

NDTA: a�3 ¼ a3 138.54 0.0000

DBA: a�4 ¼ a4 19.04 0.0000

NDBA: a�5 ¼ a5 3.97 0.1375

DTA, NDTA: a�2 ¼ a�3 and a2 = a3 31.93 0.0000

DTA, DBA: a�2 ¼ a�4 and a2 = a4 5.75 0.0563

NDTA, DBA: a�3 ¼ a�4 and a3 = a4 43.43 0.0000

NDTA, NDBA: a�3 ¼ a�5 and a3 = a5 24.20 0.0000

a See Table 1 for variable definitionsb Equations 1 and 2 are jointly estimated using an iterative generalized nonlinear least squares estimationprocedure based on 36,516 firm-years from 1986 to 2001c The likelihood ratio statistic for the full model is [2nLn(SSRc/SSRu)] = 2 9 36,516 9 Ln(36,959/36,812) = 291.45


123

the Mishkin test, hypotheses H1 and H2 examine whether the market’s assessment of

earnings persistence for firm-years with large tax accruals (high tax conformity) is con-

sistent with the observed persistence in earnings. The primary tests build on prior research

that documents market anomalies related to accruals and market valuation (Sloan 1996;

Xie 2001; Fairfield et al. 2003; Rajgopal et al. 2003; Hanlon 2005). The accrual anomaly

(Sloan, 1996) suggests that the market does not understand that accruals are less persistent

than cash flows and extreme accruals imply less persistent earnings. Thus, high (low)

current year accruals are associated with negative (positive) future returns.

Our evidence supports hypothesis H1, which predicts that the market expectations

(measured by stock returns) fail to reflect correctly the persistence attributable to the

accrual components of earnings. Panel A, Table 5 shows that the valuation coefficients

market assigns to discretionary tax accruals (DTA), non-discretionary tax accruals

(NDTA), discretionary book accruals (DBA), and non-discretionary book accruals

(NDBA) are 1.47, 2.58, 1.13 and 1.40, respectively. These coefficients (a�i ) obtained in the

second stage for all four accrual components are higher than their corresponding fore-

casting coefficients (ai) obtained in the first stage. The evidence indicates that, for the

sample period of 1986–2001, the market overestimates the persistence of all four accrual

components (DTA, NDTA, DBA and NDBA). Consistent with prior studies (Sloan 1996;

Xie 2001; Fairfield et al. 2003; Rajgopal et al. 2003; Hanlon 2005) the market undervalues

the cash flow from operations, The coefficient on cash flow from operations, (a�i ¼ 0:66), is

lower than its counterpart in the forecasting equation (a1 = 0.95). Thus, the market does

not appear to rationally anticipate the higher (lower) persistence of earnings performance

attributable to the cash flow (accruals) components of earnings.

The Mishkin test is a statistical comparison between the market’s assessment of the per-

sistence of earnings components (a�i ) and the historical persistence of earnings components

(ai). According to estimates from the valuation equation (Panel A, Table 5), investors appear

to treat the accrual components as if they are more persistent than the forecasting equation

estimates indicate. Panel B, Table 5 reports that the likelihood ratio for the full model is

291.45, rejecting the null hypothesis that the market rationally prices jointly all five earnings

components (p value = 0.0000). Except for the NDBA, the likelihood ratio statistic rejects

the null hypothesis of rational pricing of all earnings components individually. The likelihood

ratio ranges from 25.59 to 138.54. Consistent with hypothesis H2, the tax accruals (DTA and

NDTA) show the highest overvaluation in contrast with the discretionary book accruals

(DBA and NDBA). It is interesting to note that in Panel A, Table 5, the market overvalues the

non-discretionary tax accruals (2.04) more than the discretionary tax accruals (0.99). On the

other hand, between the two book accrual components, the market overvalues the discre-

tionary book accruals (0.64) more than the non-discretionary book accruals (0.45). The

likelihood ratio statistic rejects the null hypotheses that the market overprices non- discre-

tionary tax accruals and discretionary book accruals to the same extent (a�3 ¼ a�4 and a3 = a4,

LR = 43.43). Furthermore, the likelihood ratio statistic also rejects the null hypotheses that

the market overprices non-discretionary tax accruals and non-discretionary book accruals to

the same extent (a�3 ¼ a�5 and a3 = a5, LR = 24.20). Overall, the likelihood ratio tests

indicate that the overvaluation is more severe for the non-discretionary tax accruals (NDTA)

than for the other accrual components. In addition, the likelihood ratio statistic rejects the null

hypotheses that the market overprices discretionary tax accruals (DTA) and discretionary

book accruals (DBA) to the same extent (a�2 ¼ a�4 and a2 = a4, LR = 5.75). It is possible that

the market better understands the financial consequences of the book accruals than the tax

accruals, and consequently the mispricing is higher for the tax accruals.


123

In general, the evidence in Table 5 reveals that the market’s perceived persistence of

accruals and cash flows differs significantly from actual persistence for all earnings

components. The forecasting function of the Mishkin test results indicate that discretionary

tax accruals (a2 = 0.480) and discretionary book accruals (a4 = 0.496) are the least per-

sistent, whereas cash flow (a1 = 0.952) and non-discretionary book accruals (a5 = 0.948)

are the most persistent, of the five earnings components. The results also suggest that the

market’s inability to correctly assess the persistence of accruals is more severe for tax

accruals than the book accruals providing evidence in support of hypothesis H2. Two

possibilities can explain this finding: (1) the market has more difficulty understanding the

financial consequences of some of the tax accruals and needs more time to fully com-

prehend their value implications, or (2) the limited disclosure of corporate tax information

negatively affects the market assessment of the persistence of these accruals. Finally, the

largest overvaluation of the non-discretionary tax accruals in Table 5 suggests that the

market mispricing is most severe in assessing the tax consequences of growth in sales and

changes in business cycles.

3.3 Results of the Hedge test

The results from tests of hypotheses H1 and H2 imply that abnormal stock returns can be

earned by exploiting investors’ inability to distinguish correctly between the accruals and

cash flow components of earnings. The Mishkin test (Table 5) shows that investors assign a

larger valuation coefficient to accruals relative to their forecasting coefficient. The evidence

is stronger for the tax accruals. As a result, companies with positive abnormal accruals will

be overvalued by the market. On the other hand, companies with negative abnormal accruals

will be under-valued by the market. In any case, the observed stock prices will equal those

expected in an efficient market. This suggests that a strategy exploiting this mispricing can

be implemented to generate abnormal returns. In particular, a long position in firms

reporting low levels of accruals and a short position in firms reporting high levels of accruals

should yield positive abnormal stock returns. A test of this hedging strategy provides further

support for the inferences drawn based on the Mishkin test.

Table 6 (Panels A, B, C and D) reports the average abnormal size-adjusted returns for

each accrual decile over the 16 years sample period (1986–2001), as well as the abnormal

returns to the hedge portfolio.16 Portfolio deciles are formed annually based on the ranking

of discretionary tax accruals, non-discretionary tax accruals, discretionary book accruals

and non-discretionary book accruals for Panel A, B, C and D, respectively. Taking a long

position in the lowest decile portfolio and a short position in the highest decile portfolio

forms the hedge portfolio.

Panel A, Table 6 reports the results for deciles formed based on discretionary tax

accruals. The size-adjusted abnormal returns for the most negative accrual decile (lowest)

are significantly positive in years t ? 1 (0.086, t = 5.12), t ? 2 (0.084, t = 4.21) and t ? 3

(0.099, t = 4.60). The size-adjusted abnormal returns for the most positive accrual decile

are lower than the size-adjusted abnormal returns for the lowest decile in year t ? 1

(-0.041, t = -3.58), t ? 2 (0.033, t = 2.45) and t ? 3 (0.054, t = 3.37). Consequently,

the hedge portfolio yields positive size-adjusted abnormal returns in all 3 years. The overall

abnormal return over the 3-year period is 22.2%. The largest abnormal return reported is

12.7% in year t ? 1 and 5% for t ? 2 and 4.5% for t ? 3. The significantly positive

16 Palmon et al. (2008) use a trading strategy based on the interaction of company size and accruals usingraw security returns.


123

Table 6 Time-series means (t-statistics) of annual size-adjusted abnormal returns for each portfolio in3 years after portfolio formationa

Portfolio rankingb Size adjusted returns

Year t ? 1 Year t ? 2 Year t ? 3

Panel A: Discretionary tax accrual ranking

Lowest 0.086 0.084 0.099

5.12*** 4.21*** 4.60***

2 0.064 0.091 0.081

4.75*** 6.46*** 5.34***

3 0.036 0.083 0.092

3.30*** 6.44*** 6.38***

4 0.047 0.055 0.046

4.37*** 4.57*** 3.50***

5 0.045 0.032 0.039

4.15*** 2.71*** 2.98***

6 0.053 0.049 0.033

5.04*** 4.23*** 2.65***

7 0.043 0.059 0.046

3.98*** 4.86*** 3.71***

8 0.016 0.068 0.061

1.51 NS 5.81*** 4.51***

9 0.019 0.028 0.044

1.71* 2.27** 3.23***

Highest -0.041 0.033 0.054

-3.58*** 2.45** 3.37***

Hedgec 0.127 0.050 0.045

6.25*** 2.09** 1.69*

n 35,432 24,806 20,344

Panel B: Non-discretionary tax accrual ranking

Lowest 0.089 0.089 0.064

6.31*** 6.27*** 3.87***

2 0.064 0.066 0.042

5.26*** 5.04*** 3.11***

3 0.072 0.041 0.073

6.38*** 3.53*** 5.28***

4 0.038 0.043 0.052

3.48*** 3.81*** 4.11***

5 0.037 0.064 0.061

3.44*** 5.24*** 4.66***

6 0.038 0.090 0.051

3.37*** 7.05*** 3.03***

7 0.039 0.060 0.074

3.56*** 3.92*** 5.08***

8 0.030 0.074 0.053

2.65*** 5.29*** 3.95***


123

Table 6 continued



9 0.002 0.037 0.059

0.12 NS 2.66*** 3.94***

Highest -0.039 0.017 0.063

-3.26*** 1.20 NS 3.87***

Hedgec 0.128 0.072 0.001

6.93*** 3.59*** 0.04 NS

n 35,432 24,806 20,344

Panel C: Discretionary book accrual ranking

Lowest 0.051 0.061 0.056

3.69*** 4.07*** 3.47***

2 0.055 0.080 0.084

4.23*** 5.86*** 5.33***

3 0.071 0.042 0.037

6.28*** 3.44*** 2.67***

4 0.051 0.049 0.065

4.75*** 4.02*** 5.04***

5 0.049 0.066 0.046

4.38*** 5.47*** 3.37***

6 0.021 0.033 0.048

2.02** 2.92*** 4.02***

7 0.021 0.061 0.043

1.95* 3.88*** 3.32***

8 0.018 0.064 0.041

1.65* 5.12*** 3.08***

9 0.021 0.051 0.063

1.87* 4.20*** 3.56***

Highest 0.011 0.072 0.111

0.76 NS 4.73*** 6.37***

Hedgec 0.039 -0.011 -0.055

1.96** -0.51 NS -2.33**

n 35,432 24,806 20,344

Panel D: Non-discretionary book accrual ranking

Lowest 0.040 0.038 0.076

2.89*** 2.82*** 5.00***

2 0.041 0.081 0.075

3.42*** 5.04*** 5.10***

3 0.041 0.072 0.070

3.53*** 5.49*** 5.03***

4 0.022 0.043 0.057

2.10** 3.49*** 4.37***

5 0.037 0.067 0.047

3.33*** 5.26*** 3.50***


123

abnormal returns to the hedge portfolio in years t ? 1, t ? 2 and t ? 3 are consistent with

the market overpricing the discretionary tax accruals in the portfolio formation year t.

Panel B, Table 6 reports the results for deciles formed based on non-discretionary tax

accruals. When the hedge portfolio is formed based on non-discretionary tax accruals, the

results indicate that the hedging strategy generate positive abnormal returns in year t ? 1

and t ? 2. The size-adjusted abnormal returns for the most negative accrual decile (lowest)

are significantly positive in years t ? 1 (0.089, t = 6.31), t ? 2 (0.089, t = 6.27) and

t ? 3 (0.064, t = 3.87). The size-adjusted abnormal returns for the most positive accrual

decile are lower than the size-adjusted abnormal returns for the lowest decile in year t ? 1

(-0.039, t = -3.26), t ? 2 (0.017, t = 1.20) and t ? 3 (0.063, t = 3.87). The hedge

portfolio yields positive size-adjusted abnormal returns in the first 2 years. Again, this

supports previous results. The significantly positive abnormal returns to the hedge portfolio

in year t ? 1, and year t ? 2 are consistent with the market overpricing the non-discre-

tionary tax accruals in the portfolio formation year t.

Panel C, Table 6 reports the results for deciles formed based on discretionary book

accruals. The hedge portfolio yields significant positive size-adjusted abnormal returns

(0.039, t = 1.96) only in the first year after the formation of the portfolio (year t ? 1).17

This suggests that the mispricing of the discretionary book accruals is not as severe as the

Table 6 continued



6 0.021 0.050 0.040

1.98** 4.12*** 3.10***

7 0.036 0.048 0.057

3.15*** 3.75*** 4.01***

8 0.034 0.055 0.078

2.97*** 4.33*** 4.33***

9 0.060 0.065 0.042

5.01*** 4.80*** 3.12***

Highest 0.037 0.062 0.050

2.71*** 4.40*** 2.95***

Hedgec 0.003 -0.023 0.025

0.17 NS -1.20 NS 1.10 NS

n 35,432 24,806 20,344

*, ** and *** denote significance at the 0.10, 0.05 and 0.01 level, respectively, based on a two-tailed t-testfor the time series (16 years) of annual portfolio abnormal returns. NS not significant. T-values are in italicsa See Table 1 for variable definitionsb Portfolio deciles are formed annually based on the ranking of discretionary tax accruals, non-discretionarytax accruals, discretionary book accruals and non-discretionary book accruals for Panel A, B, C and D,respectivelyc The hedge portfolio is formed by taking a long position in the lowest decile portfolio and a short positionin the highest decile Portfolio

17 Xie (2001) reports size-adjusted return of 11 percent for discretionary book accruals in year t ? 1. Thedifferences in returns between Xie and our study may be partly due to sample time periods used in twostudies. Xie’s sample covers 1971–1992 periods whereas our sample is from 1986–2001 periods.


123

mispricing of the tax accruals. Furthermore, Panel D reports the results for deciles formed

based on non-discretionary book accruals. Abnormal returns on the hedge portfolio are not

significantly different from zero in any of the 3 years after the formation of the portfolio in

year t. The evidence from panel D suggests that investors do not misprice the non-dis-

cretionary book accrual component of earnings. Overall, the results in Table 6 show that

investors in year t ? 1 earn 25.5% abnormal returns using tax accrual hedging strategy and

4.2% abnormal returns using the book accruals hedging strategy. Comparatively, Sloan

(1996) using total book accruals hedging strategy earns 10.4% return in year t ? 1 and Xie

(2001) reports abnormal returns of 13.3% in year t ? 1. Our results demonstrate that the

highest abnormal return in year t ? 1 is earned in using tax accruals hedging strategy thus

providing supporting evidence for hypothesis H3.

Table 7 Nonlinear generalized least squares estimation (the Mishkin test) of the market pricing of cashfrom operations, tax accruals, and book accruals with respect to their implications for 1-year-ahead earningsafter controlling for growth in net operating assetsa, b (n = 36,516)

Forecasting equation

EARNtþ1 ¼ a0 þ a1CFOt þ a2DTAt þ a3NDTAt þ a4DBAt þ a5NDBAt þ a6GrNOAt þ ttþ1

Valuation equation

SARtþ1 ¼ b0 þ b1ðEARNtþ1 � a0 � a�1CFOt � a�2DTAt � a�3NDTAt � a�4DBAt � a�5NDBAt

� a�6GrNOAtÞ þ etþ1

Forecasting coefficients Valuation coefficients

Parameter Estimate Asymptotic SE Parameter Estimate Asymptotic SE Market valuation

Panel A: Market pricing of earnings components with respect to their implications for 1-year aheadearnings

a1 (CFO) 0.9546 0.0100 a�1 (CFO) 0.6457 0.0839 -0.31 = under

a2 (DTA) 0.5809 0.0195 a�2(DTA) 1.2655 0.1643 0.68 = over

a3 (NDTA) 0.6633 0.0304 a�3(NDTA) 2.3629 0.2620 1.70 = over

a4 (DBA) 0.5222 0.0251 a�3 (DBA) 1.0885 0.2088 0.57 = over

a5 (NDBA) 0.8392 0.0404 a�3 (NDBA) 1.6426 0.3355 0.80 = over

a6 (GrNOA) -0.1257 0.0075 a�6 (GrNOA) 0.2690 0.0639 0.39 = over

Null hypotheses Likelihood ratio statistics Marginal significance level

Panel B: Test of rational pricing of earnings components

CFO, DAC,NDAC: a�1 ¼ a1



371.03 0.0000

CFO: a�1 ¼ a1 26.99 0.0000

DTA: a�2 ¼ a2 33.54 0.0000

NDTA: a�3 ¼ a3 88.67 0.0000

DBA: a�4 ¼ a4 15.68 0.0001

NDBA: a�5 ¼ a5 11.71 0.0006

GrNOA: a�6 ¼ a6 76.78 0.0000

a See Table 1 for variable definitionsb Equations 1 and 2 are jointly estimated using an iterative generalized nonlinear least squares estimationprocedure based on 36,516 firm-years from 1986 to 2001


123

3.4 Sensitivity tests

In order to assess the robustness of the previous conclusion that the market overvalues

accruals and that the overvaluation is more severe for tax accruals, the Mishkin test is

estimated after controlling for growth in net operating assets. Fairfield et al. (2003) point

out that accruals are a component of growth in net operating assets as well as a component

of earnings. For a growth firms, sustaining a current level of growth in net operating assets

(GrNOA) reduces profitability due to conservative accounting and diminishing returns.

Table 7 provides evidence on the mispricing of earnings components after controlling for

growth in net operating assets. As expected, the forecasting equation (Panel A) shows that

GrNOA is negatively associated with 1-year-ahead earnings. Consistent with the results

from Table 5, the valuation coefficients in Panel A, Table 7 show that the market un-

derprices the cash flow component of earnings and overprices the accrual components and

the growth in net operating assets. Furthermore, the results from Table 7 continue to

indicate that the overvaluation problem is more severe for the non-discretionary tax

accruals. However, controlling for the growth in net operating assets reduces the over-

valuation of three of the accrual components: the discretionary tax accruals, non-discre-

tionary tax accruals and discretionary book accruals. In addition, the market overvalues the

growth in net operating assets. Thus, consistent with Fairfield et al. (2003) a portion of the

overvaluation of accruals is explained by the lower persistence of earnings attributed to

growth in net operating assets. However, after controlling for GrNOA the results show that

the overpricing of the non-discretionary book accruals is higher than before (0.80 versus

0.45). In general, the evidence from Table 7 shows that the market recognizes the higher

persistence of the non-discretionary book accruals (0.839, Panel A) relative to discre-

tionary book accruals (0.522, Panel A) but continues to overvalue them, even after con-

trolling for the growth in net operating assets. The likelihood ratios in Panel B, Table 7

show that the mispricing is significant for all variables. These results show that market

expectations (measured by stock returns) fail to correctly reflect the persistence attributable

to the cash flow and accrual components of earnings. Finally, Table 7, Panel A shows that

non-discretionary tax accruals variable (NDTA) is the most overvalued variable similar to

Panel A, Table 5.

In Table 8, next period size-adjusted abnormal returns are regressed on accrual de-

ciles (ACCtdec) in order to further assess the robustness of the Mishkin and hedge tests.

Panels A, B, C and D of Table 8 report the results assuming hedge positions on

discretionary tax accruals, non-discretionary tax accruals, discretionary book accruals,

and non-discretionary book accruals, respectively. Table 8 also shows regression esti-

mates from pooled and average annual regressions. Consistent with the Mishkin and the

hedge tests, the regression results show that hedge positions on discretionary tax

accruals (Panel A), non-discretionary tax accruals (Panel B), and discretionary book

accruals (Panel C) generate abnormal stock returns. In other words, the larger the

accruals in Panels A, B, and C the lower the size-adjusted returns in the next period. In

addition, consistent with the hedge test (Panel A, Table 6), the regression results show

that hedge positions on non-discretionary book accruals (Panel D, Table 8) do not

generate abnormal returns.18

18 Regression using Eq. 10a is also estimated. Untabulated results show that the sign of the coefficients fortax and book accrual coefficients are positively and negatively significant, respectively.


123

Table 9 shows the results of calendar-time portfolio analysis using the three-factor

Fama and French (1992) model and the momentum factor (see Eq. 11).19 The data for the

four factors were obtained from French’s website.20 Our results show that the intercept

term is significant in each of the four panels indicating that abnormal returns are earned

when portfolio returns are classified by book and tax accruals. Consistent with Lam et al.

(2010), the sign of the coefficients of the Fama–French factors are positively significant for

Table 8 Summary regression statistics of the relation between abnormal stock returns and accrual decilerankingsa, b

MODEL SARtþ1 ¼ c0 þ c1ACCdect þ etþ1

Parameter Predicted Sign Pooled regression Means from annual regressions

Estimate t-statistics Estimate t-statistics

Panel A: ACCtdec = Discretionary tax accrual ranking

c0 ? 0.0052 8.21*** 0.0768 4.23***

c1 - -0.0008 -7.01*** -0.0828 -3.51***

R2 0.0013 0.0020

N 43,558 2,215

Panel B: ACCtdec = Non-discretionary tax accrual ranking

c0 ? 0.0053 9.22*** 0.0828 4.71***

c1 - -0.0008 -7.65*** -0.0924 -4.39***

R2 0.0014 0.003

N 43,558 2,215

Panel C: ACCtdec = Discretionary book accrual ranking

c0 ? 0.0034 5.75*** 0.0624 3.13***

c1 - -0.0004 -3.45*** -0.0516 -2.31**

R2 0.0003 0.001

n 43,558 2,215

Panel D: ACCtdec = Non-discretionary book accrual ranking

c0 ? 0.0017 3.12*** 0.0360 2.64***

c1 - -0.0000 -0.33 NS 0.0000 0.00 NS

R2 0.0000 0.002

n 45,356 2,215

*, ** and *** denote significance at the 0.10, 0.05 and 0.01 level, respectively, based on a one-tailed t-test.NS = not significant. Pooled t-statistics are based on clustered standard errors (Rogers 1993)a See Table 1 for variable definitionsb Accrual deciles are formed annually based on the ranking of discretionary book-tax accruals, non-discretionary book-tax accruals, discretionary book- accruals and non-discretionary book-only accruals forPanel A, B, C and D, respectivelyc The t-statistics for the average annual regressions are computed as follows: tð�ciÞ ¼ ð�ci= rc=

ffiffiffinp� �

, where n

is the number of months in the period, and ry is the standard deviation of the annual coefficients

19 The following steps are used in running Eq. 11: decile ranking for each firm-year is first obtained,followed by constructing ten portfolios for each year, and then computing equally weighted monthly averageportfolio returns for 10 portfolios for year t ? 1, finally, the risk free rate is subtracted from the portfolioreturns in order to obtain excess portfolio returns. We are thankful to the reviewer for suggesting Eq. 11 andfor the calculation of excess portfolio returns.20 http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.


123

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

the MRP variable and negatively significant for the WML variable. Furthermore, the beta

coefficient of MRP is much below 1.0 and there is little effect of market momentum on

abnormal returns in each of the portfolios. Consistently significant beta in each of the

panels supports Sharpe (1964); Lintner (1965); Black’s (1972) prediction of positive

association between excess returns and risk premium. Overall, the regression results in

Table 9 Summary regression statistics of the annual stock returns and Fama–French factorsa

MODEL ERtþ1 ¼ c0 þ c1MRPt þ c2SMBt þ c3HMLt þ c4WMLt þ etþ1

Parameter Predicted sign Estimate t-statistics

Panel A: DTAtdec = discretionary tax accrual ranking

c0 0.13357 4.26***

c1 0.02300 3.32***

c2 0.01279 1.43

c3 0.01086 1.38

c4 -0.01120 -2.26**

Adjusted R2 0.1094

N 101

Panel B: NDTAtdec = Non-discretionary tax accrual ranking

c0 0.14232 4.56***

c1 0.02220 3.16***

c2 0.01550 1.66*

c3 0.00872 1.10

c4 -0.01152 -2.26**

Adjusted R2 0.1111

N 103

Panel C: DBAtdec = discretionary book accrual ranking

c0 0.12571 4.17***

c1 0.02328 3.46***

c2 0.01411 1.61

c3 0.01121 1.46

c4 -0.01066 -2.17**

Adjusted R2 0.1140

N 103

Panel D: NDBAtdec = non-discretionary book accrual

c0 0.12955 4.10***

c1 0.02420 3.51***

c2 0.01711 1.86*

c3 0.01153 1.47

c4 -0.01070 -2.09**

Adjusted R2 0.1254

N 100

*, ** and *** denote significance at the 0.10, 0.05 and 0.01 levels, respectively, based on a two-tailed t-testa ER is the excess returns computed as annual stock returns less risk free rate and MRP is the market riskpremium in year t. SMB is the small-minus-big factor in year t. HML is the high-minus-low factor in year t.WML is the momentum factor in year t


123

Table 10 Summary regression statistics of the relation between abnormal stock returns and accrual decilerankingsa, b

MODEL : SARtþ1 ¼ c0 þ c1ACCdect þ c2LnMVdec

t þ c3BETAdect þ c4LnBMdec

t þ c5EPdect þ etþ1;

Parameter Predicted sign Pooled regressions Means from annual regressions

Estimate t-statistics Estimate t-statisticsc

Panel A: ACCtdec = Discretionary tax accrual ranking

c0 ? 0.0021 1.55* 0.0039 0.90 NS

c1 - -0.0006 -5.24*** -0.0006 -3.97***

c2 - -0.0007 -5.57*** -0.0010 -2.51***

c3 ? 0.0003 2.85*** 0.0004 0.80 NS

c4 ? 0.0009 7.25*** 0.0009 2.52***

c5 ? -0.0000 -0.36 NS 0.0000 0.09 NS

Adjusted R2 0.01 0.03

n 43,558 2,212

Panel B: ACCtdec = Non-discretionary tax accrual ranking

c0 ? 0.0029 2.05** 0.0047 1.06 NS

c1 - -0.0006 -5.30*** -0.0006 -3.62***

c2 - -0.0008 -6.03*** -0.0010 -2.61***

c3 ? 0.0004 3.02*** 0.0004 0.88 NS

c4 ? 0.0008 6.39*** 0.0008 2.21**

c5 ? -0.0001 -0.88 NS 0.0000 -0.03 NS


n 43,558 2,212

Panel C: ACCtdec = Discretionary book accrual ranking

c0 ? 0.0020 1.49* 0.0043 0.96 NS

c1 - -0.0005 -4.19*** -0.0006 -3.99***

c2 - -0.0008 -6.06*** -0.0011 -2.67***

c3 ? 0.0003 2.65*** 0.0004 0.75 NS

c4 ? 0.0010 7.80*** 0.0010 2.71***

c5 ? -0.0001 -0.95 NS 0.0000 -0.02 NS


N 43,558 2,212

Panel D: ACCtdec = Non-discretionary book accrual ranking

c0 ? 0.0006 0.47 NS 0.0024 0.64 NS

c1 - -0.0002 -1.47 NS -0.0002 -0.62***

c2 - -0.0008 -5.82*** -0.0010 -2.55***

c3 ? 0.0003 2.82*** 0.0004 0.81 NS

c4 ? 0.0010 7.77*** 0.0010 2.52***

c5 ? -0.0002 -1.57* -0.0001 -0.21 NS


n 43558 2,212

*, ** and *** denote significance at the 0.10, 0.05 and 0.01 level, respectively, based on a two-tailed t-test. NS = notsignificant. Pooled t-statistics are based on clustered standard errors (Rogers 1993)a See Table 1 for variable definitionsb Accrual deciles are formed annually based on the ranking of discretionary book-tax accruals, non-discretionary book-tax accruals, discretionary book- accruals and non-discretionary book-only accruals for Panel A, B, C and D,respectively

c The t-statistics for the average annual regressions are computed as follows: tð�ciÞ ¼ ð�ci= rc=ffiffiffinp� �

, where n is the

number of months in the period, and rc is the standard deviation of the annual coefficients


123

Table 9 demonstrates that abnormal returns are earned in each of the panels indicating that

partitioning the sample by discretionary and non-discretionary tax and book accruals earns

excess returns.

Results of sensitivity test reported in Table 10 demonstrate that the Fama and French

(1992) factors and both the Sloan (1996) and the Basu (1977) anomalies do not change the

results reported in Table 8. Our results show that size variable is negatively associated with

next period size adjusted returns supporting the previous work of Fama and French (1992)

and Banz (1981). Our results are also supportive of the earlier studies demonstrating

positive association between beta and average returns (Sharpe 1964; Lintner 1965). Similar

to Rosenberg et al. (1985) and Chan et al. (1991) our results show that next period size

adjusted returns are positively associated with book to market ratio. Further, the earnings/

price ratio is not significant in our regression runs. Finally, similar to Table 8 our results

show that the accrual variables in each of the panels are negatively associated with next

period’s size-adjusted returns.

4 Summary and conclusion

The purpose of this study is to investigate whether the decomposition of total accruals into

book and tax accruals better explain market’s pricing of accruals and cash flows. To

achieve these objectives, total accruals are decomposed into discretionary tax accruals,

non-discretionary tax accruals, discretionary book accruals, and non-discretionary book

accruals. Our findings contribute to the extant literature in several ways. First, our analysis

reveals that companies use more income-decreasing tax accruals than book accruals

thereby reducing their tax liability while enhancing their reported earnings. These findings

are consistent with the US Treasury Department claims (Department of the Treasury 1999)

that firms are increasingly engaging in various tax shelter activities. However, the use of

income-decreasing tax accruals reduce the probability of an IRS challenge by eliminating

the need to report to the IRS a book-tax difference which may flag out tax returns for IRS

scrutiny. Second, our results shed light on how taxes affect the extent to which the market

uses financial information efficiently. Overall, the results reveal that disaggregating

earnings into operating cash flow, discretionary tax accruals, discretionary book accruals,

non-discretionary tax accruals, and non-discretionary book accruals enhances the predic-

tive ability of earnings components.

A hedge portfolio for the deciles formed based on discretionary tax accruals yields

positive size-adjusted abnormal returns even 3 years after the formation of the port-

folios. Our evidence suggests that the market has greater difficulty in assessing the

economic consequences of tax accruals, particularly discretionary tax accruals, com-

pared to book accruals. GAAP give managers some flexibility in recognizing the

accrual portion of earnings, allowing managers the opportunity to increase or decrease

reported earnings as they exercise their discretion in recognizing accruals. Our evidence

suggests that investors do not fully understand the implications that current period

accruals have for future earnings, and this is largely due to the managed portion of

book accruals and due to tax accruals. Finally, our results using Fama–French and

momentum factors show that next period risk-adjusted returns increase when firms

increase tax accruals reinforcing our results based on hedged portfolio returns using tax

accruals.


123

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