Center for Financial Markets & Policy

Assessing the Quality of the Income Tax Accrual

Preeti Choudhary

McDonough School of Business

Georgetown University

pc299@georgetown.edu

Allison Koester*

McDonough School of Business

Georgetown University

apk29@georgetown.edu

Terry Shevlin

Merage School of Business

University of California - Irvine

tshevlin@uci.edu

Current Draft: August 21, 2013

First Draft: June 7, 2012

*Corresponding author.

Acknowledgements:

This paper has benefitted from comments by Bill Baber, Brad Blaylock, Katharine Drake, Alex Edwards, Andrew Finley, Michelle Hanlon (2013 FARS discussant), Susan Krische, Wayne

Nesbitt (2013 ATA discussant), tax readings groups at the University of Arizona and the

University of Texas, workshop participants at American University and George Mason

University, and conference participants at the 2012 Washington Accounting Research

Symposium, the 2013 FARS mid-year meeting, and the 2013 ATA mid-year meeting.

http://finpolicy.georgetown.edu

Assessing the Quality of the Income Tax Accrual

Abstract:

Following the framework of Dechow and Dichev (2002), we develop a measure of income tax

accrual quality based on variation in the extent to which the tax accrual maps into tax-related

cash flows. We interpret a lack of mapping as indicative of poor tax accrual quality- a concept

influenced by, but distinct from, tax avoidance and earnings management and thus, not a proxy

for these concepts. We assess the construct validity of our measure in two ways. First, we show

that poor tax accrual quality is related to proxies for (1) GAAP-induced mismapping and (2) the

presence of judgment and complexity in applying GAAP which increases estimation error in the

tax accrual. Second, we establish our measure’s predictive validity by documenting that poor tax

accrual quality is associated with future tax-related financial statement restatements and tax-

related internal control weaknesses (two third-party assessments of existing or potential

estimation error in the tax accrual). We conclude by suggesting a number of uses for and

research questions that can be addressed with our tax accrual quality measure.

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1. Introduction

Financial reporting uses accruals to adjust the recognition of cash inflows and outflows

so recognized revenues and expenses better reflect a firm’s economic performance (Dechow

1994; Dechow et al. 1998). However, “accruals are frequently based on assumptions and

estimates that, if wrong, must be corrected in future accruals and earnings” (Dechow and Dichev

2002, p.36). These errors in assumptions, errors in estimation, and the related corrections that

occur in future periods add noise to the beneficial role of accruals, such that the quality of

accruals (and therefore earnings) is decreasing in the magnitude of these errors and corrections.

Survey evidence indicates three out of four CFOs view earnings comprised of accruals that are

eventually realized as cash flows to be of high quality (Dichev et al. 2013), highlighting the

importance of the relation between accruals and cash flows. This paper seeks to develop a

measure of income tax accrual quality. Following the framework of Dechow and Dichev (2002)

(hereafter DD), we consider a tax accrual that more precisely maps into tax-related cash flows to

be of higher quality.

When tax accrual quality is high, tax expense is more likely to reflect a firm’s actual tax

liability, resulting in after-tax earnings being more reflective of a firm’s underlying economic

performance. Understanding tax accrual quality is important because income tax expense is one

of the only sources of information available to investors that provides insight into firms’ taxable

income. When there is variation in the mapping between the tax accrual and cash tax payments, a

GAAP-based ETR is unlikely to provide investors with the transparency necessary to assess

taxable income. Corporations have recently come under Congressional scrutiny for discrepancies

between their income tax provision and income taxes paid, “highlight[ing] how difficult it is to

get a fix on exactly what companies pay the Treasury” from firms’ financial statements

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(Linebaugh et al. 2013). Because investors anchor on after-tax net income (Graham et al. 2005),

an income tax expense number that does not map into a firm’s tax obligations can obfuscate a

firm’s underlying economic performance.

Focusing on a single accrual “can permit a more complete characterization of the relation

between accruals and cash flows, and can potentially result in a better understanding of the role

played by estimation error” (McNichols 2002, p. 68). We believe the income tax accrual is

particularly interesting to evaluate for at least four reasons: (1) all corporations estimate it; (2) it

is a large component of earnings; (3) it is subject to significant judgment and complexity; and (4)

it has a distinct estimation process. The final two items distinguish the tax accrual from other

accruals. Estimating the tax accrual requires technical knowledge in the application of tax rules

as well as knowledge of how financial income and taxable income articulate. Therefore, the tax

accrual is often estimated and reviewed by internal and external parties with technical knowledge

who are not involved in estimating non-tax accruals.

Following Hribar and Collins (2002), we define the tax accrual as the difference between

income tax expense (an income statement account) and income taxes paid (the account’s related

cash flow).1 Following DD, we measure income tax accrual quality (TaxAQ) as the standard

deviation of the residuals from firm-specific regressions of a firm’s income tax accrual on prior,

current, and future period income taxes paid and control variables that capture changes in long-

term deferred tax assets and liabilities.2 The measure captures the precision of the mapping of the

tax accrual into its related cash flows. A higher standard deviation of the residuals represents a

1 Two alternative approaches to defining the tax accrual include using the change in taxes payable or current tax

expense less cash taxes paid. Both of these definitions have weaknesses that include inducing measurement error,

omitting estimation error we want to retain, and sample loss. See Section 3.1 for details. 2 We are able to assess the extent to which the income tax accrual maps into its associated cash flows because U.S.

GAAP requires firms to disclose the amount of income taxes paid during the current period (ASC 230-10-50-2).

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poor mapping or lower precision, and lower precision in a signal reduces its informativeness.

The purpose of the control variables is to limit what remains in the residual to estimation error.

Our measure of tax accrual quality only includes items in the tax accrual and not

controlled for by cash taxes paid in t-1, t, or t+1 and changes in long-term deferred tax assets

(DTAs) and deferred tax liabilities (DTLs) (for details see Appendix 2, and discussed further

below). While the correct application of Generally Accepted Accounting Principles (GAAP) can

lead to differences between tax expense and cash taxes paid, these differences will not

necessarily affect our measure of tax accrual quality for several reasons. First, timing differences

between financial reporting and tax reporting lead to temporary book-tax differences. We include

changes in long-term DTAs and DTLs as additional independent variables to control for the

portion of the tax accrual not expected to map into tax-related cash flows in years t-1 through

t+1.3 In contrast, permanent book-tax differences do not affect the tax accrual (or the residual)

because tax expense and cash taxes paid are affected in the same manner. As permanent and

temporary book-tax differences are commonly used as proxies of tax avoidance, our measure is

conceptually different from (and therefore not a proxy for) tax avoidance because neither

temporary nor permanent book-tax differences are in the residual. Consistent with this claim, we

document low correlations between our measure of tax accrual quality and tax avoidance

proxies.

Beyond temporary and permanent differences, the correct application of GAAP can still

result in differences between tax expense and cash taxes paid. Examples include accounting

3 By including changes in long-term DTAs and DTLs as control variables, it is reasonable to expect that the tax

accrual will map into cash flows between periods t-1 and t+1. Empirical support is evidenced by the small increase

in adjusted R2 (0.3 percent) when we expand cash flows to t-3 through t+3. This expansion also results in a sample

loss of 55 percent because we cannot estimate TaxAQ values for four of the nine years currently included in our

sample (2002, 2003, 2009, and 2010).

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standards related to employee stock options and uncertain tax positions. Many of these

differences are eliminated from the residual by controlling for cash taxes paid in t-1 through t+1.

We refer to the differences that remain in the residual as examples of “GAAP-induced

mismapping.”

Furthermore, the presence of judgment in applying GAAP can lead to both intentional

and unintentional estimation error, which results in less precise tax accrual estimates (see

Appendix 2). While prior research finds evidence of intentional estimation error in the tax

accrual (Dhaliwal et al. 2004; Schrand and Wong 2003; Frank and Rego 2006; Cazier et al.

2012; Krull 2004), our tax accrual quality measure is not a proxy for earnings management

because it is intended to also capture unintentional estimation error. Unintentional estimation

error arises from transactions that affect the tax accrual. For example, uncertainty in applying tax

statutes to estimate the amount of taxable income, the jurisdiction and accounting period in

which this income is taxable, and the relevant tax rate that should be applied all affect the tax

accrual. A May 29, 2012 Wall Street Journal article reported that 28 percent of CFOs cite

financial reporting for income taxes as their firm’s greatest tax risk (Murphy 2012), highlighting

the challenges managers face when estimating the income tax accrual. Thus, our tax accrual

quality measure captures variation in mismapping between the tax accrual and cash taxes paid

due to GAAP-induced mismapping and judgment in applying GAAP.

We validate our tax accrual quality measure by examining its construct validity in two

ways.4 First, we identify variables that capture GAAP-induced mismapping and judgment in the

application of GAAP. We use three proxies of GAAP-induced mismapping that affect our

4 Construct validity refers to “the degree to which inferences can legitimately be made from the operationalizations

in [a] study to the theoretical constructs on which those operationalizations are based” (Trochim and Donnelly 2007,

p.56).

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measure of tax accrual quality: (1) the presence of foreign operations, (2) the presence of

employee stock options, and (3) the magnitude of uncertain tax positions. These three items can

also capture judgment and estimation present in the tax accrual. We use four firm characteristics

as proxies for items that complicate judgment in the application of GAAP which are captured by

the estimation error (Et in Appendix 2): (1) earnings volatility, (2) the presence of a tax benefit,

(3) the presence of discontinued and extraordinary items, and (4) a lack of firm resources

available to devote to the tax function. We find that tax accrual quality is lower in both the

presence of greater GAAP-induced mismapping and characteristics that complicate judgment in

the application of GAAP.

Second, we examine our measure’s predictive validity – its ability to predict what it

should theoretically be able to predict – by examining the measure’s relation with third-party

assessments of actual or potential estimation error in the income tax account. We find that low

tax accrual quality is associated with two proxies of third-party assessments of estimation error

in the income tax account, future tax-related restatements and future tax-related internal control

weaknesses. These tests are in the spirit of prior research which finds that low working capital

accruals quality is associated with restatements (Jones et al. 2008; Srinivasan et al. 2012) and

internal control weaknesses (Doyle et al. 2007a). Importantly, these relations hold after

controlling for GAAP-induced mismapping and firm characteristics that complicate judgment in

the application of GAAP. This highlights that our measure captures estimation error beyond

identifiable characteristics. Furthermore, our results are incremental to including working capital

accruals quality as an additional control variable, highlighting that our measure is also distinct

from pre-tax earnings quality. Lastly, we show that our measure is not associated with non-tax-

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related restatements and internal control weaknesses, highlighting that our measure captures

properties unique to the tax accrual.

We expect our tax accrual quality measure to be useful to researchers in a variety of

settings. For example, future research could use our measure to explore cross-sectional variation

in tax accrual quality. Variation can exist across countries due to differences in taxation systems

(e.g., worldwide vs. territorial), financial reporting regimes, tax law enforcement, or financial

reporting enforcement. Variation can also exist within a country through differences in expertise,

audit quality, governance, ownership structures, changes in financial reporting, or changes in tax

reporting. Our measure could also serve as a useful diagnostic for tax law enforcement, financial

reporting enforcement, and auditors in ex-ante identifying firms with heightened risk of a tax-

related restatement or tax-related internal control weakness. Finally, researchers could examine

the valuation implications of tax accrual quality through differences in analyst forecast accuracy,

analyst forecast precision, the post-earnings announcement drift, or the accrual anomaly.

Our paper proceeds as follows. Section 2 explains the richness of our particular research

setting and discusses related literature and Section 3 discusses our research design choices.

Section 4 presents our empirical findings, Section 5 presents our robustness tests, and Section 6

concludes.

2. Background

2.1 Why focus on the income tax accrual?

Our study answers the call of Healy and Whalen (1999) and McNichols (2002) for more

analysis of individual accruals, as the accrual generating process is better understood at an

individual account level. An ideal specific accrual for study is one that is common across

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industries, represents a large portion of earnings, and is subject to discretion (Stubben 2010). We

focus on the income tax accrual because it not only satisfies these three criteria but also has an

estimation process distinct from other accruals. We elaborate on these four criteria below.

First, in contrast to studies that focus on an industry-specific individual accrual (e.g.,

Petroni’s (1992) study on property-casualty loan-loss reserve estimates), our tax expense accrual

quality measure is widely applicable because all corporations are subject to income tax and are

required to account for income tax expense (or benefit) each period. In addition, our analysis

includes firms from the financial services (SIC 6000-6999) and utilities (SIC 4900-4999)

industries, which are often excluded in studies that examine financial reporting for income taxes

(e.g., Phillips et al. 2003; Lev and Nissim 2004; Hanlon 2005).5 Because tax accrual quality is

measured at a firm-level, our measure can be used to study all industries.

Second, the income tax account is economically meaningful. Survey evidence finds that

for firms that manage earnings, approximately 10 percent of EPS is managed (Dichev et al.

2013). In our sample, the mean (median) income tax expense is 46 (34) percent of the absolute

value of pre-tax earnings, and the mean (median) absolute value of the income tax accrual is 50

(11) percent of the absolute value of pre-tax earnings, highlighting the economic significance of

the tax accrual. In addition, income tax expense is often of a larger dollar magnitude relative to

other individual accounts examined in accruals quality studies. While Cecchini et al. (2012)

report that mean bad debt expense is 1.2 percent of sales and Cohen et al. (2011) report that

mean warranty expense is 1.4 percent of sales in their respective samples, mean income tax

expense is 6.1 percent of sales in our sample (untabulated).

5 Untabulated analyses indicate that financial and non-financial firms have similar tax accrual quality (p>0.10),

while utility firms have lower tax accrual quality relative to non-utility firms (p<0.01).

8

Third, there is a large degree of judgment and estimation inherent in the income tax

accrual. While both economic uncertainty in firm operations and financial reporting complexity

increase estimation error in all accruals (Dechow and Dichev 2002), the tax accrual has two

elements of additional complexity. First, it is challenging to apply tax rules to a firm’s specific

facts and circumstances because of the numerous legislative statutes, administrative practices,

and judicial case law in each taxable jurisdiction in which a firm operates (Hanlon and Heitzman

2010). Second, the tax accrual reflects the reconciliation of economic performance as measured

by financial reporting standards versus tax statutes, requiring managers to understand how two

sets of accounting records articulate. These additional elements of complexity suggest estimation

error in the tax expense accrual is likely to operate differently from estimation error in non-tax

accruals. Furthermore, the large amount of uncertainty within the tax accrual and the fact that it

is often estimated last in the financial statement preparation process allows managers to apply

their discretion opportunistically (Dhaliwal et al. 2004; Frank and Rego 2006; Gleason and Mills

2008; Cook et al. 2008).

Finally, the process and people involved in the tax expense accrual estimation process

differ substantially from the process and people involved in the non-tax accruals estimation

process. In practice, the tax expense accrual is often estimated or significantly reviewed by a

firm’s external tax return preparer. Even when a firm prepares its tax returns internally, the tax

department is generally separate from the department involved in estimating working capital

accruals. In contrast, working capital accruals are generally estimated and/or reviewed only by

internal personnel and the auditor during the financial statement preparation process. These

procedural differences suggest that, inferences from examining a firm’s working capital accruals

quality are unlikely to be completely informative with respect to a firm’s tax accrual quality.

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2.2 Prior research on accruals

Studies of accruals are prevalent in the accounting literature, beginning with Healy

(1985), DeAngelo (1986), and McNichols and Wilson (1988). Jones (1991) proposed the first

accruals model, which divided accruals into discretionary and non-discretionary components.

The Jones model as modified by Dechow et al. (1995) and Kothari et al. (2005) has been used in

hundreds of papers as a proxy for accruals earnings management. Dechow and Dichev (2002)

introduced an accruals quality measure that examined the extent to which current period working

capital accruals map into past, current, and future period operating cash flows, where firms with

weak mapping were considered to have low accruals quality.

We are not the first to focus on a specific account. Using alternative modeling techniques,

researchers have also considered the discretionary component of specific accounts such as the

allowance for bad debts (McNichols and Wilson 1988; Cecchini et al. 2012), loan loss reserves

of property-casualty insurers (Petroni 1992; Beaver and McNichols 1998; Nelson 2000; Petroni

et al. 2000; Beaver et al. 2003), loan loss provisions in the banking industry (Moyer 1990;

Whalen 1994; Beatty et al. 1995; Collins et al. 1995; Beaver and Engel 1996), warranty reserves

(Cohen et al. 2011), and accounts receivable (Stubben 2010). We focus on the income tax

account for the reasons noted in section 2.1.

2.3 Prior research on the properties of income tax expense

Our tax accrual quality measure is distinct from other properties of income tax expense

examined by prior research. Many studies have used GAAP-based ETRs, cash-based ETRs, and

different specifications of book-tax differences (e.g., temporary, permanent, or both) as proxies

for tax avoidance (see Section 3 of Hanlon and Heitzman (2010) for a review). Our tax accrual

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quality measure does not capture firms’ magnitude of tax avoidance (see Section 4.4). In

addition, recent research finds mixed evidence on the relation between tax avoidance volatility

and firm risk as measured by future stock returns (Guenther et al. 2012) or implied cost of equity

capital (Hutchens and Rego 2012). Our measure captures the volatility of the mapping of the tax

accrual into cash taxes paid (i.e., the volatility of estimation error), not volatility in tax

avoidance.

Finally, prior research in the tax literature finds evidence of earnings management

through various components of the tax accrual. Researchers have found evidence of earnings

management measured as (1) differences between the third and fourth quarter ETR (Dhaliwal et

al. 2004; Gleason and Mills 2008; Cook et al. 2008), (2) changes in the valuation allowance for

deferred tax assets (Schrand and Wong 2003; Frank and Rego 2006), (3) changes in the reserve

for uncertain tax positions (Gupta et al. 2011; Cazier et al. 2012), and (4) the designation of

foreign earnings as permanently reinvested (Krull 2004). As different tax sub-accounts can be

used to manage the tax accrual each period, investigating a single tax sub-account can lead to

Type I or II errors.6 An additional advantage of our measure is that it captures not only

intentional estimation error across all tax accrual sub-accounts but also unintentional estimation

error in these sub-accounts. Unintentional estimation error is important, as highlighted by

Plumlee and Yohn’s (2010) finding that 57 percent of restatements relate to internal errors rather

than intentional manipulation or standard/transaction complexity. The authors also find that tax

issues are one of the five most common reasons for restatements due to internal errors. Thus,

while our measure may be affected by tax avoidance or earnings management, it is conceptually

6 We acknowledge that our measure also suffers from Type I or II errors if managers switch between managing

earnings through tax and non-tax accounts.

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distinct from both tax avoidance and earnings management and is therefore not a proxy for either

construct.

3. Research Design and Hypotheses Development

3.1 Defining Tax Accrual Quality (TaxAQ)

Dechow and Dichev (DD, 2002) develop an empirical measure of working capital

accruals quality (AQ) by examining the extent to which working capital accruals map into past,

current, and future period cash flow from operations. DD’s theoretical basis for this research

design is motivated by the following:

“(1) accruals are temporary adjustments that delay or anticipate the recognition of

realized cash flows plus an estimation error term; (2) accruals are negatively related to

current cash flows and positively related to past and future cash flows; and (3) the error

term captures the extent to which accruals [do not] map into cash flow realizations... [so

that the error term] can be used as a measure of accrual and earnings quality” (p. 40).

We apply DD’s approach to develop our measure of tax accrual quality. Our measure is

based on the variation in the extent to which the income tax accrual in year t maps into tax-

related cash flows in years t-1, t, and t+1, which yields the following equation:7

TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + εt (1a)

We include the control variables CTP at periods t-1 through t+1 to remove items in the tax

accrual unrelated to estimation error (e.g. ESO-related transactions, changes in unrecognized tax

benefits, non-articulating items, etc.; see Appendix 2, Part 1). We predict β1 > 0, β2 < 0, and β3 >

0. Following Hribar and Collins’ (2002) definition of an accrual as the difference between an

income statement revenue/expense and its related cash in/outflow, our dependent variable is the

7 We do not use quarterly data because cash taxes paid is not required to be disclosed quarterly and therefore is not

in COMPUSTAT (Deloitte 2013).

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income tax accrual (TaxACCt), defined as the difference between total tax expense (TTEt) for

financial reporting purposes and tax-related cash outflows (CTPt).

There are two alternative approaches to calculating the tax accrual: the change in taxes

payable or current tax expense less cash taxes paid. Using the change in taxes payable has two

issues. First, this definition would exclude tax sub-accounts that contain significant judgment

and estimation (e.g., deferred taxes, the valuation allowance, tax reserves, etc.), which we want

to retain in the residual. Second, the change in taxes payable includes non-income related taxes

(e.g., property, sales, employment, etc.) which will not map into income tax-related cash flows,

inducing measurement error in the residual that is unrelated to estimation and judgment. Not

defining the tax accrual as the change in taxes payable further differentiates our measure from

working capital accruals quality.8

Alternatively, defining the tax accrual using current tax expense (CTE) instead of total

tax expense (TTE) has two issues. First, using CTE omits short-term changes in DTAs and DTLs

from the tax accrual, which can contain estimation error we want to retain in the residual (see

Appendix 2, Part 2). Second, if we used CTE we would only want to capture the part of cash

taxes paid that relates to CTE, meaning we must also adjust cash taxes paid to define the current

tax accrual properly. This adjustment requires additional data items (e.g. CTE, deferred tax

expense, and the change in total DTA/DTL), resulting in a sample loss of 52 percent of firm-year

observations (untabulated).9

8 To illustrate, the taxes payable account is equal to the following: opening balance + current tax expense = cash

taxes paid + closing balance. Rearranging terms yields the following: closing balance – opening balance = current

tax expense – cash taxes paid, or ∆tax payable = current tax accrual. Untabulated analysis reveals that the correlation

between our tax accrual measure and the change in taxes payable (COMPUSTAT TXPt – TXPt-1) is 0.31, consistent

with our measure capturing a different aspect of the tax account relative to the change in taxes payable. 9 Untabulated analysis reveals that median (mean) current tax expense is 92 (80) percent of total tax expense in our

sample. This suggests that using total tax expense to calculate the tax accrual yields similar values as would be

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Appendix 2 provides examples of transactions which affect the tax accrual, either through

their impact on income tax expense and/or cash income taxes paid. Equation A1 in Appendix 2

shows that TaxACC is comprised of a variety of items, including temporary timing differences

between financial and tax reporting, changes in the valuation allowance, changes in UTBs, non-

articulating items, ESO-related transactions, changes in the designation of foreign earnings as

permanently reinvested, statutory tax rate changes, and tax-related adjusting journal entries.

Timing differences between financial and tax reporting – commonly referred to as “temporary

book/tax differences” in the tax accounting literature – give rise to DTLs (DTAs) result in a

higher (lower) total tax expense relative to cash taxes paid in the current period, increasing

(decreasing) the tax accrual. To remove this known source of mis-mapping unrelated to

estimation error, we include the change in long-term deferred tax liabilities (∆DTL_LT) and

long-term deferred tax assets (∆DTA_LT) as control variables. Including ∆DTL_LT and

∆DTA_LT as controls ensures that the tax accrual maps into tax-related cash payments in

periods t-1 through t+1.10

This yields the following equation:

TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4∆DTL_LTt + β5∆DTA_LTt + εt (1b)

All variables are defined in detail in Appendix 1 and scaled by total assets. As ΔDTL_LT

(ΔDTA_LT) increase (decrease) the tax accrual, we predict β4 > 0 (β5 < 0).

obtained by using current tax expense to calculate the tax accrual yet allows us to capture short-term changes in

DTAs and DTLs and does not require additional data items. 10

Empirical evidence supports this notion. When we estimate Equation 1b and expand the number of years of cash

tax payments to t-3 through t+3, we find that the CTPt+2 and CTPt+3 (CTPt-2 and CTPt+3) coefficients are significantly

different from zero in a pooled OLS regression specification (p<0.10, untabulated). However, the adjusted R2 is only

0.3 percent higher than the adjusted R2 related to estimating Equation 1b (as reported in Column 1 of Panel A in

Table 3). In addition, this expansion results in a 55 percent loss of the firm-year observations in our sample. Our

TaxAQjt measure from Equation 1b requires data from t-8 through t+1. We begin our analyses post-FAS 109 in

1994, so data from 1994 through 2003 is used to generate TaxAQ estimates for 2002. Expanding the number of

years of tax payments to t-3 through t+3 requires data from t-10 through t+3, such that we lose TaxAQ estimates for

2002, 2003, 2009, and 2010. In addition, firms need 14 years of data instead of 10 years to estimate TaxAQ,

resulting in further sample loss.

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Our tax accrual quality measure (TaxAQ) is the standard deviation of the residuals (εt)

from firm-level estimates of Equation 1b. The residual captures both GAAP-induced

mismapping and estimation error that arises from judgment and complexity in estimating the tax

accrual. Examples of transactions that give rise to GAAP-induced mapping include changes in

the classification of permanently reinvested earnings (PRE),11

changes in statutory tax rates that

affect short-term DTAs and DTLs, employee stock option exercise shortfalls under SFAS

123(R), and changes in tax reserves for uncertain tax positions related to permanent book-tax

differences (see Appendix 2).

The residual also captures estimation error that arises from judgment and complexity in

applying GAAP. Errors can arise when estimating short-term DTAs and DTLs. For example,

warranty expense recognized for financial reporting in period t is not deductible for tax purposes

until paid in t+1, creating a temporary timing difference. Managers must estimate the amount and

timing of the associated short-term DTA, which affects the tax accrual. If realizations differ from

estimates, the cash payment in t+1 will be too high or low relative to the tax accrual in t,

resulting in estimation error. Additional examples and explanations are provided in Section 3 and

Appendix 2. Defining our measure as the volatility of the tax accrual (TaxACC) as opposed to

the residual (ε) would yield a noisy estimate because the measure would include volatility of

items unrelated to estimation error.

TaxAQ is measured over eight-year rolling windows similar to the DD and Francis et al.

(2004) approach to measuring working capital accruals quality. We multiply the standard

11

PRE-related transactions that affect the residual include unclassifying unremitted foreign earnings designated as

PRE prior to t and not remitting those earnings for tax purposes in t or t+1, as well as classifying unremitted

earnings earned prior to t-1 as PRE in t. See Appendix 2 Transactions 8c and 8g.

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deviation of the residuals by negative 1 so higher values of TaxAQ indicate higher tax accrual

quality.12

We do not include additional variables in Equation 1b for both empirical and

conceptual reasons. Because we estimate Equation 1b at a firm-level, including additional

variables reduces degrees of freedom, requiring additional years of data to obtain a valid estimate

of TaxAQ. Conceptually, the common application of accrual quality models uses a simplified

firm-specific equation and controls for cross-sectional differences unrelated to the researchers’

variable of interest (e.g., Francis et al. 2005).

Our additional control variables are not perfect proxies for known timing differences

expected to reverse outside of periods t-1 through t+1. While most assets and liabilities are

classified as current or non-current based on whether the assets are used up and liabilities are

satisfied during the next year, deferred tax assets (DTAs) and liabilities (DTLs) are classified as

current or non-current based on the current or non-current classification of the asset or liability to

which the DTA or DTL relates, not to the timing of when the accrual will reverse. If a DTA

(DTL) does not relate to an underlying asset (liability), the DTA (DTL) is classified according to

its expected reversal date. Because DTAs and DTLs are not classified solely on their expected

reversal dates, the inclusion of ∆DTA_LT and ∆DTL_LT removes some of the potential

estimation error we would like to retain in the residual.

Given these empirical challenges, we construct a second measure of tax accrual quality

that relies on control variables that proxy for the most common and economically significant

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DD acknowledge there is measurement error in estimating their measure of working capital accruals quality due to

using reported cash flow from operations as explanatory variables in their analysis, as a portion of operating cash

flows is unrelated to changes in working capital accruals (pp.40-41). Li et al. (2012) attempt to remove this

measurement error by calculating adjusted cash flows for sales, purchases, and other current assets and liabilities but

note this is difficult to do for tax-related cash flows. We also acknowledge that our explanatory variable (reported

cash taxes paid) also contains measurement error as a portion of cash taxes paid in t-1 through t+1 is unrelated to the

tax accrual in period t.

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components of long-term deferred tax liabilities and assets. We look to concurrent research to

determine which components are of the largest magnitude and most prevalent across firms.

Using a hand-collected sample, Raedy et al. (2011) show that the largest components of annual

deferred tax expense relate to timing differences are (1) depreciating plant, property, and

equipment, (2) amortizing intangible assets, (3) expensing employee benefits, and (4)

establishing and utilizing tax net operating losses. While proxies for the second and third largest

components are unavailable in machine-readable format, we are able to capture the first (fourth)

largest component affecting deferred tax with current period cash outflows related to capital

expenditures, or CAPX (the current period change in net operating losses, or ∆NOL).13

Modifying Equation 1a to include these two components of deferred taxes yields the

following equation:

TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4CAPXt + β5∆NOLt + εt (1c)

Our alternate tax accrual quality measure (TaxAQ2) is the standard deviation of the residuals

from firm-level estimates of Equation 1c, measured over eight-year rolling windows. As CAPX

(ΔNOLs) increase (decrease) the tax accrual, we predict β4 > 0 (β5 < 0). We again multiply the

standard deviation of the residuals by negative 1 so higher values of TaxAQ2 indicate higher tax

accrual quality. Because CAPX and ∆NOL in Equation 1c captures only a portion of deferred tax

expense that does not map into cash taxes paid in periods t-1 through t+1, it is ex-ante unclear

whether TaxAQ or TaxAQ2 will yield better estimates of tax accrual quality. In Section 4 we

present our empirical findings using both measures.

13

We would like to capture the difference between financial reporting (expenses) and tax reporting (deductions,

which generally correspond to cash payments) for these two items. However, there are no Statement of Cash Flow

variables in COMPUSTAT that capture current period expenditures on intangible assets or defined benefit plan cash

contributions.

17

3.2 Identifying Firm Characteristics Associated with our Measure of Tax Accrual Quality

We validate our tax accrual quality measure by examining its construct validity. We

identify firm characteristics that capture GAAP-induced mismapping and judgment in the

application of GAAP, both of which affect our tax accrual quality measure. GAAP-induced

mismapping arises when transactions affect the tax accrual (because of differences in total tax

expense and cash taxes paid) and are not controlled for by the model’s independent variables.

See Appendix 2 for detailed examples of GAAP-induced mismapping. We use three proxies to

capture GAAP-induced mismapping that remain in the Equation 1b residual: (1) the presence of

foreign operations, (2) the presence of employee stock options, and (3) the magnitude of

uncertain tax positions. Note that these three items also require judgment in the application of

GAAP, which can lead to estimation error in the tax accrual.

The first firm characteristic we examine that gives rise to GAAP-induced mismapping is

the presence of foreign operations. Firms with foreign operations are able to classify unremitted

foreign earnings as permanently reinvested (PRE) abroad. U.S. firms are allowed to defer

payment of U.S. taxes on foreign earnings until remittance, and Accounting Principles Board

(APB) No. 23 allows firms to not accrue income tax expense for financial reporting purposes

related to unremitted earnings. Subsequently, unclassifying earnings designated as PRE without

remittance will affect the tax accrual but none of the control variables in Equation 1b, thus

remaining in our residual (see Appendix 2, Transaction 8c). In addition, classifying unremitted

foreign earnings on which income tax was accrued prior to period t-1 as PRE in t without

remittance will also affect the tax accrual but none of the control variables in Equation 1b, thus

remaining in our residual (see Appendix 2, Transaction 8g). In addition, changes in future

statutory tax rates that require re-valuation of short-term DTLs and DTAs will also affect the tax

18

accrual but none of the control variables in Equation 1b, thus remaining in our residual (see

Appendix 2, Transaction 9b).14

While the U.S. federal statutory tax rate has been constant during

our sample period, foreign statutory tax rates have fluctuated (KPMG, 2013).15

In addition, U.S.

multinationals are required to understand the tax statutes, regulations, and administrative

practices as well as the financial reporting for income taxes for every jurisdiction in which they

operate, which adds additional judgment and complexity in estimating the tax accrual. Thus, we

expect firms with foreign operations to have worse tax accrual quality.

The second firm characteristic we examine that gives rise to GAAP-induced mismapping

is the presence of employee stock options (ESOs). While the tax accrual is affected by ESOs due

to different measurement bases for financial and tax reporting (see Appendix 2, Transactions 7a

– 7f), our control variables will remove most of the effect of ESOs from the residual. However,

ESO exercise shortfalls under SFAS 123(R) when there is no excess APIC to offset the

unrealized portion of the associated DTA will remain in the residual (see Appendix 2,

Transaction 7d). In addition, ESOs can lead to estimation error because the timing of the

financial reporting expense precedes the tax return deduction, giving rise to a DTA. Judgment is

required when estimating whether the DTA will be realized, which gives rise to uncertainty in

estimating the timing and magnitude of a valuation allowance. We expect firms with ESOs to

have worse tax accrual quality.

Our third firm characteristic that gives rise to GAAP-induced mismapping is the

magnitude of unrecognized tax benefits (UTBs). FIN 48 requires firms to accrue tax expense for

14

Re-valuations of long-term DTLs and DTAs also affect the tax accrual but are controlled for by ΔDTL_LT and

ΔDTA_LT and therefore do not affect our residual (see Appendix 2, Transaction 9a). 15

We acknowledge that U.S. state statutory tax rates have changed during our sample period. However, the

magnitude and impact of foreign tax rate changes is larger than U.S. state tax rate changes.

19

uncertain tax positions, such that the tax benefit of the position does not reduce tax expense.

Changes in the UTB related to permanent differences between financial and tax reporting

unrelated to settlements will affect the tax accrual but none of the control variables in Equation

1b, thus remaining in our residual (see Appendix 2, Transaction 5a).16

In addition, the presence

of uncertain tax positions reflects the inherent uncertainty managers face when applying tax

statutes, administrative practices, and case law to estimate their firms’ taxable income, the

jurisdiction and time period in which the income is taxable, and the applicable tax rate. All of

these uncertainties have the potential to lead to greater estimation error. We expect firms with

greater uncertain tax positions to have worse tax accrual quality.

We also identify firm characteristics that capture judgment in the application of GAAP,

which affects our tax accrual quality measure. Estimation error arises from judgment, reducing

the quality of accounting information. Accounting textbooks suggest that firm characteristics can

affect estimation error (Palepu et al. 2000). We use four firm characteristics as proxies for items

that complicate judgment in the application of GAAP (the Et in Appendix 2): (1) earnings

volatility, (2) the presence of a tax benefit, (3) the presence of discontinued and extraordinary

items, and (4) a lack of firm resources available to devote to the tax function.

The first firm characteristic we examine that can give rise to estimation error due to

judgment and complexity in applying GAAP is pre-tax earnings volatility. Following APB 28

(para 19), a firm must make its best estimate of the effective tax rate expected to be applicable

for the full fiscal year when recording tax expense. Thus, quarterly tax expense is based on the

annualized estimate of the firm’s tax obligation. In addition, most firms file their tax returns

16

While increases in the UTB related to temporary differences for current period positions and decreases due to

settlements that have been reserved for affect the tax accrual, they will not affect the residual because we control for

cash taxes paid in t (see Appendix 2, Transactions 5c and 5e).

20

subsequent to their 10-K filing, such that managers must estimate their tax obligations in

advance of their finalized tax return for the corresponding period.17

As pre-tax earnings volatility

increases, the potential for estimation error in the tax accrual increases. We expect firms with

greater pre-tax earnings volatility to have worse tax accrual quality.

The second firm characteristic we examine that can give rise to estimation error due to

judgment and complexity in applying GAAP is the presence of a tax benefit (i.e. negative tax

expense). The presence of tax benefits is expected to increase estimation error because there is

significant uncertainty regarding the timing and magnitude of future realizations of the tax

benefit. We expect firms with tax benefits to have worse tax accrual quality.

The third firm characteristic we examine that can give rise to estimation error due to

judgment and complexity in applying GAAP is the presence of discontinued operations and/or

extraordinary items. The tax effects of these transactions affect the tax accrual but not the

residual because of our control variables (see Appendix 2, Transaction 6). However, these

transactions are both atypical and complicated because their timing and amount can be difficult

to assess. We expect more estimation error related to these transactions. While other types of

items charged or credited directly to shareholders’ equity can also affect the tax accrual, but not

the residual, they are generally less frequent and of a smaller magnitude than discontinued

operations and/or extraordinary items. 18

Thus, we expect firms with discontinued operations and

extraordinary items to have worse tax accrual quality.

17

Quarterly cash tax payments are due on the 15th of the fourth, sixth, ninth, and twelfth months of a corporation’s

tax year. Thus, a firm’s first cash tax payment is remitted two weeks after quarter-end and based on an estimate of

annualized taxable income using first quarter financial results. The remaining three cash tax payments are remitted

two weeks prior to each quarter-end and based on estimated taxable income using the prior quarter’s financial

results (IRS, 2013). 18

Examples of other items charged directly to shareholders’ equity that will not affect the tax accrual because they

do not affect tax expense or cash taxes paid include unrealized gains and losses, foreign currency translations, and

21

The final firm characteristic we examine that can give rise to estimation error due to

judgment and complexity in applying GAAP is a lack of firm resources available to devote to the

tax function. Larger firms are more likely to engage in more sophisticated transactions and

operate in a greater number of taxing jurisdictions, increasing the difficulty in estimating the

income tax accrual. However, larger firms also have more resources they can devote to the tax

function and are more likely to have a dedicated tax staff (or funds to hire an external expert)

with experience in understanding how transactions differentially affect financial reporting and

tax reporting. These resources should decrease the challenges associated with estimating the

income tax accrual. Thus, we expect smaller firms to have worse tax accrual quality. In

summary, our first hypothesis is stated as follows:

H1: Firm characteristics that give rise to GAAP-induced mismapping and judgment and

estimation error in applying GAAP are associated with worse tax accrual quality.

We evaluate the relation between our tax accrual quality measures and the firm

characteristics expected to be associated with worse tax accrual quality. As we are not interested

in assessing the incremental associations among the firm characteristics, our main analysis

focuses on the univariate correlations between tax accrual quality and each firm characteristic.

However, we also examine the relation between tax accrual quality and these firm characteristics

in a multiple regression setting. Regression analysis is useful because future researchers might be

changes in accounting principal. Examples of technical items charged directly to shareholders’ equity that could

affect the tax accrual and residual include changes in contributed capital such as “certain deductible expenditures

reported as a reduction of the proceeds from issuing capital stock for financial reporting purposes; dividends paid on

unallocated shares held by an employee stock ownership plan (ESOP) that are charged to retained earnings for

financial accounting purposes; and deductible temporary differences and carryforwards that existed at the date of

certain quasi reorganizations” (Hanlon 2003; p.843). As Hanlon notes that these technical items are infrequent in

nature and small in magnitude, we do not proxy for them.

22

interested in examining additional determinants of or cross-sectional variation in tax accrual

quality. We use the following multivariate regression:

TaxAQjt (TaxAQ2jt) = αjt + αyear + αindustry + β1FOREIGNjt + β2ESO_INDUSTRYjt

+ β3UTB_ESTjt (or UTB_ACTUALjt) + β4PTBI_VOLjt + β5TAX_BENEFITjt

+ β6DISC&EXTRAjt + β7SIZE+ εjt

(2)

All data items referenced in parentheses are obtained from COMPUSTAT. FOREIGN

proxies for the presence of foreign operations (defined as an indicator equal to one if TXFO is

non-zero). ESO_INDUSTRY captures industries which are likely to issue employee stock

options (defined as an indicator equal to one for SIC codes 30-39 and 70-89).19

UTB_EST

proxies for the magnitude of uncertain tax positions and is estimated following Equation 1 in

Rego and Wilson (2012). An estimate is required because UTB data are not available until

2007.20

UTB_ACT is disclosed UTB values available beginning in 2007 (defined as

TXTUBEND/AT). PTBI_VOL captures pre-tax earnings volatility (defined as the standard

deviation of PI/AT measured from t-7 to t). TAX_BENEFIT captures the presence of a tax

benefit (defined as an indicator if TXT is less than 0). DISC&EXTRA captures the presence of

discontinued operations and/or extraordinary items (defined as an indicator equal to one if the

absolute value of XIDOC is greater than one percent of revenues (REVT)). SIZE proxies for the

magnitude of available resources (defined as the natural log of AT). We estimate Equation 2

using eight-year rolling window estimates of both TaxAQ and TaxAQ2. We calculate each firm

19

We use an industry indicator to capture firms likely to issue stock option grants because COMPUSTAT data on

grants does not begin until 2005 and does not cover all firms in our sample. We select SIC codes 30-39 and 70-89

following Lev and Nissim (2004) based on their interpretation of Table 1 in Huson et al. (2001). 20

Appendix 2 shows that only changes in tax reserves for uncertain tax positions related to permanent book-tax

differences give rise to GAAP-induced mis-mapping, while uncertain tax positions related to temporary book-tax

differences represent estimate error due to judgment and complexity in applying GAAP. The model we use to

estimate unrecognized tax benefits pertains to the total tax reserve (both permanent and temporary), so the relation

we document between TaxAQ (TaxAQ2) and UTB_EST captures both GAAP-induced mis-mapping and estimation

error.

23

characteristic at time t. For example, FOREIGN is calculated as an indicator variable in year t if

foreign tax expense (TXFO) is non-missing and not equal to zero in year t. Equation 2 is

estimated at the firm level using an OLS regression specification with industry (Fama French 48)

fixed effects. H1 predicts that β1 through β7 < 0.

3.3 Assessing the Predictive Validity of our Tax Accrual Quality Measure

We next assess the predictive validity of our measure. Predictive validity refers to an

“operationalization’s ability to predict something it should theoretically be able to predict”

(Trochim and Donnelly 2007, p.60), and we assess this type of validity by examining the relation

between tax accrual quality and future period tax-related financial restatements and future period

tax-related internal control weaknesses. Prior research finds that working capital accruals quality

is negatively associated with restatements (Jones et al. 2008; Srinivasan et al. 2012). We use tax-

related financial statement restatements as an indicator of estimation error in the tax accrual and

expect future period tax-related restatements to be associated with worse tax accrual quality.21

An internal control weakness (ICW) is “a deficiency, or a combination of deficiencies, in

internal control over financial reporting, such that [it is] reasonably possible [or probable] that a

material misstatement of the company's annual or interim financial statements will not be

prevented or detected on a timely basis” (Appendix A, Item A7 of Auditing Standard No. 5,

PCAOB 2007). Doyle et al. (2007a) find that working capital accruals quality is negatively

related to the presence of an ICW. We extend this logic to a tax setting. Prior research finds that

tax-related ICWs are one of the most prevalent account-specific ICWs (Bauer 2011) and firms

21

We do not distinguish between tax-related restatements driven by pre-tax accounting errors versus tax-related

restatements that originate in the tax account because both types of restatements capture estimation error within the

tax account.

24

with tax-related ICWs are more likely to engage in earnings management via the tax expense

account (Gleason et al. 2011). We expect firms with documented deficiencies in the processes

and procedures involved in estimating and recording tax expense to have worse tax accrual

quality because these deficiencies could increase the likelihood of estimation error. Both of these

expected relations are summarized by the following conceptual hypothesis:

H2: Third-party assessments of estimation error in the tax accrual are associated with

worse tax accrual quality.

An advantage of using external indicators like restatements or internal control

weaknesses relative to researcher-estimated proxies is that an outside source has identified an

existing or potential problem with the firm’s financial reporting (Dechow et al. 2010).

Restatements and internal control weaknesses capture both intentional and unintentional

misstatements, which correspond with our measure of tax accrual quality capturing both

intentional and unintentional estimation error in the tax accrual.

We test H2 using the following equation:

Yjt+1 = αjt + αyear + αIndustry + β1TaxAQjt (TaxAQ2jt) + β2FOREIGNjt

+ β3t ESO_INDUSTRYjt + β4UTB_EST + β5PTBI_VOLjt + β6TAX_BENEFITjt

+ β7DISC&EXTRAjt + β8SIZEjt + β9AQjt + εjt+1

(3)

The dependent variable TAX_RESTATEt+1 (TAX_ICWt+1) is an indicator variable set equal to

one if a firm discloses a tax-related restatement (internal control weakness) in year t+1, and set

equal to zero otherwise.22

We obtain these data from Audit Analytics. We include firm

22

Data on tax-related financial restatements are from Audit Analytics’ non-reliance filings database and are

available beginning in 2000. Data on tax-related internal controls over financial reporting weaknesses are from

Audit Analytics’ SOX 404 internal controls disclosures database and are available beginning in 2004. We do not

include TAX_RESERVE or TAX_RESERVE_MISS as control variables in Equation 3 because the unit of

observation is at the firm-year and tax reserve data are only available beginning in 2007. This is in contrast to our

inclusion of TAX_RESERVE in Equation 2 where the unit of observation is at the firm and TAX_RESERVE is

estimated over the years available for each firm.

25

characteristics from above and working capital accruals quality (AQ) as control variables to

demonstrate that our measure is incrementally useful in predicting third-party estimation error in

the tax account. We estimate Equation 3 using eight-year rolling window firm-specific estimates

of TaxAQ (TaxAQ2) and AQ, with firm characteristics measured in period t. All continuous

variables are winsorized at the 1st and 99th percentiles (pooled). We predict β1 < 0 and make no

directional prediction for the other coefficients.23

4. Empirical Findings

4.1 Sample Selection

Our sample selection is summarized in Table 1. We begin with the COMPUSTAT

universe of firms with annual data from 1993 through 2011. Our sample begins in 1993 to

coincide with the implementation of FAS 109 to ensure consistent financial reporting for income

taxes over the sample period. We require firm-year observations to have non-missing values for

the variables required to estimate Equations 1b and 1c (e.g., TaxACCt, CTPt-1, t, t+1, ∆DTL_LTt,

∆DTA_LTt, CAPXt, and ∆NOLt), yielding a sample of 96,471 firm-year observations.24

Our next

screen follows the DD requirement that all firms have a minimum of ten consecutive years of

data in order to obtain a minimum of eight regression residuals per firm to calculate TaxAQ and

23

It is unclear which control variables should be included in this regression, as no published paper has modeled the

determinants of tax-related restatements or tax-related internal control weaknesses. Similar to the working paper by

DeSimone et al. (2012), we include control variables found to be associated with restatements and internal control

weaknesses in our robustness tests with no change in inferences regarding our variable of interest. 24

FAS 109 permits firms to net their short-term DTAs/DTLs and long-term DTAs/DTLs and in practice many firms

net their short-term net DTA/DTL and long-term DTA/DTL. We reset missing values of COMPUTSTAT item

TXDB equal to net DTA/DTL (TXNDB) less short-term DTL (TXDBCL) less short-term DTA (TXDBCA), with

missing values of TXDBCL (TXDBCA) reset to zero when TXDBCA (TXDBCL) is not equal to missing.

26

TaxAQ2, yielding 48,789 firm-year observations.25

We then require data to estimate uncertain

tax benefits, yielding a sample of 44,511 firm year observations. Our main analysis begins in

2002 so that we have ten observations from t-9 to t+1 to estimate our first value of TaxAQ

yielding 18,079 firm year observations that correspond to 3,290 unique firms.

4.2 Descriptive Statistics

We tabulate descriptive statistics for our regression variables in Panel A of Table 2. The

mean and median book tax accrual (TaxACCt) values are positive, consistent with tax expense

(TEt) exceeding cash taxes paid (CTPt). The mean values of ∆DTA_LTt and ∆DTL_LTt are also

positive, reflecting average annual growth in firms' long-term deferred tax assets and liabilities.

The mean market capitalization (annual revenue) for our sample firms is $2.8 ($2.2) billion.

Panel B of Table 2 presents the correlations across the Equation 1b and 1c variables. We

discuss only the Spearman correlations for brevity. As predicted, TaxACCt is negatively

correlated with CTPt (ρ = ‒0.07) and positively correlated with CTPt+1 (ρ = 0.19). In contrast to

our expectations, TaxACCt is negatively correlated with CTPt-1 (ρ = ‒0.01). Dechow and Dichev

(2002) similarly find that the current period change in working capital in period t is not

positively associated with cash flows from operations in t-1 until they control for cash flows

from operations in period t (DD’s Panel B of Table 2). We find that after controlling for CTPt,

the partial correlation between TaxACCt and CTPt-1 is 0.05 and significant (p<0.01,

25

Requiring ten years of data potentially introduces survivorship bias. Our design follows the estimation approach

of Dechow and Dichev (2002). However, papers following DD have employed cross-sectional estimation

approaches with five years of residuals, requiring only seven year of data to estimate. We discuss this approach in

the Robustness Section (V).

27

untabulated).26

Consistent with our predictions, TaxACCt is positively correlated with the control

variables ∆DTL_LTt and CAPXt and negatively correlated with the control variables ∆DTA_LTt

and ∆NOLt (p<0.05).

4.3 Estimating Tax Accrual Quality (TaxAQ and TaxAQ2)

Table 3 presents the regression results from estimating TaxAQ. Panel A of Table 3

presents our pooled regression analysis using OLS with industry and year fixed effects and

standard errors clustered by firm. Column 1 presents the results from estimating Equation 1a. We

find that TaxACCt is negatively related to CTPt and positively related to CTPt-1 and CTPt+1, as

predicted, with an adjusted R2 of 14 percent. We include ∆DTL_LTt and ∆DTA_LTt as control

variables in Column 2 and find that TaxACCt is positively related to ∆DTL_LTt and negatively

related to ∆DTA_LTt, consistent with our predictions. These relations hold for the industry-level

and firm-level analyses for the average firm presented in Panels B and C of Table 3.27

The

industry specifications yield relatively higher adjusted r-squares than the firm-specific

regressions, indicating that cross-sectional estimation of tax accrual quality explored in Section 5

yields reliable estimates. When ∆DTL_LTt and ∆DTA_LTt are added to the pooled (mean firm-

level) regression the adjusted R2 increases from 14 to 25 (29 to 44) percent, consistent with these

two variables providing significant incremental explanatory power.

26

Dechow and Dichev (2002) explain the need to control for CFOt because “∆WCt is negatively correlated with

CFOt, and CFOt is positively correlated with [CFOt-1], which counteracts the expected positive relation between

∆WCt and [CFOt-1]” (p.42). 27

T-statistics in Panel B (C) in Tables 3 and 4 are determined based on the distribution of the 48 (3,290) coefficients

obtained from regressions at the industry (firm) level and ignore any cross-sectional correlation in the data,

suggesting the results should be viewed as descriptive rather than definitive.

28

Table 4 presents the regression results from estimating TaxAQ2 using Equation 1c,

which replaces the control variables ∆DTL_LTt and ∆DTA_LTt with CAPXt and ∆NOLt.

Column 2 of Panel A reveals that in a pooled specification, TaxACCt is positively related to

capital expenditures (CAPXt) and negatively related to changes net operating loss carryforwards

(∆NOLt), consistent with our predictions. Inferences at the industry level in Panel B are similar

to those in the pooled regression with respect to the CTP and CAPX coefficients. The mean

ΔNOL coefficient is not significant at conventional levels (p>0.10), possibly due to documented

issues with the COMPUSTAT NOL variable not always identifying firms with tax return loss

carryforwards (Mills et al. 2003).

The firm-specific OLS regression results in Panel C reveal the mean firm exhibits the

predicted relations between TaxACCt and all independent variables excluding CTPt-1 (although

the CTPt-1 coefficient is positive for the median firm). The inclusion of the two control variables

CAPXt and ∆NOLt increases the adjusted R2 for the mean firm from 29 (untabulated) to 32

percent, consistent with these two variables providing incremental explanatory power.28

We

estimate our remaining tests are using firm-level eight-year rolling window regressions of tax

accrual quality.

4.4 Evidence that Tax Accrual Quality is not a Proxy for Tax Avoidance

A large portion of the tax accounting literature focuses on tax avoidance. Our measure of

tax accrual quality does not directly address (and is not intended to capture) tax avoidance

because temporary and permanent book-tax differences are excluded from our measure of tax

28

For comparison, DD report mean (median) adjusted R2 coefficients for their firm-specific change in working

capital accruals quality regressions of 0.47 (0.55) in their Panel A of Table 3.

29

accrual quality (see Appendix 2). Thus, a firm that engages in tax avoidance could have high or

low tax accrual quality (and vice versa). However, Frank et al. (2009) find that tax avoidance is

associated with high discretionary pre-tax accruals, suggesting that tax avoidance combined with

poor financial reporting could lead to low tax accrual quality. To assess the extent of overlap

between tax accrual quality and tax avoidance, we estimate the correlations between our tax

accrual quality measures (TaxAQ and TaxAQ2) and four common tax avoidance proxies: three-

year measures of GAAP-based ETRs (GAAPETR3), cash-based ETRs (CASHETR3), total

book-tax differences (TOTALBTD3), and permanent book-tax differences (PERMBTD3).

Descriptive statistics for these four tax avoidance proxies are presented in Panel A of

Table 5. Note that our sample size drops from 18,079 to 11,552 firm-years because the two ETR-

based measures require positive pre-tax book income. The correlations between these proxies

and our TaxAQ/TaxAQ2 measures are presented in Panel B of Table 5. We first note that many

of the relevant correlations, while significant, are all less than 0.10 in absolute value. Spearman

correlations reveal that TaxAQ is significantly positively associated with CASHETR3 and

TaxAQ2 is significantly positively associated with both GAAPETR3 and CASHETR3 (p<0.05).

However, TaxAQ is unassociated with GAAPETR3 and both TaxAQ and TaxAQ2 are

unassociated with TOTALBTD3 and PERMBTD3 (p>0.10). Pearson correlations reveal that

while TaxAQ/TaxAQ2 are significantly correlated with all four proxies, the correlations are

small in magnitude (from -0.09 to 0.10, p<0.05). These findings provide empirical evidence that

tax accrual quality is distinct from tax avoidance.

30

4.5 Empirical Tests of the Relation between Firm Characteristics and Tax Accrual Quality

Table 6 details the results from testing the relation between our measure of tax accrual

quality and firm characteristics expected to be associated with GAAP-induced mismapping and

judgment and complexity in applying GAAP, both of which give rise to estimation error in the

tax accrual. Panel A reports descriptive statistics. Nearly half of the firm-years have foreign

operations (FOREIGN) and more than half of all firm-years operate in high stock options

granting industries (ESO_INDUSTRY). Median estimated reserves for uncertain tax positions

are equal to 1.1 percent of assets (UTB_EST) during our sample period, and median actual

values available after 2006 total 1.3 percent of assets (UTB_ACTUAL). Sixteen percent of the

firm-years report a tax benefit (TAX_BENEFIT) and six percent of firm-years report a

discontinued operations and extraordinary items value greater than one percent of total revenues

(DISC&EXTRA). The median firm-year in our sample reports total assets of $540 million

(unlogged value of SIZE), suggesting our sample is comprised of larger firms.

Panel B of Table 6 presents the Pearson and Spearman correlation coefficients, and only

Spearman correlations are discussed for brevity. TaxAQ and TaxAQ2 are highly correlated

(ρ=0.81, p<0.01), consistent with both measures capturing the same underlying construct. Both

measures are negatively correlated with the presence of foreign operations, stock option granting

industries, uncertain tax positions, pre-tax earnings volatility, tax benefits, discontinued

operations and extraordinary items, and firm resources (p<0.05), consistent with our first

hypothesis. The correlation between TaxAQ (TaxAQ2) and UTB_ACTUAL is -0.09 (-0.08) and

available for 4,841 firm-years (untabulated, p<0.05). The largest correlations relate to stock

option granting industries, pre-tax earnings volatility, tax benefits, and firm resources, with

Spearman coefficient values ranging between -0.16 and -0.47.

31

Panel C of Table 6 presents the results from regressing TaxAQ (TaxAQ2) on the firm

characteristics capturing GAAP-induced mismapping and judgment and complexity in applying

GAAP. The regression results reveal that the firm characteristics which capture foreign

operations, volatile earnings, the presence of a tax benefit, large discontinued/ extraordinary

items, and a lack of firm resources are related to low tax accrual quality (p<0.05). In Column 2

we replace UTB_EST with UTB_ACTUAL, which limits our time period to post-2006. These

regression results show that UTB_ACTUAL is negatively associated with TaxAQ2 (p<0.05),

while FOREIGN and DISC&EXTRA lose significance. Columns 3 and 4 show the results after

replacing the dependent variable TaxAQ with TaxAQ2. Column 3 reveals that all firm

characteristics are incrementally related to TaxAQ2 in the predicted direction (p<0.10), with the

exception of UTB_EST being positively related to TaxAQ2 (p<0.05).29

When UTB_EST is

replaced with UTB_ACTUAL in Column 4, UTB_ACTUAL is negative and significantly related

to TaxAQ2 (p<0.05), while FOREIGN and DISC&EXTRA become insignificant (p>0.10). In

sum, while the multivariate analyses presented in Panel C can be useful to future researchers in

applying our measure, we view the correlations in Panel B as providing evidence that our

empirical measure of tax accrual quality captures the underlying construct of estimation error in

the tax accrual.

In untabulated tests we evaluate the relation between TaxAQ/TaxAQ2 and working

capital accruals quality (AQ). The mean (median) value of AQ is -0.023 (-0.015) and larger in

magnitude than the mean (median) value of TaxAQ or TaxAQ2, consistent with working capital

29

There are two possible reasons for the positive relation between UTB_EST and TaxAQ2. First, there is a high

correlation between UTB_EST and FOREIGN (0.59; p<0.01), such that UTB_EST becomes insignificant (p>0.10) when FOREIGN is omitted from Equation 2. In addition, pre-FIN 48 it is unclear whether and at what dollar value

firms were recording reserves for uncertain tax positions. The model used to estimate UTB_EST (Rego and Wilson

2012, Equation 1) implicitly assumes the tax reserve is estimated and recorded similarly pre- and post-FIN 48.

32

accruals quality capturing estimation error in multiple accounts while tax accrual quality captures

estimation error in only the tax account. We also find that AQ is significantly correlated with

both TaxAQ and TaxAQ2 (Spearman ρ=0.37 and ρ=0.40; Pearson ρ=0.32 and ρ=0.31

respectively, p<0.05). When we re-estimate Columns 1 and 3 after adding AQ as an independent

variable, we find a positive and significant association between AQ and TaxAQ/TaxAQ2

(p<0.01). Firm characteristics continue to have an association with TaxAQ/ TaxAQ2 similar to

Panel C of Table 6 but DISC&EXTRA becomes insignificant (p>0.10). Thus, consistent with

our expectations, while there is some overlap between working capital and tax accrual quality

measures, the measures are distinct. We further illustrate this difference in our subsequent

analyses.

4.6 Empirical Tests of the Predictive Validity of our Tax Accrual Quality Measure

Our next set of tests examine the relation between tax accrual quality and two third-party

assessments of actual or potential estimation errors in the income tax account – future period tax-

related restatements and future period tax-related internal control weaknesses.30

Panel A of Table

7 reports the frequency of tax-related restatements and internal control weaknesses by TaxAQ

quartile. We find that tax-related restatements are nearly twice as likely for firm-years in the

lowest TaxAQ quartile (0.7 versus 1.3 percent) and tax-related internal control weaknesses are

nearly four times as likely for firm-years in the lowest TaxAQ quartile (1.1 versus 4.2 percent).

Inferences are similar in Panel B when using TaxAQ2.

30

Ideally, we would like to use unrestated data in our empirical tests. However, many of our variables of interest are

unavailable in the Compustat Unrestated U.S. Quarterly Data dataset. A tax-related restatement is expected to yield

a revised tax expense value but not a revised cash taxes paid value. As our tax accrual quality measures capture the

mapping of tax expense into cash taxes paid, we believe we will still be able to detect lower tax accrual quality in

restatement firms using restated data for our empirical tests.

33

Our regression analyses related to H2 are presented in Panel C of Table 7. We regress the

presence of a tax-related restatement (internal control weakness) in period t+1 on

TaxAQ/TaxAQ2. We control for the firm characteristics found to be associated with tax accrual

quality in Panel B of Table 6 and working capital accruals quality because we want to assess the

predictive ability of tax accrual quality above and beyond proxies for estimation error in the tax

accrual (i.e., firm characteristics) and pre-tax earnings quality (i.e., working capital accruals

quality). The probit regression results presented in Columns 1 and 2 indicate that firms with

lower tax accrual quality are more likely to report a tax-related restatement in period t+1

(p<0.05), and that this relation is incremental to the inclusion of the firm characteristics which

are associated with tax accrual estimation error. This result highlights that our tax accrual quality

measure is incrementally useful in identifying documented estimation error in the tax account.

While prior research finds that lower working capital accruals quality is associated with

restatements (Jones et al. 2008; Srinivasan et al. 2012), we find that AQ is unrelated to tax-

related financial restatements (p>0.10). This result is consistent with our measure of tax accrual

quality being distinct from working capital accrual quality in its ability to identify documented

estimation error in the income tax account. In sum, these findings show that neither firm

characteristics nor working capital accruals quality are substitutes for our measure of tax accrual

quality as a determinant of tax-related restatements.

As the magnitude of probit regression coefficients are not directly interpretable, we

assess economic significance by considering the marginal effect of a change in TaxAQ

(TaxAQ2) on the probability of a future tax-related restatement. Holding all control variables at

their mean values, moving from the first to third TaxAQ (TaxAQ2) quartile is associated with a

158 (77) basis point decline in the probability of a tax-related restatement at t+1 (untabulated). In

34

untabulated robustness tests we include general determinants of restatements as additional

control variables and note that the TaxAQ and TaxAQ2 coefficients remain negative and

significant (p<0.01 and p<0.10, respectively).31

In Columns 3 and 4 we repeat this analysis with TAX_ICWt+1 as the dependent variable.

We find that firms with lower tax accrual quality are more likely to report a tax-related internal

control weaknesses in period t+1 (p<0.05). This relation is incremental to the firm characteristics

found to be associated with tax accrual quality in Table 6 and working capital accruals quality.

These findings again highlight that our measure of tax accrual quality is distinct from both firm

characteristics related to tax accrual quality and working capital accruals quality in its ability to

assess the potential for estimation error in the income tax account.

We again turn to marginal effects to assess economic significance. Holding all control

variables at their mean values, moving from the first to third TaxAQ (TaxAQ2) quartile is

associated with a 458 (204) basis point decline in the probability of a tax-related internal control

weakness in t+1 (untabulated). In untabulated robustness tests we include general determinants

of internal control weaknesses as additional control variables and note that the TaxAQ and

TaxAQ2 coefficients remain negative and significant (p<0.01 and p<0.10, respectively).32

As a discriminant validity (i.e., falsification) test, we estimate Equation 3 using the

presence of a non-tax-related restatement (internal control weakness) in t+1 as an alternate

dependent variable. We expect our measure to not be associated with future period restatements

31 These control variables include profitability, Big6 auditor, institutional ownership, the presence of a

merger/acquisition or restructuring, finance and equity raised, market-to-book ratio, and interest coverage ratio

(Burns and Kedia 2006; Efendi et al. 2007; Bryant-Kutcher et al. forthcoming). 32 These control variables include profitability, number of business segments, Big6 auditor, institutional ownership,

the presence of a merger/acquisition or restructuring, sales growth, inventory levels, Z-score, auditor resignation,

past restatements, and operating in a litigious industry (Ge and McVay 2005; Doyle et al. 2007b; Ashbaugh et al.

2009).

35

(internal control weaknesses) unrelated to the tax account, and we find evidence consistent with

this prediction (i.e., TaxAQ and TaxAQ2 coefficients are not significant at conventional levels

(p>0.10), untabulated). In sum, the regression results presented in Panel C of Table 7 confirm

that our tax accrual quality measure demonstrates predictive ability through its association with

future tax-related restatements and future tax-related internal control weaknesses. Our findings

also highlight that neither firm characteristics nor working capital accruals quality are substitutes

for a measure of tax accrual quality in identifying actual and potential estimation error in the

income tax account.

5. Robustness Tests

Following Francis et al. (2005), we estimate our tax accrual quality measure using cross-

sectional industry-year regressions and require a minimum of 20 firms per industry-year.

Industries are defined following the Fama-French 48 industry classification. We estimate TaxAQ

(TaxAQ2) following Equation 1b (1c) as the standard deviation of a firm’s residual over the five

year period from t-4 to t. Cross-sectional estimation reduces survivorship bias by requiring only

seven years (instead of ten years) of firm data to estimate the tax accrual quality measure. The

Spearman correlation between the firm-specific and cross-sectional estimates of TaxAQ

(TaxAQ2) is 0.59 (0.61) (p<0.01, untabulated). In addition, re-estimating Tables 6 and 7 using

cross-sectional estimates of TaxAQ (TaxAQ2) yield results of similar sign and significance to

those reported. We conclude that cross-sectional estimation of our measure yields qualitatively

similar values such that future researchers may find a cross-sectional approach useful depending

on their research setting.

36

6. Conclusion

We develop a measure of tax accrual quality which captures the precision with which the

income tax accrual maps into past, current, and future income taxes paid, after controlling for

known timing differences. While accruals aid in timing the recognition of revenues and expenses

to better reflect a firm’s economic performance relative to cash inflows and outflows, “accruals

are frequently based on assumptions and estimates that, if wrong, must be corrected in future

[period] accruals and earnings” (Dechow and Dichev 2002, p. 36). Errors in assumptions and

estimates in the tax account manifest as poor mapping of the income tax accrual into income

taxes paid, resulting in lower tax accrual quality.

We validate our tax accrual quality measure by examining the measure’s construct

validity. We first identify firm characteristics that capture GAAP-induced mismapping and

judgment and complexity in the application of GAAP, both of which affect our measure of tax

accrual quality. Consistent with our predictions, we find that tax accrual quality is worse when

firms have foreign operations, employee stock options, greater uncertain tax positions, greater

pre-tax earnings volatility, the presence of tax benefits, the presence of discontinued operations

and extraordinary items, and a lack of firm resources available to devote to the tax function.

These tests validate that our measure of tax accrual quality capture what we purport it to capture.

We establish predictive validity and the usefulness of our measure by documenting that

future tax-related restatements and future tax-related internal control weaknesses (two third-party

assessments of the existence of or potential for estimation error in the tax account) are also

associated with worse tax accrual quality. Our measure is useful over and above firm

characteristics and working capital accruals quality, suggesting neither are substitutes for our

37

measure of tax accrual quality. This construct validity test aids in our understanding of the

economic consequences associated with poor mapping of the tax accrual into cash taxes paid.

We expect our tax accrual quality measure to be useful to researchers in a variety of

settings, such as cross-sectional and time-series variation in tax accrual quality both across and

within countries. Our measure could also serve as a useful diagnostic for auditors and/or the SEC

in ex-ante identifying firms with heightened risk of a tax-related restatement or internal control

weakness. Finally, we expect investors to be interested in firms’ tax accrual quality because poor

mapping is unlikely to provide investors with the transparency necessary to assess firms’

economic performance.

38

Appendix 1: Variable Definitions

Variable Definition

Tax Accrual Quality Variables

TTE Total tax expense (TXTt), scaled by total assets (ATt)

CTP Cash taxes paid related to income taxes (TXPDt), scaled by total assets

(ATt)

TaxACC Total tax accrual, defined as tax expense (TXTt) - cash taxes paid

(TXPDt), scaled by total assets (ATt)

∆DTA_LT

Change in the long-term portion of the deferred tax asset (TXDBAt -

TXDBAt-1), scaled by total assets (ATt). Because FAS 109 permits firms

to net their short-term DTAs/DTLs and long-term DTAs/DTLs and in

practice many firms net their short-term net DTA/DTL and long-term

DTA/DTL, we reset missing values of TXDB equal to net DTA/DTL

(TXNDB) less short-term DTL (TXDBCL) less short-term DTA

(TXDBCA), with missing values of TXDBCL (TXDBCA) reset to zero

when TXDBCA (TXDBCL) is not equal to missing. If TXDBAt is

missing and TXDBt is not missing, TXDBAt is reset to zero (N= 22,086).

∆DTL_LT

Change in the long-term portion of the deferred tax liability (TXDBt -

TXDBt-1), scaled by total assets (ATt). Because FAS 109 permits firms to

net their short-term DTAs/DTLs and long-term DTAs/DTLs and in

practice many firms net their short-term net DTA/DTL and long-term

DTA/DTL, we reset missing values of TXDB equal to net DTA/DTL

(TXNDB) less short-term DTL (TXDBCL) less short-term DTA

(TXDBCA), with missing values of TXDBCL (TXDBCA) reset to zero

when TXDBCA (TXDBCL) is not equal to missing. If TXDBt is missing

and TXDBAt is not missing, TXDBt is reset to zero (N= 659).

CAPX Capital expenditures from the statement of cash flows (CAPXt), scaled by

total assets (ATt)

∆NOL

Change in the net operating loss for tax purposes (TLCFt - TLCFt-1),

scaled by total assets (ATt). If TLCFt is missing, ∆NOLt is reset to zero

(N= 15,575).

TaxAQ

Standard deviation of the residuals from firm-specific estimates of

Equation 1b (TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 +

β4∆DTL_LTt + β5∆DTA_LTt + εt), multiplied by -1 so larger values

indicate better tax accrual quality. A minimum of eight residuals per firm

is required to estimate TaxAQ.

TaxAQ2

Standard deviation of the residuals from firm-specific estimates of

Equation 1c (TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4CAPXt +

β5∆NOLt + εt), multiplied by -1 so larger values indicate better tax accrual

quality. A minimum of eight residuals per firm is required to estimate

TaxAQ2.

39

Variable Definition

Tax Avoidance Proxies

GAAPETR3

3-year GAAP-based effective tax rate, defined as total tax expense (TXTt)

summed over periods t-2 through t, divided by pre-tax book income (PIt)

summed over periods t-2 through t

CASHETR3

3-year cash-based effective tax rate, defined as cash taxes paid (TXPDt)

summed over periods t-2 through t, divided by pre-tax book income (PIt)

less special items (SPIt) summed over periods t-2 through t

TOTALBTD3

3-year total book-tax difference, defined as pre-tax book income (PIt)

summed over periods t-2 through t less estimated taxable income summed

over periods t-2 through t, scaled by lagged total assets (ATt-1). Estimated

taxable income is calculated by grossing up current tax expense ((TXFED

+ TXFO) ÷ U.S. statutory tax rate) and subtracting the change in net

operating loss carryforwards (TLCFt – TLCFt-1)

PERMBTD3

3-year permanent book-tax difference, defined as pre-tax book income

(PIt) summed over periods t-2 through t less estimated taxable income

prior to applying the change in net operating loss ((TXFED + TXFO) ÷

U.S. statutory tax rate) summed over periods t-2 through t less grossed-up

deferred tax expense (TXDI ÷ U.S. statutory tax rate) summed over

periods t-2 through t, scaled by lagged total assets (ATt-1)

Firm Characteristics related to Tax Accrual Quality

FOREIGN Indicator variable set equal to one when a firm reports non-zero foreign

tax expense (TXFOt), and set equal to zero otherwise

ESO_INDUSTRY

Indicator variable set equal to one if a firm operates in an industry with

potentially large tax benefits from the exercise of options (defined as

industry SIC codes 30-39 and 70-89), and set equal to zero otherwise

UTB_EST Predicted value of unrecognized tax benefits, estimated from Equation 1

in Rego and Wilson (2012)

UTB_ACTUAL Unrecognized tax benefits (TXTUBENDt) scaled by total assets (ATt) for

which data are available (2007 – 2010)

PTBI_VOL Standard deviation of pre-tax book income (PTBIt) scaled by total assets

(ATt), measured from years t-7 through t

TAX_BENEFIT Indicator variable set equal to one when total tax expense (TXT) is less

than zero, and set equal to zero otherwise

DISC&EXTRA

Indicator variable set equal to one when a firm reports a large

discretionary/extraordinary item (defined as discontinued and

extraordinary items from the Statement of Cash Flows (XIDOCt) > one

percent of revenue (REVTt)), and set equal to zero otherwise

SIZE Natural log of total assets (ATt)

40

Variable Definition

Predictive Validity Variables

TAX_RESTATEt+1

Indicator variable set equal to one if a firm has a tax-related restatement

(RES_ACC_RES_FKEY_LIST = '|18|' which relates to ‘tax expense/

benefit/deferral/other (FAS109) issues,’ from the Audit Analytics’ Non-

Reliance Restatements database) in year t+1 in our sample period for

which data are available (2000 – 2010), and set equal to zero otherwise

TAX_ICWt+1

Indicator variable set equal to one if a firm reports a tax-related internal

control weakness (IC_IS_EFFECTIVEt = 'N' and

NOTEFF_ACC_REAS_KEYSt = ‘41’from Audit Analytics’ SOX 404

Internal Controls database) in year t+1 in our sample period for which

data are available (2004 – 2010), and set equal to zero otherwise

Other Variables

AQ

Standard deviation of the residuals from firm-specific estimates of ∆WCt

= α + β1CFOt-1 + β2CFOt + β3CFOt+1 + β4∆REVt + β5PPEt + εt, multiplied

by -1 so larger values indicate better working capital accruals quality.

Following Francis et al. (2005), ∆WCt is the change in working capital

accruals (Δ current assets (ACTt - ACTt-1) – Δ current liabilities (LCTt -

LCTt-1) – Δ cash (CHEt - CHEt-1) + Δ current portion of long-term debt

(DLCt - DLCt-1). CFOt is cash flows from operations (OANCFt), ∆REVt is

– Δ revenue (REVTt – REVTt-1), and PPEt is gross plant, property, and

equipment (PPEGTt). All variables are scaled by average total assets ((ATt

+ ATt-1) ÷ 2). A minimum of eight residuals per firm is required to

estimate AQ.

TA Total assets (ATt)

REV Total revenue (REVTt)

MVE Market value of equity, defined as common shares outstanding (CSHOt) *

end of fiscal year stock price per share (PRCC_Ft)

All variable source names in parentheses refer to COMPUSTAT unless otherwise stated.

41

Appendix 2: What is in the Residual Estimated in Equation (1b)33

The purpose of this Appendix is to provide examples of common complex transactions that affect financial and tax reporting, our

measure of the tax accrual, and whether they will affect the residual term (and thus our TaxAQ measure). These examples are not

meant to be exhaustive of all complex financial reporting issues related to taxes, but rather to be representative of some more common

transactions that receive differential treatment for financial reporting relative to tax reporting. The Appendix is intended for readers

who want to thoroughly understand what our TaxAQ captures. For readers comfortable with concluding that our tax accrual model

captures the mismapping of the tax expense accrual into the tax-related cash flows in t-1, t, and t+1 after controlling for accruals in the

tax expense that are long-term deferrals due to estimation error, the appendix can be skimmed.

The Appendix is divided into two parts. Part I explains how we calculate the tax accrual (TaxACC), the dependent variable in

Equation (1b and 1c). Equation (A1) shows that TaxACC is comprised of temporary book-tax differences, changes in the valuation

allowance, changes in UTBs, non-articulating items, ESO-related transactions, changes in the designation of foreign earnings as

permanently reinvested, statutory tax rate changes, and tax-related adjusting journal entries. Part I also explains how we determine

which components of TaxACC are not in the Equation (1b) residual due to the inclusion of the five control variables CTPt-1, CTPt,

CTPt+1, ΔDTL_LTt, and ΔDTA_LTt. This analysis demonstrates that the residual on which TaxAQ is comprised primarily of

estimation error (Et) related to items in TaxACCt and GAAP-induced mismapping related to changes in permanent UTBs unrelated to

settlements, ESO shortfalls post-123R, some changes in the classification of PRE, and statutory tax rate changes related to short-term

DTA/DTLs. Part II illustrates common transactions that affect tax expense and/or cash taxes paid and whether these transactions affect

the Equation (1b) residual (assuming no estimation error). Note that Part II is not intended to be comprehensive of all transactions.

Part I: What is in the Tax Accrual (TaxACCt) and the Residual (εt): Variable definitions include references to transactions listed in Part II. Part II explains how commonly transactions affect total tax expense and cash taxes paid in

t-1, t, and t+1.

Part I, Section 1: Variable Definitions

TTEt: Total Tax Expense

CTPt: Cash Taxes Paid

TaxACCt: Income Tax Accrual = TTEt – CTPt

33

We thank Andrew Finley (former tax manager at KPMG, LLP) and Katharine Drake (former senior manager at CBIZ/MHM, LLC) for their insightful

comments and review of this appendix. Any errors that remain are our own.

42

PTBIt: Pre-tax Book Income

STR: Statutory Tax Rate

PermBTDst: Permanent Book-Tax Differences are revenues/expenses that appear in one set of books (financial or tax) but not the other in period t.

Examples include municipal bond interest income/expense, qualifying incentive stock options, 50% of meals and entertainment expenditures, and the

domestic qualified production activities deduction (Section 199). [Transaction 1]

TaxCreditst: Tax Credits which reduce a firm’s tax liability dollar for dollar (as opposed to tax deductions, which only reduce a firm’s tax liability by the

STR multiplied by the deduction amount).

TempBTDst: Temporary Book-tax Differences occur due to timing differences in when revenues or expenses are recognized for financial or tax purposes,

tax effected by the STR. They are comprised of long-term and short-term change in deferred tax liability/asset (ΔDTL/ΔDTAs) established or reversed in

period t. Examples include accelerated depreciation for tax purposes, deferred compensation which is earned in one period and paid in another period,

warranty expenses accrued and deducted in different periods, net operating loss carryforwards, etc. [Transactions 2a-2j]

NOLtCarryback: NOL generated in t and carried back to a prior period tax return, tax effected by the STR. [Transaction 3]

ΔValAllowt: Change in the valuation allowance related to DTAs recorded in t. A valuation allowance is a contra-asset account which offsets deferred tax

assets (DTA) not expected to be realized due to management expectations of insufficient future taxable income required to use the DTA. [Transaction 4]

ΔUTBt, perm: Increases in the tax reserve (uncertain tax benefits, or UTBst) related to a permanent book-tax difference related to a transaction originating in

the current year and increases (decreases) in the tax reserve related to a permanent book-tax difference related to a transaction originating in a prior year.

UTBs represent financial reporting reserves for tax positions that the firm has taken where there is uncertainty about the ultimate tax treatment of the

transaction. Evaluations of uncertain tax positions are required under SFAS 5 with revised recognition and measurement standards as well as separate

disclosure of UTBs required by FIN 48. [Transaction 5a]

Increase in UTBt, temp for CY Positions: Increases in the tax reserve related to temporary book-tax differences due to a transaction occurring in t. UTBs

represent financial reporting reserves for tax positions that the firm has taken where there is uncertainty about the ultimate tax treatment of the transaction.

Evaluations of uncertain tax positions are required under SFAS 5 with revised recognition and measurement standards as well as separate disclosure of

UTBs required by FIN 48. This is an example of Transactions 2c or 2d. [Transaction 5b]

ΔUTBt, temp for PY Positions: Increases in the tax reserve related to a temporary book-tax difference due to new uncertainties related to a transaction

originating prior to t; decrease in the UTB related to a temporary book-tax difference due to the favorable resolution of uncertainties (i.e., a position is no

longer uncertain or a statute of limitation has expired) related to a transaction originating prior to t. UTBs represent financial reporting reserves for tax

positions that the firm has taken where there is uncertainty about the ultimate tax treatment of the transaction. Evaluations of uncertain tax positions are

required under SFAS 5 with revised recognition and measurement standards as well as separate disclosure of UTBs required by FIN 48. [Transaction 5c]

Decrease in UTBt where Settlement = Amount Reserved for as a UTB: The decrease of a previously recorded tax reserves in t as a result of a settlement

of that tax position in t with the taxing authorities. UTBs represent financial reporting reserves for tax positions that the firm has taken where there is

uncertainty about the ultimate tax treatment of the transaction. Evaluations of uncertain tax positions are required under SFAS 5 with revised recognition and

measurement standards as well as separate disclosure of UTBs required by FIN 48. [Transaction 5d]

Decrease in UTBt where Settlement > Amount Reserved for as a UTB: When a firm is “under-reserved” (i.e., the settlement amount is greater than the

amount of uncertain tax position the firm originally reserved for). Firms are less likely to be under-reserved than over-reserved because FIN 48 does not

allow firms to consider expected probabilities of position outcomes. UTBs represent financial reporting reserves for tax positions that the firm has taken

where there is uncertainty about the ultimate tax treatment of the transaction. Evaluations of uncertain tax positions are required under SFAS 5 with revised

recognition and measurement standards as well as separate disclosure of UTBs required by FIN 48. [Transaction 5e, incremental to 5d]

43

Decrease in UTBt where Settlement < Amount Reserved for as a UTB: When a firm is “over-reserved” (i.e., the settlement amount is less than the

amount of uncertain tax position the firm originally reserved for). Firms are more likely to be over-reserved than under-reserved because FIN 48 does not

allow firms to consider expected probabilities of position outcomes. UTBs represent financial reporting reserves for tax positions that the firm has taken

where there is uncertainty about the ultimate tax treatment of the transaction. Evaluations of uncertain tax positions are required under SFAS 5 with revised

recognition and measurement standards as well as separate disclosure of UTBs required by FIN 48. [Transaction 5f, incremental to 5d]

Non-articulating Itemst: Include discontinued operations, extraordinary items, and items charged directly to owners’ equity that do not appear on the

income statement (FAS 109 Paragraphs 35-36) but do appear in comprehensive income and have tax affects that are deductible in t. [Transaction 6]

ESO Exercisepre-123(R): Tax return deduction on exercise date equal to non-qualified employee stock options (ESOs) intrinsic value when there is no fair

value recognition for financial reporting pre-SFAS 123(R). [Transaction 7a; also an example of Transaction 6 (a non-articulating item)]

ESO Exercise Windfallpost-123(R): Occurs post-FAS 123(R) when the fair value financial reporting expense of the non-qualified ESO is less than the intrinsic

value tax return deduction of the ESO (i.e., windfall). [Transaction 7c]

ESO Exercise Shortfallpost-123(R): Occurs post-FAS 123(R) when the fair value financial reporting expense of the non-qualified ESO exceeds the intrinsic

value tax return deduction of the ESO (i.e., shortfall) and a firm does not have prior excess APIC to offset the valuation differences. [Transaction 7d]

Classifying Earningst as PRE: Classifying earnings earned in t as permanently reinvested abroad. This classification designates that the earnings will not

be repatriated, and thus are not subject to US taxes. [Transaction 8a]

Un-classifying Earnings Designated as PRE prior to t and Remitting in t: Changing the classification of earnings earned prior to t from PRE such that

they can and are repatriated to US Parent in period t, and thus taxable in the US. [Transaction 8b]

Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1: Changing the classification of earnings earned prior to t from PRE

such that they can be repatriated, but are not taxable in the US until repatriation occurs. [Transaction 8c]

Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1: Changing the classification of earnings earned prior to t from PRE such that

they can and are repatriated to US Parent and taxable in the US in period t+1. [Transaction 8d]

Not Classifying Earningst as PRE and not Remitting in t: Tax expense related to foreign earnings that are not designated as PRE and not remitted to the

US parent, thus not taxable in the US in period t. [Transaction 8e]

Classifying Unremitted Earningst-1 as PRE in t: Reversal of tax expense accrued in t-1 on foreign earnings earned in t-1 due to these earnings being

designated as PRE in period t. [Transaction 8f]

Classifying Unremitted Earningst-2 as PRE in t: Reversal of tax expense accrued in any period prior to t-1 (for simplicity we refer to this as t-2) on foreign

earnings earned in any period prior to t-1 due to these earnings being designated as PRE in period t. [Transaction 8g]

ΔSTRt+1 affecting DTL_LT and DTA_LT: Change in a statutory tax rate (STR) effective for periods t+1 and beyond that require a revaluation of existing

long-term temporary book-tax differences (i.e., DTLs and DTAs) expected to reverse when the new statutory tax rate is effective. Changes in tax rates can

apply to foreign, US federal, or state jurisdictions.[Transaction 9a]

ΔSTRt+1 affecting DTL_ST and DTA_ST: Change in a statutory tax rate (STR) effective for periods t+1 and beyond that require a revaluation of existing

short-term temporary book-tax differences (i.e., DTLs and DTAs) expected to reverse when the new statutory tax rate is effective. Changes in tax rates can

apply to foreign, US federal, or state jurisdictions. [Transaction 9b]

Tax True-Upt,perm: Adjustments to estimated tax expense for financial reporting and cash taxes paid for tax reporting when estimation related to a

permanent book-tax difference for period t-1 differed from realizations on the tax return for period t-1. These adjustments are typically made in period t after

filing Form 10-Kt-1. [Transaction 10a]

44

Tax True-Upt,temp: Reclassification between estimated current and deferred tax expense for financial reporting and adjustment to cash taxes paid for tax

reporting when estimation related to a temporary book-tax difference for period t-1 differed from realizations on the tax return for period t-1. These

adjustments are typically made in period t after filing Form 10-Kt-1. [Transaction 10b]

Tax AJEt: Tax-related adjusting journal entry (AJE) related to t and paid in t+1. A firm realizes in t+1 prior to filing its financial statements for t that its

estimate of tax expense is too high or too low, so the firm records an AJE that is reflected in period t financial statements. However, the cash payment related

to this adjustment is made in t+1. [Transaction 11]

Et: Estimation Errort occurs when expectations reflected in the financial statements differ from tax return realizations, such that an item in the tax accrual

(TaxACC) is not completely controlled for by CTPt-1, CTPt, CTPt+1, ΔDTL_LTt, or ΔDTA_LTt due to estimation error. In other words, items in both TTE

and CTP cancel completely only if the estimated amount in TTE is equal to the cash paid in t-1, t, or t+1 or the change in DTL_LT and DTA_LT. Value

differences will be captured by Et. An example of estimation error in a short-term DTA using warranties is illustrated below:

Book income in t is $1,000. $100 of warranty expense is not deductible for tax purposes until paid, so taxable income in t is $1,100. The $100

related to the warranty is expected to occur in t+1. Assume a statutory tax rate of 35 percent.

Period t Period t+1: No error situation: $100 paid in t+1

DR Tax Expense 350 DR Taxes Payable (or CTP) 35

DR DTA-ST 35 CR DTA-ST 35

CR Taxes Payable (or CTP) 385

Period t+1: Error situation: $90 paid in t+1 and $10 paid in t+2

(e.g., warranty deduction less than expected in t+1)^

DR Taxes Payable (or CTP) 31.5

CR DTA-ST 31.5

^Note that 3.5 of DTA-ST remains outstanding at the end of t+1.

Part I, Section 2: What is in the tax accrual (TaxACC)

Many researchers think of total tax expense reported on a firm’s income statement as the product of pre-tax book income adjusted for permanent differences and

a statutory tax rate [(PTBIt – PermBTDt) * STR].34

However, this is a simplification of a more complicated process. Practical application of estimating tax

expense reported on financial statements requires additional adjustments estimated by tax professionals. We provide a more detailed description of more common

adjustments that are made to estimate tax expense properly. These adjustments are not meant to be completely exhaustive, rather representative of transactions

that have different financial and tax treatments. Example transactions in Part II describe how the transactions we investigate affect total tax expense (TTEt) and

cash taxes paid (CTPt) to result in the following:

34

Scholes et al. (2008), Appendix 2.2, Equation A2.1.

45

Equation (1a): TaxACCt = TTEt – CTPt

TTEt = [((PTBIt – PermBTDst) * STR) – TaxCreditst] – NOLtCarryback + ΔValAllowt + ΔUTBt, perm

+ (Decrease in UTBt where Settlement > Amount Reserved for as a UTB) – (Decrease in UTBt where Settlement < Amount Reserved for as a UTB)

+ ESO Exercise Shortfallpost-123(R) + ESO Expires Unexercisedpost-123(R)

– Classifying earningst as PRE + (Un-classifying Earnings Designated as PRE prior to t and Remitting in t)

+ (Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1)

+ (Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1) – Classifying Unremitted Earningst-1 as PRE in t

– Classifying Unremitted Earningst-2 as PRE in t + (ΔSTRt+1 affecting DTL_LT and DTA_LT) + (ΔSTRt+1 affecting DTL_ST and DTA_ST)

+ Tax True Upt,perm + Tax AJEt

CTPt = [((PTBIt – PermBTDst) * STR) – TaxCreditst] – TempBTDst – NOLtCarryback – (Increase in UTBt, temp for CY positions)

+ (Decrease in UTBt where Settlementt = Amount Reserved for as a UTB) + (Decrease in UTBt where Settlementt > Amount Reserved for as a UTB) –

(Decrease in UTBt where Settlementt < Amount Reserved for as a UTB) + Non-articulating Itemst – ESO Exercisepre-123(R)

– ESO ExerciseWindfallpost-123(R) – Classifying Earningst as PRE + (Un-classifying Earnings Designated as PRE prior to t and Remitting in t)

– (Not Classifying Earningst as PRE and not Remitting in t) + Tax True Upt,perm – Tax True Upt,temp

Because we define tax accrual as the difference between total tax expense and cash taxes paid, transactions that affect both in the same direction will be

eliminated as follows:

TaxACCt = TTEt – CTPt

= [ [((PTBIt – PermBTDst) * STR) – TaxCreditst] – NOLtCarryback + ΔValAllowt + ΔUTBt, perm

+ (Decrease in UTBt where Settlement > Amount Reserved for as a UTB) – (Decrease in UTBt where Settlement < Amount Reserved for as a UTB)

+ ESO Exercise Shortfallpost-123(R) + ESO Expires Unexercisedpost-123(R)

– Classifying earningst as PRE + (Un-classifying Earnings Designated as PRE prior to t and Remitting in t)

+ (Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1)

+ (Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1) – Classifying Unremitted Earningst-1 as PRE in t

– Classifying Unremitted Earningst-2 as PRE in t + (ΔSTRt+1 affecting DTL_LT and DTA_LT) + (ΔSTRt+1 affecting DTL_ST and DTA_ST)

+ Tax True Upt,perm + Tax AJEt ]

– [ [((PTBIt – PermBTDst) * STR) – TaxCreditst] – TempBTDst – NOLtCarryback – (Increase in UTBt, temp for CY positions)

+ (Decrease in UTBt where Settlementt = Amount Reserved for as a UTB) + (Decrease in UTBt where Settlementt > Amount Reserved for as a UTB)

– (Decrease in UTBt where Settlementt < Amount Reserved for as a UTB) + Non-articulating Itemst – ESO Exercisepre-123(R)

– ESO ExerciseWindfallpost-123(R) – Classifying Earningst as PRE + (Un-classifying Earnings Designated as PRE prior to t and Remitting in t)

– (Not Classifying Earningst as PRE and not Remitting in t) + Tax True Upt,perm – Tax True Upt,temp]

The following shows the items that remain in the tax accrual after cancelling items and replacing the ‘TempBTDs’ component of CTPt with

‘[(ΔDTL_LTt + ΔDTL_STt) – (ΔDTA_LTt + ΔDTA_STt)].’ Note that estimation error (Et) can only arise from items that remain in the tax accrual. In addition,

items in both TTE and CTP cancel completely only if the estimated amount in TTE is equal to the cash paid in t-1, t, or t+1 or changes in DTL_LT or DTA_LT.

46

TaxACCt = ΔValAllowt + ΔUTBt, perm

– (Decrease in UTBt where Settlement < Amount Reserved for as a UTB)

+ ESO Exercise Shortfallpost-123(R) + ESO Expires Unexercisedpost-123(R)

+ (Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1)

+ (Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1) – Classifying Unremitted Earningst-1 as PRE in t – Classifying Unremitted Earningst-2 as PRE in t + (ΔSTRt+1 affecting DTL_LT and DTA_LT) + (ΔSTRt+1 affecting DTL_ST and DTA_ST)

+ Tax AJEt + [(ΔDTL_LTt + ΔDTL_STt) – (ΔDTA_LTt + ΔDTA_STt)] + (Increase in UTBt, temp for CY positions)

– (Decrease in UTBt where Settlementt = Amount Reserved for as a UTB)

– Non-articulating Itemst + ESO Exercisepre-123(R)

+ ESO ExerciseWindfallpost-123(R)

+ (Not Classifying Earningst as PRE and not Remitting in t) + Tax True Upt,temp + Et

Grouping similar items together yields the following re-arranged equation:

TaxACCt = [ (ΔDTL_LTt + ΔDTL_STt) – (ΔDTA_LTt + ΔDTA_STt)] + ΔValAllowt

[ + ΔUTBt, perm + (Increase in UTBt, temp for CY positions) – (Decrease in UTBt where Settlementt = Amount Reserved for as a UTB)]

– Non-articulating Itemst

[ + ESO Exercise Shortfallpost-123(R) + ESO Exercisepre-123(R) + ESO ExerciseWindfallpost-123(R) + ESO Expires Unexercisedpost-123(R)]

[ + (Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1) (A1)

+ (Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1) + (Not Classifying Earningst as PRE and not Remitting in t)

– Classifying Unremitted Earningst-1 as PRE in t – Classifying Unremitted Earningst-2 as PRE in t ]

[ + (ΔSTRt+1 affecting DTL_LT and DTA_LT) + (ΔSTRt+1 affecting DTL_ST and DTA_ST) ]

+ Tax True Upt,temp

+ Tax AJEt

+ Et

Equation A1 shows that the tax accrual is comprised of temporary book-tax differences, changes in the valuation allowance, changes in UTBs, non-articulating

items, ESO-related transactions, changes in the designation of foreign earnings as permanently reinvested, changes in statutory tax rates, tax true-ups, and tax-

related adjusting journal entries.

We next illustrate the purpose of our control variables. Below is the regression used to estimate TaxAQ, which we define as the standard deviation of the

residuals (εt).

Equation (1b): TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4ΔDTL_LTt + β5ΔDTA_LTt + εt

The independent variables in Equation 1b are controlling for items in the tax accrual (TaxACCt) to limit the residual (εt) to capturing estimation error (Et).

Specifically, each independent variable controls for the following items in the tax accrual:

47

Control Variable Items in TaxACC this Variable Controls for

CTPt-1 (β1 > 0)

ΔDTL_LTt and ΔDTA_LTt [Transaction 2e]

ΔDTL_STt and ΔDTA_STt [Transaction 2f]

Classifying Unremitted Earningst-1 as PRE in t [Transaction 8f]

CTPt

(β2 < 0)

ΔDTL_LTt and ΔDTA_LTt [Transactions 2a, 2c, 2e, 2g]

ΔDTL_STt and ΔDTA_STt [Transactions 2b, 2d, 2f, 2h]

Increase in UTBt, temp for CY positions [Transaction 5b]

Decrease in UTBt where Settlementt = Amount Reserved for as a UTB [Transaction 5d]

Non-articulating Itemst [Transaction 6]

ESO Exercisepre-123(R) [Transaction 7a]

ESO ExerciseWindfallpost-123(R) [Transaction 7c]

Not Classifying Earningst as PRE and not Remitting in t [Transaction 8e]

Tax True-Upt,temp[Transaction 10b]

CTPt+1 (β3 > 0)

ΔDTL_LTt and ΔDTA_LTt [Transaction 2a]

ΔDTL_STt and ΔDTA_STt [Transaction 2b]

Un-classifying Earnings Designated as PRE prior to t and Remitting in t+1 [Transaction 8d]

Tax AJEt [Transaction 11]

ΔDTL_LTt (β4 < 0)

ΔDTL_LTt [Transactions 2a, 2c, 2e]

Increase in UTBt,temp for CY positions [Transaction 5b]

ΔSTRt+1 affecting DTL_LT [Transaction 9a]

ΔDTA_LTt (β5 > 0)

ΔDTA_LTt [Transactions 2a, 2c, 2e]

ΔValAllowt [Transaction 4]

Increase in UTBt, temp for CY positions [Transaction 5b]

ESO Expires Unexercisedpost-123(R) [Transaction 7e]

ΔSTRt+1 affecting DTA_LT [Transaction 9a]

Thus, after comparing the above variables in Equation (A1) to the control variables in Equation (1b) we are left with the following items in the residual:

εt = (Un-classifying Earnings Designated as PRE prior to t and not Remitting in t or t+1) – Classifying Unremitted Earningst-2 as PRE in t

+ (ΔSTRt+1 affecting DTL_ST and DTA_ST) + ESO Exercise Shortfallpost-123(R) + ΔUTBt, perm + Et

Thus, a majority of the transactions that have different financial and tax reporting treatment do not affect the Equation 1b residual (or our measure of TaxAQ)

because the items either cancel or are controlled for by CTPt-1, CTPt, CTPt+1, ΔDTL_LTt, or ΔDTA_LTt. The residual is comprised of items from GAAP-induced

mismapping (e.g., foreign earnings, ESOs, and UTBs), as well as items that arise from judgment in applying GAAP-related to items in the tax accrual

(TaxACCt), which manifests as estimation error (Et).

48

Part II. Examples of Transactions and their Effects on Tax Expense, Cash Taxes Paid, and the Regression Residual

Below are some more common examples of complicated transactions that do not articulate between financial reporting and tax reporting. We investigate each

transaction and provide a description of how it would affect tax expense in t, cash taxes paid in t-1 through t+1, and our residual (assuming no estimation error

exists). These transactions help us arrive at the decomposition of total tax expense and cash taxes paid reported in Parts I and II. Recall that the starting point for

calculating both tax expense (TTEt) and cash taxes paid (CTPt) is pre-tax book income (PTBIt) multiplied by the statutory tax rate (STR).

Transaction Tax Expense (TTEt)

(where TTEt = PTBIt * STR) Cash Taxes Paid (CTP)

In the Residual

(assuming no estimation error)

1 Permanent BTDs established in t CTE decrease or increase Decrease or increase in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

2a Temporary BTDs: DTL_LT (DTA_LT)

35 established in t that

reverse in t+1 No effect

Decrease (increase) in t

No effect in t-1

Increase (decrease) in t+1

No because we control for

ΔDTL_LT (ΔDTA_LT), CTPt,

and CTPt+1

2b Temporary BTDs: DTL_ST (DTA_ST) established in t that

reverse in t+1 No effect

Decrease (increase) in t

No effect in t-1

Increase (decrease) in t+1

No because we control for

CTPt and CTPt+1

2c Temporary BTDs: DTL_LT (DTA_LT) established in t that

reverse after t+1 No effect

Decrease (increase) in t

No effect in t-1 or t+1

No because we control for

ΔDTL_LT (ΔDTA_LT) and

CTPt

2d Temporary BTDs: DTL_ST (DTA_ST)

2 established in t that

reverse after t+1 No effect

Decrease (increase) in t

No effect in t-1 or t+1

No because we control for

CTPt

2e Temporary BTDs: DTL_LT (DTA_LT

)2 established in t-1 that

reverse in t No effect

Increase (decrease) in t

Decrease (increase) in t-1

No because we control for

ΔDTL_LT (ΔDTA_LT), CTPt,

and CTPt-1

2f Temporary BTDs: DTL_ST (DTA_ST) established in t-1 that

reverse in t No effect

Increase (decrease) in t

Decrease (increase) in t-1

No because we control for

CTPt, and CTPt-1

2g Temporary BTDs: DTL_LT (DTA_LT)

2 established prior to t-1

that reverse in t No effect

Increase (decrease) in t

No effect in t-1 or t+1

No because we control for

CTPt

2h Temporary BTDs: DTL_ST (DTA_ST)

2 established prior to t-1

that reverse in t No effect

Increase (decrease) in t

No effect in t-1 or t+1

No because we control for

CTPt

35

Assumption that long-term (short-term) classification relates to a long-term (short-term) underlying liability or asset and not the expected reversal date.

49

Transaction Tax Expense (TTEt)

(where TTEt = PTBIt * STR) Cash Taxes Paid (CTP)

In the Residual

(assuming no estimation error)

2i

Temporary BTDs: DTL_LT (DTA_LT) established in t-1 and

reclassified as DTL_ST (DTA_ST) in t because they will reverse

in t+1

No effect

No effect in t

Decrease (increase) in t-1

Increase (decrease) in t+1

No because it is not included

in TaxACCt

2j

Temporary BTDs: DTL_LT (DTA_LT) established prior to t-1

and reclassified as DTL_ST (DTA_ST) in t because they will

reverse in t+1

No effect No effect in t-1 or t

Increase (decrease) in t+1

No because it is not included

in TaxACCt

3 Generate NOL in t and carryback to prior period CTE decrease36

Decrease in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

4 Increase (decrease) in the Valuation Allowance related to

DTA_LT2 that will reverse in t+1

DTE increase (decrease) No effect in t-1, t, or t+1 No because we control for

ΔDTA_LT37

5a

Increase in UTBt related to permanent differences for current

period and increase (decrease) in UTBt related to permanent

differences for prior period positions

[referred to as ΔUTBt, perm in Part I]

CTE increase (decrease)38

No effect in t-1, t, or t+1 Yes

5b

Increase in UTBt related to temporary differences for current

period positions that reverse in t+1

[acts like Transactions 2a and 2b]

No effect

Decrease in t39

No effect in t-1

Increase in t+1

No, because we control for

CTPt and CTPt+1

5c Increase (decrease) in UTBt related to temporary differences for

prior period positions taken prior to t-1 No effect No effect in t-1, t, or t+1

No because it is not included

in TaxACCt

5d Decrease in UTBt where Settlementt = Amount Reserved for as a

UTB No effect

Increase in t

No effect in t-1 or t+1

No because we control for

CTPt

5e Decrease in UTBt where Settlementt > Amount Reserved for as a

UTB [i.e., firm is “under-reserved”; this transaction is viewed as

incremental to Transaction 5d]

CTE increase Increase in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

5f Decrease in UTBt where Settlementt < Amount Reserved for as a

UTB [i.e., firm is “over-reserved”; this transaction is viewed as

incremental to Transaction 5d]

CTE decrease Decrease in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

36

Confirmation that tax expense is current (http://accounting.utep.edu/sglandon/c16/c16b.pdf, bottom of page 1). 37 The change in valuation allowance is not in the residual because COMPUSTAT records firms’ DTAs net of the valuation allowance. 38

DTE, not CTE, is affected for firms that report a loss for financial reporting purposes. 39

CTP decreases in period t in Transaction 5b because the starting point when calculating CTP in our model is ‘((PTBIt – PermBTDst) * STR) – TempBTDs.’

An uncertain tax position related to a temporary difference between book income and taxable income will be included in TempBTDst, as the latter only relates to

items which generate DTAs and DTLs. Thus, we subtract ‘Increase in UTBt, perm for CY positions’ in our CTPt equation.

50

Transaction

Tax Expense (TTEt)

(where TTEt = PTBIt * STR) Cash Taxes Paid (CTP)

In the Residual

(assuming no estimation error)

6 Non-articulating Items Includable/Deductible in t No effect

Increase or decrease in t

No effect in t-1 or t+1

No because we control for

CTPt

7a ESO Exercisepre-123(R) (APB 25)40

No effect

Decrease by intrinsic value

at exercise date in t

No effect in t-1 or t+1

No because we control for

CTPt

7b ESO Exercisepost-123(R), when Fair Value = Intrinsic Value

(example of Transactions 2f or 2g) No effect

Decrease in t41

No effect in t-1

No effect in t+1

No because we control for

ΔDTA_LT

7c ESO Exercise Windfallpost-123(R), when Fair Value < Intrinsic

Value No effect

Decreased in t

No effect in t-1 or t+1

No because we control for

CTPt

7d ESO Exercise Shortfallpost-123(R), when Fair Value > Intrinsic

Value and no prior excess APIC CTE increase No effect in t-1, t, or t+1 Yes

7e ESO Optionpost-123(R), Expires Unexercised

(example of Transactions 2e and 2g; DTA that is never realized) DTE increase No effect in t-1, t, or t+1

No because we control for

ΔDTA_LT

7f ESO Option post-123(R) During Vesting Period

[example of DTA in Transactions 2a and 2c] No effect

Increase in t

No effect in t-1 or t+1

No because we control for

ΔDTA_LT

8a Classifying earningst as permanently reinvested earnings (PRE) CTE decrease

Decrease in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

8b Un-classifying earnings designated as PRE prior to t and

remitting in t CTE increase

Increase in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

8c Un-classifying earnings designated as PRE prior to t and not

remitting in t or t+1 CTE increase No effect in t-1, t, or t+1 Yes

8d Un-classifying earnings designated as PRE prior to t and

remitting in t+1 CTE increase

No effect in t-1 or t

Increase in t+1

No because we control for

CTPt+1

40 Pre-FAS123(R) (June 15, 2006) ESOs were recognized for financial reporting at their intrinsic value (typically zero) at issuance and deducted for tax purposes

at their intrinsic value at exercise date. The difference in ESO values was similar to a permanent book-tax difference but treated as a credit to APIC instead of a

reduction in tax expense, resulting in a large difference between tax expense and cash taxes paid. Post-FAS123(R), ESOs are recognized for financial reporting at

their fair value at issuance with no change in tax reporting. Measurement differences between book and tax were smaller post FAS123(R) because tax expense

reflected some of the eventual tax return deduction. The timing of the financial reporting expense precedes the tax return deduction, giving rise to a DTA.

However, some measurement differences still exist. Specifically, if the intrinsic value at exercise exceeds the fair value financial reporting expense, the excess

tax benefit ("windfall") is credited to APIC at the exercise date. Alternatively, if the intrinsic value at exercise is less than the fair value financial reporting

expense, the unrealized portion of the deferred tax asset ("shortfall") is offset to APIC, and any remainder increases income tax expense. 41

This decrease is already accounted for under temporary BTDs (Transactions 2f and 2g) so we do not include it as a separate item in the equation.

51

Transaction Tax Expense (TTEt)

(where TTEt = PTBIt * STR) Cash Taxes Paid (CTP)

In the Residual

(assuming no estimation error)

8e Not classifying earningst as PRE and not remitting in t (e.g.,

Apple example, see Linebaugh et al. 2013) No effect

Decrease in t

No effect in t-1 or t+1

No because we control for

CTPt

8f

Classifying unremitted foreign earnings earned in t-1 (on which

income tax was accrued) as PRE in t

[Transaction 8e must have occurred in t-1]

CTE decrease No effect in t or t+1

Decrease in t-1

No because we control for

CTPt-1

8g

Classifying unremitted foreign earnings earned prior to t-1 (on

which income tax was accrued) as PRE in t

[Transaction 8e must have occurred prior to t-1]

CTE decrease No effect in t-1, t, or t+1 Yes

9a

Increase (decrease) in statutory tax rate effective in or after t+1

related to existing DTL_LTs (DTA_LTs)2 that reverse when the

new statutory tax rate is effective

DTE increase (decrease) No effect in t-1, t, or t+1 No because we control for

ΔDTL_LT (ΔDTA_LT)

9b

Increase (decrease) in statutory tax rate effective in or after t+1

related to existing DTL_STs (DTA_STs)2 that reverse when the

new statutory tax rate is effective

DTE increase (decrease) No effect in t-1, t, or t+1 Yes

10a Tax True-Upt,perm (Accrual adjustment made in t related to

permanent difference in t-1, after filing Form 10-Kt-1) CTE increase or decrease

Increase or decrease in t

No effect in t-1 or t+1

No because it is not included

in TaxACCt

10b

Tax True-Upt,temp (Accrual adjustment made in t but related to

temporary difference in t-1, after filing Form 10-Kt-1) [reversal

in future periods is an example of Transactions 2a-2d]

No effect; reclassification

between CTE and DTE

Decrease in t

No effect in t-1 or t+1

No because we control for

CTPt

11 Tax Adjusting Journal Entry (accrual for t and paid in t+1) CTE increase or decrease No effect in t-1 or t

Increase or decrease in t+1

No because we control for

CTPt+1

52

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56

Table 1: Sample Selection

COMPUSTAT universe of firm-year observations (1993 – 2011) 180,755

Less: Firm-year observations with missing values required to estimate Equations 1b

and 1c (TaxACCt, CTPt-1,t, t+1, ∆DTL_LTt, ∆DTA_LTt, CAPXt, and ∆NOLt) (84,284)

96,471

Less: Firm-year observations with less than ten years of consecutive data

(8 regression residuals are required to estimate TaxAQ/TaxAQ2) (47,682)

48,789

Less: Firm-year observations with missing data to estimate UTB (4,278)

Final number of firm-year observations 44,511

Less: Firm-year observations with data pre-2001 (26,432)

Firm-year observations used to estimate Table 6 (2002 – 2010) 18,079

Final number of firms (2002 – 2010) 3,290

57

Table 2: Descriptive Statistics and Correlations

Panel A: Descriptive Statistics

Variables N Mean P25 P50 P75 S.D.

Total Assetst (TAt) ($M) 44,511 2,615 65 309 7,031 6,746

Revenuet (REVt) ($M) 44,511 2,202 67 319 5,840 5,366

Market Value of Equityt (MVEt) ($M) 43672 2,808 54 308 8,290 7,791

Pre-tax Book Incomet (PTBIt) 44,511 0.029 0.001 0.061 0.209 0.199

Tax Expenset (TEt) 44,511 0.024 0.001 0.019 0.035 0.034

Tax Accrualt (TaxACCt) 44,511 0.002 -0.005 0.001 0.025 0.024

Cash Taxes Paidt (CTPt) 44,511 0.022 0.002 0.012 0.028 0.027

Cash Taxes Paidt-1(CTPt-1) 44,511 0.020 0.002 0.012 0.025 0.025

Cash Taxes Paidt+1(CTPt+1) 44,511 0.025 0.002 0.013 0.033 0.032

Change in Long-Term Deferred Tax Liabilitiest

(∆DTL_LTt) 44,511 0.002 0.000 0.000 0.014 0.014

Change in Long-Term Deferred Tax Assetst

(∆DTA_LTt) 44,511 0.001 0.000 0.000 0.010 0.010

Capital Expenditurest (CAPXt) 44,511 0.059 0.020 0.040 0.067 0.066

Change in Net Operating Loss (∆NOLt) 44,511 0.020 0.000 0.000 0.144 0.134

Panel B: Pearson\Spearman Correlations

TaxACCt CTPt CTPt-1 CTPt+1 ∆DTL_LTt ∆DTA_LTt CAPXt ∆NOLt

TaxACCt - -0.07 -0.01 0.19 0.29 -0.16 0.09 -0.08

CTPt -0.12 - 0.71 0.72 0.04 0.02 0.16 -0.11

CTPt-1 -0.05 0.68 - 0.57 0.02 0.02 0.14 -0.04

CTPt+1 0.15 0.70 0.52 - 0.07 0.01 0.12 -0.13

∆DTL_LTt 0.26 -0.01 -0.03 0.02 - -0.07 0.13 -0.04

∆DTA_LTt -0.24 0.00 0.00 -0.01 -0.04 - -0.01 0.03

CAPXt 0.06 0.08 0.05 0.05 0.12 -0.02 - -0.03

∆NOLt -0.02 -0.10 -0.08 -0.10 -0.03 0.00 -0.03 -

Notes: All variables are defined in Appendix 1 and all continuous variables are winsorized at the 1

st and 99

th

percentile (pooled). All variables in Panel A except Total Assets, Revenue, and Market Value of Equity are scaled

by total assets. In Panel B correlations significant at the five percent level (using two-tailed p-values) are in bold.

58

Table 3: Estimating our First Tax Accrual Quality Measure (TaxAQ)

TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4∆DTL_LTt + β5∆DTA_LTt + εt

Panel A: Pooled Regression

Variable Prediction [1] [2]

Intercept ? -0.000 -0.001

(0.45) (-0.78)

CTPt-1 + 0.042*** 0.050***

(4.68) (5.76)

CTPt ‒ -0.423*** -0.414***

(-40.75) (-40.88)

CTPt+1 + 0.353*** 0.340***

(49.08) (48.20)

∆DTL_LT + 0.437***

(30.38)

∆DTA_LT ‒ -0.540***

(-23.58)

Industry and Year Indicators Y Y

N 44,511 44,511

Adj. R2 14% 25%

Panel B: Industry Specific Regression (48 Industries)

Variable Prediction Mean P25 P50 P75 S.D.

Intercept ? 0.002** -0.001 0.002 0.004 0.004

CTPt-1 + 0.096*** 0.035 0.081 0.136 0.130

CTPt ‒ -0.439*** -0.538 -0.426 -0.305 0.208

CTPt+1 + 0.325*** 0.240 0.323 0.396 0.164

∆DTL_LT + 0.474*** 0.347 0.503 0.609 0.225

∆DTA_LT ‒ -0.593*** -0.731 -0.630 -0.524 0.273

Adj. R2 54% 45% 56% 69% 20%

Panel C: Firm Specific Regression (3,290 firms)

Variable Prediction Mean P25 P50 P75 S.D.

Intercept ? 0.003 -0.003 0.002 0.009 0.016

CTPt-1 + 0.065*** -0.220 0.033 0.299 1.402

CTPt ‒ -0.494*** -0.832 -0.476 -0.115 1.322

CTPt+1 + 0.295*** 0.040 0.272 0.575 1.344

∆DTL_LT + 0.521*** 0.000 0.168 0.729 2.415

∆DTA_LT ‒ -0.302*** -0.564 0.000 0.000 2.358

Adj. R2 44% 19% 49% 76% 40%

Notes: All variables are defined in Appendix 1 and all continuous variables are winsorized at the 1st and 99

th

percentile (pooled). Panel A presents the coefficients from a pooled OLS regression with year and industry (Fama

59

French 48) fixed effects and standard errors clustered by firm. Panel B presents the coefficients from industry-level

OLS regressions estimated at the industry level. Panel C presents the coefficients from firm-level OLS regressions.

***, **, and * indicate significance at the 1%, 5%, and 10%, respectively. In Panels B and C, statistical significance

is based on t-test whether the mean of the distribution of coefficients is different from zero (one-tailed for directional

predictions).

60

Table 4: Estimating our Alternate Tax Accrual Quality Measure (TaxAQ2)

TaxACCt = β0 + β1CTPt-1 + β2CTPt + β3CTPt+1 + β4CAPXt + β5∆NOLt + εt

Panel A: Pooled Regression

Variable Prediction [1] [2]

Intercept ? -0.000 -0.002

(0.45) (-2.02)

CTPt-1 + 0.042*** 0.040***

(4.68) (4.46)

CTPt ‒ -0.423*** -0.429***

(-40.75) (-41.37)

CTPt+1 + 0.353*** 0.353***

(49.08) (49.04)

CAPXt + 0.034***

(11.82)

∆NOLt ‒ -0.004***

(-3.52)

Industry and Year Indicators Y Y

N 44,511 44,511

Adj. R2 14% 15%

Panel B: Industry Specific Regression (48 industries)

Variable Prediction Mean P25 P50 P75 S,D.

Intercept ? 0.000 -0.002 0.000 0.002 0.004

CTPt-1 + 0.060*** -0.007 0.056 0.088 0.121

CTPt ‒ -0.463*** -0.577 -0.462 -0.329 0.237

CTPt+1 + 0.294*** 0.201 0.316 0.373 0.179

CAPXt + 0.047*** 0.017 0.040 0.057 0.067

∆NOLt ‒ -0.004 -0.006 0.000 0.001 0.022

Adj. R2 15% 6% 11% 17% 16%

Panel C: Firm Specific Regression (3,290 firms)

Variable Prediction Mean P25 P50 P75 S.D.

Intercept ? 0.002*** -0.008 0.001 0.013 0.028

CTPt-1 + -0.106*** -0.287 0.005 0.285 1.946

CTPt ‒ -0.534*** -0.882 -0.507 -0.117 2.139

CTPt+1 + 0.256*** 0.015 0.277 0.595 2.066

CAPXt + 0.056*** -0.112 0.025 0.211 0.717

∆NOLt ‒ -0.013 -0.036 0.000 0.012 0.500

Adj. R2 32% 4% 37% 64% 42%

Notes: All variables are defined in Appendix 1 and all continuous variables are winsorized at the 1st and 99

th

percentile (pooled). Panel A presents the coefficients from a pooled OLS regression estimated with year and

61

industry (Fama French 48) fixed effects and standard errors clustered by firm. Panel B presents the coefficients from

industry-level OLS regressions estimated at the industry level. Panel C presents the coefficients from firm-level

OLS regressions. ***, **, and * indicate significance at the 1%, 5%, and 10%, respectively. In Panels B and C,

statistical significance is based on t-test whether the mean of the distribution of coefficients is different from zero

(one-tailed for directional predictions).

62

Table 5: Relations between TaxAQ (TaxAQ2) and Tax Avoidance Proxies

Panel A: Descriptive Statistics

N Mean P25 P50 P75 S.D.

TaxAQ 11,552 -0.009 -0.011 -0.006 -0.004 0.008

TaxAQ2 11,552 -0.010 -0.012 -0.007 -0.004 0.010

GAAPETR3 11,552 0.331 0.276 0.347 0.383 0.270

CASHETR3 11,552 0.258 0.147 0.253 0.338 0.193

TOTALBTD3 11,552 0.029 0.003 0.022 0.045 0.054

PERMBTD3 11,552 0.034 -0.003 0.027 0.062 0.067

Panel B: Pearson\Spearman Correlations

[1] [2] [3] [4] [5] [6]

[1] TaxAQ 1 0.81 0.00 0.03 -0.01 0.01

[2] TaxAQ2 0.78 1 0.03 0.07 -0.01 0.00

[3] GAAPETR3 0.06 0.10 1 0.38 -0.32 -0.12

[4] CASHETR3 0.02 0.05 0.29 1 -0.44 -0.48

[5] TOTALBTD3 -0.08 -0.09 -0.23 -0.32 1 0.72

[6] PERMBTD3 -0.07 -0.07 -0.04 -0.36 0.62 1

Notes: All variables are defined in Appendix 1 and all continuous variables are winsorized at the 1

st and 99

th percentile (pooled). Significant sample loss occurs

due to the 3-year GAAP ETR and 3-year CASH ETR variables requiring the 3-year sum of pre-tax net income to be positive. In Panel B correlations significant

at the five percent level (using two-tailed p-values) are in bold.

63

Table 6: Firm Characteristics that Capture GAAP-Induced Mismapping and Require Judgment in Estimation

Panel A: Descriptive Statistics

Variables N Mean P25 P50 P75 S.D.

TaxAQjt 18,079 -0.010 -0.012 -0.007 -0.004 0.011

TaxAQ2jt 18,079 -0.012 -0.014 -0.008 -0.004 0.013

FOREIGNjt 18,079 0.475 0.000 0.000 1.000 0.499

ESO_INDUSTRYjt 18,079 0.520 0.000 1.000 1.000 0.500

UTB_ESTjt 18,079 0.011 0.007 0.011 0.015 0.005

UTB_ACTUALjt 4,841 0.002 0.007 0.013 0.016 0.018

PTBI_VOLjt 18,079 0.113 0.039 0.070 0.126 0.145

TAX_BENEFITjt 18,079 0.163 0.000 0.000 0.000 0.369

DISC&EXTRAjt 18,079 0.059 0.000 0.000 0.000 0.024

SIZEjt 18,079 6.218 4.706 6.292 7.797 2.246

Panel B: Pearson\Spearman Correlations (N=18,079)

[1] [2] [3] [4] [5] [6] [7] [8] [9]

[1] TaxAQjt - 0.81 -0.07 -0.18 -0.08 -0.43 -0.16 -0.05 0.24

[2] TaxAQ2jt 0.78 - -0.06 -0.15 -0.05 -0.47 -0.19 -0.05 0.21

[3] FOREIGNjt 0.01 0.00 - 0.21 0.59 -0.02 -0.02 -0.01 0.28

[4] ESO_INDUSTRYjt -0.16 -0.14 0.21 - 0.30 0.24 0.04 -0.01 -0.23

[5] UTB_ESTjt -0.05 -0.03 0.58 0.32 - 0.08 -0.06 -0.05 0.24

[6] PTBI_VOLjt -0.27 -0.29 -0.09 0.14 0.10 - 0.21 0.06 -0.48

[7] TAX_BENEFITjt -0.14 -0.16 -0.02 0.04 -0.03 0.11 - 0.07 -0.12

[8] DISC&EXTRAjt -0.04 -0.04 -0.01 -0.01 -0.04 0.06 0.07 - -0.02

[9] SIZEjt 0.28 0.23 0.29 -0.22 0.16 -0.43 -0.12 -0.05 -

64

Table 6: Firm Characteristics that Capture GAAP-Induced Mismapping and Require

Judgment in Estimation (cont.)

Panel C: Regression Results

TaxAQjt (or TaxAQ2jt) = αjt + αyear + αindustry + β1FOREIGNjt + β2ESO_INDUSTRYjt

+ β3UTB_ESTjt (or UTB_ACTUALjt) + β4PTBI_VOLjt + β5TAX_BENEFITjt

+ β6DISC&EXTRAjt + β7SIZE+ εjt

Y = TaxAQjt Y = TaxAQ2jt

Pred. [1] [2] [3] [4]

Intercept +/‒ -0.012*** -0.014*** -0.012*** -0.014***

(-9.74) (-10.27) (-9.58) (-7.82)

FOREIGNjt ‒ -0.001** 0.000 -0.001*** 0.000

(-1.91) (0.28) (-2.73) (0.35)

ESO_INDUSTRYjt ‒ -0.000 -0.000 -0.002* -0.002**

(-0.45) (-0.39) (-1.53) (-1.85)

UTB_ESTjt ‒ 0.003 0.122**

(0.05) (2.04)

UTB_ACTUALjt ‒ -0.029** -0.046**

(-1.87) (-2.16)

PTBI_VOLjt ‒ -0.012*** -0.010*** -0.018*** -0.024***

(-4.60) (-3.05) (-5.98) (-4.67)

TAX_BENEFITjt ‒ -0.003*** -0.002*** -0.004*** -0.003***

(-9.20) (-4.08) (-10.95) (-5.34)

DISC&EXTRAjt ‒ -0.001*** -0.001 -0.001** -0.001

(-2.55) (-1.14) (-2.04) (-1.22)

SIZEjt +/- 0.001*** 0.001*** 0.001*** 0.001***

(8.02) (7.13) (5.17) (5.34)

N 18,079 4,841 18,079 4,841

Adj. R2 15% 15% 15% 18%

Notes: All variables are defined in Appendix 1 and continuous variables are winsorized at the 1

st and 99

th percentiles

(pooled). In Panel B correlations significant at the five percent level (using two-tailed p-values) are in bold. In Panel

C we use an OLS regression specification. T-statistics are presented in parentheses below each coefficient. ***, **,

and * indicate significance at the 1%, 5%, and 10% respectively using a t-test to determine whether the distribution

of coefficients are different from zero (one-tailed for directional predictions). We cluster standard errors by firm.

65

Table 7: Testing the Predictive Validity of our Tax Accrual Quality Measure

Panel A: Descriptive Statistics by TaxAQ Quartile

Frequency

TaxAQjt

Quartile

TaxAQjt

Mean TAX_RESTATEjt+1 TAX_ICWjt+1

N=18,079 N=18,079 N=10,365

1 (best) -0.002 0.7% 1.1%

2 -0.005 1.0% 2.1%

3 -0.009 1.1% 3.3%

4 (worst) -0.024 1.3% 4.2%

Difference: 1 - 4 0.022 -0.6%*** -3.1%***

Panel B: Descriptive Statistics by TaxAQ2 Quartile

Frequency

TaxAQ2jt

Quartile

TaxAQ2jt

Mean TAX_RESTATEjt+1 TAX_ICWjt+1

N=18,079 N=18,079 N=10,365

1 (best) -0.002 0.8% 1.1%

2 -0.006 0.9% 2.1%

3 -0.010 1.1% 2.6%

4 (worst) -0.028 1.3% 3.7%

Difference: 1 - 4 0.026 -0.5%*** -2.6%***

66

Table 7: Testing the Predictive Validity of our Tax Accrual Quality Measure (cont.)

Panel C: Predicting Tax-Related Restatements and Tax-Related Internal Control Weaknesses

Yjt+1 = αjt + αyear + αIndustry + β1TaxAQjt (or TaxAQ2jt) + β2FOREIGNjt + β3t ESO_INDUSTRYjt

+ β4UTB_ESTjt + β5PTBI_VOLjt + β6TAX_BENEFITjt + β7DISC&EXTRAjt + β8SIZEjt

+ β9AQjt + εjt+1

Y = TAX_RESTATEt+1 Y = TAX_ICWt+1

Variables [1] [2] [3] [4]

Interceptjt ? -2.789*** -2.767*** -1.855*** -1.817***

(-9.73) (-9.59) (-5.18) (-5.05)

TaxAQjt ‒ -5.659*** -8.335***

(-2.37) (-2.39)

TaxAQ2jt ‒ -3.630** -5.557**

(-1.72) (-1.98)

FOREIGNjt +/‒ 0.191*** 0.192*** 0.440*** 0.444***

(2.59) (2.60) (5.49) (5.53)

ESO_INDUSTRYjt +/‒ -0.118 -0.125 0.005 -0.005

(-0.66) (-0.70) (0.03) (-0.03)

PTBI_VOLjt +/‒ -6.740 -6.173 -13.916 -13.633

(-0.83) (-0.76) (-1.49) (-1.45)

UTB_ESTjt +/‒ 0.305 0.296 -0.713* -0.723*

(1.08) (1.05) (-1.68) (-1.71)

TAX_BENEFITjt +/‒ 0.083 0.087 0.276*** 0.272***

(1.12) (1.17) (3.54) (3.49)

DISC&EXTRAjt +/‒ 0.181* 0.181* -0.059 -0.050

(1.79) (1.81) (-0.43) (-0.36)

SIZEjt +/‒ -0.008 -0.011 -0.063** -0.068**

(-0.45) (-0.64) (-2.20) (-2.37)

AQjt +/‒ 2.657 2.395 -5.404** -5.512**

(1.48) (1.36) (-2.28) (-2.30)

Year and Fama French

Industry Indicators Y Y Y Y

N 16,928 16,928 9,875 9,875

N where Y = 1 187 187 267 267

Pseudo R2

5% 5% 13% 13%

Area under ROC 0.69 0.69 0.80 0.79

Notes: All variables are defined in Appendix 1 and all continuous variables are winsorized at the 1st and 99

th

percentile (pooled). Panel C is estimated using a probit regression specification with year and industry fixed effects

and standard errors clustered by firm. Including industry fixed effects does not change our main inferences, but does

result in a sample size loss of 6 (5) percent when Y=TAX_RESTATEjt+1 (Y= TAX_ICWjt+1) due to lack of variation

in the dependent variable within industry. T-statistics are presented in parentheses below each coefficient. ***, **,

and * indicate significance at the 1%, 5%, and 10% respectively (one-tailed for directional predictions).