mayberry mcguire omer

7/27/2019 Mayberry McGuire Omer

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Smooth taxable income, tax avoidance, and the information content of taxable

income

Michael A. Mayberrya

University of Florida(352) 294-1691

[email protected]

Sean T. McGuire

Texas A&M University(979) 845-7935

[email protected]

Thomas C. Omer

Texas A&M University

(979) [email protected]

aCorresponding Author

We appreciate helpful comments from workshop participants at the University of Texas - San Antonio.


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Smooth taxable income, tax avoidance, and the information content of taxable income

Abstract: Prior research examines whether firms smooth their financial statement earnings.

However, recent research also suggests that firms have significant incentives to smooth their

taxable income. This study investigates innate and discretionary components of smooth taxableincome and whether those characteristics influence the outcomes of firms future tax avoidance

activities as well as the information content of taxable income. We find that firms with smoother

taxable income have more favorable outcomes in their future tax avoidance activities (i.e.,

exhibit higher levels of future tax avoidance), which is consistent with smoothness reducing the

uncertainty associated with future tax benefits and allowing firms to develop more successful tax

avoidance strategies. Contrary to research that finds that smoothness enhances the information

content of financial statement income, we find that smoothness reduces the information content

of taxable income. This finding is consistent with the smoothness of taxable income either

eliminating or reducing the information contained in the unique economic shocks experienced by

taxable income.

Key Words:Income smoothing; taxable income; tax avoidance; information content

JEL Classifications: G32, H25, H32, M41


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I. Introduction

Prior research suggests that firms smooth their earnings in an effort to achieve specific

financial reporting outcomes (Myers et al. 2007)and to convey information to market

participants (Tucker and Zarowin 2006). Recent research also suggests that some firms have

incentives to reduce the volatility of their taxable income (Graham and Smith 1999; Lev and

Nissim 2004). The purpose of this study is to investigate whether the smoothness of a firms

taxable income is associated with the level of a firms tax avoidance in future periodsand

whether the smoothness of a firms taxable income influences the information content of taxable

income.

In a financial reporting context, Francis et al. (2004) argue that the smoothness of a

firms earnings is a combination of a firms innate characteristics (e.g., operating environment)

and managers discretionary choices. Similar to financial accounting, we expect that the

smoothness of a firms taxable income is also a function of innate firm characteristics and

managers discretionary tax reporting choices. For example, prior research finds that

approximately 50 percent of firms have incentives to intentionally smooth taxable income

(Graham and Smith 1999), which suggests that some managers likely proactively smooth taxable

income while other firms exhibit smooth taxable income due to innate characteristics. Regardless

of the underlying reason for the smoothness of a firms taxable income, it is an empirical

question whether the smoothness of a firms taxable income is associated with tax avoidance or

alters the information content of taxable income.

We expect that the smoothness of a firmstaxable income influences tax planning

activities in the current period. Volatile taxable income creates uncertainty about future pre-tax

cash flows which limits firmstax planning opportunities (Scholes et al. 2008). Smoothing


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taxable income allows managers to make accurate forecasts of future taxable income, which

reduces the uncertainty of the future benefits and costs associated with a given tax planning

activity. In other words, smooth taxable income likely increases the efficiency of firms tax

planning decisions in the current period. Because the benefits of tax planning activities in the

current period are often realized in both the current and future periods, we expect that firms with

smoother taxable income will exhibit higher levels of tax avoidance in future periods.

We also investigate whether the smoothness of taxable income affects its information

content. Prior research finds that taxable income provides value relevant information to market

participants (Ayers et al. 2009;Hanlon et al. 2005).Ex ante, it is unclear whether the smoothness

of taxable income will influence its information content. In the context of financial statement

income, prior research finds that smoothness is associated with more persistent earnings (Dichev

and Tang 2009)as well as increased informativeness about current and future earnings (Tucker

and Zarowin 2006;Hunt et al. 2000). These results suggest that the information content of

taxable income is higher for firms with smoother taxable income. However, it is also likely that

smoother taxable income contains less information relative to volatile taxable income. Lev and

Nissim (2004) argue that taxable income is informative because it contains unique economic

shocks relative to financial statement income. To the extent that firms with smoother taxable

income do not experience unique economic shocks or the economic shocks are significantly

dampened, we expect that smoother taxable income potentially contains less information than

volatile taxable income. In combination, prior research in financial reporting suggests that the

smoothness of taxable income should influence its information content.

On the other hand, the findings of prior financial reporting research may not translate to

taxable income. Unlike book income, the primary purpose of taxable income is not to convey


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information to shareholders but to serve as a basis for revenue collection by government agencies

(Hanlon et al. 2005; Hanlon and Maydew 2009). Hanlon et al. (2005) demonstrate that, while

taxable income contains useful information, shareholders primarily rely on book income to

assess performance. Because taxable income is not a primary means of conveying information to

shareholders, it seems less likely that the smoothness of taxable income would influence its

information content. Accordingly, we examine whether smoothness is associated with the

information content of taxable income.

Using a sample of firm-year observations from 1993 to 2009, we measure the smoothness

of a firms taxable income as the standard deviation of a firms taxable income because prior

research assumes that firms that do not smooth earnings exhibit higher earnings variability (e.g.,

Leuz et al. 2003). Consistent with prior research, we also measure smoothness as the ratio of the

standard deviation of taxable income to the standard deviation of pretax cash flows (Francis et al.

2004; Leuz et al. 2003). To examine the association between the smoothness of taxable income

and the level of firms future tax avoidance, we estimate two separate proxies that capture a wide

variety of tax avoidance activities. Specifically, we estimate the current and cash effective tax

rates over the subsequent five year period to capture (Ayers et al. 2009; Dyreng et al. 2008). To

examine whether smoothness is associated with the information content of taxable income, we

estimate the earnings response coefficient for firms taxable income (Ayers et al. 2009; Hanlon

et al. 2005).

We find that firms with smoother taxable income exhibit higher levels of tax avoidance

(i.e., more favorable tax outcomes) in future periods. Our findings suggest that smoothness

reduces the uncertainty associated with future tax benefits and costs and allows firms to

participate in more efficient tax planning activities that result in greater tax avoidance in future


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periods. We also find that smoother taxable income is less informative relative to volatile taxable

income. This result is consistent with the smoothness of taxable income either eliminating or

reducing the information contained in the unique economic shocks experienced by taxable

income.1Our findings are robust among a sample of firms identified as engaging in high levels

of tax avoidance, suggesting that the influence of smoothing on the information content of

taxable income is incremental to the influence of tax avoidance in Ayers et al. (2009).

In supplemental analysis, we follow Francis et al. (2004) and decompose our measures of

smoothness into their innate and discretionary components to examine the influence of each

component on tax avoidance and information content. We find that discretionary smoothness is

associated with greater tax avoidance in the future. This result is consistent with managers

intentionally smoothing taxable income to improve the effectiveness of their tax planning

activities. We also find that the innate smoothness of a firms taxable income does not influence

its information content. However, we find that discretionary smoothness is associated with less

informative taxable income, which suggests that intentional actions by managers reduces the

information contained in taxable income.

This study contributes to several areas of accounting research. First, we contribute to the

literature that investigates the determinants of firms tax avoidance activities. Prior research has

examined firm-level characteristics (Frank et al. 2009;Lisowsky 2010;Wilson 2009),

managerial incentives (Rego and Wilson 2012; Robinson et al. 2010), and ownership structure

(Chen et al. 2010;McGuire et al. 2011)as determinants of tax avoidance. We extend this line of

research by providing evidence consistent with the notion that the smoothness of firmstaxable

income facilitates tax avoidance. Second, we contribute to the emerging literature that examines

1We confirm that smooth book earnings contain significantly more information than taxable income.


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firmsincentives to smooth taxable income (Boynton et al. 1992;Graham and Smith 1999;

Scholes et al. 1992). We extend this line of research by investigating the consequences of having

smooth taxable income, specifically the influence of smoothing on future tax avoidance

outcomes.

We also contribute to the literature on the information content of taxable income. Prior

research finds that taxable income contains information incremental to book income about a

firms performance(Ayers et al. 2009; Hanlon et al. 2005). Graham et al. (2012) note that there

is limited evidence outside of Ayers et al. (2009) and Hanlon et al. (2005) on whether taxable

income is priced and call for more research that investigates what information is contained in

taxable income and what the market is pricing. We answer this call for research more broadly by

providing evidence that the smoothness of taxable income reduces its information content.

The remainder of the paper is structured as follows. In the next section we discuss prior

literature and develop our hypotheses. In Section 3, we define our variables and describe our

research design. Section 4 describes our sample selection and provides descriptive statistics.

Section 5 describes the results of our main analysis while Section 6 describes our supplemental

analysis. Section 7 describes our robustness tests and Section 7 concludes.

II. Background and Hypothesis Development

Smoothness of Taxable Income

Francis et al. (2004) argue that earnings smoothness is a combination of a firms innate

characteristics and managersdiscretionary reporting and implementation choices. Similar to

financial accounting, we expect that the smoothness of a firms taxable income is also a function

of innate firm characteristics and managers tax reporting choices. Indeed, Graham and Smith

(1999) find that approximately 50 percent of the firms in their sample face a convex tax function,


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which suggests that some managers have incentives to proactively smooth taxable income while

other firms likely exhibit smooth taxable income due to innate characteristics.

Although a detailed examination of how firms intentionally smooth taxable income is

beyond the scope of this study, prior research suggests that managers intentionally smooth

taxable income by shifting income across tax years and through the use of financial instruments

such as options swaps and other derivatives (Graham and Smith 1999;Nance et al. 1993).

Anecdotal evidence also suggests that managers have the ability to manipulate the timing of

income and expense items. Hanway and Vance (2010)detail tax strategies to accelerate taxable

income, including filing changes in accounting method for revenue recognition, capitalization

rules, and recurring deductions, in order to obtain tax benefits from expiring net operating losses

(NOLs) or tax credits as well as to exploit tax rate differences involving pass-through entities.

Ayers et al. (2011)note that public accounting firms offer tax planning services to strategically

structure transactions and identify favorable accounting methods that will result in the deferral of

taxable income. Thus, in addition to smoothness related to innate firm characteristics, managers

have tools at their disposal to intentionally smooth taxable income.

Hypothesis Development

In the context of tax shelters, Hanlon and Slemrod (2009)note that firms engage in tax

planning strategies to minimize tax payments net of the associated costs. Although we do not

specifically examine firms decision to invest in a tax shelter, we expect that firms evaluate a

potential tax strategy based on the net present value of the expected future benefit of the tax

strategy relative to the net present value of the tax strategys expected costs (including both

current period costs as well as future penalties). Accordingly, the predictability of taxable

income plays a significant role in firms tax planning process because forecasting the future tax


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benefits requires estimates of future taxable income as well as marginal tax rates (Dhaliwal et al.

1994; Francis and Reiter 1987;Shevlin 1990). Indeed, Scholes et al. (2008, 203) note that

uncertainty about future pre-tax cash flows limits firms tax planning opportunities. Anecdotal

evidence suggests firms are aware of both the smoothness of their taxable income and its effects

on tax avoidance outcomes. For example, Amazon.coms 2010 10-K states Our effective tax

rate is subject to significant variation due to several factors, including variability in accurately

predicting our taxable income. In addition, Dow Chemicals 2004 annual report suggests that a

recent merger will ensure a more predictable taxable income stream and allow Dow Chemical

to lower its annual effective tax rate (ETR).

In addition, smooth taxable income reduces the uncertainty associated with estimating

future marginal tax rates (Graham 1996;Shevlin 1990). Significant variation in the expected

marginal tax rate likely discourages investment in new tax avoidance strategies because it

increases the risk that firms marginal tax rates will be lower than expected, which lowers future

tax benefits, and reduces the net present value of potential tax avoidance strategies. Prior

research argues that the benefits of tax planning activities in the current period are often realized

over multiple periods in the future (Dyreng et al. 2008; Hanlon and Slemrod 2009). Thus, we

expect that firms with smoother taxable income will exhibit higher levels of tax avoidance in

future periods because smoothness allows managers to invest in tax planning activities with the

highest net present value of tax savings. Accordingly, our first hypothesis is as follows:

H1: Smoother of taxable income is associated with higher levels of future tax

avoidance (i.e., more favorable tax outcomes)

Although the purpose of financial accounting income is to convey information to

shareholders (Dechow 1994), taxable income is calculated according to the Internal Revenue


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Code to determine the tax liability of the firm and facilitate government collection of revenue

(Scholes et al. 2001). Lev and Nissim (2004) predict that taxable income and financial statement

income both contain unique information to the extent that each measure experiences different

performance shocks as well as differences in the managed component of each income measure.

Consistent with this expectation, prior research provides compelling evidence suggesting that

taxable income contains information about firm performance.

Shevlin (2002)and Hanlon et al. (2005) find that estimated taxable income has

incremental explanatory power relative to book income when explaining firms annual stock

returns. Ayers et al. (2009) examine the relative information content of taxable income and find

that, relative to financial accounting income, taxable income is relatively less informative when

firms engage in high levels of tax avoidanceand relatively more informative when firms

financial statement income is of low quality. In addition, Lev and Nissim (2004) and Hanlon

(2005) provide evidence that suggests that the difference between financial statement income and

taxable income is related to earnings growth, future stock returns, and earnings persistence,

which suggests that taxable income is a useful performance metric. Accordingly, we examine

whether the smoothness of taxable income influences its information content.

At the outset, it is not clear whether smoothness is associated with the information

content of taxable income. In a financial reporting context, prior research finds that smoothness

increases the informativeness of book income. Dichev and Tang (2009) find that smoother

earnings are better able to predict future earnings and are more persistent than firms with more

volatile earnings. In addition, Tucker and Zarowin (2006) find that share prices of firms with

smooth earnings impound more information about next periods earnings than firms with volatile

income. To the extent that prior evidence on smooth financial statement income generalizes to


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taxable income, smooth taxable income likely provides a more accurate expectation of the firms

future performance, which suggests that the information content of taxable income is higher for

firms with smoother taxable income. However, as discussed above, Lev and Nissim (2004)

predict that taxable income contains unique information because it experiences different

performance shocks relative to financial accounting income. To the extent that firms with

smoother taxable income do not experience unique economic shocks or the economic shocks are

significantly dampened, we expect that smoother taxable income potentially contains less

information than volatile taxable income. In combination, prior research in financial reporting

suggests that the smoothness of taxable income likely influences its information content.

On the other hand, unlike financial reporting income, the primary purpose of taxable

income is to serve as a basis for revenue collection by government agencies, not to convey

information to shareholders (Hanlon et al. 2005; Hanlon and Maydew 2009). Hanlon et al.

(2005) demonstrate that, while taxable income contains useful information, shareholders

primarily rely on book income to assess performance. Because the purpose of taxable income is

not to provide information to shareholders, it seems less likely that the smoothness of taxable

income would influence its information content. Accordingly, we test the following null

hypothesis:

H2: Smoothness is not associated with the information content of taxable income.

III. Research Design

Proxies for Smoothness of Taxable Income

Consistent with prior research, we assume that firms with smoother earnings exhibit

lower earnings volatility (Barth et al. 2008;Leuz et al. 2003). We estimate two separate

measures of smoothness, TAXSMOOTHand SMOOTH RATIO. First, we measure the


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smoothness of firmstaxable income (TAXSMOOTH) by calculating the standard deviation of

taxable income, deflated by total assets (AT), from year t-4to year t. Consistent with prior

research (Ayers et al. 2009; Hanlon et al. 2005), we calculate taxable income as the sum of

current federal tax expense (TXFED) and current foreign tax expense (TXFO) divided by the top

statutory tax rate (35%) less the change in net operating loss carryforwards (TLCF).2If either

current federal tax expense or current foreign tax expense is missing, we measure tax expense as

the difference between total income tax expense (TXT) and deferred tax expense (TXDI) (Ayers

et al. 2009; Hanlon et al. 2005).

Our second measure, SMOOTH RATIO, is the ratio of the standard deviation of taxable

income to the standard deviation of pre-tax cash flows (PTCF). Like financial statement income,

taxable income has both an accrual component and a cash flow component. Accordingly,

SMOOTH RATIO is designed to capture the extent to which accruals smooth income (Francis et

al. 2004; Leuz et al. 2003).3We calculate pretax cash flows as cash flows from operations

(OANCF) plus cash taxes paid (TXPD), scaled by total assets (AT). Consistent with prior

research (e.g., Francis et al. 2004), we rank both TAXSMOOTHand SMOOTH RATIOinto

deciles and multiple by negative one so that higher values greater smoothness of taxable income.

Proxies for Tax Avoidance

Prior research defines tax avoidance as any strategy that reduces a firms tax liability

(Dyreng et al. 2008). Consistent with Hanlon and Heitzman (2010), we view tax avoidance as a

continuum that ranges from clearly legal activities (e.g., investments in municipal bonds) to

those of questionable legality (e.g., tax shelters). The tax avoidance literature has developed a

wide variety of proxies for tax avoidance that capture tax avoidance at different points along the

2Unless otherwise noted, all data items are from Compustat and measured on an annual basis. 3We do not intend to capture the smoothing of our estimates of taxable income associated with GAAP tax accounts,

such as the valuation allowance.


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continuum (Hanlon and Heitzman 2010). Because we are interested in measuring tax outcomes

across the entire continuum of activities, we estimate two broad proxies of tax avoidance.

The current effective tax rate, CURETR, is our first measure of tax avoidance. Following

Ayers et al. (2009), we measure CURETRover a five year period and define CURETR as the

sum of current tax expense (TXC) over the five-year period from t+1 to t+5 scaled by the sum of

pre-tax book income (PI) less special items (SPI) over the same time period. We measure

CURETRover year t+1 to year t+5because we are interested in the influence of smoothing

taxable income on future tax outcomes. CURETRis a commonly used measure of a firms tax

burden (e.g., Ayers et al. 2009, 2010; Dyreng et al. 2011). However, CURETRdoes have

limitations. For example, changes in valuation allowances and changes in tax contingency

reserves both affect current tax expense (Dyreng et al. 2008). Thus, CURETRis the product of

both tax avoidance activities and the management of tax accruals. In addition, CURETR excludes

the benefit of stock options and thus, overstates current tax expense for firms with stock option

deductions. Consistent with Ayers et al. (2009), lower values of CURETRreflect favorable tax

outcomes in the future (i.e., an increased level of future tax avoidance).

The cash effective tax rate, CASHETR, is our second measure of tax avoidance.

Following Dyreng et al. (2008), CASHETRis defined as the sum of cash taxes paid (TXPD) from

year t+1 to year t+5 divided by the sum of pre-tax book income (PI) less special items (SPI)

over the same period of time. CASHETRreflects the assumption that managers view effective tax

planning as the ability to minimize cash taxes paid over an extended period (Dyreng et al. 2008).

Unlike CURETR, CASHETRis not affected by changes in tax accounting accruals and reflects

the tax benefits of stock options (Dyreng et al. 2008). Thus, CASHETRreflects any activity that

reduces cash taxes paid in a given period, many of which may not affect net income (Dyreng et


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al. 2008). Following Dyreng et al. (2008), lower values of CASHETRrepresent more favorable

future tax outcomes (i.e., higher levels of tax avoidance in the future).4

Test of the Association between Smoothness and Tax Avoidance (H1)

To examine the association between the smoothness of taxable income and tax

avoidance, we estimate the following OLS regression:

(1)

where all variables are defined in the Appendix and discussed below. The dependent variable

(TAXOUTCOME) is one of our two proxies for tax avoidance discussed above. Our variable of

interest (SMOOTH) represents one of our two proxies for the smoothness of taxable income

(TAXSMOOTH or SMOOTH RATIO). We estimate equation (1) for each combination of the tax

avoidance and taxable income smoothness proxies. To test our first hypothesis, we examine the

coefficient on SMOOTH (1). Our first hypothesis predicts that smoother taxable income is

associated with higher levels of future tax avoidance (i.e., more favorable future tax outcomes).

Accordingly, we expect a negative and significant coefficient on SMOOTH.

In addition to our variable of interest, we also control for factors that prior research

suggests are associated with tax avoidance to examine whether SMOOTH incrementally

contributes to firms future tax outcomes.5We control for the smoothness of financial accounting

income to account for the possibility that the smoothness of taxable income is a by-product of the

smoothness of financial income.6Specifically,BOOKSMOOTHis one of our two measures of

4Consistent with Dyreng et al. (2008), we winsorize (reset) CURETR and CASHETR to be between zero and one.5We tabulate and discuss the results of using contemporaneous values of the control variables. Results are

inferentially similar when using the five-year average of the control variables.6As discussed in Section 7, we also control for the volatility of pre-tax cash flows and our inferences remain the

same.


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pretax income smoothness. In models where TAXSMOOTH(SMOOTH RATIO) is the variable of

interest, we usePISMOOTH (PI SMOOTH RATIO). We definePISMOOTHas the standard

deviation of pretax income (PI) over the previous five years, analogous to TAXSMOOTH.PI

SMOOTH RATIOis the ratio of the standard deviation of pretax income to the standard deviation

of pretax cash flows over the prior five years and is similar to the financial income smoothness

measure employed in Francis et al. (2004). As with our taxable income smoothness measures, we

rank pretax smoothness measures into quintiles and multiply by negative one for ease of

interpretation.

We also control for leverage (LEV), firm size (SIZE), income from foreign operations

(FORINC), capital intensity (CAPINT), research and development activities (R&D), and growth

opportunities (MTB), because prior research suggests that economies of scale and firm

complexity influence tax avoidance (Chen et al. 2010;Mills et al. 1998; Rego 2003). In addition,

we control for firm profitability (ROA) and net operating loss carryforwards (NOL andNOL) to

proxy for a firmsneed to pursue tax avoidance activities (Rego 2003; Chen et al. 2010). Finally,

we include industry fixed effects to control for the cyclicality of different industries which might

influence the smoothness of firmstaxable income as well as because prior research documents

that tax avoidance varies by industry (Dyreng et al. 2008).

Test of the Association between Smoothness and the Information Content of Taxable Income

(H2)

To examine the association between the smoothness of taxable income and the

information content of taxable income, we follow Tucker and Zarowin (2006) and estimate the

following OLS regression:

(2)


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where all variable are defined in the Appendix and discussed below. Our dependent variable

(RET) is firms 16-month market-adjusted buy-and-hold returns. Consistent with Ayers et al.

(2009), we measure returns from the start of the fiscal year until four months following the end

of the fiscal year to allow earnings to be announced.

To proxy for earnings surprises, we follow Hanlon et al. (2005) and Ayers et al. (2009)

and use the change in taxable income (TI) and the change in book income (PTBI) scaled by

firmslagged market value of equity. Our first-differences approach assumes that earnings

surprises follow a random-walk (Thomas and Zhang 2010)and that shareholders use the

previous years level of book and taxable income in forming their expectations for book income

and taxable income in the current year. The coefficient onTIrepresents the earnings response

coefficient for taxable income, holding constant the level of taxable income and book income

smoothing. To examine the influence of smoothness on the information content of taxable

income, we analyze the coefficient onTI*SMOOTH. To the extent that smoothness increases

the information content of taxable income, we expect a positive and significant coefficient on

TI*SMOOTH. However, to the extent that smoothness distorts the information in taxable

income, we expect a negative and significant coefficient onTI*SMOOTH.

In addition to our variable of interest, we also control for the change in pre-tax book

income (PTBI) to examine whether taxable income provides information that is incremental to

book income. We includePTBI*BOOKSMOOTHto control for the influence of book income

smoothness on the information content of book income. We expect a positive and significant

coefficient onPTBI*BOOKSMOOTHbecause prior research finds that the smoothness of book

income increases its information content (Tucker and Zarowin 2006). Finally, we interact


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BOOKSMOOTHwith TI to account for the possibility that the smoothness of taxable income is

a by-product of the smoothness of financial income.

IV. Sample Selection and Descriptive Statistics

Our primary sample consists of the intersection of the Compustat database and the Center

for Research in Security Prices (CRSP) monthly stock returns for fiscal years 1993 to 2009. We

begin our sample in 1993 because it is the year that the current financial accounting rules for

income taxes (ASC 740) became effective. We limit our sample to firms incorporated in the

United States and exclude financial institutions (SIC codes 60006999) and public utilities (SIC

codes 49004999) because these firms have different tax and regulatory environments relative

to the remaining Compustat population. In addition, we require that firm-year observations have

sufficient data to allow us to estimate our measures of smoothing described above. We also

require that firm-year observations have sixteen consecutive monthly returns from CRSP to

calculate the dependent variable in equation (2). Finally, consistent with Hanlon et al. (2005) and

Ayers et al. (2009), we eliminate observations that have absolute changes in taxable income or

pretax book income (scaled by market value of equity) in excess of one to avoid the influence of

extreme outliers.

Because the test of our first hypothesis requires measures of future tax outcomes, we

limit the sample used to test our first hypothesis to firm-year observations whose aggregate pre-

tax book income from year t+1 to year t+5 is positive (i.e., we require the sum of pre-tax book

income from year t+1 to year t+5 to be positive). The final sample used to estimate equation (1)

varies based on the availability of each proxy of future tax outcomes. Specifically, the sample

used to estimate equation (1) contains 15,472 (15,108) firm-year observations when CURETR

(CASHETR)serves as our proxy future tax outcomes. To test our second hypothesis, we relax the


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requirements of our samples for our first hypothesis and require firm-year observations to have

sufficient data to estimate equation (2). The final sample used to estimate equation (2) contains

40,185 firm-year observations.7

Table 1 reports the descriptive statistics for all variables used in equations (1) and (2). To

examine whether taxable income exhibits different levels of smoothness relative to financial

accounting income, we compare the smoothness of taxable income to the smoothness of financial

accounting income. We find that TAXSMOOTH is significantly smaller thanPISMOOTH while

SMOOTH RATIO is significantly larger thanPI SMOOTH RATIO (untabulated, all p < 0.01),

which suggests that taxable income is smoother than financial accounting income.

8

In addition,

the means and medians of our tax avoidance measures, CURETR and CASHETR, are consistent

with prior research. Specifically, the mean (median) of CURETR is 0.308 (0.316) while the mean

(median) of CASHETR is 0.297 (0.290). Consistent with Dyreng et al. (2008), CASHETRis

significantly lower than CURETR. In untabulated analysis, we do not find a significant

difference in the changes in taxable income,TI, and the changes in pretax income,PTBI, (p =

0.28). Finally, the descriptive statistics of the control variables are similar to prior studies.

V. Multivariate Results

Results of Tax Avoidance Analysis (H1)

Table 2 presents the results of the tests of our first hypothesis. In all specifications, we

cluster standard errors by firm and year (Gow et al. 2010;Petersen 2009). The coefficients on

7

Our tests of H1 are not sensitive to including firm-year observations that are missing returns data from CRSP.Likewise, our tests of H2 are not sensitive to restricting the sample used to test H2 to firm-year observations with the

data necessary to calculate our proxies of future tax avoidance.8To examine the overlap between firms that smooth financial reporting income and firms that smooth taxable

income, we designate firms that are below the median of our measures of smoothing tax (financial) income as those

smoothing income. In untabulated analysis, we find that approximately 38 percent of the firms that smooth their

financial accounting income also smooth their taxable income. This result suggests that our estimates of taxable

income smoothing capture a unique construct that is separate from the smoothing of financial accounting income.

Moreover, in robustness tests described in Section 7, we employ measures of taxable income smoothness that are

orthogonal to book income smoothness and our inferences remain the same.


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industry fixed effects are not reported for the sake of brevity. As described above, lower values

of CURETR and CASHETR represent higher levels of tax avoidance.

Columns (1) and (2) present the results for our first measure of smoothing,

TAXSMOOTH, while columns (3) and (4) tabulate the results for our second smoothing measure,

SMOOTH RATIO. Consistent with the smoothness of taxable income aiding firms tax avoidance

activities, we find a negative and significant coefficient on TAXSMOOTH (p < 0.01) and

SMOOTH RATIO (p < 0.01) when CURETR serves as the proxy for future tax outcomes.

Likewise, the coefficients on both TAXSMOOTH andSMOOTH RATIO are negative and

significant (p < 0.01) when CASHETRproxies for future tax outcomes.

Our results suggest that the influence of the smoothness of taxable income on tax

avoidance is economically significant. Specifically, a one-decile increase in the smoothness of a

firms taxable income, on average, decreases CURETRby 0.9% (1.0%) and CASHETRby 0.7%

(0.8%). In combination, our findings suggest that the smoothness of taxable income reduces the

uncertainty associated with future tax outcomes and allows firms to develop more successful tax

avoidance strategies. The coefficients on our control variables are broadly consistent with prior

research.

Results of Information Content Analysis (H2)

Table 3 presents the results of testing the information content of taxable income. In all

specifications, we cluster standard errors by firm and year (Gow et al. 2010; Peterson 2009).

Column (1) presents our replication of prior research (Ayers et al. 2009; Hanlon et al. 2005).

Consistent with prior research, we find that both taxable income and financial accounting income

contain unique information, but that investors rely more on financial accounting income.

Columns (2) and (3) examine whether the smoothness of taxable income influence its


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information content. Specifically, Column (2) presents our model estimates using TAXSMOOTH

while column (3)usesSMOOTH RATIO. To test our second hypothesis we examine the

coefficients onTI*SMOOTH.We find a negative and significant coefficient on

TI*TAXSMOOTH (p < 0.01) in column (2) andTI*SMOOTH RATIO (p < 0.10) in column

(3), which suggests that the information content of taxable income is lower when firms have

smoother taxable income. This result is consistent with the notion that firms with smoother

taxable income either do not experience unique tax-related economic shocks or the economic

shocks are significantly dampened.

In addition, we also examine the influence of book income smoothing on the information

content of book income by examining the coefficients onPTBI*PISMOOTHandPTBI*PI

SMOOTH RATIO.Consistent with prior research (e.g., Tucker and Zarowin 2006), we find

positive and significant coefficients onPTBI*PISMOOTH (p < 0.01) in column (2) and

PTBI*PI SMOOTH RATIO(p < 0.01) in column (3). This suggests that the smoothness of book

income increases the information content of book income. We find no evidence that the

smoothness of book income increases the information content of taxable income as the

coefficients onTI*PISMOOTHandTI*PI SMOOTH RATIOare insignificant. In combination,

our results are consistent with prior research (e.g., Tucker and Zarowin 2006), that suggests the

smoothness of firmsbook income conveys additional information. In contrast, we find that the

smoothness of taxable income reduces the information content of taxable income.

VI. Additional Analysis

Like financial accounting income, we expect that the smoothness of taxable income is

likely composed of innate and discretionary components (Francis et al. 2004). Accordingly, we

investigate the influence of innate smoothness and discretionary smoothness on tax avoidance


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and the information content of taxable income. Specifically, we follow Francis et al. (2004) and

decompose our SMOOTHmeasures into their innate and discretionary components using

equation (3). For each year, we regress each SMOOTHmeasure on seven innate factors which

the literature has previously determined to influence accounting systems (Francis et al. 2004;

Dechow and Dichev 2002).9

(3)

We use the fitted value of equation (3) to measure the innate component of the

smoothness of taxable income (INNATE SMOOTH) and the residual () as a measure of

discretionary taxable income smoothness (DISCRET SMOOTH). CAPINTis the firms capital

intensity, measured as the ratio of capital expenditures (CAPX) to net property, plant, and

equipment (PPENT). To measure intangible intensity, we includeINTAN INT, the ratio of

intangible assets (XRD + XAD) to sales (SALE), and an indicator variable for firms with zero or

missing intangible values (DUM INTAN). We also control for the number of tax losses over the

prior five years withNEGTI, which is the percentage of years with negative taxable income over

the prior five years. OPCYLCEis the natural log of a firms operating cycle, measured as the

sum of a firms days accounts receivable (RECT/SALE) and days inventory (INVT/COGS).

Sizeis the natural log of total assets (AT). SALES VOL is the standard deviation of sales (SALE),

scaled by total assets (AT), over the prior five years.

9Francis et al. (2004) include the standard deviation of cash flows as an innate characteristic of the smoothness of

earnings. We omit the standard deviation of pre-tax operating cash flows in order to avoid a potential mechanical

association with SMOOTH RATIO. While we tabulate and discuss results using a model without the standard

deviation of cash flows, all results remain the same when we include the standard deviation of cash flows in

equation (3).


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Results of Innate and Discretionary Smoothness

We present the results of our first-stage regression of innate and discretionary smoothness

in Table 4. Equation (3) is estimated annually; we therefore present average coefficients andp-

values calculated with the Fama-MacBeth (1973)methodology. Our results are broadly

consistent with Francis et al. (2004) with two notable exceptions. First, we find that intangible

intensity is positively related to SMOOTH RATIOwhereas Francis et al. (2004) find a negative

association between intangibles and the smoothness of book income. Second, we find that size is

negatively related to SMOOTH RATIOwhereas Francis et al. (2004) find a positive association

between size and the smoothness of book income.

Table 5, Panel A presents our results of estimating equation (1) with the innate and

discretionary components of taxable income smoothness. The dependent variable in odd-

numbered (even-numbered) columns is CURETR(CASHETR). We find a negative and

significant relation between discretionary smoothness and the level of firms future tax

avoidance for both TAXSMOOTH and SMOOTH RATIOmeasures (all p < 0.01). These results

are consistent with prior research that argues that some firms take deliberate actions to smooth

their taxable income in order to facilitate higher levels of future tax avoidance (Graham and

Smith 1999; Lev and Nissim 2004). We find inconsistent results with the innate component of

taxable income smoothness. Specifically, we find positive and significant coefficients for

INNATE TAX SMOOTH(all p < 0.05) but negative and significant coefficients forINNATE

SMOOTH RATIO (all p < 0.01). Because SMOOTH RATIO is designed to capture the extent to

which accruals smooth income (Francis et al. 2004; Leuz et al. 2003), the differences in results

across our measures of innate smoothness suggests that the smoothness of a firms tax accruals

likely plays a significant role in firms tax avoidance activities.


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Table 5, Panel B presents the results of our analysis of the influence of innate and

discretionary smoothness on the information content of taxable income. We find that the

coefficients on TI*INNATE TAX SMOOTHand TI*INNATE SMOOTH RATIOare not

statistically significant, which suggests that the innate smoothness of taxable income does not

influence its information content. However, we find negative and significant coefficients on

TI*DISCRET TAX SMOOTHand TI*DISCRET SMOOTH RATIO(both p < 0.01) which

suggests that discretionary smoothness reduces the information content of taxable income.

Combined, our results suggest that intentional (i.e., discretionary) actions taken by managers to

smooth taxable income facilitates future tax avoidance, but also garbles the information

contained in taxable income.

VII. Robustness Tests

Alternate Measures of Taxable Income Smoothing

We test the robustness of our findings to two different measures of the smoothness of

taxable income. Because our estimate of taxable income is based on financial statement

disclosures, prior research suggests that TAXSMOOTHand SMOOTH RATIOpotentially suffer

from measurement error (Hanlon 2003; McGill and Outslay 2004).10

Therefore, we use a second

measure of the smoothing (CASHTAXSMOOTH)that is based on cash taxes paid. Cash taxes

paid are not influenced by tax-related financial accounting accruals and properly reflect the

effect of stock option expense deductions on a firms tax liability (Dyreng et al. 2008). We

define CASHTAXSMOOTHas the standard deviation of a firms cash taxes paid (TXPD) scaled

by assets (AT) from years t-4to year t. Similar to TAXSMOOTH, we rank CASHTAXSMOOTH

10Hanlon (2003) and McGill and Outslay (2004)suggest that the use of financial statement data to estimate taxable

income and tax payments is problematic. Briefly, the problems stem from differences in financial accounting and tax

accounting related reserves for uncertain tax positions, intraperiod tax allocation, consolidation, employee stock

option exercises, tax credits, and foreign operations (Hanlon 2003).


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into deciles and multiply by negative one. Our second smoothness measure, SMOCOR, is the

correlation between tax accruals (TIPTCF) and pretax cash flows (PTCF) over the previous

five years, multiplied by negative one such that higher values indicate a greater level of

smoothness. SMOCOR is analogous to the smoothness measure used in Tucker and Zarowin

(2006).

To examine whether our results are robust to alternative measures of the smoothness of

taxable income, we re-estimate equation (1) and regress future tax avoidance on decile-ranks of

CASHTAXSMOOTH and SMOCOR. In untabulated analysis, we continue to find significant and

negative coefficients for both measures of the smoothness of taxable income when CURETR

serves as the proxy for future tax avoidance outcomes (all p < 0.05) and when CASHETRis our

proxy for tax avoidance (all p < 0.05).

We also examine whether our results on the information content of taxable income are

robust to alternative measures of smoothness. In untabulated analysis, we find a negative and

significant coefficient on the interaction of TIwith CASHTAXSMOOTH (p < 0.01). However,

the coefficient on TI*SMOCOR is not significant. Overall, our results are generally robust to

alternative measures of smoothness.

Measurement Error in Taxable Income

Because we estimate taxable income based on financial statements, it is subject to a

number of limitations, arising from net operating losses, tax credits, and foreign earnings

(Hanlon 2003). We attempt to minimize the likelihood that our results are due to measurement

error by re-estimating equations (1) and (2) over various subsamples where measurement error is

likely to be less.


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First, The US Internal Revenue Code allows for firms to carry their losses into future

periods and reduce taxable income. Because our measure of taxable income includes the change

in tax loss carryforwards, our measure of the smoothness of firms taxable incomemight be

detecting the smoothing of tax loss carry forwards and would therefore be mechanically related

to ETRs. To accommodate this alternative explanation, we remove all observations where firms

experience any pre-tax loss between year t- 4and year t, reducing the likelihood that results are

driven by tax losses from prior years shielding future period income from taxation. In

untabulated analysis, we continue to find the coefficients on TAXSMOOTH and SMOOTH

RATIO are significantly negative (p < 0.01). We continue to confirm H1 and find that taxable

income smoothing is positively and significantly associated with favorable tax avoidance

outcomes in future periods. Also, in untabulated analysis, we continue to find that smoothing

taxable income smoothing reduces the information content of taxable income (p < 0.01).

Second, research and development expenditures can qualify for tax credits, lowering our

estimate of taxable income as well as our tax avoidance measures. Research and development

also impacts the value relevance of earnings (Lev and Sougiannis 1996). Therefore, we remove

firms with positive research and development expenses (XRD > 0) from our sample. We

continue to find that the smoothness of taxable income is significantly and positively related to

future tax avoidance outcomes for both TAXSMOOTH and SMOOTH RATIO(p < 0.05). Also

consistent with our prior findings, TAXSMOOTHis negatively and significantly related to the

information content of taxable income (p < 0.01). However, the interaction between SMOOTH

RATIOand TIis insignificant in this subsample.

Third, foreign earnings can qualify for foreign tax credits as well as be subject to

different statutory tax rates in foreign jurisdictions. Foreign earnings influence returns differently


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than domestic earnings (Thomas 1999). Therefore, we remove firms from our sample that report

a non-missing foreign tax expense (TXFOR) or have non-missing foreign pretax income

(PIFOR). We continue to confirm H1 and find that the smoothness of taxable income is

significantly and positively related to future tax avoidance using both our smoothness measures

(p < 0.01). Also, we continue to find the smoothness of taxable income significantly decreases its

information content (p < 0.10).

Finally, Guenther et al. (2012)find that the results in Hanlon et al. (2005) are driven by

the combination of profit firms and loss firms in the same sample. After removing loss firms

from their sample, Guenther et al. (2012) do not find a significant association between changes

in taxable income (i.e., current tax expense that is not grossed up by the statutory tax rate) and

contemporaneous stock returns. To examine whether our results are subject to similar concerns,

we limit our sample to firms with positive pre-tax book income in the current year. Our

inferences remain the same and we continue to find that smoothing reduces the information

content of taxable income.

Additional Controls for the Smoothness of Pretax Income

While our primary analyses include the smoothness of pretax income in all model

specifications, there remains the possibility that the smoothness of taxable income is a function

of the smoothness of pretax income. We further verify that our findings are not a function of the

smoothness of pretax income by orthogonalizing TAXSMOOTHand SMOOTH RATIOon our

measures of pretax income smoothness. We regress TAXSMOOTH onPISMOOTHand

SMOOTH RATIOonPI SMOOTH RATIOand use the residuals (RESSMO andRESSR,

respectively) as our measures of the smoothness of taxable income. UsingRESSMOandRESSR,

we continue to find a negative and significant association between the smoothness of taxable


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income and future CURETR and CASHETR(p < 0.01). Consist with our primary analysis, we

find negative and significant interactions between TIandRESSMOandRESSR (p < 0.01),

suggesting that the smoothness of taxable income decreases the information content of taxable

income.

Additional Controls for the Smoothness of Pretax Cash Flows

While we do not include the smoothness of pretax cash flows in our primary analysis in

order to avoid a potential mechanical association between SMOOTH RATIOand the smoothness

of pretax cash flows, we do include the smoothness of pretax cash flows (CFSMOOTH) as a

robustness test. In untabulated analysis, we continue to find negative and significant relations

between both of the smoothness measures, TAXSMOOTH and SMOOTH RATIO, and both tax

avoidance measures, CURETRand CASHETR(p < 0.01). Also in untabulated analysis, we

interact the change in taxable income with CFSMOOTHin our information content tests to

determine if our prior results are a function of the smoothness of cash flows, rather than taxable

income. Inferences remain the same (p < 0.05).

Tax Avoidance and the Information Content of Taxable Income

Ayers et al. (2009) find that tax avoidance decreases the relative and incremental

information content of a firms taxable income.11

Given that we find the smoothness of taxable

income is significantly and positively related to future tax avoidance, our results for equation (2)

might be an artifact of tax avoidance and not the smoothness of taxable income. We test the

robustness of our results by reexamining how the information content of taxable income varies

across levels of tax avoidance.

11We are able to replicate Ayers et al.s (2009) findings in our sample. We confirm that the taxable income of firms

in the bottom quintile of CURETRand CASHETRhave significantly lower relative and incremental information

content when compared to all other firms.


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We rank firms into quintiles by industry and year based on CURETR.12

Consistent with

Ayers et al. (2009), we consider firms in the bottom two deciles of their industry-year to be

engaging in a high level of tax avoidance. We then estimate equation (2) with an indicator

variable for firms with a high level of tax avoidance (TA)and interact this indicator variable with

the change in taxable income (TI*TA). If tax avoidance is a correlated, omitted variable, then

the coefficients onTI*TAXSMOOTH andTI*SMOOTH RATIOwill be insignificant and only

the interaction between the change in taxable and TAwill be significantly negative. If, on the

other hand, the effect that the smoothness of taxable income has on the information content of

taxable income is incremental to the effect of tax avoidance, we expect to find significant and

negative coefficients onTI*TAXSMOOTH andTI*SMOOTH RATIO.

In untabulated results, we confirm the findings of Ayers et al. (2009). We find a negative

and significant coefficient (p < 0.01) for (TI*TA), consistent with tax avoidance impairing the

information content of taxable income. We also find a negative and significant coefficient on

TI*TAXSMOOTH (p < 0.01) and an insignificant coefficient onTI*SMOOTH RATIO.

Overall, our results are consistent with our smoothness results being distinct from and

incremental to the tax avoidance effect documented in Ayers et al. (2009).

VIII. Conclusion

Prior research finds that firms smooth their book income in order to obtain future benefits

such as beating earnings benchmarks (Myers et al. 2007), decreasing underinvestment (Barton

2001), and lowering their costs of capital (Francis et al. 2004). However, prior research also

suggests that firms have incentives to smooth their taxable income (Graham and Smith 1999;

Lev and Nissim 2004). In this paper, we examine whether the smoothness of taxable income is

12For purposes of this test, CURETRis calculated using information from year t-5to year t-1, consistent with Ayers

et al. (2009). Inferences remain the same if we define a high level of tax avoidance with CASHETR.


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related to tax avoidance in future periods (i.e. future tax outcomes) as well as the impact that the

smoothness of taxable income has on the information content of taxable income.

Using a sample of firm-year observations from 1993 to 2009, we find that firms with

smoother taxable income have more favorable outcomes of their future tax avoidance activities

(i.e., exhibit higher levels of future tax avoidance), which is consistent with smoother taxable

income reducing the uncertainty associated with future tax benefits and allowing firms to

develop more successful tax avoidance strategies. We also find that smoother taxable income is

less informative relative to volatile taxable income. This result is consistent with the smoothness

of taxable income either eliminating or reducing the information contained in the unique

economic shocks experienced by taxable income.

In supplemental analysis, we decompose the smoothness of taxable income into its innate

and discretionary components. We find that discretionary smoothness is associated with higher

levels of future tax avoidance. However, we also find that discretionary smoothness reduces the

information content of taxable income. Collectively, these results suggest that intentional (i.e.,

discretionary) actions taken by managers to smooth taxable income facilitates future tax

avoidance, but also garbles the information contained in taxable income.

This study contributes to several areas of accounting research. First, we contribute to the

literature that investigates the determinants of firms tax avoidance activities. Prior research has

examined firm-level characteristics (Frank et al. 2009;Lisowsky 2010;Wilson 2009),

managerial incentives (Rego and Wilson 2012; Robinson et al. 2010), and ownership structure

(Chen et al. 2010;McGuire et al. 2011)as determinants of tax avoidance. We extend this line of

research by providing evidence consistent with the notion that the smoothness of firms taxable

income facilitates tax avoidance. Second, we contribute to the emerging literature that examines


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firms incentives to smooth taxable income (Boynton et al. 1992;Graham and Smith 1999;

Scholes et al. 1992). We extend this line of research by investigating the consequences of having

smooth taxable income, specifically the influence of smoothing on future tax avoidance

outcomes.

We also contribute to the literature on the information content of taxable income. Prior

research finds that taxable income contains information incremental to book income about a

firms performance(Ayers et al. 2009; Hanlon et al. 2005). Graham et al. (2012) note that there

is limited evidence outside of Ayers et al. (2009) and Hanlon et al. (2005) on whether taxable

income is priced and call for more research that investigates what information is contained in

taxable income and what the market is pricing. We answer this call for research more broadly by

providing evidence that the smoothness of taxable income reduces its information content.


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Appendix: Variable Definitions

Dependent Variables

CURETR The five-year current effective tax rate from Ayers et al. (2009). We

accumulate a firms current tax expense (TXC) from the period t+1to t+5

and scale by pretax income net of special items over the same period (PI -

SPI)

We require both the numerator and the denominator to be positive and

then winsorize at 0 and 1.

CASHETR The five-year cash effective tax rate from Dyreng et al. (2008). We

accumulate cash taxes paid (TXPD) over the period t+1tot+5and scale

by pretax income net of special items over the same time period (PI

SPI).

If a firm is missing its current tax (TXC) in a given year, we substitute the

difference between total tax expense (TXT) and deferred tax expense

(TXDI) for TXC. We require both the numerator and the denominator tobe positive and then winsorize at 0 and 1.

RET 16-month market-adjusted buy-and-hold returns, We measure returns from

the start of the fiscal year until four months following the end of the fiscal

year to allow earnings to be announced.

Variables of Interest

TAXSMOOTH The standard deviation of taxable income from year t-4 to year tmultiplied

by negative one. We calculate taxable income by grossing up the sum of

current federal tax expense (TXFED) and current foreign tax expense

(TXFO) by the statutory tax rate (35%) adjusted for the change in net

operating loss for the year (TLCF). If either current federal tax expense or

current foreign tax expense is missing, we follow Hanlon (2005) andcalculate taxable income by grossing up the different between total tax

expense (TXT) and deferred tax expense (TXDI). We scale taxable

income by total assets (AT).

SMOOTH RATIO The ratio of the standard deviation of the standard deviation of taxable

income to the standard deviation pretax cash flows (OANCF + TXPD),

from year t-4to year t, multiplied by negative one

TI The change in taxable income form period t-1to period t, scaled by lagged

market value of equity (PRCC_F*CSHO)

PTBI The change in pretax income (PI) less minority interest (MII) from period

t-1to period t, scaled by lagged market value of equity (PRCC_F*CSHO)

Control Variables

PISMOOTH The standard deviation of PI less MI scaled by AT over years t-4to year t,multiplied by negative one

PI SMOOTH RATIO The ratio of the standard deviation of pretax cash flows (OANCF +

TXPD) to the standard deviation of pretax income, from year t-4to year t,

multiplied by negative one

Lev The ratio of current and long term debt (DLC + DLTT) and assets (AT).

Size The natural log of total assets (AT)

MTB The ratio of a firms market value of equity (PRCC_F*CSHO) to book

value of equity (CEQ)

ROA The ratio of pretax income (PI) to total assets (AT)


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R&D The ratio of research and development expenses (XRD) to sales (SALE)

CAPINT The ratio of gross property, plant, and equipment (PPEGT) to assets (AT)

FORINC An indicator variable equaling one if a firm has a nonmissing value of

PIFO and zero otherwise.

NOL Current period net operating loss carryforward scaled by total assets

(TLCF/AT). We set missing values of TLCF equal to zero.

NOL The change in TLCF from period t-1to period t scaled by total assets (AT)

Determinants of Innate Smoothness

INTAN INT The ratio of research and development (XRD) and advertising (XAD) to

sales (SALE)

DUM INTAN An indicator variable equaling one if a firm has zero or missing XRD and

XAD and zero otherwise

NEGTI The proportion of years with negative taxable income from years t-4 to

year t

OPCYCLE The natural log of a firms operating cycle, measured as the sum of a

firms days accounts receivable (RECT/SALE) and days inventory

(INVT/COGS).

SALE VOL The standard deviation of sales (SALE), scaled by total assets (AT), over

the prior five years.


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Table 1

Descriptive Statistics

N Mean Std Dev 25th Pctl Median 75th Pctl

TAXSMOOTH 40185 -0.038 0.032 -0.051 -0.029 -0.016

SMOOTH RATIO 39428 5.629 82.041 0.980 1.530 2.712

INNATE TAXSMOOTH 39673 -0.036 0.013 -0.043 -0.033 -0.027

DISCRET TAX SMOOTH 39673 -0.002 0.030 -0.014 0.003 0.016

INNATE SMOOTH RATIO 38928 5.385 3.240 3.32 5.050 7.056DISCRET SMOOTH RATIO 38928 -1.395 11.311 -4.999 -2.903 -0.798

PISMOOTH 40185 -0.070 0.072 -0.088 -0.048 -0.026

PI SMOOTH RATIO 40185 1.459 1.442 0.698 1.087 1.716

CURETR 15472 0.308 0.162 0.230 0.316 0.376

CASHETR 15108 0.297 0.176 0.202 0.290 0.362

RET 40185 0.075 0.934 -0.358 -0.060 0.291

TI 40185 0.003 0.117 -0.030 0.003 0.037

PTBI 40185 0.003 0.132 -0.033 0.009 0.042

LEV 40185 0.209 0.179 0.033 0.192 0.336

SIZE 40185 5.818 1.878 4.442 5.737 7.106

MTB 40185 2.508 2.278 1.208 1.889 3.032ROA 40185 0.050 0.131 0.011 0.064 0.120

R&D 40185 0.039 0.083 0.000 0.000 0.039

CAPINT 40185 0.538 0.357 0.247 0.459 0.769

FORINC 40185 0.413 0.492 0.000 0.000 1.000

NOL 40185 0.058 0.214 0.000 0.000 010

NOL 40185 0.008 0.074 0.000 0.000 0.000

All continuous variables are truncated at the 1stand 99

thpercentile, except for CURETRand CASHETRwhich are winsorized at 0 and 1.


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Table 2

Influence of Smoothness on Future Tax Avoidance Outcomes

(1) (2) (3) (4)

CURETR CASHETR CURETR CASHETR

Coefficient Coefficient Coefficient CoefficientVariable

a (p-value) (p-value) (p-value) (p-value)

Constant 0.363*** 0.383*** 0.377*** 0.397***

(0.000) (0.000) (0.000) (0.000)

TAXSMOOTH -0.009*** -0.010***

(0.000) (0.000)

PISMOOTH 0.008*** 0.009***

(0.000) (0.000)

SMOOTH RATIO -0.007*** -0.008***

(0.000) (0.000)

PI SMOOTH RATIO 0.011*** 0.012***

(0.000) (0.000)

LEV -0.047*** -0.026* -0.047*** -0.027*

(0.000) (0.065) (0.000) (0.066)

SIZE -0.005*** -0.010*** -0.006*** -0.011***

(0.000) (0.000) (0.000) (0.000)

MTB -0.002** -0.007*** -0.002** -0.007***

(0.037) (0.000) (0.037) (0.000)

ROA 0.171*** 0.111*** 0.175*** 0.117***

(0.000) (0.005) (0.000) (0.002)R&D -0.015 -0.265*** -0.023 -0.270***

(0.825) (0.001) (0.739) (0.001)

CAPINT -0.028*** -0.023** -0.030*** -0.026***

(0.000) (0.012) (0.000) (0.009)

FORINC 0.005 0.001 0.004 0.000

(0.269) (0.910) (0.311) (0.982)

NOL -0.180*** -0.161*** -0.189*** -0.172***

(0.000) (0.000) (0.000) (0.000)

NOL 0.083* 0.097** 0.095** 0.111**

(0.060) (0.035) (0.029) (0.017)Observations 15,472 15,108 15,472 15,108

adj-R2 0.0771 0.0882 0.0755 0.0863*, **, *** indicates significance at the 0.10, 0.05, and 0.01 levels, respectively. We cluster standard

errors by firm and year (Petersen 2009; Gow et al. 2010). All p-values are based on two-tailed tests

unless a directional hypothesis is made.aAll variables are defined in the Appendix


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Table 3

Influence of Smoothness on the Information Content of Taxable Income

(1) (2) (3)

RET RET RETCoefficient Coefficient Coefficient

Variablea (p-value) (p-value) (p-value)

Constant 0.068 0.110 0.062

(0.158) (0.135) (0.173)

TAXSMOOTH -0.009***

(0.000)

PISMOOTH -0.001

(0.947)

SMOOTH RATIO -0.001

(0.764)PI SMOOTH RATIO 0.004

(0.719)

TI 0.642*** 1.064*** 0.737***

(0.000) (0.000) (0.000)

PTBI 1.540*** 1.183*** 1.057***

(0.000) (0.000) (0.000)

TI*TAXSMOOTH -0.103***

(0.000)

PTBI*PISMOOTH 0.134***

(0.001)

TI*PISMOOTH -0.011

(0.708)

TI*SMOOTH RATIO -0.054*

(0.064)

PTBI* PI SMOOTH RATIO 0.547***

(0.000)

TI * PI SMOOTH RATIO 0.061

(0.151)

Observations 40,185 40,185 39,428adj-R2 0.0680 0.0714 0.0732

*, **, *** indicates significance at the 0.10, 0.05, and 0.01 levels, respectively. We cluster

standard errors by firm and year (Petersen 2009; Gow et al. 2010). All p-values are based on

two-tailed tests unless a directional hypothesis is made.aAll variables are defined in the Appendix


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Table 4

First Stage: Innate and Discretionary Smoothness

(1) (2)

TAXSMOOTH SMOOTH RATIO

Coefficient CoefficientVariable (p-value) (p-value)

Intercept -0.023*** 9.258***

(0.000) (0.000)

CAPINT -0.023*** -1.799*

(0.000) (0.081)

INTAN INT -0.004 16.131***

(0.273) (0.000)

DUM INTAN 0.004*** 1.545***

(0.000) (0.000)

NEGTI -0.055*** -7.274***

(0.000) (0.000)

OPCYCLE -0.001*** 0.069

(0.000) (0.569)

SIZE 0.001*** -1.045***

(0.000) (0.000)

SALE VOL -0.017*** 7.628***

(0.000) (0.000)

Observations 63,797 59,380

Average adj-R2 0.121 0.068Number of Years 17 17

*, **, *** indicates significance at the 0.10, 0.05, and 0.01 levels, respectively. All

coefficient estimates are averages from annual regressions. P-values are based on the

standard error estimates from the annual regressions.aAll variables are defined in the Appendix


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35

Table 5

Innate and Discretionary Smoothness

Panel A (Tax Avoidance):

(1) (2) (3) (4)

CURETR CASHETR CURETR CASHETR

Coefficient Coefficient Coefficient Coefficient

Variable (p-value) (p-value) (p-value) (p-value)

Constant 0.366*** 0.385*** 0.408*** 0.426***

(0.000) (0.000) (0.000) (0.000)

INNATE TAXSMOOTH 0.004*** 0.004**

(0.007) (0.032)

DISCRET TAX SMOOTH -0.016*** -0.019***

(0.000) (0.000)PISMOOTH 0.007*** 0.007***

(0.000) (0.000)

INNATE SMOOTH RATIO -0.014*** -0.015***

(0.000) (0.000)

DISCRET SMOOTH RATIO -0.017*** -0.018***

(0.000) (0.000)

PI SMOOTH RATIO 0.007*** 0.008***

(0.000) (0.000)

CONTROLS YES YES YES YES

Observations 15,303 14,946 15,303 14,946

adj-R2 0.0821 0.0951 0.0724 0.0842*, **, *** indicates significance at the 0.10, 0.05, and 0.01 levels, respectively. We cluster standard

errors by firm and year (Petersen 2009; Gow et al. 2010). All p-values are based on two-tailed tests



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36

Table 5

Innate and Discretionary Smoothness

Panel B (Information Content):

(1) (2)RET RET

Coefficient Coefficient

Variable (p-value) (p-value)

Constant 0.118 0.030

(0.134) (0.488)

TI 1.147*** 0.879***

(0.000) (0.002)

PTBI 1.157*** 1.048***

(0.000) (0.000)

TI*INNATE TAXSMOOTH -0.059

(0.234)

TI*DISCRET TAXSMOOTH -0.200***

(0.000)

PTBI*PISMOOTH 0.140***

(0.000)

TI*PISMOOTH -0.009

(0.742)

TI*INNATE SMOOTH RATIO -0.006

(0.939)

TI*DISCRET SMOOTH RATIO -0.175***

(0.004)

PTBI*PI SMOOTH RATIO 0.540***

(0.000)

TI*PI SMOOTH RATIO 0.054

(0.226)

CONTROLS YES YES

Observations 39,673 38,928adj-R2 0.0711 0.0755

*, **, *** indicates significance at the 0.10, 0.05, and 0.01 levels,

respectively. We cluster standard errors by firm and year (Petersen

2009; Gow et al. 2010). Allp-values are based on two-tailed tests



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