Financial Constraints and the Incentive for Tax Planning

Alexander Edwards Rotman School of Management

University of Toronto alex.edwards@rotman.utoronto.ca

Casey Schwab

Terry College of Business University of Georgia

cschwab@terry.uga.edu

Terry Shevlin The Paul Merage School of Business

University of California at Irvine tshevlin@uci.edu

August 14, 2013

Keywords: Tax planning, Cash taxes, Financial constraints

JEL codes: E69, H25, H60 Data Availability: Data used in this study are available from public sources identified in the paper.

We appreciate helpful comments and suggestions from the University of Iowa Tax Readings Group, Ben Ayers, Andy Bauer, Bradley Blaylock, Andy Call, John Campbell, Anne Ehinger, Stacie Laplante, Scott Liao, Dan Lynch, Devan Mescall, Wayne Nesbitt, Gord Richardson, and Steve Utke. We also thank seminar participants at the University of Toronto, the 2013 ATA Midyear Meeting, the 2013 Deloitte Tax Policy Research Symposium, and the 2013 CAAA Craft of Accounting Research Workshop and Annual Conference. We gratefully acknowledge financial support from the Rotman School of Management, University of Toronto; the Terry College of Business, University

of Georgia; and the Paul Merage School of Business, University of California at Irvine.

Abstract

In this study, we investigate the association between financial constraints, at both the

macroeconomic and firm-specific level, and one potentially significant source of internal funds

available to firms – cash savings generated through tax planning. We predict that as financial

constraints increase, the supply of external funds decreases and the cost of external funds

increases leading firms to take actions to increase internally-generated funds via tax planning.

Measuring financial constraints based on both macroeconomic measures (change in GDP and

bank lending tightening) and firm-specific measures (the decile ranking of both the Altman Z-

score and the Whited and Wu 2006 financial constraint index), we find that firms facing financial

constraints exhibit lower cash effective tax rates. Understanding how financial constraints affect

tax avoidance and the interplay between macroeconomic forces and firm-level tax avoidance

behavior is important as legislators look for ways to reduce the federal deficit.

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1. Introduction

In this study, we examine the effect of financial constraints, measured at both the

macroeconomic-level and the firm-level, on corporate tax avoidance behavior. While

understanding the tax effects of financial constraints at the firm-level is important as researchers

attempt to explain tax avoidance behavior (see Shackelford and Shevlin 2001 and Hanlon and

Heitzman 2010 for a comprehensive review), understanding the tax effects of macroeconomic

financial constraints is potentially more important because these constraints impact all firms in

the economy simultaneously. If firms simultaneously increase tax avoidance when faced with

macroeconomic financial constraints, this behavior has the potential to magnify the effect of an

economic contraction on government revenues. Government revenues are likely to decrease due

to both a reduction in the tax base (i.e., lower taxable incomes due to the contraction) and, to a

lesser extent, an increase in corporate tax avoidance activities. As the federal deficit becomes a

key factor in the future financial health of the country, it is important to understand the interplay

between macroeconomic forces and firm-level tax avoidance behavior as legislators look for

ways to reduce the federal deficit.

We define tax avoidance broadly as all actions taken by managers to reduce their cash

income tax liability and measure avoidance using current-year worldwide cash effective tax rates

(cash ETR). Our proxies for macroeconomic financial constraints (change in gross domestic

product and change in lending standards) capture an increased cost of and/or increased difficulty

in accessing external funds. Our proxies for firm-level financial constraints (the decile rank of

the Whited-Wu financial constraint index and Altman's Z score) capture investment-related

constraints (i.e., firms constraints resulting from an inability to fund all profitable investment

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opportunities) and distress-related constraints (i.e., constraints resulting from a need to cover

short-term working cash flow obligations) respectively.

In these settings, tax planning can be viewed as an alternative source of financing.

Because traditional financing sources (i.e., debt or equity) often become more costly or more

difficult to acquire during periods of financial constraints, firms look to alternative sources of

funds. Funds can be “acquired” through tax planning by reducing current reported taxable

income or increasing tax credits, thereby decreasing the cash taxes paid. The cost of these funds

is a function of amount of cash taxes saved, the timing of eventual repayment (if at all), and any

interest and payments eventually paid to the tax authority as a result of the planning activities.

We anticipate constrained firms will engage in tax planning as a source of funds for

several reasons. First, unlike many other cost-cutting techniques (e.g., reducing research and

development, advertising, capital expenditures, staffing, etc.), reducing cash taxes is less likely to

adversely impact firm operations. Second, recent research provides evidence that managers

primarily focus on tax strategies that produce both a cash and financial reporting benefit (i.e., tax

strategies that produce permanent book tax differences) with only a secondary interest in

strategies that only produce a cash benefit (i.e., deferral strategies that produce temporary book

tax differences) (Armstrong, Blouin, and Larcker 2012; Graham, Hanlon, Shevlin, and Shroff

2012). These studies suggest firms likely have not exhausted opportunities to generate cash via

deferral planning strategies. Third, anecdotal evidence suggests constrained firms are more likely

to use tax planning as a source of cash. Specifically, practitioners indicate that, during tough

economic times, “cash is king, and a lot of companies are receptive to focusing on opportunities

in the tax area that they may not have been eager to focus on in the past” (Leone 2008).

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To test our prediction, we first investigate the association between cash tax avoidance and

various macroeconomic and firm-level financial constraints. Consistent with our predictions,

firms facing financial constraints arising from either macroeconomic conditions or firm-specific

financial constraints exhibit lower cash ETRs. Moreover, the reduction in cash ETRs is

economically significant. Our results indicate that, on average, firms’ one year-ahead cash ETRs

are approximately 1.5% lower following periods of macroeconomic financial constraint relative

to periods with no macroeconomic constraint and approximately 2% lower for firms facing

higher firm-level financial constraints.

In our analyses discussed above, we exclude loss firms to be consistent with prior

research examining tax planning. Because loss firms are likely an important subset of financially

constrained firms, we conduct supplemental analysis including firms with a loss in the current

year but cumulative profits over the available loss carryback period (i.e., five years for

observations with year ends from 2008 through 2010 and two years for all other observations).

These firms have an incentive to increase their taxable loss to maximize their current refund.

Results from these tests are consistent with our expectations and suggest that financially-

constrained firms with pretax profits or losses increase tax avoidance to generate additional cash

The findings of this study are important for several reasons. First, a reduction in taxes

paid during times of financial constraint could have significant consequences on the overall

economy. Specifically, if firms simultaneously increase their tax planning activities when faced

with financial constraints induced by macroeconomic conditions, this behavior has the potential

to magnify the effect of an economic contraction on government revenues. Government revenues

would decrease as a result of both the decrease in the corporate tax base caused directly by the

contraction and an increase in tax avoidance behavior.

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The impact of the financial crisis of the late 2000s is consistent with the conjecture

presented above. In the United States, the federal deficit increased during the crisis to

unprecedented levels. Our analysis suggests an average decline of approximately 3% in cash

ETRs due to tax avoidance activities during the macroeconomic contraction that occurred during

2009. This estimated ETR effect equates to approximately a $23 billion decline in corporate tax

revenues and represents approximately 13% of the $182 billion total income taxes after credits

from all profitable C-corporations for 2009.

Second, this study contributes to the literature examining the effects of financial

constraints. Research examining the consequences of financial constraints has become of

increased interest in recent years as firms across the globe have experienced a significant credit

crisis. Examining firms’ responses through the tax account to financial constraints is

advantageous relative to examining responses to financial constraints through other behaviors

because financial accounting rules for income taxes require a relatively comprehensive set of

disclosures. In addition to the total accrued tax expense, firms must identify the portion of the

current fiscal period’s tax provision that is being deferred into subsequent periods as well as the

amount of total cash taxes paid during the period. Thus, we can measure with a higher degree of

precision how financial constraints affect cash taxes paid by firms.

Finally, we contribute to the growing literature on the determinants of firms’ tax

avoidance behavior and the relative importance of avoiding cash payments of taxes versus

reducing financial accounting tax expense. We consider whether increased financial constraints

trigger an increase in tax avoidance behavior. It is of particular interest that this increase in

financial constraints can be firm-specific or economy-wide. This study is one of the first to

investigate whether macroeconomic forces affect firm-level tax avoidance behavior. This study

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also sheds light on the debate related to the relative importance of tax planning activities

generating cash flow savings versus financial reporting benefits. Recent studies provide evidence

suggesting that managers focus primarily on tax planning strategies that reduce total tax expense

(which increases both net cash flows and reported earnings) with only a secondary interest in tax

planning strategies that produce a cash flow benefit but no financial statement benefit

(Armstrong, Blouin, and Larcker 2012; Graham, Hanlon, Shevlin, and Shroff 2012). Our study

provides evidence of specific conditions that increase managers’ focus on cash tax savings.

The remainder of this paper proceeds as follows. The next section develops our

hypotheses relating financial constraints to tax avoidance. Section 3 details the sample, Section 4

describes the research design, Section 5 presents univariate statistics, Section 6 presents our

findings and discusses the economic significance, and Section 7 concludes.

2. Hypothesis Development

In this study, we define both tax avoidance and financial constraint broadly. We define

tax avoidance as all actions taken by managers to reduce their total cash income tax liability. Tax

avoidance can include both legal planning strategies in full compliance with tax laws and more

aggressive strategies resulting from aggressive interpretations of ambiguous areas within the tax

laws. Our measures are discussed in greater detail in Section 4 and capture worldwide tax

avoidance. Our aim is not to specifically measure tax aggressiveness, tax risk, tax evasion, or tax

sheltering. Instead, we employ a broad measure that captures a firm’s propensity to reduce its

cash tax burden relative to its reported financial accounting pretax income. This definition is

consistent with prior research and stems primarily from Dyreng, Hanlon, and Maydew (2008).2

2 Unlike Dyreng, Hanlon, and Maydew (2008) who focus on long-run tax avoidance (measured over 5 or 10 years), we focus on one-year measures of tax avoidance to capture firms’ near-term responses to current financial

6

We take a broad view of financial constraint and define a firm as more financially

constrained if it experiences an increase in the cost of external financing or an increase in the

difficulty of accessing external funds (Whited and Wu 2006; Denis and Sibilkov 2010). The

financing need and the resulting constraint can arise from a variety of sources. We focus on two

major sources of the financing need: investment opportunities and financial distress. Firms with

unfunded investment opportunities require additional cash in order to finance those additional

investments. Firms in financial distress require additional cash in order to finance existing

operations and remain solvent. For both of these sources of the financing need, the financially

constrained firm needs additional financing through the least costly source available. Constrained

firms have an increased incentive to reduce cash taxes regardless of whether the source of the

constraint is a macroeconomic shock or a firm-specific event such as the loss of a major

customer. As a result, we exam both macroeconomic and firm-specific financial constraints.

Examining financially constraints from a macroeconomic perspective has the added advantage in

that macroeconomic constraints are generally exogenous to the firm. The exogenous nature of

the macroeconomic shock allows for better identification in our empirical analysis. We predict

that an increase in financial constraints decreases the supply and/or increases the cost of external

funds which incentivizes a firm to generate additional cash funds internally.

2.1. Tax Planning and Financial Constraints

Corporate income taxes are a non-discretionary expenditure imposed by the government

that all profitable firms must incur. Although income taxes are imposed on all firms at specified

statutory rates, a manager can implement various strategies to reduce the firm’s tax liability. A

growing stream of literature examines the determinants of a firm’s tax avoidance behavior (for a

constraints. These near-term tax responses may or may not be reflected in long-run measures, which likely blend tax avoidance during both constrained and unconstrained periods.

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review of the literature see Shackelford and Shevlin 2001 and Hanlon and Heitzman 2010). In

this study, we examine the impact of financial constraints, arising at both the macroeconomic

level and the firm level, on a firm's tax avoidance behavior. We predict that financially

constrained firms will take actions to increase internally-generated funds via cash tax planning.

We focus on cash tax planning as a source of internal funds for the following reasons.

First, a financially constrained firm that attempts to generate additional internal funds

could reduce cash outflows through a variety of options. Most cost-cutting options, such as

reducing advertising, research and development, capital expenditures, or labor costs, often

adversely impact the firm's long-term performance. Unlike these cost-cutting techniques,

reducing a firm's cash tax burden is unlikely to have negative long-term consequences assuming

the tax strategies are upheld upon audit.3

Second, recent research suggests that managers primarily focus on strategies that produce

both a cash and financial reporting benefit (i.e., permanent tax strategies) with only a secondary

interest in strategies that only produce a cash benefit (i.e., deferral strategies). For example,

Armstrong, Blouin, and Larcker (2012) find a strong negative association between tax director

incentive compensation and GAAP effective tax rates, but no relation between incentive

compensation and cash effective tax rates (i.e., cash tax savings). Furthermore, Graham, Hanlon,

Shevlin, and Shroff (2012) survey corporate tax executives and report that 47 percent of the

managers in their sample of publicly-traded firms indicate that their firm’s GAAP effective tax

rate is the most important tax metric to top management, whereas only 15 percent state that cash

3 Even if the strategies are not sustained upon audit, if the interest and penalties paid to the tax authority are less than the interest that would have been paid to a third party lender, the tax planning firm is better off. This discussion does not include costs associated with implementing tax planning strategies. Although these costs are not trivial, prior research estimates an average return of approximately $4 for every $1 invested in general tax planning (Mills, Erickson, and Maydew 1998).

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taxes paid is the most important tax metric. In general, these studies suggest that "cash is not

king" in terms of tax planning for most firms. Anecdotal evidence from practitioners supports

these recent academic findings. Practitioners from large international accounting firms indicate

that profitable public companies have not historically been interested in tax accounting issues

related to timing (i.e., deferral strategies) but instead focus on issues that impact earnings-per-

share (i.e., permanent strategies) (Leone 2008). Collectively, these studies and anecdotes suggest

that firms likely have not exhausted their opportunities to generate cash via tax planning.

Third, anecdotal evidence suggests that financially constrained firms are more likely to

use tax planning as a source of cash. For example, David Auclair, managing principal in Grant

Thornton's national tax office, indicates that during the recent financial crisis "a lot of companies

are receptive to focusing on opportunities in the tax area that they may not have been eager to

focus on in the past" (i.e., before the financial crisis). Mel Schwarz, Grant Thornton's director of

tax legislative affairs, states that "there is nothing like the current economic situation to spur

companies to generate cash." John Salza, a BDO Seidman tax partner and leader of the firm's

national tax accounting methods group, also adds that "with the economy sagging and cash

becoming more valuable, even publicly-traded companies are looking at what we call timing

items, cash benefits…even though it doesn't affect their effective tax rate."4 These statements

suggest that financial constraints impact not only a firm's focus on tax planning as a source of

cash but also the nature of the tax strategies that firms will consider (i.e., both permanent and

deferral-based tax strategies). Echoing the likelihood that constrained firms will turn to tax

planning to generate cash, Josephine Feehily, the Chairman of the Office of the Revenue

Commissioners in Ireland, suggested that there could be an increase in tax avoidance as the

4 These quotes are from Leone (2008). Anecdotes from conversations with tax partners at several of the Big 4 firms present views similar to those discussed in Leone (2008).

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economy experiences a recession stating, "In a downturn, money is tighter, so people may be

tempted to evade tax" (McBride 2009).

In sum, we predict that financially constrained firms will take actions to increase

internally-generated funds via cash tax planning because (1) firms prefer reducing tax costs

rather than cutting other operating costs, (2) firms likely have untapped opportunities to save

cash taxes, and (3) anecdotal evidence suggests that constrained firms are indeed more likely to

take advantage of those opportunities as a source of additional cash. Thus we predict that

financially constrained firms will take actions to reduce cash taxes paid. Stated formally, we

propose the following hypothesis:

H1: Near-term cash taxes paid are negatively associated with financial constraints.

Although we anticipate a negative association between both macroeconomic and firm-

level financial constraints and cash taxes, there are reasons why we might not observe our

hypothesized relation. For example, many tax avoidance strategies require an upfront investment

without an immediate benefit. If financially constrained firms simply cannot afford to implement

the tax avoidance strategies (even when the benefits are in the near future), we will not observe a

significant association between constraints and cash taxes. Also, if potential future losses of

constrained firms reduce the expected benefit of engaging in current period tax avoidance, we

might not observe our hypothesized relation. Further, if the financial constraint is primarily at the

parent company, constrained firms with international operations can access foreign cash holdings

to alleviate the constraint. If constrained firms have foreign cash available in low tax

jurisdictions, additional U.S. taxes could be due upon repatriation of those foreign earnings,

which would increase the firm’s cash effective tax rate and reduce the likelihood of observing

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our hypothesized result.5

2.2. Tax Planning as a Source of Financing

To more clearly illustrate the theory behind our hypotheses, we discuss viewing tax

planning as a source of financing. As previously discussed, when a firm is facing financial

constraints they have an increased need for cash. For investment-related constraints, this need

arises due to the desire to fund additional investment. For distress-related constraints, this need

arises due to a need to cover short-term working cash flow obligations. If traditional financing

sources become too costly or are unavailable, firms look for alternative sources of funds. In this

context, tax planning can be viewed as an alternative source of financing. Cash can be

“acquired” from the tax authority by reducing current reported taxable income or increasing tax

credits, thereby decreasing the taxes paid (or increasing the tax refund received) in the current

period. The cost of funds obtained in this manner has an implicit discount rate that depends on

(1) the amount of cash taxes saved, (2) the timing of eventual repayment (if at all) and (3) any

interest and payments eventually paid to the tax authority as a result of the planning activities. In

the case of a tax planning strategy that defers tax payments, the firm is effectively receiving an

interest-free loan from the government for the duration of the deferral period. In the case of a tax

planning strategy that permanently avoids tax payments, there are no principal or interest

payments if the tax authority does not challenge the position and repayment of principle, interest,

and penalties if the tax authority successfully challenges the position.

Obtaining financing in this manner, the firm knows (1) the amount borrowed, (2) the

length of the borrowing period and (3) expected future payments. This enables the manager to

5In supplemental tests we repeat our analysis using only firms that do not report foreign earnings to ensure that any confounding effect related to repatriations is not impacting our results. Inferences from the observed results under this specification are unchanged from our main analysis.

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estimate a marginal cost of capital for the tax savings and weight the relative merits of financing

through tax planning versus other more traditional forms of financing such as debt or equity.

Prior to facing the financial constraint in question the firm has presumably already accessed the

cheapest “tax financing.” The marginal tax planning opportunities will have a higher cost, and so

utilizing this source of funds will only make sense if the returns to the project will exceed the

costs of the marginal tax plan and there is no cheaper source of financing.

Viewing tax planning as a source of financing, in conjunction with standard theories in

finance (e.g., pecking order theory; Myers 1984), supports the prediction that managers will rely

more heavily on generating funds via tax planning when those funds represent the cheapest

source of financing available to the firm. Financial constraints likely rearrange the rank ordering

of this cost of capital; external funds (both debt and equity) can become more costly, thereby

causing managers to reevaluate possible internal sources of funds. The fact that managers did not

access all possible tax planning projects during non-constrained times is not necessarily

indicative of inefficiencies. For example, deferral strategies, which are basically an interest-free

loan from the government, might not be pursued vigorously because the benefits are not

recognized for financial reporting purposes. For deferral strategies, the GAAP effective tax rate

is unchanged as is reported net income. Armstrong, Blouin, and Larcker (2012) provide evidence

that tax directors are incentivized to reduce the level of tax expense reported in the financial

statements. Also consistent with this notion, Edgerton (2012) shows that tax incentives for

investment are more effective when the incentive impacts accounting income (e.g., investment

tax credits) than when the incentives do not affect accounting income (e.g., bonus depreciation).

3. Sample

To investigate the effect of financial constraints on firms’ tax planning activities, we

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begin with firms listed on Compustat from 1987, the first year following the most recent major

tax reform, to 2011. Consistent with prior tax avoidance studies, we eliminate financial firms and

utility firms, firm-year observations with missing or negative pretax income, and firm-year

observations missing the necessary data to compute the tax planning, financial constraint and

control variables used in our analyses.6 Table 1 summarizes our sample selection process.

To investigate the effect of firm-level financial constraints on firms’ tax planning

activities, we utilize the same primary sample of 44,328 firm-years with the firm-level financial

constraint measures (the decile rank of the Altman Z-score and the rank of the Whited and Wu

investment financial constraint index).

To investigate the effect of macroeconomic financial constraints, we require additional

data on GDP growth and economy-wide lending practices. To retain the largest sample possible,

we impose each of these restrictions separately resulting in samples of 44,328 (37,290) firm-year

observations when using GDP growth (tightening of lending standards) to proxy for

macroeconomic constraints.

4. Research Design

To examine the relation between financial constraints and tax avoidance, we estimate the

following regression:

Tax_Avoidancei,t = β0 + β1 Constrainti,t-1 + ΣβkControlsi,t + ε (1)

4.1. Tax Avoidance

When testing the relation between tax avoidance and macroeconomic and firm-level

6 Despite eliminating firms with negative pretax income, we observe large variation in our firm-specific financial constraint measures. In supplemental analyses (see Section 6.3), we include loss firms that can likely benefit from additional tax avoidance in the current period (i.e., firms that can carry back current losses to obtain a refund of taxes paid in prior years) while continuing to exclude loss firms that are unlikely to benefit from additional tax avoidance in the current period (i.e., firms that must carry forward current losses to potentially offset future income).

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financial constraints, Tax_Avoidance is set equal to a firm’s cash effective tax rate (CashETR),

measured as the ratio of cash taxes paid to pretax income adjusted for special items [Compustat

data items txpd / (pi – spi)].7,8 Cash taxes vary with firms profitability: more profitable firms are

expected to pay higher taxes. Thus we scale cash taxes by pretax book income to reflect this

relation, which is particularly important in our setting where we examine macroeconomic

downturns which lead to declines in firm profitability. If a firm’s CashETR is above one (below

negative one), CashETR is set equal to one (negative one).9 As discussed by Hanlon and

Heitzman (2010) in their review of the literature on tax research, it is important to select a tax

avoidance measure appropriate to the research question and not simply apply a laundry list of

measures. We utilize cash ETR because we are interested in how firms respond to financial

constraints that result in a need to generate additional cash. A firm’s cash ETR is the most direct

measure of a firm’s cash tax burden. Tax planning that decreases a firm’s cash tax burden will

have a direct impact on a firm’s cash ETR. Unlike prior studies that use long-run ETR measures

to avoid noise in the one-year measure (see Dyreng, Hanlon, and Maydew 2008), we utilize a

one-year cash ETR measure to capture timely responses to existing financial constraints. There

are a number of potential strategies that firms can implement in a relatively short time period.

For example, firms can more aggressively expense instead of capitalize expenditures, shift

income to lower tax jurisdictions, take advantage of programs such as the domestic

7 Throughout the remainder of the manuscript all variable abbreviations detailing the construction of our measures refer to Compustat data items unless specifically noted otherwise. 8 Following Dyreng, Hanlon, and Maydew (2008) we adjust pretax income for special items. However, due to concerns that (1) negative special items may be more likely during a macroeconomic downturn or periods of financial distress and (2) adjusting the denominator but not the numerator of CashETR may impact our results, we conduct two robustness tests (untabulated). First, we repeat our analysis using unadjusted pretax income in the denominator. Second, we repeat our analysis after deleting observations with special items. All results and inferences hold under both of these alternatives. 9 Much of the prior literature resets CashETR at zero and one. To allow for refunds (i.e., negative cash taxes paid in the numerator), we reset CashETR at negative one. Our results are qualitatively similar if we reset CashETR at zero and one.

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manufacturing deduction, and engage in timing strategies which accelerate deductions and delay

income recognition. 10

4.2. Financial Constraints

The variable of interest in equation (1), Constraint, captures the level of either the

macroeconomic or firm-specific financial constraints faced by the firm. As discussed in the

hypothesis development section, we consider two possible drivers of the financial constraint:

investment opportunities and financial distress. Our measure, Constraint, equals the lagged value

of one of two macroeconomic financial constraint measures (GDP% and Tightening) or the

lagged value of one of two firm-level financial constraint measures (RankZ for distress related

financial constraint and RankWW for investment related financial constraint). We use lagged

values of financial constraints because tax avoidance strategies generally require time to plan and

implement. We examine the sensitivity of our results to this assumption in Section 6.6.

Our first macroeconomic financial constraint measure, GDP%, is based on data from the

Bureau of Economic Analysis. GDP% equals negative one times the percentage change in

inflation-adjusted GDP. We multiply the variable by negative one so that higher values of

GDP% correspond to higher levels of macroeconomic financial constraint. Higher (lower) values

of GDP% are associated with economic contractions (growth) during which external funding is

often more limited (more abundant) and firms are more (less) likely to face financial constraints.

Our second macroeconomic financial constraint measure, Tightening, is based on data from the

10 Although CashETR is the best measure of a firm's cash tax liability, CashETR has several potential limitations. For example, there is a potential timing mismatch between the numerator and denominator (i.e., cash payments for taxes may not occur within the same fiscal period as the income to which they relate). The potential mismatch can result in payments or refunds from adjacent years being included in our year of interest, a concern that is heightened for constrained firms if these firms delay tax payments to future years. A more complete discussion of this concern and other potential limitations of CashETR is included in section 6.3. To alleviate these concerns, we use two additional accrual measures, the current ETR and the US Federal ETR, in supplemental analyses. Results are discussed in section 6.3 and are consistent with those using CashETR.

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Federal Reserve Board’s Senior Loan Officer Opinion Survey. Tightening equals the average net

percentage of domestic respondents reporting tightening standards in year t-1 for commercial and

industrial loans. Positive (negative) values of Tightening correspond with a tightening

(loosening) of lending standards and an increase (decrease) in macroeconomic financial

constraints. The tightening of lending standards directly captures the ease with which firms can

obtain credit financing.12

Our first firm-specific measure, RankZ, is based on the firm’s Altman (1968) bankruptcy

prediction Z-score. Firms closer to bankruptcy face greater difficulty accessing external funds.

To reduce noise in this measure, we use the decile rank of the firm’s Z-score in year t-1 where

higher values indicate they are more likely to be financially distressed.13 RankWW equals the

decile ranking of a firm’s investment related financial constraint index developed in Whited and

Wu (2006). RankWW is coded so that higher values represent higher financial constraints.14 If

financial constraints increase tax planning behavior, we anticipate negative coefficients on

Constraint across our various specifications.

4.3. Controls

In addition to our explanatory variable of interest, Constraint, we include a battery of

control variables in our regression model. Many tax deductions, exclusions, and tax credits are

12

For brevity we focus on these two measures of macroeconomic financial constraint. In untabulated robustness tests we repeat our analysis using a measure of economic contraction based on NBER data that equals the number of months in year t-1 that the economy is contracting divided by 12, and a measure of equity market frothiness that equals the inverse of IPO volume in year t-1 based on data from Jay Ritter’s website. Results are qualitatively and quantitatively similar to those reported in the main analysis using these alternative proxies. 13Many studies use the Z-score to construct a financial distress indicator equal to one when the Z-score is below 1.8 and zero otherwise. Our results are robust to replacing RankZ with the financial distress indicator. 14There are a number of firm-specific financial constraint measures utilized in the literature. For brevity, we focus on a subset of these measures but repeat our analysis with a number of alternative, commonly used measures. Alternative measures include (1) an indicator variable equal to one for firms that pay no dividends in year t-1 and zero otherwise, (2) an indicator variable equal to one for firms with a Standard & Poor's (S&P) domestic long-term issuer credit rating in year t-1 consistent with non-investment grade debt and zero otherwise, and (3) the decile rank of a firm’s likelihood of bankruptcy based on Shumway (2001). Results are qualitatively and quantitatively similar to those reported in the main analysis using these alternative proxies.

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not perfectly correlated with economic activity of the firm but are instead fixed over a relevant

range (Zimmerman 1983; Wilkie 1988). For example, a firm can often increase or decrease

production without purchasing additional property, plant and equipment such that the

depreciation tax deduction is fixed and does not vary directly with the activity. We refer to this

relation as the fixed tax shield effect. To address this “nonlinearity” we include both an intercept

and pretax return on assets, PROA (pi/at), as an additional explanatory variable. We expect a

positive coefficient on PROA because a decrease (increase) in PROA as a proxy for economic

activity will decrease (increase) the cash ETR due to the fixed tax shield effect. Additionally we

include industry fixed effects which allow the intercept to vary across industries and we identify

the association between tax avoidance and financial constraints by within industry variation

rather than across industry variation (since cross-industry variation, such as fixed asset intensity,

might reflect differences in the fixed tax shield effects).15

We control for firm size by including Size, measured as the natural log of total assets

[ln(at)]. Large firms are widely viewed as more sophisticated and can structure complex tax-

reduction transactions with the help of the best tax advisors (Mills, Erickson, and Maydew 1998;

Hanlon, Mills, and Slemrod 2007). If large firms conduct more successful tax planning, then Size

will be negatively related to tax costs. On the other hand, large, mature firms would have fewer

tax shields and hence higher ETRs as their capital investment slows. Because size can capture

15 We do not explicitly control for the various tax brackets in our main analysis. Although financially constrained firms likely have lower taxable income than non-constrained firms, U.S. federal corporate taxes rates are at or near 35% for all income above $75,000 (the rate varies between 34% and 39% between $75,000 and $18,333,333 and is 35% for taxable income above $18,333,333) resulting in a relatively flat tax rate. In untabulated robustness tests, we include indicator variables (together and separately) for pretax income below $75,000 and pretax income below $18,333,333. Results from these specifications are qualitatively and quantitatively similar to those reported in the paper. In a similar vein, it is unlikely our results are driven by overpayments or refunds that could result from large changes in taxable income that could accompany financial constraint. We assume that firms, particularly firms facing cash shortages during financial constraint, will adjust estimated payments in a timely matter and avoid overpayments in order to conserve cash in the near term.

17

many effects, we make no directional prediction.

An extensive literature establishes that corporate taxpayers respond to tax incentives to

place income in lower taxed jurisdictions (see Klassen and Laplante 2012 for recent evidence).

Because segment disclosures no longer require foreign asset disclosures, we use the absolute

value of the ratio of foreign pretax income to worldwide pretax income (pifo/pi) as a proxy for

foreign operations (Foreign). Following Mills and Newberry (2004), we set foreign pretax

income equal to zero for firm years where it is missing.

To control for the existing capital structure of the firm, we include Leverage which

equals the ratio of long-term debt to assets [(dltt+dlc)/at]. Prior literature argues that debt

provides an important tax shield (Graham 1996) and provides evidence of a negative relation

between leverage and marginal tax rates. However, interest deductions decrease income for both

tax and financial reporting purposes making it unclear whether leverage would necessarily

decrease effective tax rates. Further, additional debt would increase cash outflows in the form of

interest payments by a greater amount than the tax savings the interest expense would generate.

Newberry and Dhaliwal (2001) argue that multinationals can place debt in high-tax locations and

thus reduce their effective tax rates. Firms can also structure off-balance-sheet financing to

maximize interest deductions without decreasing book income (Mills and Newberry 2004) or can

structure debt to use foreign tax credits (Newberry 1998). Collectively, these studies suggest that

debt is negatively associated with effective tax rates. Finally, both of our firm-specific measures

of financial constraints have measures of leverage as inputs. The inclusion of leverage as a

control variable in our model helps ensure that the relation between financial constraints and tax

avoidance we document is incremental to the effect of leverage.

We include CapEx, the ratio of capital expenditures to total assets (capx/at), as a proxy

18

for tax planning opportunity. Governments often use tax policy to spur economic investment,

especially during economic downturns. Consistent with legislated tax shields, capital-intensive

firms have lower tax burdens (Gupta and Newberry 1997), higher book-tax differences (Mills

and Newberry 2001; Wilson 2009; Lisowsky 2010), and higher IRS deficiencies (Rice 1992;

Mills 1998). Furthermore, many tax shelters during the 1990s involved long-lived capital assets

(McGill and Outslay 2004). We expect that CapEx will be negatively related to cash ETRs.16

We include R&D, the ratio of research and development expense to revenues (xrd/sale),

to control for intellectual property. Intellectual property, such as patents and brand intangibles,

increases opportunities to decrease taxes via income shifting. Additionally the R&D tax credit

reduces cash ETRs. As such, we expect R&D to be negatively related to cash ETRs.

To control for aggressive financial reporting practices, we include DiscAccruals.

DiscAccruals equals performance-matched discretionary accruals as measured in Kothari, Leone,

and Wasley (2005). If firms that exhibit more aggressive financial reporting practices are more

tax aggressive as suggested by Frank, Lynch, and Rego (2009), then we would expect a negative

association between DiscAccruals and tax rates.

We include an indicator variable (NOL) to control for the presence of net operating loss

carryforwards (i.e., a non-zero value for tlcf). Consistent with Chen, Chen, Cheng, and Shevlin

(2010), we expect that NOL firms have lower tax rates because they are less profitable and are

able to utilize the loss carryforwards to reduce taxable income and thus cash taxes.18

We also include the book-to-market ratio, BM, to control for firm growth. Growth firms

often have substantial tax deferral opportunities and also often rely heavily on stock-based

16 Results are robust to defining CapEx as the ratio of net property, plant, and equipment to total assets (ppent/at). 18

Also note that financially distressed firms are more likely to have NOL carryforwards. By including NOLs separately, we are examining the effect of the financial distress constraint incremental to the effects of NOLs.

19

compensation, both of which decrease CashETRs. Finally, because tax subsidies are often unique

to particular industries, we include industry-fixed effects (Barth, Beaver, and Landsman 1998).19

5. Descriptive Statistics and Correlations

Table 2 presents descriptive statistics for the tax avoidance, financial constraint, and

control variables used in this study. Similar to evidence documented in prior studies (e.g.,

Dyreng, Hanlon, and Maydew 2008), cash effective tax rates are substantially lower than the

statutory rate of 35%. Focusing first on the macroeconomic constraint measures, GDP grows at

an average rate of approximately 2.8% per year. The annual mean net tightening of lending

standards (Tightening) is positive 6.5%. Focusing on the firm-level constraint measures, we

present descriptive statistics for the underlying measures but use decile ranks in the regression

models. The interquartile range is 2.46 to 5.71 for the underlying Altman (1968) Z-score and -

0.36 to -0.22 for the underlying Whited and Wu (2006) financial constraint index. Collectively,

these descriptive statistics indicate substantial variation in financial constraints at both the

macroeconomic and firm level during our sample period.

Table 3 presents correlations between our tax and financial constraint measures, with

Pearson correlations above the diagonal and Spearman rank correlations below the diagonal.

Consistent with H1, CashETR is negatively correlated with GDP%, Tightening, RankZ, and

RankWW. These correlations provide support for the assertion that financially constrained firms

exhibit increased tax avoidance. The macroeconomic financial constraints are positively

correlated with one another. It is interesting to note that RankWW is negatively correlated with

RankZ (ρ = -0.09). This result is not entirely surprising given the different aspects of financial

19

We do not include year fixed effects as our proxies for macroeconomic financial constraints are cross-sectional (i.e., within year) constants. However, our results are robust to including year fixed effects when using firm-specific measures of financial constraints (e.g., RankZ and RankWW).

20

constraint that these measures are intended to capture (i.e., constraints due to financial distress

and bankruptcy concerns versus insufficient capital to fund investment opportunities).20

6. Multivariate Results

6.1. Financial Constraints and Cash ETRs

Panel A of Table 4 presents the results from estimating equation (1) using CashETR as

the dependent variable and macroeconomic measures of financial constraints. The negative and

significant coefficients on GDP% and Tightening are consistent with H1. To assess the economic

significance of a macroeconomic increase in financial constraints, we focus on each measure

separately. An increase of one standard deviation in GDP% is accompanied by a 1.43% decrease

in a firm’s CashETR (-0.8251*0.0173), which represents an average reduction of $3.67 million

in cash taxes and an increase of 1.33% of operating cash flows for sample firms.21 An increase of

one standard deviation in Tightening is accompanied by a 1.44% decrease in a firm’s CashETR (-

0.0007*20.632), which represents an average reduction of $3.70 million in cash taxes and an

increase of 1.34% of operating cash flows for our sample firms. These reductions in CashETR

are economically significant, and are after controlling for the level of economic activity on cash

taxes by scaling cash taxes by pretax book income and including pretax ROA as an additional

explanatory variable.

Panel B of Table 4 presents the results from estimating equation (1) using CashETR as

the dependent variable and firm-specific measures of financial constraints. The coefficients on

20 Insignificant or even negative correlations across measures of financial constraint are not uncommon. In fact, Whited and Wu (2006, p.545) report that their measure is negatively correlated (ρ = -0.019) with another common measure of financial constraint developed by Kaplan and Zingales (1997). 21 Calculations related to the cash tax reductions and the ratio of cash savings to operating cash flows for the macroeconomic measures of financial constraint follow: GDP%: $3.67 million cash tax benefit = -1.43%*$256.71 (mean adjusted pretax income). 1.33% of operating cash flows = $3.67 million/$276.73 million (mean operating cash flows). Tightening: $3.70 million cash tax benefit = -1.44%*$256.71 (mean adjusted pretax income). 1.34% of operating cash flows = $3.70 million/$276.73 million (mean operating cash flows).

21

both RankZ and RankWW are negative and significant. These results are consistent with H1 and

suggest that financially-constrained firms increase tax avoidance to generate additional cash. The

magnitude of the effect is also economically significant. For the ranked measure of financial

distress, RankZ, a one decile increase in the independent variable is associated with a decrease in

CashETR of 1.82, which represents an average reduction of $4.67 million in cash taxes and an

increase of 1.69% of operating cash flows for our sample firms.22 For the measure of financial

constraint from Whited and Wu (2006), RankWW, a one decile increase in the independent

variable is associated with a decrease in CashETR of 2.02%, which represents an average

reduction of $5.19 million in cash taxes and an increase of 1.87% of operating cash flows for our

sample firms. In the interests of brevity, we do not discuss in detail the results for the control

variables: many exhibit significant coefficients in directions consistent with prior literature.

6.2. Loss Firms

We exclude loss firms in our main analysis to be consistent with prior research examining

tax planning. Because loss firms are likely an important subset of financially constrained firms,

we conduct supplemental analysis including firms with a loss in the current year but cumulative

profits over the current and prior two years (prior five years for 2008-2010). In general, a firm is

able to carry a current year loss back to the prior two years and receive a refund of taxes

previously paid.23 As such, these firms have an incentive to increase their taxable loss to

22

Calculations related to the cash tax reductions and the ratio of cash savings to operating cash flows for the firm-level measures of financial constraint follow: RankZ: $4.67 million cash tax benefit = -1.82%*$256.71 (mean adjusted pretax income). 1.69% of operating cash flows = $4.67 million/$276.73 million (mean operating cash flows). RankWW: $5.19 million cash tax benefit = -2.02%*$256.71 (mean adjusted pretax income). 1.87% of operating cash flows = $5.19 million/$276.73 million (mean operating cash flows). 23 Firms with adjusted pretax book income less than zero must have cumulative pretax income over the prior two years to be included. We extend this window from two to five years for 2008 through 2010 to correspond with the legislated increase in the loss carryback period during that time. Firms with current losses that must be carried

22

maximize their current refund. Consistent with this notion, prior research has documented

intertemporal income shifting by firms to increase NOLs and cash refunds (Maydew 1997;

Erickson, Heitzman, and Zhang 2012). In this analysis, we re-estimate equation (1) after adding a

loss indicator (Loss) set equal to one when adjusted pretax income is negative (pi-spi<0) and an

interaction between Loss and Constraint. These additional variables allow us to examine the

relation between financial constraints and tax planning for loss firms.

There are four possible combinations of cash taxes and pretax book income when

including both profit and loss firms. We discuss profitable firms first. When a firm reports

positive pretax book income and positive cash taxes paid (i.e., CashETR>0), we expect a

negative coefficient on Constraint. This result would be consistent with our earlier hypotheses

and indicate that these constrained firms take actions to reduce their positive tax liability. When a

firm reports positive pretax book income and negative cash taxes (i.e., CashETR<0), we expect a

negative coefficient on Constraint. This result would be consistent with our earlier hypotheses

and indicate that these constrained firms take actions to increase their tax refund. Because the

coefficient on Constraint captures the relationship between financial constraints and cash ETRs

for profitable firms, these patterns suggest a negative coefficient on Constraint.

Next we consider loss firms. When a firm reports negative pretax book income and

positive cash taxes (i.e., CashETR<0 and Loss=1), we expect a positive coefficient on the

Loss*Constraint interaction. This result would indicate that these constrained firms take actions

to reduce their positive tax liability. When a firm reports negative pretax book income and

negative cash taxes (i.e., CashETR>0 and Loss=1), we expect a positive coefficient on the

Loss*Constraint interaction. This result would suggest that these constrained firms try to

forward cannot lower their current period cash taxes as they are already zero and cannot increase their cash refunds because they cannot carry back. Thus we continue to exclude these firms.

23

increase their refund. These predictions imply an expected positive coefficient on the

Loss*Constraint term and on the sum of the coefficients on Constraint and Loss*Constraint (as

the sum represents the overall constraint coefficient estimate for the loss firms). The following

figure summarizes the predicted coefficients on Constraint and the Loss*Constraint interaction.

Expected Coefficient on Constraint when CashETR is the Dependent Variable

Positive cash taxes Negative cash taxes (refund)

Positive pretax book income CashETR>0 and Loss=0

NEGATIVE coefficient

(constrained firm reduces cash

taxes paid)

CashETR<0 and Loss=0

NEGATIVE coefficient

(constrained firm increases

cash refund)

Negative pretax book income CashETR<0 and Loss=1

POSITIVE coefficient

(constrained firm reduces cash

taxes paid)

CashETR>0 and Loss=1

POSITIVE coefficient

(constrained firm increases

cash refund)

Panel A of Table 5 presents the results from estimating equation (1) using the

macroeconomic measures of financial constraints when including loss firms and the variables

Loss and Loss*Constraint. The coefficients on Constraint and the Constraint*Loss interaction

are consistent with expectations when either GDP% or Tightening is used to measure

macroeconomic constraints. Specifically, we find negative and significant coefficients on

Constraint (p-values of < 0.0001) and positive and significant coefficients on the

Loss*Constraint interaction (p-values of < 0.0001). Also consistent with expectations, the sum of

the Constraint and Loss*Constraint coefficients are positive and significant.

Panel B of Table 5 presents the results from estimating equation (1) using the firm-

specific measures of financial constraints when including loss firms and the variables Loss and

Loss*Constraint. The coefficients on Constraint and the Constraint*Loss interaction are

24

consistent with expectations when either RankZ or RankWW is used to measure firm-level

constraints. Specifically, we find negative and significant coefficients on Constraint (p-values of

< 0.0001) and positive and significant coefficients on the Loss*Constraint interaction (p-values

of < 0.0001 and 0.0540 respectively). However, the sum of the Constraint and Loss*Constraint

coefficients are not significantly positive using the firm-level constraint measures.

These results are generally consistent with our expectations and suggest that financially-

constrained firms with pretax profits or losses increase tax avoidance to generate additional cash

flows by reducing tax payments or increasing refunds.24

6.3. Alternative Measures of Tax Planning

In this subsection we examine the impact of financial constraints on tax planning using

two alternative measures of tax avoidance, CurrentETR and FederalETR. CurrentETR is defined

as the ratio of current tax expense to pretax income adjusted for special items [txc / (pi – spi)]

and FederalETR is defined as the ratio of current federal income taxes to domestic pretax income

(txfed/pidom).25 Although CashETR is a more direct measure of our construct of interest, cash

savings through tax planning, there is a potential timing mismatch between the numerator and

denominator (i.e., cash payments for taxes may not occur within the same fiscal period as the

income to which they relate). The potential mismatch can result in payments or refunds from

adjacent years being included in our year of interest, a concern that is heightened for constrained

firms if these firms delay tax payments to future years.26 By using the accounting accrual (both

24 In untabulated robustness tests, we repeat this analysis including only loss firms to ensure that the substantial portion of the sample with positive pretax income is not driving the result. The results are consistent with those reported in the tables. 25 As with CashETR, for both CurrentETR and FederalETR, if a firm’s ETR is above one (below negative one), the measure is set equal to one (negative one). 26 A related concern to the timing mismatch is that, in addition to direct changes in tax avoidance, firms could attempt to reduce their estimated payments in order to save cash. Although this would be a very short term savings and is not the primary mechanism we hypothesize, it would reduce the cash ETR and increase net cash flows in

25

current tax expense and federal tax expense) we are able to ensure that our results are not driven

by attempts to generate short term savings by manipulating the amount and timing of estimated

tax payments (although even this strategy could be viewed as a tax avoidance strategy to reduce

short term cash outflows). Further, CashETR is a more direct proxy for a firm’s worldwide cash

tax burden but FederalETR is the best proxy available for a firm’s U.S. cash tax burden. As such,

FederalETR can provide more direct evidence regarding domestic tax revenues.

Panel A of Table 6 presents the results using CurrentETR and FederalETR to proxy for

tax planning. For brevity, the coefficients on control variables are not reported. For both tax

planning proxies the coefficients on all constraint measures are negative and significant,

consistent with our main findings (p-values of < 0.0001). These results confirm that our earlier

results are not due to timing mismatches between the recognition of pretax book income and the

payment of cash taxes (CurrentETR) and provide additional evidence that tax planning during

times of financial constraint reduces U.S. tax revenues (FederalETR).28

6.4. Permanent tax savings vs. tax deferral

To better understand the types of tax planning strategies that managers employ to reduce

cash taxes when facing financial constraints, we decompose tax savings into two components:

tax savings resulting from permanent planning strategies and tax savings from deferral-based

planning strategies. Although both permanent and deferral-based strategies produce cash tax

savings, permanent strategies are potentially more beneficial than deferral strategies because they

difficult financial times. Another possible limitation of our measure relates to tax refunds. Refunds could be associated with our financial constraint variables if firms make estimated tax payments based on expected higher taxable income and then, following an unexpected macroeconomic or firm-level shock, report lower taxable income and owe less tax. Robustness test using the current tax expense and federal tax expense, both accrual numbers, mitigate this concern. Further mitigating this concern, we find no consistent correlation between financial constraints and either taxes payable or the presence of a refund (untabulated). 28 Some caution should be used when interpreting the revenue effect of the constraint coefficients in the FederalETR regressions because FederalETR is an accrual number and does not capture cash flows directly.

26

(1) result in higher earnings for financial reporting purposes (via a reduction in total tax expense)

and (2) produce, dollar for dollar, larger cash savings in present value terms because they do not

reverse in future years (unlike deferral-based strategies). Recent research (see the prior

discussion of Armstrong, Blouin, and Larcker 2012 and Graham, Hanlon, Shevlin, and Shroff

2012) provides evidence suggesting that managers on average focus primarily on tax planning

strategies that reduce both cash taxes and financial statement income tax expense (i.e., permanent

strategies) with only a secondary interest in tax planning strategies that only produce a cash flow

benefit (i.e., deferral strategies).

In our setting, we anticipate that managers of financially constrained firms likely still

have a preference for permanent tax planning strategies because financially constrained firms

have incentives to increase both cash flows and reported earnings. However, because financially

constrained firms have a greatly increased need for cash relative to unconstrained firms and firms

likely have untapped deferral-based tax planning opportunities, we anticipate that they are also

more likely to engage in deferral-based strategies despite the lack of a financial reporting benefit.

To examine whether any reduction in a firm’s cash ETR is the result of permanent versus

temporary tax planning strategies, Tax_Avoidance is measured as Permanent or Deferral

respectively.29 Permanent equals negative one multiplied by the difference between the statutory

tax rate and the ratio of total tax expense to pretax income adjusted for special items [-1*(35% -

txt / (pi – spi))]. Deferral equals negative one multiplied by the ratio of deferred tax expense to

pretax income adjusted for special items [-1*(txdfed + txdfo) / (pi – spi)].30 By multiplying each

measure by negative one, lower values of Permanent and Deferral indicate increased tax

29 Permanent and Deferral are not meant to be a perfect decomposition of CashETR. Instead, Permanent and Deferral are simply intended to shed light on two of the primary types of tax planning strategies that can be used to decrease a firm's CashETR. 30 We substitute txdi for (txdfed + txdfo) when (txdfed + txdfo) is missing.

27

avoidance (just as lower values of CashETR indicate increased tax avoidance). Hypothesis 1

predicts a negative coefficient on Constraint when either Permanent or Deferral are used to

measure tax avoidance.

Panel B of Table 6 presents the results using Permanent and Deferral to proxy for tax

planning. For brevity, the coefficients on control variables are not reported.31 For both tax

planning proxies the coefficients on all constraint measures are negative and significant,

consistent with our main findings (p-values of < 0.0001 with the exception of the regression of

Permanent on Tightening which produces a p-value of 0.0939). These results suggest that firms

use a broad range of tax strategies to reduce cash taxes when faced with financial constraints.

To examine the relative importance of tax planning strategies that result in permanent tax

savings versus deferral-based tax planning strategies, we use seemingly unrelated regression

analysis (untabulated) to compare the magnitudes of the estimated coefficients on the various

financial constraints measures when Permanent is the dependent variable to the analogous

coefficients on the various financial constraint measures when Deferral is the dependent

variable. Focusing first on the macroeconomic measures of financial constraints, we observe

mixed evidence. The coefficient on GDP% is significantly more negative when the dependent

variable is Permanent, suggesting a greater increase in permanent tax strategies relative to

deferral tax strategies. The coefficient on Tightening is significantly more negative when

Deferral is the dependent variable, suggesting a greater increase in deferral tax strategies relative

to permanent tax strategies. Focusing next on the firm-level measures of financial constraints, the

coefficients on RankZ and RankWW are significantly more negative when the dependent variable

is Permanent providing some evidence that managers facing firm-specific financial constraints

31 The coefficients on the control variables are generally consistent with prior research although the signs on some control variables vary depending on the tax planning proxy implemented.

28

focus more on tax planning strategies that result in permanent tax savings.

Overall, it appears that for macroeconomic induced financial constraints, managers

implement tax planning strategies that achieve savings via both permanent and deferral tax

strategies without a strong propensity to implement one method over the other. For firm-level

induced financial constraints, managers achieve tax savings through both deferral and permanent

tax planning strategies but implement permanent tax saving strategies to a greater extent. Given

that financially constrained firms have incentives to increase cash flows as well as earnings for

financial reporting purposes, it is not entirely surprising that more often than not the evidence

suggests that firms attempt to increase tax avoidance via permanent tax planning strategies. In

light of prior research suggesting that managers generally favor tax avoidance strategies that

increase cash flows and lower ETRs (permanent strategies), the general increase in tax savings

via deferral strategies is nevertheless interesting.

6.6. Additional Sensitivity Analyses

In this section we discuss a series of sensitivity tests (untabulated). Our first sensitivity

test examines the role that foreign operations play in our overall results. Multinational firms

(MNCs) face a potentially different set of tradeoffs when making decisions regarding financial

constraints and tax planning. MNCs can face constraints in the U.S., abroad, or globally (i.e.,

both in the U.S. and abroad). A MNC’s response to financial constraint will vary depending on

the source of the constraint. For example, a U.S. MNC could relieve a financial constraint at the

U.S. parent level by repatriating foreign profits held abroad. The repatriation would likely trigger

U.S. taxation on the foreign earnings (taxed at 35% less any available foreign tax credit) but

would result in a net inflow of cash to the U.S. parent. This type of behavior biases against us

finding a negative association between financial constraints and CashETR because repatriations

29

can result in an increase in cash taxes paid but not affect worldwide income, thereby increasing

the firm’s CashETR. Alternatively, it is possible that large MNCs are better able to increase their

tax avoidance behavior during periods of financial constraint through activities such as income

shifting. This behavior could result in drastically different outcomes depending upon the location

of the constraint. For U.S. firms constrained domestically, there is an incentive to shift income

into the U.S. from foreign locations. This could result in an increase in U.S. taxes paid (and

likely total taxes paid given the high statutory U.S. rate) but would alleviate the constraint. In

contrast, a firm facing financial constraints abroad could attempt to shift income out of the U.S.

into foreign locations resulting in a reduction in U.S. taxation but potentially an increase in

foreign taxes (and an uncertain impact on worldwide taxes). Due to data limitations it is difficult

to measure financial constraints and cash taxes at a country level. To ensure that our earlier

results are not solely driven by multinational firms, we perform several additional tests. First,

because our macroeconomic measures capture the economic conditions in the U.S., and our firm

specific measures capture worldwide constraints that are likely driven by constraints at the U.S.

parent company, we attempt to capture tax planning in the U.S. using the FederalETR measure

described in Section 6.4. As previously noted, results using FederalETR are consistent with our

hypotheses. Second, we repeat our analysis on a subsample of our firms that do not report any

foreign pretax income and, as a result, do not suffer from potential jurisdictional mismatching of

financial constraints and tax planning proxies. Inferences from the results using this sample of

domestic firms are largely unchanged from the main analysis.32

32 One particular complication related to multinationals is the choice to designate foreign earnings as permanently reinvested (PRE). When a firm designates foreign earnings as PRE, the firm does not need to record the associated deferred tax expense related to repatriating those earnings. This designation would increase our Deferral measure without actually reducing current period tax payments. In our supplemental analysis of firms that do not report any foreign pretax income, we continue to observe a negative and significant coefficient on all four measures of

30

We also examine the relation between cash tax avoidance and financial constraints using

a changes analysis. The changes analysis controls for any correlated omitted variables that are

stationary through time. In this analysis, we use the annual change in CashETR as our dependent

variable and include changes (rather than levels) of our control variables. For the constraint

measures we use the change in the firm specific measures, RankZ and RankWW, as our test

variables but continue to use the macroeconomic measures, GDP% and Tightening, as previously

defined since these are already measured in changes (i.e., the annual percentage change in GDP

and the change in lending standards). Consistent with our hypotheses, we continue to observe

significant negative coefficients on the constraint measures using this specification.

We also perform a sensitivity test that examines the relation between cash tax avoidance

and both macroeconomic and firm-specific financial constraints simultaneously. To do this, we

include both a macroeconomic constraint measure and a firm-specific constraint measure in our

regression model concurrently. We find significant negative coefficients on both measures

indicating that firms’ cash tax avoidance behavior is incrementally related to both firm specific

and economy wide financial constraints.

Our next two sensitivity tests focus on when financial constraints are measured. Because

it is possible that tax planning strategies undertaken by financially constrained firms take longer

than a year to implement, we first repeat our analysis using the two year lag of our constraint

measures (i.e., we measure Constraint in year t-2) and observe results that are qualitatively and

quantitatively similar to those reported in the main analysis.

In our second timing sensitivity test, we measure Constraint in year t. Our original

research design, which measures Constraint in year t-1, implicitly assumes that managers do not

constraint when Deferral is the dependent variable. This gives comfort that the PRE designation is not driving our main Deferral results.

31

anticipate that their firms will become financially constrained. The insider trading literature,

however, provides evidence that managers do understand how profitable their firms will be for

several years into the future (see, for example, Piotroski and Roulstone 2004). If managers are

able to anticipate impending financial constraints, they will likely take actions to increase cash

flows in the periods of financial constraint. This foresight by managers is more likely to apply to

firm-specific financial constraints than macroeconomic constraints (as that would require

foresight into macroeconomic cycles which, as the financial crisis indicates, is difficult). We

repeat our analysis using both firm-specific constraints and CashETR in year t and observe

significant negative coefficients on our firm-specific measures of financial constraint. These

results are consistent with managerial foresight for firm-specific financial constraints. When we

repeat our analysis using both macroeconomic constraints and CashETR in year t, we observe

significant negative coefficients on only one of the two macroeconomic measures. These results

support the notion that managers have greater foresight for future firm conditions but less

foresight for macroeconomic conditions.

An additional potential concern with our research design is that our observed findings,

particularly in the case of the macroeconomic tests, are the result of government tax relief during

times of economic hardship. The most prominent example of such relief during our sample

period is the bonus depreciation provisions that were implemented during the 2000s.33 To control

for this possibility we create an indicator variable Bonus equal to one for years with bonus

depreciation and zero otherwise. We then interact Bonus with capital expenditures (as bonus

depreciation only applies to firms that make new capital expenditures during those time

33 The U.S. Government instituted bonus depreciation tax relief through various legislation covering assets purchased from September 10, 2001 through December 31, 2004; and January 1, 2008 through December 31, 2010.

32

periods).34 This approach effectively allows the impact of capital expenditures on cash taxes to

vary in years with bonus depreciation in place. Regression results obtained after including the

Bonus*CapEx interaction term are qualitatively and quantitatively similar to those reported in the

main analysis. When performing this sensitivity test, we do not include the Bonus main effect.

Because bonus depreciation rules are enacted during periods of macroeconomic financial

constraint, including Bonus in equation (1) effectively results in two financial constraint

measures, one indicator (Bonus) and one continuous measure (Constraint), being simultaneously

included in the regression model. In fact, the correlations between our macroeconomic financial

constraint proxies and the bonus depreciation indicator are all greater than 0.35. As an alternative

test we drop Constraint and include the Bonus main effect as our measure of financial constraint.

Doing so results in a negative and significant coefficient on Bonus which is consistent with the

hypothesis that firms decrease CashETRs in times of financial constraint.

6.7. Impact of tax planning on corporate tax revenues during the financial crisis

In this section, we illustrate the impact of tax planning on government revenues during

2009, the height of the financial crisis. Based on our regression results, cash ETRs would be 3%

lower. Using the tax base from all profitable C-corporations in 2008 from the IRS Statistics of

Income Tax Stats website, this would represent a reduction in government revenue of $24 billion

or 13% of total income taxes after credits from all profitable C-corporations.35

34 Note, the Compustat data item capex does not capture assets purchases that are eligible for bonus depreciation perfectly (for example, capital expenditures by foreign subsidiaries do not quality). Unfortunately we are not aware of an alternative publicly available proxy that would capture this more precisely. We repeated this analysis excluding firms with foreign operations to mitigate this concern. Results are consistent with those in the broader sample. 35 Cash ETR change is calculated by multiplying the regression coefficient on GDP% by the change in real GDP during 2009 (-0.8251 x -0.035 = 3%). Data in this subsection are from the IRS Statistics of Income Tax Stats website (SOI), available at http://www.irs.gov/taxstats/article/0,,id=170728,00.html. The revenue reduction of $24 billion is calculated as 3% x $816 billion 2009 tax base. The 13% is calculated as $24 billion divided by $182 billion income taxes after credits from all profitable C-corporations.

33

The discussion and calculations above are based on the regression estimates obtained

from our tests. As a simple check on the reasonableness of our estimate, we obtain an alternative

estimate of the effect of tax planning using the raw SOI data from the IRS. From 2008 to 2009,

the tax base – total income subject to tax – for all profitable C-corporations fell at a rate of 10%

from $910 billion to $816 billion, a $94 billion decrease. At the same time total income tax after

credits fell at an even faster rate of 12% from $207 billion to $182 billion. The change in the tax

base of $94 billion is likely primarily due to the deterioration of macroeconomic conditions

during the financial crisis and, possibly to a lesser extent, due to an increase in tax planning by

firms. We calculate an effective tax rate using the SOI data by dividing “Total income tax after

credits” by “Income subject to tax.” In 2009, the ETR decreased by 1% from 23% ($207/910) in

2008 to 22% ($182/$816) in 2009. The change in effective tax rate of 1% is likely attributable to

an increase in tax planning by firms as financial resources became more scarce. In our analysis

we control for a number of other factors that could also impact the tax planning activities of

firms but the estimate we obtain from our regression models, 3%, is comparable to the

unadjusted rate reduction of 1% observed in the IRS data.

7. Conclusion

The extant academic literature examining the determinants of firms’ tax planning

activities focus almost exclusively on firm-level characteristics (for a review of the literature see

Shackelford and Shevlin 2001 and Hanlon and Heitzman 2010) and more recently on the impact

of specific executives (Dyreng, Hanlon, and Maydew 2010; Armstrong, Blouin, and Larcker

2012). In this study, we extend this literature and are one of the first to investigate whether

macroeconomic factors also affect firm-level tax avoidance behavior. The factor of interest in

this study, financial constraints, can impact a firm as a result of its own circumstances or as a

34

result of macroeconomic conditions.

In this study, we take a broad view of financial constraint and define a firm as more

financially constrained if it experiences an increase in the cost of external financing or an

increase in the difficulty of accessing external funds. The financing need and the resulting

constraint can arise from a variety of sources. We focus on two major sources of the financing

need: investment opportunities and financial distress. Firms with unfunded investment

opportunities require additional cash in order to finance those additional investments. Firms in

financial distress require additional cash in order to finance existing operations and remain

solvent. For both of these sources of financing need, the financially constrained firm needs

additional financing through the least costly source available. As such, financially constrained

firms are likely to search for new sources of internal funds. In this study, we investigate the

association between financial constraints, at both the macroeconomic and firm-specific level, and

a significant source of internal funds available to firms – cash tax savings, or more generally tax

avoidance.

We document results consistent with our predictions, firms facing either macroeconomic

financial constraints or firm-specific financial constraints exhibit lower near-term cash ETRs.

The reduction in cash ETR is also economically significant. Based on macroeconomic measures

of constraint (change in GDP and bank lending tightening) cash ETRs are approximately 2%

lower following periods of financial constraint. Based on firm-level measures of constraint (the

decile rank of both the Altman Z-score and Whited and Wu 2006 financial constraint index),

cash ETRs are approximately 2% lower for financially constrained firms.

In addition to documenting an association between both macroeconomic and firm-level

financial constraints and near-term cash ETRs, we examine whether the decrease in cash ETRs is

35

the result of permanent and/or deferral-based tax planning strategies. We find firms increase the

level of tax planning via both permanent and deferral-based strategies following periods of

financial constraint. Several recent studies have documented evidence consistent with managers

focusing on tax avoidance behavior that first and foremost reduces the tax expense accrued on

the financial statements with less concern on the actual cash flow savings (or deferral) generated

by the tax strategies (e.g., Graham, Hanlon, Shevlin, and Shroff 2012). Our study provides

evidence that there are some instances that increase managers’ focus on cash tax savings

regardless of the potential financial reporting benefits.

The findings of this study are potentially of interest for several reasons. First, we

contribute to the growing literature on the determinants of firms’ tax avoidance behavior.

Second, this study also contributes to the broad literature on financial constraints. Third, this

study informs the debate related to the relative importance of tax planning activities generating

cash flow savings versus financial reporting benefits. Finally, given the record high level of the

federal deficit and current economic conditions, it is important to understand the interplay

between macroeconomic forces and firm-level tax avoidance behavior as legislators look for

ways to reduce the federal deficit.

36

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39

Appendix A

Variable definitions and construction

Variable Definition

Tax measures CashETR the ratio of cash taxes paid to pretax income adjusted for special items (txpd/(pi – spi)) CurrentETR the ratio of the current income taxes to pretax income adjusted for special items [txc/(pi -

spi)] FederalETR the ratio of the current federal income taxes to domestic pretax income (txfed/pidom) Permanent negative one multiplied by the U.S. statutory rate less the ratio of total tax expense to pretax

income adjusted for special items [-1*(35% - txt/(pi – spi))] Deferral negative one multiplied by the ratio of deferred tax expense to pretax income adjusted for

special items [-1*(txdfed + txdfo)/(pi – spi); if missing (txdfed + txdfo), then (-1*txdi/(pi – spi)]

Financial constraints GDP% negative one multiplied by the annual percentage change in GDP (measured in chained 2005

dollars) measured at the end of firm i’s fiscal year t. This data is from the Bureau of Economic Analysis (http://www.bea.gov/national/index.htm#gdp)

Tightening the average net percentage of domestic respondents to the Federal Reserve Board’s Senior Loan Officer Opinion Survey reporting tightening standards in year t-1 for commercial and industrial loans. Tightening is the percentage reporting tightening minus the percentage reporting loosening. Positive (negative) values indicate tightening (loosening) of standards

Z-Score the Altman (1968) Z-score calculated as 3.3*[(pi +xint)/at] + 1.2*(wcap/at) + (sale/at) + 1.4*(re/at) + 0.6*[(chso*prcc_f)/lt]

WW the Whited and Wu (2006) financial constraints index calculated as −0.091*cfo − 0.062*(1 if dv>0, 0 otherwise) + 0.021 *(dltt/at) − 0.044[ln(at)] − 0.035*[(salet-salet-1)/salet-1)]

RankZ the decile rank of the firm’s Altman (1968) Z-score in year t-1

RankWW the decile rank of the firm’s Whited and Wu (2006) level of financial constraints in year t-1

Tax planning opportunities PROA the ratio of pretax income adjusted for special items to total assets (pi-spi/at)

Size the natural logarithm of total assets (at)

Foreign the absolute value of the ratio of pretax foreign income to total pretax income (|pifo/pi|); if missing pretax foreign income, foreign pretax income is set equal to zero

Leverage the ratio of total debt to total assets ((dltt+dlc)/at)

CapEx the ratio of capital expenditures to total assets (capx/at)

R&D the ratio of R&D expense to total revenues (xrd/sale)

DiscAccruals discretionary accruals computed at the end of the year estimated using a modified Jones' model (Kothari, Leone, and Wasley 2005)

NOL an indicator variable if the firm reported a net operating loss (tlcf) in any of the last three years and zero otherwise

BM the ratio of the book value of equity to the market value of equity (ceq/(csho*prcc_f))

Loss an indicator variable equal to one if adjusted pretax income is negative [(pi – spi)<0] and zero otherwise

Bonus an indicator variable equal to one for years with bonus depreciation and zero otherwise. The U.S. Government instituted bonus depreciation tax relief through various legislation covering investment assets purchased between from September 10, 2001 through December 31, 2004; and January 1, 2008 through December 31, 2010

40

Table 1

Sample Selection

Data Restrictions N

Starting Compustat sample of non-regulated firms reporting positive pretax income 93,348

Less firms without data necessary to compute tax measures:

Firms missing data necessary to compute tax measures -25,390

Less firms missing data necessary to compute control variables -12,402

Less firms missing data necessary to compute firm-level financial constraint measures: -11,228

Primary firm-level financial constraint sample 44,328

Samples with additional financial constraint restrictions:

Sample with GDP% 44,328

Sample with Tightening 37,290

Detailed variable definitions are presented in Appendix A.

41

Table 2

Descriptive Statistics

Variable N Mean StdDev P10 Q1 Median Q3 P90

Tax Measures

CashETR 44,328 0.2613 0.2428 0.0160 0.1154 0.2610 0.3721 0.4950

Macroeconomic Financial Constraint Measures

GDP% 44,328 -0.0275 0.0173 -0.0446 -0.0399 -0.0307 -0.0201 -0.0066

Tightening 37,290 6.476 20.632 -14.500 -7.975 -0.638 18.188 40.425

Firm-Level Financial Constraint Measures

Z-Score 44,328 5.3122 8.9165 1.5961 2.4612 3.7005 5.7177 9.6515

WW 44,328 -0.2948 0.3096 -0.4311 -0.3630 -0.2866 -0.2162 -0.1586

Control Variables

PROA 44,328 0.1060 0.0720 0.0272 0.0534 0.0909 0.1428 0.2047

Size 44,328 5.6816 1.9670 3.1587 4.2429 5.5923 7.0190 8.3351

Foreign 44,328 0.1543 0.2808 0.0000 0.0000 0.0000 0.1817 0.6126

Leverage 44,328 0.2088 0.1748 0.0000 0.0486 0.1905 0.3247 0.4476

CapEx 44,328 0.0636 0.0594 0.0129 0.0244 0.0458 0.0809 0.1341

R&D 44,328 0.0275 0.0508 0.0000 0.0000 0.0000 0.0305 0.0997

DiscAccr 44,328 -0.0029 0.1375 -0.1532 -0.0655 -0.0011 0.0636 0.1476

NOL 44,328 0.2812 0.4496 0.0000 0.0000 0.0000 1.0000 1.0000

BM 44,328 0.5958 0.4358 0.1804 0.3029 0.4907 0.7694 1.1326

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels.

42

Table 3

Correlation Table

Variable (1) (2) (3) (4) (5)

(1) CashETR 1.000 -0.0509 -0.0639 -0.1351 -0.0909

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001)

(2) GDP% -0.0595 1.000 0.6214 0.0486 -0.0763

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001)

(3) Tightening -0.0634 0.4268 1.000 0.0847 -0.053

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001)

(4) RankZ -0.2041 0.0323 0.0754 1.000 -0.0919

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001)

(5) RankWW -0.1278 -0.0612 -0.0359 -0.0948 1.000

(<0.0001) (<0.0001) (<0.0001) (<0.0001) (<0.0001)

Pearson (Spearman) correlations are presented above (below) the diagonal. Detailed variable definitions are presented in Appendix A. All continuous variables are winsorized at the 1st and 99th percentiles.

43

Table 4

The Relationship Between Financial Constraints and Tax Planning

Panel A: Macroeconomic Financial Constraints

CashETR

GDP% Tightening

Coeff. Coeff.

Variable Pred. (p-value) (p-value)

Intercept ? 0.2277 0.2343

(<0.0001) (<0.0001)

Constraint - -0.8251 -0.0007

(<0.0001) (<0.0001)

PROA + 0.2009 0.2395

(<0.0001) (<0.0001)

Size ? 0.0025 0.0028

(0.0071) (0.0057)

Foreign ? 0.0666 0.0588

(<0.0001) (<0.0001)

Leverage - -0.0611 -0.0623

(<0.0001) (<0.0001)

CapEx - -0.0105 -0.0168

(0.3400) (0.2741)

R&D - -0.3487 -0.3547

(<0.0001) (<0.0001)

DiscAccruals - 0.0507 0.0385

(<0.0001) (<0.0001)

NOL - -0.0736 -0.0652

(<0.0001) (<0.0001)

BM ? 0.0308 0.0330

(<0.0001) (<0.0001)

Industry FE Yes Yes

Adj R2 0.0530 0.0534

N 44,328 37,290

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels. Regression models include untabulated industry fixed effects. Huber-White robust standard errors clustered by firm are used to control for heteroscedasticity and serial correlation.

44

Table 4 (continued)

The Relationship Between Financial Constraints and Tax Planning

Panel B: Firm-level Financial Constraints

CashETR

RankZ RankWW

Coeff. Coeff.

Variable Pred. (p-value) (p-value)

Intercept ? 0.3057 0.4856

(<0.0001) (<0.0001)

Constraint - -0.0182 -0.0202

(<0.0001) (<0.0001)

PROA + 0.0195 0.1514

(0.4380) (<0.0001)

Size ? 0.0037 -0.0242

(<0.0001) (<0.0001)

Foreign ? 0.0705 0.0642

(<0.0001) (<0.0001)

Leverage - 0.0775 -0.0459

(<0.0001) (<0.0001)

CapEx - -0.0546 -0.0176

(0.0153) (0.2455)

R&D - -0.4499 -0.2691

(<0.0001) (<0.0001)

DiscAccruals - 0.0274 0.0564

(0.0007) (<0.0001)

NOL - -0.0663 -0.0717

(<0.0001) (<0.0001)

BM ? 0.0469 0.0325

(<0.0001) (<0.0001)

Industry FE Yes Yes

Adj R2 0.0723 0.0600

N 44,328 44,328

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels. Regression models include untabulated industry fixed effects. Huber-White robust standard errors clustered by firm are used to control for heteroscedasticity and serial correlation.

45

Table 5

The Relationship Between Financial Constraints and Tax Planning

Panel A: Macroeconomic Financial Constraints; Profit and Loss Firms Included

CashETR

GDP% Tightening

Coeff. Coeff.

Variable Pred. (p-value) (p-value)

Intercept ? 0.2460 0.2517

(<0.0001) (<0.0001)

Constraint - -0.8599 -0.0008

(<0.0001) (<0.0001)

Loss*Constraint + 2.4388 0.0035

(<0.0001) (<0.0001)

PROA + 0.0263 0.0825

(0.3009) (0.0025)

Loss ? -0.4115 -0.4944

(<0.0001) (<0.0001)

Size ? 0.0020 0.0022

(0.0268) (0.0240)

Foreign ? 0.0561 0.0496

(<0.0001) (<0.0001)

Leverage - -0.0771 -0.0766

(<0.0001) (<0.0001)

CapEx - -0.0051 -0.0072

(0.4209) (0.3967)

R&D - -0.2816 -0.2862

(<0.0001) (<0.0001)

DiscAccruals - 0.0404 0.0290

(<0.0001) (0.0017)

NOL - -0.0703 -0.0632

(<0.0001) (<0.0001)

BM ? 0.0175 0.0209

(<0.0001) (<0.0001)

Yes Yes

Adj R2 0.1966 0.1926

N 47,006 39,451

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels. Regression models include untabulated industry fixed effects. Huber-White robust standard errors clustered by firm are used to control for heteroscedasticity and serial correlation.

46

Table 5 (continued)

The Relationship Between Financial Constraints and Tax Planning

Panel B:Firm-level Financial Constraints; Profit and Loss Firms Included

CashETR

RankZ RankWW

Coeff. Coeff.

Variable Pred. (p-value) (p-value)

Intercept ? 0.3426 0.5062

(<0.0001) (<0.0001)

Constraint - -0.0201 -0.0204

(<0.0001) (<0.0001)

Loss*Constraint + 0.0190 0.0059

(<0.0001) (0.0540)

PROA + -0.2242 -0.0274

(<0.0001) (0.2838)

Loss ? -0.6062 -0.5200

(<0.0001) (<0.0001)

Size ? 0.0034 -0.0244

(0.0001) (<0.0001)

Foreign ? 0.0607 0.0526

(<0.0001) (<0.0001)

Leverage - 0.0568 -0.0641

(<0.0001) (<0.0001)

CapEx - -0.0533 -0.0143

(0.0168) (0.2872)

R&D - -0.3707 -0.2065

(<0.0001) (<0.0001)

DiscAccruals - 0.0172 0.0464

(0.0279) (<0.0001)

NOL - -0.0631 -0.0684

(<0.0001) (<0.0001)

BM ? 0.0293 0.0188

(<0.0001) (<0.0001)

Yes Yes

Adj R2 0.2129 0.2012

N 47,006 47,006

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels. Regression models include untabulated industry fixed effects. Huber-White robust standard errors clustered by firm are used to control for heteroscedasticity and serial correlation.

47

Table 6

The Relationship Between Financial Constraints and Tax Planning

Panel A: Alternative Measures of Tax Planning

GDP% Tightening RankZ RankWW

Coeff. Coeff. Coeff. Coeff.

Dependent Variable Pred. (p-value) (p-value) (p-value) (p-value)

CurrentETR - -0.8090

-0.0007

-0.0125

-0.0107

(<0.0001) (<0.0001) (<0.0001) (<0.0001)

FederalETR -

-0.6863

-0.0007

-0.0175

-0.0097

(<0.0001) (<0.0001) (<0.0001) (<0.0001)

Panel B: Permanent and Deferral Based Strategies

GDP% Tightening RankZ RankWW

Coeff. Coeff. Coeff. Coeff.

Dependent Variable Pred. (p-value) (p-value) (p-value) (p-value)

Permanent -

-0.5022

-0.0001

-0.0059

-0.0084

(<0.0001)

(0.0939)

(<0.0001)

(<0.0001)

Deferral - -0.2508 -0.0005

-0.0056

-0.0029

(<0.0001) (<0.0001)

(<0.0001)

(0.0010)

Detailed variable definitions are presented in Appendix A. All continuous variables are winsorised at the 1 and 99 percent levels. Each line represents the coefficients on the various constraint measures from regression model (1). Control variables, including industry fixed effects are untabulated for brevity. Huber-White robust standard errors clustered by firm are used to control for heteroscedasticity and serial correlation.