THE ACCOUNTING REVIEW American Accounting Association Vol. 88, No. 5 DOI: 10.2308/accr-50496 2013 pp. 1657–1682 Tax-Motivated Loss Shifting Merle M. Erickson The University of Chicago Shane M. Heitzman University of Rochester X. Frank Zhang Yale University ABSTRACT: This paper examines the implications of tax loss carryback incentives for corporate reporting decisions and capital market behavior. During the 1981 through 2010 sample period, we find that firms increase losses in order to claim a cash refund of recent tax payments before the option to do so expires, and we estimate that firms with tax refund-based incentives accelerate about $64.7 billion in losses. Tax-motivated loss shifting is reflected in both recurring and nonrecurring items and is more evident for financially constrained firms. Analysts do not generally incorporate tax-motivated loss shifting into their earnings forecasts, resulting in more negative analyst forecast errors for firms with tax-based incentives than for firms without. Holding earnings surprises constant, however, investors react less negatively to losses reported by firms with tax loss carryback incentives. Keywords: taxes; net operating losses; liquidity; analyst forecasts; capital markets. Data Availability: Data are available from sources identified in the paper. I. INTRODUCTION T ax rules give the firm an option to obtain a cash refund of recently paid taxes by reporting a tax loss. This cash infusion can be particularly valuable for financially constrained firms. In fact, the purported liquidity benefits of these tax loss ‘‘carrybacks’’ played a central role in at least two attempts to stimulate the business sector during the past decade, and refunds of We appreciate comments from John Harry Evans III (senior editor), two anonymous referees, and workshop participants at the National University of Singapore, Singapore Management University, Yale University, and the Iowa Tax Readings Group. Professor Erickson appreciates the financial support of the Booth School of Business. Editor’s note: Accepted by John Harry Evans III. Submitted: January 2012 Accepted: April 2013 Published Online: April 2013 1657
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THE ACCOUNTING REVIEW American Accounting AssociationVol. 88, No. 5 DOI: 10.2308/accr-504962013pp. 1657–1682
Tax-Motivated Loss Shifting
Merle M. Erickson
The University of Chicago
Shane M. Heitzman
University of Rochester
X. Frank Zhang
Yale University
ABSTRACT: This paper examines the implications of tax loss carryback incentives for
corporate reporting decisions and capital market behavior. During the 1981 through 2010
sample period, we find that firms increase losses in order to claim a cash refund of recent
tax payments before the option to do so expires, and we estimate that firms with tax
refund-based incentives accelerate about $64.7 billion in losses. Tax-motivated loss
shifting is reflected in both recurring and nonrecurring items and is more evident for
financially constrained firms. Analysts do not generally incorporate tax-motivated loss
shifting into their earnings forecasts, resulting in more negative analyst forecast errors
for firms with tax-based incentives than for firms without. Holding earnings surprises
constant, however, investors react less negatively to losses reported by firms with tax
loss carryback incentives.
Keywords: taxes; net operating losses; liquidity; analyst forecasts; capital markets.
Data Availability: Data are available from sources identified in the paper.
I. INTRODUCTION
Tax rules give the firm an option to obtain a cash refund of recently paid taxes by reporting a
tax loss. This cash infusion can be particularly valuable for financially constrained firms. In
fact, the purported liquidity benefits of these tax loss ‘‘carrybacks’’ played a central role in
at least two attempts to stimulate the business sector during the past decade, and refunds of
We appreciate comments from John Harry Evans III (senior editor), two anonymous referees, and workshop participantsat the National University of Singapore, Singapore Management University, Yale University, and the Iowa Tax ReadingsGroup. Professor Erickson appreciates the financial support of the Booth School of Business.
Editor’s note: Accepted by John Harry Evans III.
Submitted: January 2012Accepted: April 2013
Published Online: April 2013
1657
corporate tax payments by the federal government exceeded $95 billion in both 2009 and 2010.1 In
this paper, we address the accounting and economic consequences of allowing firms to carry back
tax losses. Specifically, we investigate whether firms increase their reported tax losses to obtain
cash refunds of prior tax payments, whether financial analysts anticipate the effect of these tax
incentives on reported earnings, and how investors respond to the earnings news for firms with
tax-based incentives to report losses.
U.S. tax law limits corporate tax refunds to the taxes paid in the most recent (currently two) years.
Thus, for taxes paid on profits in year t�2, year t is generally the last year the firm can claim a refund of
those taxes. To reduce the firm’s expected tax liability, and therefore increase the firm’s after-tax cash
flow, the manager will often have an incentive to report tax losses in year t to maximize the cash refund
of taxes paid on income in t�2. When the firm exhausts its capacity to carry a loss back to get a refund,
or delays recognizing a tax loss altogether, liquidity benefits disappear and the economic value of the
tax loss is discounted because of uncertainty and the time value of money.2
Our study complements and extends other research that focuses on corporate and market
responses to the Tax Reform Act of 1986 (TRA 86). The significant decline in corporate marginal
tax rates resulting from TRA 86 created strong incentives for managers to accelerate losses (Scholes
et al. 1992; Guenther 1994; Maydew 1997) so that the losses would apply under the higher tax rates
and thus reduce current taxes by a larger amount. Tax rate shifts of that magnitude are infrequent, so
evidence on the influence of loss-shifting incentives when statutory tax rates are relatively constant,
as in the last 25 years in the U.S., is important. A firm experiencing a negative economic shock will
often be in a position to decide between accelerating the recognition of a loss for a certain and
immediate cash refund or deferring the recognition of the loss for an uncertain and discounted tax
benefit. These negative shocks can be idiosyncratic or systematic, as in times of recession, and thus
tax-based incentives for accelerating tax losses represent a pervasive issue for managers, policy
makers, and capital market participants.
Each year we identify a set of firms in a position to recognize a tax loss in the current period
that would provide a cash refund of prior tax payments that otherwise would be lost after year-end.
These are firms that (1) paid income taxes on profits in the earliest carryback year that have not yet
been refunded, and (2) are expected to report a loss in the current year. The first condition ensures
that there is actually a cash refund available. The second condition narrows our focus to those firms
with expected benefits from tax-motivated loss shifting.
We find that firms with tax-motivated loss-shifting incentives report significantly larger losses
than a comparison sample of firms that are also expected to report a loss but do not have access to a
potential cash tax refund. The loss equates to 11.25 percent lower reported earnings for the average
loss firm with carryback incentives versus comparable firms and implies that incentives for
tax-motivated loss shifting play an important role in reported earnings. These accelerated losses
1 A comment letter from Financial Executives International to congressional leaders dated January 13, 2009stated, ‘‘Extending the carryback period to five years will enhance liquidity of businesses with current losses,while helping to insulate against future losses. This provides companies with more capital to make investmentsthat will help move the economy forward.’’ In a speech on the floor of the Senate on November 3, 2009, SenatorPatty Murray of Washington State argued that the Worker, Homeownership, and Business Assistance Act of2009 ‘‘would also provide a critical boost to businesses . . . by extending their ability to carry back losses they’vesuffered in 2008 or 2009. This tax provision will provide badly needed capital to help companies avoid layoffs,expand their operations, and create jobs.’’ See also Leone (2010).
2 The uncertainty in the tax loss carryforward is driven by uncertainty about future taxable income and thepossibility that a future ownership change will put a binding constraint on the firm’s ability to use thesecarryforwards. With respect to the latter, a number of firms have adopted so-called ‘‘NOL poison pills’’ designedto prevent the constraint triggered by Section 382 of the Internal Revenue Code, which limits tax loss usagefollowing a change in ownership (Erickson and Heitzman 2010). Section 382 concerns increase the incentive toaccelerate tax losses.
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reduce operating income and increase one-time losses. In addition, we find that financially
constrained firms more aggressively accelerate losses to obtain cash refunds. This result supports
the idea that these firms view tax refunds as an important source of cash and implies that liquidity
benefits outweigh the incremental direct and indirect costs of accelerating the tax loss.
We then investigate whether and how financial analysts account for these incentives when
forecasting earnings. A large body of literature argues that analysts are sophisticated and that their
forecasts are a reasonable proxy for market expectations.3 However, studies based on financial
reporting and tax law ‘‘events’’ suggest that analysts often do not fully utilize the information in tax
footnote disclosures (Amir and Sougiannis 1999) and have difficulty incorporating the predictable
effects of tax law changes (Chen and Schoderbek 2000; Plumlee 2003; Shane and Stock 2006). We
expand upon these studies by not constraining our analysis to one-time events. Although managers
respond to tax-loss reporting incentives in predictable ways, we find that analysts do not incorporate
these incentives into their earnings forecasts.4 Analysts’ forecasts are significantly less precise for firms
with tax incentives to shift losses than for comparable loss firms without these tax incentives. These
results are not driven by systematic differences in the measurement of forecasted and actual earnings.
Finally, we evaluate how investors react to the earnings of firms with incentives to accelerate
tax losses. Although these firms tend to have negative earnings surprises based on past earnings and
analyst forecasts, the market’s reaction to the news is less negative for those firms with incentives to
accelerate tax losses. This result implies that investors recognize the value inherent in tax-motivated
loss shifting. The results suggest that tax-motivated losses represent positive decisions by managers
to increase firm value in the presence of potential contracting and financial reporting consequences.
To put the main results of our paper in context, consider homebuilder Lennar Corporation.5 In
fiscal years 2005 and 2006, current tax expense figures indicate that Lennar incurred federal and
state income tax liabilities of $805 million and $547 million, respectively. Thus, 2007 was the last
year Lennar could claim a refund for the $805 million of taxes paid in 2005. Faced with a continued
decline in the homebuilding sector, Lennar took several actions to generate tax losses at the end of
2007, which was two years before the temporary extension of the loss carryback window. For
example, in the final month of the 2007 fiscal year, Lennar sold land to a partnership they formed
with Morgan Stanley, generating an $800 million tax loss for Lennar (Lennar 10-K). Lennar also
wrote off $530 million in deposits and pre-acquisition costs for building lots the company decided
not to pursue. According to the CEO of Lennar, ‘‘As a by-product of our strategic fourth quarter
3 See Brown et al. (1986), O’Brien (1987), and Doyle et al. (2006). During the earnings season, Wall Streettypically compares a firm’s reported earnings with analysts’ most recent forecasts to assess earnings surprises.Prior research concludes that similar patterns between analyst forecast errors and stock returns also support thisassumption. For example, Sloan (1996) shows that high-accrual firms have lower future stock returns, whereasBradshaw et al. (2001) find that high-accrual firms have overly optimistic earnings forecasts. Zhang (2006a)shows that investors underreact more to new information in cases of greater information uncertainty, whereasZhang (2006b) finds a similar pattern for analysts.
4 The results are consistent with the idea that analysts either do not have the ability to incorporate the tax-motivated loss shifting or that analysts understand such corporate reporting behavior but choose not toincorporate it in their earnings forecasts. Our evidence is more consistent with the first view. In Table 4, we findanalyst forecast errors are more negative for firms with carryback incentives. In the ‘‘Analyst Revisions of FutureEarnings’’ section, we find that analysts gradually incorporate the effect of NOL-related loss shifting in theirforecasts of current year’s earnings while keeping next year’s forecasts relatively unchanged.
5 While Lennar’s numbers may be unusually large, such strategic choices and corporate decisions are likely toapply to other companies, a phenomenon that underpins the key point of the paper. For example, one weekfollowing the passage of the five-year carryback window on November 6, 2009, William Lyon Homes revealedin the company’s 10-Q filing that, ‘‘In considering ways to maximize such tax refund, the Company isdetermining whether to elect to defer certain cancellation of indebtedness income generated from its repurchaseof Senior Notes during 2009.’’ The company subsequently recorded losses through the sale of assets, and by theend of fiscal year 2009 expected a federal income tax refund of $101.8 million. This would nearly double thefirm’s cash balance. See also Leone (2010).
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moves, we have generated losses that have resulted in the receipt of a cash tax refund of $852
million subsequent to the close of the quarter’’ (press release, January 24, 2008).6 The week before
earnings were released, analysts forecasted losses ranging from $0.00 to $4.45 per share, with an
average expected loss of $1.84 per share. Lennar surprised analysts by reporting a loss of nearly
$7.92 per share. With 159.9 million shares outstanding, this translates to an unexpected accounting
loss of nearly $972 million. Nevertheless, the market reacted positively to the news, with Lennar’s
three-day stock return around the earnings announcement date exceeding 25 percent, reflecting a
$493 million increase in market value.
Our study’s first contribution is to provide evidence that firms accelerate tax losses to obtain
cash inflows through refunds of prior tax payments, even when statutory tax rates are constant. We
show that this tax-motivated loss shifting is reflected in both recurring and nonrecurring items and
is more pronounced for financially constrained firms. To our knowledge, this paper is one of the
first to link liquidity demands to tax and financial reporting decisions. Second, we provide a broader
examination of the capital market implications of tax loss carryback incentives. We find that
analysts do not incorporate tax loss carryback incentives into their earnings forecasts, yet
stockholders react less negatively to reported losses when firms have tax incentives to accelerate
losses. Taken together, our evidence provides new insight on how managers and capital market
participants incorporate tax-based incentives to accelerate losses into their decision-making. Our
evidence is also relevant to understanding the growing importance of tax losses on firm value, as tax
losses are becoming increasingly important for fiscal and corporate policy decisions (Graham and
Kim 2009; Erickson and Heitzman 2010). Overall, our evidence suggests that the tax-based
incentive to accelerate reported losses plays a material and persistent role in corporate reporting
decisions and capital market activities.
Section II next reviews prior literature and develops hypotheses. Section III describes the data
and provides summary statistics. Section IV presents the results. Section V provides a variety of
additional analyses, and Section VI concludes.
II. PRIOR LITERATURE AND HYPOTHESIS DEVELOPMENT
Managers have incentives to reduce the firm’s total tax liability over the life of the firm because
a dollar less paid to the tax authority is a dollar more for shareholders. Moreover, firms face
asymmetric tax treatment of profits and losses because taxes are paid immediately on profits, but
taxes are not necessarily refunded on losses. This means that a firm with zero expected pretax
income will still have a positive expected tax liability that is increasing in income uncertainty
(Scholes et al. 2008, 172). Thus, Graham and Smith (1999) show that firms facing such a convex
tax schedule have incentives to hedge in order to reduce expected tax liabilities.
Net operating loss provisions contained in the tax code partially mitigate this asymmetry. To
illustrate, a firm that paid taxes in the recent past can claim a refund of those taxes in a year in which
it reports a loss. This is achieved through tax loss carryback rules that allow the firm to use its tax
loss in the current year to reduce taxable income in a prior tax year (i.e., a carryback of the current
tax loss for a refund of prior tax payments), starting with the earliest tax year of the carryback
period. Put differently, when the firm pays taxes on income, it effectively gets an option to claim a
refund of those taxes that expires after the length of the carryback window, T. This option gives
some firms an incentive to accelerate their losses to generate cash flow through a refund of prior tax
6 These tax losses were also reflected in Lennar’s financial statements, albeit in a somewhat different form. Thetransaction was treated as a sale for tax purposes, but not for GAAP purposes, because Lennar retained 50percent of the voting rights in the partnership. In Lennar’s financial statements, the decline in the value of theseassets was recorded, but as an asset impairment rather than as a loss on sale.
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payments because otherwise the option will expire. For example, assume the loss carryback period
(T) is two years. If a firm paid taxes on profits in year t�2 and those taxes have not been refunded
through losses in year t�1, then the firm will have an incentive to accelerate losses into year t in
order to maximize a refund of taxes paid in year t�2. If the firm did not report taxable income in a
recent year, or there is no tax to be refunded, then it can carry the current year’s tax loss forward and
use it to reduce taxable income in a future year. For example, a startup firm with accumulated losses
cannot claim a refund of taxes they have not paid. Current tax losses are carried forward to reduce
taxable income if and when the firm becomes profitable. If the firm does not generate enough future
taxable income to use the loss before the carryforward period expires, then the loss expires unused.
An accelerated tax loss reduces current year taxes, and if the loss is large enough, leads to a
cash refund. But for the profitable firm this strategy will only increase the tax liability in the
following period. Because consistently profitable firms face more symmetric tax treatment, they
derive fewer benefits from accelerating losses (Graham and Smith 1999). Thus, the present value of
the cash tax benefit from accelerating a loss is strongest if the firm is already in a tax loss position
(that is, before considering the tax incentives to report additional losses) and does not expect to
immediately return to profitability. These firms obtain immediate and certain tax benefits by
accelerating the recognition of the loss to recoup prior tax payments and face uncertain and
discounted tax benefits if they do not. The benefit of accelerating those losses to generate cash flows
is therefore stronger when the firm expects losses in future periods as well.
Shifting a tax loss to generate a refund requires the manager to alter real decisions, reporting
decisions, or both. Since the incremental benefit of the refund must be weighed against the
incremental cost to shareholders, the expected tax benefits could go unclaimed if accelerating a loss:
(1) involves costly real actions—such as disposing of productive assets or deferring sales, (2)
generates financial reporting costs—such as violating a debt covenant, or (3) increases the taxing
authority’s scrutiny of the firm’s tax positions.7 Thus, whether the incentive to accelerate a tax loss
has a material effect on corporate reporting and capital market activity is an open question.
The incentives for tax-motivated loss shifting increase when the marginal tax rate during the
carryback window exceeds the expected marginal tax rate during current and future periods. Prior
research examines firms’ reporting behavior around TRA 86, which reduced the top statutory corporate
tax rate from 46 percent in 1986 to 34 percent in 1988 (Scholes et al. 1992; Guenther 1994; Maydew
1997; Shane and Stock 2006). Among all firms that report tax losses during a ten-year window,
Maydew (1997) finds that firms appear to report larger losses when the relative tax benefit of the
carryback, measured as difference between tax rates in the current and carryback years, is greater. He
finds that loss-shifting actions are evident in both operating income and nonrecurring losses.
We extend this research to a general setting in which statutory tax rates are effectively constant.
Maydew (1997) suggests that firms facing losses always have incentives to increase their refund of
prior years’ taxes for at least two reasons. First, the cash flows from tax refunds are certain, whereas
expected cash flows from operations are not. Second, the time value of money provides an incentive
to defer income and accelerate deductions. The ability to claim a certain refund of cash taxes paid is
permanently lost when the carryback window closes, substantially reducing the present value of the
tax loss.8 We extend these points by emphasizing that a tax refund represents real cash inflows that
7 There is an extensive literature that analyzes how managers consider the tradeoff between taxes (benefits andcosts) and GAAP accounting effects. See for example Matsunaga et al. (1992), Engel et al. (1999), Shackelfordet al. (2010), and Hanlon and Heitzman (2010).
8 Consider the change in the NOL carryback period in 2008–2010. The extension of the carryback window fromtwo to five years was motivated by a desire to provide a refund of prior cash taxes paid to firms in a difficulteconomic climate (Graham and Kim 2009). Such tax refunds were unavailable to firms prior to the law changesbecause the carryback period prevented firms from claiming refunds of taxes paid in years outside the then-current two-year carryback window.
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provide liquidity. The liquidity motivation is likely to be more relevant for loss firms facing
difficulty raising external capital. In essence, even in periods of constant statutory tax rates, firms
will have incentives to accelerate losses.9 This leads to the following prediction:
H1: Reported earnings are decreasing in tax loss carryback incentives.
In testing this hypothesis, we explicitly consider variation in the costs and benefits to firms that
execute this strategy. For firms that are persistently profitable and consistently pay taxes, the
benefits of accelerating a loss to claim a tax refund are either unavailable or too small to make a
difference. Thus, more powerful tests of the hypothesized behavior require comparing firms with
tax-motivated loss-shifting incentives, which we operationalize as firms that paid taxes during the
earliest year of the carryback window and expect to have losses in the current year, to firms without
such incentives, which are then firms with similar expected losses but no tax payments to recoup.
Our tests assume that the loss reported to the tax authority is also reflected in GAAP earnings, so the
incremental tax benefits from increasing a tax loss should be weighed against the incremental costs
of increasing an accounting loss, such as violating a debt covenant.
If tax rules create incentives for firms to increase reported losses, then a natural question is
whether analysts anticipate corporate responses to these incentives when forecasting earnings.
Analysts are often viewed as sophisticated users of accounting information, but their forecasts may
ignore carryback-based incentives if the tax disclosures are complex or provide noisy signals of true
tax status (Chen and Schoderbek 2000; Dhaliwal et al. 2004). For example, Amir and Sougiannis
(1999) find that analysts do not incorporate the information in deferred taxes contained in the SFAS
No. 109 disclosure, while Chen and Schoderbek (2000) document that analyst forecasts do not
incorporate the predictable earnings effect from the revaluation of deferred tax assets and liabilities
following a one percentage point increase in the top marginal corporate tax rate in 1993 (from 34
percent to 35 percent). Based on capital market responses to TRA 86, Plumlee (2003) finds that
analysts do not incorporate the impact of tax incentives and tax disclosures, particularly for more
complex tax issues.10 Shane and Stock (2006) show that analysts do not incorporate income
shifting induced by the 1986 tax rate change when forecasting earnings.
While the existing evidence is informative, it is limited to a handful of events that radically
changed tax law or GAAP disclosures of tax circumstances. Even if analysts ignore the impact of
one-time macro events, the tax benefits of accelerating losses are recurring and apply to a significant
set of firms every year. This provides a stronger case for analysts to forecast such information. This
reasoning leads to the following hypothesis:
H2: Analyst forecasts do not incorporate tax loss carryback incentives.
Finally, we examine the equity market’s reaction to tax-motivated loss shifting. If analysts
do not incorporate tax-motivated loss shifting in their earnings forecasts, then their estimates
9 Like Maydew’s (1997) focus on declining statutory marginal tax rates, our setting can potentially be interpretedas a decline in expected marginal tax rates, holding statutory tax rates largely constant. In other words, a firm thataccelerates a loss to claim a refund of taxes paid in a prior year essentially secures a tax benefit at anundiscounted statutory tax rate. But if management decides to wait to report the loss, then it is less likely the firmwill be able to carry the loss back for an immediate refund, and instead the firm would have to carry the lossforward to offset income in some future period, reducing the effective tax benefit of the deduction. Directestimates of the marginal tax rate, such as the simulated tax rates of Shevlin (1990), Graham (1996), and Blouinet al. (2010), are not well suited to our analysis for several reasons. First, they provide an estimate of theexpected marginal tax rate for current year profits and losses, but not the expected marginal tax rate in futureyears. Second, they do not directly address the dollar amount of potential refunds from carrybacks. Third, thesemeasures are endogenous to the reporting decisions we are analyzing.
10 Moreover, Outslay and McGill (2002) provide evidence that the tax disclosures of some firms are quite difficultto interpret and understand.
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are likely to be systematically optimistic. Such optimism would lead to negative earnings
surprises as reflected in analysts’ forecast errors, measured as actual earnings minus forecasted
earnings. However, ‘‘unexpected’’ losses that generate cash tax refunds arguably create value
by reducing the present value of taxes paid and providing liquidity, so the market’s response to
losses motivated by cash tax benefits should be tempered relative to the firm whose losses are
not. Prior evidence suggests that investors do not understand the implications of tax incentives
on reported earnings (Shane and Stock 2006). However, there is some evidence that
informative disclosure of the tax-based reasons behind the earnings surprise leads to more
efficient market responses (Chen and Schoderbek 2000). We predict that managers have
incentives to disclose the transitory nature of tax-motivated losses to investors through
financial reporting disclosures, conference calls, and future earnings guidance. This leads to the
final hypothesis:
H3: The market reacts less negatively to earnings surprises of firms with tax-motivated loss-
shifting incentives.
III. SAMPLE DATA AND DESCRIPTIVE STATISTICS
Each year, we identify firms that have the incentive to accelerate tax losses to obtain a tax
refund by analyzing the time-series of estimated taxable income.11 We first calculate tax loss
carryback capacity (NOLC), which is an estimate of refundable income taxes paid in the earliest
year of the carryback period in year t and is described in Appendix B.12 The length of the carryback
period ranges from two to five years over our sample period. Unrefunded tax payments in the
earliest carryback year will expire if the firm does not claim a refund in year t. Thus, our main test
variable (D_NOL) for the period is an indicator variable equal to 1 if in year t the firm has
unrefunded tax payments on income in the earliest carryback year and analysts expect the firm to
report a loss in year t. This approach identifies a set of firms that will lose the ability to claim a
refund of taxes paid in a prior year (D_NOL) and the corresponding amount of potentially
refundable taxes (NOLC).
Because tax returns are unobservable, we follow prior research and rely on GAAP earnings
numbers to identify tax-motivated loss shifting (Scholes et al. 1992; Guenther 1994; Maydew 1997;
Shane and Stock 2006). Thus, we focus on forecasts and realizations of GAAP earnings and assume
that book earnings reflect the underlying tax loss reporting. We expect GAAP earnings numbers to
11 An alternative research design is to focus on tax law changes, as in Maydew (1997), who compares firm-yearswith loss carrybacks during a period immediately after TRA 86 to firm-years with loss carrybacks in otherperiods. This alternative setting differs from ours in two primary ways. First, Maydew (1997) tests the additionaltax incentives introduced by TRA 86, whereas we are interested in the general phenomenon whereby firmsalways have incentives to shift income and carryback losses. Second, Maydew (1997) conducts an ex postanalysis using firm-years with loss carrybacks. We do not require firms to have loss carrybacks, because avariable based on realized loss carrybacks would have a look-ahead bias in our capital market tests (that is, weare interested in capital market responses to expected tax loss shifting, which is measured prior to the returnwindow). Instead, we focus on an ex ante variable and predict whether firms and the capital market behave incertain ways. Maydew (1997) carefully controls for the look-ahead bias issue because he takes firm-years withloss carrybacks in other periods as the benchmark and examines the impact of additional tax incentivesintroduced by TRA 86.
12 Ideally, we would incorporate the firm’s actual net operating loss carryforwards to calculate tax status. NOLcarryforwards can arise from domestic, foreign, and local tax jurisdictions, but we do not have access to firms’tax returns, and information on the source of the NOL carryforwards is inconsistently disclosed in financialreports. Moreover, Compustat provides a single data item for NOL carryforwards, and this has been shown tohave significant measurement problems (Mills et al. 2003).
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be a noisy proxy for the reported tax numbers, and therefore this approach works against finding
evidence consistent with our predictions.13
The ex ante nature of the D_NOL measure of the tax incentives to shift losses is important when
drawing inferences about capital market behavior. All information to construct D_NOL is available at
the beginning of year t. In this way, we test whether measures of tax loss carryback incentives are
associated with subsequent actions of managers, analysts, and investors. Because we focus on a single
year of tax payments and require that the firm have an expected loss for the year, D_NOL is a
conservative measure of the incentive to shift losses into the current year. We compare firms with
incentives to accelerate tax losses (D_NOL¼ 1) to a set of firms also expected to report a loss, but
without cash taxes available for refund. To do this, first we define an indicator variable D_NEG equal
to 1 if analysts forecast a loss eight months before the fiscal year-end, independent of tax carryback
opportunities. Because D_NOL is an interaction between D_NEG and the indicator for potential tax
refunds, the coefficient on D_NEG is the estimated effect for expected loss firms without carryback
opportunities, while the coefficient on D_NOL represents the incremental effect for expected loss firms
with carryback opportunities.
We focus on the manager’s financial reporting decisions to understand analysts’ and investors’
reaction to tax-motivated loss shifting. We include all firm-year observations with non-missing
earnings or analysts’ earnings forecasts, resulting in a final sample of 99,564 firm-year observations
from 1981 to 2010. Table 1 provides summary statistics of the primary variables used in this study.
Annual earnings, as a percentage of stock price, average�8.4 percent with a median of 4.4 percent.
Unexpected earnings, based on the difference between reported earnings and analysts’ forecasts
eight months prior to year-end (scaled by stock price), has a mean of�3.1 percent and median of
0.4 percent, respectively. With regard to financial variables, the average firm in our sample has a
market value (MV) of $2.967 billion and a book-to-market equity ratio (BM) of 0.576. The average
book leverage ratio for sample firms is 22.2 percent, while EBITDA averages 11.2 percent of total
assets. All financial variables are measured at the end of year t�1. On average, about 10.8 percent of
firms are expected to report losses in our 1981 through 2010 sample period (D_NEG ¼ 1). Of all
such firms with expected losses, the subset of firms with the incentive to accelerate tax losses under
our definition (D_NOL ¼ 1) account for 2.6 percent of all firm-year observations, compared with
7.8 percent (10.8 percent � 2.6 percent) for loss firms without these incentives.
IV. EMPIRICAL EVIDENCE
Evidence of Tax-Motivated Loss Shifting Based on a Time-Series Earnings Model
To test whether firms with tax-motivated loss-shifting incentives increase losses, we estimate
the following regression that includes a set of control variables:
13 Tax reporting rules generally start with financial reporting rules, but there are significant exceptions. First, theGAAP financial statements will tend to consolidate more entities than the firm’s U.S. tax return. GAAPeffectively requires the firm to consolidate all entities owned at least 50 percent, whereas the U.S. tax returnignores foreign subsidiaries and those where the firm owns less than 80 percent. Second, tax rules often requirean actual transaction to record a loss. For example, an impairment of an asset’s value would show up as anexpense on the GAAP financial statements but would be absent from the firm’s tax returns, and hence thecalculation of taxable income, until the firm actually sells the asset. Maydew (1997) finds that income shiftingaround the 1986 Tax Act was concentrated in gross margin and SG&A numbers.
Et is annual Compustat earnings before extraordinary items per share scaled by stock price at the firm’s fiscal year-end.Forecast error (FE) is calculated as the difference between the actual earnings and the median analyst forecast made eightmonths prior to fiscal year-end, scaled by stock price at the forecast date. RETt is year t’s annual returns starting eightmonths prior to fiscal year-end. ARETt is average three-day earnings announcement return in year t, measured as rawreturns minus value-weighted market returns over the three-day [�1, 1] period, where day 0 is the earningsannouncement date. NOLC is the net operating loss carryback capacity limit (see Appendix B for variable measurement).D_NOL is a dummy variable with the value of 1 if NOLC is positive for a firm in an expected loss position, and 0otherwise, indicating the firm’s incentives to carry back NOLs and to claim tax refunds. D_NEG is a dummy variablewith the value of 1 if analysts’ forecasts of year t’s earnings are negative, where forecasts were made eight months priorto fiscal year-end. MV is a firm’s market value of equity at the end of year t�1. BM is the book-to-market ratio at the endof year t�1. COV is the number of analysts covering the firm at the forecast date. ACC is total accruals scaled by averageassets. LEV is the leverage ratio. EBITDA is earnings before interest, taxes, depreciation, and amortization scaled byaverage total assets. Please see Appendix A for detailed variable definitions. The sample includes 99,564 firm-yearobservations with non-missing observations of FE or annual earnings from 1981 to 2010. All variables except forD_NOL, D_NEG, COV, and return variables are winsorized at the 1st and 99th percentiles.
Tax-Motivated Loss Shifting 1665
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where:
E ¼ the reported earnings per share scaled by the firm’s stock price at fiscal year-end;
D_NOL¼ a dummy variable indicating a firm’s incentive to carry back tax losses to claim a tax
refund;
D_NEG¼ a dummy variable that takes a value of 1 if analysts are forecasting negative annual
earnings for year t four months after year t begins;
Et�1 and Et�2 ¼ reported earnings for years t�1 and t�2, respectively;14
LOSSt�1 (LOSSt�2) ¼ a dummy variable taking a value of 1 if Et�1 (Et�2) is negative, and 0
otherwise;
MV ¼ a firm’s market value of equity at the beginning of the year;
ACC ¼ total accruals scaled by average assets; and
RET ¼ the 12-month buy-and-hold return beginning eight months before a firm’s fiscal year-
end.
Earnings variables and ACC are winsorized at the 1st and 99th percentiles.
Table 2 presents results for three progressively richer regression models, with D_NOL as the
main variable of interest. We expect the coefficient on D_NOL to be negative, reflecting the
hypothesized tax-motivated loss shifting. Because expected earnings for D_NOL firms are negative
by definition, we include D_NEG in the regression to ensure that the coefficient on the D_NOLvariable does not pick up any difference in earnings surprises between profit and loss firms (Hayn
1995). Because D_NOL is implicitly an interaction between D_NEG and an indicator for carryback
potential, the coefficient on D_NOL reflects the incremental loss reported by firms with an option to
use losses to obtain a cash refund of taxes paid in the earliest carryback year.
Across the three specifications of Equation (1) in Table 2, the coefficient on D_NOL is
significantly negative. For example, in column (1), the coefficient on D_NOL is�0.073 (t¼�2.61),
indicating that earnings are about 7.3 percent of prior-year-end market value lower in years when
the firm has a tax-based incentive to accelerate losses.15 The magnitude of D_NOL is also
economically significant. As the coefficient on D_NEG is �0.157 (t ¼�7.90), we interpret the
results to mean that reported earnings are 46 percent (¼ 0.073/0.157) lower for loss firms with tax-
based incentives to accelerate losses than for loss firms without those incentives. This result holds
across specifications with additional controls in columns (2) and (3). Overall, the results in Table 2
provide consistent support for the prediction that firms engage in tax-motivated loss shifting even
when statutory tax rates are constant.
Firms have a number of ways to accelerate losses, such as frontloading expenses, writing down
inventory, and selling assets at a loss. To provide more evidence on the drivers of reported losses
for firms with tax loss carryback incentives, we analyze recurring and nonrecurring items during the
event years, and compare them to both previous and subsequent years. As the literature offers no
well-established model for earnings components, we adopt a simple random walk model and use
both previous and subsequent years as the benchmark.
14 Following the capital markets research, we scale earnings and earnings surprises by stock price. In this way, thedeflator is stock price for both stock returns and earnings surprises in the return regressions.
15 The economic magnitude is large for two reasons. First, we use annual earnings, and some firms report largelosses relative to their market values. Second, we winsorize the data and do not introduce any ad hoc cutoff ofdata based on reported earnings. If we delete observations with earnings scaled by market value in the top andbottom 1 percent, the coefficient on D_NOL becomes �0.049 (p , 0.01). If we delete observations with anabsolute value of earnings scaled by market value above 1, the coefficient on D_NOL becomes �0.026 (p ,0.01). Although the magnitude of the coefficient drops as we drop more observations with extreme values, the t-statistics and p-values change very little. In all our tables, we follow the general practice in the literature ofwinsorizing the variables at 1 percent and 99 percent.
1666 Erickson, Heitzman, and Zhang
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Panel A of Table 3 documents firm performance in the D_NOL years relative to previous or
subsequent years. Using the previous year as the benchmark, we find that loss firms with carryback
incentives have lower unexpected earnings than loss firms without such incentives, with the mean
and median differences of �11.3 percent (t ¼�3.17) and �0.5 percent (t ¼�1.97), respectively.
Unexpected operating income is also significantly lower for D_NOL firms, but unexpected special
items are similar to those of loss firms without carryback incentives. Because D_NOL firms are
presumed to accelerate tax losses from future periods, it is also useful to compare the reported
numbers to earnings in the subsequent year. When we do this in the lower half of Panel A, earnings,
operating income, and special items all show significant differences between loss firms with
TABLE 2
Analysis of Reported Earnings Based on Time-Series Models
(1) (2) (3)
Intercept �0.053 0.005 �0.080
(�2.64) (0.94) (�5.52)
D_NOL �0.073 �0.079 �0.084
(�2.61) (�3.06) (�3.14)
D_NEG �0.157 �0.129 �0.114
(�7.90) (�7.32) (�5.94)
Et�1 0.948 0.408 0.594
(5.10) (6.87) (6.15)
Et�2 0.130 �0.142 �0.308
(2.35) (�1.12) (�1.55)
LOSSt�1 �0.064 �0.035
(�3.89) (�2.35)
LOSSt�2 �0.030 �0.039
(�2.42) (�2.75)
Et�1 � LOSSt�1 0.555 0.270
(2.74) (1.99)
Et�2 � LOSSt�2 0.292 0.549
(1.52) (1.89)
ln(MVt�1) 0.011
(7.60)
ACCt�1 �0.159
(�4.16)
RETt�1 0.094
(3.86)
Adj. R2 0.252 0.258 0.281
This table reports multivariate regression results. The dependent variable is Et, the annual Compustat earnings beforeextraordinary items per share scaled by stock price at a firm’s fiscal year-end. LOSSt�1 (LOSSt�2) is a dummy variablewith the value of 1 if Et�1 (Et�2) is negative, and 0 otherwise. NOLC is the net operating loss carryback capacity limit(see Appendix B for variable measurement). D_NOL is a dummy variable with the value of 1 if NOLC is positive for afirm in an expected loss position, and 0 otherwise, indicating the firm’s incentives to carry back tax losses to claim a taxrefund. D_NEG is a dummy variable with the value of 1 if analysts’ forecasts of year t’s earnings are negative, whereforecasts were made eight months prior to fiscal year-end. MV is a firm’s market value of equity at the end of year t�1.ACC is total accruals scaled by average assets. RET is the 12-month buy-and-hold return starting from eight monthsbefore a firm’s fiscal year-end. Please see Appendix A for detailed variable definitions. The sample includes 85,577 firm-year observations with non-missing earnings variables (Et, Et�1, and Et�2) from 1981 to 2010. t-statistics in parenthesesare based on the Fama-MacBeth regression approach. Earnings variables and ACC are winsorized at the 1st and 99thpercentiles.
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TABLE 3
Analysis of Recurring and Nonrecurring Items
Panel A: Performance Relative to Previous or Subsequent Year
Special items �0.170 �0.001 �0.072 0.000 �0.098*** �0.001***
[(SIt � SItþ1)/P] (�4.97) (�6.88)
Panel B: Logistic Model of Negative One-Time Items in Event Years
Negative Special Items Loss on Sale of PP&E and Investment
Coefficient(p-value) Marginal Effects
Coefficient(p-value) Marginal Effects
Intercept �1.847 �1.756
(, 0.01) (, 0.01)
D_NOL 0.622 14.23% 0.247 5.01%
(, 0.01) (, 0.01)
D_NEG �0.294 �6.65% �0.268 �5.41%
(, 0.01) (, 0.01)
Et�1 �0.411 �9.41% �0.083 �1.67%
(, 0.01) (0.011)
Et�2 �0.406 �9.32% �0.103 �2.03%
(, 0.01) (0.009)
LOSSt�1 0.519 11.76% 0.032 0.63%
(, 0.01) (0.338)
LOSSt�2 0.287 6.49% 0.047 1.00%
(, 0.01) (0.145)
ln(MVt�1) 0.221 5.03% 0.134 2.71%
(, 0.01) (, 0.01)
ACCt�1 0.347 8.00% �0.759 �15.55%
(, 0.01) (, 0.01)
RETt�1 �0.198 �4.53% �0.035 �0.71%
(, 0.01) (0.002)
(continued on next page)
1668 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
carryback incentives and loss firms without. In general, the magnitude of the loss is larger when we
use the subsequent year rather than the previous year as the benchmark, especially with medians.
This result indicates that the earnings changes are transitory, and is consistent with D_NOL firms
shifting expenses and losses from the subsequent year to the current year. Finally, the magnitude of
the difference in operating income is similar to that of the earnings difference, especially for
medians, and this is driven by the infrequency and variability of special items.
In Table 3, Panel B, we further examine whether firms with tax incentives are more likely to
report negative one-time items. We focus on negative special items and the loss on the sale of
PP&E and investment under the premise that firms can sell assets at a loss to recapture taxes paid in
previous years. Both logistic models show significant coefficients on D_NOL, and the marginal
effects suggest that firms with carryback incentives are 14.23 percent more likely to report a
negative special item and 5.01 percent more likely to report a loss from an asset sale. As D_NOL is
implicitly an interaction between D_NEG and an indicator for carryback potential, these effects are
incremental to what we observe for loss firms without carryback incentives (D_NEG ¼ 1 and
D_NOL ¼ 0). Finally, the coefficients on control variables are largely significant with expected
signs. Profitable firms and firms with high past returns are less likely to report negative one-time
items, whereas past loss firms and firms with high accruals tend to report negative one-time items.
In sum, we find strong evidence that firms increase losses in order to claim tax refunds. Both
core earnings and one-time items are significantly lower in D_NOL years than in adjacent years,
suggesting that firms use both recurring and non-recurring items to shift losses.
Do Analysts Incorporate Tax-Motivated Loss Shifting in Their Earnings Forecasts?
If analysts anticipate tax-motivated loss shifting and incorporate these incentives into their
forecasts, then we expect to find no difference in analyst forecast errors—actual earnings less the
analysts’ forecast of earnings—between firms with tax incentives to accelerate losses (D_NOL¼ 1)
and those without (D_NOL¼0). But if analysts ignore or do not fully incorporate information about
taxes, then their forecast errors should be more negative for firms with tax incentives to accelerate
losses. We conduct both univariate and multivariate analyses on analysts’ forecast errors. In
univariate analyses, Panel A of Table 4 shows that the average analyst forecast error for firms with a
tax-motivated loss-shifting incentive (D_NOL firms), scaled by stock price, is �9.5 percent (p ,
0.01). For all firms without this carryback incentive, including firms with expected positive earnings
TABLE 3 (continued)
**, *** Indicate significant differences at the 5 percent and 1 percent levels, respectively.Panel A reports financial performance relative to previous and subsequent years, respectively. Loss firms are defined as
firms with negative analyst earnings forecasts made eight months prior to fiscal year-end. Earnings are earnings beforeextraordinary items. Operating income (OPINC) is operating income after depreciation and amortization. P is the marketvalue of equity. There are 2,210 and 8,068 firm-year observations for loss firms with and without carryback incentives,respectively. Panel B reports the results of estimating a logistic model for negative one-time items. The data on gain/losson sale of PP&E and investment start in 1995. D_NEG is a dummy variable with the value of 1 if analysts’ forecasts ofyear t’s earnings are negative, where forecasts were made eight months prior to fiscal year-end. E is annual Compustatearnings before extraordinary items per share scaled by stock price at a firm’s fiscal year-end. LOSSt�1 (LOSSt�2) is adummy variable with the value of 1 if Et�1 (Et�2) is negative, and 0 otherwise. NOLC is the net operating loss carrybackcapacity limit (see Appendix B for variable measurement). D_NOL is a dummy variable with the value of 1 if NOLC ispositive for a firm in an expected loss position, and 0 otherwise, indicating the firm’s tax incentive to accelerate losses.MV is a firm’s market value of equity at the end of year t�1. ACC is total accruals scaled by average assets. RET is the12-month buy-and-hold return starting from eight months before a firm’s fiscal year-end. The sample includes 85,577firm-year observations with non-missing earnings variables from 1981 to 2010.
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TABLE 4
Analyst Forecast Error Properties
Panel A: Analyst Forecast Errors for Firms with and without Tax-Motivated Loss-ShiftingIncentives
Loss Firms withTax Incentives(D_NOL ¼ 1)
Other Firms(D_NOL ¼ 0)
Difference(t-stat.)
Loss Firms withoutTax Incentives
(D_NEG ¼ 1, D_NOL ¼ 0)Difference
(t-stat.)
A B A � B C A � C
Entire Sample
Forecast error �0.095 �0.029 �0.066
(�27.85)
�0.042 �0.053
(�9.91)
1987–1990
Forecast error �0.204 �0.055 �0.149
(�10.37)
�0.143 �0.071
(�3.24)
Panel B: Multivariate Regressions of Analyst Forecast Errors (FEt)
(1) (2)
Intercept �0.078 �0.048
(�10.82) (�11.06)
FEt�1 0.426
(10.88)
D_NOL �0.048 �0.027
(�6.25) (�3.81)
D_NEG �0.015 0.004
(�1.86) (0.72)
ln(MVt�1) 0.009 0.005
(8.92) (7.60)
ln(COVt) 0.004 0.002
(2.86) (1.87)
BMt�1 �0.023 �0.018
(�5.42) (�4.38)
RETt�1 0.035 0.027
(6.23) (5.45)
ACCt�1 �0.006 �0.058
(�0.87) (�8.96)
Adj. R2 0.112 0.180
Forecast error, FE, is calculated as the difference between I/B/E/S actual earnings and the median analyst forecast madeeight months prior to a firm’s fiscal year-end, scaled by stock price at the forecast date. NOLC is the net operating losscarryback capacity limit (see Appendix B for variable measurement). D_NOL is a dummy variable with the value of 1 ifNOLC is positive for a firm in an expected loss position, and 0 otherwise, indicating the firm’s tax incentive to acceleratelosses. D_NEG is a dummy variable with the value of 1 if analysts’ forecasts of year t’s earnings are negative, whereforecasts were made eight months prior to fiscal year-end. MV is a firm’s market value of equity at the end of year t�1.COV is the number of analysts covering the firm at the forecast date. BM is the book-to-market ratio at the end of yeart�1. RET is the 12-month buy-and-hold return starting from eight months before a firm’s fiscal year-end. ACC is totalaccruals scaled by average assets. Please see Appendix A for detailed variable definitions. The sample includes 83,875firm-year observations with non-missing FE from 1981 to 2010. In all columns, t-statistics in parentheses are based onthe Fama-MacBeth approach. FE, BM, and ACC are winsorized at the 1st and 99th percentiles.
1670 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
surprises, analyst forecast errors are lower, averaging �2.9 percent.16 The resulting difference in
analyst forecast errors of 6.6 percent of stock price (p , 0.01) is highly significant. We also
compare the forecast errors in D_NOL firms to expected loss firms without carryback incentives and
find that D_NOL firms have significantly greater negative forecast errors, differing by 5.3 percent of
stock price (p , 0.01) between the two groups of firms. Overall, these results are consistent with
the conclusion that analysts do not fully incorporate tax-motivated loss-shifting behavior into their
earnings forecasts.
To control for other factors that could be correlated with both the tax incentives to shift losses
and the forecast error, we estimate the following equation:
where FE is analyst forecast error. If firms increase losses in year t to capture tax refunds and
analysts do not anticipate this behavior, then we expect a negative coefficient on D_NOL, where
again the coefficient on D_NOL represents the effect that is incremental to the association between
expected losses and realized forecast errors estimated by the coefficient on D_NEG. Following
previous research, we control for other determinants of earnings forecast bias. The literature argues
that analysts have incentives to issue optimistic forecasts for firms with poor information
environments to obtain access to management (Francis and Philbrick 1993; Lim 2001). We include
firm size (MV) and analyst coverage (COV) to capture a firm’s information environment (Atiase
1987; Zhang 2006b). We also include the book-to-market ratio (BM) to control for growth
opportunities, as growth firms have stronger incentives to meet or beat earnings targets, suggesting
a negative coefficient on BM. Prior literature documents evidence indicating that analysts are not
fully rational (see Kothari [2001] for a review). To allow for this possibility, we include RET and
FEt�1 to control for analyst underreaction to the information contained in stock returns and forecast
errors in the prior period. We further include accruals to control for the possibility that analysts do
not fully understand the implication of accruals for future earnings (Bradshaw et al. 2001; Teoh and
Wong 2002).
Table 4, Panel B summarizes the results of the forecast error regressions with and without the
lagged dependent variable as a control. In column (1), the coefficient on D_NEG is only marginally
significant (coeff. ¼�0.015, t ¼�1.86), providing weak evidence that analysts are surprised by
negative earnings news even when they expect the firm to report a loss. Turning to our variable of
interest, the coefficient on D_NOL is�0.048 (t¼�6.25), which is much larger than the coefficient
on D_NEG, and indicates that analysts fail to anticipate the additional losses reported by firms with
tax incentives to shift income and that analysts’ forecast errors are predictable ex ante. We add the
lagged forecast error as a control in column (2) to control for unobservable firm effects, and find
that the coefficient on D_NOL drops to �0.027 but remains highly significant (t ¼ �3.81).
Economically, analysts’ forecast errors, scaled by stock price, are about 2.7 percentage points larger
for loss firms with carryback incentives than for firms without. This translates into about $64.7
billion of unexpected loss shifting for firms with incentives to use those losses to obtain cash tax
refunds between 1981 and 2010.17
16 The observed negative forecast errors for D_NOL ¼ 0 firms is consistent with the optimistic bias in analysts’earnings forecasts documented in the prior literature (O’Brien 1987). Analysts’ forecast errors are reliablynegative when the forecast horizon is long, and turn to zero or positive immediately before earningsannouncements (Richardson et al. 2004).
17 We estimate the $64.7 billion as the 2.7 percent multiplied by the average sample firm’s market value of $1.204billion and then multiply that by 1,990 firm-year observations with tax incentives in Model (2).
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Equity Market Response to Tax-Motivated Loss Shifting
Finally, we examine the reaction of equity investors to tax-motivated loss shifting. If investors
naively follow analysts’ earnings forecasts, which tend to miss the tax incentives for accelerating
losses, then the market price will not fully reflect the expected tax benefits and the market reaction
will be determined by analysts’ forecast errors. Alternatively, if investor reactions are determined
by the revision in expected future cash flows and discount rates, then the positive cash flow effects
associated with accelerating a tax loss should lead to more positive (or less negative) market
reactions for firms with the tax-based incentives to shift losses, independent of the size of the
forecast error.
We consider both annual returns and earnings announcement returns and report the results in
Table 5. The first two columns are based on annual returns, and we estimate them with and without
the analyst forecast error as a control. In the full model, we control for analyst forecast errors, firms
with expected losses at the beginning of the period using D_NEG, as well as size, book-to-market,
and prior returns. Column (1) shows that the partial correlation between D_NOL and annual returns
is positive, albeit insignificant, suggesting that the market reaction to negative earnings
announcements by D_NOL firms is similar to those by non-D_NOL firms, even though D_NOLfirms report much larger losses as shown in Tables 2 and 4. Since D_NOL is negatively correlated
with the forecast error, we add analyst forecast errors as a control variable in column (2), and find a
positive and significant coefficient on D_NOL (coeff.¼ 0.074, t¼ 2.17), implying that the annual
stock return of a firm with tax-motivated loss-shifting incentives is about 7.4 percent greater than a
loss firm without such incentives, holding analyst forecast errors constant.
In columns (3) and (4), we use abnormal return during the earnings announcement window as
the dependent variable. This allows us to focus on the importance of the earnings release in
conveying information about cash flow effects of the tax loss. Similar to the annual return
regressions, we find a positive yet insignificant coefficient on D_NOL without controlling for
analyst forecast errors, and this turns positive and significant once we include analyst forecast errors
(coeff. ¼ 0.006, t ¼ 3.23). Overall, the results suggest that investors understand either the tax
benefits of the loss carryback, the transitory nature of the accelerated losses claimed by carryback
firms, or both.
In summary, we find that the market reaction to earnings reported by firms with incentives to
accelerate tax losses is less negative than the market reaction to earnings by firms without such
incentives. This occurs despite the fact that firms with tax incentives to shift losses actually report
larger losses using both prior earnings and analyst forecasts as a benchmark, and is consistent with
these losses being transitory, increasing cash flows and providing liquidity.18
V. ADDITIONAL ANALYSIS AND SENSITIVITY CHECKS
Cross-Sectional Variation in Tax-Motivated Loss Shifting
In Table 4, we provide some evidence of the time-series variations in firms’ incentives to
engage in tax-motivated loss shifting—firms have particularly strong tax incentives to shift losses
around TRA 86. As Maydew (1997) shows, TRA 86 reduced the corporate tax rate from 46 percent
in 1986 to 34 percent in 1988, providing firms with stronger incentives to accelerate losses between
18 Our market reaction results are in contrast to those in Shane and Stock (2006), who show that investors do notunderstand income shifting around one-time tax rate change around 1986. We attribute the different resultsbetween these two research settings to the recurring nature of loss carrybacks and better firm communicationwith the market in the 1990s and 2000s. Management guidance was virtually non-existent in the 1980s.
1672 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
1987 and 1990 in order to generate a refund of taxes paid at the higher rate. In this section, we
explore the cross-sectional variations in firms’ incentives to carry back tax losses.
While firms have a variety of incentives to carry back losses, we specifically test whether the
demand for liquidity drives the firm’s decision to increase cash flow through a tax refund. This
implicitly assumes that the incremental cost of external funds is higher than the cost of funds
obtained through a tax refund. Empirically, we measure financial constraints (FC) using a firm’s
debt minus cash and short-term investment scaled by total assets. We then add FC, measured at
prior year-end, and its interaction term with D_NOL (D_NOL � FC) to Equations (1) and (2) as
RETt is year t’s annual returns starting from eight months prior to fiscal year-end. ARETt is the average three-day earningsannouncement return in year t, measured as raw returns minus value-weighted market returns over the three-day [�1, 1]period, where day 0 is the earnings announcement date. FEt is the forecast error for year t, calculated as the differencebetween I/B/E/S actual earnings and the median analyst forecast made eight months prior to a firm’s fiscal year-end,scaled by stock price at the forecast date. NOLC is the net operating loss carryback capacity limit (see Appendix B forvariable measurement). D_NOL is a dummy variable with the value of 1 if NOLC is positive for a firm in an expectedloss position, and 0 otherwise, indicating the firm’s incentives to carry back NOLs and to claim tax refunds. D_NEG is adummy variable with the value of 1 if analysts’ forecasts of year t’s earnings are negative, where forecasts were madeeight months prior to fiscal year-end. MV is a firm’s market value of equity at the end of year t�1. BM is the book-to-market ratio at the end of year t�1. RETt is the 12-month buy-and-hold return starting from eight months before a firm’sfiscal year-end. Please see Appendix A for detailed variable definitions. The sample includes 83,875 firm-quarterobservations with non-missing observations of FE and return variables from 1981 to 2010. In all columns, t-statistics inparentheses are based on the Fama-MacBeth regression approach. FE and BM are winsorized at the 1st and 99thpercentiles.
Our main prediction is that the coefficients on the interaction term D_NOL � FC should be
significantly negative in Equations (3) and (4), suggesting that more financially constrained firms
have stronger loss-shifting incentives. In Table 6, we find this is indeed the case. In the regression
of future earnings, the coefficient on the interaction term D_NOL � FC is�0.105 (t¼�1.97). In the
regression of analyst forecast errors, the coefficient on the interaction term D_NOL � FC is�0.028
(t ¼�2.24). If we further add the prior-period forecast errors as an additional control variable to
Equation (4), then the interaction term D_NOL � FC becomes marginally significant (coeff. ¼�0.018, t ¼�1.65). The results provide some support for the role of liquidity benefits because
financially constrained firms appear more likely to accelerate losses to access cash from tax refunds,
and this behavior results in more negative earnings and analyst forecast errors for those firms.
Analyst Revisions of Future Earnings
Section IV shows that analysts do not fully incorporate tax-related losses in their earnings
forecasts. It is possible that some analysts may learn about such tax-motivated loss shifting over
time, for example when the firm announces earnings or an asset sale, and revise their earnings
forecasts accordingly. If tax-related losses represent one-time attempts to shift income, then a
testable implication is that current-year earnings forecasts should fall, but future earnings forecasts
should be relatively unchanged, suggesting a smaller correlation in analysts’ forecast revisions
between the current and subsequent years’ earnings. To test this prediction, we analyze the
where REVt measures analyst forecast revision for year t’s earnings from eight months before year
t’s fiscal year-end to one month after, and REVtþ1 measures analyst forecast revision for year tþ1’s
earnings during the same period. We expect that on average b3 will be positive (revisions are
positively correlated), b5 will be negative (less correlated for negative earnings shocks), and b4 will
be negative (revisions of tþ1 forecasts are even less sensitive to current revisions given tax
incentives to report losses).
The results are consistent with our predictions. Untabulated results show a positive coefficient
on REVt (b3 ¼ 0.558, t ¼ 22.50) and a negative coefficient on REVt � D_NEG (b5 ¼�0.114, t ¼�4.44). More importantly, the coefficient on REVt � D_NOL is significantly negative (b4¼�0.068,
t¼�2.05). The results suggest that revisions of future years’ earnings are less sensitive to revisions
in current-year earnings for firms with tax loss carryback incentives, consistent with the idea that
tax-related losses reflect one-time attempts to shift income. In other words, to the extent that
analysts revise their current-year forecasts downward to reflect better information about the firm’s
tax-based incentive to accelerate losses into that year, they are less likely to revise forecasts of
future earnings in the same direction.
Other Robustness Checks
Our main analysis is based on an indicator variable version of NOLC, the capacity for tax loss
carrybacks. In untabulated analysis, we incorporate the magnitude of tax loss carrybacks by
replacing D_NOL with NOLC and re-estimate the regressions. The results continue to hold. For
example, the coefficient on NOLC in Equation (2) is�0.795 (t¼�3.54), while the coefficient on
1674 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
TABLE 6
Analysis of Financial Constraints
Panel A: Regression of Earnings (Et)
Intercept �0.118
(�9.46)
D_NOL �0.060
(�2.48)
D_NEG �0.133
(�4.47)
FCt�1 �0.055
(�5.52)
D_NOL � FCt�1 �0.105
(�1.97)
D_NEG � FCt�1 �0.241
(�3.65)
Et�1 0.509
(7.79)
Et�2 �0.038
(�0.45)
LOSSt�1 �0.029
(�2.49)
LOSSt�2 �0.029
(�3.23)
Et�1 � LOSSt�1 0.174
(2.43)
Et�2 � LOSSt�2 0.133
(1.20)
ln(MVt�1) 0.016
(10.77)
ACCt�1 �0.108
(�4.58)
RETt�1 0.079
(5.94)
Adj. R2 0.259
Panel B: Regression of Analyst Forecast Errors (FEt)
Intercept �0.082
(�14.21)
D_NOL �0.030
(�4.86)
D_NEG �0.014
(�2.02)
FCt�1 �0.021
(�6.40)
D_NOL � FCt�1 �0.028
(�2.24)
D_NEG � FCt�1 �0.062
(�2.85)
(continued on next page)
Tax-Motivated Loss Shifting 1675
The Accounting ReviewSeptember 2013
NOLC in Equation (3) is �0.151 (t ¼�2.29). One caveat of the NOLC regressions is that actual
losses may not be linearly correlated with loss carryback capacity.
We use annual observations in the main analysis on the premise that tax reporting is done
annually. As a robustness check, we rerun our analysis based on quarterly observations by
assigning D_NOL in year t�1 to four quarterly earnings surprises in year t. A caveat of the quarterly
approach is that four quarterly observations within a firm-year are not independent. As an
alternative, we execute our analyses using only the fourth-quarter observations. In both
specifications, the tenor of the results is unchanged (e.g., significantly negative coefficients on
D_NOL in the regressions of earnings and analyst forecast errors, and positive coefficients on
D_NOL in the return regressions). We also examine how the coefficient pattern varies across
quarters and find that our results are driven by the third and fourth fiscal quarters, consistent with
the idea that firms are more likely to shift losses in later quarters as they receive more precise
information about expected tax and accounting profits, loss-shifting opportunities, and liquidity
needs.
VI. CONCLUSION
We identify firms with an incentive to exercise an option to obtain a cash refund of prior tax
payments that would otherwise expire at the end of the year. Over the 1981–2010 period with
relatively stable statutory tax rates, firms appear to accelerate reported losses to generate cash flows
from tax refunds, and do so to a greater extent when they are financially constrained. This evidence
suggests that such tax-based incentives have pervasive effects on reporting decisions across time
even when statutory tax rates are stable and thus have broad implications for capital markets
research.
TABLE 6 (continued)
ln(MVt�1) 0.010
(11.18)
ln(COVt) 0.003
(2.70)
BMt�1 �0.018
(�6.29)
RETt�1 0.029
(7.27)
ACCt�1 �0.013
(�2.42)
Adj. R2 0.128
Panels A and B report regression results for earnings (Et) and analyst forecast errors (FEt), respectively. E is annualCompustat earnings before extraordinary items scaled by stock price at a firm’s fiscal year-end. FE is the differencebetween I/B/E/S actual earnings and the median analyst forecast made eight months prior to a firm’s fiscal year-end,scaled by stock price at the forecast date. D_NOL is a dummy variable with the value of 1 if a firm has carrybackincentives, and 0 otherwise. D_NEG is a dummy variable with the value of 1 if analysts’ forecasts of year t’s earnings arenegative, where forecasts were made in the fourth month after fiscal year-end. FC is financial constraint measured as afirm’s debt minus cash and short-term investment scaled by total assets. LOSSt�1 (LOSSt�2) is a dummy variable with thevalue of 1 if Et�1 (Et�2) is negative, and 0 otherwise. MV is a firm’s market value of equity at the end of year t�1. ACC istotal accruals scaled by average assets. RET is the 12-month buy-and-hold return starting from eight months before afirm’s fiscal year-end. COV is the number of analysts covering the firm at the forecast date. Please see Appendix A fordetailed variable definitions. The sample includes 85,577 firm-year observations with non-missing earnings variables (Et,Et�1, and Et�2) in Panel A and 83,875 firm-year observations with non-missing FE in Panel B from 1981 to 2010.Earnings variables FE, BM, and ACC are winsorized at the 1st and 99th percentiles, and t-statistics in parentheses arebased on the Fama-MacBeth regression approach.
1676 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
Our evidence also suggests that analysts do not incorporate these tax-motivated loss-shifting
incentives into their earnings forecasts because we find that analyst forecast errors are significantly
more negative for firms with incentives to accelerate tax losses. This evidence contrasts with the
view that analyst forecast errors proxy for earnings surprises, and reinforces the evidence on
analysts’ disregard for the information in the firm’s tax disclosures. Despite the relatively larger
unexpected losses for firms with tax incentives to accelerate losses, the stock market reacts in a way
that suggests investors value tax-motivated loss shifting. If we control for the size of the reported
loss, then the stock returns of firms with tax-motivated loss-shifting incentives are significantly less
negative than similar loss firms without such incentives.
Our evidence is relevant to understanding the growing importance of tax losses on firm value.
Recent innovations in takeover defenses are designed specifically to protect the value of tax losses,
and within the last decade, Congress has argued that the temporary liberalization of tax loss
carryback rules injects needed liquidity into the business sector. Taken together, our evidence
suggests that the incentive to carry back tax losses plays a material and persistent role in corporate
reporting decisions and capital markets activities.
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Et E is annual Compustat earnings before extraordinary items per share scaled by stock price
at a firm’s fiscal year-end;
FEt analyst forecast error, defined as (E � F)/Pt�1, where E is reported annual earnings per
share from I/B/E/S, F is the median analysts’ earnings-per-share forecast made eight
months prior to fiscal year-end, and Pt�1 is stock price at the forecast date;
NOLCt�1 net operating loss carryback capacity (see the estimation process in Appendix B for
details), indicating a firm’s tax paid in the earliest year of the NOL carryback window
that has not been refunded yet;
D_NEG a dummy variable with the value of 1 if analysts’ forecasts of year t’s earnings are
negative, where forecasts were made eight months prior to fiscal year-end;
D_NOL a dummy variable with the value of 1 if the firm has an expected loss (D_NEG ¼ 1) and
the net operating loss carryback capacity is positive (NOLC . 0), and 0 otherwise;
MVt�1 the market value of equity at the end of year t�1;
COVt the number of analysts following the company at the forecast date (eight months prior to
fiscal year-end);
BMt�1 the book-to-market ratio, measured as the book value of equity divided by its market
value, at the end of year t�1;
RETt the 12-month buy-and-hold return starting from eight months before a firm’s fiscal year-
end;
ARETt average earnings announcement return of four quarterly earnings announcements for year t.Quarterly earnings announcement return is defined as raw returns minus value-weighted
market returns over the three-day [�1, 1] period, where day 0 is the earnings
announcement date;
ACCt�1 total accruals in year t�1, measured as (DCA � DCash) � (DCL � DSTD � DTP) �DEPEXP scaled by average total assets, where DCA ¼ change in current assets, DCash¼ change in cash and cash equivalents, DCL ¼ change in current liabilities, DSTD ¼change in debt in current liabilities, and DEPEXP ¼ depreciation and amortization
expense;
FCt�1 financial constraint, measured as total debt minus cash and short-term investment scaled by
total assets, at the end of year t�1;
LEVt�1 the leverage ratio, measured as total debt divided by total assets, at the end of year t�1;
and
EBITDAt�1 the ratio of earnings before interest, taxes, depreciation, and amortization scaled by average
total assets, measured in year t�1.
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APPENDIX B
Variable Measurement
Timeline of the Variables (using December Fiscal Year-End as an Example)
Estimating Net Operating Loss Carryback Capacity (NOLC)
NOLC is meant to capture tax paid in the earliest year of the NOL carryback window that has
not been refunded by the beginning of year t. We estimate net operating loss carryback capacity
(NOLC) depending on the time period of the loss. Before 1997, firms could carry back NOLs up to
three years and carry forward NOLs up to 15 years. Since 1997, firms can carry back NOLs up to
two years and carry forward NOLs up to 20 years.
The Post-1997 Period (Fiscal Year-End of August 1998 and Later)
Firms can carry back NOLs up to two years:
Our main test is whether firms have incentives to report larger losses in year t based on whether
the firm can carry back losses against income in the earliest carryback year (t�2). We define taxable
income (TI) as current tax expense divided by the top statutory tax rate. We calculate NOLC as
In words, A1 defines the capacity to carry back losses (NOLC) in year t as the amount of taxable
profits in t�2 that has not been used to claim a refund from tax losses in year t�1. If the firm did not
generate a taxable profit in t�2 (TIt�2 � 0), then there is no tax available to refund, and the outside
maximization function ensures that NOLC will simply equal 0. But if the firm has taxable profits in
t�2 (TIt�2 . 0), then we must first determine how much of those taxable profits in t�2 were offset
through tax losses in year t�1. This adjustment is given by MIN[0,TIt�1 þ MAX(0,TIt�3)] in
Equation (A1). If the firm has a taxable profit in year t�1, then this adjustment equals 0 and the full
amount of t�2 taxes paid is available for refund. If the firm had taxable losses in year t�1 (TIt�1 ,
0), then we must ask whether the firm had taxable income in t�3. A loss in year t�1 will first be
carried back against profits in year t�3, and the profits available to be offset by year t�1 losses are
presented by MAX(0,TIt�3). If the year t�1 loss exceeds the year t�3 income (if any), then the
1680 Erickson, Heitzman, and Zhang
The Accounting ReviewSeptember 2013
excess loss is taken against t�2 income, and this is the adjustment given by MIN[0,TIt�1 þMAX(0,TIt�3)].
To illustrate the potential values of NOLC as a function of prior taxable profit and loss patterns,
consider the cases in the following table:
Case
TaxableProfits/Losses
in EarliestCarryback Year
TIt�2
TaxableProfit/Lossin Year t�1
TIt�1
Taxable Profitsin Year t�3
Available to OffsetYear t�1 Losses
MAX(0,TIt�3)
Amount of Yeart�1 Loss Not Covered
by Profits in t�3MIN[0,TIt�1
þ MAX(0,TIt�3)]
Max. Amountof Loss in Year
t that can beCarried Back
to Obtain Refundof t�2 Taxes
NOLC
(1) (2) (3) (4) (5)
1. 10 0 20 0 10
2. 5 5 10 0 5
3. 10 �10 10 0 10
4. 10 �20 10 �10 0
5. 10 �15 10 �5 5
6. �10 0 0 0 0
Cases 1 through 5 represent firms with taxes paid on profits in the earliest carryback year. Cases 1
and 2 represent firms with no tax loss in t�1 (and hence no offset of t�2 profits). Case 3 provides an
example of a firm whose tax loss in year t�1 was offset entirely against profits in year t�3,
preserving the entire capacity of t�2 profits to offset losses in t. Case 4 represents the case where a
loss in t consumed both t�3 and t�2 profits, while in Case 5, only a portion of the profits in t�2 are
used up to offset losses in t�1. The remainder in Case 5 is the amount available for use against
losses in t. The final case simply illustrates that firms that paid no taxes in t�2 (or reported a loss)
will have no capacity for carryback of t losses regardless of what happens in year t�1 or t�3.
The Pre-1997 Period
Firms can carry back NOLs up to three years.
Here, we calculate NOLC as follows:
NOLC ¼ MAX
�0; TIt�3 þMIN
h0; TIt�2 þMAXð0; TIt�5Þ þMAXð0; TIt�4Þ
i
þMINh0; TIt�1 þMAX
�0; TIt�4 þMIN
�0; TIt�2 þMAXð0; TIt�5Þ
��i�: ðA2Þ
Due to the dynamics involved with three carryback years, the formula is more complex. But the
intuition and results are similar as in A1. Numerical examples using this formula are available from
the authors upon request, but can be easily replicated.
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D_NOL
D_NOL is a dummy variable that takes a value of 1 if NOLC is positive for a firm in an
expected loss position, and 0 otherwise. Firms with expected losses are those with negative
analysts’ consensus (median) forecasts made eight months prior to fiscal year-end (D_NEG ¼ 1).
Our NOLC (and hence D_NOL) measure is subject to a potential sources of measurement error.
First, taxable income includes both operating income/loss and capital gain/loss, which have
different carryback and carryforward rules. We do not make such a distinction because the
carryback periods are largely similar and because we can only estimate taxable income. Second,
measurement errors arise because the average tax rate is not equal to the top statutory tax rate owing
to progressive tax schedules. Third, current tax expense does not reflect the tax benefits from the
exercise of non-qualified employee stock options (reflected as a reduction in current tax liability)
and is reported net of tax cushions and tax credits (Hanlon 2003). Fourth, we do not incorporate the
magnitude of expected losses related to previous years’ profits, as analysts’ earnings forecasts are a
noisy proxy for a firm’s tax profits/losses. Incorporating the magnitude of expected losses would
make our NOLC formula too complicated. Fifth, firms were allowed to carryback NOLs for five
years in 2001/2002 and 2008/2009. We do not incorporate the five-year carry backs in our measure,
as the five-year carryback period was often not known until a later date. In addition, a five-year
carryback would make our measure extremely complicated. Finally, we do not incorporate the
information of net operating loss carryforwards on the balance sheet because of jurisdictional
differences and the impact of NOLs acquired in mergers and acquisitions. Moreover, research by
Mills et al. (2003) raises a number of additional concerns using Compustat data to infer net
operating loss positions. We hand-checked a number of cases and find that many firms were able to
claim tax refunds when reporting non-missing NOL carryforwards in their financial statements.
While we can certainly refine our NOLC measure along the directions mentioned above,
incorporating such issues would make our measure unduly complicated. We believe that such
measurement errors introduce noise to our measure and, if anything, are likely to bias against
finding any significant results. With that in mind, we prefer a relatively simple measure as used in
the paper.
Alternative Specifications of NOLC and D_NOL
We consider the following alternative specifications of NOLC and D_NOL. In the first
alternative specification, we replace expected losses proxied by analysts’ forecasts with those based
on a time-series earnings models in which we regress current year’s earnings (from Compustat) on
last year’s earnings and earnings in the year before. Then we use coefficient estimates based on
historical data and the most recent set of earnings data to calculate forecasted earnings for the next
year. D_NOL is equal to 1 if NOLC is positive and forecasted earnings are negative. In the second
alternative specification, we drop the requirement of expected losses. Rather, we require taxable
income to be positive in year t�2 and to be negative in year t�1 in the post-1997 period. In the pre-
1997 period, we require taxable income to be positive in year t�3 and to be negative in year t�2 and
t�1. In both cases, we require that tax paid in the first year of the NOL carryback window has not
been fully refunded. We find robust empirical results across these two alternative specifications
(results not tabulated).
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