Substitution between Real and Accruals-Based Earnings Management
after Voluntary Adoption of Compensation Clawback Provisions

ABSTRACTTo deter financial misstatements, many companies have recently adopted compensation
recovery policies – commonly known as “clawbacks” – that authorize the board to recoupcompensation paid to executives based on misstated financial reports. Clawbacks havebeen previously shown to reduce financial misstatements and increase investors’
confidence about earnings information. We show that such benefits come at the cost offirms substituting earnings management tools. In particular, while clawback-adopting
firms reduce accruals management, they increase real transactions management (e.g.,
reduce R&D expenditures). As such, the total amount of earnings management does notdecrease subsequent to clawback adoption. We further show that the substitution effect ismore pronounced in firms with high growth opportunities, as these firms’ stock prices
typically drop sharply after missing earnings benchmarks. Finally, we show that those
clawback firms that engage in more real transaction management experience greater
underperformance as measured by return on assets in the post-adoption period. In
summary, clawbacks may have unintended consequences for firms whose managers feelpressure to maintain certain profitability levels.

I. INTRODUCTION
One of the most notable recent changes in executive compensation practices has
been an increase in the use of compensation recovery policies – commonly known as“clawbacks” – among public companies. Clawbacks are provisions that authorize theboard of directors to recoup compensation paid to managers based on misstated financial
reports. Among industrial firms covered in the Russell 3000, the number of firms withclawbacks increased from 19 to 444 over the 2005 to 2009 period. This number is
expected to increase further as Section 954 of the 2010 Dodd-Frank Wall Street Reformand Consumer Protection Act (hereafter, DFA 954) requires all U.S. listed companies toadopt and implement clawbacks as of July 2012. 1
Given that clawback provisions have become a widely-used governance mechanismthat is now mandatory for all U.S. listed firms, the effectiveness of clawbacks has
attracted a great deal of attention from academics and the business press alike. Extant
research suggests that clawbacks voluntarily adopted by firms lead to a reduction in
financial misstatements, which investors welcome as indicated by higher earnings
response coefficients (ERCs) for adopting firms. External auditors also respond toclawback initiation positively by reducing effort when auditing clients with such

1

Regulatory clawbacks were first introduced by Section 304 of the Sarbanes-Oxley Act (SOX) in 2002.
Specifically, SOX 304 authorizes the Securities and Exchange Commission (SEC) to recoup bonuses paid
to CEOs and CFOs of public companies when the company restates its financial statements due tomaterial noncompliance with any financial reporting requirement as a result of misconduct. However, as
Chan et al. (2012) point out, SOX 304 has rarely been enforced by the SEC, likely due to the SEC’s
limited recourses and difficulty in proving managerial misconduct. In response, Section 954 of the DoddFrank Act designates the board of directors rather than the SEC as the enforcer of clawbacks. Note that
because the Dodd-Frank Act only became effective in July 2012, the effectiveness of mandatory
clawbacks cannot be examined at this time.

1

provisions (Chan et al. 2012; DeHaan et al. 2012). 2 Therefore, firm-initiated clawbacks
appear to effectively deter financial misstatements.
However, a reduction in the occurrence of accounting restatements subsequent toclawback adoption does not necessarily suggest an improvement in earnings quality. As
Denis (2012) argues, decreased financial misstatements after clawback initiation may be
driven by managers’ reluctance to disclose restatements to avoid triggering clawbacks orby auditors’ reduced effort to uncover accounting irregularities. As such, whether
earnings manipulation does indeed decrease after clawback adoption remains an open
question.
In this study, we first examine whether clawbacks reduce accruals management. We
predict that clawbacks deter managers from using accruals management as highaccounting accruals tend to attract more scrutiny from the SEC and auditors, and hence
are more likely to be associated with accounting restatements, which trigger clawbacks(Dechow et al. 2010).
Next, we investigate whether clawbacks cause managers to use greater realtransactions management – that is, whether there is a substitution between accruals andreal transactions management. Relative to accruals management, real transactions are
considered less risky as they are unlikely to be deemed illegal by auditors and regulators.
The rational expectations equilibrium model constructed by Ewert and Wagenhofer (2005)
also shows that a regulation intended to improve earnings quality (e.g., reduce
discretionary accruals or improve ERCs) may actually induce managers to resort to otherforms of earnings management such as real transactions management. In particular, with2

Moreover, Iskandar-Datta and Jia (2013) find a significantly positive market reaction to announcementsof clawback adoption and a reduction in bid-ask spreads following adoption, particularly in firms withprevious restatements.

2

a higher ERC, any increase in earnings will lead to a higher valuation multiple, which inturn will increase the value of managers’ stock-based compensation or stock holdings andthereby provide stronger incentives for managers to manipulate earnings. 3 Consistent
with this prediction, Cohen et al. (2008) find that while the Sarbanes-Oxley Act reduces
accruals-based earnings management, it causes managers to use real transactions tomanage earnings. Roychowdhury (2006) and Zang (2012) also show that managers arelikely to use real transactions management instead of accruals management when they are
subject to tighter scrutiny. Thus, while clawbacks may constrain accruals management,
they may also encourage real transactions management. This substitution represents anunintended consequence of clawback provisions that has not been documented before.
Our study starts with a sample of non-financial clawback adopters and non-adoptersin the Russell 3000 index as covered by the Corporate Library dataset. To deal with thepotential endogeneity associated with clawback adoption, we use a double propensityscore-matching approach to identify 239 pairs of clawback adopters and non-adopterswith the closest firm characteristics (e.g., firm size, industry membership, growth
opportunities) to test our empirical hypotheses. Using a difference-in-differences design,
we find that the adoption of clawback provisions is associated with lower accruals
management, which is consistent with two contemporaneous papers (Babenko et al. 2012;
Chen et al. 2013). Importantly, we find the reduced accrual manipulation is accompanied
by greater real transactions management. In particular, relative to pre-adoption periods
and control firms, clawback adopters exhibit a reduction in positive discretionary accruals

3

Real transactions management refers to actions taken by managers that deviate from optimal businesspractices to achieve certain earnings benchmarks (Jiambalvo 1996; Roychowhury 2006). Examples
include discretionary reduction of R&D or SG&A expenses or overproduction to lower costs of goods
sold.

3

(but not in negative discretionary accruals), and they also exhibit a reduction indiscretionary expenses such as R&D, SG&A, and marketing. Moreover, we find that after
implementing clawbacks, clawback adopters have abnormally low operating cash flow,which is another common measure of real transactions management. This could be driven
by an intention to inflate sales revenue via aggressive price discounts or credit terms thatare too lenient (Roychowdhury 2006). Taken together, the results imply that clawback
provisions increase the cost of accounting-based manipulation and thus lead managers toresort to less detectable forms of earnings management. Our results are robust to using
the Heckman model to address the endogeneity issues associated with earnings
management or clawback adoption.
Following Badertscher (2011), we also construct a measure of total earnings
management by cumulating the amounts of accruals management and real transactions
management. This measure indicates that total earnings management does not decrease after
clawbacks (rather, it increases marginally) – that is, the decrease in accruals management
seems to be offset by an increase in real transactions management subsequent to clawback
initiation. This result further confirms that clawbacks are associated with unintended

consequences.
Next, we find that the substitution between accruals management and realtransactions management is mainly driven by clawback adopters with higher growth
opportunities (relative to non-adopting firms with similar growth characteristics). This
result is consistent with Matsumoto’s (2002) finding that managers of high growth firms
have stronger incentives to manage reported earnings to avoid negative earnings surprises,
as they suffer a larger drop in share price if they miss consensus forecasts as compared tovalue firms (Skinner and Sloan 2002).
4

Finally, we find that clawback firms that engage in a greater extent of realtransactions management after adoption (relative to clawback adopters that do notincrease real transactions management) experience a decline in future profitability as
measured by return on assets in the post-adoption period, and the underperformance ispersistent up to three years. This result is consistent with previous studies (e.g., Bhojraj et
al. 2009; Cohen and Zarowin 2010) that show that real transactions management
decreases long-term firm value as it represents a deviation from optimal operating
decisions.
Our study has implications for the mandatory clawback provisions recently
implemented under DFA 954. Complementing the finding in Chan et al. (2012) and
DeHaan et al. (2012) that firm-initiated clawbacks reduce financial misstatements, wedocument that such provisions also lead to a reduction in accruals manipulation – a moreprevalent form of earnings management. However, we show that the decrease in accruals
manipulation is met with an increase in real transactions management. This substitution isconsistent with Cohen et al. (2008), who show that firms switched from accruals
manipulation to real transactions management after the passage of SOX. 4 Thus, our study
implies that a mechanism designed to improve financial reporting quality may haveunintended consequences. In particular, we provide evidence of clawbacks’ costs: those
clawback adopting firms that engage in more real transactions management perform
worse in subsequent years. Moreover, we document that the substitution of accruals
manipulation by real transactions management occurs mainly among clawback adopters
4

Although Cohen et al. (2008) document a substitution between accruals management and real transactions
management after the passage of SOX, it is not clear which section of SOX contributes to this effect. In
particular, Sections 302 and 404 (disclosure of internal control weakness) are both shown to improve
accruals quality (e.g., Ashbaugh-Skaife et al. 2008), and Section 304 introduces the first mandatory
clawbacks (which may also affect managers’ choice of earnings management tools). As our study focuses
on firm-initiated clawbacks, we are better able to draw conclusions on the effects of such provisions.

5with high growth opportunities, which suggests that the unintended consequences
associated with clawback provisions may be more severe for certain types of firms. In
particular, as long as managers have pressure to beat or meet earnings benchmarks, theuniform adoption of clawback provisions as required by DFA 954 may not necessarily
improve overall financial reporting quality.
The rest of the paper is organized as follows. Section II develops our testable
hypotheses. Section III discusses the sample. Section IV presents our research design andreports the results. Section V concludes.

II. HYPOTHESIS DEVELOPMENT
Accruals Management
Firm-initiated clawbacks have become popular among public companies since 2005.
For instance, 194 firms on the S&P 500 index had adopted clawbacks as of early 2011
(Addy and Yoder 2011). While the financial media have raised questions about theeffectiveness of firm-initiated clawbacks (e.g., Dvorak and Ng 2006; Weiss 2009; Lublin
2010), Chan et al. (2012) and DeHaan et al. (2012) find that financial misstatements
decrease, and investors consider earnings to be more informative, after clawback
adoption. Moreover, Chan et al. (2012) find that audit fees are lower after clawback
provisions are adopted. Iskandar-Datta and Jia (2013) further find a significantly positivemarket reaction to clawback adoption announcements. Although the above findings are
subject to alternative interpretations (Denis 2012), firm-initiated clawbacks appear todeter financial misstatements and improve the integrity of financial reporting. 55Denis (2012) argues that the decrease in financial misstatements after clawback initiation may be driven
by managers’ reluctance to disclose restatements to avoid triggering clawbacks or by auditors’ reduced

6

We expect clawback adoption to lead to a reduction in accounting-based
manipulation, i.e., accounting accruals manipulation. First, to avoid accounting
restatements, managers of clawback adopters are expected to engage in earnings
manipulation that is less likely to exceed the boundaries of GAAP and hence less likely
to be detected by regulators or auditors. 6 As Dechow et al. (2010, page 349) argue,
financial reports with high accruals tend to attract more scrutiny from the SEC and are
more likely to trigger accounting restatements. Second, managers subject to clawback
provisions enhance internal control systems to prevent potential misstatement (Chan et al.
2012). As Ashbaugh-Skaife et al. (2008) show, remediation of internal control
deficiencies prevents managers from accruals manipulation (e.g., misreporting warranty
liabilities or the allowance for bad debt). Accordingly, we predict that accruals
management decreases following the adoption of clawbacks. More formally:
H1a: Accruals-based earnings management decreases subsequent to the adoption of
clawback provisions.

Real Transactions Management
However, it is unlikely that clawback provisions eliminate all types of earnings
manipulation, particularly when managers have pressure to meet or beat earnings
targets. 7 Previous research shows that, in addition to accruals management, real

effort to discover accounting irregularities. That is, overall financial reporting quality may not necessarily
improve subsequent to clawback adoption.
6
As indicated in Collins and McInnis (2011), an earnings management tool is considered more costly if it
has a higher probability of attracting regulatory scrutiny or shareholders’ attention.
7
Meeting certain earnings benchmarks is important as doing so increases the firm’s credibility with thecapital market, supports the firm’s stock price, and promotes the reputation of the management team
(Burgstahler and Dichev 1997; Graham et al. 2005). Missing an earnings benchmark, in contrast, creates
uncertainty about the company’s future and can lead executives to suffer personal financial penalties(Matsunaga and Park 2001). Other than capital market incentives, executive compensation is also tied to7

transactions management (e.g., cutting back on R&D or SG&A expenditures) is anothermeans to manage earnings. The use of real transactions represents a deviation from
optimal operating decisions, but is not likely to be deemed illegal by regulators or
auditors (Roychowdhury 2006). Thus, managers often resort to real transactions before
turning to accruals to meet or beat earnings targets (Zang 2012). In their survey of CFOs,
Graham et al. (2005) find that a majority of financial executives are willing to cut
discretionary expenditures such as R&D or advertising to maintain accounting
appearances even if such actions sacrifice the firm’s long-term performance.
Using a rational expectations model, Ewert and Wagenhofer (2005) demonstrate thata regulation intended to improve earnings quality may actually lead managers to use
other manipulation tools such as real transactions. The reason is that better earnings
quality leads to higher value relevance (i.e., a stronger association between reported
earnings and stock price). In addition, better earnings quality can encourage
compensation committees to put more weight on reported earnings in determining
executive compensation. Thus, managers benefit more by increasing earnings using
lawful real transactions management. Consistent with this prediction, Cohen et al. (2008)
show that after the passage of SOX, accruals management decreases while realtransactions management increases. That is, when regulatory scrutiny or shareholder
monitoring increase, managers tend to shift from accruals management to realtransactions management. Accordingly, we predict that managers of clawback adopters
increase the use of real transactions management subsequent to the adoption of clawbacks.
More formally:

reported earnings, thereby providing incentives for managers to manipulate earnings. Please see Beyer etal. (2010) for a detailed literature review.

8H1b: Real transactions management increases subsequent to the adoption of
clawback provisions.

Clawback Adopters with High vs. Low Growth Opportunities
Hypotheses H1a and H1b predict that clawback provisions lead firms to substituteearnings management tools. We next predict that this phenomenon is more pronounced
among clawback firms with high growth opportunities. Skinner and Sloan (2002) showthat growth companies experience a sharper decline in share price after missing
consensus forecasts as compared to value firms. Further, extant literature on executive
compensation shows that executives of firms with higher growth opportunities (e.g.,firms with high market-to-book) tend to receive more stock options or restricted stock
than executives of firms with lower growth opportunities (e.g., Murphy 2003). Taken
together, this evidence suggests that relative to CEOs of value firms, managers of growthcompanies experience a larger financial loss if their firms fail to meet or beat earnings
benchmarks and hence have stronger incentives to achieve earnings targets. We thus
predict that among clawback adopters, those with greater growth opportunities are more
likely to turn to real transactions management to meet or beat earnings targets. Moreformally:
H2: Among clawback adopters, those with high growth opportunities are more
likely to shift from accruals management to real transactions management
subsequent to the adoption of clawback provisions.

9III. SAMPLE
We obtain data on clawback provisions from Corporate Library. Corporate Libraryidentifies 638 firms in the Russell 3000 index as clawback adopters as of early 2010.
Since we are interested in the effect of firms’ voluntary initiation of clawback provisions
on managers’ choice of earnings management tools, we exclude financial firms from theanalysis because financial institutions that received federal bailout funds during thefinancial crisis in 2008 and 2009 are subject to mandatory clawbacks enforced by the
Department of Treasury. After excluding financial firms and those whose clawback
provisions are solely related to “non-compete” restrictions, we have 444 firms withclawback provisions in place by fiscal year-end 2009, and 1,918 firms without suchprovisions. 8 For the 444 clawback firms, we manually identify the year in which they
initiated their clawback policy by searching company websites, news announcements,and firms’ proxy statements. As shown in the first column of Table 1, Panel A, firminitiated clawbacks were rare in 2005 (there were only 19 firms with such provisions),
but became increasingly popular since 2006. In Panel B of Table 1, we present theindustry distribution for the 444 clawback adopters in the Corporate Library database.
Based on two-digit SIC codes, we find that clawback adopters are fairly evenly
distributed over industries.

8

Non-compete clawback provisions are restrictive covenants that apply to executives who violate noncompete clauses. For example, the non-compete clawback provision of Texas Instruments Inc. states that
“Options may be cancelled if the grantee competes with TI during the two years after employment
termination or discloses TI trade secrets. In addition, for options received while the grantee was an
executive officer, the company may reclaim (or ‘claw back’) profits earned under grants if the officer
engages in such conduct. These provisions are intended to strengthen retention and provide a reasonable
remedy to TI in case of competition or disclosure of our confidential information.” Because non-compete
clawback provisions are not related to accounting restatements or misconduct, we exclude them from ouranalysis. However, some companies have both non-compete clawback provisions as well as clawback
provisions that deal with misconduct leading to accounting fraud or restatements of financial statements(e.g., Chubb Corporation). We include such firms in our clawback sample.

10

To test our empirical hypotheses, we require clawback adopters and non-adopters tohave the necessary data in Compustat, CRSP, Corporate Library, Risk Metrics, and Audit
Analytics. This merging process reduces our primary sample to 343 firms with clawback
provisions in place as of 2009 and 1,840 firms that do not have such provisions in placeat any point during our sample period.
[INSERT TABLE 1 HERE]
Panel C compares salient firm characteristics across the 343 clawback adopters and
1,840 non-adopters. We find that, on average, clawback adopters have larger firm size,
lower sales growth, more operating segments, better profitability, and better corporate
governance in terms of institutional ownership and board independence. The informationin Panel C indicates that clawback adopters are different from non-adopters along several
dimensions, suggesting potential endogeneity associated with the decision to adopt
clawbacks. As such, we employ propensity score matching (PSM) to control forobservable differences between clawback adopters and non-adopters. Specifically,following Chan et al. (2012) and DeHaan et al. (2012), we model clawback adoption as afunction of firm size, market-to-book ratio, sales growth, leverage, ROA, number ofsegments, restatement history, institutional ownership, board independence, industry
membership, and year fixed effects using a Probit model. Results of this analysis arereported in Table A1 in the Appendix. We find that clawbacks are positively associatedwith firm size and number of segments and negatively related to sales growth. Consistent
with Babenko et al. (2012), we also find that clawback adoption is marginally positive
associated with a firm’s restatement history and board independence. Next, for each
clawback adopter, we choose the non-adopter with the closest propensity score as the11control firm. Specifically, we use a one-to-one firm matching with a caliper of 0.1, and acommon support range of [0.1 to 0.9] (Caliendo and Kopeinig 2008). This procedureyields 254 pairs of clawback adopters and control firms. One concern with a single roundof PSM is that it may not control fully for observable differences across clawback
adopters and non-adopters. Thus, as suggested in Peel and Makepeace (2009), we
perform a double PSM – that is, we perform the same procedure as described earlier (i.e.,the clawback selection model) on the 254 matched pairs again. This second round of
PSM further reduces the sample size to 239 pairs of clawback adopters and control firms,
which we use as the primary sample for our empirical tests.
The two rounds of PSM seem to successfully alleviate observable differences acrossclawback adopters and control firms as shown in Panel D of Table 1. That is, considering
the same set of firm characteristics as in Panel C, clawback adopters are on average
statistically indistinguishable from their matched control firms, indicating that ourmatching procedure achieves a covariate balance. 9

IV. EMPIRICAL RESULTS
Following extant studies on firm-initiated clawbacks (Chan et al. 2012; DeHaan et al.
2012), we use the difference-in-differences approach to test our hypotheses. Specifically,
we employ the following research design:
Y = α + β1PostClawback + βX + u + d + ε,

9(1)

We notice that after the first round of matching, the 254 clawback adopters on average still have larger
firm size and better ROA than the control firms, with the difference marginally significant at the 10%
level. To fully achieve covariate balance, we perform the second-round matching.

12where Y is the dependent variable of interest (i.e., the absolute value of discretionary
accruals or measures of real transactions management). PostClawback is an indicatorvariable that equals one if the company is a clawback adopter in those years in which theclawback provision is implemented, and zero otherwise. The coefficient on
PostClawback measures the change in the dependent variable of interest across pre- andpost-adoption periods for a clawback firm compared to the change over the same interval
for a control firm. X is a vector of control variables. u and d denote firm- and yearspecific fixed effects. The inclusion of firm fixed effects helps control for time-invariant
differences across clawback adopters and control firms that may not be alleviated by
PSM. Finally, standard errors are adjusted based on the Huber-White sandwich estimateof variances and are clustered by firm.

Accruals-Based Earnings Management
Following existing literature, we use performance-adjusted discretionary accruals toproxy for accruals management (see Kothari et al. 2005). Specifically, we first estimate
the following modified Jones model (1991) cross-sectionally for industry-years with atleast 20 observations:
TAit /Asseti,t-1 = α + β1(1/ Asseti,t-1) + β2(∆Salesit /Asseti,t-1)+ β3( PPEit/Asseti,t-1)+ εit,(2)

where TA is earnings before extraordinary items and discontinued operations minus theoperating cash flow reported in the statement of cash flows in year t (Collins and Hribar2002). Asset denotes total assets, and PPE is gross property, plant, and equipment.
Finally, following Kothari et al. (2005), we subtract the change in accounts receivable

13

from the change in sales revenue (∆Sales) prior to estimating equation (2). 10 The
estimated residuals from equation (2) are discretionary accruals and are used to proxy for
accruals manipulation.

Real Transactions Management
Following Roychowdhury (2006), we proxy for real transactions management using
three measures, ABCash, ABExp, and ABProd, which represent abnormal levels of cash
flow from operating activities, discretionary expenses (the sum of R&D, advertising, and
SG&A expenses), and production costs, respectively. ABCash, ABExp, and ABProd, areresiduals obtained from the following three regressions:
Expense =α +β1(1/Assett-1) + β1(Salest-1/Assett-1)+ εt(3)

Production =α + β1(1/Assett-1) + β1(Salest /Assett-1 )+ β2(∆Salest /Assett-1 )+ β3(∆Salest-1/Assett-1 )+ εt.

(4)

CFO =α +β1(1/Assett-1) + β1(Salest /Assett-1)+ β2(∆Salest /Assett-1)+ εt(5)We estimate equations (3) to (5) by year and two-digit SIC codes for all firms in
Compustat during our sample period (2000-2009). 11 The estimated coefficients from thecorresponding industry-year are used to compute firm-specific ABExp, ABProd, andABCash. Roychowdhury (2006) posit that managers often cut discretionary expenses
such as advertising or R&D expenses to boost short-term earnings, suggesting a negative
ABExp. Moreover, a positive ABProd suggests that managers overproduce inventory
10

Kothari et al. (2005) indicate that subtracting the change in accounts receivable from the change in sales
in the first stage helps to avoid overestimating discretionary accruals for firms with extreme growth. Also,
following Kothari et al. (2005), we include an intercept in equation (2); our results remain qualitatively
similar if we exclude the intercept.
11
As in footnote 10, we again include an intercept in equations (3) to (5) following Roychowdhury (2006)
and Gunny (2010); our results remain qualitatively similar if we exclude the intercept.

14

items to reduce costs of goods sold per unit for a higher reported operating income.
Finally, to inflate sales revenue, managers are likely to offer price discounts or lenientcredit terms, though these practices may lead to lower operating cash flow (a negative
ABCash). We also create an overall measure of real transactions management bysumming ABCash, ABExp, and ABProd (Badertscher 2011). Specifically, we multiply
ABExp and ABCash by -1 so that the three variables represent real transactions
management in a consistent fashion (because companies with greater real transactions
management are expected to have a positive ABProd but a negative ABExp and ABCash).

The Impact of Clawbacks on Accruals Management
To examine whether firms that adopt clawback provisions decrease accruals
management (H1a) and increase real transactions manipulation (H1b), we estimate thefollowing regression models, which follow Ashbaugh-Skaife et al. (2008), Cohen andZarowin (2010), and Zang (2012):
AMit (or RTMit) = α+ β1PostClawbackit + β2Sizeit + β3M/Bit + β4ROAt + β5ZScoreit+ β6MktShareit + β7MTRit + β8Inst%it + β9BigFourit + β10AuditTenureit+ β11Cycleit + β12NOAit + β13RTMit (or AMit) + ui + dt + εit.

(6)

AM is the value of performance-adjusted accruals as described earlier. RTM is one ofthree measures, ABCash, ABExp, and ABProd, as defined above. PostClawback isdefined as in equation (1). Size is the natural log of total assets. M/B is the market-tobook ratio. ROA is income before extraordinary items divided by lagged total assets.
Following Zang (2012), we include ZScore, MktShare, MTR, and Inst% to control for thecosts associated with real transactions management: ZScore is the decile of Altman’s z-

15

score, MktShare is the Herfindahl index using 2-digit SIC-codes, MTR is the marginal tax
rate, and Inst% is the percentage of institutional ownership. Zang (2012) shows that firms
with better financial health (higher ZScore) and larger market share (MktShare) are more
likely to engage in real transactions management. On the other hand, higher marginal tax
rates (MTR) and institutional ownership (Inst%) constrain the use of real transactions
management. Next, we include BigFour, AuditTenure, NOA, and Cycle to proxy for thecosts related to accruals manipulation. BigFour is a dummy variable equal to one if thecompany is audited by one of the Big-4 CPA firms, and zero otherwise. AuditTenure is adummy variable equal to one if the number of years the auditor has audited the client isabove the sample median, and zero otherwise. NOA is a dummy variable equal to one if
net operating assets (i.e., shareholders’ equity less cash and marketable securities plus
total debt) at the beginning of the year divided by lagged sales is above the median of thecorresponding industry-year, and zero otherwise. Cycle is days receivable plus days
inventory less days payable. We expect that managers are less likely to use accruals
manipulation when they face stronger scrutiny by external auditors, suggesting that Big-4
auditors (BigFour) and auditor tenure (AuditTenure) are negatively related to accruals
management. The use of accruals management in the current year is expected to beconstrained by prior years’ accruals manipulation, suggesting a negative association
between NOA and the amount of accruals management (Barton and Simko 2002). Firms
with a longer operating cycle are expected to have more flexibility in using accruals
management, suggesting a positive relation between Cycle and AM. Finally, following
prior studies that document a substitution between real transactions management andaccruals manipulation (e.g., Cohen et al. 2008), we include AM (RTM) as a control

16

variable when the dependent variable is RTM (AM). ui and dt are, respectively, firm andyear fixed effects. This regression is based on 3,582 firm-year observations for 239 pairsof clawback adopters and non-adopters over the 2000 to 2009 period. The coefficient on
PostClawback measures the change in the levels of discretionary accruals and realtransactions management for a firm before and after clawback adoption and compares
this change with that for a control firm over the same period.
[INSERT TABLE 2 HERE]
The results of equation (6) are presented in Table 2. Before moving to the regression
results, in Panel A we provide descriptive statistics for key variables used to test equation(6). We find that relative to the control firms, clawback adopters have a lower absoluteamount of discretionary accruals (|AM|), while they have a similar amount of signed
discretionary accruals (AM). For real transactions management, we find that clawback
adopters on average have lower discretionary expenses and lower cash flow operating
activities, suggesting that they have greater real transactions management.
Next, turning to the regression results in Panel B, we find that in the first column,
where the dependent variable is the absolute value of discretionary accruals (|AM|), thecoefficient on PostClawback is significantly negative (-0.013, t = -2.35), indicating thatthe amount of unsigned discretionary accruals is lower subsequent to the adoption of
clawback provisions. 12 In the second column, where the dependent variable is signed

12

To confirm the robustness of our results, we also use an accruals measure following Dechow and Dichev(2002). Specifically, we run the following regression for each industry based on 2-digit SIC codes: ∆WC= β0 + β1CFOt-1 + β2CFO t + β3CFOt+1 + ε, where CFO is operating cash flow scaled by total assets, andWC is computed as {[∆Current Assets - ∆Cash and Short-term Investments]-[∆Liabilities - ∆Debt inCurrent Liabilities - ∆Taxes Payable]} scaled by total assets. After performing the regression, we
calculate the mean absolute value of the residual (ε) for each industry, and we then subtract the industrymean residual from the absolute value of each firm’s residual. We find that our conclusions are unaffected17

accruals, the coefficient on PostClawback becomes statistically insignificant (-0.009, t = -1.02). The inconsistent results between the first two columns may be caused byclawback provisions’ different impacts on positive and negative accruals. To further
investigate this issue, we next estimate equation (6) separately for firms with positive andnegative accruals – that is, we partition the 3,582 firm-year observations into two groups
based on the sign of discretionary accruals. The results of this analysis are provided in thethird and fourth columns. The coefficient on PostClawback is negatively significant in
the third column (-0.024, t = -3.00), whereas it is positive but insignificant in the fourthcolumn (0.004, t = 0.46). The results indicate that the reduction in discretionary accruals
subsequent to clawback adoption is driven primarily by positive discretionary accruals.
Thus, clawback provisions seem to constrain income-increasing accruals, but not
downward accruals manipulation.
Next, we present the results of real transactions management in columns (5) to (8).
In column (5), where ABExp is the dependent variable, we find that the coefficient on
PostClawback is significantly negative (-0.022, t = -2.19), suggesting that adopting firms
reduce discretionary expenses after clawback adoption. Turning to the sixth column,
which presents results using ABProd as the dependent variable, we find that thecoefficient on PostClawback is insignificant, which indicates that clawback adopters do
not engage in abnormal production after adopting clawbacks. In column (7), where thedependent variable is ABCash, we find that the coefficient on PostClawback issignificantly negative (-0.017, t = -2.02), indicating that clawback adopters are associatedwith abnormally low operating cash flow. We also consider the overall measure of RTM,

by using this method to calculate accruals. Untabulated results indicate that the coefficient on
PostClawback is -0.020 (t = -2.58), suggesting that clawback adoption improves accruals quality.

18

which is the sum of ABCash, ABExp, and ABProd, as the dependent variable. As statedearlier, we multiply ABExp and ABCash by -1 to ensure the three variables represent real
management in a consistent fashion (the more positive the number is, the higher the real
manipulation). The results in column (8) confirm that clawback adopters engage in more
real transactions manipulation in the post-adoption period as the coefficient on
PostClawback is significantly positive (0.032, t = 2.78). The control variables, wheneversignificant, take the predicted signs. To summarize, the results in Panel B of Table 2
indicate that the passage of clawback provisions leads to reduced accruals manipulation
but greater real transactions management. Given the two opposite effects, a natural
question to ask is how clawbacks affect the overall level of earnings management. To doso, we sum the unsigned accruals (AM) and the aggregate real transactions management(RTM) to construct EM, the overall level of earnings management. The result of thisanalysis is presented in column (9). We find that the coefficient on PostClawback issignificantly positive (0.024, t = 1.69), indicating that the increase in real transactions
management dominates the reduction in accruals manipulation, thereby leading to amarginal increase in the total amount of earnings management subsequent to clawback
initiation.13
As Cheng and Warfield (2005), Bergstresser and Philippon (2006), and Efendi et al.
(2007) find, earnings manipulation activities are affected by incentives stemming from
option grants or managers’ stock holdings. To check the robustness of our findings, we
13

As suggested in Roberts and Whited (2013), we also repeat the analyses in Table 2 without any
covariates. That is, we include only PostClawback and firm and year-fixed effects without any control
variables and re-estimate equation (6). Roberts and Whited (2013) indicate that if the assignment oftreatment and control firms is random, the inclusion of covariates (control variables) should have anegligible effect on the coefficient of PostClawback. The analysis (untabulated) suggests that thecoefficient on PostClawback is quite comparable to those reported in Table 2. This provides further
support that the double PSM procedure has achieved random assignment of treatment (clawback adopters)
and control firms (non-adopters).

19next add control variables related to executive compensation and re-estimate equation (6).
Specifically, following Cheng and Warfield (2005) and Cohen et al. (2008), we include
the variables Bonus, Option_Grant, Option_Ex, Option_Un, and Owner. Bonus is CEO
annual bonus compensation as a proportion of total compensation. Option_Grant is thenumber of options granted to the CEO during the year divided by the firm’s totalcommon shares outstanding. Option_Ex is the number of exercisable options held by the
CEO at year-end divided by the firm’s total common shares outstanding. Option_Un is
the number of unexercisable options (excluding annual option grants) held by the CEO at
year-end divided by the firm’s total common shares outstanding. Owner is shares ownedby the CEO divided by the firm’s total common shares outstanding.
The results of this analysis are presented in Panel C, Table 2. In short, the results are
similar to those reported in Panel B. In particular, clawback initiation leads to a reductionin the use of discretionary accruals (i.e., positive discretionary accruals), while it
increases reliance on real transactions management. Turning to the control variables,
consistent with Cohen et al. (2008), we find that the number of unexercisable options
held by the CEO, annual option grants to the CEO, and CEO stock ownership are
positively related to the use of accruals management. 14 In contrast, we find that bonus asa proportion of total pay and unexercisable options deter managers from engaging in realtransactions management.
To summarize, the results in Table 2 support Hypotheses H1a and H1b, which positthat clawback adoption leads to less accruals management but greater real transactions
14

Another reason to control for compensation variables in the analysis of earnings management is that theinitiation of clawback provisions may be accompanied by changes in executive compensation practices.
Indeed, prior studies find that regulations that affect financial reporting practices tend to also change
executive compensation practices. For example, Carter et al. (2009) and Cohen et al. (2012) find that thepassage of SOX reduces accruals manipulation, and the reduced earnings manipulation allows firms to put
more weight on accounting earnings in the determination of the CEO’s annual bonus.

20management.

Robustness Test – Using the Heckman Model to Address the Endogeneity
Associated with Clawback Adoption
As indicated in Tucker (2010), PSM is useful in alleviating observed differences
across treatment and control firms, but it cannot control for their unobserved differences.
Although unobservable differences across clawback adopters and non-adopters can be
mitigated to a certain extent by the inclusion of firm fixed effects, we nonethelessperform the Heckman test to check the robustness of our findings. Specifically, we again
estimate the clawback adoption model described in Section III (page 11, which is themodel used in the PSM). However, to satisfy the “excluding restriction” as indicated in
Lennox et al. (2012), we add two instrumental variables, Enforceability and PeerAdopt,to the model. Enforceability is a state-level enforcement index of non-competition clauses
included in the employment contracts, which is obtained from Garmaise (2011).
Garmaise (2011) posits that a legal clause is more likely to be included in theemployment contract if it is more enforceable in the state. As such, this index is expected
to be positively related to clawback adoption – that is, clawback adoption should be more
likely if such provisions are more enforceable in the specific state. PeerAdopt is definedas the percentage of peer firms in the same industry (2-digit SIC codes) that also haveclawback provisions in place. We expect that this variable is positively related toclawback adoption. That is, we argue that a company is more likely to initiate clawbacks
when more of its peer firms do so. Importantly, the two instruments Enforceability and21

PeerAdopt are not expected to be directly associated with the second-stage dependent
variables AM or RTM.
Results of this analysis are provided in Table A2 in the Appendix. In Panel A, wefind that clawback adoption is positively associated with PeerAdopt, while it is not
significantly related to Enforceability. Next, we compute the inverse Mills ratio(IMR_Clawback) and include it in the estimate of equation (6). The abbreviated results
are provided in Panel B of Table A2. Generally, our main findings remain unchanged:
clawback adoption is related to less accruals manipulation but greater real transactions
management. We find that the variance inflation factor (VIF) associated with the inverse
Mills ratio (IMR_Clawback) and PostClawback is 1.89, suggesting that multicollinearity
is very low in this specification. According to Lennox et al. (2012), a low VIF suggeststhat Enforceability and PeerAdopt satisfy the “excluding restriction” and thus are valid
instruments. 15
To summarize, we find supporting evidence for Hypotheses H1a and H1b by using
the Heckman model to control for unobservable differences across clawback adopters andnon-adopters.

A Two-Stage Model to Account for the Endogenous Decision to Manage Earnings
The results in Table 2 indicate that clawback adoption leads to a trade-off between
accruals manipulation and real transactions management. However, the decision for firms
to engage in earnings manipulation is not exogenous. Moreover, as argued in Watts andZimmerman (1986), except when used for opportunistic purposes, earnings management

15

Our results in Panel B of Table A2 remain qualitatively similar if we include Bonus, Option_Grant,
Option_Ex, Option_Un, and Owner as control variables.

22

may also be efficient. For example, managers may use discretionary accruals to convey
information about company prospects (Subramanyam 1996). As such, to verify whether
the substitution between accruals manipulation and real transactions management
subsequent to clawbacks does indeed represent opportunistic behavior, we use the
Heckman model to address the self-selection associated with earnings manipulation
decisions. Specifically, following Cohen and Zarowin (2010) and Zang (2012), we firstmodel a company’s decision to manage reported earnings as the following probit model:
Suspect_EMit = α + β1Clawbackit + β2Sizeit + β3M/Bit + β4Leverageit + β5HabitBeater+ β6Shares+β7ROAit + β8NAnalystit + dt + εit,(7)

where Clawback is a dummy variable equal to one if the company is a clawback adopter,and zero otherwise. Suspect_EM is a dummy variable equal to one if either AM or RTM isabove the industry-year median, and zero otherwise (Cohen and Zarowin 2010). Based on
this definition, 2,244 firm-years among the full sample can be classified as suspect firmyears. Leverage is long-term liabilities divided by total assets. Size, M/B, and ROA are aspreviously defined. We include these variables to control for the effects of capital
structure, profitability, firm size, and growth opportunities on earnings management (seeDechow et al. 2010 for a review of the earnings management literature). HabitBeater isthe number of times analysts’ forecast consensus was met or beat over the past four
quarters. Shares is the log number of shares outstanding. As posited by Cohen andZarowin (2010), HabitBeater and Shares capture capital market incentives for managers
to engage in more earnings management to meet earnings targets, suggesting a positive
sign on the two variables. NAnalyst is the number of analysts following the firm at the
beginning of the year. There are two alternative predictions on the sign of NAnalyst. On
23the one hand, being followed by more analysts could provide stronger incentives for
managers to manage earnings. On the other hand, financial analysts with sophisticatedfinancial and industry knowledge could constrain managers’ earnings management
activities. In short, there is no predicted sign on NAnalyst.
[INSERT TABLE 3 HERE]
The results of equation (7) are presented in Panel A, Table 3. We find that thecoefficient on Clawback is statistically insignificant, suggesting that clawback adopters
do not differ from control firms in their propensity to meet or just beat earnings
benchmarks. Consistent with Cohen and Zarowin (2010) and Zang (2012), we find thatthe likelihood of engaging in earnings manipulation to achieve earnings targets is
positively related to firm size, leverage, a prior history of meeting or beating earnings
benchmarks, and the number of shares outstanding and is negatively related to number ofanalysts following.
After estimating equation (7), we compute the inverse Mills ratio (IMR) and include
it to re-estimate equation (6) using the 2,244 suspect firm-years. The results are presented
in Panel B, Table 3. To save space, we only present coefficients on PostClawback and
IMR. In general, the results are qualitatively similar to those reported in Table 2. In
particular, using a sample of firms-years suspected of earnings manipulation, we find thatclawback adopters reduce accruals manipulation while increasing real transactions
management subsequent to clawback initiation. 16
16

Alternatively, following Zang (2012), we classify a firm-year as associated with earnings management if
one of the following situations holds: (1) earnings before extraordinary items divided by total assets falls
between 0 and 0.005; (2) the change in basic EPS excluding extraordinary items between year t and year
t-1 falls between zero and $0.02; or (3) actual EPS minus the latest analyst consensus forecast (ormanagement forecast) before the fiscal year-end falls between zero and $0.01. Based on this definition,
806 firm-years among the full sample can be classified as suspect firm years, with the remaining 2,776

24

Subgroup Analysis - Clawback Adopters with High vs. Low Growth Opportunities
Hypothesis H2 predicts that clawback firms with high growth opportunities are more
likely to resort to real activities management to meet or beat earnings targets relative toclawback adopters with low growth opportunities. To test this conjecture, we partition the239 pairs of clawback adopters and non-adopters into two groups based on the medianmarket-to-book ratio. That is, a company is considered as having high growth
opportunities if its average market-to-book ratio over the entire sample period is above
the sample median; otherwise we classify it as a firm with low growth opportunities. We
then estimate equation (6) separately for clawback adopters and non-adopters with highgrowth opportunities and those with low growth opportunities. In doing so we compare
treatment firms (clawback adopters) and control firms (non-adopters) on the samegrounds. The results of this analysis are provided in Table 4. Again, to save space, weonly present results for variables of interest.
[INSERT TABLE 4 HERE]
We find that our results are mainly driven by clawback adopters with high growth
opportunities. Specifically, we find that the coefficient on PostClawback is significant incolumns (1), (5), (9), and (11), suggesting that clawback adopters with high growth
opportunities engage in less accruals management (in particular, positive discretionary
accruals), while they switch to real activities management to a greater extent after
initiating clawbacks. As such, the total amount of earnings management actually
increases after clawback adoption for adopters with high growth opportunities. In contrast,
firm-years classified as non-suspect years. We then estimate equation (6) separately for suspect- and nonsuspect firm-years. We find that our main findings mainly occur in suspect firm-years. This test again
confirms that the substitution among earnings management tools subsequent to clawback adoption isdriven by opportunistic purposes.

25

we do not observe the same phenomenon for clawback firms with low growth
opportunities. Further tests reveal that these differences between the two groups are on
average statistically significant.

The Impact of Clawbacks on Firm Performance
The results in Tables 2 to 4 suggest that clawback adoption causes a shift from
accruals manipulation to real transactions management. It is thus natural to ask whether
this shift indeed represents an unintended consequence – that is, whether it is associatedwith any costs for those adopting firms. It is possible that the increase in real transactions
management actually represents an efficient outcome. For example, shareholders expect
managers to make such a shift when clawback provision is instituted or to convey
information about company future prospects (Gunny 2010). If this argument holds, thenwe should not observe any negative consequence subsequent to clawback initiation.
Alternatively, the increase in real transactions management may create adverse
consequences for clawback adopters. This is because real transactions management
represents a deviation from optimal operating decisions (e.g., overproduction orunderinvestment) and has direct adverse effects on cash flows, whereas accruals
manipulation involves the adjustment of revenue or expense accruals and has no direct
impact on cash flows. Supporting this argument, Cohen and Zarowin (2010) show thatfirms with seasoned equity offerings (SEO) engage in both accruals manipulation andreal transactions management, and that the post-SEO underperformance documented in
the literature is mainly due to real transactions management rather than accruals

26manipulation. Similarly, Bhojraj et al. (2009) and Gupta et al. (2010) find that firms
experience stock underperformance after engaging in real transactions management.
Based on the above discussion, we investigate whether clawback adopters, which
engage in greater real transactions management, experience underperformance
subsequent to clawback adoption. To do so, we estimate the following model, which issimilar as the one used in Cohen and Zarowin (2010):∆ROA(t, t+i) = α + β1Clawback_IRTM t + β2Clawback_DRTM t + β3∆Size(t, t+i)
+ β4∆M/B(t, t+i) + β5∆Leverage(t, t+i) + dt + εit,(8)

where ∆ROA(t, t+i) is the industry-adjusted change in ROA from year t to t+i, i = 1, 2, and3. Year t is the year during which the clawback provision is initiated. ∆Size is the change
in Size. ∆M/B is the change in M/B. ∆Leverage is the change in Leverage. Size, M/B, and
ROA are as previously defined. dt is year-specific fixed effects. Clawback_IRTM(Clawback_DRTM) equals one if the clawback adopter increases (decreases) its amountof real transactions management during the adoption year relative to pre-adoption years,
and zero otherwise. That is, a clawback adopter is considered as increasing its use of realtransactions management only if its amount of real transactions management in year t islarger than in the pre-adoption period, otherwise we consider the clawback adopter as
decreasing its use of real transactions management. This definition is quite stringent inthat a clawback adopter will not be classified as engaging in more real transactions
management unless it immediately increases real transactions management in the
adopting year. Using this definition enables us to investigate how increased realtransactions management affects future performance in one to three years. The results arereported in Table 5.
27

[INSERT TABLE 5 HERE]
The coefficient on Clawback_IRTM is significantly negative in all three columns,
suggesting that clawback adopters that increase real transactions management experiencea reduction in ROA. In contrast, the coefficient on Clawback_DRTM is insignificant inall columns, suggesting that clawback adopters that decrease real transactions
management do not experience changes in firm performance after adopting clawbacks.
Indeed, when we consider all clawback adopters as one group, we find that clawback
adoption is not related to future underperformance, as the coefficient on Clawback is
insignificant in columns ((2), (4), and (6). Further tests reveal that the differences inchangesin

ROA

betweenthetwocoefficients(Clawback_IRTM

versusClawback_DRTM) are statistically significant up to year t+2.
To summarize, the results in Table 5 are consistent with the notion that clawback
adoption causes managers to engage in suboptimal operating activities to meet or beatearnings targets, suggesting a cost incurred by such provisions.

V. CONCLUSIONSIn this study we examine whether firm-initiated clawback provisions, policies that
aim to reduce financial misstatements by allowing firms to recoup compensation frommanagers in the event of accounting restatements, influence managers’ choice between
within-GAAP accruals management and real transactions management to meet or beatearnings targets. Using Russell 3000 non-financial firms to form a matched sample ofclawback adopters and non-adopters, we first show that clawback adoption leads to lessaccruals management but greater real transactions management. Specifically, we find that28

relative to pre-adoption periods and firms without clawbacks, clawback adopters areassociated with lower positive discretionary accruals (but not downward accruals), but
are more likely to cut back on discretionary expenses such as R&D or SG&A or
manipulate sales revenue (as reflected in abnormally low cash flow from operating
activities). This suggests that managers subject to clawbacks move away from accruals
manipulation to less detectable real activities management to achieve earnings targets,and that this phenomenon occurs mainly among clawback adopters with greater growth
opportunities. Finally, we find that clawback adopters that engage in greater real
activities management experience a reduction in operating performance subsequent toclawback adoption, consistent with the notion that real activities management sacrifices
long-term firm value.
Taken together, our results indicate that although clawbacks deter managers fromengaging in financial misreporting, they do not fully eliminate earnings management. In
particular, clawbacks appear to cause managers to reduce expenses that may create longterm benefits, with this phenomenon more pronounced for firms with greater growth
opportunities. Clawback provisions may therefore have unintended consequences forcertain types of firms. Mandatory clawback adoption pursuant to the Dodd-Frank Act
may lead to the same unintended consequences.
Our study has a few limitations. First, we examine the effect of firm-initiatedclawbacks on managers’ reporting behavior. Because clawbacks as required by the DoddFrank Act are mandatory, our results may not generalize due to the fundamental
difference between firm-initiated and mandatory clawbacks. Further study is thus needed
to investigate the consequences of mandatory clawbacks. Second, as firm-initiated29clawbacks became popular after 2006, the short time horizon prevents us fromperforming certain tests to examine the subsequent underperformance of clawback
adopters. Future research could revisit this issue by examining whether managers’ risktaking or investment behavior is affected by clawback initiation. Such evidence would
help us better understand the consequences of clawback provisions.

30

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34

TABLE 1
Descriptive statistics
Panel A: Number of Industrial Firms with Firm-initiated Clawbacks in the Corporate
Library Dataset by Year
Year
2005
2006
2007
2008
2009

Number of Clawback Adopters
19
92
200
336
444

Number of New Adopters
19
73
108
136
108

Panel B: Number and Percentage of Clawback Adopters by Two-digit SIC code
Clawback adopters in Corporate Library
Frequency
%
16
3.58
15
3.36
19
4.25
35
7.83
16
3.58
49
10.96
26
5.82
28
6.26
23
5.15
17
3.8
19
4.25
7
1.57
22
4.92
9
2.01
1
0.22
8
1.79
137
30.65
444
100

Industry (SIC) distribution
Oil and gas (13, 29)
Food products (20)Paper and paper products (24-27)
Chemical products (28)Manufacturing (30-34)
Computer equipment and services (35, 73)
Electronic equipment (36)Transportation (37, 39,40-42,44,45)
Scientific instruments (38)Communications (48)Electric, gas, and sanitary services (49)
Durable goods (50)Retail (53, 54,56,57,59)
Eating and drinking establishments (58)Entertainment services (70, 78,79)
Health (80)
All others
Total

35

Panel C: Descriptive Statistics of 343 Clawback Adopters and 1,840 Non-adopters with
Available Data in Compustat and Corporate Library

Size
M/B
SaleG
Leverage
ROA
Segment
Inst%
BDIndepnClawback
firms
7.958
3.037
0.100
0.207
0.037
1.780
0.600
0.677
343

Mean
Nonadopters
6.755
2.975
0.131
0.185
0.012
1.480
0.527
0.632
1,840

Diff.
t-stat.
13.20***
0.39-3.05***
2.06**
3.55***
6.73***
3.40***
5.45***

Clawback
firms
7.898
2.505
0.074
0.187
0.043
1.963
0.679
0.687
343

MedianNonadopters
6.586
2.375
0.098
0.156
0.035
1.384
0.596
0.643
1,840

Diff.
z-stat.
11.48***
1.20-3.45***
3.35***
2.68***
6.61***
4.78***
5.27***

Panel D: Descriptive Statistics of 239 Pairs of Clawback Adopters and Non-adopters
Identified by the Propensity Score Matching
Size
7.700
7.781
-0.59
7.594
7.838
-0.93
M/B
2.505
2.844
-1.07
2.039
2.185
-0.62
SaleG
0.077
0.089
-1.01
0.079
0.085
-0.55
Leverage
0.219
0.226
-0.37
0.187
0.199
-0.03
ROA
0.028
0.030
-0.14
0.051
0.044
0.81
Segment
1.503
1.425
0.90
1.791
1.386
0.90
Inst%
0.585
0.605
-1.32
0.706
0.743
-0.92
BDIndep
0.648
0.637
0.95
0.647
0.647
0.56
n
239
239
239
239
Tests for differences in mean (median) are based on t- (z-) statistics. ***, **, * indicatessignificance at the 0.01, 0.05, and 0.10 level, respectively.
Panel A provides the yearly distribution of number of industrial firms with clawback provisions in
the Corporate Library dataset, and Panel B presents distribution of clawback adopters based on
industry membership (2-digit SIC code). Panel C provides descriptive statistics of 343 clawback
adopters and 1,840 non-adopters with available data in Compustat and Corporate Library. Panel D
provides the same set of descriptive statistics of 239 pairs of clawback adopters and non-adopters
matched based on the propensity-score-matching.
Size =M/B =SaleG =
Leverage =ROA =Segment =Inst% =
BDIndep =the natural log of total assets.
the market to book ratio.
a one-year sales growth.
long-term liabilities divided by total assets.
income before extraordinary items divided by lagged total assets.
the natural log of the number of business segments.
the percentage of shares owned by institutional investors.
the number of independent directors divided by the total number of directors on
the board.

36

TABLE 2
The Effects of Clawback Provisions on Accrual Management and Real Transactions Management
Panel A: Descriptive Statistics of Key Variables
Mean

MedianDiff.
t-stat.
-3.26***
1.40-3.60***-0.92-5.05***

Diff.
z-stat.
-1.71*
1.60-2.44**
0.13-4.24***

Clawback firms
Non-adopters
Clawback firms
Non-adopters
|AM|
0.064
0.073
0.043
0.047
AM
-0.006-0.012-0.004-0.006
ABExp
0.012
0.051
-0.028-0.001ABProd
-0.045-0.039-0.034-0.038ABCash
0.087
0.113
0.070
0.093
n
1,762
1,820
1,762
1,820
Tests for differences in mean (median) are based on t- (z-) statistics. ***, **, * indicates significance at the 0.01, 0.05, and 0.10 level, respectively.

Panel B
AM+RTM
RTM (Real Transaction Management)

AM (Accrual Management)

PostClawback
Size
M/B
ROA
ZScore| AM |(1)-0.013**(-2.35)-0.001(-0.26)0.001**(2.17)-0.175***(-9.01)-0.005***AM(2)-0.009(-1.02)-0.034***(-5.75)-0.001*(-1.87)0.443***(16.12)0.011***

AM>0(3)-0.024***(-3.00)-0.023***(-3.63)-0.000(-0.54)0.079**(2.16)
0.002

AM<0
(4)
0.004
(0.46)-0.016***(-2.67)-0.002***(-3.22)0.313***(12.45)0.012***

37

ABExp
(5)
-0.022**(-2.19)-0.071***(-4.68)-0.005***(-3.99)-0.257***(-3.60)-0.010**

ABProd(6)
0.002(0.27)
0.001(0.19)-0.002***(-3.22)-0.213***(-6.66)-0.008***ABCash(7)-0.017**(-2.02)0.016*(1.89)
0.002**(2.18)
0.237***(5.76)
0.009***

RTM(8)
0.032***(2.78)
0.055***(4.69)
0.000(0.31)-0.159***(-2.72)-0.004(TotalManagement)

EM(9)0.024*(1.69)
0.032**(2.49)-0.002(-1.31)0.302***(4.92)-0.005

MktShare
MTR
Inst%
BigFour
AuditTenure
Cycle
NOA
RTM
AM
Firm and year
fixed effects
R-squaredn(-3.28)-0. 232(-1.19)0.014(1.17)
0.006*(1.69)
0.003(0.48)-0.001*(-1.94)0.000**(2.05)-0.012***(-3.15)-0.045***(-5.60)-(4.69)
0.345(1.38)-0.026(-1.58)0.004(0.84)-0.005(-0.51)-0.000(-0.03)0.000***(2.96)
0.006(1.17)
0.084***(7.72)-(1.02)
0.094(0.35)
0.004(0.23)
0.006(1.10)
0.009(0.90)-0.000(-0.48)0.000**(2.22)-0.007(-1.18)-0.001(-0.06)-(5.63)
0.551*(1.78)-0.019(-1.16)-0.002(-0.33)0.014(1.31)
0.000(0.15)-0.000(-0.10)0.013**(2.46)
0.081***(7.32)-(-2.23)-0 .857**(-2.31)
0.043*(1.69)
0.021*(1.71)
0.003(0.19)
0.002(1.32)
0.000(1.50)-0.016(-1.44)-(-3.91)-0.019(-0.08)-0.015(-0.88)0.005(0.96)-0.009(-0.82)0.001(1.28)
0.000**(2.47)
0.006(0.98)-(3.36)-0.478**(-2.00)0.014(0.72)
0.003(0.50)
0.018(1.46)
0.001(0.97)
0.000(1.06)
0.023***(3.37)-(-1.12)
1.316***(3.19)-0.084***(-2.74)-0.017(-1.26)-0.010(-0.48)-0.001(-0.75)-0.000(-0.99)-0.005(-0.38)-0.002(0.03)-0.091***(-3.22)0.163***(3.88)-0.278***(-3.83)(-1.26)1.792***(3.51)-0.121***(-3.53)-0.006(-0.59)-0.007(-0.32)-0.002(-1.16)-0.000(-0.15)0.010(0.86)
-

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

0.08
3,582

0.12
3,582

0.07
1,696

0.14
1,886

0.11
3,582

0.10
3,582

0.13
3,582

0.09
3,582

0.06
3,582

38

Panel C

PostClawback
Bonus
Option_Grant
Option_Ex
Option_Un
Owner
Controlvariables
Firm and year
fixed effects
R-squaredn

AM+RTM(TotalManagement)
RTM
EM
(8)
(9)
0.031**
0.021(2.53)(1.43)-0.115***-0.154***(-4.06)(-4.55)0.031
0.070***(1.60)(3.06)
0.008
0.016**(1.33)(2.14)-0.036***-0.044***(-2.72)(-2.75)-0.0010.001(-0.53)(0.54)

RTM (Real Transaction Management)

AM (Accrual Management)| AM |(1)-0.013**(-2.40)0.019(1.62)
0.015*(1.89)-0.008(-1.16)0.007*(1.80)
0.002**(2.41)

AM(2)-0.008(-1.03)-0.031(-1.57)0.022**(2.21)
0.008(0.27)
0.007(1.52)
0.002*(1.95)

AM>0(3)-0.021***(-2.68)-0.006(-0.38)0.020*(1.76)-0.014(-1.40)0.012**(2.42)
0.003***(3.23)

AM<0
(4)
0.007
(0.93)-0.014(-0.85)-0.009(-0.81)0.004(1.19)-0.002(-0.30)-0.000(-0.04)ABExp(5)-0.024**(-2.38)0.065***(2.82)
0.004(0.23)-0.005(-1.05)0.021*(1.92)
0.000(0.33)ABProd(6)-0.002(-0.26)-0.0101(-0.67)-0.002(-0.16)0.001(0.26)-0.000(-0.04)0.000(0.40)

ABCash(7)-0.009(-1.52)0.039**(2.42)-0.037***(-3.35)-0.002(-0.58)0.015**(1.97)
0.001(0.81)

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes
0.06
2,811

Yes
0.07
2,811

Yes
0.05
1,295

Yes
0.04
1,516

Yes
0.11
2,811

Yes
0.09
2,811

Yes
0.14
2,811

Yes
0.08
2,811

Yes
0.06
2,811

The t-statistics based on robust standard errors clustered by firm are reported in parentheses. ***, **, * indicates significance at the 0.01, 0.05, and0.10 level, respectively.
| AM |= the absolute value of performance-adjusted abnormal accruals, which is computed following Kothari et al. (2005).
AM = performance-adjusted abnormal accruals, which is computed following Kothari et al. (2005).

39

ABExp = abnormal discretionary expenses, measured as the deviations from the predicted values of the corresponding industry-year
regression, as defined by Roychowdhury (2006).
ABProd = abnormal production cost, measured as the deviations from the predicted values of the corresponding industry-year
regression, as defined by Roychowdhury (2006).
ABCash = abnormal cash flow from operations, measured as the deviations from the predicted values of the corresponding industryyear regression, as defined by Roychowdhury (2006).
RTM = total amount of real transaction management, computed as the sum of ABProd, ABExp, and ABCash.
EM = total earnings management, which is the sum of AM and RTM.
PostClawback = 1 if the company is a clawback adopter in those years in which the clawback provision is implemented, and 0 otherwise .
Size = the natural log of total assets.
M/B = the market to book ratio.
ROA = income before extraordinary items divided by lagged total assets.
ZScore = decile of Altman’s z-score.
MktShare = Herfindahl index using 2-digit SIC-codes.
MTR = the marginal tax rate.
Inst% = the percentage of shares owned by institutional investors.
BigFour = 1 if the company is audited by Big-4 CPA firms, and 0 otherwise.
AuditTenure = 1 if the number of years the auditor has audited the client is above the sample median, and 0 otherwise.
Cycle = the days receivable plus the days inventory less the days payable.
NOA = 1 if the net operating assets (i.e., shareholders’ equity less cash and marketable securities and plus total debt) at the
beginning of the year divided by lagged sales is above the median of the corresponding industry-year, and 0 otherwise.
Bonus = CEO’s annual bonus compensation as a proportion of total compensation.
Option_Grant = number of option granted to the CEO during the year divided by the firm’s total common shares outstanding
Option_Ex = number of exercisable options held by the CEO at year-end divided by the firm’s total common shares outstanding
Option_Un = number of unexercisable options (excluding annual option grants) held by the CEO at year-end divided by the firm’s totalcommon shares outstanding
Owner = shares owned by the CEO divided by the firm’s total common shares outstanding

40

TABLE 3
The Effects of Clawback Provisions on Accrual and Real Transaction Management– Using the Heckman Model to Deal with the Endogeneity Associated with Earnings Management
Panel A : The First Stage Model - Determinants of Earning Management
Suspect_EM
Clawback
0.025(0.38)
Size
0.107***(2.61)
M/B-0.008(-0.96)
Leverage
0.645***(3.58)
HabitBeater
0.071***(3.11)
Shares
0.117**(2.25)
ROA-0.141(-0.49)NAnalyst-0.012*(-1.95)
Year fixed effects
Yes
Pseudo R-squared
0.05
n
3,582
Panel B: The Second Stage Model -The Effects of Clawback Provisions
EM
|AM|
AM
AM>0
AM<0
RTM
(1)
(2)
(3)
(4)
(5)
(6)
PostClawback-0.027***-0.011-0.029***0.019
0.033**
0.020(-3.59)(-1.16)(-3.22)(1.12)(2.08)(1.14)
IMR-0.065-0.118**-0.116**0.113-0.179**-0.285***(-1.60)(-2.43)(-2.41)(1.22)(-2.15)(-3.14)Controlvariables
Yes
Yes
Yes
Yes
Yes
Yes
Firm and year
fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
R-squared
0.05
0.05
0.04
0.02
0.09
0.07
n
2,244
2,244
1,548
696
2,244
2,244
The z-statistics (t-statistics) based on robust standard errors clustered by firm are reported in parentheses.
***, **, * indicates significance at the 0.01, 0.05, and 0.10 level, respectively.
Suspect_EM = 1 if either AM or RTM is above the industry-year median, and 0 otherwise.
Clawback = 1 if the company is a clawback adopter, and 0 otherwise.
41

Size = the natural log of total assets.
M/B = the market to book ratio.
Leverage = long-term liabilities divided by total assets.
Labor = 1 minus capital intensity, where capital intensity equals gross PP&E divided by total
sales.
HabitBeater = the number of times analysts’ forecast consensus was met or beat over the past four
quarters.
Shares = the log number of shares outstanding.
ROA = income before extraordinary items divided by lagged total assets.
Nanalyst = the number of analyst following at the beginning of the year.
| AM |= the absolute value of performance-adjusted abnormal accruals, which is computed
following Kothari et al. (2005).
AM = performance-adjusted abnormal accruals, which is computed following Kothari etal. (2005)
RTM = total amount of real transaction management, computed as the sum of ABProd,
ABExp, and ABCash.
EM = total earnings management, which is the sum of AM and RTM.
PostClawback = 1 if the company is a clawback adopter in those years in which the clawback
provision is implemented, and 0 otherwise.
IMR = the inverse Mills Ratio estimated from the first-stage model (Panel A) of the
Heckman model.

42

TABLE 4
The Effects of Clawback Provision on Accrual and Real Transaction Management– High vs. Low Growth Firms
|AM|
High
Low
growth growth(1)(2)
PostClawback-0.021** -0.004(-2.67)(-0.99)t-test for high versus
2.02**
low growth firms

AM
High
Low
growth growth(3)(4)-0. 008-0.004(-0.09)(-0.03)

AM>0
High
Low
growth growth(5)(6)-0.023*** -0.007(-2.75)(-0.42)

AM<0
High
Low
growth growth
(7)
(8)
0.007
-0.002(0.64)(-0.17)

RTM
High
Low
growth growth(9)(10)
0.047*** 0.018(3.46)(0.65)EM
High
Low
growth growth
(11)
(12)
0.032*
0.006(1.95)(0.40)

0.25

1.93*

0.48

2.04**

1.85*

Control variables
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Firm and year
fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
R-squared
0.07
0.06
0.07
0.08
0.05
0.08
0.10
0.12
0.07
0.05
0.05
0.04
n
1,791
1,791
1,791
1,791
782
915
1,009
876
1,791
1,791
1,791
1,791
The t-statistics based on robust standard errors clustered by firm are reported in parentheses. ***, **, * indicates significance at the 0.01, 0.05, and 0.10level, respectively.
AM =
RTM =
EM =
PostClawback =performance-adjusted abnormal accruals, which is computed following Kothari et al. (2005)
total amount of real transaction management, computed as the sum of ABProd, ABExp, and ABCash.
total earnings management, which is the sum of AM and RTM.
1 if the company is a clawback adopter in those years in which the clawback provision is implemented, and 0 otherwise.

43

TABLE 5
The Impacts of Clawback Adopter’s Increased Use of Real Transaction Management on Future
Performance

Clawback_IRTM(t-1, t)
Clawback_DRTM(t-1, t)
Clawback∆Size(t-1, t)∆M/B(t-1, t)∆Leverage(t-1, t)∆ROA(t, t+1)

∆ROA(t, t+1)

∆ROA(t, t+2)

∆ROA(t, t+2)

∆ROA(t, t+3)

∆ROA(t, t+3)

(1)
-0.021**(-2.26)0.006(0.66)-0.055***(-2.84)-0.001(-0.82)0.152***(5.10)
Yes
0.12
449

(2)

(3)
-0.028**(-2.44)-0.002(-0.12)-0.070**(-2.47)0.000(0.11)
0.115(1.39)
Yes
0.11
442

(4)

(5)
-0.014*(-1.81)-0.004(-0.58)-0.078***(-4.36)-0.000(-0.65)0.107**(2.21)
Yes
0.12
364

(6)

-0.009(-1.13)-0.059***(-3.01)-0.001(-0.76)0.146***(4.89)
Yes
0.11
449

-0.015(-1.55)-0.074***(-2.60)0.000(0.20)
0.123(1.49)
Yes
0.10
442

-0.009(-1.39)-0.080***(-4.46)-0.000(-0.61)0.105**(2.19)
Yes
0.11
364

Year fixed effects
R-squarednt- test for
Clawback_IRTM =2.36**
1.99**
1.09
Clawback_DRTM
The t-statistics based on robust standard errors clustered by firm are reported in parentheses. ***, **, *indicates significance at the 0.01, 0.05, and 0.10 level, respectively.

∆ROA(t, t+i) = the industry-adjusted change in ROA from year t to t+i; i = 1, 2, and 3. Year t is
the year during which the clawback provision is initiated.
Clawback = 1 if the company is a clawback adopter, and 0 otherwise.
Clawback_IRTM = 1 if the clawback adopter increases its amount of real transaction management
during the adoption year relative to pre-adoption years, and 0 otherwise.
Clawback_DRTM = 1 if the clawback adopter decreases its amount of real transaction management
during the adoption year relative to pre-adoption years, and 0 otherwise.
∆Size = change in firm size (as measured by total assets) .
∆M/B = change in the firm’s market-to-book ratio.
∆Leverage = change in the firm’s leverage ratio.

44

Appendix
TABLE A1
Determinants of Adoption of Clawback Provisions for Propensity Score Matching
Clawback
0.548***(9.89)
M/B
0.009(0.55)
SaleG-0.715**(-2.41)
Leverage-0.174(-0.45)ROA
0.059(0.11)
Segment
0.224***(2.70)
PriorRestate
0.263*(1.79)
Inst%
0.033(0.31)
BDIndep
0.827*(1.78)
Industry and year fixed effects
Yes
Pseudo R-squared
0.127
n
8,868
The z-statistics based on robust standard errors clustered by firm are reported in parentheses. ***,**, * indicates significance at the 0.01, 0.05, and 0.10 level, respectively.
Size

Size =M/B =SaleG =
Leverage =ROA =Segment =PriorRestate =the natural log of total assets.
the market to book ratio.
a one-year sales growth.
long-term liabilities divided by total assets.
income before extraordinary items divided by lagged total assets.
the natural log of the number of business segments.
1 if firm has any earnings restatement during prior three years, and 0
otherwise.
Inst% = the percentage of shares owned by institutional investors.
BDIndep = the number of independent directors divided by the total number of directors
on the board.

45

TABLE A2
The Effects of Clawback Provisions on Accrual Management
and Real Transactions Management– Using the Heckman Model to Deal with the Endogeneity Associated with Clawback Adoption
Panel A: The First Stage regression - Determinants of Clawback Adoption
ClawbackSize
0.268***(9.30)
M/B
0.012(0.67)
SaleG-0.350**(-2.24)
Leverage-0.256(-1.22)ROA
0.029(0.11)
Segment
0.142***(2.61)
Inst%
0.039(0.66)
BDIndep
0.446*(1.90)
Enforceability-0.006(-0.36)PeerAdopt
0.569***(4.24)
Industry and year fixed effects
Yes
Pseudo R-squared
0.143
n13,010Panel B: The Second Stage Regression - The Effects of Clawback Provisions

PostClawback
IMR_Clawback
Control variables
Firm and year
fixed effects
R-squared
n

|AM|
(1)
-0.015**(-2.57)0.003**(2.25)
Yes
Yes
0.12
13,010

AM
AM>0
(2)
(3)
-0.005-0.024***(-0.80)(-3.51)0.060***
0.033***(41.36)(12.51)
Yes
Yes
Yes
0.14
13,010

Yes
0.11
6,040

46

AM<0
RTM
EM
(4)
(5)
(6)
0.005
0.045***
0.036**(0.53)(3.60)(2.54)
0.013***
0.071***
0.126***(5.37)(17.33)(27.14)
Yes
Yes
Yes
Yes
0.15
6,970

Yes
0.08
13,010Yes
0.08
13,010

The t-statistics based on robust standard errors clustered by firm are reported in parentheses. ***, **,* indicates significance at the 0.01, 0.05, and 0.10 level, respectively.
Size =M/B =SaleG =
Leverage =ROA =Segment =Inst% =
BDIndep =Enforceability =PeerAdopt =
AM =
RTM =
EM =
PostClawback =IMR_Clawback =the natural log of total assets.
the market to book ratio.
a one-year sales growth.
long-term liabilities divided by total assets.
income before extraordinary items divided by lagged total assets.
the natural log of the number of business segments.
the percentage of shares owned by institutional investors.
the number of independent directors divided by the total number of directors on
the board.
a state level enforceability index of non-competition clause developed in
Garmaise (2011).
the percentage of peer firms in the same industry (2-digit SIC codes) that also
have clawback provisions in place.
performance-adjusted abnormal accruals, which is computed following Kothari
et al. (2005)
total amount of real transaction management, computed as the sum of ABProd,
ABExp, and ABCash.
total earnings management, which is the sum of AM and RTM.
1 if the company is a clawback adopter in those years in which the clawback
provision is implemented, and 0 otherwise.
the inverse Mills ratio estimated from the first-stage model (Panel A) of the
Heckman model.

47