made 2-the economic consequences of financial restatements evidence from the market for corporate...

THE ACCOUNTING REVIEW American Accounting AssociationVol. 90, No. 1 DOI: 10.2308/accr-508692015pp. 1–29

The Economic Consequences of FinancialRestatements: Evidence from the Market for

Corporate Control

Amir Amel-Zadeh

University of Cambridge

Yuan Zhang

The University of Texas at Dallas

ABSTRACT: This paper investigates whether and how financial restatements affect the

market for corporate control. We show that firms that recently filed financial restatements

are significantly less likely to become takeover targets than a propensity score matched

sample of non-restating firms. For those restating firms that do receive takeover bids, the

bids are more likely to be withdrawn or take longer to complete than those made to non-

restating firms. Finally, there is some evidence that deal value multiples are significantly

lower for restating targets than for non-restating targets. Our analyses suggest that the

information risk associated with restating firms is the main driver of these results.

Overall, this study finds that financial restatements have profound consequences for the

allocation of economic resources in the market for corporate control.

Keywords: financial restatements; market for corporate control; mergers and acquisi-tions; information risk; corporate governance.

JEL Classifications: D82; G14; G34; M41.

Data Availability: Data are available from sources identified in the paper.

I. INTRODUCTION

This paper investigates whether and how financial restatements affect the market for

corporate control. Prior evidence suggests that financial restatements are associated with

significant economic consequences. A large literature examines the capital market effects of

We appreciate helpful comments from John Harry Evans III (senior editor), Bin Ke (editor), and two anonymousreviewers. We also thank John Core, Wei Jiang, Sarah McVay, Geoff Meeks, Raghu Rau, seminar participants atColumbia University, The Ohio State University, University of California, Irvine, University of Cambridge, Universityof Illinois at Urbana–Champaign, The University of Texas at Dallas, and conference participants at the 2011 AmericanAccounting Association Annual Meeting for helpful comments and suggestions. All errors are our own.

Editor’s note: Accepted by Bin Ke.

Submitted: June 2012Accepted: June 2014

Published Online: July 2014

1

financial restatements (Anderson and Yohn 2002; Hribar and Jenkins 2004; Palmrose, Richardson,

and Scholz 2004), their consequences for labor markets (Srinivasan 2005; Desai, Hogan, and

Wilkins 2006b; Kedia and Philippon 2009), and the associated legal costs (Palmrose and Scholz

2004; Karpoff, Lee, and Martin 2008). Yet, little research has examined the consequences for the

market for corporate control.

Why might financial restatements have an effect on the takeover market? The market for

corporate control exerts a disciplinary role in firm management because it establishes powerful

incentives for outsiders to intervene with takeover offers for inefficiently managed firms in order to

eliminate mismanagement and increase shareholder value (Manne 1965; Jensen and Ruback 1983).

In theory, continued underperformance of a firm in the capital market should serve as a signal of

mismanagement, offering profit opportunities for potential acquirers. However, empirical studies

have produced mixed results on the link between market prices and takeovers (Agrawal and Jaffe

2003; Edmans, Goldstein, and Jiang 2012). Moreover, to the extent that inferior financial

performance is disguised through misstatement of earnings, inefficiencies are less likely to be

detected by the market.

Restatement filings may, therefore, serve as visible signals of corporate governance failures and

ineffective internal control that otherwise would be difficult for outsiders to detect (Ashbaugh-

Skaife, Collins, and Kinney 2007). In addition, because financial restatements are, on average,

associated with significantly negative stock returns, both around the announcements and in the

medium to long term (Anderson and Yohn 2002; Palmrose et al. 2004), potential bidders may

conclude that these firms can be acquired at relatively low prices. Thus, acquirers would have an

incentive to take control of these firms to restore them to their potential. Accordingly, restating

firms might be more likely to become takeover targets in the market for corporate control

subsequent to their restatements.

On the other hand, financial restatements might also lead to a lower likelihood of receiving a

takeover offer. Financial statements play a pivotal role in the effective monitoring of managerial

action and the efficient allocation of financial resources (Healy and Palepu 2001). Although

restatements are ex post corrections of previous accounting misstatements, announcements of

financial restatements increase information asymmetries between insiders and outsiders

(Bhattacharya, Desai, and Venkataraman 2010), signal high information risk (Kravet and Shevlin

2010) and, therefore, increase the cost of adverse selection. Such information asymmetry is

particularly detrimental to major investment decisions such as takeovers. Potential acquirers have to

rely on publicly available information at the initial stages of the takeover process in determining

whether an offer should be made. They also only obtain very limited inside information once the

confidentiality agreements are signed in preparation for negotiations about the deal terms before the

acquisition is made public.1 Hence, the information risk inherent in restating firms is expected to

decrease the incentives for prospective acquirers to make takeover offers.

Overall, while the lack of effective management and control at restating firms calls for outside

intervention through takeovers, the information risk of these firms might reduce such incentives of

potential acquirers. Whether the costs of the information risk outweigh the potential benefits of a

takeover after financial restatements is an empirical question we investigate in this study.

We seek to provide evidence on the consequences of financial restatements on the likelihood,

the outcome, and the valuation of takeovers. More specifically, our first research question examines

whether firms that file financial restatements are more or less likely to become takeover targets in

the subsequent 12 months than a matched control group of firms that do not restate earnings. Based

on a sample of 1,963 propensity score matched pairs of restating and non-restating firms during

1 See Wangerin (2012) for a more detailed discussion of the due diligence process in mergers and acquisitions.

2 Amel-Zadeh and Zhang

The Accounting ReviewJanuary 2015

2001–2008, we find that restating firms experience a significantly lower likelihood of receiving a

takeover bid than non-restating firms. The propensity score matching technique ensures that our

control group is very similar in their likelihood of being a restating firm based on firm

characteristics identified in the prior literature (Beneish 1999; Dechow, Ge, Larson, and Sloan

2011), except that these firms did not file restatements. In regression analyses, we find that non-

restating firms have, on average, a 5.7 percent likelihood of receiving a takeover bid versus 3.2

percent for their restating counterparts, reflecting an economically and statistically significant 44

percent difference in the takeover likelihood.

We also find that restatements due to both accounting errors and irregularities have a similar

negative impact on the takeover likelihood, suggesting that potential acquirers are broadly

concerned with information uncertainty, regardless of whether this uncertainty is due to

management’s intentional misstatements or erroneous application of GAAP. Further analyses

show that our results are not driven by litigation risks, internal control weaknesses, or CEO

turnovers associated with the financial restatements.

Our second research question examines whether takeover bids made to restating targets are

more or less likely to be withdrawn than those made to non-restating targets. We conjecture that

after an initial offer has been made and the deal publicly announced, higher information risk of the

restating targets may increase the likelihood of the offer being withdrawn if the bidder’s due

diligence exposes adverse information. Our third and final research question investigates whether

prior restatements affect the pricing of takeover targets. The target’s firm-specific information plays

an important role in assessing the synergies of an acquisition (Martin and Shalev 2009). The

heightened information risk associated with restating target firms affects their cost of capital, which

is expected to have an adverse effect on acquirers’ valuations of the targets.

Based on a sample of 2,271 takeover bids made between 2002 and 2009, we find that offers

made to restating targets are significantly more likely to be withdrawn or take longer to complete

than offers made to non-restating targets. Furthermore, our results on offer price multiples provide

some evidence that target firms with previous financial restatements receive lower acquisition

valuations compared with non-restating target firms. The discount ranges between 25 percent and

28 percent, although this effect is not consistently strong across different valuation measures and,

therefore, should be interpreted with caution.

Overall, the results presented in this paper suggest that financial restatements have significant

consequences for the allocation of economic resources in the market for corporate control. These

results add to the recent literature that examines the economic consequences of financial

restatements (Desai et al. 2006b; Hribar and Jenkins 2004; Karpoff et al. 2008; Gleason, Jenkins,

and Johnson 2008; Wilson 2008). We provide evidence of previously undocumented consequences

of financial restatements showing that restating firms are significantly less likely to become

takeover targets. Takeover offers made to restating firms are also more likely to be withdrawn and

have lower deal multiples, consistent with a higher cost of capital for restating firms (Hribar and

Jenkins 2004; Kravet and Shevlin 2010). These results also complement prior research on the

implications of financial restatements for resource allocation and investment decisions. Prior

research documents negative economic effects of restatements on investment decisions of firms that

previously engaged in misstatements (McNichols and Stubben 2008; Kedia and Philippon 2009),

while we focus on investments in firms that previously engaged in misstatements.

Furthermore, this paper also contributes to the corporate finance literature on the characteristics

of takeover targets (Jensen 1988; Mitchell and Lehn 1990; Andrade and Stafford 2004; Gorton,

Kahl, and Rosen 2009) and the determinants of takeover valuations (Eckbo and Langohr 1989;

Officer 2003; Bates and Lemmon 2003). Our results have important implications for firms that

engage in mergers and acquisitions activities, providing insights for target selection and bidding

strategies. For example, because bids made to firms that recently filed financial restatements are

Consequences of Financial Restatements: Evidence from the Market for Corporate Control 3


more likely to be withdrawn due to adverse selection costs, potential acquirers would benefit from

more diligent information acquisition before making an offer.

Several recent studies (Martin and Shalev 2009; Marquardt and Zur 2013; Skaife and

Wangerin 2013) also examine the implications of other measures of financial information quality

for mergers and acquisitions, without examining how financial information quality affects the

takeover decisions in the first place. We provide empirical analyses on this important question. In

addition, our focus on financial restatements is arguably more likely to capture low information

quality attributable to managerial choices than these studies’ focus on accruals-based earnings

quality measures. Accruals-based information quality measures are often constructed to capture the

mapping of accruals into cash flows and, thus, are partly attributable to firm fundamentals.

Furthermore, unlike these accruals-based measures, restatements provide a directly observable

signal of low information quality, a characteristic that is useful in practice.

Next, Section II discusses the prior literature on restatements and takeovers and develops our

predictions. Section III describes the sample selection and matching procedure. Sections IV–VI

present empirical results and discussions of each of our three research questions. We conclude in

Section VII.

II. RELATED LITERATURE AND PREDICTIONS

The prior literature on financial restatements has shown that firms that restate their earnings

experience significant shareholder losses (Anderson and Yohn 2002; Palmrose et al. 2004), have

higher costs of capital (Hribar and Jenkins 2004), incur substantial fines and reputational costs

(Karpoff et al. 2008), and face a higher likelihood of litigation (Palmrose and Scholz 2004).

Beyond these direct capital market effects, accounting restatements also have important labor

market consequences for the involved managers and directors. Management and directors of firms

that announce restatements face a higher likelihood of being replaced and subsequently face poorer

employment prospects (Srinivasan 2005; Desai et al. 2006b). Moreover, restatements have negative

consequences for aggregate employment and investments in their respective industries (Kedia and

Philippon 2009).

Despite this large body of literature on the effects of restatements on capital and labor markets,

we know of no direct evidence on the consequences of restatements for investment decisions in the

market for corporate control. This study attempts to fill this gap.

Financial Restatements and Takeover Likelihood

Our first research question examines whether firms with recent filings of financial restatements

face a higher or lower likelihood of becoming a takeover target. Firms that engage in aggressive

earnings management and subsequently file financial restatements are associated with ineffective

internal controls (Ashbaugh-Skaife et al. 2007), signaling agency costs. Takeovers are an important

mechanism for mitigating these agency costs through replacement of inefficient management and

the improvement of internal governance (Morck, Shleifer, and Vishny 1989; Shivdasani 1993;

Schwert 2000). Furthermore, the significantly negative stock returns after restatement announce-

ments documented in prior research (Anderson and Yohn 2002; Palmrose et al. 2004; Desai,

Krishnamurthy, and Venkataraman 2006a; Karpoff et al. 2008) can also make the restating firms

attractive takeover targets.2

2 For example, Palmrose et al. (2004) find average abnormal returns of about �9 percent over two days around therestatement announcements.



However, several other studies argue that financial restatements increase the information

asymmetry between insiders and outsiders (Diamond and Verrecchia 1991; Bhattacharya et al.

2010). Kravet and Shevlin (2010) further show that financial restatements increase information risk,

which may raise the cost of adverse selection in the acquisition process. Figure 1 illustrates that

during the preliminary due diligence, the acquirer must rely exclusively on publicly available

information as the basis for the decision to approach a potential target. Even during negotiations of

the initial deal terms, the acquirer is granted only limited private information from the target

(Wangerin 2012). Therefore, the information risk and uncertainty inherent in restating firms may

reduce potential acquirers’ incentives to initiate takeovers.

Overall, while poor performance and weak governance of restating firms may provide

incentives for potential acquirers to make takeover offers, their higher information risk and the

greater cost of adverse selection may reduce such incentives. The effect of financial restatements on

the likelihood of a firm to become a takeover target is, thus, an empirical question. These

considerations might also affect takeover outcomes once acquiring firms have decided to launch a

bid, which we discuss next.

Financial Restatements and the Likelihood of Withdrawal of Takeover Bids

Our second research question examines how financial restatements filed in the 12 months prior

to the takeover bid affect the likelihood that the bid will be withdrawn. When the information risk is

high and the credibility of the target’s management low, bidders are likely to perform more diligent

analyses of the target’s financial statements (Wangerin 2012). The higher information risk of the

restating targets may increase the likelihood of an initial bid being withdrawn, either because the

takeover parties could not agree on the final acquisition price, or because of remaining risks

exposed by the bidder’s due diligence once the takeover bid is initiated and the acquisition

agreement signed. Despite the binding nature of the acquisition agreement, investigation covenants

and other closing conditions, such as material adverse change clauses or termination clauses in the

agreement, enable the bidder to withdraw if the due diligence fails to confirm the accuracy of the

representations and warranties made by the target (Wangerin 2012; Skaife and Wangerin 2013).

FIGURE 1Schematic Diagram of a Friendly Takeover Process after Financial Restatement Filings

This figure sketches the timeline of the general process during takeover negotiations after announcements of financialrestatements, and the extent of the bidder’s access to information about the target.



Martin and Shalev (2009) and Marquardt and Zur (2013) examine the effects of target firm-

specific information and accruals quality, respectively, on takeover outcomes. Both studies find that

the likelihood of withdrawal of an acquisition offer decreases with the target’s information quality.

Our research differs from this literature, which examines the effects of financial reporting on

investment decisions conditional on the acquisition decision having been made. In contrast, our first

research question examines whether and how financial reporting quality affects the decision to

make a takeover bid in the first place.

Furthermore, restatements signal low financial reporting quality that can be more reliably

attributed to aggressive accounting or earnings management. In contrast, the financial reporting

quality measures examined in these prior studies are often constructed to capture the mapping of

accruals into cash flows or the ability to predict future earnings. Low financial reporting quality as

measured in these studies could stem from earnings volatility or high growth rather than aggressive

accounting/earnings management alone. Francis, LaFond, Olsson, and Schipper (2005) similarly

suggest that the conventional accruals-based measures of financial reporting quality are related to both

economic fundamentals and management choices, which are expected to have different implications

for potential acquisition decisions. Finally, financial restatements are readily observable signals, in

contrast to accruals-based measures that require estimating regression models.

Financial Restatements and Deal Valuation

Our last research question examines whether acquirers value restating targets differently from

non-restating targets. The offer price reflects the acquirer’s valuation of the target, as well as

achievable synergies based on knowledge of the target firm obtained from publicly available

financial reports and possibly from private information. The quality of the information is, thus,

pivotal for the pricing of the target.

A number of studies examine the association between the target’s information environment and

takeover premiums. For example, Martin and Shalev (2009) and Raman, Shivakumar, and Tamayo

(2013) show that expected synergies are positively correlated to the target’s information quality.

However, Martin and Shalev (2009) find that target shareholder returns from an acquisition

decrease with information quality of the target firm. A possible explanation is that the market

corrects previous underpricing of target firms with low information quality upon the

announcements of takeovers. This possibility is particularly relevant for restating firms because

the market might overreact to restatements. Thus, market-based measures of deal value are affected

by not only expected deal synergies, but also other factors such as misvaluation of the target,

probability of bid failure, and competition during acquisitions. Therefore, we choose to follow

Officer (2007) and focus on deal multiples in the form of ratios of offer prices to firm fundamentals,

which more unambiguously reflect bidders’ decision making.

Our analyses of deal multiples also help shed light on the results in Hribar and Jenkins (2004)

that financial restatements increase the firm’s cost of capital. Their evidence is consistent with

Easley and O’Hara (2004) and Lambert, Leuz, and Verrecchia (2007), who show that the quality of

accounting information affects the cost of capital. This suggests that acquirers incorporate a higher

cost of capital in valuing the target and make lower takeover offers.

III. SAMPLE SELECTION

We obtain data on takeover transactions from the Securities Data Corporation (SDC) database.

Consistent with Martin and Shalev (2009), we only consider deals in which the acquirer seeks to

purchase 100 percent of a public target so that the acquirer does not have access to private information

prior to the bid. The restriction to public targets ensures the availability of restatement information and

other financial data. These requirements yield a total of 3,762 takeover bids during 2002–2009.



For the sample period of 2001–2008,3 we obtain 4,143 financial restatements from Audit

Analytics for firms that are also covered in Compustat.4 Our empirical tests employ two different

samples based on different intersections between the sample of takeover transactions and the

sample of financial restatements. For our first research question addressing the effects of financial

restatement on takeover likelihood, we obtain a propensity score matched sample between restating

and non-restating firms based on estimated propensity scores of reporting material accounting

misstatements. We first collapse our financial restatements to a sample of 3,756 restating firm-years

because some firms had multiple restatements in one year. We then identify all firm-years in

Compustat that filed no financial statements during 2001–2008. We pool these two samples and use

the filing date of the last financial restatement in the year (the fiscal year-end) as the event date for

the restating (non-restating) firm-years.

For this pooled sample, we estimate a propensity score for reporting material accounting

misstatements based on a modified logistic regression model developed in Dechow et al. (2011). The

Dechow et al. (2011) model focuses on predicting AAERs (Accounting and Auditing Enforcement

Releases by the Securities and Exchange Commission [SEC]), which often lead to financial

restatements. However, AAERs are likely to capture more extreme forms of earnings management

and are also subject to other potential selection biases, as described by Dechow et al. (2011, 18).

Starting with the Dechow et al. (2011) model,5 we add the following additional controls for other firm

characteristics that are likely to differ between restating and non-restating firms: size, leverage, return

on assets, earnings-price ratio, and liquidity (DeFond and Jiambalvo 1994; Dechow and Dichev 2002;

Doyle, Ge, and McVay 2007; Ashbaugh-Skaife, Collins, Kinney, and LaFond 2008; Sun, Yung, and

Rahman 2012).6 For each of our restating firm-years, we identify the non-restating firm in the same

year and industry that has the closest propensity score with less than 0.02 in score difference. This

procedure leads to a final matched sample of 1,963 pairs of restating and non-restating firms with data

available for all required control variables.7 We merge the matched sample with the above takeover

sample of 3,762 deals. If the firm receives a takeover bid within 12 months after the event date, then

we code TAKEOVER as 1, and 0 otherwise. All variables are defined in Appendix A.

Our second and third research questions examine the effects of financial restatements on the

likelihood of takeover withdrawal and on deal valuation. Starting with the sample of 3,762 takeover

transactions, if the firm filed any financial restatements in the 12 months prior to the bid

announcement based on our sample of 4,143 restatements, then we code RESTATE as 1, and 0

otherwise. Our regression analyses for these two research questions are based on 2,271 deals or

smaller samples, depending on the availability of other information required for the specific analyses.8

3 Our research design requires a one-year lag between the restatement sample period and the takeover sample period.4 About 10 percent of the restatements during our sample period in the Audit Analytics database are income-increasing.

Excluding these restatements in the sample does not affect the inferences of this study.5 For space considerations, we refer the readers to Dechow et al. (2011) for the details of their model specification. We

start with their model 3 (Table 7), in which the authors employ financial statement, accruals quality, off-balancesheet, and market-based variables as determinants of misstatements. A similar model is used in Beneish (1999).

6 As a robustness check, we also use a simple one-to-one matching procedure by size, industry, and year instead of thepropensity score matching procedure. The results of our analyses remain qualitatively similar.

7 Our modified model has a concordant rate of 62 percent and a correct prediction rate of 60 percent, comparable tothose reported in Dechow et al. (2011).

8 We do not use a propensity score matched sample in our deal outcome and valuation analyses because of sample sizelimitations. Only 161 restating firms are acquired, and requiring deal values and matching pairs would further reducethe sample size significantly. For example, we can only get 45 pairs of matching restating and non-restating firms thathave information on the ratio of deal value to EBITDA (earnings before interest, taxes, depreciation, andamortization). Such a small sample size fails to provide reliable estimates that can offer useful insights. Therefore, weuse the unmatched sample design in these regressions, but control for a comprehensive list of variables, including thevariables used in the propensity score model.



IV. FINANCIAL RESTATEMENTS AND TAKEOVER LIKELIHOOD

Research Design and Descriptive Statistics

This section examines how prior financial restatements affect the probability of receiving a

takeover bid. Based on the 1,963 pairs of restating and non-restating firms matched on propensity

scores, our test employs the following regression model:

ProbðTAKEOVER ¼ 1Þ ¼ f b0 þ b1�RESTATEþX

bi�CONTROLi þX

yiYEARi þ e� �

:

ð1Þ

Based on prior literature estimating takeover likelihood, we include controls for firm size,

measured as the log of market value (SIZE) as in Hasbrouck (1985) and Palepu (1986), book-to-

market (BM) as in Dong, Hirshleifer, Richardson, and Teoh (2006), and the earnings-to-price ratio

(EP) as in Garvey, Milbourn, and Xie (2011). We proxy for performance using ROA, calculated as

operating income before depreciation and amortization over total assets (Jensen and Ruback 1983;

Cremers, Nair, and John 2009).

Following Palepu (1986) and Ambrose and Megginson (1992), we control for sales growth

(SGROW) and leverage (LEVERAGE), which are both expected to be negatively associated with

takeover likelihood. We further include tangibility of assets (TANG) and liquidity (LIQUIDITY),

based on Ambrose and Megginson (1992) and Berger and Ofek (1996). We also construct a

growth-resource dummy variable (GRDUMMY) similar to Palepu (1986), which is equal to 1 if the

firm either has low growth, high liquidity, and low leverage, or high growth, low liquidity, and high

leverage, and equal to 0 otherwise, where high and low reflect the respective variable values above

and below the Compustat median in the year. Finally, we control for the percentage of institutional

ownership (INST) as a proxy for effective monitoring (Shleifer and Vishny 1986; Cremers et al.

2009). All of our control variables are measured as of the end of the event year. We include year

dummies in all of our regressions to control for takeover waves (Harford 2005).

Figure 2 plots the frequency of matching pairs in our sample. We observe the highest number

of restatement filings in 2006 and the lowest number in 2001. This figure also plots the time-series

of the percentages of restating and non-restating firms receiving takeover bids in the subsequent

year. In every year, a lower percentage of restating firms than non-restating firms receive takeover

bids.

Table 1 reports descriptive statistics for the control variables used in Model (1) for the restating

and non-restating firms, respectively. All continuous variables are winsorized at the 1st and 99th

percentiles. Table 1 reports no statistically significant differences in means of the control variables

of restating versus non-restating firms, and small differences in medians in earnings-to-price ratio

and return on assets, suggesting covariate balance and effective matching. Overall, Table 1 suggests

that our restating and non-restating sample firms are generally similar, except for the incidence of

restatements.

Empirical Results

Table 2 reports the test results of the effects of filing financial restatements on the likelihood of

receiving a takeover bid. Panel A cross-tabulates the frequency of takeovers for the restating and

non-restating firms and provides univariate tests. Consistent with Figure 2, restating firms are less

likely to receive takeover bids than non-restating firms. Of the 1,963 restating firms, only 75 (3.8

percent) receive takeover offers within 12 months of the event date, compared to 132 (6.7 percent)

of their matched non-restating counterparts. This difference in frequencies is statistically significant

at less than 1 percent level (Chi-square 16.77).



We next examine our research question in more robust multivariate logistic regressions (Model

(1)). The dependent variable is TAKEOVER, which is equal to 1 if the firm received a takeover bid,

and 0 otherwise. Standard errors are clustered at the two-digit SIC industry level, as in all other

regressions in this study. The regression results are reported in Column (1) of Table 2, Panel B.

Consistent with univariate results, the coefficient on RESTATE is significantly negative at�0.60 (p

, 0.01). We estimate the probability of receiving a takeover bid for a restating (non-restating) firm

when RESTATE is set at 1 (0) and all other variables are set at their respective sample averages.

When RESTATE¼ 0, the predicted probability of takeover is 5.7 percent, and when RESTATE¼ 1,

the predicted probability is 3.2 percent. Thus, the marginal effect of RESTATE on takeover

likelihood is �2.5 percent, a 44 percent (2.5 percent/5.7 percent) decrease.9

Consistent with the prior literature, the likelihood of a takeover bid is negatively associated

with sales growth and positively associated with leverage, the growth-resource dummy, and the

percent of institutional holdings. All other control variables are generally insignificant. The R2 of

the regression in Column (1) in Table 2, Panel B is 1.85 percent and is in line with the generally low

FIGURE 2The Time-Series of Financial Restatements

This figure is based on 1,963 pairs of restating and non-restating firms matched on propensity of financial misstatementsestimated based on a modified Dechow et al. (2011) model. The sample period is 2001–2008. The figure shows the timetrend of the number of restating firms and percentage of restating and non-restating firms that receive takeover bids in thenext year.

9 As discussed in Section II, our focus on financial restatements is different from the earnings quality measure used inMarquardt and Zur (2013) and Raman et al. (2013). Nevertheless, we also estimate their measure, which followsDechow and Dichev (2002), for our sample and find a correlation of 0.06 between RESTATE and their measure,suggesting that they indeed capture different aspects of financial information quality. In untabulated results, we addthis measure to Model (1) and reestimate the regression. The coefficient on RESTATE remains statistically negative,while the earnings quality variable is not.



explanatory power of tests on acquisition likelihoods (Ambrose and Megginson 1992; Powell

1997).

Different types of restatements may have a different impact on the acquirer’s perception of the

potential costs and risks involved. During our sample period, we observe two types of restatements that

are less likely to be driven by information risk: those related to leases and stock options backdating. The

Financial Accounting Standards Board’s (FASB) clarification on accounting for operating leases in

February 2005 led to a wave of restatements, primarily by industries with significant amounts of leases

on equipment and real estate. These restatements most likely reflect a misunderstanding of the standard

prior to the FASB clarification, as opposed to deliberate attempts to mislead investors. Similarly,

restatements related to stock options backdating might be more related to poor governance of the firm

rather than a signal of poor financial reporting quality and information risk (Collins, Gong, and Li 2009).

We identify 304 firm-years that have restatements related to either leases or stock options

backdating. Column (2) of Table 2, Panel B reports the results of a modified Model (1) with

separate indicators for these types of restatements (LEASE/BACKDATING) and all other

restatements (OTHER). The coefficient for LEASE/BACKDATING is marginally significant at

TABLE 1

Descriptive Statistics of Matched Restating and Non-Restating Sample

Variable n Mean Median P25 P75 Std. Dev.

RESTATE ¼ 1

SIZE 1,963 5.44 5.44 4.04 6.81 1.94

BM 1,963 0.48 0.45 0.24 0.73 1.80

EP 1,963 �0.22 0.01*** �0.13 0.05 0.97

LEVERAGE 1,963 0.18 0.11 0.00 0.28 0.21

SGROW 1,963 0.15 0.07 �0.04 0.21 0.53

LIQUIDITY 1,963 0.34 0.30 0.15 0.49 0.22

TANG 1,963 0.26 0.18 0.07 0.39 0.23

ROA 1,963 0.02 0.08*** 0.00 0.14 0.25

GRDUMMY 1,963 0.35 0.00 0.00 1.00 0.48

INST 1,963 0.42 0.39 0.05 0.75 0.34

RESTATE ¼ 0

SIZE 1,963 5.55 5.54 3.92 7.11 2.18

BM 1,963 0.46 0.45 0.25 0.75 2.01

EP 1,963 �0.24 0.03 �0.09 0.06 1.36

LEVERAGE 1,963 0.18 0.12 0.00 0.28 0.20

SGROW 1,963 0.15 0.08 �0.02 0.21 0.51

LIQUIDITY 1,963 0.33 0.28 0.16 0.47 0.22

TANG 1,963 0.27 0.18 0.08 0.41 0.24

ROA 1,963 0.03 0.10 0.02 0.15 0.27

GRDUMMY 1,963 0.36 0.00 0.00 1.00 0.48

INST 1,963 0.44 0.44 0.06 0.77 0.34

*, **, *** Indicate two-sided significance levels of 10 percent, 5 percent, and 1 percent, respectively, for the differencebetween the restating firms and the non-restating firms, based on t-tests for means and Wilcoxon tests for medians.This table is based on 1,963 pairs of restating and non-restating firms matched on propensity of financial misstatementsestimated based on a modified Dechow et al. (2011) model. The sample period is 2001–2008. RESTATE equals 1 if thefirm filed financial restatement in the year, and 0 otherwise. All variables are measured at the end of the year of therestatement filing. All continuous variables are winsorized at 1 percent and 99 percent.All variables are defined in Appendix A.



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�0.42 (p¼ 0.10). In contrast, the coefficient for OTHER is significantly negative and much higher

in magnitude at �0.64 (p , 0.01). These results are consistent with information risk being one

important driver of the lower likelihood of takeover bids for restating firms.

Financial restatements can be caused by fraud, less serious accounting irregularities such as

intentional aggressive accounting, or simply clerical errors. Ex ante, it is not clear how prospective

acquirers might view these differently. On the one hand, regardless of the motivation of the initial

misstatements, restatements signal unreliable financial information and low earnings quality. On the

other hand, accounting fraud and irregularities might be viewed as more severe than clerical errors,

given that prior research has shown that accounting irregularities have significantly more adverse

effects on the capital market and the CEO/CFO turnover decision than accounting errors (Hennes,

Leone, and Miller 2008).

We use the GAO restatements data provided by Hennes et al. (2008)10 to examine possible

different implications of restatements due to errors and those due to accounting irregularities. To

further identify possible differential effects of accounting frauds, we merge these data with fraud cases

identified from the Audit Analytics database. We apply the same matching procedure as before and

obtain 989 pairs of restating and non-restating firms with all required data available during 2001–

2006, among which 756 are classified as errors, 190 as irregularities, and 43 as fraud.11

We first estimate Model (1) based on this alternative sample for comparability and find similar

results as in Column (1) of Table 2, Panel B (not tabulated). Specifically, the coefficient on

RESTATE is �0.57 (p , 0.01). We next modify Model (1) by separating RESTATE into three

indicator variables, ERROR, IRREGULARITY, and FRAUD, and report the results in Column (3) of

Table 2, Panel B. The coefficient on IRREGULARITY (�0.92) is larger in magnitude than that on

ERROR (�0.56), and both are significantly negative. However, they are not statistically different

from each other. The coefficient on FRAUD, on the other hand, is insignificant, possibly due to lack

of testing power from the infrequent fraud cases.

Overall, to the extent that both accounting irregularities and accounting errors significantly

decrease takeover likelihood, our results suggest that prospective acquirers are concerned about low

accounting quality in general, irrespective of whether the reason for the low quality is due to

intentional misstatements or erroneous application of GAAP. Unreliable accounting numbers

increase information asymmetry and uncertainty, which impedes the acquirer’s assessment of the

target’s value and demotivates them from making acquisition offers.

Additional Analyses

In this subsection, we examine the implications of several alternative factors associated with

financial restatements for acquisition decisions: litigation risk, internal control weaknesses, and

CEO turnover.

Litigation Risk

Financial restatements impose significant litigation risk on the restating firms (Palmrose and

Scholz 2004). Unless an acquisition is structured as an asset purchase, the acquirer generally

10 An updated version of the sample of restatements from the Government Accountability Office (GAO) databasedifferentiated into errors and irregularities is available on Andy Leone’s webpage at: http://sbaleone.bus.miami.edu/.We thank Hennes et al. (2008) for making the data publicly available.

11 Hennes et al. (2008) combine fraud and irregularity cases in their irregularity category, possibly due to theinfrequency of fraud cases, which is also evident in our merged sample. As Hennes et al. (2008) do not separatelyidentify fraud cases in their sample, it is not clear how many of the fraud cases included in their study overlap withthose included in the Audit Analytics database.



assumes all existing and contingent liabilities of the target (Reed, Lajoux, and Nesvold 2007) and,

thus, presumably will take the litigation risk of the restating firms into account when considering an

offer.

We estimate whether the litigation risk of the restating firms influences the takeover decision of

a prospective acquirer by splitting our RESTATE variable into two indicator variables, LITI and

NOLITI, which identify, respectively, our sample firms that are and are not subject to litigation

during the period from one year prior to the event date to one year after.12 The litigation data are

obtained from the Securities Class Action Clearinghouse at Stanford University.13

Table 3, Column (1) presents our estimation results. Both LITI and NOLITI have significantly

negative coefficients with similar magnitude (�0.58 and�0.60, respectively), suggesting litigation

risk has little incremental explanatory power for acquisition decisions. Thus, litigation risk is less

likely driving our main results, and information risk of the restating firms plays the more important

role in the takeover decision.14

Internal Control Weaknesses

Restating firms often (although not always) have ineffective internal control systems in financial

reporting. Like restatements, internal control weaknesses also signal low financial reporting quality

(Doyle et al. 2007) and weak governance. However, arguably, many internal control weaknesses, such

as lack of segregation of duty, are more likely reflective of governance problems that can potentially be

alleviated by installing a more effective management team after takeovers.

We are able to obtain information from Audit Analytics on the effectiveness of internal

controls based on Section 302 or 404 disclosures as required by the Sarbanes-Oxley Act for 2,884

(1,442 pairs) firm-years in our sample during 2004–2008. About 48 percent of restating firms report

ineffective internal controls (WEAKIC) compared to 8 percent of non-restating firms. The

correlation between RESTATE and WEAKIC is 0.44, suggesting that internal control weaknesses

potentially represent different underlying firm characteristics than financial restatements.

We add WEAKIC to Model (1) and also interact WEAKIC with RESTATE to examine how

internal control weaknesses affect the effects of financial restatements on takeover bids. Table 3,

Column (2) shows that the coefficient on RESTATE remains significantly negative (�0.79, p ,

0.01). The coefficient on both WEAKIC and its interaction with RESTATE are positive, but

insignificant. We leave it to future research for a comprehensive analysis on the effects of internal

control weaknesses on acquisitions.

CEO Turnover

The prior literature shows that there is a higher likelihood of top management turnover

following financial restatements (Srinivasan 2005; Desai et al. 2006b). If restating firms choose to

12 According to Palmrose and Scholz (2004), it is significantly less likely that shareholder lawsuits are filed againstrestating firms more than one year after the restatement announcement. This is consistent with the statute oflimitations in securities law under Section 1658(b) related to the filing of lawsuits claiming violation of Section 10(b),which limits the right to litigate to two years from the discovery of a misstatement (which usually occurs before therestatement announcement). We also include a one-year window prior to the restatements because a number of firmsin our sample have other restatements earlier in the year.

13 We are grateful to Mary Billings for providing the litigation data from Billings (2010).14 In untabulated robustness analyses, instead of using actual litigation filed, we estimate an ex ante measure of litigation

probability based on Palmrose and Scholz (2004). We identify restating firms within the top quintile of the litigationprobability as having high litigation risk (HIGHLITI) and the rest as having low litigation risk (LOWLITI). We useHIGHLITI and LOWLITI to replace RESTATE in Model (1). Both LOWLITI and HIGHLITI have significantlynegative coefficients (�0.70 and �0.91, respectively) that are insignificantly different from each other.



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proactively address governance problems by replacing incumbent management, then this can

mitigate the incentives for external acquirers to intervene, which provides an alternative explanation

to our main results in Table 2. We, therefore, investigate whether CEO turnover affects the relation

between financial restatements and the takeover likelihood.

Our data source of CEO turnover is ExecuComp. In order to increase our sample size and,

hence, the power of our tests, we regenerate our propensity score matched pairs based on all firms

that are covered by ExecuComp with all other procedures exactly the same as described in Section

III. We obtain 673 pairs of restating and non-restating firms with all required data available. A total

of 114 (17 percent) of restating firms and 68 (10 percent) of non-restating firms experience CEO

turnover in the event year. The difference in turnover frequency between the two groups of firms is

statistically significant (p , 0.01), consistent with prior research that restating firms are more likely

to replace CEOs.

We add an indicator variable, TURNOVER, and its interaction with RESTATE to our regression

Model (1). Table 3, Column (3) reveals that the coefficient on RESTATE remains significantly

negative at �0.71 (p ¼ 0.07), suggesting that the negative effects of financial restatements on the

takeover likelihood is robust to controls for the effects of CEO turnover. The coefficients on

TURNOVER and its interaction with RESTATE are both insignificant.

Overall, this section provides robust evidence that the filing of financial restatements is

negatively associated with the likelihood of receiving a takeover bid. This effect is both statistically

and economically significant. Further analyses show that our results are robust to controlling for

additional factors, including litigation risk, internal control effectiveness, and CEO turnover,

suggesting that information risk is most likely the driving factor in potential acquirers’ hesitation to

make takeover offers to restating firms.

V. FINANCIAL RESTATEMENTS AND LIKELIHOOD OF TAKEOVER WITHDRAWAL


This section examines our second research question, how a previous financial restatement

affects the likelihood of withdrawal of a takeover bid, by applying the following model for our

empirical tests:

ProbðWITHDRAW ¼ 1Þ ¼ f b0 þ b1�RESTATEþX

bi�CONTROLi þX

yiYEARi þ e� �

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ð2Þ

The dependent variable is WITHDRAW, which takes a value of 1 if the deal status was coded as

withdrawal in SDC, and 0 otherwise. The variable of interest is RESTATE, which takes a value of 1

if the target firm filed any restatements in the 12 months prior to the takeover announcement, and 0

otherwise. Following Skaife and Wangerin (2013), we control for both deal characteristics and

target characteristics measured as of the fiscal year-end prior to the takeover announcement. In

general, the prior literature suggests that most of the same target characteristics that make firms

attractive takeover targets, such as SIZE, BM, and INST, are associated with takeover completion

likelihood, as well (Ambrose and Megginson 1992; Schwert 2000; Dong et al. 2006; Cremers et al.

2009; Gorton et al. 2009). Therefore, we include all control variables from Model (1). In addition,

we control for insider holdings (INSIDER) following Moeller (2005), where insider holdings

proxies for entrenched and more powerful boards that are better able to oppose takeover bids.

Prior evidence also suggests a strong association between deal characteristics and takeover

completion rates. Following this literature (Betton, Eckbo, and Thorburn 2008; Schwert 2000;

Bates and Lemmon 2003; Moeller, Schlingemann, and Stulz 2004; Skaife and Wangerin 2013), we



include the following deal characteristics: diversifying takeovers (DIV), multiple bidders (MBID),

hostile bids (HOST), tender offers (TENDER), the percentage of stock used as payment

(PCTSTOCK), and existence of termination fee clauses for bidder and target (ATERM and TTERM).

We obtain 2,271 deals with data available for all control variables during 2002–2009. Figure 3

plots the frequency of takeover bids and the percentage of restating firms over time for this sample.

Largely consistent with economic cycles, we observe the highest number of takeover bids in 2006–

2007 and the lowest number during the financial crisis of 2008–2009. The percentage of restating

targets generally follows the pattern in Figure 2, with a higher frequency of restating targets in

2005–2006 and a lower frequency in 2002 and 2009.

Table 4 reports descriptive statistics of all variables used in Model (2) separately for the

takeover deals with restating targets (RESTATE¼ 1) in Panel A, and for all other takeover deals in

the sample (RESTATE ¼ 0) in Panel B. On average, the 161 restating targets have significantly

lower sales growth (4 percent versus 15 percent) and significantly lower liquidity (38 percent versus

43 percent) than the 2,110 non-restating targets, but significantly higher leverage (19 percent versus

16 percent) and significantly higher insider holdings (5 percent versus 3 percent). Differences in

medians are generally much smaller in magnitude and/or insignificant. All other target

characteristics are not statistically different between the two groups.

Table 4 also reports that restating targets are more likely to be diversifying (56 percent versus

49 percent) and less likely to receive tender offers (6 percent versus 13 percent) than non-restating

targets. All other deal characteristics are not significantly different. On average, 11 percent (9

percent) of restating (non-restating) targets receive multiple bids, 6 percent (6 percent) receive

hostile offers, 20 percent (16 percent) have acquirer termination fee clauses, and 61 percent (59

FIGURE 3The Time-Series of Takeover Activities

This figure is based on 2,271 takeover bids during 2002–2009. The figure shows the time trend of the number of takeoverbids and percentage of takeover target firms that restate financial statements in the previous year.



TABLE 4

Descriptive Statistics of the Takeover Sample

Panel A: Restating Firms (RESTATE ¼ 1)


SIZE 161 5.14 5.18 3.93 6.68 1.98

BM 161 �1.37 0.51 0.31 0.78 11.88

EP 161 �1.01 0.01 �0.10 0.06 6.42

LEVERAGE 161 0.19* 0.13 0.00 0.30 0.23

SGROW 161 0.04*** 0.05* �0.06 0.15 0.23

LIQUIDITY 161 0.38*** 0.33*** 0.16 0.57 0.24

TANG 161 0.22 0.12 0.04 0.37 0.24

ROA 161 0.03 0.08 0.01 0.12 0.21

GRDUMMY 161 0.39 0.00 0.00 1.00 0.49

INST 161 0.41 0.37 0.06 0.73 0.34

INSIDER 161 0.05** 0.00* 0.00 0.03 0.11

MBID 161 0.11 0.00 0.00 0.00 0.31

HOST 161 0.06 0.00 0.00 0.00 0.23

DIV 161 0.56* 1.00* 0.00 1.00 0.50

TENDER 161 0.06*** 0.00*** 0.00 0.00 0.23

PCTSTOCK 161 16.71 0.00 0.00 0.00 34.87

ATERM 161 0.20 0.00 0.00 0.00 0.40

TTERM 161 0.61 1.00 0.00 1.00 0.49

Panel B: Non-Restating Firms (RESTATE ¼ 0)


SIZE 2,110 4.99 4.96 3.54 6.55 2.19

BM 2,110 �1.87 0.52 0.29 0.86 31.14

EP 2,110 �2.25 0.03 �0.13 0.06 23.77

LEVERAGE 2,110 0.16 0.08 0.00 0.25 0.21

SGROW 2,110 0.15 0.06 �0.04 0.20 0.75

LIQUIDITY 2,110 0.43 0.40 0.20 0.66 0.26

TANG 2,110 0.21 0.11 0.03 0.30 0.23

ROA 2,110 0.02 0.07 0.01 0.13 0.25

GRDUMMY 2,110 0.35 0.00 0.00 1.00 0.48

INST 2,110 0.42 0.38 0.09 0.71 0.33

INSIDER 2,110 0.03 0.00 0.00 0.02 0.07

MBID 2,110 0.09 0.00 0.00 0.00 0.28

HOST 2,110 0.06 0.00 0.00 0.00 0.23

DIV 2,110 0.49 0.00 0.00 1.00 0.50

TENDER 2,110 0.13 0.00 0.00 0.00 0.33

PCTSTOCK 2,110 18.16 0.00 0.00 0.00 34.85

ATERM 2,110 0.16 0.00 0.00 0.00 0.36

TTERM 2,110 0.59 1.00 0.00 1.00 0.49

*, **, *** Indicate two-sided significance levels of 10 percent, 5 percent, and 1 percent, respectively, for the differencebetween the restating targets and the non-restating targets, based on t-tests for means and Wilcoxon tests for medians.This table is based on 2,271 takeover bids during 2002–2009. RESTATE equals 1 if the target firm filed financialrestatements in the year prior to the bid announcement, and 0 otherwise. Panel A shows descriptive statistics forRESTATE¼ 1 and Panel B shows descriptive statistics for RESTATE¼ 0. All variables are measured at the end of thefiscal year prior to the takeover announcements. All continuous variables are winsorized at 1 percent and 99 percent.All variables are defined in Appendix A.



percent) have target termination fee clauses. The percentage of stock used in the acquisition of these

targets is, on average, 16.7 percent for restating versus 18.2 percent for non-restating firms.

Empirical Results

Table 5, Panel A reports the contingency table between RESTATE and WITHDRAW for the

sample of 2,271 deals of Model (2). Among the 161 deals with restating targets, 33 (20.5 percent)

were eventually withdrawn compared to 273 (12.9 percent) among the 2,110 deals with non-

restating targets. This difference in frequencies is statistically significant at 0.01 (Chi-square ¼7.33).

Column (1) of Table 5, Panel B provides logistics estimates of Model (2) that includes target

and deal characteristics as control variables. Column (2) additionally includes variables from the

Dechow et al. (2011) model we use in our matching procedure in the previous section (coefficients

suppressed in the table). In both columns, the coefficient on RESTATE is positive and statistically

significant (0.71 and 0.59, p ¼ 0.01 and p ¼ 0.05, respectively). In Column (1), restating targets

have a 15.4 percent likelihood of withdrawal compared to 8.2 percent for non-restating targets,

setting all other variables at their corresponding sample means. Thus, previous financial

restatements increase the likelihood of takeover bids being withdrawn by almost 88 percent

relative to takeover bids to non-restating targets.

Columns (1) and (2) further show that the likelihood that takeover bids will be withdrawn is

negatively correlated with firm size, tender offers, and the existence of target termination fee

clauses, and positively associated with institutional ownership, insider holdings, the presence of

multiple bidders, hostile bids, and diversifying mergers. There is also a higher likelihood of

withdrawal with increasing percentage of stock used in the acquisition. The signs of the coefficients

on the control variables and the explanatory power of the model (R2 around 20 percent) are

generally consistent with prior evidence (Golubov, Petmezas, and Travlos 2012; Skaife and

Wangerin 2013).

Additional Tests

Financial restatements may not only increase the likelihood of bid withdrawal, but also lead to

a lengthier transaction process. Once the takeover bid is initiated and the acquisition agreement

signed, the bidder begins the due diligence process to verify the target’s financial information and to

gain more current information to value the target’s assets and liabilities. If the information risk is

higher in takeover attempts of target firms that have previously filed financial restatements, then we

expect the acquirer to exert more effort during the due diligence. Following the prior literature, we

count the number of days between the acquisition announcement and the day of completion as a

proxy for the effort in the due diligence (Wangerin 2012; Marquardt and Zur 2013). We use the

decile ranks of this time lag as our dependent variable TIME.

Table 6 presents the OLS regression results for time to completion. We use the same control

variables as before (except for the indicator variables for termination fee clauses), following the

prior literature (Golubov et al. 2012; Wangerin 2012; Marquardt and Zur 2013). Specifically,

Column (1) includes target and deal characteristics as control variables, and Column (2)

additionally includes the misstatement determinant variables from Dechow et al. (2011). The

coefficients on RESTATE are positive and statistically significant in both specifications (0.56 and

0.73, both p ¼ 0.04), suggesting that transactions involving restating targets take significantly

longer to complete. We interpret this as evidence that bidders exert more effort and care in the due

diligence for acquisitions of targets with higher information risk. Wangerin (2012) provides

corroborating evidence using other target characteristics as proxies for information risk, and

Marquardt and Zur (2013) similarly find a negative relation between accounting quality and time to



TABLE 5

Likelihood to Withdraw

Panel A: Univariate Test Results

RESTATE

WITHDRAW

Total0 1

0 1,837 273 2,110

[87.1%] [12.9%] [92.9%]

1 128 33 161

[79.5%] [20.5%] [7.1%]

Total 1,965 306 2,271

[86.5%] [13.5%]

v2 7.33***

p-value 0.00

Panel B: Logistic Regression Results

(1) (2)

Coefficient v2 p-value Coefficient v2 p-value

RESTATE 0.71 7.45*** 0.01 0.59 3.96** 0.05

SIZE �0.15 10.01*** 0.00 �0.14 7.17*** 0.01

BM �0.01 1.21 0.27 �0.02 2.49 0.11

EP 0.02 1.29 0.26 0.03 2.62 0.11

LEVERAGE 0.16 0.22 0.64 0.12 0.11 0.75

SGROW 0.05 0.92 0.34 �0.04 0.25 0.62

LIQUIDITY 0.19 0.15 0.70 1.15 1.37 0.24

TANG 0.57 1.30 0.25 2.16 4.56** 0.03

ROA 0.20 0.26 0.61 �0.09 0.06 0.81

GRDUMMY 0.22 2.41 0.12 0.19 1.20 0.27

INST 0.71 5.46** 0.02 0.69 3.21* 0.07

INSIDER 1.77 3.96** 0.05 0.95 1.10 0.29

MBID 2.27 143.04*** 0.00 2.24 77.82*** 0.00

HOST 2.89 76.82*** 0.00 2.77 55.62*** 0.00

DIV 0.55 15.95*** 0.00 0.66 21.44*** 0.00

TENDER �0.74 8.69*** 0.00 �0.76 7.32*** 0.01

PCTSTOCK 0.01 20.95*** 0.00 0.01 13.97*** 0.00

ATERM 0.33 2.12 0.15 0.29 2.53 0.11

TTERM �0.81 14.68*** 0.00 �0.94 12.80*** 0.00

Intercept �2.52 30.52*** 0.00 �4.39 18.22*** 0.00

Further controls No Yes

Year dummies Yes Yes

Obs. 2,271 1,654

R2 20.01% 22.01%

*, **, *** Indicate two-sided significance levels of 10 percent, 5 percent, and 1 percent, respectively.This table is based on 2,271 takeover bids during 2002–2009. Panel A reports the v2 test for the contingent distributionbetween WITHDRAW and RESTATE. RESTATE equals 1 if the target firm filed restatements in the year prior to the bidannouncement, and 0 otherwise. WITHDRAW equals 1 if the bid is coded as withdrawal by SDC, and 0 otherwise. PanelB reports logistic regression results on the dependent variable WITHDRAW. Column (2) includes determinant variablesfor financial restatements from Dechow et al. (2011) as controls (coefficient estimates not tabulated), in addition to

(continued on next page)



completion. Consistent with the prior literature, bids involving larger targets, targets with higher

leverage, higher profitability, higher percentage of stock used as payment, as well as hostile bids,

take longer to complete. On the other hand, targets with higher sales growth, higher insider

holdings, and higher institutional ownership are associated with a shorter time to completion.

To summarize, the results in this section suggest that acquirers are not only less likely to make

takeover bids to restating firms, but if they make bids to such firms, then the bids are also more

TABLE 5 (continued)

variables included in Column (1). All regressions control for year fixed effects. All variables are measured at the end ofthe fiscal year prior to the takeover announcements. All continuous variables are winsorized at 1 percent and 99 percent.Standard errors are clustered at the industry level.All variables are defined in Appendix A.

TABLE 6

Time to Deal Completion

(1) (2)

Coefficient t-stat p-value Coefficient t-stat p-value

RESTATE 0.56 2.13** 0.04 0.73 2.12** 0.04

SIZE 0.36 6.72*** 0.00 0.39 6.37*** 0.00

BM 0.00 �1.43 0.16 0.00 �0.70 0.48

EP 0.00 1.46 0.15 0.00 0.34 0.73

LEVERAGE 0.78 1.91* 0.06 0.73 1.77* 0.08

SGROW �0.17 �2.30** 0.02 �0.18 �1.86* 0.07

LIQUIDITY �0.33 �0.49 0.62 �0.88 �1.06 0.30

TANG �0.28 �0.45 0.65 0.72 0.75 0.46

ROA 1.15 3.06*** 0.00 0.47 1.12 0.27

GRDUMMY �0.28 �2.13** 0.04 �0.13 �0.72 0.47

INST �1.55 �3.37*** 0.00 �0.44 �1.39 0.17

INSIDER �2.21 �2.57*** 0.01 0.15 0.18 0.86

MBID 0.56 1.27 0.21 0.99 2.61*** 0.01

HOST 3.82 6.02*** 0.00 3.38 4.45*** 0.00

DIV �0.16 �0.74 0.46 0.09 0.60 0.55

TENDER �2.78 �9.00*** 0.00 �2.33 �10.30*** 0.00

PCTSTOCK 0.02 6.06*** 0.00 0.02 6.10*** 0.00

Intercept 4.37 9.79*** 0.00 4.23 3.76*** 0.00



Obs. 1,595 1,122

R2 29.62% 30.47%

*, **, *** Indicate two-sided significance levels of 10 percent, 5 percent, and 1 percent, respectively.This table reports results of OLS regressions on the dependent variable TIME, which is the decile rank of the number ofdays from announcement to completion of the takeover. RESTATE equals 1 if the target firm filed restatements in theyear prior to the bid announcement, and 0 otherwise. The sample period is 2002–2009. Column (2) includes determinantvariables for financial restatements from Dechow et al. (2011) as controls (coefficient estimates not tabulated), in additionto variables included in Column (1). All regressions control for year fixed effects. All continuous variables arewinsorized at 1 percent and 99 percent. All variables are measured at the end of the fiscal year prior to the takeoverannouncements. Standard errors are clustered at the industry level.All variables are defined in Appendix A.



likely to be withdrawn. Furthermore, we find evidence that takeover offers for restating targets

require more effort from the bidder during the due diligence and take longer to complete. These

results provide further support to the conjecture that financial restatements and the resulting high

information risk introduce frictions to the market for corporate control, impeding the efficient

allocation of economic resources.

VI. FINANCIAL RESTATEMENTS AND TAKEOVER DEAL VALUATIONS


We examine whether takeover bids for restating targets are associated with lower takeover deal

valuation. Following Officer (2007), we examine valuation ratios provided by the SDC database:

deal value excluding assumed liabilities to EBITDA, deal value excluding assumed liabilities to

sales, and offer price to book value per share. As explained in more detail in Section II, we focus on

valuation multiples instead of market-based measures to understand how financial restatements

affect the decision making by acquiring firms. Our control variables follow the prior literature and

include both target and deal characteristics (Moeller et al. 2004; Officer 2007; Betton et al. 2008).

Descriptive statistics and univariate tests for the three ratios are provided in Table 7, Panel A.

For the ratio of deal value to EBITDA,15 the mean and the median of the 105 deals involving

restating targets are 14.41 and 9.83, respectively, versus a mean of 19.70 and median of 11.06 for

the 1,343 deals involving non-restating targets, where only the difference in means is statistically

significant (at the 0.01 level). For the second ratio, deal value to sales, the mean (median) for the

141 deals involving restating targets is 1.77 (1.31) versus a mean (median) of 3.01 (1.67) for the

1,852 deals involving non-restating targets. The differences in means and medians are both

statistically significant at the 0.01 and 0.05 levels, respectively. For offer price to book value per

share, the means and medians are lower for the 127 acquisitions of restating targets (2.96 and 2.28,

respectively) than for the 1,689 acquisitions of non-restating targets (3.39 and 2.34, respectively),

but the differences are not statistically significant.

Empirical Results

Table 7, Panels B, C, and D report OLS regression estimates on the deal valuation ratios.

Column (1) includes target and deal characteristics as controls, and Column (2) additionally

includes restatement determinants from Dechow et al. (2011) (coefficients suppressed in the table).

In Panel B, the dependent variable is the ratio of deal value to EBITDA. The results are based on a

sample of 1,448 and 1,056 takeovers with non-missing data, respectively. The coefficients on

RESTATE are�3.40 (p¼0.03) and�6.57 (p , 0.01), respectively, suggesting that, ceteris paribus,takeover bids for restating targets have, on average, lower deal values by about five times of

EBITDA (the average of 3.40 and 6.57). Considering that the average ratio of deal value to

EBITDA for acquisitions of non-restating targets (reported in Table 7, Panel A) is 19.70, this

represents a discount of about 25 percent.

15 This earnings-based multiple should be interpreted with caution because it is truncated and only meaningful andreported by SDC when EBITDA is positive, which is why we also examine non-earnings-based multiples. Onepossible way to address this issue is to use the inverted ratio by dividing EBITDA with deal value excluding assumedliabilities, each reported by SDC individually. However, the inverted ratios are not a linear transformation of theoriginal valuation ratios, which can change the relation between these deal multiples and our independent variables,especially considering that we estimate a linear regression. Moreover, the inverted ratios are not what investors use forvaluation and, thus, may not be helpful in understanding acquirers’ valuation of the target. In untabulated analyses, weuse the inverted ratio EBITDA to deal value as our dependent variable. RESTATE is insignificant in this specification.



TABLE 7

Ratios of Takeover Offer Prices to Fundamentals

Panel A: Univariate Test Results


RESTATE ¼ 1

Deal Value/EBITDA 105 14.41*** 9.83 6.72 16.20 17.33

Deal Value/Sales 141 1.77*** 1.31** 0.59 2.49 1.65

Offer Price/Book Value 127 2.96 2.28 1.56 3.28 2.87

RESTATE ¼ 0

Deal Value/EBITDA 1,343 19.70 11.06 6.70 18.04 35.73

Deal Value/Sales 1,852 3.01 1.67 0.68 3.26 5.76

Offer Price/Book Value 1,689 3.39 2.34 1.48 3.59 5.45

Panel B: Regression Results (Dependent Variable: Deal Value/EBITDA)

(1) (2)


RESTATE �3.40 �2.25** 0.03 �6.57 �3.51*** 0.00

SIZE 0.15 0.18 0.86 0.07 0.10 0.92

BM �0.03 �0.58 0.56 0.03 0.61 0.54

EP 0.07 1.30 0.20 �0.08 �1.33 0.19

LEVERAGE �12.86 �1.83* 0.07 �7.31 �1.36 0.18

SGROW 6.60 1.37 0.18 7.10 1.81* 0.07

LIQUIDITY 20.18 1.88* 0.06 3.33 0.49 0.62

TANG �1.65 �0.37 0.71 �48.59 �4.23*** 0.00

ROA �75.06 �4.42*** 0.00 �97.01 �5.20*** 0.00

GRDUMMY �2.15 �1.08 0.28 �1.26 �0.66 0.51

INST 10.42 2.35** 0.02 1.56 0.42 0.68

INSIDER �5.41 �0.63 0.53 �8.86 �0.89 0.38

MBID 0.27 0.08 0.94 �2.58 �0.96 0.34

HOST �3.33 �1.38 0.17 �3.47 �1.51 0.14

DIV �2.28 �1.09 0.28 �4.72 �3.16*** 0.00

TENDER 7.49 2.00** 0.05 2.30 1.34 0.19

PCTSTOCK �0.07 �3.29*** 0.00 0.01 0.53 0.60

Intercept 13.54 2.02** 0.05 64.09 6.99*** 0.00



Obs. 1,448 1,056

R2 13.03% 30.32%

Panel C: Regression Results (Dependent Variable: Deal Value/Sales)

(1) (2)


RESTATE �0.80 �2.51*** 0.01 �0.87 �2.24** 0.03

SIZE 0.50 5.58*** 0.00 0.50 3.62*** 0.00

BM 0.00 �0.72 0.48 �0.01 �1.22 0.23




TABLE 7 (continued)

(1) (2)


EP 0.00 0.67 0.51 0.00 0.49 0.63

LEVERAGE �0.49 �0.45 0.65 0.01 0.01 0.99

SGROW 1.36 1.58 0.12 1.53 1.12 0.27

LIQUIDITY 3.08 1.90* 0.06 �6.60 �3.15*** 0.00

TANG 0.87 1.51 0.14 �12.18 �3.01*** 0.00

ROA �5.21 �2.08** 0.04 �4.97 �2.58*** 0.01

GRDUMMY �0.35 �1.02 0.31 �0.24 �1.01 0.32

INST 0.03 0.04 0.97 �0.43 �1.09 0.28

INSIDER �1.45 �1.96** 0.05 �1.17 �1.21 0.23

MBID �0.26 �0.72 0.48 �0.70 �1.50 0.14

HOST 0.28 0.39 0.70 0.62 0.66 0.51

DIV �0.15 �0.50 0.62 �0.19 �0.50 0.62

TENDER 0.89 2.68*** 0.01 0.83 2.64*** 0.01

PCTSTOCK 0.01 1.45 0.15 0.01 1.26 0.21

Intercept �1.11 �0.88 0.38 14.58 3.47*** 0.00



Obs. 1,993 1,451

R2 13.25% 23.10%

Panel D: Regression Results (Dependent Variable: Offer Price/Book Value)

(1) (2)


RESTATE �0.51 �1.45 0.15 �0.33 �0.94 0.35

SIZE 0.29 1.64 0.11 0.51 1.99** 0.05

BM �0.08 �2.24** 0.03 �0.13 �1.45 0.15

EP 0.06 1.02 0.31 �0.04 �0.82 0.41

LEVERAGE 5.78 1.87* 0.07 8.21 2.52*** 0.01

SGROW 0.44 1.93* 0.06 0.30 0.91 0.36

LIQUIDITY 2.47 2.21** 0.03 5.23 3.06*** 0.00

TANG �0.21 �0.19 0.85 �0.34 �0.19 0.85

ROA �1.75 �1.22 0.23 �2.01 �1.40 0.17

GRDUMMY �0.18 �0.54 0.59 �0.38 �1.05 0.30

INST 0.49 0.72 0.47 �0.98 �1.38 0.17

INSIDER 0.45 0.52 0.60 �0.10 �0.10 0.92

MBID �0.12 �0.28 0.78 �0.31 �0.71 0.48

HOST �0.64 �2.54*** 0.01 �0.72 �2.66*** 0.01

DIV �0.07 �0.28 0.78 �0.33 �1.65* 0.10

TENDER 0.75 2.16** 0.04 0.20 0.62 0.54

PCTSTOCK 0.00 �0.43 0.67 0.00 0.02 0.98

Intercept �0.52 �0.46 0.64 �3.00 �1.22 0.23



Obs. 1,815 1,292

R2 6.13% 10.58%




In Table 7, Panel C, the dependent variable is the ratio of deal value to sales, and the samplesize is 1,993 for Column (1) and 1,451 for Column (2). In both columns, the coefficient onRESTATE is significantly negative (�0.80 and �0.87, p ¼ 0.01 and p ¼ 0.03, respectively).Compared to the mean deal value to sales ratio of 3.01 for non-restating targets, on average,restating targets are offered an approximately 28 percent discount. In Panel D, the dependentvariable is the ratio of offer price to book value per share. The coefficients on RESTATE arenegative, albeit insignificantly so (�0.51 and�0.33, p¼ 0.15 and p¼ 0.35, respectively). Table 7,Panels B, C, and D also provide some evidence (although not in all specifications) that takeoverdeal valuations are increasing in target firms’ size, leverage, sales growth, liquidity, and for tenderoffers, but decreasing in the target firms’ tangibility, ROA, insider holdings, for hostile bids, anddiversifying deals, which is broadly consistent with the prior literature (Moeller et al. 2004; Officer2007; Betton et al. 2008).

Overall, we find some evidence, albeit not consistently strong across different measures, thattargets that have previously restated their financial statements are valued at lower deal multiples byacquirers than similar non-restating targets. Although one has to exercise caution in interpreting thesedeal multiples, these results complement our earlier analyses by showing that financial restatementsnot only affect the likelihood of takeover, but also the valuation of restating firms, consistent with thenotion that the higher information risk of restating targets increases their cost of capital.

VII. CONCLUDING REMARKS

In this study, we examine the consequences of financial restatements for the market forcorporate control. We find that firms that recently filed financial restatements are significantly lesslikely to become takeover targets than a sample of matched non-restating firms. Our results furthershow that takeover bids made to restating firms are also more likely to be withdrawn, and takelonger to complete, than takeover bids to non-restating firms. Finally, there is some evidence thatdeal value multiples of completed acquisitions are significantly lower for restating targets than fortarget firms that did not previously restate their earnings.

Our results complement prior research on the economic consequences of financial restatementsby showing that financial restatements affect takeover decisions and valuations in the market forcorporate control. We show that higher information risk after restatement filings deters potentialbidding firms from correcting inefficiencies within restating firms via the forces of the disciplinarytakeover.

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TABLE 7 (continued)

*, **, *** Indicate two-sided significance levels of 10 percent, 5 percent, and 1 percent, respectively.This table is based on takeover bids during 2002–2009. RESTATE equals 1 if the target firm filed financial restatements

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APPENDIX A

Variable Definitions

Variable Definition

ATERM Indicator variable equal to 1 if there is a termination fee clause for the acquirer

in place, and 0 otherwise (data from SDC).

LEASE/BACKDATING Indicator variable equal to 1 if the restatement is related to stock options

backdating or lease accounting, and 0 otherwise (data from Audit Analytics).

BM Book-to-market ratio [CEQT/(PRCC � CSHO)].

DIV Indicator variable equal to 1 if takeover is diversifying, and 0 otherwise, where

diversification is based on two-digit SIC codes.

EP Earnings-to-price ratio [EPSPX/PRCC].

ERROR Indicator variable equal to 1 if the restatement is due to error based on GAO

restatements provided by Hennes et al. (2008), and 0 otherwise.

FRAUD Indicator variable equal to 1 if the restatement is due to fraud as identified by

Audit Analytics, and 0 otherwise.

GRDUMMY Growth-resource mismatch dummy following Palepu (1986). Equal to 1 for

firms with low growth (SGROW), high liquidity (LIQUIDITY), and low

leverage (LEVERAGE) or for firms with high growth, low liquidity, high

leverage, and 0 otherwise, where low and high for each variable is defined

relative to Compustat median in the year.

HOST Indicator variable equal to 1 if takeover bid is classified as hostile, and 0

otherwise (data from SDC).




APPENDIX A (continued)

Variable Definition

INSIDER Percentage of insider holdings (data from Thomson Reuters).

INST Percentage of institutional ownership (data from Thomson Reuters).

IRREGULARITY Indicator variable equal to 1 if the restatement is due to irregularity based on

GAO restatements provided by Hennes et al. (2008), and 0 otherwise.

LEVERAGE Financial leverage [(DLTT þ DLC)/AT].

LIQUIDITY Liquidity [(CHE þ RECT)/AT].

LITI Indicator variable equal to 1 if restating firm has been subject to shareholder

litigation in the year around the restatement filing, and 0 otherwise (data from

Billings [2010]).

MBID Indicator variable equal to 1 if multiple bidders are involved in the takeover

process, and 0 if only one bidder is involved (data from SDC).

NOLITI Indicator variable equal to 1 if restating firm has not been subject to shareholder

litigation in the year around the restatement filing, and 0 otherwise (data from

Billings [2010]).

OTHER Indicator variable equal to 1 if the restatement is not related to either stock

options backdating or lease accounting, and 0 otherwise (data from Audit

Analytics).

PCTSTOCK Percentage of stock offered as payment in the acquisition by the bidding firm

(data from SDC).

RESTATE Indicator variable equal to 1 if firm has restated earnings, and 0 otherwise (data

from Audit Analytics).

ROA Return on assets [INCOME/AT].

SGROW Sales growth rate [SALEt/SALEt�1 � 1].

SIZE Natural logarithm of market value of equity [PRCC � CSHO].

TAKEOVER Indicator variable equal to 1 if firm has received a takeover offer, and 0


TANG Tangibility [PPENT/AT].

TENDER Indicator variables equal to 1 if takeover classified as tender offer, and 0


TIME Decile rank of the number of days from announcement of the takeover to

completion (data from SDC).

TTERM Indicator variable equal to 1 if there is a termination fee clause for the acquirer

in place, and 0 otherwise (data from SDC).

TURNOVER Indicator variable equal to 1 if the firm experiences a change in CEO in the

event year, and 0 otherwise (data from ExecuComp).

WEAKIC Indicator variable equal to 1 if the firm reports ineffective internal control based

on Section 302 or 404 disclosures required by the Sarbanes-Oxley Act, and 0

otherwise (data from Audit Analytics).

WITHDRAW Indicator variable equal to 1 if takeover offer has been withdrawn, and 0




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