






































1 

Advertising Response to Financial Misreporting and 

the Implications for Firm Value 

Stacey Sharpe, Ph.D. 

California State University, Los Angeles 

Do firms adjust advertising spending around accounting-based brand scandal events such as 

fraudulent restatement announcements? To address this question, this study presents an empirical 

assessment of firm-level advertising spending around fraudulent restatement announcements. This 

analysis is guided by opposing propositions presented in the brand scandal and marketing-finance 

literature regarding expectations for firm-level advertising response to brand scandals. To test these 

opposing conjectures, an empirical investigation is conducted on a sample of 136 firms accused of 

financial reporting fraud. The dataset is constructed using the SEC and Department of Justice 

enforcement action database for corporate misrepresentation compiled by Karpoff, Lee, and Martin 

(2008a) (KLM) and annual Compustat industrial files. The potential implications of advertising 

spending on post-restatement firm value are also assessed. The results of this study indicate that, on 

average, firms reduce advertising expenditures around fraudulent restatement announcements. The 

reduction in advertising is shown to effectively mitigate the potential damages to firm value. In 

addition to generating support and managerial guidance regarding the relevance of advertising 

expenditures to a firm's reputation management strategies, this paper is the first known study to 

investigate the relationship between advertising spending and an accounting-based brand scandal. This 

study also makes multiple contributions to the advertising, brand scandal, and reputation management 

literature. 

Keywords: Advertising Spending; Restatements; Brand Scandal; Reputation Management; Financial 

Misconduct 

Introduction 

Do firms adjust advertising expenditures around accounting-based brand scandal events such as 
financial reporting fraud? As the primary mode of firm-to-consumer communication, advertising is 
the "voice of the brand" (Keller, 2007, p. 55) and represents an essential aspect of building and 
protecting a firm’s reputation.  Therefore, it is not surprising to find that among marketing scholars 
and practitioners, increased advertising is a preferred and recommended approach to countering the 
negative effects of product-related brand scandal events, including but not limited to product-failures 
and recalls (Cleeren et al, 2008; Cleeren et al., 2013; Rubel et al., 2011).   

http://journals.sfu.ca/abr ADVANCES IN BUSINESS RESEARCH 
2020, Volume 10, pages 1-17 



 

 

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While the subset of marketing literature which focuses on product-related brand scandals is 
extensive and growing, published research focusing on accounting related brand scandals such as 
financial reporting fraud remains nascent among marketing scholars. This is likely due to the overtly 
financial nature of accounting brand scandals as such events are typically lacking in any immediate 
consequences for consumers (i.e., no impact on product, price, availability, overall quality, etc.). 
However, from a resource advantage perspective, brands represent key market-based (intangible) 
assets of the firm and are widely recognized as sources of differentiation, competitive advantage, and 
enhanced cash flows (Srivastava et al.,1998). As such, all adverse brand-related events, product-related 
or not, are of immediate concern to the firm and its stakeholders and should be examined for the 
purpose of strategic understanding and application.  To this end, this investigation purports that the 
studied contexts of brand scandal should be extended to include accounting-based brand scandals, 
namely in the context of financial reporting fraud.  

Financial misreporting (also referred to as fraudulent restatements) involves the conscious 
omissions of relevant information from the firm's financial reports in order to alter the overall image 
presented to investors and other relevant users. As demonstrated by high-profile cases of financial 
reporting fraud involving Enron in 2001 and WorldCom Inc. in 2002, this type of corporate 
misconduct can lead to financial ruin for the accused firm and its investors, instigate widespread 
mistrust among consumers, as well attract regulatory attention (e.g. the Securities Act of 1933 and the 
Sarbanes-Oxley Act of 2002). According to Karpoff et al. (2008a), the legal penalties, levied against 
individual firms accused of financial misreporting between 1978 and 2002 exceeded $23 million on 
average. These authors also show that, on average, the impact of the reputational losses to the affected 
firms tend to be more than 7.5 times the legal penalties.   

The far-reaching implications of these accounting-based brand scandals substantiate the sustained 
scholarly interest in financial reporting fraud events. In addition to the implications of financial 
misreporting, accounting and finance scholars have also given substantial attention to the recovery 
efforts employed by firms accused of fraudulent behavior. Changes to the composition of their boards 
of directors (Farber, 2005), reducing CEO option-based compensation (Cheng & Farber, 2008), 
dismissal of CEO's and other culpable employees (Karpoff et al, 2008b; Wilson, 2008), naming a 
successor CEO (Gomulya & Boeker, 2014), and replacing auditors (Wilson, 2008) are among the 
studied repair strategies—each of which have been shown to have positive effects on firm recovery. 
These studies also provide evidence of investors' interest in and sensitivity to fraudulent restatement 
announcements. However, to date, no attention has been given towards examining marketing-based 
strategies to address the reputational damages of financial misreporting.   

Independent arguments and findings from the extant accounting and marketing-finance literature 
lead to the conclusion that both announcements of financial misconduct and adjustments in 
advertising expenditures are immediately relevant for brand associations and investor behavior. 
Accordingly, the primary objectives of this investigation are, first, to examine the effect (if any) of 
financial reporting fraud on advertising expenditures, and second, to determine the effect (if any) of 
advertising spending on firm value following such events.  

This study tests whether firms adjust their level of advertising spending in the years around (i.e., 
prior to, during, or after) the revelation of financial misreporting. Of note, the traditional views and 
associated findings of the extant brand scandal literature and that of the recent insights generated by 
the empirical findings from marketing-finance studies support conflicting expectations for advertising 
spending strategies around fraudulent restatement announcements and the related implications for 
firm value. While both perspectives support the use of advertising strategies for mitigating potential 
losses to the firm around brand scandal events, the brand scandal and marketing-finance literature 
support differing expectations regarding the associated outcomes of such strategies. Insights from 
brand scandal literature suggests a positive outcome will be achieved by increasing firm-level 



 

 

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advertising, while those of the marketing-finance literature suggests positive outcomes will be achieved 
by a decrease in firm-level advertising. 

 To test these opposing conjectures, an empirical investigation is conducted on a sample of 136 
firms accused of financial reporting fraud between 1977 and 2010. The dataset is constructed using 
the SEC and Department of Justice enforcement action database for corporate misrepresentation 
compiled by Karpoff, Lee, and Martin (KLM) and annual Compustat industrial files. Furthermore, the 
potential implications of advertising spending on post-restatement firm value are also assessed. The 
results of this study indicate that, on average, firms reduce advertising expenditures around fraudulent 
restatement announcements. In addition, the reduction in advertising is shown to effectively mitigate 
the potential damages to firm value. This examination makes multiple contributions to the extant 
literature in the areas of marketing-finance, brand scandal, and financial misconduct. It provides 
support and guidance regarding the relevance of advertising expenditures to a firm's reputation 
management strategies. In sum, the propositions derived from the marketing-finance literature are 
empirically and economically supported by the results of this analysis. Based on what is known, this 
study is the first to investigate the relationship between firm-level advertising expenditures, 
accounting-based brand scandal, and the subsequent implications for firm value. In doing so, this 
study makes several noteworthy contributions to the advertising, brand scandal, and reputation 
management literature —each of which are discussed in the latter sections of the paper. 

The remainder of the paper proceeds as follows: the next section provides a discussion of the 
relevant literature and presents the hypotheses of the investigation. The data and key measures are 
described in the third section. The methodological approach and results of the empirical tests are 
presented in the fourth section, and concluding remarks, contributions, and future research are 
presented in section five. 

 
Literature Review and Hypothesis Development 

 
Strategic Advertising and Brand Building 

 
Advertising as part of the firm's competitive conduct is a common tactic in marketing practice 

and a heavily studied area among marketing scholars. Advertising provides firms with a unique 
opportunity to capture and influence the attention of its target population. Advertising is a widely 
studied area in the marketing discipline. Prior investigations into the potential firm outcomes 
associated with advertising spending indicate that it has the potential to strategically modify consumer 
preference (Chamberlin, 1933; Moorthy & Zhao, 2000), create brand loyalty (Chamberlin, 1933), 
influence changes in market composition (Comanor & Wilson, 1974), increase profitability (Comanor 
& Wilson, 1974; Currim et al., 2012; Joshi & Hanssens, 2010), mitigate the negative implications of 
corporate social irresponsibility on firm performance (Sharpe & Hanson, 2018), influence investor 
attention (Chemmanur & Yan, 2009; Lou, 2014; Madsen & Niessner, 2019), and increase firm value 
(Cohen et al., 2010).  According to the theories of market-based assets (Srivastava et al., 1998) and 
customer equity (Rust et al., 2004), increased investments in marketing helps to generate strong brand 
recognition and a loyal consumer following for the firm. Additionally, Srivastava et al. (1998) theorize 
that greater marketing expenditures create valuable intangible assets through which the firm can create 
barriers to entry and switching, as well as signal greater future profitability.  The robust insights 
generated from these and other studies exploring the firm-level outcomes of advertising spending in 
the context of pursuing competitive advantage illustrate the relevance of increased advertising as part 
of the firm's strategic conduct.  
 

 



 

 

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Strategic Advertising and Brand Scandal Response 

 
To date, advertising remains a key component of firm-level marketing strategy and a heavily 

studied area among marketing scholars. In this study, the relationship between accounting-based 
brand scandals and advertising spending is examined from the crisis management perspectives of 
image repair theory (Benoit, 1995) and the closely aligned situational crisis communication theory 
(SCCT) (Coombs 1998; Coombs 2013). Image repair theory posits that communication is a goal-
oriented activity and that maintaining a favorable reputation is a key goal of communication. Building 
on these key assumptions, Coomb's SCCT purports that organizations will use strategic 
communication to help mitigate the potential for reputational damage during turbulent periods 
(Benoit, 2015; Coombs, 2013; Coombs, 2015; Sellnow & Seeger, 2013). SCCT is a relevant and 
commonly applied approach to image repair by organizations in crisis. The SCCT approach provides 
a succinct list of crisis response strategies organized into four postures—denial (i.e., attack the accuser, 
denial, and shift blame strategies), diminish (i.e., excuse and justification strategies), rebuild (i.e., 
compensation and apology strategies) and bolstering (i.e., bolstering, ingratiation, and victimage 
strategies) (Coombs, 2012, p. 155; see also 2015).  

In the context of brand scandals, insights and recommendations from the extant marketing and 
crisis communications literature support a bolstering posture—namely, a communication-based crisis 
management strategy aiming to reduce the potential for reputational harm thru increased 
communication efforts designed to remind stakeholders of the organization's positive attributes 
(Cleeren et al., 2008; Cleeren et al., 2013; Sharpe & Hanson, 2018). More specifically, this subset of 
literature consistently indicates that by increasing advertising-based communications, scandal facing 
firms can reinforce their desired image and leverage their established relationships with key 
stakeholders through increased visibility.  In doing so, it is also shown that such firms can effectively 
mitigate the potential losses associated with the brand scandal event (Cleeren et al., 2008; Cleeren al., 
2013; Sharpe & Hanson, 2018).  

In their investigation into advertising spending around product-harm related brand scandal 
events, Rubel et al. (2011) propose and test a dynamic model of advertising in which, at each point in 
time, there exists a nonzero probability for the occurrence of a scandal event that hurts brand sales 
and influences marketing effectiveness. Using sales and advertising expenditures data for the 
corresponding weeks associated with product-harm scandals affecting three top automotive brands, 
they find that product harm scandals can reduce baseline sales up to 35% and positively influence 
advertising spending behavior. Moreover, a statistically significant relationship is shown between 
brand scandal occurrence and positive adjustments in post-scandal advertising expenditures—thereby 
suggesting that managers intentionally increase advertising spending levels in response to brand 
scandal occurrences. Based on their findings, and consistent with the recommendations of other 
marketing scholars, Rubel et al. (2011) encourage increases in post-scandal advertising as a strategic 
response to limit, and ultimately recover from, the potential losses associated with brand scandals.  
Additional empirical support for this recommended approach to post-brand scandal advertising is 
generated by Cleeren et al. (2008), Cleeren, et al. (2013), Sharpe & Hanson, (2018), and others.  

From a bolstering posture perspective, increased advertising following a brand scandal event can 
demonstrate (signal) that the firm is committed to the affected brand and thereby generate positive 
expectations among the firm's key stakeholders (consumers, investors, employees, etc.). Based on the 
assumption that brand managers are rational, stakeholders will generally expect that established firms 
will act in the interest of overcoming brand scandals by undertaking necessary investments to mitigate 
potential losses—including but not limited to response actions such as directing brand-related 
communications, voluntary product recalls, and issuing restitutions. Given the heightened levels of 
brand awareness and media attention around financial reporting fraud events along with the serious 



 

 

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threats to the firm's reputation and profitability, accused firms may be prompted to action based on 
the assumption that consumers and investors alike will be exposed to their response strategy.  

The aforementioned theoretical assumptions and the documented preference for increased 
advertising investments following (other categories of) brand scandal events leads to the expectation 
that the same strategy will be implemented by firms facing brand scandals derived from financial 
reporting fraud. More formally, it is anticipated that:   

 
H1a: firms increase advertising expenditures around financial reporting fraud announcements. 
 

Diminished firm value is a major consequence of financial reporting fraud (Karpoff et al., 2008a; 
Murphy et al., 2009). However, the positive expectations and outcomes associated with increased 
advertising spending in both the general and brand scandal contexts lead us to consider the potential 
effect of this strategy on post-restatement firm value. Additionally, growing evidence from the 
marketing-finance literature demonstrates advertising's positive effects on firm value in multiple 
investor-relevant contexts—namely, stock liquidity (Grullon et al., 2004), shareholder value (Lou & 
Donthu, 2006), analyst following (Lou & de Jong, 2012), implied cost of capital (Huang & Wei, 2012), 
and equity offerings (Belo, Lin, & Vitorino, 2014; Chemmanur & Yan, 2009; Lou, 2014). Consistent 
with the arguments and evidence from the extant brand scandal literature regarding the use of 
increased advertising to protect and remediate the brand's position during the post-scandal period, it 
is also expected that: 

 
H1b: increased advertising around financial reporting fraud announcements will mitigate the negative effect of financial 
reporting fraud on post-restatement firm value. 
 
Strategic Advertising and Investor Attention 

 
Studies conducted by Chemmanur and Yan (2009), Lou (2014), and Belo et al. (2014) examine 

strategic advertising activity around equity offerings and the implications of these actions for investor 
behavior. Collectively, these authors argue that firm managers are aware of the positive effect of 
advertising on investor attention and intentionally adjust advertising expenditures around key financial 
market events in order to strategically leverage this attention and thus influence the firm's stock 
returns. For example, in their examination of annual advertising spending among a sample of equity 
issuing firms in the initial public offering (IPO) year and the adjacent non-IPO years (specially, the 
two years before and two years after), Chemmanur and Yan (2009) find that IPO  firms make 
significant increases to advertising spending prior to making initial public offerings (from year t-1 to 
the IPO year t). Advertising spending between the IPO year t and the year immediately following 
(t+1) are also shown to be significantly reduced. These authors further conclude that the significant 
increase in advertising expenditures just prior to the IPO year followed by the significant decrease in 
advertising expenditures in the year after gives cause to suspect that managers intentionally adjust 
advertising to increase firm visibility prior to initial public offerings. Additionally, they find that the 
stock returns for firms with this practice tend to be unusually high during the IPO year.  

Similar advertising spending strategies are also observed around seasoned equity offerings 
(SEOs). In similar studies, Lou (2014) and Belo et al. (2014) confirm Chemmanur and Yan's findings 
regarding the adjustment of advertising around SEOs. Lou (2014) provides additional evidence of 
increased advertising leading to contemporaneous growth in abnormal stock returns. This research 
also finds that managers opportunistically adjusting advertising spending around insider sales. More 
specifically, to examine the extent to which managers adjust advertising expenditures in the years 
before, contemporaneous, and subsequent to insider sales Lou conducts a pooled OLS regression 
using a sample of Compustat firms. Relative to all other years, his research reveals that the average 



 

 

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advertising spending in the years before, contemporaneous, and after insider sales is 5.3% higher, 6.9% 
higher, and 3.9% lower. Lou contends that this inverted V-shaped pattern in firm-level advertising 
spending around insider sales provides evidence of intentional behavior among managers to exploit 
the effect of advertising on stock returns for the benefit of their firm. Compared to a matched sample 
of firms which did not have insider sales Lou finds that, the average advertising expenditures for firms 
with insider sales is significantly higher in the two years before insider selling (i.e., t-2 and t-1) and 
significantly lower in the two years after (i.e., t+1 and t+2). Moreover, this analysis provides additional 
support for the argument that managers intentionally adjust advertising spending for the purpose of 
influencing investor behavior and stock prices around insider sales. In addition, a weak correlation is 
observed between advertising spending and future sales growth in periods of insider sales compared 
to other years and the observed pattern of advertising spending around insider sales is shown to be 
greater when there is an increased volume of insider selling. In an empirical analysis similar to that of 
Lou (2014), Belo et al. (2014) use an investment in brand capital (a variable constructed using annual 
advertising expenditures) to examine advertising and stock returns around SEOs. Consistent with the 
results reported by Lou (2014), they also observe an inverted V-shaped pattern in advertising 
investments around SEOs and find that this strategy has positive effects on stock returns during the 
immediate year before and contemporaneous to equity offerings.   

Furthermore, Madsen and Niessner (2019) examine the role of advertising in financial markets 
by evaluating the advertising strategies used by firms to influence investor attention around earnings 
announcements. They find that daily print advertisements, especially those in weekend business 
publications, generate significant increases in Google searches for the advertised firm's stock ticker. 
These results illustrate how a firms' advertising activity can effectively attract investors' attention. 
Madsen and Niessner also test for differences in advertising volume around earnings announcements 
and find that when earnings are positive firms weekly advertising increases by 3% starting one week 
prior to the earnings announcement through two weeks after the announcement—then returning to 
average advertising levels in the following weeks. These findings offer evidence consistent with that 
of an earlier study by Cohen et al., (2010) showing that managers engage in real earnings management 
behavior to meet financial reporting benchmarks. More specifically, Cohen and authors find that, on 
average, managers in their sample intentionally reduced advertising expenditures to alleviate potential 
losses and or decreases in earnings. The insights generated by Cohen et al. (2010) and Madsen and 
Niessner (2019) showing that firms tend to reduce advertising when anticipating the release of negative 
information is contrary to the established support and recommendation from extant marketing and 
brand scandal literatures. This observed inconsistency suggests that managers anticipate that the 
interpretation of the firm's advertising around brand scandal events will be different for investors and 
consumers. As such, it can also be assumed that the firm's advertising spending strategy will differ 
when facing a product-based brand scandal event versus an accounting-based brand scandal event. 

Chen et al. (2009), examination of investor sensitivity to the firm's brand scandal response, 
generate further support for this view. Chen et al. (2009), measures the effect of proactive and passive 
response strategies on firm's financial value following a product-recall. To facilitate their investigation, 
the authors use a sample of Consumer Product Safety Commission recall announcements and daily 
stock return data for firms publicly traded on the New York Stock Exchange between 1996 to 2007. 
Using event study analysis, they show that, on average, proactive response strategies (i.e. voluntary 
recalls, product replacements, etc.)  have a more negative effect on firm value compared to more 
passive strategies—irrespective of firm and product characteristics. These results suggest that 
investors interpret proactive response strategies as indicative of an expectation on the part of the firm 
for severe financial losses.   

While Chen et al. (2009) do not examine advertising response strategies, the findings of their 
study does suggest that investors would likely respond negatively towards proactive strategies 
involving increased advertising as well. This expectation is largely due to the increased visibility that 



 

 

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would be generated for the scandal facing firm as a result of an increase in advertising activity. For 
example, in the context of Chen et al. (2009) study, the proactive response to product harm crises was 
measured by the firm's voluntary recall of defective products. Though necessary for the safety and 
wellbeing of the firm's consumers at large, the recall-related communications will likely be widely 
distributed and discussed making the event highly visible. It is further assumed by the Chen and 
coauthors that the increased visibility around this negative event will likely be discouraging to investors 
who may see this action as a sure sign of culpability—therefore leading them to take action to 
disassociate with the firm.   

Benoit's image repair theory also stresses the relevance of audience (stakeholder) perceptions to 
the selection and ultimate success of communication-based crisis response strategies (Benoit, 2015, p. 
45; see also 1995). This perspective posits that, as part of their image repair strategy, the crisis facing 
organization seek to understand and influence the perceptions of multiple audiences—namely, 
employees, consumers, investors, government officials, and potentially other citizens. Benoit also 
emphasizes that different audiences can have dissimilar values and perspectives in their evaluation of 
crisis situations and, as such, a crisis response strategy designed for one audience (i.e., consumers) may 
not persuade another audience (i.e., investors). In the aforementioned study, Chen et al. (2009) provide 
strong empirical verification of investor sensitivity to product-based brand scandal response efforts. 
Furthermore, the findings suggest that pronounced differences may exist in the advertising response 
strategy used by firms when facing a nonproduct related brand scandal event. These findings and 
perspectives also support a rationale for the alternative expectation that managers will reduce 
advertising activity around accounting-based brand scandal events. That said, it also reasonable to 
expect that: 

 
H2a: firms decrease advertising expenditures around financial reporting fraud announcements. 

 
Additionally, as a result of the anticipated decrease in advertising expenditures around financial 

reporting fraud announcements, it is also expected that the positive effect of advertising on firm value 
will be significantly reduced around such events. Arguably, by decreasing their advertising activity 
around financial reporting fraud, managers would reduce the firms advertising-derived visibility and 
in doing so limit investor attention and focus towards the negative event.  This rationale motivates the 
following expectation: 

 
H2b: decreased advertising around financial reporting fraud announcements will mitigate the negative effect of 

financial reporting fraud on post-restatement firm value. 

 
Data and Key Variables 

Sample 

 
The dataset for this examination is constructed using firm-level accounting information from the 

annual Standard and Poor's Compustat industrial files and the SEC and US Department of Justice 
enforcement action database for financial misreporting compiled by Karpoff et al.(2008a, 2008b) 
(hereafter referred to as KLM). The KLM data makes it feasible to identify enforcement actions 
initiated, by the SEC and US Department of Justice against 626 firms between 1973 and 2011 for 
actions which violate one or more of the books and records, internal controls, or circumvention 
provisions outlined by the Securities Exchange Act of 1934 as amended by the Foreign Corrupt 
Practices Act of 1977 (15 U.S.C.A. § 78 m(b)(2)(A)).   

When matched at the firm and year levels, Compustat accounting data are available for 412 of 
the 626 KLM misreporting firms.  Next, the sample is separated into two groups. The first group 
includes misreporting firms for which annual advertising data are available in Compustat, while the 



 

 

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second group includes misreporting firms for which no annual advertising data is available in 
Compustat. The sample size is further reduced by the exclusion of firms in the financial and regulated 
utilities industries (SIC codes 6000-6999 and 4900-4999) and those for which the dependent or the 
control variables are missing. This selection process yields a final sample of 3,686 firm-year 
observations from 1977 to 2010 for 258 misreporting firms. There are 136 misreporting firms in the 
dataset sample with available advertising expenditures data and 122 without.  Table 1 presents the 
sample selection process leading to the final sample of misreporting firms. 

 
Table 1 - Sample Selection of Misreporting Firms 

 
Variables 

Restatement. Financial restatement reflects a form of accounting-based misconduct—occurring 
when firms provide stakeholders with financial information that is neither credible nor accurate. 
Restatements can arise from both managerial incompetence as well as from intentional acts of 
deception, both of which are damaging to a firm's reputation. Restatements provide a unique setting 
for this investigation into the relationship between financial reporting fraud and firm-level advertising 
expenditures. In this study, the Restatement variable equals one if a firm faced SEC enforcement actions 
for financial restatement in a given year and zero otherwise. 

Advertising expenditures.  In the Compustat database, advertising expenditures data are defined as 
the total annual cost of advertising media (television, radio, periodicals, etc.) and promotional 
expenses. This examination focusses on the firm's total annual advertising expenditures (defined as 
the natural logarithm of one plus advertising expenditures)—hereafter referenced as logAdx.  

Firm value. The proxy for firm value is Tobin's q—a common method of estimating the fair value 
of the stock market. Consistent with prior research, this measure is computed as the ratio of market 

This dataset is constructed using the SEC and Department of Justice enforcement action database for corporate 

misrepresentation compiled by Karpoff, Lee, and Martin (KLM) between 1973 and 2010 and annual Standard and Poor’s 

Compustat industrial files. The sample consists of 136 firms subject to enforcement actions for violating one or more of 

the books and records, internal controls, or circumvention provisions outlined by the Securities Exchange Act of 1934. 

 Number of 
Firms 

Number of 
Restatements 

All enforcement actions initiated by the SEC and DOJ in KLM database between 

1973 and 2010 (i.e., fraudulent financial reporting, bribery, criminal 

obstruction/perjury, 1933 Securities Act fraud, etc.)  

945 1102 

Less:   

– Firms identified by the SEC for having intentionally misrepresented their 

financial statements (namely, those identified by the SEC as having 

intentionally violated of one or more of the three provisions of Securities 

Exchange Act of 1934  

252 294 

– Firms with multiple fraudulent restatements (10 firms had 2 

restatements) 

10 20 

– Firms with no identifiable restatement announcement date 57 162 

– Firms not matched to Compustat database 67 67 

– Firms with no Compustat data available during or after the restatement 

announcement year  

147 147 

– Restatements lost with the exclusion of firms in the financial and 

regulated utilities industries (SIC codes 6000-6999 and 4900-4999) and 

those for which advertising, Tobin’s Q and control variables are missing.  

154 154 

Final Sample    

Firms with advertising expenditures data in Compustat database 136 136 

Firms without advertising expenditures data in Compustat database 122 122 

 258 258 

 



 

 

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value of the firm over the replacement value of its assets where the market value of assets is equals to 
the sum of book value of assets and market value of equity less the sum of book value of equity and 
deferred taxes (Hirshleifer et al., 2012).   

Control variables. Multiple firm and industry-level factors are controlled for in this examination. 
Among the firm-level controls, firm size (logAssets) is measured as the natural logarithm of the firm’s 
book value of total assets.  Sales (logSales) is measured as the natural logarithm of annual sales. Return 
on assets (ROA) controls for firm profitability and is defined as operating income before depreciation 
scaled by the book value of its total assets. Capital intensity (PPE/Emp) is captured by the ratio of net 
property, plant, and equipment to the number of employees, and firms’ market value of equity (MVE) 
is the product of a firm’s common shares outstanding multiplied by its annual closing price. 
Additionally, market-to-book is measured as the ratio of (book value of assets – book value of equity + 
value of equity) to book value of total assets. Consumer firms (Consumer) are also specified among the 
control variables. The age of the firm (logAge), defined as the natural logarithm of the number of years 
the firm has been listed in the Compustat database, is also accounted for.  Lastly, industry competition 
is controlled for using the Herfindahl-Hirschman Index (HHI).  

To minimize the effect of outliers, all the continuous and ratio variables are winsorized at the 1st 
and 99th percentile levels. Moreover, year dummies are also included in the regression analysis to 
control for potential market-wide fluctuations and business cycle effects.  

 
Empirical Analysis and Results 

Summary Statistics 

 
Table 2 presents summary information for the sample of misreporting firms with available 

advertising data in the Compustat database along with a sample of misreporting firms without available 
advertising expenditures. On average, the sample of 136 misreporting firms spend over $97 million 
annually on advertising. Additionally, the average annual growth rate of advertising expenditures for 
these firms is 20.6%. Unless otherwise noted, the empirical tests are conducted using all non-missing 
firm-year observations for the sample firms with available advertising expenditures data. This 
approach is consistent with prior studies focusing on advertising around financial events (see Belo et 
al., 2014; Madsen & Niessner, 2019; Lou, 2014).  
 
Table 2 – Summary Statistics 

 

 

Panel A: Misreporting Firms with Available Advertising Expenditures Data in Compustat  

Variable N Mean Std. Dev. Min Median Max 

Restatement 2122 0.064 0.245 0.000 0.000 1.000 

Total Assets [$M] 2122 3314.278 8871.554 0.409 257.346 59000.000 

Market Value of Equity [$M] 2122 4112.693 13000.000 0.783 221.882 85000.000 

Market-to-book 2122 2.009 2.463 0.204 1.241 20.578 

Return on Assets 2122 0.038 0.339 -2.365 0.112 0.432 

Herfindahl-Hirschman Index 2122 0.375 0.212 0.109 0.317 1.000 

Property Plant Equipment/Employees 2122 41.813 90.044 0.839 19.225 1801.882 

Sales [$M] 2122 3311.776 7976.582 0.014 310.486 44000.000 

Tobins Q 2122 2.365 2.517 0.603 1.550 21.373 

Advertising Expenditures [$M] 2122 97.032 294.062 0.000 3.899 1800.000 

% growth in advertising 2122 0.206 0.763 -1.000 0.022 3.482 

Firm Age* [Years] 2122 22.084 15.809 3.000 17.000 57.000 

 



 

 

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Baseline Results: Restatement, Advertising Investment, and Firm Value 

 
This examination is guided by the marketing, management, and accounting literature, the average 

effect of fraudulent restatement announcements on the advertising spending and firm value of the 
sample firms is examined. Preliminary assessments are made using the following ordinary least squares 
(OLS) regression model, 

 

𝑙𝑜𝑔𝐴𝑑𝑥𝑖,𝑡( 𝑄𝑖,𝑡) =  𝛼 +  β1𝑅𝑒𝑠𝑡𝑎𝑡𝑒𝑚𝑒𝑛𝑡𝑖,𝑡 +  𝛾𝑍𝑖,𝑡 +  𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑖 + 𝑌𝑒𝑎𝑟𝑡 +  𝜖𝑖,𝑡, (1) 

  
where i and t reference the firm and time index, respectively. The dependent variables are logAdx and 
Q—the previously defined measures of annual advertising expenditures and firm value, respectively. 
In this model, Restatement is the independent variable of interest. The coefficient associated with this 
variable (β1) captures the difference in logAdx (Q) between the restatement announcement year and all 
other years for the average misreporting firm in the sample. Z is a vector of the control variables 
(logAssetst-1, Market-to-bookt-1, HHIt-1, Consumer, and logAdxt-1 when logAdxt is the dependent variable and 
logAssetst-1, logSales_Growtht-1, HHIt-1, logPPE/Empt-1, and logAdxt-1 when Qt is the dependent variable).  
Year and industry fixed effects are also included to account time and industry trend effects, and 
standard errors clustered at the firm level.  

The results for Equation 1 are presented in Table 3. As expected, restatement announcements 
events are shown to have a significantly negative effect on annual advertising expenditures and firm 
value. More specifically, as shown in Panel A of Table 3, Restatement announcements have a negative 
and significant impact on logAdx. This effect is consistent in the univariate (Column 1; β = -.219, p < 
.05) and multivariate (Column 1; β = -.098, p < .01) setting. The observed relationship between 
restatement announcement and advertising expenditures is also shown to become more significant 
when consumer firms (Column 3) and advertising expenditures (Column 4) are added to the control 
variables.  

The results presented in Panel B of Table 3 show that restatement announcements also have a 
negative and highly significant effect on firm value. Specifically, in the univariate setting (Column 1), 
Restatement announcements instigates significant declines in Q (β = -.451, p < .05). This relationship 
remains negative and increases in significance after controlling for the previously defined list of 
confounding factors—β = -.458, p < .01 in Columns 2 and β = -.438, p < .01 in Column 3.  

Overall the results in Panel A of Table 3 suggest that fraudulent restatements have a negative 
impact on advertising expenditures—providing baseline support for the expectations of H2a (and 
against that of H1a).  The results in Panel B of Table 3 corroborate the expectation that misreporting 

Panel B: Misreporting Firms without Available Advertising Expenditures Data in Compustat 

Variable N Mean Std. Dev. Min Median Max 

Restatement 1564 0.070 0.256 0.000 0.000 1.000 

Total Assets [$M] 1564 1761.159 4679.757 0.848 120.976 39000.000 

Market Value of Equity [$M] 1564 1560.040 5820.896 0.671 110.404 73000.000 

Market-to-book 1564 1.755 2.227 0.199 1.047 14.715 

Return on Assets 1564 -0.004 0.387 -2.365 0.092 0.400 

Herfindahl-Hirschman Index 1564 0.024 0.018 0.008 0.019 0.133 

Property Plant Equipment/Employees 1564 57.728 121.435 1.416 20.912 742.747 

Sales [$M] 1564 2242.177 7068.434 0.030 141.555 48000.000 

Tobins Q 1564 2.137 2.390 0.572 1.378 16.076 

Firm Age [Years] 1564 17.416 12.575 3.000 12.000 57.000 

 



 

 

11 
 

negatively impacts shareholder activity (Karpoffet al., 2008a). Additionally, baseline support is 
provided for H1b (and against H2b) regarding the potential for advertising to reduce the negative 
impact of restatement on firm value. Specifically, in Column 3 in Panel B of Table 3, the effect of 
Restatement on Q is shown to be negative and significant (β = -.438, p < .01) while the effect of 
logAdx on Q is shown to be positive and significant (β = .384, p < .01). 
 
Table 3 - Baseline Regressions  

 
 

 

This table shows OLS regression results of the effects of restatement on advertising expenditures and Tobin’s Q. 
Coefficient estimates for industry dummies (based on the Fama-French 12 industry classification) and year dummies are 
not reported. T-statistics, shown in parentheses, are based on standard errors clustered at the firm level. ***, **, and * 
denote significance at 1%, 5%, and 10% respectively. 

Panel A: Restatement and Advertising Expenditures 

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

Restatement -0.219** -0.164** -0.211*** -0.098*** 
 (0.109) (0.065) (0.068) (0.033) 
logAssetst-1  0.750*** 0.766*** 0.037*** 
  (0.041) (0.040) (0.009) 
Market-to-book  0.096*** 0.082*** 0.018*** 
  (0.018) (0.022) (0.005) 
Herfindahl-Hirschman Indext-

1 
 0.207 0.081 -0.027 

  (0.553) (0.320) (0.049) 
Consumer   0.253 0.014 
   (0.237) (0.021) 
logAdvertisingt-1    0.962*** 
    (0.010) 
Year_dum Yes Yes Yes Yes 
Industry_dum Yes Yes No No 
_cons 3.202*** -1.386*** -1.855*** -0.087 
 (0.885) (0.419) (0.236) (0.058) 

N 2122 1984 1984 1822 
adj. R2 0.145 0.791 0.770 0.977 

Panel B: Restatement and Firm Value  
 (1) (2) (3) 
 Qt Qt Qt 

Restatement -0.451** -0.458*** -0.438*** 
 (0.204) (0.161) (0.166) 
logAssetst-1  -0.180*** -0.474*** 
  (0.058) (0.103) 
logSales_Growtht-1  0.313*** 0.345*** 
  (0.107) (0.118) 
Herfindahl-Hirschman Indext-1  -0.056 -0.086 
  (0.681) (0.702) 
logProperty Plant Equipment / 
Employeest-1 

 -0.011 -0.012 

  (0.009) (0.009) 
logAdvertisingt-1   0.384*** 
   (0.096) 
Year_dum Yes Yes Yes 
Industry_dum Yes Yes Yes 
_cons 1.820*** 2.499*** 3.507*** 
 (0.574) (0.752) (0.835) 

N 2122 1897 1751 
adj. R2 0.121 0.175 0.210 

 



 

 

12 
 

 
Analysis of Hypothesis 1a and 2a 

 
While the results generated by Equation 1 offer some baseline support for the propositions under 

investigation, the focus is limited to a general explanation of the effect of restatement announcements 
on advertising expenditures and firm value. As it is the aim of this investigation to evaluate advertising 
spending around fraudulent restatement announcements and the implications thereof for firm value, 
the established approaches of Lou (2014), Belo et al. (2014), and Madsen and Niessner (2019) are 
referenced, and the following pooled regression model is used to examine the conjectures of H1a and 
H2a: 

 

log (𝐴𝑑𝑥)𝑖,𝑡  =  𝛼 +  𝛽1𝑝𝑟𝑒𝐸𝑣𝑒𝑛𝑡𝑖,𝑡  + 𝛽2𝐸𝑣𝑒𝑛𝑡𝑖,𝑡 + 𝛽3𝑝𝑜𝑠𝑡𝐸𝑣𝑒𝑛𝑡𝑖,𝑡 + γ𝑍𝑖,𝑡−1

+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑖 + 𝑌𝑒𝑎𝑟𝑡 +  𝜖𝑖,𝑡, 

(2) 

where i refers to the firm and t indexes time. The dependent variable in this model is the previously 
defined advertising expenditures variable logAdx. Event, is a dummy variable which equals one if the 
firm has a restatement in that year and zero otherwise. For all years where Event equals zero, preEvent 
equals one if year t+1 is an event (restatement) year, and likewise postEvent equals one if year t-1 is an 
event year and zero otherwise.  The coefficients of these dummy variables indicate whether the average 
advertising expenditures in the year before, during, or subsequent to the restatement announcements 
are different from those in an average non-restatement year (i.e., when all three dummy variables are 
zero).  In this model, Z is a vector of the previously defined control variables. Year and industry fixed 
effects are also included to account time and industry trend effects and standard errors clustered at 
the firm level.  

H1a (H2a) predicts positive (negative) and significant coefficients around restatement 
announcements. As such, it is expected that advertising expenditures for misreporting around 
restatement announcements will be higher (lower) than in all other years. The multivariate results 
corresponding to this prediction are shown in Table 4. In Columns 1 to 3, the results indicate that on 
average annual advertising expenditures are significantly lower in the year before, contemporaneous, 
and subsequent to a restatement announcement than average advertising expenditures in a non-event 
year. When the lag of advertising expenditures and the consumer variables are included among the list 
of controls (Column 4), the negative effect of misreporting on annual advertising expenditures in the 
year prior to and following the restatement announcement loses significance. However, the average 
advertising spending in the year of the restatement announcement remains negative (β = -.102, p < 
.01). This result suggests that the average advertising expenditures in the year of fraudulent restatement 
announcements are 10.2% lower than in a non-restatement announcement year.  Taking the mean 
annual advertising expenditures for the firms in the sample ($97 million), this coefficient represents 
an average reduction of $9.9 million in annual advertising spending during the restatement year. H2a 
is, therefore, empirically and economically supported.  

In sum, the observed pattern of the event dummy coefficients reported in Table 4 indicates that 
managers reduce advertising investments during the year of the restatement announcement. These 
findings are consistent with the rationale that managers make significant reductions in advertising 
expenditures prior to the announcement of negative information to reduce the advertising-based 
visibility of their firm and to avoid the intensification of negative associations among investors.     

 
 
 

  



 

 

13 
 

Table 4 - Advertising Spending Around Financial Reporting Fraud  

 

 

Analysis of Hypothesis 1b and 2b 

 
H1b (H2b) posit that the firm's advertising around fraudulent restatement announcements will 

mitigate the negative effect of misreporting on post-restatement firm value. Consistent with the 
approach used to examine H1a and H2a, the following pooled OLS regression model is used to assess 
these predictions:    

 

𝑄𝑖,𝑡  =  𝛼 +   𝛽1𝑝𝑟𝑒𝐸𝑣𝑒𝑛𝑡𝑖,𝑡  +  𝛽2𝐸𝑣𝑒𝑛𝑡𝑖,𝑡  +  𝛽3𝑝𝑜𝑠𝑡𝐸𝑣𝑒𝑛𝑡𝑖,𝑡  
+ 𝛽4𝑝𝑟𝑒𝐸𝑣𝑒𝑛𝑡𝑖,𝑡 ∗ log 𝐴𝑑𝑥𝑖,𝑡   + 𝛽4𝐸𝑣𝑒𝑛𝑡𝑖,𝑡 ∗ log 𝐴𝑑𝑥𝑖,𝑡  
+ 𝛽4𝑝𝑜𝑠𝑡𝐸𝑣𝑒𝑛𝑡𝑖,𝑡 ∗ log 𝐴𝑑𝑥𝑖,𝑡  +  γ𝑍𝑖,𝑡−1 +  𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑖  +  𝑌𝑒𝑎𝑟𝑡  +  𝜖𝑖,𝑡, 

 

 

(3) 

  
where the dependent variable Q is firm value for firm i. The measure as well as the preEvent, Event, and 
postEvent variables are as defined in the previous section. In this model, three key interaction terms are 
used among the list of independent variables—namely, preEvent*logAdx, Event*logAdx, and 
postEvent*logAdx Including these interactions allows for the examination into how firm value is 
affected by advertising expenditures in the years before, contemporaneous, and after the restatement 
announcement. As in the prior models, Z is the vector of control variables associated with Q. Year 
and industry fixed effects are also accounted for, and standard errors are clustered at the firm level. 

If the prediction of H1b (H2b) is supported, a positive significant (insignificant) relationship 
should be observed between the postEvent*logAdx interaction and Q.  Table 5 presents the regression 
results for Equation 3.  Before and after the inclusion of the control variables, the results in Table 5 

This table shows pooled OLS regression analysis of total advertising spending around financial reporting fraud. Coefficient 
estimates for industry dummies (based on the Fama-French 12 industry classification) and year dummies are not reported. 
T-statistics, shown in parentheses, are based on standard errors clustered at the firm level. ***, **, and * denote significance 
at 1%, 5%, and 10% respectively. 

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

preEventt -0.326** -0.256*** -0.276*** -0.002 
 (0.138) (0.076) (0.085) (0.033) 
Eventt -0.279** -0.201*** -0.253*** -0.102*** 
 (0.130) (0.075) (0.079) (0.033) 
postEventt -0.305** -0.127* -0.171** -0.046 
 (0.126) (0.071) (0.075) (0.031) 
logAssetst-1  0.750*** 0.766*** 0.037*** 
  (0.041) (0.040) (0.009) 
Market-to-book  0.097*** 0.083*** 0.018*** 
  (0.018) (0.022) (0.005) 
Herfindahl-Hirschman Indext-1  0.195 0.082 -0.028 
  (0.555) (0.321) (0.049) 
Consumer   0.249 0.013 
   (0.236) (0.021) 
logAdvertisingt-1    0.961*** 
    (0.010) 
Year_dum Yes Yes Yes Yes 
Industry_dum Yes Yes No No 
_cons 3.258*** -1.338*** -1.806*** -0.083 
 (0.892) (0.424) (0.240) (0.058) 

N 2122 1984 1984 1822 
adj. R2 0.147 0.792 0.771 0.977 

 



 

 

14 
 

show that on average Q is significantly lower during the misreporting event year and the year after 
compared to a non-event year. Consistent with the baseline regression results of Panel A in Table 3, 
the logAdxt-1 variable is shown to have positive effect on Q (β = .379, p < .01).  Adding the interaction 
terms of the event variables with logAdx to the regression specifications generates strong support for 
H2b. Specifically, the results presented in Column 4 indicate that the average effect of advertising 
spending on firm value in the year of and year subsequent to the restatement announcement is positive 
but insignificant. As such, the expectation that advertising will not reduce the negative effect of 
financial reporting fraud on firm value is supported. 

In sum, it is observed that advertising spending produces no significant counter effect to the 
restatement announcements impact on losses to firm value. Given that, on average, advertising's effect 
on firm value is positive and significant, the insignificant impact of advertising around restatement 
announcements is likely attributed to the reduction in advertising expenditures in the year of the 
restatement announcement. Additionally, from the perspective of the manager and in the context of 
misreporting announcements, the effectiveness of advertising expenditures is evaluated by the 
reduction in investor visibility. As such, the positive yet insignificant impact of advertising around 
restatement announcements may suggest that reducing advertising effectively reduces firm visibility 
among investors—thereby mitigating (though not repairing) the potential damages incurred to firm 
value as a result of financial reporting fraud. Considering the findings of Chen et al. (2009), indicating 
that increased investor awareness of brand scandal events significantly diminishes firm value, actively 
reducing advertising around such events can be an effective strategy in the context of financial 
reporting fraud announcements. 

 
Table 5 - Advertising Effect on Firm Value around Restatement 

 
 
 
 

This table shows pooled OLS regression results for the effect of advertising expenditures on firm value. All models include 
industry dummies (based on the Fama-French 12 industry classification) and year dummies, whose coefficient estimates 
are not reported. T-statistics, shown in parentheses, are based on standard errors clustered at the firm level. ***, **, and * 
denote significance at 1%, 5%, and 10% respectively. 

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

preEventt -0.190 -0.285* -0.210 -0.146 
 (0.200) (0.149) (0.143) (0.227) 
Eventt -0.527** -0.530*** -0.439** -0.625** 
 (0.219) (0.177) (0.169) (0.259) 
postEventt -0.627*** -0.506*** -0.462*** -0.600** 
 (0.160) (0.166) (0.162) (0.260) 
preEvent*logAdvertisingt    -0.032 
    (0.078) 
Event*logAdvertisingt    0.095 
    (0.092) 
postEvent*logAdvertisingt    0.068 
    (0.078) 
logAdvertisingt   0.379*** 0.370*** 
   (0.086) (0.088) 
logAssetst-1  -0.181*** -0.462*** -0.459*** 
  (0.058) (0.092) (0.092) 
logSales_Growtht-1  0.309*** 0.299*** 0.293*** 
  (0.109) (0.110) (0.109) 
Herfindahl-Hirschman Indext-1  -0.056 -0.197 -0.176 
  (0.677) (0.669) (0.670) 
logPropertyPlantEquipment / 
Employeest-1 

 -0.011 -0.010 -0.010 

  (0.009) (0.008) (0.008) 
Year_dum Yes Yes Yes Yes 
Industry_dum Yes Yes Yes Yes 
_cons 1.868*** 2.533*** 3.398*** 3.412*** 
 (0.571) (0.752) (0.770) (0.776) 

N 2122 1897 1897 1897 
adj. R2 0.124 0.179 0.207 0.207 

 



 

 

15 
 

Conclusions 
 

This study examines whether firms adjust advertising expenditures around accounting-based 
brand scandal events such as financial reporting fraud.  Guided by the crisis management perspectives 
of image repair theory (Benoit, 1995) and the closely aligned, situational crisis communication theory 
(SCCT) (Coombs, 1998; Coombs, 2013), this analysis focuses on two opposing propositions presented 
in the brand scandal and marketing-finance literature regarding organizational response to adverse 
events (i.e. brand scandals). While recent findings from the marketing-finance literature show that 
managers tend to reduce advertising when anticipating the release of negative information, this 
response is contrary to the established support and recommendation from the extant brand scandal 
literature. This inconsistency suggests that firms treat product-based brand scandal events differently 
from accounting-based brand scandal events—suggesting that managers anticipate investors' response 
to advertising around brand scandal to be different from that of a consumer.   

Based on what is known, this study is the first to investigate the relationship between firm-level 
advertising expenditures, accounting-based brand scandal and the subsequent implications for firm 
value. In doing so, this study makes several noteworthy contributions to the advertising, brand scandal, 
and reputation management literature. Firstly, it explicitly attends to the paucity of marketing 
investigations into the implications of non-product market brand scandal events for advertising 
spending strategy and the implications thereof. In doing so, it introduces corporate accounting 
scandals to the studied areas of brand crises and provides empirical support for the value relevance of 
firm-level advertising expenditures. Secondly, this study contributes to the need for linking marketing 
actions to financial outcomes, which is a primary challenge facing today's marketing practitioner and 
is the primary focus of the extant literature on the marketing-finance interface. Furthermore, this study 
contributes to this growing stream of literature by quantifying the returns of firm-level advertising 
investments in financial terms—and in a non-consumer setting. Lastly, this examination also provides 
empirical support for the effectiveness of a marketing response (specifically advertising) and adds it 
to the list of post-restatement reputation building strategies currently addressed in the financial 
misconduct literature 
 
Limitations and Future Research 
 

The findings from this study offer new insight into the marketing-related managerial action taken 
by firms experiencing accounting-based brand scandals and the implications for firm value. 
Nevertheless, the overall scope of the investigation was subject to multiple data-related limitations—
which, if remedied, could provide new and promising directions for future research. One limitation is 
the lack of information about the content of the advertising around restatement announcements. This 
detail is not captured by the Compustat database and, as a result, it is not feasible to examine the 
implications of message related changes (i.e., images, copy, themes, etc.) in the advertising efforts put 
forth by our sample firms during the studied period. In addition, Compustat does not include the 
distribution of firm-level advertising expenditures. This limitation restricts the analysis from testing 
the hypotheses on the basis of the various media types across which advertising budgets are typically 
distributed (i.e., television, radio, online, outdoor, print, etc.). Such an analysis could offer additional 
insight into the differentiated approaches used by firms to communicate with consumers, investors, 
and other stakeholders during the periods around restatement announcements.  

Furthermore, the need for additional investigation into the observed relationship between 
financial misreporting, advertising spending, and firm value remains active. In particular, future 
research efforts may seek to better explain the observed impact of advertising spending for firm value 
and overall performance around restatement announcements by specifically testing for differential 
effects. For example, the results of this study indicate that, on average, the studied sample of 



 

 

16 
 

misreporting firms experience a non-significant increase in firm value in the year of the restatement 
announcement. To determine whether the non-significant increases in firm value can be attributed to 
the strategic reduction in advertising expenditures, an analysis into whether there is a differential effect 
associated with misreporting firms which advertise compared to misreporting firms which do not 
advertise would be a vital direction for future research. Additional insights into the potential sources 
of the observed difference in the advertising spending habits of firms facing accounting-based brand 
crises may also be garnered through the construction of a comparative matched sample of non-
misreporting firms. 

Also, given the observation by Romanus (2019), pre-restatement factors significantly influence 
market reaction to restatement announcements. Future research may also consider the relationship 
between pre-restatement brand equity and firm value around fraudulent restatement announcements. 
With the aim of offering empirical support for the implementation of consumer-focused strategies in 
the wake of fraudulent restatement events—future studies can also evaluate the relationship between 
financial misreporting and consumer purchasing behavior. 

 
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