The Impact of Anti-Bribery Enforcement Actions on Targeted Firms

Jonathan M. Karpoff University of Washington

D. Scott Lee Texas A&M University

Gerald S. Martin American University

First draft: November 11, 2009 This version: February 27, 2012

We thank participants at seminars at Claremont-McKenna College, the University of Utah, the NBER Conference on Finance and Ethics, American University, the Securities and Exchange Commission, and the Oxford Symposium on Corporate Reputation for helpful comments and suggestions on previous versions of this paper, and gratefully acknowledge financial support from the University of Washington’s CFO Forum and Global Business Center, and Texas A&M University’s Private Enterprise Research Center, and a Shell Foundation Development Research Grant.

The Impact of Anti-Bribery Enforcement Actions on Target Firms

Abstract

Firms prosecuted for foreign bribery experience significant costs. Their share values decline by 3.11%, on average, on the first day that news of the bribery enforcement action is reported, and by 8.98% over all announcements related to the enforcement action. Fines, internal investigation costs, and losses associated with financial restatements account for 3.20% of the cumulative loss in share values, suggesting that the remainder, 5.78%, could be attributed to a reputational impact. Closer inspection, however, indicates that most bribery enforcement actions are co-mingled with charges of financial misrepresentation and fraud, and that most of these firms’ costs are due to the financial violations, not the bribery charges per se. Excluding cases in which the bribery charges are accompanied by charges of financial fraud, the mean initial loss in share value drops to -1.60%, and the cumulative loss to -3.55%. Focusing on bribery-related announcements that are not contaminated by contemporaneous charges for financial misrepresentation, the magnitude of the initial loss drops further, to -0.47%, and is statistically insignificant. These results indicate that the financial deterrents to bribery come primarily from the direct costs imposed by regulators, and not from an impact to the firm’s reputation with counterparties.

JEL classification: G38; K22; K42; L51; M41

Keywords: Bribery, FCPA, penalties, financial misrepresentation, fraud

1

The Impact of Anti-Bribery Enforcement Actions on Target Firms

1. Introduction

The Foreign Corrupt Practices Act of 1977 (FCPA) prohibits U.S. companies from

paying bribes to foreign government officials and politicians for the purpose of obtaining

business or to influence regulation. Only in recent years, however, has the FCPA become a

priority for U.S. law enforcement agencies. Of 115 anti-bribery enforcement actions that target

publicly traded companies in the 34 years since the FCPA was enacted, 57.4% have occurred in

the past five years (2007–2011).

The recent surge in bribery enforcement has spawned an intense debate over the costs

that anti-bribery sanctions impose on firms. The U.S. Chamber of Commerce argues that the

direct costs are large: “Businesses enmeshed in a full-blown FCPA investigation conducted by

the U.S. government have and will continue to spend enormous sums on legal fees, forensic

accounting, and other investigative costs before they are even confronted with a fine or penalty,

which … can range into the tens or hundreds of millions.”1 The indirect costs may be even

larger: “Even a single incident [of bribery] can lead to irreparable economic hardship and

reputational damage that may adversely affect the overall stability and competitiveness of any

business.”2 Concern about the costs of bribery enforcement actions motivated attempts to amend

U.S. bribery laws in 2010 and 2011, with new attempts planned for 2012.3

The counterargument is that bribery enforcement actions amount to little more than a slap

on the wrist. Anecdotes suggest that firms suffer small consequences when they are caught

bribing, and that, “[T]he puny size of the penalties could provide an incentive for managers to

1 See www.instituteforlegalreform.com/restoring-balance-proposed-amendments-to-the-foreign-corrupt-practices-act.html, page 5 (accessed on February 27, 2012). 2 See PricewaterhouseCooper, Anti-Corruption, www.pwc.com.br/en/forensics/anti-corruption.jhtml 3 See Weismann and Smith (2010). The Searle Civil Justice Institute (2012) summarizes policy disputes about the FCPA.

2

stretch the rules” (Cass 2009).4 The implication of this argument is that bribery-related penalties

are not too large, but rather, too small. Regulators appear to have accepted this argument. In

2008, the Department of Justice (DOJ) and Securities and Exchange Commission (SEC) worked

in concert to impose a combined $1.657 billion fine and disgorgement of funds in a bribery

enforcement action against Siemens AG. In 2009, the DOJ and SEC imposed combined fines and

disgorgement of $600.2 million on the Halliburton Company for bribery related charges. In

another highly publicized case, a total of 19 firms settled charges for paying $230 million in

bribes to Iraqi officials in the United Nations’ Oil for Food program.5 The FBI and Department

of Justice both emphasize that anti-bribery enforcement has become a top public policy priority,

and DOJ officials have opposed attempts to weaken the FCPA (Breuer 2011). Furthermore, the

whistle-blower provisions of the Dodd-Frank Wall Street Reform and Consumer Protection Act

of 2010 increase many firms’ potential liability for bribery violations. A bill introduced in the

112th Congress in 2012, HR-3513, seeks to provide a private right of action for persons and firms

who are damaged by a foreign business that violates the FCPA, thus further increasing some

firms’ potential liabilities from bribery.

The debate over U.S. anti-bribery enforcement has evolved in the absence of data on the

size and nature of the costs to firms that are targeted by such enforcement. To address this

deficiency, this paper examines all bribery enforcement actions that target publicly traded

companies initiated by the U.S. Department of Justice (DOJ) or Securities Exchange Commission

(SEC) from 1978 through 2011. We document the frequency of such actions, the characteristics

of the target firms, the sizes and locations of the bribes, the value of the benefits sought, and the

costs imposed on target firms. These costs include the fines and penalties imposed by regulators,

the firms’ direct legal and investigation expenses, and any impacts on the firms’ reputations.

4 Cass, Dwight, “Cracks in the SEC’s Crackdown: The Securities Watchdog is Chasing High-Profile Cases, but the Fines It’s Extracting Are Peanuts,” August 12, 2009, http://money.cnn.com/2009/08/12/news/economy/sec_schapiro_fines.fortune/index.htm. 5 See Manipulation of the Oil-For-Food Program by the Iraqi Regime, Independent Inquiry Committee into the United Nations Oil for Food Program (Paul Volcker, Chairman), New York, NY: IIC, 2005.

3

On the surface, the data seem to support the view that bribery enforcement actions

impose meaningful costs on the targeted firms. Total monetary penalties imposed by the SEC

and DOJ, plus settlements from class action and derivative lawsuits, average 0.98% of the target

firm’s market value, and the total costs of internal investigations and legal fees consume an

additional 1.13% of market value, on average. Indirect costs, such as lost reputation, appear to be

even larger. The mean one-day share price reaction to the initial revelation of bribery is -3.11%.

Cumulating over all key announcements about the bribery and the related enforcement action, the

mean loss in share values is 8.98%.

Closer inspection, however, reveals that most of these consequences are not due to the

revelation of bribery or bribery-related enforcement activities per se. Rather, most bribery

enforcement activities are accompanied by charges that the company misreported its financial

statements; a small number also are accompanied by charges of financial fraud. We partition the

data along two dimensions to isolate the incremental impact of the bribery charges and

enforcement actions. The results show that most of these firms’ direct and indirect penalties are

for financial misrepresentation or fraud, not bribery.

First, we partition the sample according to whether the bribery charges are accompanied

by charges of financial fraud. When financial fraud charges are included, the total direct costs

average 3.47% of market capitalization, compared to 1.94% when they are not. More

importantly, indirect costs average 48.11% of market capitalization when fraud charges are

involved, as compared to 1.61% when they are not. In fact, the median estimate of indirect cost is

negative 0.51% for anti-bribery enforcement actions that involve no charges of financial fraud.

Second, we isolate the incremental effects of bribery charges by partitioning each

announcement about the regulatory charges and penalties into disclosures about bribery alone,

financial misrepresentation alone, or a mix of the two. Even firms that do not face charges for

financial fraud typically face charges for financial misrepresentation, if for no other reason than

to cover up the bribe payments. When the initial revelation of bribery-related misconduct

4

discloses both bribery and financial misrepresentation, the one-day abnormal stock return is

-1.85%. When the announcement discloses only financial misrepresentation (that subsequently is

related to bribery activity), the one-day abnormal return is -9.92%. But when the initial

announcement discloses only bribery, with no mention of financial misrepresentation, the one-

day abnormal stock return is -0.47% and is not statistically significant. Cumulating these

partitioned abnormal stock returns for each enforcement action, we find that misrepresentation

announcements are associated with a mean cumulative abnormal return of -5.34%, compared to a

mean of -0.60% for bribery-only announcements and -0.75% for the mixed bribery-and-

misrepresentation announcements.

These results indicate that, while the direct and indirect costs associated with bribery

enforcement actions are significant, most of these costs are attributable to financial misconduct,

not bribery. Most notably, when the bribery is accompanied by charges of financial fraud, the

direct and indirect penalties are large. This, in turn, implies that firms face large penalties for

misleading investors, not for bribery per se.

This paper proceeds as follows. Section 2 provides a brief history and description of the

Foreign Corrupt Practices Act of 1977 and related research. Section 3 describes the data used in

our analysis. Section 4 reports descriptive statistics on the characteristics of firms that are

targeted for bribery enforcement, the location and sizes of the bribes paid, and the benefits sought

by the bribing firms. Section 5 reports on the share value effects of announcements that reveal

the initiation of enforcement activities and the subsequent penalties imposed on targeted firms.

Section 6 reports on the direct costs incurred by targeted firms, including fines, penalties, lawsuit

settlements, investigation expenses, and legal expenses. Section 7 examines the indirect costs,

including the effects of financial restatements and the reputational costs borne by the targeted

firms. Section 8 concludes with a discussion of the implications of these findings.

5

2. The Foreign Corrupt Practices Act of 1977

In 1975, the International Chamber of Commerce (ICC) established the Shawcross

committee to recommend steps to combat corporate extortion and bribery. The following year,

the former Prime Minister of Japan was charged with and subsequently imprisoned for taking $2

million in bribes for assisting Lockheed Corporation in selling 21 jets to a Japanese airline.

Subsequent revelations indicated that many U.S. firms were bribing foreign officials to obtain

business and misrepresenting their financial statements to avoid detection by auditors and

investors. Contemporaneously, congressional investigations into the Watergate scandal revealed

that many corporations maintained slush funds to court favor from both domestic and foreign

government officials. In response, the SEC proposed an amnesty period to encourage firms to

conduct independent internal investigations and voluntarily disclose questionable payments.

More than 500 firms, including 100 firms in the Fortune 500, subsequently disclosed illicit

payments that exceeded $300 million.

Subsequently, Congress passed the Foreign Corrupt Practices Act of 1977 (FCPA). As

amended by the Act, 15 U.S.C. §§ 78dd (30A in the Securities Exchange Act of 1934) prohibits

any issuer, domestic concern, or other persons from obtaining anything of value by corruptly

making payments. Before 1977, federal powers to prosecute foreign bribery relied primarily on

anti-fraud and money laundering provisions of the Currency and Foreign Transactions Reporting

Act and the Travel Act. Enforcing these statutes proved difficult because they required proof of

intent (scienter), racketeering, or failure to report foreign currency transactions. With the FCPA,

the SEC and DOJ now could impose civil and criminal penalties for bribery in and of itself.

Pre-FCPA investigations revealed that many firms maintained secret accounts to facilitate

their bribe payments. To aid in the prosecution of its anti-bribery rules, the FCPA also added

three financial reporting provisions: (i) 15 U.S.C. §§ 78m(b)(2)(A), which requires firms to keep

and maintain books and records that accurately reflect all transactions; (ii) 15 U.S.C. §§

78m(b)(2)(B), which requires firms to devise and maintain a system of internal accounting

6

controls; and (iii) 15 U.S.C. §§ 78m(b)(5), in which no person shall knowingly circumvent or

knowingly fail to implement a system of internal accounting controls or knowingly falsify any

book, record, or account.6 As reported below, most enforcement actions for bribery also invoke

charges of financial misrepresentation. Our tests exploit this fact to isolate the impact of bribery

charges on the targeted firms.

The FCPA is the topic of extensive discussion in the legal literature (e.g., see Cohan,

Holland and Wolf, 2008; Davis, 2002; Dugan and Lechtman, 1997; Erbstoesser, Struck and

Chesley, 2007; Huskins, 2007; and Timmeny, 1982). Researchers also have examined the

general influence of corruption and trust on economic performance (e.g., see Shleifer and Vishny

1993, 1994; Guiso, Sapienza, and Zingales 2009) and whether bribery is inherently wrong

(Green, 2005). But there is very little empirical research on the FCPA and the effects of anti-

bribery enforcement activity. Hines (1995) reports that the FCPA decreased U.S. firms’

operations in foreign countries, although Graham (1984) reports no effect on U.S. firms’ market

shares. Cheung, Rau and Stouraitis (2011) examine the characteristics of bribes and bribe-payers

using a sample that includes 41 U.S. firms. They find that prior to paying bribes, firms tend to be

poor performers compared to their peers that do not pay bribes. Smith, Stettler, and Beedles

(1984) examine share price reactions to announcements by 98 firms that voluntarily reported

payments to foreign government officials during the SEC’s pre-FCPA amnesty program that

ended in 1978. The mean share price reaction is negative, and Smith et al. conjecture that this

reflects investors’ expectations of future government sanctions or the loss of future business.

This conjecture anticipates the current policy debate over the sizes of the direct and indirect

penalties for firms that are targeted in FCPA-related anti-bribery enforcement actions.

6 Two additional rules were added by the SEC to the Code of Federal Regulations to aid in enforcement of these provisions for entities that have a security registered pursuant to Section 12 of the Securities Act: 13b2-1 (17 CFR 240 13b2-1) and 13b2-2 (17 CFR 240 13b2-2). Maher (1981) and Shearing and Sterling (2012) provide detailed descriptions of the 1977 law that introduced these provisions.

7

3. Data

Our sample consists of all enforcement actions initiated by the SEC and DOJ from

January 1, 1978 through December 31, 2011 for foreign bribery under the Foreign Corrupt

Practices Act of 1977. Most (95%) of the enforcement actions in our sample incorporate other

charges, including aiding and abetting, conspiracy, civil and criminal fraud, racketeering, and tax

evasion. We document all such charges, and also track all related class action and derivative

lawsuits associated with each enforcement action. Table A-1 in the Appendix reports these data

in detail.

To identify the enforcement actions, we searched for specific references to the bribery

provisions of the FCPA (e.g. sections 78dd-1 through 78dd-3 and 30A) using the Lexis-Nexis

FEDSEC:SECREL library and the PACER database.7 To assure that we did not miss any bribery

enforcement actions that used other provisions of the U.S. code without including bribery charges

explicitly, we also searched for the terms “bribery”, “Foreign Corrupt Practices Act”, and

“FCPA,” and read all resulting SEC and DOJ proceedings to determine if a violation included

illegal payments to foreign officials. Since September 19, 1995, the SEC has posted selected

enforcement releases at www.sec.gov. The Department of Justice provided us additional

enforcement data for the civil and criminal enforcement proceedings for which the DOJ was

involved. Finally, we used EDGAR, PACER, Dow Jones’ Factiva, and Lexis-Nexis’ Legal

Research and General News categories to gather additional information and news releases

pertaining to the enforcement actions, including related class action and derivative lawsuits.

7 The Lexis-Nexis FEDSEC:SECREL library contains public releases from all SEC securities enforcement actions, and the PACER Service Center (pacer.psc.uscourts.gov) contains federal court documents.

8

4. Descriptive statistics on bribery enforcement, bribe payments, and bribe payers

4.1. The time trend of enforcement actions

The DOJ and SEC initiated a total of 175 bribery-related enforcement actions from

January 1978 through December 2011. Of these, 53 target private entities, including individuals,

foreign firms with no securities traded on US exchanges, and one foreign affiliate of a private US

accounting firm.8 Five actions involve publicly traded firms that lack CRSP and Compustat

coverage, and two additional actions involving recidivist firms (Baker Hughes, Inc. and ABB

Ltd) were excluded to avoid having each firm’s second violation period overlapping the

enforcement period for its first offense. The remaining 115 enforcement actions involve bribery

by agents working for publicly traded companies, and constitute the sample used in this study.

Figure 1 shows the chronological distribution of these enforcement actions. From 1978 through

2006, the median number of actions per year is one. Enforcement activity increased sharply in

2007, peaking with 19 actions initiated in 2010. Of the 82 actions initiated since 2004, 19 involve

the United Nations’ Oil-for-Food bribery scandal in Iraq.

4.2. Characteristics of bribing firms

Table 1 partitions the 115 sample firms across industries and firm size deciles. We use

SIC codes to group firms according to the industry definitions used by Transparency International

(TI), and list the industries in declining order of TI’s Sector Score. The Sector Score is an index

that reflects survey respondents’ view of the frequency with which firms in the industry pay

bribes. It is scaled from 0 to 10, with lower numbers associated with industries where bribe

paying is common practice. According to the Sector Score, perceived bribery is least common in

the Agriculture industry and most common in Public works contracts and construction.

8 The 53 actions include the highly publicized action against U.S. Representative William J. Jefferson (D-LA). Jefferson was convicted of using his office to solicit bribes to promote telecommunications deals in Nigeria, Ghana and elsewhere; oil concessions in Equatorial Guinea; satellite transmission contracts in Botswana, Equatorial Guinea and the Republic of Congo; and development of different plants and facilities in Nigeria.

9

The industries with the most frequent bribery enforcement actions are Heavy

Manufacturing (46 actions), Oil and Gas (19), and Pharmaceutical and Healthcare (13). As

shown in the table, however, this frequent incidence reflects the large number of publicly traded

firms in these industries. TI’s Heavy Manufacturing industry accounts for 40.0% of the 115

bribery-related enforcement actions, but this industry includes 16.9% of all CRSP-listed firms.

As a fraction of the number of firms in the industry, the industry with the highest number of

bribery-related enforcement actions is Arms, Defense, and Military (27.6% of firms). Although

TI’s Sector Score ranks Agriculture as the industry whose firms are least likely to bribe, a total of

14.8% of firms in this industry have been targeted by anti-bribery enforcement actions. Chi-

square tests of proportionate frequencies reject the hypotheses that the sample is distributed

equally across industries, either in terms of total actions or the fraction of firms in the industry

targeted for enforcement (p < 0.001 in both tests).

Table 1 describes two additional characteristics of the firms targeted for bribery

enforcement actions. First, targeted firms tend to have high equity value. More than half (59) of

the targeted firms reside in the largest decile of CRSP-listed firms, and none are in the smallest

three deciles. A Chi-square test of proportionate frequencies rejects the hypothesis that the

sample is distributed equally across size deciles (p < 0.001). Second, there is no significant

relation between the incidence of bribery enforcement actions and TI’s Sector Score. Indeed, the

correlation is positive 0.059, indicating a slight (statistically insignificant) tendency for bribery

actions to target firms in industries that should experience relatively little bribery, according to

TI’s ranking. This suggests either that the respondents to TI’s Sector Score are misinformed or

that targets of bribery enforcements are selected for reasons other than the industry-based

frequency of bribes.

Table 2 reports on the home countries of the bribing firms. The FCPA is a U.S. law, but

the enforcement agencies have jurisdiction over all firms that issue securities or have business

operations in the United States. So, although most (87) of the targeted companies are

10

incorporated in the United States, the sample includes 21 foreign firms with ADRs traded in U.S.

markets, and seven foreign firms with equity listed on U.S. exchanges. Most of the foreign firms

(82%) have been targeted for enforcement action since 2005.

Table 2 also reports TI’s Bribe Payers Index (BPI) for each country that was home to a

firm charged with bribery. The BPI is based on a survey of business executives, and ranks 28

countries with the world’s largest economies by the likelihood that companies from these

countries will pay bribes in other countries. A low BPI indicates a country where bribe paying is

commonplace (Russia has the lowest BPI of 6.1). A high BPI indicates countries whose

companies are less likely to pay bribes. (The Netherlands, Sweden and Switzerland share the

highest BPI of 8.8. The BPI for the United States is 8.3.) Although the largest FCPA-related fine

was imposed on a German company (Siemens), the BPI for Germany is relatively high (8.6).9

Table 3 reports two logistic regressions that examine the characteristics of bribing firms.

The data consist of a yearly panel from 1978 through 2011 using data on all Compustat-listed

firms. In Model 1, the (untransformed) dependent variable equals one for a firm targeted for a

bribery violation in the year the enforcement action was initiated. In Model 2, the dependent

variable equals one for the targeted firm in every year that the firm was accused of paying bribes.

So, Model 1 measures the characteristics of firms accused of bribery in the year they are accused,

whereas Model 2 measures the characteristics of these same firms during the years in which they

engaged in bribery. The right-hand side variables measure each firm’s size, profitability,

leverage, asset characteristics, and reliance on foreign sales. We also include dummy variables

for the firm’s industry, year, and the presence of a top quality auditor. The results in Table 3

indicate that the probability that a bribe will be revealed (Model 1), or is ongoing (Model 2), is

9 Seven firms accused of bribery are domiciled in countries not represented in TI’s BPI. For these we employ BPI scores from countries we judged as regionally and culturally similar to the missing country as BPI proxies. We use Sweden’s BPI for Norway. For Panama and Bermuda, we average the BPIs of the United States, Brazil, Argentina and Mexico. For Denmark, we average the BPIs of Germany, Netherlands and Sweden. For Hungary, we averaged the BPIs of Germany, Italy and Russia, and for Luxembourg, we averaged the BPIs of Belgium, France and Germany. These are undeniably arbitrary judgments, but they only affect seven (6.1%) of the 115 sample observations.

11

positively related to firm size, leverage, and the fraction of sales made in foreign countries. Both

probabilities are negatively related to the firm’s market to book ratio, and the probability that a

bribe is revealed is negatively related to the firm’s current ratio. Overall, the data indicate that

the firms apprehended for foreign bribery tend to be large manufacturing firms that rely heavily

on sales in foreign countries, are heavily leveraged, have low cash holdings, and have low market

to book ratios. Examples of such companies, which appear in our sample, include Lucent

Technologies Inc., Ingersoll-Rand Co., Ltd., Textron Inc., and The Dow Chemical Co.10

4.3. Where do bribes occur?

Table 4 reports on the countries where bribes were paid. The country with the most

bribery enforcement actions is Iraq (24 times), followed by Nigeria (23), China (21), Indonesia

(13), and Saudi Arabia (10). The total across countries exceeds the total enforcement actions

(115) because many actions involve charges of bribery in more than one country. As an example,

Dimon, Inc. (now known as Alliance One International, Inc.) paid more than $3 million in bribes

to Kyrgyzstan government officials to purchase Kyrgyz tobacco for resale to Dimon's customers,

and also paid bribes of more than $1.2 million to government officials of the Thailand Tobacco

Monopoly to obtain more than $18.3 million in sales contracts.11

Table 4 also reports three measures of the tendency for bribes to occur in a country. The

first is Transparency International’s 2010 Corruption Perceptions Index (CPI) and its

corresponding rank for each country. For example, Nigeria’s CPI of 2.4 ranks it 143th in

perceived corruption. At the opposite end of the CPI spectrum, Singapore’s CPI of 9.2 ranks it as 10 Consistent with Model 2, Cheung, Rau and Stouraitis (2011) also find that firms engaged in bribery tend to be larger and more levered than their peers. Unlike our results, however, Cheung et al. find that firms engaged in bribery have relatively high market to book ratios. This difference may reflect sample differences. For example, our sample consists mostly of firms domiciled firms in the U.S. (75.7%), whereas the Cheung, et al. (2011) sample includes only 38.3% U.S. domiciled firms. 11 Cheung, et. al. (2011) differ somewhat on this dimension also. In their sample, Japanese entities receive over a quarter (27) of the bribes in their sample, whereas our sample includes only one bribe recipient in Japan. Our sample’s leading country for briberies (24 actions) is Iraq, which appears only once in the sample of Cheung, et. al. (2011). On the other hand, Nigeria, China and Indonesia appear frequently in both samples.

12

the least corrupt country where bribes occurred (according to the business executives and analysts

surveyed by TI). The second measure reported in Table 4 is TI’s Global Corruption Barometer

(GCB), which is based on surveys of the general public, and the third is the United Nations’

Human Development Index (HDI). Both the GCB and HDI are scaled from 0 to 1. A value of 1

on the GCB scale indicates the worst (perceived) corruption. A value of 1 on the HDI indicates

the highest level of development based on three dimensions: life expectancy, adult literacy, and

standard of living.

Table 4 shows that bribe payments associated with FCPA-related enforcement actions

tend to occur in countries with a reputation for corruption and poor development. The mean CPI

for all countries named in bribery enforcement actions is 3.6, which corresponds to the bottom

tercile (i.e., most corrupt) of countries when ranked by their CPI measures. The mean GCB for

countries named in bribery enforcement actions is 0.340, which corresponds to the top tercile

(most corrupt) of countries when ranked by their GCB measures. The mean HDI is 0.667, which

corresponds to the bottom tercile (least developed) of countries ranked by the HDI.

4.4. Amounts paid and benefits received

One of the necessary requirements for a payment to be considered a bribe is that it must

be paid with the purpose of receiving something of value. Table 5, Panel A, indicates that bribe-

paying firms intended to stimulate sales in 95 (82.6%) of the 115 actions, to secure political or

regulatory favors in 23 (20.0%) actions, and to reduce taxes in five (4.2%) actions. Because eight

firms had multiple purposes for their bribes, the sum of these percentages exceeds 100%. In the

Dimon, Inc. case cited above, for example, the firm made improper payments to Kyrgyzstan

government officials both to procure tobacco and also to decrease its tax liability. An example of

pure tax avoidance occurred in 2001, when Baker Hughes paid an Indonesian official $75,000 for

the purpose of reducing a $3.2 million tax assessment against PT Eastman Christiensen, an

Indonesian corporation controlled by Baker Hughes.

13

Panel B of Table 5 reports on the bribe payment amounts, the amount of business the

bribes were intended to garner for the firm, and the net gains that the bribing firm expected to

receive. The data come from narratives in the SEC and DOJ enforcement releases. The mean

bribe stretched over 5.09 years (median of 4.0 years) and paid $26.85 million (median of $1.0

million). At the extreme, Siemens AG paid $1.79 billion in bribes in ten countries over a 24.75-

year period, and Montedison SpA and Halliburton each paid bribes exceeding $100 million.

Panel B also provides information about the sales that most bribes were intended to

garner, and the net benefits to the bribing firms. Our information comes from the SEC and DOJ,

which must calculate the bribe-related gains to determine the firms’ penalties.12 Buckberg and

Dunbar (2008) state that the SEC and DOJ calculations emerge from a process that begins with

the SEC or DOJ providing a “reasonable approximation” of the defendant’s illegal sales and

profit, at which time the burden of rebuttal falls on the defendant to demonstrate whether the

SEC’s calculation exceeds sales and profits that are related to the misconduct. The process for

determining the bribe-related benefits has stimulated considerable legal debate, but they provide

the most objective estimate of expected benefits available. It is noteworthy that since the early

1990s, the SEC and courts have relied on event studies and other methods familiar to financial

economists to estimate the pecuniary gains and amounts to be disgorged (Mitchell and Netter,

1994).

For 97 of the 115 enforcement actions in our sample, information about the firm’s net

gains is available from SEC and/or DOJ releases. (In 54 actions, the information comes from the

disgorgement paid by the firm, and in 42 actions, the net gain is reported verbatim.) In 17

additional actions, SEC and/or DOJ releases report on the incremental sales the firm earned, or

expected to earn, from the bribe. And in one action involving American Totalisator Co., the

12The penalties include fines and disgorgement plus pre-judgment interest of ill-gotten gains. The calculation of the bribe-related benefits are guided by the U.S. Federal Sentencing Guidelines, which state that, “‘Pecuniary gain’ … means the additional before-tax profit to the defendant resulting from the relevant conduct of the offense. Gain can result from either additional revenue or cost savings” (See www.ussc.gov/Guidelines/2011_Guidelines/Manual_HTML/Chapter_8.htm, accessed February 27, 2012.)

14

value of the ill-gotten contract was collected from a newswire announcement issued when the

contract was awarded. For these 18 actions in which we do not have SEC or DOJ calculations of

the size of the net benefit, we estimate the net benefit by multiplying each firm’s bribery-related

sales by its profit margin (from Compustat) during the years the bribery payments were made.

For the 95 briberies intended to garner sales, the expected sales increase averaged

$1,017.93 million (median = $36.56 million). On average, the ratio of the bribe to the sales

influenced is 5.71% (median is 3.30%). Expressed differently, the average bribing firm paid

$5.71 to generate $100 of additional expected revenue, or $3.30 if we focus on the median. In the

extreme, one bribing firm paid $40 to generate $100 of additional expected revenue.

On average, the fraction of the mean expected bribe-generated sales to the firm’s total

sales across the entire violation period is 4.97% (median = 0.36%). (In the extreme, one firm

expected to generate two dollars of additional sales for every dollar of current sales.) These

numbers indicate that typical bribe payments affected a small, but meaningful fraction of these

firms’ business activities.

The mean expected pecuniary gain (sales net of expenses including the bribe) is $30.66

million, and the median is $2.56 million. The bottom row of Panel B reports a mean ratio of the

expected pecuniary gain to the bribe of 1.35. Thus, for every $1 expended on bribes, the mean

expected before-tax benefit was $1.35 and the median was $2.46. At one extreme, ERHC

Energy, Inc. paid a bribe of $100,000 to obtain sales from 2004 – 2007 that were expected to

generate $20.48 million in profits, a benefit-to-bribe ratio of 204.80. At the other extreme, in

1993 Litton Industries paid a $16.3 million bribe to obtain a $197 million contract that the

Department of Justice estimated generated a profit of $2.1 million, a benefit-to-bribe ratio of only

0.13.

These estimates imply that bribe recipients tend to extract a large fraction of the gains

that the bribes are intended to garner. Indeed, the Litton Industries example seems perverse, as it

is not clear why a firm would pay more in bribes than the affected business is worth. We

15

conjecture that these estimates are affected by measurement error and/or agency problems in the

bribe paying firms. Measurement errors can arise if SEC and DOJ officials generate conservative

estimates of net gain to avoid costly fights over the penalties to be imposed upon the target firm.

Agency problems can arise if the firm’s managers extract some of the gain from the bribe-related

business activity. In some cases, for example, the bribe-paying manager and bribe-receiving

government official might both benefit at the expense of the bribe-paying firm’s shareholders.13

5. The impacts of bribery enforcement activity on share values

5.1. Initial revelation of misconduct

We are interested in measuring the extent to which bribery enforcement actions impose

costs on the targeted firms, and the nature of those costs. As a first step, we measure the share

value effects that occur when investors learn that a firm is the subject of an enforcement action

for foreign bribery. Abnormal returns are calculated by subtracting the CRSP value-weighted

index of all stocks from the raw return of the firm’s equity. Parametric t-statistics for the mean

abnormal returns are calculated from the cross-section standard error of abnormal returns. We

also report median abnormal returns and significance levels using the Mann-Whitney test.

Bribery-related enforcement actions usually involve a complex sequence of news reports,

lawsuits, enforcement activities, and penalties that relate to the targeted firm’s misconduct. The

average action in our sample has 4.99 such announcements that contain new information about

the bribe and the corresponding penalties. That is, in addition to the initial revelation about the

bribe, there is an average of 3.99 additional announcements about the nature of the bribery and

13 Although agency issues can affect managers’ incentives to pay bribes, we do not pursue this line of inquiry in this paper. Rather, we seek to measure the consequences of bribery enforcement activity for firm value. Cheung, Rau and Stouraitis (2011) estimate an average benefit to bribe ratio of between 10.18 and 11.46. Their estimation procedure and sample, however, differs substantially from ours. Cheung, Rau and Stouraitis (2011) use an event study to estimate the benefit to the bribe paying firm, and use a sample drawn from several countries that ends in 2007. We use SEC and DOJ estimates of the benefits to the bribe paying firm, using all enforcement actions initiated by U.S. enforcement agencies through 2011; 44.7% of our sample occurs after 2007.

16

the penalties imposed by the SEC and DOJ. In identifying the additional announcements, we

ignore multiple news stories that convey information that previously was made public in prior

press releases or SEC and DOJ proceedings.

Panel A of Table 6 reports the average one-day market-adjusted return for the initial

revelation of each bribery enforcement action. Averaging over all 115 firms, the mean one-day

abnormal return is -3.11% and the median is -0.26%, with both the t-statistic and Wilcoxon z-

statistic significant at the 1% level. Thus, on average, the initial announcement of misconduct

that involves bribery is associated with a significant decrease in the firm’s share values.

In most actions, the SEC and/or DOJ bring charges for other violations in addition to the

charges of bribery. Appendix Table A-1 reports on the full range of these related charges. The

most important related charges, in terms of their valuation effects, relate to financial misconduct.

In 13 of the 115 enforcement actions, the bribery charges were accompanied by charges of

financial fraud. The mean one-day abnormal return upon the initial revelation of bribery charges

for these 13 firms is -14.91% (median = -3.33%). For the remaining 102 firms, the mean one-day

abnormal return is -1.60% (median = -0.15%). The difference in these average one-day returns is

statistically significant. Hence, the average abnormal return for firms that face contemporaneous

fraud charges is much larger in magnitude than it is for firms that do not face fraud charges. This

indicates that one of the driving forces behind the negative abnormal returns associated with

bribery enforcement actions is the contemporaneous revelation of financial fraud.

A further distinction is that the information reported in the initial announcement of firm

misconduct varies in a systematic way across firms. Almost all bribery actions include charges

for financial misrepresentation, as the bribing firms must manage their financial reports to hide

the bribe payments. In 74 actions, the initial announcement revealing that the firm engaged in

illegal bribery focused only on the bribery; information about financial misrepresentation comes

later. For example, on August 7, 2009, the 10-Q of Watts Water Technologies, Inc. reported that:

17

We have received information regarding possible improper payments to foreign government officials by employees of Watts Valve (Changsha) Co., Ltd., an indirect wholly owned subsidiary of the Company in China. Such payments may violate the Foreign Corrupt Practices Act. We are conducting an investigation utilizing outside counsel and voluntarily disclosed this matter to the United States Department of Justice and the Securities and Exchange Commission. We cannot predict the outcome of this matter at this time or whether it will have a materially adverse impact on our financial condition or results of operations.14

In 28 actions, the initial revelation of the firm’s bribery also contains information about the firm’s

financial misrepresentation. For example, on March 13, 2006, a newswire release reported:

Pride International, Inc. (NYSE: PDE) announced today that it will delay the filing of its 2005 annual report on Form 10-K until after its due date on March 16, 2006. The Company has received allegations relating to improper payments to foreign government officials beginning a number of years ago in connection with certain of its overseas operations, as well as corresponding accounting entries and internal control issues. The Audit Committee of the Board of Directors is overseeing an investigation by outside counsel of such allegations. At this time, the Company does not know whether the allegations will be substantiated, and if so, who may be implicated or what impact the allegations or the investigation may have on the Company, the Company's business or the Company's financial statements.15

In the 13 remaining actions, the initial announcement of misconduct focuses only on the financial

misrepresentation and does not explicitly mention bribery. For example, on February 9, 2006,

UTStarcom’s 8-K stated that:

At the request of the UTStarcom management team, the Audit Committee of the Board of Directors of the Company has initiated an investigation by independent counsel with regard to the circumstances surrounding the premature recognition of revenue on a contract with a customer in India, and other related issues. The Company recognized approximately $22 million in revenue on the contract, with total gross margin of less than one million dollars. This revenue was recognized during several of the quarters from 2003 through 2005. At the conclusion of this investigation, the Audit Committee will assess the findings, and will evaluate the materiality of any adjustments to determine if previously issued financial statements need to be adjusted.16 When we partition the 115 initial announcements according to content (Panel A of Table

6), the market reactions suggest that investors are more concerned about financial

14 www.sec.gov/Archives/edgar/data/795403/000110465909048049/a09-18466_110q.htm (page 34). 15 "Pride International Delays Filing of Form 10-K and Reschedules Earnings Release Date." PR Newswire, Mar 13, 2006. http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/451209920?accountid=7082. 16 “UTStarcom Releases Preliminary Fourth Quarter 2005 Financial Results." PR Newswire, Feb 09, 2006. http://lib-ezproxy.tamu.edu:2048/login?url=http://search.proquest.com/docview/451258273?accountid=7082.

18

misrepresentation than they are about bribery. For the 74 initial announcements that disclose

bribery only (e.g., Watts Water Technologies, Inc.) the median market-adjusted return is -0.74%

(median of -0.03%), and is statistically insignificant. In contrast, the 28 initial announcements

that disclose both bribery and financial misrepresentation (e.g., Pride International, Inc.) result in

an average abnormal return of -2.83% (median of -1.13%), and the 13 initial announcements that

disclose only the financial misrepresentation (e.g., UTStarcom) result in an average abnormal

return of -17.19% (median of -8.48%). The abnormal returns associated with each successive

group are significantly worse than those of the preceding group, consistent with the conjecture

that the shareholder losses associated with these revelations are driven by investor concerns over

financial misrepresentation, and not by concerns over bribery.

Partitioning each of the subgroups of initial announcements into those that were or were

not associated with financial fraud leads to similar inferences about what drives the market losses

associated with bribery revelations. Of the 74 initial announcements that mention bribery only,

71 actions involve no financial fraud. The mean one-day abnormal return for these 71 actions is

-0.47% (median of -0.02%), which is in contrast to a mean abnormal return of -7.01% (median of

-0.55%) for the three remaining fraud-tainted actions. Of the 28 initial announcements with

commingled bribery and misrepresentation revelations, 22 involved no financial fraud and have a

mean one-day abnormal return of -1.85% (median of -0.43%). This is in contrast to the

significantly larger mean abnormal loss of -6.45% (median of -2.91%) for the 6 remaining actions

that involve fraud. Finally, of the 13 initial announcements that mentioned misrepresentation

only, 9 actions involving no fraud have a mean abnormal return of -9.92% (median of -3.43%).

For the 4 actions in this subgroup that had fraud charges, the mean abnormal return is -33.53%

(median of -31.96%).

The results in Panel A of Table 5 indicate that, on average, the initial revelation of

misconduct that leads to enforcement activity for bribery is associated with a significant decrease

in the target firm’s share value. The decrease, however, is concentrated among firms that are

19

prosecuted for financial fraud, and among announcements that contain information about

financial misrepresentation. Initial revelation announcements that are solely about bribery are

associated with statistically insignificant initial share price reactions.

5.2. Subsequent announcements

In addition to the initial announcement of misconduct, subsequent announcements reveal

important information about the nature of the bribery, the financial misrepresentation and/or fraud

in which the firm engaged to cover up the bribery, and the penalties imposed on the targeted firm.

In total, there are 459 such subsequent announcements related to the 115 bribery enforcement

actions, an average of 3.99 per action. Panel B of Table 5 summarizes the effects of these

announcements on share values.

Averaging over all 459 subsequent announcements, the mean one-day abnormal return is

-1.47%, with a median of -0.55%. Thus, the subsequent announcements contain important

information that, on average, is associated with decreases in share values. Once again, the size of

the abnormal return depends on the presence of contemporaneous fraud charges and the specific

content of the announcement. For the 309 follow-up announcements associated with the 102

actions that did not involve financial fraud, the mean one-day abnormal return is -0.64% (median

of -0.32%), compared to -3.18% (median of -1.12%) for 150 follow-up announcements associated

with the 13 actions that involve financial fraud.

Among 309 follow-up announcements for 102 actions that involve no fraud charges, 125

announcements mention only bribery and 19 announcements mention only financial misconduct.

The mean one-day abnormal return for news of bribery alone is -0.46% (median of -0.23%), as

compared to a significantly larger mean of -3.50% (median of -1.30%) for news about financial

misrepresentation. A similar pattern exists for subsequent announcements for actions involving

financial fraud. Here, 19 announcements mention only bribery and have a mean abnormal return

of -1.02% (median -0.43%); 106 announcements contain information about financial misconduct,

20

and have a mean abnormal return of -4.21% (median of -1.51%). These results indicate that both

initial and follow-up announcements about firms violating the anti-bribery law lead to decreases

in share values. However, most of the losses in share value occur in response to announcements

about the firm’s financial misrepresentation and/or fraud, not to revelations of bribery.

5.3. Cumulative abnormal returns

Panel C reports on the abnormal returns cumulated over all informational events available

for each action in the sample. The cumulative abnormal return for firm j is

CAR(k)j is the sum of the one-day abnormal returns, ARe(k),j, summed over the n(k)j unique events

that convey information about firm j’s bribery and the related penalties. The identifier k refers to

the type of information conveyed in the announcement. When k = all announcements, we sum

over all initial and subsequent announcements; as reported above, the mean value of n(k = all

announcements)j is 4.99. We also sum over only announcements that contain information about

bribery (k = bribery only), information about bribery and financial misrepresentation (k = mixed),

and information only about misrepresentation (k = misrepresentation only).

For the full sample of 115 firms, the mean cumulative abnormal return is -8.98% (median

of -1.49%). Consistent with the evidence presented in Panels A and B, the magnitude of the loss

is significantly larger for enforcement actions that involve financial fraud. For 13 actions with

contemporaneous fraud charges, the mean cumulative abnormal return is -51.58% (median =

-22.22%). For the 102 actions without fraud charges, the mean cumulative abnormal return is

-3.55% (median = -1.15%).

Among the 115 actions in the sample, 90 have at least one announcement that contains

information only about the firm’s bribery. For each of these 90 actions, we calculate

CAR( k )j= A R

e( k ), je( k )=1

n( k )j

!

21

CAR(k=bribery only)j and find that the mean value of CAR(k=bribery only)j is -1.46% (median of

-0.52%). In 103 actions, there is at least one announcement that contains co-mingled information

about bribery and financial misrepresentation. The mean value of CAR(k=mixed)j is -1.60%

(median of -0.55%). In 21 actions, there are announcements related to the bribery enforcement

action, but which contain specific information only about the contemporaneous financial

misrepresentation. The mean value of CAR(k=misrepresentation only)j is -35.07% (median of

-8.48%). Similarly significant differences persist when we segregate enforcement actions into

those with and without fraud charges and compare announcements pertaining only to bribery with

announcements pertaining only to financial misrepresentation.

These results indicate that, on average, information that a firm is targeted for a bribery-

related enforcement action triggers a significant reduction in share value. The losses, however,

are more closely related to charges of financial misconduct than to bribery. The losses are

greatest when the bribery violation is contemporaneous with financial fraud charges. Even

among firms that do not face fraud charges, the largest share price losses are associated with

revelations that these firms covered up the bribes by misrepresenting their financial numbers, not

with the bribery per se. Among the subsample of announcements that explicitly mention bribery

violations, the average share price reaction is negative. But even here, the share price losses are

small in magnitude and statistically significant only at the 10% level.

6. Direct costs imposed by bribery enforcement actions

The results in Table 6 indicate that firms facing bribery enforcement actions lose share

value, on average, although most of the losses are associated with charges of financial fraud

and/or misrepresentation. In this section we investigate the extent to which the losses in share

value can be attributed to fines, penalties, investigation, and legal expenses.

22

6.a. Fines and penalties

Table 7 summarizes the monetary fines and penalties imposed on the sample firms by the

SEC and DOJ, and via class action lawsuits. These include fines, criminal penalties, and civil

judgments.17 The mean penalty imposed by regulators is $43.08 million. The mean, however,

reflects several large outliers, including a penalty of $1.657 billion levied against Siemens and

$600.2 million against Halliburton/KBR, both of which had bribery programs that extended over

many years. The median penalty is $3.78 million.

Class action lawsuits were filed in conjunction with 16 of the 115 enforcement actions,

resulting in settlements that total $3,341.87 million.18 Most of this, however, reflects a large

private settlement of $3,053 million by Tyco International, Inc. for a massive financial fraud, with

which bribery charges were only tangentially related. Note that the mean fine imposed by

regulators is higher in the 102 actions that do not involve financial fraud ($46.00 million versus

$20.16 million), whereas the private lawsuit settlements tend to be larger among the 13 actions

that do involve fraud ($7.13 million versus $545.10 million). Summing monetary penalties from

both regulators and private lawsuits, the unconditional mean is $72.14 million (median of $4.33

million). For the 102 bribery but no-fraud actions, the mean monetary penalty is $46.70 million

and the median is $4.74 million. For the 13 fraud-related actions, the mean is much larger,

$271.75 million, but the median is smaller, $0.53 million.

These results indicate that monetary penalties of some type are imposed in most bribery

actions. In some actions the penalties are large. But for the median enforcement action the direct

legal penalty is small. The bottom rows in Table 6 report that the mean monetary penalty is

0.98% of the firm’s market capitalization, and the median is 0.07%. The monetary penalties are

17 As of December 31, 2011, some enforcement actions may still be ongoing and could lead to additional penalties, such that our numbers understate the amount of the penalties that are eventually meted out for these actions. Offsetting this concern is the fact that, in our sample, firms tend to settle quickly. So any lingering charges are likely to be directed at individuals rather than the firms in the sample. 18 The U.S. Supreme Court has ruled there is no private right of action conferred under any of the provisions of the FCPA. Therefore, all related class action lawsuits are brought under other securities laws.

23

larger, on average, when financial fraud charges are included, but the difference is not statistically

significant.19

6.b. Investigation and legal expenses

The U.S. Chamber of Commerce claims that firms that are targeted for anti-bribery

enforcement actions, “… spend enormous sums on legal fees, forensic accounting, and other

investigative costs before they are even confronted with a fine or penalty…” (Weissmann and

Smith, 2010, p. 5). To investigate this claim we collected data on firms’ reported direct expenses

incurred as a result of their bribery investigation. We searched all 10-K, 10-Q and 8-K filings for

the period from the initial revelation of bribery to the resolution of the enforcement action, and

found self-reported data on these expenses for 33 of our 115 sample firms.

Panel A of Table 8 reports a summary of these direct legal and forensic expenses. The

mean expense is $71.05 million, with a median of $11.00 million. The minimum reported

amount is $500,000, and the maximum, reported by Siemens AG, is $1.2 billion. These self-

reported expenses undoubtedly reflect reporting biases. They may include allocated expenses

that are not directly related to the firm’s bribery-related legal expenses. They may underreport

the costs of managers’ time in dealing with the bribery charges. It also is not clear whether the

subset of firms that report their direct legal expenses have higher or lower expenses compared to

firms that do not report these expenses. Nonetheless, the numbers from these firms provide a

rough estimate of the magnitude of these firms’ legal expenses due to their bribery-related

charges. Among these 33 firms, the mean reported legal expense equals 1.53% of the firm’s

19 In addition to these monetary fines and penalties, the SEC and DOJ frequently impose non-monetary sanctions. A tally of such sanctions is provided in Appendix Table A-2. The SEC imposed administrative and civil sanctions against a total of 91 firms in the sample, including cease and desist orders, permanent injunctions, trading suspensions, registration revocations, and debarments of officers, directors, and attorneys. The DOJ imposed sanctions or obtained criminal convictions in 71 of the enforcement actions. Once again, the actions that include fraud charges result in more severe sanctions, including prison sentences and probation. A total of 68 individuals have received prison sentences, with an average length of 13.3 months.

24

market capitalization, and the median is 1.07%. For one firm – Innospec, Inc. – the ratio of

investigation costs to market capitalization is 13.63%. Removing this outlier, firms incur internal

costs related to its bribery investigation that average 1.15% of the firm’s market capitalization

(median = 1.02% of market capitalization).

Panel B of Table 8 reports the results a simple truncated type I Tobit model of the

determinants of these firms’ investigation costs, using data from these 32 firms. The

investigation cost is negatively related to log(market capitalization) and the length of the violation

period. It is positively related to the fraction of the firm’s sales that are attributable to the bribe

payments, the number of countries involved in the bribery investigation, and the number of

unique charges brought by regulators. Panel C shows that the fitted values of investigation costs

for the 32 reporting firms closely approximate their actual investigation costs.

We use the estimators from the regression in Panel B to predict the investigation costs for

the firms with missing values, and use these fitted values where we do not have direct

observations. As shown in Panel D of Table 8, the mean of the fitted values is 1.13% of market

capitalization, with a median of 0.69%. Whether we use the subset of firms for which we have

direct data, or include estimates from all other firms, the results in Table 8 indicate that, on

average, firms that are targeted for bribery enforcement actions spend in the neighborhood of 1%

of market capitalization on internal investigation and legal expenses.

7. Indirect costs imposed by bribery enforcement actions

7.1. Restatement effect

Table 9 gathers results reported in Tables 6, 7, and 8 to compare of the sources of

shareholder loss associated with bribery enforcement actions. Averaging over all 115 bribery

enforcement actions in the sample, the mean cumulative loss in share value is 8.98%. On

average, firms pay fines and penalties equal to 0.98% of market capitalization, and incur

investigation and legal costs equal to an additional 1.13% of market capitalization. This leaves an

25

average 6.87% loss in share value unaccounted for and suggests that firms pay substantial indirect

costs associated with their bribery enforcement actions, in addition to the direct costs reflected in

fines, penalties, and investigation costs.

One indirect cost is that investors re-value the firm in light of information that the firm’s

financial statements previously were incorrect. The revaluation may reflect investors’ judgment

that share prices previously were inflated by false financial information (see Karpoff, Lee, and

Martin, 2008). In bribery actions that do not involve fraud, the financial statement inaccuracies

typically reflect attempts to conceal bribery payments rather than to inflate assets or deflate

liabilities. Yet, share prices may fall simply because investors learn that the firm’s financial

statements are less transparent than previously thought. Some of the events included in our

measure of the cumulative loss in share values are financial restatements. As a crude estimate of

the restatement effect on share values, we subtract the abnormal loss in share values on such

restatement days. Averaging over all 115 firms, the mean share value loss on restatement

announcements that are associated with the misconduct is 1.09%. The median firm has no

restatement events, so the median restatement effect is zero. Among actions without financial

fraud charges, the mean restatement effect is 0.81% of market capitalization, and among actions

with fraud charges, the mean is 3.29%. This shows that bribery enforcement actions that involve

financial fraud charges are associated with more significant financial restatements.

7.2. Reputation loss

Among the arguments for less intense bribery enforcement is the view that firms that are

charged with foreign bribery suffer large reputational losses in the form of decreased sales and

increased costs.20 Previous research shows that many firms experience reputational losses when

they are discovered to engage in other types of illegal or opportunistic behavior. Indeed, for some

20Ibid fn. 2. See also Smith et al. (1984), Hines (1995), and Weissmann and Smith (2010).

26

types of misconduct, the reputation loss swamps all of the direct costs incurred by the firm, and

represents the most consequential impact on firm value.21

The results summarized in Table 9 provide evidence on the magnitude of the reputational

loss associated with bribery enforcement actions. For all 115 actions in the sample, the mean

cumulative loss in share value is -8.98%. Fines, penalties, investigation, and legal costs, plus the

restatement effect, together explain 3.20% of that loss. Following Jarrell and Peltzman (1985),

Murphy, Shrieves, and Tibbs (2009), and others, we can interpret the difference, 5.78%, as an

estimate of the average reputational loss experienced by firms facing sanctions for foreign

bribery.

These data, however, are influenced by the subsample of actions in which the bribery

enforcement action is mixed with charges for financial fraud. Excluding actions that include

financial fraud yields a sample that more narrowly represents the impacts of bribery enforcement.

For the sample of 102 actions in which there are no financial fraud charges, the mean cumulative

share loss is 3.55%. We can attribute an average of 0.92% of the 3.55% loss to the fines and

penalties paid by these firms, 1.02% to their investigation and legal costs, and an additional

0.81% to the effects of their corresponding financial restatements. This yields an estimate of the

average reputational loss from the bribery component of these enforcement actions equal to

0.80% of market capitalization.

There are, however, two reasons to regard this 0.80% point estimate to be an

overestimate of the reputational loss attributable to bribery. First, it reflects the influence of a

21 In this literature, a reputation loss refers to the present value of the firm’s loss that accrues when counterparties change the terms of trade by which they are willing to do business. For example, firm that sell defective products have lower sales (Karpoff and Lott 1993), and firms that restate earnings have higher borrowing costs (Graham et al. 2008). Reputation losses are important for false advertising (Peltzman 1981), product recalls (Jarrell and Peltzman 1985), air safety disasters (Mitchell and Maloney 1989), environmental violations (Karpoff, Lott and Wehrly, 2005), frauds of private parties (Alexander 1999; Murphy, Shrieves, and Tibbs 2009), investigations of IPO underwriters (Beatty, Bunsis, and Hand 1998), defense procurement fraud (Karpoff, Lee, and Vendrzyk 1999), financial misrepresentation (Karpoff, Lee and Martin, 2008), venture capital (VC) firms that face lawsuits from business partners (Atanasov, Ivanov and Litvak, 2011), VC firms and the post-IPO performance of their portfolio firms (Krishnan, Ivanov, Masulis and Singh (2012), and repurchase completion rates (Adams Bonaime, 2012).

27

skew in the distribution of the cumulative loss in share values. Using medians, the upper bound

estimate of the reputational loss is negative 0.65% of market capitalization, indicating no

reputational loss. Second, it is likely that some of the impacts on share values reflect the impact

of financial misrepresentation, not bribery. That is, many of the announcements used to calculate

the 0.80% point estimate of the reputational loss include information about these firms’ financial

misrepresentation (although not fraud). It is difficult to separate the effects of bribery and

financial misrepresentation in measuring the impact on share values and the direct costs.22

Among the 13 firms whose bribery charges accompany charges of financial fraud, the

estimate of the reputation loss is very large, with a mean of 44.82% of market capitalization

(median of 18.17%). The t-statistic for the difference between these estimates and those for the

no-fraud sample is significant at the 10% level, and the Wilcoxon test statistic is significant at the

5% level. These results indicate that, even if we accept the 0.80% point estimate in the bribery-

only sample as a measure of the average reputation loss for firms targeted by bribery enforcement

action, firms’ reputational loss for engaging in foreign bribery is extremely small compared to the

reputational loss when the firm also faces charges for financial fraud.

7.3. Determinants of the indirect costs from bribery enforcement actions

Table 10 reports on multivariate tests that shed further light on the nature of the indirect

costs incurred by firms that are targeted by bribery enforcement actions. We report ordinary least

squares estimates with robust estimators from cross-section regressions using data on all 115

firms that were targeted in bribery-related enforcement actions from 1978-2011. In Model 1, the

22 As one approach, we could use the information in Panel C of Table 5 on the cumulative loss in share values on just the announcements of bribery -1.11% for the 82 non-fraud actions), or for mixed bribery and accounting announcements (-1.26% for the 91 non-fraud actions). But our data on fines and penalties, and investigation costs, comingle the effects of both bribery and misrepresentation. For example, the investigation costs reflect the costs of examining the internal compliance breakdowns that led to the bribery with the costs of examining the internal financial controls that enabled a cover-up of the bribery. So, we can estimate of the gross cost to the firm from announcements related solely to bribery (e.g., 1.11% of market capitalization), we cannot allocate the fines and penalties, or the investigation costs, that are due to the bribery enforcement activities as opposed to the financial misrepresentation.

28

dependent variable is the size of all indirect costs, defined as the firm’s cumulative abnormal

return, CAR(k=all events)j, minus its fines, penalties, investigation and legal costs measured as a

fraction of market capitalization. In Model 2, the dependent variable is the reputation loss, which

is the indirect cost minus the abnormal return on days during the enforcement period in which the

firm announced a restatement.

We examine three types of potential determinants of firms’ indirect costs: firm

characteristics, bribe characteristics, and enforcement characteristics. Firm characteristics

include: (i) the natural log of the firm’s market capitalization, measured the day before the initial

public revelation of the misconduct; (ii) Transparency International’s Industry Sector Score of

the targeted firm, with higher values representing industries in which bribery is thought to be rare;

and (iii) Transparency International’s Bribe Payers Index, with higher values representing firms

from countries that are considered relatively free of corruption.

Characteristics of the bribe include: (i) the number of countries involved in the bribery

activities; (ii) the violation period, measured as the number of years the bribery violation

persisted; (iii) the sales influenced by the bribes, as a percent of the firm’s total sales; (iv)

Transparency International’s Corruption Perceptions Index of corruption for the country in which

the bribe occurred, with higher values indicating less corruption; (v) Transparency International’s

Global Corruption Barometer, with lower values indicating less corruption (vi) a dummy variable

set equal to one for the 19 actions in our sample that involve bribery in the United Nations’ oil-

for-food scandal in Iraq, and (vi) the United Nation’s Human Development Index for the country

in which the bribery occurred, with lower values indicating less development. If the bribe

charges involve more than one country we compute the average of the corresponding countries’

CPI, GCB, and HDI values.

Characteristics of the enforcement action include: (i) the number of firm and individual

respondents named in all SEC and DOJ releases related to the bribery action; (ii) an indicator

variable set equal to one if the bribery charges are accompanied by charges of financial

29

misrepresentation, (iii) an indicator variable set equal to one if the bribery charges are

accompanied by charges of financial fraud; (iv) an indicator variable set equal to one if the

enforcement action was accompanied by a private class action lawsuit; and (v) the number of

specific violations cited in the enforcement action related to the misconduct, as summarized in

Appendix Table A-1.

The results are reported in Table 10. Indirect costs and the reputation loss both are

positively related to the log of the firm’s market capitalization, indicating that indirect costs tend

to increase with firm size. Total indirect costs are positively related to TI’s Industry Sector Score,

indicating that such costs increase when the bribing firm operates in an industry where bribes are

perceived as relatively rare. The GCB index is the sole bribe characteristic that is significantly

related to indirect costs. The positive relation, significant at the 10% level, suggests that bribes

paid in countries that are perceived to be more corrupt result in larger indirect losses for firms

caught bribing in those countries.

The most significant influence on indirect costs, however, comes from the characteristics

of the enforcement activity. Total indirect costs and the reputation loss both are larger when the

firm faces a class action lawsuit, and when there are more respondents named in the enforcement

agencies’ proceedings. Consistent with the summary statistics in Table 9, indirect costs are

higher when the firm faces a contemporaneous charge for financial fraud. The reputation loss

also is larger when fraud charges are brought, although because of a large standard error, the

estimate has a p-value of .103.

We interpret the results in Table 10 as indicating that, in the cross section of firms, total

indirect costs and reputational losses are relatively insensitive to the characteristics of the bribery.

They are affected more by the nature of the enforcement action. Misconduct that triggers class

action lawsuits, involves many firm employees, and involves financial fraud charges is associated

with relatively large indirect costs and large reputational losses. In separate tests, we find that

each of these variables is positively related to the inclusion of financial misrepresentation

30

charges. That is, the total indirect costs and the reputational loss are relatively high when the firm

faces charges for financial misrepresentation. The specific characteristics of the bribery, in

contrast, are not main drivers of the firm’s indirect costs.

8. Discussion and conclusion

The enforcement of U.S. anti-bribery laws is controversial. Critics argue that

enforcement of the FCPA increases the cost of business for U.S. firms, inefficiently decreases

foreign investment, and represents regulatory overreach by the SEC and DOJ. Defenders argue

that aggressive anti-bribery enforcement helps to improve business culture and productivity, not

only for U.S. firms, but also for other firms around the world. At the center of the debate is the

question of how costly anti-bribery enforcement actions are for the firms that are charged with

bribery.

Using data from all 115 publicly traded firms targeted by anti-bribery enforcement

actions from 1978 – 2011, we find that, on the surface, the costs appear to be very large. Direct

costs – including fines, penalties, private lawsuit settlements, investigation expenses, and legal

fees – average 2.11% of market capitalization. The indirect costs are even larger. Using event

study methods, our mean estimate of the indirect costs is 6.87% of market capitalization.

Upon closer inspection, however, most of these costs are due not to these firms’ bribery

charges, but rather, to the charges of financial misrepresentation and fraud that typically

accompany bribery-related enforcement actions. The total direct and indirect costs average

51.58% of market capitalization when the enforcement action includes charges for financial

fraud, compared to 3.55% when there are no such accompanying charges. When we examine the

content of the specific announcements that constitute an enforcement action, most of the share

price losses occur when the announcement contains information about the financial

misrepresentation that accompanies most bribery actions. When the initial announcement about

firm misconduct reports only about bribery, the abnormal loss in share values is small (0.74%)

31

and statistically insignificant. When the initial announcement conveys information that the firm

also misrepresented its financial statements, in contrast, the abnormal loss in share values is ten

times as large (7.4%), and is statistically significant.

These results indicate that firms facing sanctions for violating the FCPA’s anti-bribery

rules face substantial costs. But the costs are mostly due to the financial misrepresentation that

typically accompanies bribery, not the bribery per se. Because of the bundled nature of most

bribery and financial misrepresentation charges and penalties, we cannot allocate how much of

the direct costs are due solely to the bribery charges. We can infer, however, that the total

indirect cost of bribery charges – and particularly the reputation loss component – is small or

negligible, on average.

Previous researchers report that the penalties for some types of misconduct are large,

particularly because they include reputation losses. Examples include false advertising (Peltzman

1981), product recalls (Jarrell and Peltzman 1985; Barber and Darrough, 1996), air safety

disasters (Mitchell and Maloney 1989), frauds of private parties (Karpoff and Lott 1993;

Alexander 1999; Murphy, Shrieves, and Tibbs 2009), investigations of IPO underwriters (Beatty,

Bunsis, and Hand 1998), defense procurement fraud (Karpoff, Lee, and Vendrzyk 1999), and

opportunistic behavior by venture capital firms (Atanasov, Ivanov, and Litvak, 2011). The

penalties are large because a firm’s counterparties – its customers, suppliers, investors, and

employees – change the terms with which they are willing to do business when the firm reveals

that its managers have behaved opportunistically in ways that are costly to counterparties. Other

types of misconduct, however, are associated with small reputational losses. These include

environmental violations (Jones and Rubin 2001; Karpoff, Lott, and Wehrly 2005) and frauds of

unrelated parties (Alexander 1999; Murphy, Shrieves, and Tibbs 2009).

Our findings indicate that, in its impact on firm reputation, bribery is more like an

environmental violation and less like consumer fraud. That is, firms do not suffer large

32

reputational losses when they are caught bribing. When the bribe is accompanied by financial

misrepresentation, in contrast, the reputational loss tends to be large.

This, in turn, implies that, on average, bribery charges do not by themselves “… lead to

irreparable economic hardship and reputational damage that may adversely affect the overall

stability and competitiveness of any business.”23 At times, firms that are targeted by bribery

enforcement actions may experience large direct costs, especially in the form of large regulatory

fines and penalties. On average, however, the bribery charges do not harm the firm’s business

relationships with its customers, suppliers, or investors. That is, the firm’s counterparties tend to

care if the firm’s financial statements are misrepresented. But they do not, in general, alter their

willingness to do business with the firm when it is caught bribing.

23 Ibid, fn. 2.

33

References

Adams Bonaime, A., 2012. Repurchases, Reputation, and Return, Journal of Financial and Quantitative Analysis, forthcoming.

Alexander, C. R., 1999. On the Nature of the Reputational Penalty for Corporate Crime: Evidence. Journal of Law and Economics 42, 489-526.

Atanasov, V. A., Ivanov, V. I. and Litvak, K., 2011. Does Reputation Limit Opportunistic Behavior in the VC Industry? Evidence from Litigation against VCs. Journal of Finance, Forthcoming; Available at SSRN: http://ssrn.com/abstract=1343981.

Barber, B. M. and M. N. Darrough, 1996. Product Reliability and Firm Value: The Experience of Japanese and American Automakers 1973-1992, Journal of Political Economy 104, 1084-1099.

Beatty, R.P., H. Bunsis, and J.R.M. Hand, 1998. The Indirect Economic Penalties in SEC Investigations of Underwriters. Journal of Financial Economics 50, 151-186.

Buckberg, E. and F. C. Dunbar, 2008. Disgorgement: Punitive Demands and Remedial Offers, Business Lawyer 63, 347 – 381.

Cass, D., 2009. Cracks in the SEC’s Crackdown: The Securities Watchdog is Chasing High-Profile Cases, but the Fines It’s Extracting Are Peanuts, http://money.cnn.com/2009/08/12/news/economy/sec_schapiro_fines.fortune/index.htm, (August 12), accessed February 27, 2012.

Cohen, J. M., M. P. Holland and A. P. Wolf, 2008. Under the FCPA, Who is a Foreign Official Anyway? The Business Lawyer 63, 1243-1274.

Cheung, S. Y-L., P. R. Rau and A. Stouraitis, 2011. Which Firms Benefit from Bribes, and by How Much? Evidence from Corruption Cases Worldwide, 24th Australasian Finance and Banking Conference 2011 paper, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1772246.

Davis, K. E., 2002. Self-Interest and Altruism in the Deterrence of Transnational Bribery. American Law and Economics Review 4, 314-340.

Dugan, C. F. and V. Lechtman, 1997. The FCPA in Russia and Other Former Communist Countries, The American Journal of International Law 91, 378-388.

Erbstoesser, E. R., J. H. Struck and J. W. F. Chesley, 2007. The FCPA and Analogous Foreign Anti-bribery Laws – Overview, Recent Developments, and Acquisition Due Diligence, Capital Markets Law Journal 2, 381-403.

Graham, J. L. 1984. The Foreign Corrupt Practices Act: A New Perspective, Journal of International Business Studies 15, 107–121.

Graham, J. R., S. Li, and J. Qiu, 2008. Corporate Misreporting and Bank Loan Contracting. Journal of Financial Economics 89, 44-61.

34

Green, S. P., 2005. What’s Wrong with Bribery? Defining Crimes: Essays on the Criminal Law’s Special Part. Duff & Stuart, Oxford University Press.

Guiso, L., Sapienza, P., and Zingales, L., 2009. Cultural Biases in Economic Exchange? Quarterly Journal of Economics 124, 1095-1131.

Hines, J. R., 1995. Forbidden Payment: Foreign Bribery and American Business After 1977, NBER Working Paper 5266, National Bureau of Economic Research, Inc.

Huskins, P. C., 2007. FCPA Prosecutions, Liability Trend to Watch, Stanford Law Review 60, 1447-1458.

Jarrell, G. and S. Peltzman, 1985. The Impact of Product Recalls on the Wealth of Sellers. Journal of Political Economy 93, 512-536.

Kalb, S. and M. A. Bohn, 2010. An Examination of the SEC’s Application of Disgorgement in FCPA Resolutions, Corporate Compliance Insights, http://www.corporatecomplianceinsights.com/disgorgement-fcpa-how-applied-calculated/.

Karpoff, J. M., D. S. Lee, and G. S. Martin, 2008. The Cost to Firms of Cooking the Books. Journal of Financial and Quantitative Analysis 43, 581-612.

Karpoff, J. M., D. S. Lee, and V. P. Vendrzyk, 1999. Defense Procurement Fraud, Penalties, and Contractor Influence. Journal of Political Economy 107, 809-842.

Karpoff, J. M. and J. R. Lott, Jr., 1993. The Reputational Penalty Firms Bear from Committing Criminal Fraud. Journal of Law and Economics 36, 757-802.

Karpoff, J. M., J. R. Lott, Jr., and E. Wehrly, 2005. The Reputational Penalties for Environmental Violations: Empirical Evidence. Journal of Law and Economics 68, 653-675.

Maher, M.W., 1981. The Impact of Regulation on Controls: Firms’ Response to the Foreign Corrupt Practices Act. The Accounting Review 56, 751-770.

Mitchell, M. L. and M. T. Maloney, 1989. The Role of Market Forces in Promoting Air Travel Safety. Journal of Law and Economics 32, 329-355.

Mitchell, M. L. and J. M. Netter, 1994. The Role of Financial Economics in Securities Fraud Cases: Applications at the Securities and Exchange Commission, Business Law 49, 545-565.

Murphy, D. L., R. E. Shrieves, and S. L.Tibbs, 2009. Determinants of the Stock Price Reaction to Allegations of Corporate Misconduct: Earnings, Risk, and Firm Size Effects. Journal of Financial and Quantitative Analysis 43, 581-612.

Peltzman, S., 1981. The Effects of FTC Advertising Regulation. Journal of Law and Economics 24, 403-448.

Searle Civil Justice Institute, 2012. Policy Report. The Task Force on Foreign Corrupt Practices Act Enforcement, George Mason University School of Law, Law & Economics Center, February 28, 2012.

35

Shearing & Sterling, LLP. 2012. FCPA Digest: Cases and Review Releases Relating to Bribes of Foreign Officials Under the Foreign Corrupt Practices Acct of 1977. Philip Urofsky, editor, Danforth Newcomb: New York. (January 3), 1-696.

Shleifer, A., 2004. Does Competition Destroy Ethical Behavior? American Economic Review 94, 414-418.

Shleifer, A., and R. W. Vishny, 1993. Corruption, Quarterly Journal of Economics 108(3), 599-617.

Shleifer, A., and R. W. Vishny, 1994. Politicians and Firms, Quarterly Journal of Economics 109 (4), 995-1025.

Smith, D. B., H. Stettler and W. Beedles, 1984. An Investigation of the Information Content of Foreign Sensitive Payment Disclosures, Journal of Accounting & Economics 6, 153-162.

Timmeny, Wallace, 1982. An Overview of the FCPA, Syracuse Journal of International Law & Commerce 9, 235-244.

Weissmann, A. and A. Smith, 2010. Restoring Balance: Proposed Amendments to the Foreign Corrupt Practices Act, U.S. Chamber Institute for Legal Reform, Washington D.C., October 27. www.instituteforlegalreform.com/sites/default/files/restoringbalance_fcpa.pdf.

36

Table 1. Distribution of bribery-related enforcement actions by industry sector and firm size

Size-based distribution of the publicly traded firms targeted by all 115 enforcement actions for foreign bribery initiated by the SEC and/or DOJ from 1978-2011 partitioned across Transparency International’s (TI) industry sectors and size-based deciles. TI’s Sector Score is based on survey responses, and measures the perceived likelihood that firms in the industry pay bribes to obtain or retain business in foreign countries. The Sector Score is scaled from 0-10, with higher scores indicating lower perceived likelihood that firms in the industry bribe. For 2011, the average Sector Score is 6.6. Firms in the sector is the number of active firms in Compustat in each TI-defined sector for fiscal year 2010. Equity size deciles reflect CRSP NYSE/AMEX/NASDAQ portfolio assignments. Tests of proportionate frequencies between the sized-based deciles and industry sectors are rejected with Chi-Squares of 170.84 and 158.68 respectively, both with p-values < .001.

Firms in the sector

Bribery actions

Sized-Based Deciles:

Larger Firms Smaller Firms

Sector Sector Score Number

% of all

firms Number

% of all

actions 10 9 8 7 6 5 4 3 – 1 Agriculture 7.1 27 0.4% 4 3.5% 1 2 1 Light manufacturing 7.1 132 2.2% 0 0.0% Civilian aerospace 7.0 25 0.4% 0 0.0% Information technology 7.0 867 14.2% 8 7.0% 4 1 1 1 1 Banking and finance 6.9 1,196 19.5% 2 1.7% 2 Forestry 6.9 9 0.1% 0 0.0% Consumer services 6.8 462 7.5% 0 0.0% Telecommunications 6.7 211 3.4% 5 4.3% 2 1 1 1 Transportation and storage 6.7 181 3.0% 4 3.5% 2 1 1 Fisheries 6.6 0 0.0% 0 0.0% Arms, defense and military 6.6 29 0.5% 8 7.0% 5 1 1 1 Heavy manufacturing 6.5 1,032 16.9% 46 40.0% 27 5 6 3 3 2 Pharmaceutical and healthcare 6.4 706 11.5% 13 11.3% 5 4 1 1 2 Power generation and transmission 6.4 182 3.0% 0 0.0% Mining 6.3 178 2.9% 0 0.0% Oil and gas 6.2 358 5.8% 19 16.5% 11 4 1 1 1 1 Real estate, property, legal & business services 6.1 327 5.3% 1 0.9% 1

Utilities 6.1 54 0.9% 0 0.0% Public works contracts & construction 5.3 146 2.4% 5 4.3% 3 1 1

Total 6,122 100% 115 100% 59 17 11 8 3 9 8 0

37

Table 2. Home country and security type

Home country location and type of security traded in U.S. markets of the publicly traded firms in the 115 enforcement actions for foreign bribery initiated by the SEC and/or DOJ from 1978 through 2011. Each home country is reported with Transparency International’s 2011 Bribe Payers Index (BPI). The BPI ranks 28 of the world’s largest economies according to the perceived likelihood that companies from these countries pay bribes abroad. Higher BPI scores indicate a lower likelihood of using bribery. Panel A - Home country of firms

Country Frequency Percent BPI United States 87 75.65 8.3 Netherlands 5 4.35 8.8 Germany 4 3.48 8.6 Switzerland 4 3.48 8.8 United Kingdom 3 2.61 8.3 France 2 1.74 8.0 Italy 2 1.74 7.6 Panama1 2 1.74 7.6 Bermuda1 1 0.87 7.5 Denmark2 1 0.87 8.7 Hungary3 1 0.87 7.5 Luxembourg4 1 0.87 8.4 Norway5 1 0.87 8.8 Sweden 1 0.87 8.8 115 100.00

Proxies employed: 1. Average of United States, Brazil, Argentina and Mexico. 2. Average of Germany, Netherlands and Sweden. 3. Average of Germany, Italy and Russia. 4. Average of Belgium, France and Germany. 5. Sweden.

Panel B - Type of security traded in U.S. markets

Security Frequency Percent Common stock 94 81.74 ADR 21 18.26 115 100.00

38

Table 3. Characteristics of firms targeted for anti-bribery enforcement action

This table reports coefficient estimates of fixed-effects logistic regressions using data on all Compustat-listed firms from 1978 through 2011. In Model 1, the (untransformed) dependent variable equals one in the year the bribery was publicly revealed. In Model 2, the (untransformed) dependent variable equals one for each year during the violation period, i.e., the years in which the bribes were being paid. Log(Market capitalization) is the natural logarithm of stock market capitalization. Market-to-book is market value of equity plus total assets minus common equity divided by total assets. Current ratio is current assets divided by current liabilities. Total asset turnover is sales divided by total assets. Leverage ratio is long-term debt divided by total assets. Return on assets is net income divided by total assets. Intangibles-to-total assets are intangible assets divided by total assets. % Foreign sales are the firm’s foreign sales divided by total sales. Big 8 auditor flag =1 if the firm’s auditor was one of the Big 8 auditing firms. Market-to-book, current ratio, total asset turnover, leverage ratio, and return on assets are Winsorized at the 1st and 99th percentiles. Industry using 2-digit SIC codes and year dummies are included. p-values, reported below the coefficient estimates, are calculated using robust standard errors clustered by firm. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels.

Model 1: Year

Revealed

Model 2: Violation

Period Log(Market capitalization) 0.4667*** 0.5748*** <.001 <.001

Market-to-book -0.3188* -0.2107** 0.072 0.050

Current ratio -0.1507** -0.022 0.030 0.925

Total asset turnover 0.0862 -0.1359 0.643 0.393

Leverage ratio 0.9725*** 0.9274*** 0.002 0.002

Return on assets 0.3742 0.3551 0.386 0.232

Intangibles-to-total assets 0.1359 0.6700 0.828 0.309

% Foreign sales 1.2682*** 1.6141*** <.001 <.001

Big 8 auditor flag 0.0288 -0.0477 0.944 0.911

Industry dummies Included Included Year dummies Included Included Constant -9.1125 -6.4972 <.001 <.001

N 126,874 178,478 Pseudo R2 0.2053 0.2749 Log likelihood2 -692.45 -2424.47 χ2 644.50 1,640.01 Prob > F <.001 <.001

39

Table 4. Countries where bribes were paid

Frequency of countries in which 354 bribes occurred in all 115 enforcement actions for foreign bribery under the FCPA from 1978 – 2011 that targeted publicly-traded firms. The columns include the 2011 Transparency International Corruption Perception Index (CPI) and the associated country rank; the 2010 Global Corruption Barometer (GCB) (rankings are not published for this index); and the United Nations 2011 Human Development Index (HDI) and the associated country rank. The CPI is measured for 178 countries on a scale of 1 (most corrupt) to 10 (least corrupt) and is based on a survey of country analysts and business people. The GCB ranks countries from 0 (no corruption) to 1 (complete corruption) and is based on surveys of the general public’s views on and experiences of corruption. The HDI ranks countries by the level of human development on a scale from 0 (least developed) to 1 (most developed). Bribes were paid in three countries that are not included in the TI or UN indices, so we assign index values from related countries. Antigua and Turks & Caico each received the UK index values because they were part of the British Commonwealth at the time of the bribe. Cook Islands received New Zealand’s index values and rankings because it is an associated state of New Zealand.

Transparency International

United Nations

Country

No. of bribery actions CPI CPI Rank GCB HDI Rank

Iraq 24 1.8 175 0.559 0.573 132 Nigeria 23 2.4 143 0.628 0.459 156 China 21 3.6 75 0.093 0.687 101 Indonesia 13 3.0 100 0.182 0.617 124 Saudi Arabia 10 4.4 57 0.335 0.770 56 Egypt 9 2.9 112 0.603 0.644 113 India 9 3.1 95 0.542 0.547 134 Mexico 8 3.0 100 0.312 0.770 57 Argentina 7 3.0 100 0.124 0.797 45 Thailand 7 3.4 80 0.227 0.682 103 Greece 6 3.4 80 0.176 0.861 29 Iran 6 2.7 120 0.548 0.707 88 Venezuela 6 1.9 172 0.200 0.735 73 Angola 5 2.0 168 0.540 0.486 148 Brazil 5 3.8 73 0.039 0.718 84 Cote D'Ivoire 5 2.2 154 0.558 0.400 170 Kazakhstan 5 2.7 120 0.548 0.745 68 Russia 5 2.4 143 0.255 0.755 66 Turkey 5 4.2 61 0.326 0.699 92 United Arab Emirates 5 6.8 28 0.335 0.846 30 Bangladesh 4 2.7 120 0.548 0.500 146 Colombia 4 3.4 80 0.235 0.710 87 Ecuador 4 2.7 120 0.190 0.720 83 France 4 7.0 25 0.071 0.884 20 Italy 4 3.9 69 0.128 0.874 24 Malaysia 4 4.3 60 0.091 0.761 61 South Korea 4 5.4 43 0.024 0.897 15 Taiwan 4 6.1 32 0.071 0.687 101 Vietnam 4 2.9 112 0.439 0.593 128 Algeria 3 2.9 112 0.603 0.698 96 Bahrain 3 5.1 46 0.335 0.806 42 Chile 3 7.2 22 0.212 0.805 44 Gabon 3 3.0 100 0.540 0.674 106 Israel 3 5.8 36 0.043 0.888 17 Montenegro 3 4.0 66 0.125 0.771 54 Nicaragua 3 2.5 134 0.183 0.589 129 Niger 3 2.5 134 0.183 0.295 186 Oman 3 4.8 50 0.335 0.705 89 Philippines 3 2.6 129 0.161 0.644 112 Poland 3 5.5 41 0.151 0.813 39 Romania 3 3.6 75 0.282 0.781 50 Uzbekistan 3 1.6 177 0.548 0.641 115 Azerbaijan 2 2.4 143 0.471 0.700 91 Benin 2 3.0 100 0.558 0.427 167 Bolivia 2 2.8 118 0.299 0.663 108 Costa Rica 2 4.8 50 0.315 0.744 69 Czech Republic 2 4.4 57 0.137 0.865 27

40

Table 4. (continued)

Transparency International

United Nations

Country

No. of bribery actions CPI CPI Rank GCB HDI Rank

FYR Macedonia 2 3.9 69 0.215 0.728 78 Germany 2 8.0 14 0.023 0.905 9 Ghana 2 3.9 69 0.373 0.541 135 Hungary 2 4.6 54 0.242 0.816 38 Kuwait 2 4.6 54 0.335 0.760 63 Liberia 2 3.2 91 0.892 0.329 182 Luxembourg 2 8.5 11 0.159 0.867 25 Mali 2 2.8 118 0.558 0.359 175 Netherlands 2 8.9 7 0.024 0.910 3 Pakistan 2 2.5 134 0.494 0.504 145 Panama 2 3.3 86 0.315 0.768 58 Portugal 2 6.1 32 0.032 0.809 41 Qatar 2 7.2 22 0.335 0.831 37 Senegal 2 2.9 112 0.560 0.459 155 Singapore 2 9.2 5 0.088 0.866 26 Spain 2 6.2 31 0.050 0.878 23 Trinidad and Tobago 2 3.2 91 0.252 0.760 62 Uganda 2 2.4 143 0.857 0.446 161 Antigua 1 7.8 16 0.252 0.764 60 Austria 1 7.8 16 0.089 0.885 19 Belarus 1 2.4 143 0.270 0.756 65 Belgium 1 7.5 19 0.064 0.886 18 Bosnia and Herzegovina 1 3.2 91 0.225 0.733 74 Brunei 1 5.2 44 0.256 0.838 33 Bulgaria 1 3.3 86 0.081 0.771 55 Burkina Faso 1 3.0 100 0.558 0.331 181 Canada 1 8.7 10 0.039 0.908 6 Cape Verde 1 5.5 41 0.558 0.568 133 Congo Republic 1 2.2 154 0.540 0.533 137 Croatia 1 4.0 66 0.049 0.796 46 Cyprus 1 6.3 30 0.335 0.840 31 Dominican Republic 1 2.6 129 0.252 0.689 98 Equatorial Guinea 1 1.9 172 0.540 0.537 136 Gambia 1 3.5 77 0.558 0.420 168 Guatemala 1 2.7 120 0.315 0.574 131 Guinea 1 2.1 164 0.558 0.344 178 Guinea-Bissau 1 2.2 154 0.558 0.353 176 Honduras 1 2.6 129 0.315 0.625 121 Japan 1 8.0 14 0.089 0.901 12 Jordan 1 4.5 56 0.335 0.698 95 Kenya 1 2.2 154 0.447 0.509 143 Kyrgyzstan 1 2.1 164 0.548 0.615 126 Latvia 1 4.2 61 0.154 0.805 43 Lebanon 1 2.5 134 0.337 0.739 71 Libya 1 2.0 168 0.603 0.760 64 Malawi 1 3.0 100 0.574 0.400 171 Mauritania 1 2.4 143 0.558 0.453 159 Moldova 1 2.9 112 0.368 0.649 111 Mongolia 1 2.7 120 0.476 0.653 110 Morocco 1 3.4 80 0.603 0.582 130 Mozambique 1 2.7 120 0.574 0.322 184 Myanmar 1 1.5 180 0.256 0.483 149 Norway 1 9.0 6 0.014 0.943 1 Peru 1 3.4 80 0.220 0.725 80 Rwanda 1 5.0 49 0.574 0.429 166 Sao Tome and Principe 1 3.0 100 0.540 0.509 144 Serbia 1 3.3 86 0.174 0.766 59 Sierra Leone 1 2.5 134 0.712 0.336 180 Slovakia 1 4.0 66 0.234 0.834 35 Syria 1 2.6 129 0.335 0.632 119 Togo 1 2.4 143 0.558 0.435 162 Turkmenistan 1 1.6 177 0.548 0.686 102 Turks and Caicos Islands 1 7.8 16 0.252 0.863 28 Ukraine 1 2.3 152 0.339 0.729 76 United Kingdom 1 7.8 16 0.014 0.863 28 Uruguay 1 7.0 25 0.190 0.783 48 Yemen 1 2.1 164 0.335 0.462 154

41

Table 5. Characteristics of the bribe and benefit derived This table reports summary statistics on characteristics of the bribes for all 115 publicly traded firms targeted by anti-bribery enforcement actions from 1978 – 2011. Panel A reports on the intended effects of the bribes. Panel B reports on the sizes and violation periods of the bribes, amount of sales that the bribes sought to influence, and the net benefits obtained. Pecuniary gain is the additional multi-period before-tax profit to the defendant resulting from the bribe using information in the SEC and DOJ filings related to the action. Because early actions inconsistently reported either sales or before-tax profit, each firm’s annual profit margin and tax rate, according to Compustat, were used to derive the benefit metric that was not reported.

Panel A - Purpose for the payments The following table presents the relative frequencies of the purpose for which the bribe was used. The sum of the frequencies (123) exceeds the number of actions (115) because eight bribes had multiple purposes.

Benefit sought

Frequency

Percent of reasons given

Percent of actions

Sales/revenue 95 77.2% 82.6% Political/regulatory 23 18.7% 20.0% Tax reduction 5 4.1% 4.2% Total 123 100.0%

Panel B - Size of the payments and expected benefits derived (N=115)

Description Mean Median Minimum Maximum

Size of bribe 26,849,995 1,000,000 1,250 1,791,700,000

Period of violation (years) 5.09 4.00 0.46 24.75

Sales to be influenced 1,017,932,429 36,558,595 12,495 39,825,000,000

Bribe to sales influenced 5.71% 3.30% 0.02% 40.00%

Total sales during violation 81,371,737,296 13,505,748,000 24,120,000 1,637,799,900,000 Expected bribe-generated sales to total sales 4.97% 0.36% 0.00% 200.00%

Expected pecuniary gain 30,655,964 2,562,868 1,000 1,100,000,000 Expected pecuniary gain to bribe ratio 1.35 2.46 0.13 204.80

42

Table 6. Abnormal returns for FCPA bribe related enforcement announcements

This table reports on the abnormal stock returns for the targeted companies for key dates on which information was publicly revealed about the bribery, related misconduct, and the enforcement activities regarding the misconduct. In each panel, we report means and medians for the sample of all 115 firms, and for subsamples of firms that faced accompanying charges of financial fraud (n=13) and firms that did not face financial fraud charges (n=102). Panel A reports mean and median one-day market-adjusted returns for the initial revelation of the bribery-related misconduct. Panel B reports on the sum of the one-day market-adjusted returns for all subsequent informational events regarding the bribery-related misconduct. These subsequent events include SEC and DOJ enforcement releases, earnings restatements, and private lawsuits. Panel C reports on the sum of the one-day abnormal returns, summing over all relevant information events for each bribery action. In each panel, the events are partitioned according to the specific information contained in the announcement(s): bribery only, mixed bribery and misrepresentation, and misrepresentation only. In Panel C, all events pertaining to a given bribery action and for which the specific information is only about bribery (and not about misrepresentation), are cumulated. Asterisks next to the mean and median represent statistical significance based on a parametric t-test and rank sum test, respectively where ***, **, * indicate significance at the 0.001, 0.01, and 0.10 levels.

Panel A - All initial revelation dates

All bribery

actions Actions without financial fraud

Actions with financial fraud Difference

N 115 102 13 Mean -3.11% *** -1.60% ** -14.91% * 13.31% *

Median -0.26% *** -0.15% * -3.33% ** 3.18% ***

Information in the announcement:

Related to bribery only (a) N 74 71 3

Mean -0.74% -0.47% -7.01% 6.54% Median -0.03% -0.02% -0.55% 0.53%

Mixed bribery and misrepresentation (b)

N 28 22 6 Mean -2.83% ** -1.85% * -6.45% * 4.60% *

Median -1.13% *** -0.43% * -2.91% * 2.48% *

Related to misrepresentation only (c) N 13 9 4

Mean -17.19% * -9.92% * -33.53% 23.61% * Median -8.48% ** -3.43% * -31.96% 28.53%

Differences

(a) – (b) Mean 2.09% * 1.38% -0.56% 1.94% Median 1.10% ** 0.41% * 2.36% -1.95%

(a) – (c) Mean 16.45% * 9.45% 26.52% -17.07% Median 8.45% *** 3.41% * 31.41% -28.00%

(b) – (c) Mean 14.36% * 8.07% 27.08% -19.01% Median 7.67% * 3.00% 29.05% -26.05%

43

Table 6. (con’t)

Panel B - All subsequent announcements

All bribery

actions Actions without financial fraud

Actions with financial fraud Difference

N 459 309 150 Mean -1.47% *** -0.64% *** -3.18% *** 2.54% **

Median -0.55% *** -0.32% *** -1.12% *** 0.80% *** Information in the announcement:

Related to bribery only (a) N 144 125 19

Mean -0.54% ** -0.46% * -1.02% * 0.56% Median -0.25% ** -0.23% * -0.43% * 0.20%

Mixed bribery and misrepresentation (b)

N 190 165 25 Mean -0.45% * -0.45% * -0.43% -0.02%

Median -0.31% * -0.38% * -0.23% -0.15%

Related to misrepresentation only (c) N 125 19 106

Mean -4.10% *** -3.50% * -4.21% *** 0.71% Median -1.50% *** -1.30% ** -1.51% *** 0.21%

Differences

(a) – (b) Mean -0.09% -0.01% -0.59% 0.58% Median 0.06% 0.15% -0.20% 0.35%

(a) – (c) Mean 3.56% *** 3.04% * 3.19% ** -0.15% Median 1.25% *** 1.07% * 1.08% * -0.01%

(b) – (c) Mean 3.65% *** 3.05% * 3.78% ** -0.73% Median 1.19% *** 0.92% * 1.28% ** -0.36%

Panel C - Cumulative abnormal returns

All bribery

actions Actions without financial fraud

Actions with financial fraud Difference

N 115 102 13 Mean -8.98% ** -3.55% ** -51.58% * 48.03% *

Median -1.49% *** -1.15% *** -22.22% *** 21.07% *** Information in the announcement:

Related to bribery only (a) N 90 82 8

Mean -1.46% ** -1.11% * -5.04% * 3.93% Median -0.52% ** -0.44% * -2.94% * 2.50% *

Mixed bribery and misrepresentation (b)

N 103 91 12 Mean -1.60% ** -1.26% * -4.13% * 2.87% *

Median -0.55% * -0.52% * -1.74% * 1.22% *

Related to misrepresentation only (c) N 21 14 7

Mean -35.07% * -11.12% * -82.96% * 71.84% * Median -8.48% *** -3.46% ** -38.77% * 35.31% *

Differences

(a) – (b) Mean 0.14% 0.15% -0.91% 1.06% Median 0.03% 0.08% -1.20% 1.28%

(a) – (c) Mean 33.61% * 10.01% * 77.92% * -67.91% Median 7.96% *** 3.02% ** 35.83% * -32.81%

(b) – (c) Mean 33.47% * 9.86% * 78.83% * -68.97% Median 7.93% *** 2.94% ** 37.03% * -34.09%

44

Table 7. Monetary penalties for bribery violations

Stock market capitalization and monetary penalties imposed through federal sanctions and private civil class action settlements relating to 115 enforcement actions for foreign bribery brought under the Foreign Corrupt Practices Act from 1978-2011. The table presents monetary penalties assessed by regulators on the firm only, related private class and derivative actions, and the total of all monetary penalties against the firm. Penalties may change for 24 (twenty-two bribery and two financial fraud) enforcement actions whose proceedings were ongoing as of December 31, 2011. Asterisks next to the mean and median in the Difference column represent significance of a t-test and rank sum test respectively where ***, **, * indicate significance at the 0.001, 0.01, and 0.10 levels.

($millions)

All bribery actions

(115)

Actions without

financial fraud

charges (102)

Actions with financial

fraud charges

(13) Difference

Market capitalization N 115 102 13 Sum 2,656,432.44 2,448,528.85 207,903.60 Mean 23,099.41 24,005.18 15,992.58 8,012.60 Median 4,544.54 5,203.01 492.42 4,710.59 * Min 7.23 11.00 7.23 Max 386,402.07 386,402.07 87,255.34 Penalties imposed on firms N 115 102 13 Sum 4,953.79 4,691.70 262.09 Mean 43.08 46.00 20.16 25.84 Median 3.78 4.52 0.30 4.22 Min 0.00 0.00 0.00 Max 1,657.00 1,657.00 103.00 Class action/derivative N 16 10 6 settlements Sum 3,341.87 71.25 3,270.62 Mean 208.87 7.13 545.10 -538.00 Median 0.00 0.00 1.19 -1.19 Min 0.00 0.00 0.00 Max 3,053.25 68.75 3,053.25 Total firm monetary N 115 102 13 penalties Sum 8,295.66 4,762.95 3,532.71 Mean 72.14 46.70 271.75 -225.10 Median 4.33 4.74 0.53 4.21 Min 0.00 0.00 0.00 Max 3,109.35 1,657.00 3,109.35 % total penalties to market Mean 0.98% 0.92% 1.47% -0.55% capitalization Median 0.07% 0.06% 0.20% -0.14%

45

Table 8. Estimates of expenses incurred by firms for FCPA violations

Model of investigation expenses incurred by firms for FCPA violations based upon 33 of 115 actions where expenses were reported in periodic reports filed with the SEC or made known to the public through a public release. Panel A presents the statistics for the 33 observed values of investigation expenses. Panel B presents the results of a censored Tobit regression model using the 32 known observations. Panel C presents the statistics for the entire sample of the investigation expenses using the actual values where available and the unconditional expected value for the missing observations.

Panel A - Investigation costs as a percent of market capitalization for 33 firms in sample

N Mean Median Minimum Maximum Market capitalization 33 10,642.23 1,291.28 113.60 79,338.11 Investigation costs 33 71.05 11.00 0.50 1,200.00 % of market capitalization 33 1.53% 1.07% 0.03% 13.63% % of market capitalization1 32 1.15% 1.02% 0.03% 3.98% 1. The observation with largest value is removed as an outlier and influential observation.

Panel B – Truncated regression estimation of investigation cost

Parameter Estimate Prob > |t|

Intercept 0.0577 0.000 Log(market capitalization) -0.0025 0.000 % sales influenced to total sales 0.0421 0.000 Number of countries involved 0.0002 0.246 Violation period (years) -0.0001 0.671 Number of unique charges 0.0007 0.018

Panel C – Comparison of actual vs. predicted investigation cost for 32 firms in sample

N Mean Median Min Max Actual % 32 1.15% 1.02% 0.03% 3.98% Predicted % 32 1.15% 1.06% -0.17% 3.66%

Panel D - Investigation cost using estimates for missing observations1

N Mean Median Min Max Market capitalization 115 23,099.41 4,544.54 7.23 386,402.07 Investigation costs 115 64.18 17.98 0.24 1,361.67 % of market capitalization 115 1.13% 0.69% 0.03% 13.63%

1. Actual costs were used when available and predicted costs from the model were used for all other observations with 15 predicted values Winsorized at the lowest observed value of 0.0333%.

46

Table 9. Summary of total costs and indirect costs for firms charged with foreign bribery

This table reports the mean and median values when firms’ cumulative total losses are partitioned into direct and indirect cost components. The cumulative total loss is the negative of the sum of the market-adjusted one-day stock returns over all key informational events that pertain to a given bribery-related enforcement action. Fines and penalties are the total fines and disgorgement levied against the firm by regulatory agencies plus class action settlements paid by the firm (net of D&O insurance proceeds) divided by the firm’s market capitalization at the close of trading the day before the initial public announcement of the misconduct. The Investigation and legal costs are calculated for 33 firms for which data are available. For the remaining 82 firms, the investigation and legal costs are the fitted values from the model reported in Table 8. The Restatement effect is the sum of the one-day market-adjusted stock returns on days during the enforcement action on which the firm announced an earnings restatement. The Reputation loss is the residual of the Cumulative total loss minus total direct costs minus the restatement effect. The difference column reports the difference in the means and medians between the actions with and without fraud charges. Significance levels are based on a t-test and rank sum test, respectively, where ***, **, * indicate significance at the 0.001, 0.01, and 0.10 levels.

All bribery actions

(115)

Actions without financial fraud charges

(102)

Actions with financial fraud charges

(13) Difference

Mean Median Mean Median Mean Median Mean Median

Cumulative total loss 8.98% ** 1.49% *** 3.55% ** 1.46% *** 51.58% * 22.22% *** -48.03% * -20.76% *** (from Table 6, Panel C) Direct costs: Fines and penalties 0.98% *** 0.07% *** 0.92% *** 0.06% *** 1.47% * 0.20% ** -0.55% -0.14% Investigation expense 1.13% *** 0.69% *** 1.02% *** 0.61% *** 2.00% *** 2.12% *** -0.98% ** -1.51% *** Total direct costs 2.11% *** 1.06% *** 1.94% *** 0.84% *** 3.47% *** 2.72% *** -1.53% * -1.88% *** Indirect costs: Restatement effect 1.09% ** 0.00% ** 0.81% * 0.00% * 3.29% * 0.00% -2.48% 0.00% Reputation loss 5.78% * -0.42% 0.80% -0.65% 44.82% * 18.17% * -44.02% * -18.82% ** Total indirect cost 6.87% * -0.08% 1.61% -0.51% 48.11% * 18.17% * -46.50% * -18.68% ***

47

Table 10. Determinants of firms’ indirect costs from foreign bribery actions

The table reports ordinary least squares estimates and robust standard errors using data on all 115 bribery-related enforcement actions involving publicly traded corporations from 1978-2011. The dependent in Model 1 is the indirect cost, measured as the cumulative abnormal stock return over key informational events in the enforcement period minus fines, penalties, investigation, and legal costs. In Model 2 the dependent variable is the reputation loss, which is the indirect cost minus the (negative of the) abnormal return on days during the enforcement period in which the firm announced a restatement. Explanatory variables are defined in the text. The top number in each cell presents the estimated coefficient and the bottom number reports the associated two-tailed p-value. *, **, and *** indicate significance at the 10%, 5%, and 1% levels.

Indirect

cost Reputation

Loss Firm characteristics: Log (market capitalization) 0.0175** 0.0174** 0.038 0.042 TI Industry Sector Score 0.0969* 0.0875 0.099 0.140 TI Bribe Payers Index -0.0310 -0.0034 0.711 0.967 Characteristics of the bribe: Number of countries involved -0.0029 -0.0027 0.349 0.389 Violation period (years) -0.0045 -0.0040 0.443 0.502 % sales influenced to total sales -0.0155 -0.0133 0.864 0.885 Average TI Corruption Perception Index 0.0143 0.0203 0.628 0.495 Average TI Global Corruption Barometer 0.2349* 0.267* 0.100 0.064 UN Oil-for-Food dummy -0.0847 -0.0827 0.153 0.167 Average UN Human Development Index 0.3658 0.3611 0.128 0.137 Characteristics of the enforcement action: Number of respondents named 0.0582*** 0.0600*** 0.000 0.000 Financial misrepresentation dummy 0.0464 0.0325 0.453 0.603 Financial fraud dummy 0.1501* 0.1413 0.081 0.103 Class action flag 0.2912*** 0.2521*** 0.000 0.000 Unique US code violations -0.0016 -0.0022 0.833 0.782 Constant -1.2623 -1.4526 0.168 0.117 N 115 115 R2 0.6667 0.6465 F 13.20 12.07 Prob > F 0.000 0.000

48

Figure 1. Bribe-related enforcement actions per year, 1978-2011

0

2

4

6

8

10

12

14

16

18

20

78798081828384858687888990919293949596979899000102030405060708091011

49

Table A-1. Types of charges in foreign bribery-related enforcement actions

This table tabulates the incidence of the specific charges brought in the 115 bribery-related enforcement actions involving publicly traded corporations from 1978-2011. Panel A presents the frequency of civil and criminal U.S. Code violations, the legal citation, common alternative reference, and description of all charges faced by respondents in the foreign bribery-related enforcement actions. Panel B presents the frequency of rule violations in civil and administrative proceedings under the Code of Federal Regulations brought on respondents in the foreign bribery-related enforcement actions. Panel A - U.S. Code violations

Civil Criminal Citation Alternative Description

51 27 15 U.S.C. § 78dd-1 30A(a)(1) Foreign bribery - by issuer (FCPA)

17 15 U.S.C. § 78dd-2 30A(a)(2) Foreign bribery - by domestic concern (FCPA) 6 15 U.S.C. § 78dd-3 30A(a)(3) Foreign bribery - by others (FCPA)

96 34 15 U.S.C. § 78m(b)(2)(A) 13(b)(2)(A) Books and records (FCPA) 88 9 15 U.S.C. § 78m(b)(2)(B) 13(b)(2)(B) Internal controls (FCPA)

28 11 FCPA

pro

visi

ons

15 U.S.C. § 78m(b)(5) 13(b)(5) Knowingly circumvent internal controls (FCPA) 13 1 15 U.S.C. § 78j(b) 10(b) Manipulative and deceptive devices - purchase or

sale in any security 1 15 U.S.C. § 78lj(b) Registration – procedure and information

21 15 U.S.C. § 78m(a) 13(a) Periodical reports - issuer 10 15 U.S.C. § 78n(a) 14(a) Proxies - solicitation

1 15 U.S.C. § 78t(a) 20(a) Controlling persons 9 15 U.S.C. § 78ff False SEC filing

6 15 U.S.C. § 77q(a) 17(a) Fraudulent use of interstate commerce 25 18 U.S.C. § 2 Aiding and abetting 1 18 U.S.C. § 287 Submitting false claims against the United States 43 18 U.S.C. § 371 Conspiracy 8 18 U.S.C. § 1001 False statements 1 18 U.S.C. § 1002 Possession of false papers 4 18 U.S.C. § 1341 Mail fraud 9 18 U.S.C. § 1343 Wire fraud 1 18 U.S.C. § 1344 Bank fraud 1 18 U.S.C. § 1348 Securities fraud 2 18 U.S.C. § 1349 Attempt and conspiracy 1 18 U.S.C. § 1350 False certification of financial reports 3 18 U.S.C. § 1952 Racketeering (use of transportation) 7 18 U.S.C. § 1956 Racketeering (money laundering) 3 18 U.S.C. § 1957 Racketeering (monetary transactions) 1 18 U.S.C. § 2332d Terrorism financial transactions 2 22 U.S.C. § 2778 Control of arms export and import 3 26 U.S.C. § 7206 Fraud and false tax statements 1 31 U.S.C. § 1059 Export and import monetary instruments (CFTRA) 1 31 U.S.C. § 1101 Export and import monetary instruments (CFTRA) 2 31 U.S.C. § 5316 Export and import monetary instruments

1

Non

-FC

PA p

rovi

sion

s

50 U.S.C. § 1701

Engaging in transactions with a specially-designated global terrorist

50

Table A-1 (con’t) Panel B - Code of Federal Regulations (Rule) violations

Civil Citation Description

31 17 C.F.R. 240.13b2-1 Falsification of accounting records (FCPA) 10 17 C.F.R. 240.13b2-2 Misrepresentations to auditors (FCPA)

FCPA

13 17 C.F.R. 240.10b-5 Manipulative and deceptive devices - intent to defraud 17 17 C.F.R. 240.12b-20 Additional information to make statement not misleading – antifraud

18 17 C.F.R. 240.13a-1 Annual reports (10-K and 10KSB) 7 17 C.F.R. 240.13a-11 Current reports (8-K)

14 17 C.F.R. 240.13a-13 Quarterly reports (10-Q and 10QSB) 2 17 C.F.R. 240.13a-14 False certification of periodic reports (SOX)

3 17 C.F.R. 240.14a-3 Information requirements (proxies)

8 17 C.F.R. 240.14a-9 False or misleading statements (proxies) 1 17 C.F.R. 243.100 Disclosure - general rule regarding selective disclosure

1 22 C.F.R. 120 Violations and penalties 1 22 C.F.R. 130 Political contributions, fees and commissions

1 31 C.F.R. 103.23 Reports of transactions of currency or monetary instruments (CFTRA)

1

Non

-FC

PA

31 C.F.R. 103.25 Reports of transactions with foreign financial agencies (CFTRA)

51

Table A-2. Non-monetary legal sanctions for bribery violations

Non-monetary legal sanctions imposed through federal sanctions relating to 115 enforcement actions for foreign bribery brought under the Foreign Corrupt Practices Act from 1978 – 2011. The table presents non-monetary sanctions against all respondents in the enforcement proceedings including pretrial agreements (deferred and non-prosecution). Only partial sanction information is presented for 24 actions (22 without financial fraud and 2 with financial fraud) whose proceedings were ongoing as of December 31, 2011.

All bribery

actions

Actions without financial

fraud charges

Actions with financial

fraud charges

# Enforcement Actions N 115 102 13 # actions with SEC sanctions N 97 85 12 # actions with DOJ sanctions N 75 67 8 Total number of administrative and civil sanctions

Cease and desist orders N 46 35 11 Injunctive actions N 142 107 35 Trading suspensions N 1 0 1 Revocations N 1 0 1 Officer & director bars N 17 1 16 Accountant bars N 8 2 6 Other bars N 2 1 1 Total number of criminal sanctions, including pretrial agreements

Sanctions N 242 185 57 Average # criminal sanctions Mean 2.1 1.8 4.4 Unknown sentences N 5 2 3 Pending sentences N 7 6 1 Awaiting trial N 12 10 2 Pretrial agreements N 53 51 2 Prison (months) N

Mean 26

42.5 10

15.7 16

59.2 Probation (months) N

Mean 79

33.6 67

32.0 12

42.0 Halfway house (months) N

Mean 2

4.5 2

4.5 0

0.0 Home detention (months) N

Mean 9

4.7 4

3.0 5

6.0 Supervised release (months) N

Mean 10

23.1 5

27.0 5

19.2 Community service (hours) N

Mean 2

400 1

600 1

200

52