the causes and consequences of accounting fraud

MANAGERIAL AND DECISION ECONOMICS

Manage. Decis. Econ. 18: 587–599 (1997)

The Causes and Consequences of AccountingFraud

Mason Geretya,* and Kenneth Lehnb

a Department of Finance, Northern Arizona Uni6ersity, Flagstaff, AZ USAb Katz School of Business, Uni6ersity of Pittsburgh, Pittsburgh, PA USA

One of the fundamental purposes of corporate accounting is to facilitate the monitoring ofmanagers. Since managers are instrumental in the production of accounting numbers, andsince it is costly to monitor their behavior in this regard, firms sometimes report fraudulentaccounting numbers. This paper tests several hypotheses concerning why some firms, and notothers, commit accounting fraud. This is accomplished through examination of a sample of62 firms charged with disclosure violations by the Securities and Exchange Commission(SEC) during the period 1981–1987. We also examine whether directors of companies thatcommit accounting fraud are disciplined in the managerial labor market.

We adopt the perspective that the decision to commit fraud is governed by the expectedcosts and benefits of this behavior (This approach to the study of fraud has been usedelsewhere, e.g. Darby and Karni (1973) Michael R. Darby and Edi Karni, ‘‘Free Competi-tion and the Optimal Amount of Fraud’’, Journal of Law and Economics 16 (April 1973),68–88. For a brief discussion of the economics of fraud, see Edi Karni (1989) ‘‘Fraud’’ inThe New Palgra7e: Allocation, Information, and Markets, edited by John Earwell, MurrayMilgate, and Peter Newman, New York: W.W. Norton, 117–119). Accordingly, a theory ofaccounting fraud requires an understanding of how these costs and benefits vary across firms.Those costs and benefits can be varied by external forces, through institutions such as equitymarkets and independent auditors, or internally through the design of monitoring and rewardsystems. We will divide our attention between the external and internal forces that changethe costs and benefits of accounting fraud. © 1997 John Wiley & Sons, Ltd.

INTRODUCTION

Discussions of the efficient structure of a corpora-tion date at least from Berle and Means (1933).Their focus was the supposed inefficiency of theseparation of ownership and control. Empiricalinvestigation of the efficient corporate structurehas become prominent recently. For example,Demsetz and Lehn (1985) find that ownershipstructure varies based on firm size, profit instabil-ity, regulation, and amenity potential. They pro-pose that external forces are the determinants ofcorporate structure. In a very real way, corporateownership structure is a response to marketforces. We adopt that perspective here. We con-trol for firm size and industry and test whether

anything else matters in the frequency of account-ing fraud. We separate our investigation into ex-ternal (market determined) and internal(endogenous responses to the market) forces thatcould vary between those firms accused of fraudand those not accused. Our results support theconcept that market forces shape corporate activi-ties more that internal structures.

In a window around the commencement ofaccounting fraud, we find evidence that stockperformance increases relative to an industrymatch firm. Fraud seems to fool the market, atleast in the short term. We also find that theannouncement of SEC charges of accountingfraud result in statistically significant average cu-mulative abnormal returns of −3.05% during a 3day window surrounding these announcements.These results document that SEC charges impose

* Correspondence to: Department of Finance, Northern Ari-zona University, Flagstaff, AZ. Tel.: +1 520 5237355.

CCC 0143–6570/97/070587-13$17.50© 1997 John Wiley & Sons, Ltd.

588 M. GERETY AND K. LEHN

costs on firms (or revise investor expectationsregarding true asset value). The frequency of ‘Big-Eight’ versus ‘non-Big-Eight’ auditors does notdiffer significantly across the two samples, sug-gesting that auditor reputation does not effect thelikelihood of committing accounting fraud. Wefind that a significant direct relationship existsbetween R&D expenditures and the frequency ofaccounting fraud across 256 industry groups. Thisresult suggests that the more costly it is to valueassets, the more likely is accounting fraud. An-other proxy for the ease of valuing assets, intangi-ble assets, is positively, although not significantly,related to the frequency of accounting fraud.

We find that several classic corporate gover-nance variables do not differ significantly acrossthe sample of offenders and a sample of controlfirms in the same industries. For example, none ofthe following variables differ significantly acrossthe two samples: The mix of outside and insidedirectors, the presence or absence of audit com-mittees, or the presence or absence of classifiedboards. We do find that while aggregate stockownership by the board of directors has a weak,and statically insignificant influence over theprobability of fraud, concentration of ownershipin one individual on the board significantly re-duces the probability of fraud. The frequency ofaccounting based executive compensation pack-ages is slightly, but not significantly, higher forthe sample of offenders than for the control sam-ple. This suggests that the reliance on accountingbased managerial compensation incentives doesnot increase the likelihood of accounting fraud.

Some of these results, especially those involvingthe mix of inside and outside directors, are atodds with other research investigating the role ofdirectors in the incidence of accounting fraud. Forexample, Beasley (1996) finds that firms with agreater proportion of outside directors are lesslikely to commit accounting fraud. In a multivari-ate logit design, he finds robust results that indi-cate that holding many other firm characteristicsconstant, the percentage of outside board mem-bers matters. The multivariate logit design of hiswork has some advantages over our research de-sign, as he can hold constant other influences. Onthe other hand, while Beasley includes in hissample firms matched by size and industry, hecan’t control specifically for the match. He canonly balance his sample with offender and non-of-fender firms. Our methodology, described later,

does not allow for ceterus paribus tests, but doesallow for direct matching of the same industry,same size offenders and non-offenders. This dif-ference in test design may account for the differ-ent results.

We also find evidence of Fama’s (Fama, 1980)managerial labor market at work within the mar-ket for corporate directors. The number of otherdirectorships held by the directors of firmscharged with accounting fraud declines signifi-cantly compared with the corresponding numberof directorships for directors of the control firms.This evidence is consistent with the argument thatthe managerial labor market penalizes directorswho serve on boards of firms charged with ac-counting fraud.

In short, we find that the decision to commitfraud seems to be governed by the cost of valuingits assets. Corporate governance structures, thereputation of the auditor, and its reliance onaccounting-based executive compensation plansdo not appear to significantly affect the likelihoodof accounting fraud, while there appears to beevidence that concentration of stock ownershipmatters. Consistent with Fama (1980), there ap-pears to be some ‘ex post settling up’ in the labormarket for directors of firms committing account-ing fraud. We will divide this work into foursections. The first describes the sample, a few ofthe cases of accounting fraud, and outlines thetypes of fraud committed. The second examinesand tests hypotheses regarding the external forcesthat determine the costs and benefits of account-ing fraud. The third does the same for the internalforces. Finally, we turn our attention to the evi-dence regarding ex-post settling up.

EXAMPLES OF ACCOUNTING FRAUD

In some ways, the term accounting fraud is mis-leading. A more generic term, disclosure 6iolation,might be more appropriate for our purposes. Ouroriginal dataset contained violations that run thegamut from failure to file appropriate and re-quired financial statements with the Securities andExchange Commission to internal fraud thatshows lack of proper internal controls to clearand willful misrepresentation of the financialhealth of the firm. There are also some notableoutliers, including a set of banks that werecharged with improper accounting for loan loss

© 1997 John Wiley & Sons, Ltd. Manage. Decis. Econ. 18: 587–599 (1997)

589CAUSES AND CONSEQUENCES OF ACCOUNTING FRAUD

reserves and one case of a violation of the ForeignCorrupt Practices Act. All the results reported inthe paper were replicated dropping the banksfrom the sample, and there were no noticeablechanges in the results. Splitting the sample intotypes of fraud was considered. There are manyspecific types of fraud, and splitting to a fine levelof distinction produces too few observations tomake the results meaningful. Grouping to allevi-ate the problem of limited observations becomesad hoc. We maintained the dataset in its entirety,only eliminating firms due to lack of data. Wenow give an overview of some representative, andentertaining, cases from the sample.

Many of the firms that started in our samplewere dropped because they had failed to file anydocuments at all with the SEC, and as a result wewere unable to find any relevant information re-garding their corporate structure. Our originalsample was quickly whittled to 62 firms. Therestill remained seven firms charged with a failure tofile some document. Typical in this regard is theSEC v. Permeator Corporation. On March 29,1983 the SEC filed for civil injunctive actionagainst Permeator alleging that they failed to filetheir 1982 10-K report, and filed various otherreports late. Other firms in the sample filed late,or failed to file one or more reports. To beincluded in the sample they must have filed atleast some reports with the SEC at some time.

A more common violation was the inflation ofrevenue and/or earnings, or the shifting of rev-enue and/or earnings. Two cases that describe thetypical violation are SEC v. McCormick & Com-pany and SEC v. Tandem Computers Incorpo-rated et al. In the case of McCormick & Co., thefirm and the general manager of a division wereaccused of inflating revenues. This was accom-plished by ‘‘(1) the systematic deferral of therecognition of substantial amounts of promo-tional and advertising expense; and (2) the recog-nition of sales revenue in a fiscal period for goodsthat were prepared for shipment in that periodbut not shipped until a later period’’1. The ac-cused general manager was also a member of theBoard of Directors. Because the manager hadincentive clauses based on bottom line accountingnumbers in his contract, he was shifting his bonusforward one period, increasing its present value.The case of Tandem Computers et al. was similar.In this case, the CEO, COO, and controller werealso named in the case. Tandem was alleged to be

involved in a concerted effort to lie about thefinancial health of the firm. This was allegedlyaccomplished by shifting sales revenue, recogniz-ing a contingent order as a sale, and recognizingrevenue on goods not yet shipped. The allegationsof shifting revenue or income, or inflating revenueor income, comprise 18 of our final 62 firms.

Another common allegation involved firms whomade false or misleading statements about thefinancial prospects of the firm. Two classic casesare SEC v. Equity Gold et al. and SEC v. ZoeProducts. Equity Gold was a firm that claimed tobe in the gold mining business, and also reclaimedold mines. It is alleged that from its inception thefirm and the directors engaged in systematic falsestatements regarding the amount of gold in re-serves and the amount of drilling done in testingfor gold, in an attempt to increase the price of thestock selling on the OTC. At one point theyclaimed to possess more gold at one mine thanhad been taken from any gold district up to andincluding the year 1959 (i.e. this mine had moregold in it than the entire California district duringthe California Gold Rush). The statements madeby Zoe Products are, in retrospect, just as ludi-crous. Zoe Products was in the business of pro-ducing and marketing natural vitamins, and in an8-K report they claimed to have found a productthat they marketed as ‘Sober-Aid’. This productwould return an intoxicated person to sobriety. Itis easy to dismiss these kinds of cases based onmateriality, but in this regard the case of ZoeProducts is illuminating. Zoe traded on the OTC,and as of 1982 (the year of the announcement ofSober-Aid) had the following financial informa-tion: book assets of $1 387 000; long term debt of$26 000 (much of this was a car loan and somerevolving credit card debt used to buy an officecopier); one employee; 6059 shareholders, and amaximum market value of $45 221 498. It wouldappear that someone believed the claims made byZoe.

The allegation of inadequate internal controlsconstitutes another type of disclosure violationfound in our dataset. The case of Tonka Corpora-tion is one situation where there were not onlyinadequate internal controls, but perhaps none.Tonka makes toys, and before 1981 made a profitdoing this. Prior to 1981, they had no cash man-agement plan to speak of, and their short termcash was held exclusively in certificates of depositand commercial paper. They had no short term or



long term investment policy. Indeed, they had noChief Financial Officer. In 1981 a CFO was hired,in the main to provide a short and long terminvestment strategy. Unbeknownst to Tonka, theCFO set up a shell company in Iowa and issued14% preferred stock, which the CFO purchasedusing Tonka’s money. The CFO and his partnerin the Iowa firm then used the cash proceeds towrite covered call options. In a matter of 2 yearsthe CFO had lost over $3 000 000. The disclosureviolation alleged that no one on the Board ofDirectors of Tonka ever asked for any informa-tion about the firm in Iowa, although they autho-rized all purchases of the preferred stock. Therewere no internal controls that mitigated this typeof fraud.

The last obvious grouping of firms was a set offive banks that were alleged to have improperlyaccounted for loan loss reserves. Typical of thistype of allegation was the matter of Texas Com-merce Bankshares. The allegation in this caserevolved around the lack of an adequate systemto identify problem credits. The Commission ar-gued that when the bank grew, it did not addsufficient staff to review the growing portfolio. Inan ex-post fashion, the SEC looked at the bankafter it got into trouble, and alleged that thebank, if it had examined the portfolio with duediligence, would have written down some of theloans prior to their becoming insolvent.

There were many variations on these themespresent in the data, and some that were one-of-a-kind accusations. In this vein is the violation ofthe Foreign Corrupt Practices Act by AshlandOil. We argue that because these violations havemany dimensions, finding a consistent theme inthe data will strengthen the work, not detract. Wenow outline the market forces that influence thedecision to commit accounting fraud. This will befollowed by a discussion of the internal corporatestructures that either enhance or mitigate theprobability of a firm committing accountingfraud.

EXTERNAL FORCES THAT EFFECT THECOSTS AND BENEFITS OF ACCOUNTING

FRAUD

One major external force that drives the choice tocommit accounting fraud may be the inherentdifficulty the market has for valuing some assets.

As a general proposition, the prevalence of fraudis expected to be higher in markets where it iscostly to verify the quality of the transacted good.In a discussion of fraud in The New Palgrave,Karni2 discusses this phenomenon: ‘‘Fraud is asprevalent and as persistent as the asymmetricalinformation necessary to support it. The fraudmay occur whenever the cost of verification of theproducer’s claims to the actual purchase of thegood or service is prohibitively high’’. In short,the probability of detecting fraudulent behavior,and hence the expected costs of fraud, variesinversely with the costs of verifying product qual-ity.

Following this reasoning the probability of de-tecting accounting fraud is likely to be relatedinversely to the costs of valuing a firm’s assets.For example, outsiders presumably have moredifficulty detecting accounting malfeasance infirms with high research and development (R&D)expenditures or substantial intangible assets thanin firms with ‘hard’ assets that are more easilyvalued. Since the probability of detection variesdirectly with the expected cost of committingfraud, accounting fraud should be more likely infirms with assets that are difficult to value.

Another external force to be examined is theeffect of conscientious independent auditing. Therole of the independent auditor is to provideoutside verification of the veracity of accountingnumbers. Arguably, the major asset of auditors istheir reputation for verifying the quality of ac-counting numbers produced by corporate man-agers. Watts and Zimmerman (1986) describe theimportance of an auditor’s reputation:

Reputation gives auditors incentives to be inde-pendent. It is costly to establish a track record andreputation for discovering and reporting contractbreaches, but once established, reputation in-creases the demand for the auditor’s services andfees… If found to have been less independent thanexpected, the auditor’s reputation is damaged andthe present value of the auditor’s services is re-duced. He bears the cost. Thus the auditor’s repu-tation (a valuable asset) serves as a collateral bondfor independence.

To the extent that the more reputable auditors aremore likely to detect accounting fraud, it can beargued that firms with such auditors are less likelyto commit accounting fraud. Assuming that ‘BigEight (now ‘Big Six’)’3 auditors have the mostreputational capital, we examine the prevalence ofthe use of Big Eight auditors in the sample.



Table 1. Summary Statisticsa

Accused firmFirm characteristic p-Value on differenceControl firm

Total assets $3980.28 (mil) $2592.12 (mil) 0.423$22.56 (mil) 0.874R&D expense $19.42 (mil)

0.803 0.831Big 8 auditor (proportion) 0.6810.158 0.5640.121Classified board (proportion)

0.7609.67Number of directors 10.050.576 0.910% Directors insider 0.566

0.395 0.373% Directors outsiders 0.8090.667 0.569 0.278Audit committee (proportion)0.579 0.466Compensation committee (proportion) 0.220

0.4260.2930.228Nomination committee (proportion)0.089 0.121ESOP (proportion) 0.5840.446 0.310Accounting bonus plan (proportion) 0.131

0.28917.4614.30Stockholdings, largest board holding0.42027.65Total board holdings 24.39

1.30 0.722Number of 5% stockholdings 1.3853.88 53.77Age of directors 0.9297.79 8.69 0.789Dispersion of age (S.D.)7.02 8.22 0.120Tenure on board

0.8705.915.07Dispersion of tenure (S.D.)

The means here are of all firms for which data was available. Means will differ in matched pairs testsperformed later due to the necessity that both the accused and control firms must have the relevant dataavailable.

SAMPLE AND EVIDENCE

Our final sample consists of 62 firms charged withfinancial disclosure violations by the Securitiesand Exchange Commission (SEC) during thefiscal years 1981–1987. The sample was collectedby inspecting the SEC annual reports during thisperiod. Firms were eliminated from the sampleeither because (a) their returns were not containedon the Center for Research on Security Prices(CRSP) daily or NASDAQ tapes; or (b) becausethey are not covered by the Moody’s Industrials,OTC, Public Utility, Bank and Finance, or Trans-portation manuals in the fiscal year immediatelypreceding the SEC charges.

For each of the 62 firms we selected a controlfirm that was not charged with accounting fraudby the SEC. The control sample consists of thefirm in the same 4-digit Standard Industrial Clas-sification (SIC) code that was nearest in size, asmeasured by total book value of assets, to thecorresponding offender in the fiscal year preced-ing the SEC charges. To avoid matching firmswith divergent asset mixes, the ratio of currentassets to total assets was compared for each of thepair of firms. When the ratio of current assets tototal assets diverged by an order of magnitudeand an alternative match was available, the alter-native was chosen. This only happened twice in

the sample. Additional requirements for inclusionin the control sample are that: (a) the firms hadnot been previously or subsequently charged withaccounting violations by the SEC; (b) financialdata on the firms are contained on the Compustattape; (c) the firms are listed in the Moody’s manu-als in the fiscal year preceding the SEC charges;and (d) SEC proxy filings for the firm are avail-able in the fiscal year preceding the SEC charges.4

Table 1 provides summary statistics on theaccused firms and their controls. Presented are themean (or percentage or standard deviation if ap-propriate) of the accused sample, the same rele-vant statistic for the control sample, and thep-value from the test of the hypothesis (non-paired) that the statistics are equal. As can be seenfrom the univariate statistics presented for theentire sample, the two samples are not signifi-cantly different at a reasonable level of signifi-cance. This lack of significant difference willcontinue in most dimensions when we examinethe sample in a series of matched-pair tests.

Despite our attempts to match on size, theaverage difference in the total assets of offendersversus the control sample ($1.38 million) is statis-tically significant from zero (Wilcoxon (paired)t-statistic of 2.5) in the year preceding the SECcharges. When ten banks are excluded from thesample, however, this difference ($400 000) is not



statistically different from zero (Wilcoxon t-statis-tic of 1.34). The average difference in the ratio ofcurrent to total assets is not statistically differentfrom zero (Wilcoxon t-statistic) for the sample ofnon-banks.5

A fraud is not material if there is no relianceupon the information by an unsophisticated in-vestor. We examine materiality by looking atstock price performance near the beginning of thefraudulent period as well as stock price perfor-mance upon the announcement of the fraud. Wefind that, on average, the cases in the sample werematerial.

To examine materiality, we examined a windowsurrounding the beginning of the firm’s account-ing fraud. The choice of a date for the commence-ment of fraud was somewhat tenuous, but wechose the release date of the first 10-K or 10-Qthat the SEC claimed was fraudulent. We foundfor a sample of 23 matched pairs of firms forwhich data existed, in the 150 trading days priorto the commencement of fraud the accused firmsperformed 7.4% worse6 than their industry matchfirm. In the 150 trading days following the com-mencement fraud, the offender did as well as theindustry match (difference in CARs −0.004). Itseems that the market was fooled by the fraud, atleast in the short run.

To verify that SEC charges of accounting fraudactually impose costs on firms, we estimated theaverage effect that the announcements of thesecharges had on the stock prices of firms in oursample. Various editions of the Wall Street Jour-nal Index (WSJI) were used to identify the firstpublic announcement of the SEC charges. If noannouncement was contained in the WSJI, thedate on which the SEC announced the chargeswas used. These announcement ranged from ru-mors of SEC charges to definitive announcementsof SEC charges. Conventional event studymethodology is used to estimate the stock priceeffects of these announcements over a three dayperiod: the day before through the day after theannouncements. Sufficient stock return data forthe event study are available for only 37 of the 62companies. This sample of 37 firms contains 18NYSE and AMEX firms and 19 NASDAQ firms.

The average cumulative abnormal return forthe 37 firms over the 3 day window surroundingthese announcements is −3.05%, which is statisti-cally different from zero (t-statistic= −1.89).The 3 day CAR ’s ranged from −34.39% (Flo-

rafax International) to 18.7% (Charter Company).The average CAR is less negative for NYSE andAMEX firms (−2.15%, with a t-statistic of−1.79) than for firms that trade on the NASDAQsystem (−3.91%, with a t-statistic of −2.02).This difference may result from the fact thatcompared with NASDAQ companies, the eventdates for NYSE and AMEX companies are morelikely to be rumors, rather than definitive SECcharges. Alternatively, this evidence may suggestthat charges of accounting misdeeds convey moreinformation about lesser known firms (i.e. NAS-DAQ) than the do about better known firms (i.e.NYSE).

Next we turn to an examination of the cost ofvaluing assets. Assuming that the costs of valuingassets varies systematically across industries, weexpect the distribution of firms committing ac-counting fraud to be clustered in industries inwhich these costs are especially high. To testwhether the sample of offenders is distributedrandomly across industries, we compare the ac-tual and expected number of offenders in each3-digit SIC code. We had definitive 3-digit SICclassifications for 55 of our original 62 firms. Theother seven were spread across more than one3-digit SIC code. The expected number of offend-ers in each industry was computed by multiplyingthe sample size by the proportion of the fullCOMPUSTAT sample that fell in the correspond-ing industry. For example, SIC code 738, miscel-laneous office products, had 166 firms in theCOMPUSTAT sample, or about 1.5% of the to-tal. To find the expected number of offenders inthis industry, 1.5% is multiplied by the total num-ber of firms in our sample, 55, to generate anexpected number of 0.83. The Chi-square statisticcorresponding to the absolute value of the differ-ence between the actual and the expected numberof offenders by industry is 28 717, which revealsrather decisively that the offenders are not dis-tributed randomly across industries.7

The difference between the actual and expectednumber of offenders for the top 20 and bottom 20SIC codes is listed in Table 2. The incidence ofoffenders (i.e. the difference between the actualand expected number of offenders) is highestamong office computing and accounting machines(SIC code 357), commercial and stock savingsbanks (SIC code 602), drugs (SIC code 283),computer programming and data processing ser-vices (SIC code 737), and electric lighting and



Table 2. Twenty 3-digit SIC Codes with Smallest and Largest Difference between Actual and ExpectedNumber of Fraud Cases

3-Digit SIC codes Actual–expected Descriptionnumber of cases

Panel A: Industries most underrepresented−2.73578 Miscellaneous investing679

131 −2.26885 Crude petroleum and natural gas−1.31257 Electronic components367

581 −1.15667 Eating and drinking places−0.92533 Telephone communications481

308 −0.72920 Misc plastic products492 −0.63868 Gas production and distribution

Grocery stores−0.59845541Resh, development, testing services−0.58336873

−0.56324 Trucking421−0.51295 Motion picture production781

451 −0.46769 Scheduled air transportationSoap, detergent, toilet preps284 −0.43752

−0.43752 Steel work, roll & finish mill331344 −0.42746 Fabricated structural metal

−0.41740 Apparel, other finished products230−0.41237 Electrical goods-wholesale506

Refrig & service ind machines−0.40735358799 −0.40735 Misc amusement & rec svcs353 −0.39226 Constr, mining, matl handling eq

Panel B: Industries most over-representedSugar & confectionery prods0.844100206Misc food preps0.849129209

0.879303 Petroleum & pete prod, wholesale5170.889361 Paper & paper prod, wholesale511

808 0.889361 Home health care svcsGen bldg contractors-res152 0.924564

733 0.929593 Mailing, repo, comml art Svcs286 0.934622 Industrial org chem

0.939651 Functions rel to deposit banking609162 0.959767 Hvy Constr, ex highway

0.959767 Misc transportation equip379639 0.989941 Insurance Carriers, nec738 1.165183 Misc business services

Security brokers and dealers1.532301621Ins agents, brokers & service1.753578641

1.763636 Electric lighting, wiring3641.827466 Comp programming, data proc737

283 1.908704 DrugsCommercial banks602 4.838297

8.149323 Computer & office equip357

wiring equipment (SIC code 364). Industries withthe lowest incidence of offenders are miscella-neous investing (SIC code 679), crude petroleumand natural gas (SIC code 131), electronic compo-nents and accessories (SIC code 367), eating anddrinking places (SIC code 581) and telephonecommunications (SIC code 481).

To test whether the distribution of accountingfraud cases across industries varies according tothe cost of valuing assets in industries, we regressthe difference between the actual and expectednumber of fraud cases by industry on proxies forthe cost of valuing industry assets. One proxy is

the ratio of aggregate R&D expenditure in each3-digit SIC industry to the sum of the aggregatecost of goods sold and general administrativecosts in the industry. We expect that as R&Dincreases relative to other costs, the difficulty ofmonitoring asset values increases. The secondproxy is the ratio of aggregate intangible to aggre-gate total assets in each 3-digit SIC industry,which also is expected to vary directly with thecosts of valuing assets.

The regression of the frequency of fraud on theR&D variable yields the most favorable results.The frequency of fraud varies directly, and signifi-



Table 3. Summary of Results

Panel A: Evidence on Big-Eight auditors% Control only% Neither % Off only% BothN

12.911.370.9 4.8Big 8 auditors 62

Panel B: Evidence on determinants of accounting fraudCorporate governance variables—matched pairs t-tests

Offender-Control t-TestN

Percentage outside directors 52 −0.016 −0.4310.9170.038Percentage inside directors 52

−0.021 −1.211Percentage professional directors 520.6890.096Accounting based compensation 52

−1.793Ownership by largest board 52 −4.512member

Corporate governance variables—percentages% Neither % Control only% Off only% BothN

26.7 10.6Audit committees 47 53.2 8.53.8 13.4 7.775.0Classified boards 52

Panel C: Evidence on ex-post settling upPercentage change in number of directorships

Z-scoreYears after Excess lost byoffenders

2.54+1 Year 5.7%+2 Years 6.2% 2.14

1.78+3 Years 5.7%

Panel D2 Years later 3 Years later1 Year later

−0.2587−0.2312Not bad performing accused −0.1623−0.2696 −0.3444Poor Performing accused −0.1720

−0.2320Control Sample −0.1007 −0.17401.4010.198Z-statistic (null is not bad 0.663

performing equals poorperforming)

cantly at the 0.01 level (t-statistic of 3.02), withR&D expenditures. The regression in which theratio of intangible to total assets serves as theindependent variable also yields a positive rela-tionship, but is insignificant (t-statistic of 1.38).Although this evidence is mixed, it is generallyconsistent with the argument that the morecostly it is to value assets, the more likely isaccounting fraud.

Is the likelihood of committing accountingfraud lower for firms audited by major account-ing firms? To test this, we recorded whethereach offender and control firm had a ‘Big Eight’auditor in the year preceding the SEC charges.Data on auditors were obtained from SECproxy statements in the year preceding the SECcharges for 62 matched pairs. The results onauditor reputations are shown in Table 3, panelA. Both the offender and the control firm had a

Big Eight auditor in 70.9% of the pairs, andneither firm had a Big Eight auditor in 4.8% ofthe pairs. In 11.3% of the pairs only the of-fender had a Big Eight auditor, and in 12.9% ofthe cases only the control firm had a Big Eightauditor. The frequency of Big Eight auditors isslightly higher among the control firms, al-though this difference is not statistically signifi-cant.

INTERNAL DETERMINANTS OFACCOUNTING FRAUD

We turn our attention to an evaluation of theeffects of the structure of internal monitoring andreward systems on the probability of a firm com-mitting accounting fraud. The governance struc-ture of firms has been suggested as a variable that



affects the likelihood of committing accountingfraud. For example, much of the debate in the1970s over corporate governance centered on therole of boards of directors in mitigating accountingfraud. Outside directors, some argued, havestronger incentives than inside directors to monitorthe activities of managers, including the managers’production of accounting numbers. In the late1970s and the early 1980s there was a substantialincrease in the ratio of outside to inside directorsof publicly traded companies, perhaps due in partto this public policy controversy.8

In addition, the New York Stock Exchange(NYSE) adopted a listing standard in 1978 thatrequires NYSE-listed companies to have auditcommittees made up of directors who are indepen-dent of management. The purported role of theaudit committee in mitigating fraud was summa-rized in 1977 by Harold Williams, then-Chairmanof the SEC:

It should be evident, but perhaps bears repeating,that integrity in reporting financial data is vitalboth to an efficient and effective securities marketand to capital formation. One key to increasingpublic confidence in that data long advocated bymany segments of the financial community, in-cluding public accounting firms, is more directinvolvement by boards of directors in the auditingprocess and the integrity of reported financialinformation. The vehicle, which the Securities andExchange Commission, the New York Stock Ex-change and an increasing number of public corpo-rations have turned to, has been the independentaudit committee. (Williams, 1977)

Some legal scholars and regulators have ap-plauded the proliferation of outside directors andaudit committees, on the grounds that they raise theprobability of detecting, and hence increase theexpected cost of accounting fraud. Alternatively,others argue that outside directors and audit com-mittees are largely perfunctory and have little or noeffect on corporate governance.

An additional part of a firm’s governance struc-ture that is thought to affect the incentives ofdirectors to monitor managers is whether or not theboard is classified. Boards of directors are classified(sometimes referred to as staggered) if in any yearonly a subset of directors stand for election orreelection. Usually, with classified boards, one-third of the directors stand for election or reelectionto a 3 year term every year. Consequently, classifiedboards impede quick transfers of control, and arefrequently viewed as anti-takeover devices.

Two competing views of the effect of classifiedboards on accounting fraud exist. Viewed as ananti-takeover device, classified boards may dullincentives of board members to monitor managers,and therefore increase the likelihood of accountingfraud. However, as Weston, Chung, and Hoagpoint out, (Weston et al., 1990) ‘‘management’spurported rationale in proposing a staggered boardis to assure continuity and experience,’’ whichsuggests that classified boards might mitigate ac-counting fraud.

The final variable of interest is the extent towhich a firm uses accounting based incentives inmanagement compensation plans. It is commonlyacknowledged that accounting choices are gov-erned in part by contractual considerations.9 Inparticular, the frequent use of accounting basedincentives in executive compensation plans areoften thought to be important factors affectingaccounting choices (See, e.g. Healy, 1985). We testthe hypothesis that the presence or absence ofaccounting based executive compensation planshas no effect on the likelihood that a firm willcommit accounting fraud.

To test whether the structure of boards ofdirectors affects the likelihood of committing ac-counting fraud, we collected various data on theoffenders’ boards and those of their correspondingcontrols in the year immediately preceding the SECcharges. The source for these data are variousproxy statements filed with the SEC. The numberand identity of board members is listed in the proxystatements for 52 pairs of offenders and controlfirms. Offenders had slightly larger board sizes, butthis average difference (0.403) is not statisticallydifferent from zero (Wilcoxon t-statistic of 0.56).

To examine the extent to which the mix ofoutside to inside directors, or the number of ‘pro-fessionals’ on a board affects the likelihood ofcommitting accounting fraud, we classified eachboard member of all 52 offenders and their controlfirms. Inside directors include present or formeremployees of the firm, founders of the firm andtheir families, representatives of suppliers to thefirm including the firm’s lawyers, and representa-tives of the firm’s customers. Professional directorsinclude representatives of the firm’s commercial orinvestment bankers, and outside directors as allothers.

This categorization of directors is somewhatarbitrary, but generally consistent with other stud-ies. Hermalin and Weisbach (1988) and Weisbach



(1988) define full time employees and ex-em-ployees as insiders, those with business dealings as‘grays’ and others as outsiders. Rosenstein andWyatt (1990) define outsiders as those notpresently or formerly employed. Bryd and Hick-man (1990) as well as Baysinger and Butler (1985)define employees and ex-employees as executives,investment bankers and bankers as ‘instrumental’directors, and all others as monitoring directors.We adopt the convention that those with mone-tary gains at stake are insiders, those with possibleoutside business-oriented brand names (e.g.bankers and investment bankers) are profession-als, and those with no contractual relationshipother than their membership are outsiders.

The data, shown in Table 3, panel B, reveal nosignificant difference in the mix of outside andinside directors for the offenders and their corre-sponding controls. The average differences in thenumber of inside directors, expressed as a percent-age of all directors, is negative (meaning thatthere are fewer inside directors on the boards ofoffenders), although this difference is not signifi-cantly different from zero (Wilcoxon t-statistic of−0.43). Similarly, the average difference in thenumber of outside directors, expressed in thesame way, is positive (more outside directors onboards of offenders), but this difference is notstatistically significant (Wilcoxon t-statistic of0.917). The null hypothesis that the likelihood ofaccounting fraud is not related to the mix ofoutside to inside directors cannot be rejected.

Next we turn to the question of whether thepresence of audit committees affects the likeli-hood of committing accounting fraud. We exam-ined the proportion of offenders that had auditcommittees in the year before the SEC charges, tosee if that proportion was lower than the corre-sponding proportion for the control firms. Sincethe NYSE mandates audit committees, we ex-cluded five matched pairs from this analysis be-cause one of the two firms traded on the NYSEwhile the other did not. This leaves 47 matchedpairs for this analysis.

Table 3, panel B, contains the empirical resultson audit committees. In 53.2% of the matchedpairs both firms had an audit committee, and in27.6% of the matched pairs neither firm had anaudit committee. For more than 80% of thematched pairs, the presence or absence of an auditcommittee was identical for both the offendersand the control firms. In 10.6% of the matched

pairs only the offender has an audit committee,and in 8.5% of the sample only the control firmhad an audit committee. The presence of auditcommittees was actually higher for the offendersthan the control firms, although this difference isnot statistically significant. The results fail to re-ject the null hypothesis that the presence of anaudit committee has no effect on the likelihood ofcommitting accounting fraud.

We also tested the null hypothesis that thelikelihood of committing accounting fraud is notaffected by whether a firm has a classified boardof directors. Data on how directors were electedin the year before the SEC charges are availablein SEC proxy filings for 52 matched pairs. Neitherthe control firm nor the offender had a classifiedboard in 75% of the matched pairs, both firmshad classified boards in 3.8% of the pairs (seeTable 3, panel B). In almost 80% of the pairs,there was no difference in the frequency ofclassified boards. In 13.4% of the pairs only theoffender had a classified board and in the remain-ing 7.7% of the pairs, only the control firm had aclassified board. The frequency of classifiedboards is slightly higher among offenders thancontrol firms, although this difference is notstatistically significant. This result fails to rejectthe null hypothesis that the likelihood of account-ing fraud does not depend on whether or not afirm has a classified board.

Our results regarding board ownership of eq-uity suggests that ownership of equity matters:with higher board ownership the likelihood of afirm committing accounting fraud falls. It is inter-esting that the ownership that matters is notaggregate board holdings, but the holdings of thelargest stockholder on the board. In the controlsample, the largest shareholder held on average4.51% more equity than on the offender sample(t=1.793). Having a large shareholder on theboard reduces the probability of accountingfraud. These results are also summarized in Table3, panel B.

To examine whether the presence of account-ing-based management compensation plans af-fects the likelihood of committing accountingfraud, we collected compensation data for thechief executive officer of each offender and con-trol firm in the year before the SEC charges.These data were collected from the relevant SECproxy filing for each firm. We identified compen-sation plans as having accounting-based incen-



tives if they contained bonus plans, profit sharingplans, or incentive stock options that were trig-gered by achieving some level of accounting per-formance. The number of these types of planswas then contrasted across the samples. Theseresults are contained in Table 3, panel B. Themean difference is 0.096 plans, which is consistentwith the argument that accounting-based com-pensation plans increase the likelihood of ac-counting fraud. However, this difference is notstatistically significant (Wilcoxon t-statistic of0.689).

In summary, most forces that are internallydetermined by the structure of the monitoringand reward systems of the firm have no bearingon the probability of accounting fraud, holdingconstant firm size and industry. The only effectthat was marginally significant was equity owner-ship by the largest shareholder on the board. Wefind that large single shareholders impede ac-counting fraud.

EVIDENCE OF EX-POST SETTLING UP

In addition to probing why some firms and notothers commit accounting fraud, we examinewhether or not directors of firms that commitaccounting fraud are disciplined in the market forcorporate directors. Fama (1980) argues that themanagerial labor market disciplines corporatemanagers who deviate from profit maximization.The ex-post settling up imposed by this marketserves to mitigate agency problems that purport-edly arise from diffuse structures of equity owner-ship. In a recent paper, Kaplan and Reishus(1990) find that directors of companies that cutdividends are less likely to serve on boards ofdirectors in the future, a result that is consistentwith Fama.

To test whether directors of companies chargedwith disclosure violations are disciplined in thelabor market, we examine the number of boardson which directors of offenders served, before andafter the SEC charges. To control for normalchanges in the number of board seats held bydirectors over comparable periods, we also exam-ine this change for the directors of the corre-sponding control firms. Data on other board seatsheld by directors of 62 matched pairs of offendersand control firms are collected from various SECproxy statements. These results are also contained

in Table 3, panel C. In the year before the SECcharges, 523 directors of the 62 offenders held 724other board seats and 543 directors of the corre-sponding 62 control firms held 660 other boardseats listed in proxy statements. Those otherboards were listed on the proxy statements, andof those other boards, 57% of the companies werelisted in Moody’s. We tracked these directors onother boards for three years after the SEC an-nouncement of fraud using the Moody’s manuals.

One year following the SEC charges, the num-ber of other board seats held by directors of theoffenders declined by 15.7%. The correspondingdecline for directors of the control firms was only10%; the difference is statically significant (z-statistic of 2.54). Two years following the SECcharges, directors of the offenders were on 23.6%fewer boards, while those of the control firmswere on 17.4% fewer boards. This difference isstatistically significant (z-statistic of 2.14). Fi-nally, 3 years after the SEC charges, the numberof other directorships held by directors of thecontrol firms had fallen by 28.9%, while those ofthe control firms had fallen by only 23.2%. Thisdifference is also statistically significant (z-statis-tic of 1.78) at the 0.1 level.

These results reject the null hypothesis that thenumber of directorships held by directors of com-panies charged with accounting fraud does notchange relative to the control group followingthese charges. This evidence is consistent with theargument that directors of companies chargedwith accounting fraud suffer a reputational loss inthe market for corporate directors. This reputa-tional loss, which serves as a form of ‘ex-postsettling up,’ is similar to that found by Kaplanand Reishus (1990) for a sample of companiesthat cut dividends during the early 1980s.

An alternative hypothesis is that directors ofpoorly performing firms are disciplined by themanagerial labor market. Because we know thatthe accused sample performed abnormally poorly,this is an hypothesis that deserves examination.We divided the accused sample of directors inhalf based on stock price performance in the 250trading days prior to the SEC announcement ofthe charges. The results are summarized in PanelD of Table 3. We find that directors of poorlyperforming accused firms do lose more director-ships than those of the relatively well performingaccused firms, but both sub-samples have morelosses than the directors of the control sample.



CONCLUSION

This paper empirically investigates the causes andconsequences of accounting fraud. Adopting theperspective that the commission of accountingfraud is governed by rational choice, several hy-potheses are tested. We divide these hypothesesbroadly into external and internal forces thateffect the choice to commit accounting fraud. Wefind evidence suggesting that the cost of valuingassets influences the choice to commit accountingfraud. Furthermore, evidence suggests that theimmediate effect of the instigation of accountingfraud does increase stock prices, while the an-nouncement of charges by the SEC significantlylowers stock prices. Corporate governance struc-tures, auditor reputation, and the use of account-ing based executive compensation schemes appearunimportant in affecting the decision to committhis type of fraud. We do, however, find that theconcentration of ownership in a single individualmitigates the probability of accounting fraud. Fi-nally, directors of firms committing accountingfraud appear to be punished in the manageriallabor market.

In general, we find significant effects from ex-ternal forces, and minimal effects from internalforces. Given that internal compensation andmonitoring plans are choice variables for equityowners, while external forces are market deter-mined, it is not surprising that in equilibrium thechoice variables would have little influence whileexternal forces would drive the choice to commitaccounting fraud.

Acknowledgements

The majority of this work was done while both authors werein the Office of Economic Analysis, Securities and ExchangeCommission. This work does not express the views of eitherthe Commission or the authors’ colleagues at the commission.The authors wish to thank D.B. Johnson, C.M. Lindsay, M.T.Maloney, L. Morweis, J.H. Mulherin, S. Rosenstein, K. Scott,an anonymous referee, and seminar participants at ClemsonUniversity and the Arizona Finance Symposium for commentson earlier drafts.

NOTES

1. Litigation Release No. 9842/December 21, 1982, Se-curities and Exchange Commission v. McCormick &Company, Incorporated, et al. (United States Dis-trict Court for the District of Columbia, Civil Ac-tion No. 82-3614).

2. Karni, supra note 1, at 117.3. The following auditors are considered ‘Big Eight’:

Arthur Andersen, Aurthur Young, Coopers and Ly-brand, Deloitte Haskins & Sells, Ernst & Whinney,Peat Marwick Mitchell, Price Waterhouse, andTouche Ross. Our sample predates the subsequentmergers of Deloitte Haskins & Sells and ToucheRoss, and Aurthur Young and Ernst & Whinney.For our purposes the term ‘Big Eight’ retains mean-ing.

4. One possible problem arises from matching NYSEfirms with non-NYSE firms. NYSE firms arguablyhave more stringent reporting requirements. Thistype of match occurred with only five firms. Wherethis is most important, for the presence of indepen-dent audit committees, those firms were droppedfrom the sample.

5. There existed a tradeoff in the choice of controlfirms. By expanding the industry classification to thethree digit level we would have had more matchcandidates, and could have controlled more exactlyfor firm size. Because we had a prior belief that thetype of business a firm did was more important thanfirm size in determining the proclivity to commitaccounting fraud, we felt it better to err on the sideof size than on line of business.

6. These numbers are average comulative abnormalreturns (CARs).

7. It is possible that three digit classifications are toonarrow to examine this question. Data was aggre-gated to the two digit level and the test statistic wasrecalculated. The resulting Chi-squared statistic was957.24.

8. For a sample of 142 New York Stock Exchangecompanies, Hermalin and Weisbach find that theaverage percentage of directors who were outsidedirectors increased from 37.6% in 1971 to 53.9% in1983. The corresponding percentage for inside direc-tors fell from 49.1% in 1971 to 34.3%. (See Hermalinand Weisbach, 1988).

9. For a rich discussion of this literature, see Watts andZimmerman (1986), supra note 5.

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