Audit Firm Tenure and Financial Restatement_an Analysis of Industry Specialization n Fee Effects

Journal of Accounting and Public Policy 26 (2007) 131–159

www.elsevier.com/locate/jaccpubpol

Audit firm tenure and financialrestatements: An analysis of industry

specialization and fee effects

Jonathan D. Stanley a,1, F. Todd DeZoort b,*

a The University of Alabama, Culverhouse School of Accountancy, 365 Alston Hall,

Tuscaloosa, AL 35487-0220, United Statesb The University of Alabama, Culverhouse School of Accountancy, 328 Alston Hall,

Tuscaloosa, AL 35487-0220, United States

Abstract

This study investigates the relation between audit firm tenure and clients’ financialrestatements. Specifically, we extend the audit tenure literature by assessing restate-ment-based reporting failures using dimensions of auditor expertise and independencepreviously assumed to underlie short and long audit tenure problems. Short tenureexpertise and independence effects are hypothesized using audit firm industry specializa-tion and audit fees as proxies. Long tenure independence effects are hypothesized usingnonaudit fees as a proxy. Using matched-sample logistic regression and 382 companieswith and without financial restatements during 2000–2004, the results support priorfindings by indicating a negative relation between the length of the auditor–client rela-tionship and the likelihood of restatement. For short tenure engagements, we find thatauditor industry specialization and audit fees are negatively related to the likelihood ofrestatement. This result is consistent with concerns about reduced audit quality due toa lack of client-specific knowledge and low audit fees on new audit engagements.

0278-4254/$ - see front matter � 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.jaccpubpol.2007.02.003

* Corresponding author. Tel.: +1 205 348 6694; fax: +1 205 348 8453.E-mail addresses: [email protected] (J.D. Stanley), [email protected] (F. Todd

DeZoort).1 Tel.: +1 205 348 6131.

mailto:[email protected]

mailto:[email protected]

132 J.D. Stanley, F. Todd DeZoort / Journal of Accounting and Public Policy 26 (2007) 131–159

Alternatively, the long tenure results indicate an insignificant relation between nonauditfees and the likelihood of restatement. This finding contradicts independence concernsabout nonaudit fees paid to entrenched auditors.� 2007 Elsevier Inc. All rights reserved.

Keywords: Audit tenure; Financial restatements; Industry specialization; Audit fees; Nonaudit fees

1. Introduction

The objective of this study is to investigate the relation between audit firmtenure and financial restatements. We extend the audit tenure literature byexamining short tenure and long tenure expertise and independence factorspreviously only assumed to underlie the tenure problem. For example, Johnsonet al. (2002) found that short audit tenures were inversely related to clients’abnormal accruals, suggesting that a lack of client-specific knowledge or pres-sure to retain and profit from new clients could undermine audit quality. Gei-ger and Raghunandan (2002) made similar suggestions when interpreting theirfindings of an inverse relation between audit tenure and the likelihood of abankrupt company previously receiving an unqualified audit report. Whileboth studies draw attention to longstanding concern about short tenure effects,there is little direct empirical evidence to support or refute suggestions that theeffects are a function of auditor expertise and/or independence.

Beyond short tenure concerns, interest in long tenure problems continuesdespite a lack of empirical evidence indicating their existence. The GAO(2003) highlighted that pressure to retain longstanding clients and high comfortlevels with client management support calls for mandatory audit firm change tomaintain adequate auditor objectivity and professional skepticism.2 The Chair-man and CEO of TIAA-CREF (Biggs, 2002) argued before the US Senate formandatory audit firm rotation every five to seven years to (1) reduce auditors’financial incentives to subordinate judgment to management, (2) reduce theproblem of cross-selling consulting and other services, and (3) close the ‘‘revol-ving door’’ that allows auditors to move to audit-sensitive positions in auditedcompanies. Despite counterarguments emphasizing the importance of continu-ity and expertise in maintaining audit quality, the Sarbanes-Oxley Act (2002)mandated further study of the audit firm rotation issues.3 This study revisits

2 The GAO (2003) recommended that a decision about mandatory audit firm rotation be deferredto allow time to evaluate the effectiveness of the Sarbanes-Oxley Act’s provisions. However, it alsorecommended that audit committees consider rotating audit firms when there is ‘‘lengthy tenure ofthe auditor of record’’ (p. 51).

3 The Sarbanes-Oxley Act (2002) highlights the difference between audit partner rotation andaudit firm rotation. Specifically, while the Act only requires further study of the audit firm rotationissue, it mandates lead and concurring partner rotation every five years.

J.D. Stanley, F. Todd DeZoort / Journal of Accounting and Public Policy 26 (2007) 131–159 133

the long tenure independence question using nonaudit fees as a proxy for auditfirm independence.

We consider financial restatements to be a unique and substantive domainfor studying the relationship between audit tenure and financial reporting qual-ity for two reasons. First, financial restatements due to error or fraud are defacto reporting failures.4 When audited financial statements are restated, thevalidity of the audit opinion and the underlying audit process are subject toquestion because the originally released information was not free from materialmisstatement. While the extant literature (e.g., Geiger and Raghunandan,2002; Johnson et al., 2002; Chung and Kallapur, 2003; Myers et al., 2003) pro-vides some evidence of tenure effects using alternative quality proxies (e.g.,abnormal accruals, audit opinions), our use of restatements helps address Car-cello and Nagy’s (2004b) call for tenure effects research using objective anddirect measures of financial reporting quality.

Second, financial restatements among public companies represent a costlyproblem in US capital markets. The GAO (2002) estimated that restate-ments involving accounting irregularities increased 145% and cost investorsapproximately $100 billion during the five-year period ending June 30, 2002.The SEC (2002) listed financial restatements as a major factor undermininginvestor confidence in financial reporting and market efficiency. In addition,numerous empirical studies (e.g., Dechow et al., 1996; Turner et al., 2001;Wu, 2003; Palmrose et al., 2004) provide evidence of strong negative mar-ket reactions to restatement announcements. Consideration of factorsunderlying restatement-based reporting failures has brought the externalaudit function under severe scrutiny (AICPA, 2002; GAO, 2002). One spe-cific external audit attribute that has long been associated with auditors’ability to provide adequate assurance is the length of the auditor–clientrelationship (e.g., Mautz and Sharaf, 1961; AICPA, 1978; POB, 2000; Imh-off, 2003).

Using matched samples of restatement and non-restatement companies, theresults indicate a significant inverse relation between audit tenure and the like-lihood of financial restatement. For companies with short audit tenures, themultivariate results indicate that industry specialization and audit fees areinversely related to the likelihood of restatement. Finally, we find no evidencethat nonaudit fees for long audit tenure companies are positively related to thelikelihood of restatement. Collectively, these results contribute to the tenureeffects literature by providing evidence that audit tenure problems documentedin other reporting domains (e.g., accrual accounting, going concern opinions)

4 Not all restatements are a result of errors or fraud in previously reported financial statements.For example, certain changes in accounting principle require restatement of prior period financialstatements. These mandated restatements are beyond the scope of this study because they are notreporting failures.


are robust to financial reporting failures reported in formal restatements. Theseresults also extend the literature by empirically addressing expertise and inde-pendence factors previously only speculated as relevant to tenure-related finan-cial reporting problems.

The remainder of this paper is organized into four parts. Section 2 providesthe hypothesis development. Section 3 describes the study’s design and method.Section 4 presents the results. The final section concludes with discussion of thestudy’s implications and limitations.

2. Literature and hypothesis development

2.1. Audit tenure effects

Previous audit tenure studies (e.g., Geiger and Raghunandan, 2002; John-son et al., 2002; Myers et al., 2003; Mansi et al., 2004; Carcello and Nagy,2004b; Ghosh and Moon, 2005) have predicted early tenure audit and financialreporting problems due to a lack of client-specific knowledge and/or a lack ofindependence due to the auditor’s incentive to maintain new client relation-ships. Studies in this area have used a single audit tenure variable (length ofauditor–client relationship) to evaluate links between audit tenure and variousproxies for audit/financial reporting quality.

For example, several studies provide evidence of a link between the lengthof the auditor–client relationship and accrual quality. Johnson et al. (2002)found that audit tenure of less than three years was associated with higherabsolute levels of unexpected accruals and lower accrual persistence in earn-ings. Similarly, Chung and Kallapur (2003) found that the length of theauditor–client relationship was inversely related to abnormal accruals. Myerset al. (2003) found a positive relation between the length of auditor–clientrelationship and earnings quality (proxied by discretionary and currentaccruals).

The tenure effects literature also extends to audit reporting and regula-tion. Geiger and Raghunandan (2002) used knowledge and independencearguments when questioning whether the length of auditor–client relation-ship was related to the issuance of going concern opinions for bankruptcompanies. Their results indicated that the likelihood of a company receiv-ing a going concern opinion prior to bankruptcy was lower when auditorswere in the initial years of the engagement. Carcello and Nagy (2004b) eval-uated audit tenure affects among companies with fraudulent financial report-ing identified in SEC Accounting and Auditing Enforcement Releases

(AAERs). They find that the likelihood of fraudulent financial reportingis greater in the initial three years of audit tenure. Alternatively, they do


not find that long audit tenure is associated with increased likelihood offraud.

Other recent studies extend the literature by considering market-basedaudit tenure effects. Overall, results in this area suggest that market partici-pants discount the auditor’s monitoring ability during initial audit engage-ment years, consistent with a perception that audit/financial reportingquality increases with tenure. For example, Mansi et al. (2004) documentan inverse relation between firms’ cost of public debt and auditor tenure.Similarly, Ghosh and Moon (2005) show that the impact of reported earningson (1) stock returns, (2) stock rankings, and (3) analysts’ one-year-aheadearnings forecasts is directly related to the length of the auditor–clientrelationship.

We extend the literature involving the length of the auditor–client relation-ship to examine whether previous findings are robust in the context of financialrestatements. Specifically, prior to specific assessment of potential factorsunderlying audit tenure effects, we predict an overall inverse relation betweenaudit tenure and client financial restatement. Stated formally:

H1: The likelihood of financial restatement is inversely related to thelength of the auditor–client relationship.

2.2. Audit firm expertise

While prior studies discuss audit expertise and independence as potentialunderlying causes of audit tenure effects, empirical evidence is lacking. Wetest the effects of audit firm industry specialization as a dimension ofexpertise that can facilitate audit effectiveness in new engagements. BothAshton (1991) and Bonner and Lewis (1990) found that industry expertisewas positively correlated with an auditor’s ability to identify problemswithin financial statements. Auditors gain industry expertise by workingwith clients from within an industry and by becoming familiar with theindustry’s unique accounting practices and risks. Industry expertise isrelated to auditor tenure because industry expertise can help compensatefor a lack of client-specific knowledge. More specifically, to the extent thata new audit client operates in an industry where the audit firm has exten-sive experience and knowledge, the engagement learning curve should beless pronounced.

Theories explaining the effect of industry expertise on auditor judgment anddecision-making (JDM) remain largely untested at the audit firm level (Gram-ling and Stone, 2001). However, several studies (e.g., Carcello and Nagy,2004a; Krishnan, 2003) posit that increases in industry expertise at the auditfirm level should be related to increases in industry expertise at the individ-ual auditor level. Industry specialist firms are likely to have developed


industry-specific training materials, databases, checklists, and other audit sup-port aids (Carcello and Nagy, 2004a; Krishnan, 2003).

The empirical literature is starting to provide evidence of a positive linkbetween industry specialization at the audit firm level and financial reportingquality. For example, Dunn and Mayhew (2004) found a positive associa-tion between audit firm industry specialization and client disclosure qualityproxied by analysts’ evaluations in AIMR reports. Carcello and Nagy(2004a) found a negative association between audit firm industry specializa-tion and client financial fraud disclosed in SEC AAERs. Furthermore, theextant literature provides evidence that clients of industry specialist auditfirms have larger earnings response coefficients (e.g., Balsam et al., 2003)and lower levels of discretionary accruals (e.g., Balsam et al., 2003; Krish-nan, 2003). These studies’ results support the prediction of a significant rela-tion between industry specialization and the likelihood of financialrestatement. Specifically, audit firms that enter new audit engagements withrelatively high industry specialization should be able to provide higher auditquality that lessens the chance of financial restatements. Stated formally (inalternative form):

H2: For companies with short audit tenures, the likelihood of financialrestatement is inversely related to the audit firm’s industry specialization.

2.3. Audit firm independence

Accounting policymakers (e.g., GAO, 2003; SEC, 2000, 2003) haveargued that auditor independence is affected by audit tenure. Consistentwith this concern, a number of studies (e.g., Simon and Francis, 1988; Ettr-edge and Greenberg, 1990; Deis and Giroux, 1996; Sankaraguruswamy andWhisenant, 2005) have found that auditors frequently engage in low ballingtactics where they offer audit services at prices substantially below marketvalue or cost to attract new clients. Theoretically, future quasi-rents earnedby incumbent auditors justify and offset losses on the early engagements(DeAngelo, 1981).

Despite a lack of supportive evidence (Watkins et al., 2004), regulators havebeen critical of this practice because of the perceived independence problems itcreates. For example, the Commission on Auditors’ Responsibilities (1978)issued a report (the Cohen Report) arguing that performing audit services belowcost with the intention of recouping upfront losses at a later date is similar to per-forming audit services for a client that has unpaid audit fees outstanding(AICPA, 1978). This regulatory concern is supported by findings from studiesexamining the psychology of sunk costs. Simon and Francis (1988) suggest thatsunk costs resulting from lowball audit fees create an escalated commitment to


continue the engagement in an attempt to recover the initial loss in later years.5

This commitment hinders auditor independence above and beyond the economicbond resulting from future quasi-rents.

The empirical literature provides evidence of tenure effects in the initial yearsof auditor–client relationships. For example, adverse tenure effects documentedby Geiger and Raghunandan (2002), and Johnson et al. (2002) lessened whenauditor–client relationships exceeded five years and three years, respectively.These findings would be expected if such adverse short tenure effects were afunction of lowball audit fees that reverted to normal levels after the initialaudit years (Simon and Francis, 1988). Accordingly, we hypothesize an associ-ation between audit fees and the likelihood of financial restatement by a com-pany with a short audit firm tenure. Specifically, relatively low audit feesshould be positively related to the likelihood of restatement in the initial yearsof the auditor–client relationship. Stated formally:

5 Simlowbal

6 Madecadeaudito(US Se

H3: For companies with short audit tenures, the likelihood of financialrestatement is inversely related to audit fees.

While only short tenure effects have emerged in the empirical literature, con-cerns about long tenure independence problems persist. For example, regula-tors and interest groups argue that disproportionately large nonaudit feesthat accumulate with audit tenure can diminish audit quality because they cre-ate incentive for auditors to acquiesce to client pressure (e.g., ConferenceBoard, 2003; POB, 2000). The Sarbanes-Oxley Act (2002) addressed theseentrenchment concerns by limiting the consulting services audit firms can pro-vide their clients and by requiring study of the mandatory audit firm rotationissue.6 In its commissioned study, the GAO (2003) supported an earlier Con-ference Board (2003) call for audit committees to carefully consider auditorrotation when the auditor has long tenure and/or when the audit firm provides‘‘significant nonaudit services’’ to the company. While noting the potentiallyhigh financial and institutional knowledge costs of mandatory rotation, theGAO acknowledged that both auditors under tenure limits and new auditorscan bring a needed ‘‘fresh look’’ to financial reporting issues that long tenureauditors may lack.

The extant literature provides mixed evidence about the associationbetween audit and nonaudit fees and financial reporting quality. However,no study has empirically examined the long audit tenure/nonaudit service

on and Francis (1988) explain that audit fee data can only be used for an indirect test forling. Proprietary audit cost and profit margin data are required for direct testing.ndatory audit firm rotation in the US has been discussed periodically over the past severals. For example, the Metcalf Committee Report suggested in 1976 that the independence ofrs would be enhanced if audit firms were required to rotate clients after a set number of yearsnate, 1976).


link of concern to policymakers and regulators. Frankel et al. (2002) founda positive (negative) relationship between nonaudit (audit) fees and the like-lihood of reporting small earnings surprises and various abnormal accrualsmeasures. As a result, they suggested the need to investigate the relationshipbetween audit (nonaudit) fees and financial restatements. Alternatively, anumber of studies (e.g., Ashbaugh et al., 2003; Chung and Kallapur,2003; Raghunandan et al., 2003; Reynolds et al., 2004) fail to find signifi-cant links between fees and reporting quality. This study extends the litera-ture by specifically examining nonaudit fees and lengthy auditor–clientrelationships. Given persistent concerns that nonaudit fee entrenchment isassociated with decreased financial reporting quality for long audit tenures,we expect the likelihood of financial restatement to be a function of thenonaudit fees earned by audit firms with long tenures. Stated formally,

H4: For companies with long audit tenures, the likelihood of financialrestatement is positively related to nonaudit fees.

3. Design and sample

3.1. Model specification

We use a series of logistic regression models to test the hypotheses. To testthe first hypothesis, the following model was estimated to assess whether thetenure effect findings in prior audit tenure studies (e.g., Geiger and Raghunan-dan, 2002; Johnson et al., 2002; Myers et al., 2003; Carcello and Nagy, 2004b)are robust in the context of restatements:

RSTMT ¼ b1TENUREþ b2INDSPEC þ b3ADTFEE

þ b4NONADTFEEþ b5ZFC þ b6AGE

þ b7MERGER þ e ð1Þ

where RSTMT equals 1 if financial statements were restated, else 0; TENUREequals the length of the auditor–client relationship (in years); INDSPEC equalsthe audit firm’s industry marketshare based on total sales audited within 2-digitSIC code; ADTFEE equals the natural log of total audit fees; NONADTFEEequals the natural log of total nonaudit fees; ZFC equals Zmijewski’s (1984)financial condition index; AGE equals the length of time as a publicly-tradedcompany (in years); and MERGER equals 1 if the company was involved inmerger activity, else 0.

Similar to several prior matched-sample studies in accounting (e.g., Archam-beault and DeZoort, 2001; Carcello and Nagy, 2004b; Menon and Williams,2004), we estimate no-intercept models that address the independence assump-tion violation inherent in matched-sample designs. Hosmer and Lemeshow(2000) highlight that matched pair designs violate general logistic regression


assumptions because they involve creation of matched observations that are notindependent. Therefore, we calculated paired differences (case minus control) forall variables and estimated no-intercept models using a constant (reflecting thedifference between each matched case and control company) as the dependentvariable.7

Although restatements often involve multiple years, we measured all vari-ables in the first year restated. This approach is consistent with prior research(e.g., Richardson et al., 2003) and with the study’s objective to investigatefinancial reporting quality at the time the problems first arose, not when theproblems were subsequently disclosed.

TENURE was calculated using COMPUSTAT and annual proxy state-ments.8 We reviewed proxy statements to minimize measurement error associ-ated with COMPUSTAT tenure measures. For example, COMPUSTAT mayunderstate tenure because it records auditor data for companies only after theybecome public. Conversely, COMPUSTAT may overstate tenure because itcan record up to three years of financial data (as usually presented in the S-1registration statement and initial 10-K filing) for new IPO companies addedto the database. Thus, first year auditors reporting on multiyear comparativestatements for an IPO company may appear to have a three-year audit tenure.9

Auditor changes attributable to audit firm mergers were coded as a continua-tion of the prior auditor.

Several control variables are included in the model to enhance its ability todetect tenure differences between the restatement and control samples, reducethe possibility that the tenure results are a function of correlated omitted vari-ables, and enhance comparability with prior studies and our subsequent shorttenure and long tenure models. First, we used an industry marketshare proxyfor INDSPEC to control for differences in industry specialization among auditfirms. Similar to prior studies (e.g., Carcello and Nagy, 2004a; Krishnan, 2003;Dunn and Mayhew, 2004), industry marketshare was calculated for each auditfirm as the revenue of audit clients within a specific industry (denoted by 2-digit

7 Traditional logit models (with intercept) produced qualitatively similar results to those reportedin the paper.

8 We used proxy statements to calculate TENURE if sufficient information was publiclydisclosed. Otherwise, TENURE was calculated using COMPUSTAT. TENURE was truncated asof 1974 to minimize the influence of extreme observations and because COMPUSTAT does notcontain auditor/opinion data for years prior to 1974. AGE also was truncated as of 1974 to beconsistent with the TENURE calculation.

9 Mansi et al. (2004) note similar issues regarding tenure calculations based on COMPUSTATdata.


SIC code) divided by the total revenue of all audited companies within thatindustry.10 Second, ADTFEE and NONADTFEE were used because of con-cern about the impact of audit and nonaudit fees on auditor independenceand audit quality (e.g., SEC, 2000). Fee data were collected from annual proxystatements corresponding to the first year restated.11 Third, we included afinancial condition measure (ZFC) to control for differences in distress levelsbetween the restatement and control samples because management’s incentiveto manipulate financial statements is likely associated with the health of thecompany (Summers and Sweeney, 1998). Similar to prior studies (e.g., Carcelloand Neal, 2000, 2003), we computed the ZFC index using coefficients fromZmijewski’s (1984) weighted probit model, where higher index values representgreater financial distress levels. AGE was used because company age is likelycorrelated with the length of the auditor–client relationship (i.e., a one-yearincrease in tenure is, by default, a one-year increase in age). Finally, we con-trolled for the presence of merger activity because Kinney et al. (2004) foundthat acquisition activity was positively related to the likelihood of restatement.Following Kinney et al. (2004), MERGER was coded as a one if COMPU-STAT footnote data indicated the presence of merger activity, and zerootherwise.12

To test H2 and H3 (H4), we estimated the following logit model using amatched sample of restatement companies and control companies with short(long) audit tenures and publicly available fee data to test for differences inaudit firm industry marketshare and audit fees (nonaudit fees):

RSTMTðST=LTÞ ¼ b1INDSPECþ b2ADTFEE

þ b3NONADTFEE þ b4ZFC þ b5AGE

þ b6MERGER þ e ð2Þ

10 The portfolio share ratio is an alternative to the industry marketshare ratio. The portfolio shareapproach focuses on an audit firm’s concentration in a specific industry and has a denominatorequal to the sum of all clients’ revenue. We did not use this alternative measure because it is highlycorrelated with industry size and it tends to ignore smaller industries (Neal and Riley, 2004). Inaddition, studies using the portfolio approach tend to lack variation in industry expertise whencompanies are matched on size and industry because industry size is highly correlated with thismeasure.11 In 2000, the SEC required all registrants to disclose the most recent year’s audit and nonaudit

fees in annual proxy statements filed on or after February 5, 2001. Therefore, fee data is onlyavailable for companies that restated 2000 financial statements or later.12 We also considered a variety of alternative growth, complexity, risk, and governance control

proxies that appear in other related studies. Specifically, we controlled for book-to-market,earnings-to-price, total asset change (%), presence of foreign operations, number of businesssegments, operating cash flow effects, number of audit committee meetings, and board size. None ofthese control variables affected the significance of our hypothesized variables.


where RSTMT(ST), for short (63 years) tenure firms equals 1 if financial state-ments were restated, else 0; and RSTMT(LT), for long (P5 years) tenure firmsequals 1 if financial statements were restated, else 0.

The remaining variables are as previously defined. While the literature failsto provide clear consensus on specific short tenure and long tenure cutoffs, weinitially define short tenure in Model 2 as less than or equal to three years to beconsistent with prior studies (e.g., Stice, 1991; Heninger, 2001; Geiger and Rag-hunandan, 2002; Johnson et al., 2002). In addition, we initially set the long ten-ure threshold in Model 2 at five years to be consistent with Myers et al. (2003)and Geiger and Raghunandan (2002).13 Subsequent sensitivity analysis willevaluate the robustness of our results to alternative short and long tenuredefinitions.

3.2. Sample development

Table 1 provides an overview of the restatement companies. The restatementsample was identified using a Boolean search (using the term ‘‘restatementnear(5) financial’’) of annual SEC filings within 10-K Wizard for the five-yearperiod 1/1/2000–12/31/2004. As indicated in Table 1, Panel A, the search iden-tified 1599 unique company observations. For companies with restatementscovering multiple years, we focused data collection and analysis on the firstyear of reported misstatement. We removed 756 companies with technicalrestatements to focus the sample on companies with annual restatementsinvolving intentional or unintentional misapplications of GAAP. We alsodeleted 288 companies that did not use a Big 5/4 audit firm in the first yearof restatement. The focus on Big 4/5 auditors helps control for possible auditquality differences between Big 5/4 and non-Big 5/4 audit firms (e.g., Beckeret al., 1998) and manage the lack of tenure and industry specialization dataavailable for many non-Big 5/4 firms. Three hundred fifty-one (351) companieswere removed because of missing data (e.g., audit fees, nonaudit fees, and ZFCcomponents). Finally, we removed 13 companies that had no reasonable non-restatement control company match (matching criteria described below). Thesample screening process resulted in a final sample of 191 restatementcompanies.

Table 1, Panel B, describes the distribution of restatement companies by firstfiscal year restated. The concentration of sample companies restating annualfinancial statements originally filed during 2000 or 2001 is due to the large

13 Myers et al. (2003, p. 785) described ‘‘three stages of the auditor–client relationship’’, using 5+years as the long tenure stage, 3–4 years as a middle tenure stage, and 1–2 years as the short tenurestage. Their justification for this partitioning included reference to Congressional focus on fiveyears as a potential target for mandatory firm rotation. Geiger and Raghunandan (2002) found thatearly tenure audit reporting failures ‘‘appear to taper off’’ after five years.

Table 1Sample description

Panel A: Restatement sample development

Initial number of unique company restatements 1,599Less: Interim and technical restatements (756)

Restatements involving non-Big 5/4 auditors (288)Companies lacking proxy or financial statement data (351)Companies without a suitable match (13)

Final sample 191

First fiscal yearrestated

Full sample Short tenuresample (63 years)

Long tenuresample (P5 years)

Panel B: Distribution by first fiscal year restated

2000 74 (39%) 17 (34%) 41 (39%)2001 69 (36%) 17 (34%) 42 (40%)2002 36 (19%) 13 (26%) 15 (14%)2003 11 (6%) 3 (6%) 5 (5%)2004 1 (1%) 0 (0%) 1 (1%)Total 191 50 104

Industry Full sample Short tenuresample (63 years)

Long tenuresample (P5 years)

Panel C: Distribution by industry

Computers 39 (20%) 14 (28%) 19 (18%)Durable manufacturers 43 (23%) 16 (32%) 18 (17%)Extractive 5 (3%) 1 (2%) 2 (2%)Financial 0 (0%) 0 (0%) 0 (0%)Pharmaceuticals 11 (6%) 1 (2%) 9 (9%)Retail 22 (12%) 4 (8%) 13 (13%)Services 25 (13%) 5 (10%) 13 (13%)Transportation 23 (12%) 8 (16%) 14 (13%)Utilities 8 (4%) 0 (0%) 7 (7%)Other 15 (8%) 1 (2%) 9 (9%)

Total 191 50 104

Mean Med. Std. Min. Max.

Panel D: Summary financial statistics for restatement companies

Total assets ($ MM)Full sample 1619.65 252.87 6422.94 4.97 73501.00Short tenure sample (63 years) 676.70 251.11 1355.15 4.97 6260.59Long tenure sample (P5 years) 1696.13 296.37 4814.28 5.87 42227.00

Total sales ($ MM)Full sample 919.02 177.71 2776.70 0.04 30293.00Short tenure sample (63 years) 480.24 144.24 844.86 1.72 4820.83Long tenure sample (P5 years) 1065.78 256.00 3254.19 0.04 30293.00

Net income ($ MM)Full sample �90.69 �3.45 512.85 �5487.92 1232.00Short tenure sample (63 years) �138.42 �16.32 380.43 �2351.75 34.39Long tenure sample (P5 years) �92.75 �0.13 621.74 �5487.92 612.00


Table 1 (continued)

Mean Med. Std. Min. Max.

Operating cash flow ($ MM)Full sample 72.87 7.50 357.31 �712.54 3681.00Short tenure sample (63 years) �0.54 2.24 76.42 �301.73 169.68Long tenure sample (P5 years) 72.63 10.31 264.00 �712.54 1991.59

Tenure (years) Full restatement sample Full control sample

Panel E: Tenure distribution

1 38 (20%) 23 (12%)2 13 (7%) 10 (5%)3 14 (7%) 14 (7%)4 15 (8%) 13 (7%)5 9 (5%) 14 (7%)6 16 (8%) 11 (6%)7 14 (7%) 13 (7%)8 8 (4%) 8 (4%)9 16 (8%) 3 (2%)10+ 48 (25%) 82 (43%)Total 191 191

This table presents descriptive information for the full sample of restatement companies, and for theshort and long tenure subsamples. Short tenure (Long tenure) is defined as an auditor–client rela-tionship lasting less than or equal to three years (at least five years). Panel A presents the sampledevelopment process. Panel B presents the distribution of restatement companies by the first fiscalyear restated. Panel C presents the distribution of restatement companies by industry. FollowingRaghunandan et al. (2003), industries are defined using SICs as follows: computers (7370–7379, 3570–3579, 3670–3679), durable manufactures (3000–3999, excluding 3570–3579 and 3670–3679), extrac-tive (2900–2999, 1300–1399), financial (6000–6799), pharmaceuticals (2830–2836), retail (5000–5999),services (7000–8999, excluding 7370–7379), transportation (4000–4899), utilities (4900–4999). PanelD presents summary financial information for the restatement (sub)samples. Panel E presents fre-quency distributions for auditor tenure for the full sample of restatement and control companies.


percentage of filings restating multiple years and our focus on the first yearrestated. Table 1, Panel C, presents the industry distribution results. Similarto Raghunandan et al. (2003), the restatements are concentrated in the Com-puters and Durable Manufacturers industries.14 Panel D of Table 1 presentssummary financial statistics for the sample. The mean (median) total assetsfor the full sample is $1,619.65 ($252.87) million.15

14 Financial institutions are not represented in the final sample because they generally lackclassified balance sheet information needed for the computation of the ZFC control variable (e.g.,current assets and current liabilities).15 The extant restatement literature in accounting reveals considerable variance in both the

number of restatements identified and the size of restatement firms across sample time period andselection criteria. For example, while our sample firms are similar in size to the sample firms inKinney et al. (2004), Palmrose and Scholz (2004), Palmrose et al. (2004), and Desai et al. (2006),they are smaller than those examined by Raghunandan et al. (2003). Accordingly, we suggest theneed for caution when generalizing results across restatement studies.


To test H1, we created a matched sample by matching each restatementcompany with a non-restatement control company based on year (the firstyear restated in the Form 10-K or Form 10-K/A), industry classification(SIC), company size (total assets), and audit firm size (Big 4/5) to controlfor systematic temporal and cross-sectional differences.16 The control com-pany’s Form 10-K corresponding to the year on which the restatement andcontrol company were matched, and all subsequent annual filings, were thenreviewed to ensure that the match year’s Form 10-K had not been restated.Table 1, Panel E, reports tenure frequency distributions for the full sample ofrestatement and control companies used to test H1. Although restatementsoccur across a range of audit tenures, the results indicate a relatively largenumber of restatements in the first year of audit tenure. The frequency resultsalso show a relatively large number of control companies with extended (10+years) audit tenures.

To test the short tenure hypotheses (H2 and H3), we matched 50 restate-ment companies with audit tenures of three years or less with non-restate-ment companies with audit tenure of three years or less. For the longtenure hypothesis (H4), 104 restatement companies with audit tenures ofat least five years were matched with non-restatement companies with audittenures of five years or more. The matching criteria related to fiscal year,industry, company size, and auditor size also were imposed on thesesubsamples.17

4. Results

4.1. Overall tenure results

The results in Table 2, Panel A, present descriptive statistics for the 382companies (191 restatement and 191 control) used to test H1. A t-test indicates

16 The matching protocol involved selecting a non-restatement company from the same four-digitSIC and within 15% in total assets. If no control company met these criteria, we then used three-digit or two-digit SIC match, respectively, and a maximum size deviation of ±30%. The restatementcompany was dropped from the sample if no control company was within ±30% of total assets andfrom the same two-digit SIC. Of the 191 restatement companies, 104, 25, and 62 were matched atthe four-digit, three-digit, and two-digit SIC level, respectively. 173 (18) were matched on totalassets within ±15% (±30%).17 Audit firm tenure and company size (total assets) were not significantly different between

restatement and non-restatement companies for any of the short and long tenure subsamples(p > 0.10 in all cases). Of the 50 short tenure restatement companies, 14, 11, and 25 were matched atthe four-digit, three-digit, and two-digit SIC level, respectively. 30 (20) were matched on total assetswithin ±15% (±30%). Of the 104 long tenure restatement companies, 48, 14, and 42 were matchedat the four-digit, three-digit, and two-digit SIC level, respectively. 90 (14) were matched on totalassets within ±15% (±30%).

Table 2

Overall tenure results

Restatement sample (n = 191) Control sample (n = 191) Difference

Mean Med. Std. Mean Med. Std. Pred. t

Panel A: Univariate results

TENURE 7.684 6.000 7.342 10.343 7.000 8.528 (�) �3.80***

INDSPEC 0.210 0.193 0.075 0.208 0.202 0.069 (�) 0.37

ADTFEE 12.605 12.489 1.042 12.436 12.324 0.923 (?) 2.83***

NONADTFEE 12.015 12.360 2.611 12.030 12.445 2.553 (?) �0.06

ZFC �1.534 �2.238 3.165 �2.466 �2.758 1.963 (+) 3.67***

AGE 11.529 8.000 8.687 12.005 9.000 9.281 (�) �0.62

MERGER 0.262 0.000 0.441 0.157 0.157 0.365 (+) 2.82***

Variable (1) (2) (3) (4) (5) (6) (7)

Panel B: Correlations among independent variables (Pearson above diagonal, Spearman below)

(1) TENURE �0.062 0.119* 0.018 �0.137* 0.561*** �0.089

(2) INDSPEC �0.061 �0.091 0.020 0.001 �0.062 �0.077

(3) ADTFEE 0.147** �0.053 0.267*** 0.182** 0.086 0.072

(4) NONADTFEE 0.020 0.123* 0.313*** 0.075 �0.036 �0.034

(5) ZFC �0.192*** 0.008 0.127* �0.028 �0.080 0.081

(6) AGE 0.526*** �0.010 0.104 �0.046 �0.112 0.019

(7) MERGER �0.079 �0.091 0.047 0.036 0.094 �0.002

Variable Pred. Coefficient v2

Panel C: Logistic regression results

TENURE H1 (�) �0.074 10.70***

INDSPEC (�) 1.082 0.41

ADTFEE (?) 0.523 5.81**

NONADTFEE (?) �0.041 0.60

ZFC (+) 0.118 4.65**

AGE (�) 0.031 2.55

MERGER (+) 0.559 2.91**

This table presents univariate and multivariate results from the full sample analysis. *,**,*** represent significance at the .10, .05,

and .01 level (one-tailed for results in the predicted direction), respectively. The variables are defined as follows:

RSTMT = 1 if financial statements were restated, else 0;

TENURE = length of the auditor–client relationship (in years);

INDSPEC = audit firm’s industry marketshare based on total sales audited within 2-digit SIC code;

ADTFEE = natural log of total audit fees;

NONADTFEE = natural log of total nonaudit fees;

ZFC = Zmijewski’s (1984) financial condition index;

AGE = length of time as a publicly-traded company (in years); and

MERGER = 1 if the company was involved in merger activity, else 0.

Panel A presents the mean, median, and standard deviation for the test variable of interest, TENURE, and the control variables.

The mean log audit fees equal $298,045 (restatement sample) and $251,702 (control sample) in mean raw audit fees. The mean log

nonaudit fees equal $165,215 (restatement sample) and $167,711 (control sample) in mean raw nonaudit fees. The tests of

differences in means are based on paired-sample t-tests. Nonparametric Wilcoxon rank sum tests yield qualitatively similar results

in all cases. Panel B presents Pearson (Spearman) correlations among the test and control variables above (below) the diagonal.

Panel C presents estimation results from the following matched-sample logistic regression model (Model 1):

RSTMT ¼ b1TENUREþ b2INDSPECþ b3ADTFEEþ b4NONADTFEEþ b5ZFCþ b6AGEþ b7MERGERþ e

Model v2 = 37.290; p < 0.0001. Max-rescaled R2 = 23.65%. n = 191 matched pairs.



that the restatement companies have a shorter mean audit tenure (7.684 years)than the non-restatement companies (10.343 years; p < 0.01).18 In addition, thecontrol variable results reveal that restatement companies pay higher audit fees(p < .01), have greater financial distress levels (p < 0.01), and engage in moremerger activity (p < 0.01) than non-restatement companies. Alternatively, thematched companies are similar in age, auditor industry specialization, andnonaudit fees (p > 0.10 for all comparisons).

Table 2, Panel B, presents correlation results among TENURE and thecontrol variables used in the multivariate analysis. Not surprising, the larg-est correlation is between TENURE and AGE (Pearson q = 0.561,p < 0.01). Otherwise, the correlation coefficients are generally small, suggest-ing that multicollinearity is not a problem. Furthermore, we estimated var-iance inflation factors (VIFs) for Model 1 and found the largest to be 1.53,well below the 10.00 threshold of concern recommended by Neter et al.(1996).

The logit results in Panel C of Table 2 indicate a significant TENUREmodel (v2 = 37.290; p < 0.0001). As hypothesized, the results indicate a signif-icant negative relation between TENURE and the likelihood of financialrestatement (p < 0.01).19 Consistent with the univariate analysis, the ADTFEE,ZFC, and MERGER coefficients are significant (p < 0.05) and in the expecteddirection, while the INDSPEC, NONADTFEE, and AGE coefficients areinsignificant.

Collectively, these results provide support for H1 and suggest that prior ten-ure findings (e.g., Geiger and Raghunandan, 2002; Johnson et al., 2002; Myerset al., 2003; Carcello and Nagy, 2004b) generalize to financial restatement con-texts. Furthermore, our findings of (1) larger audit fees, (2) similar nonauditfees, and (3) increased merger activity for the restatement companies withinour full sample is consistent with results documented in other recent restate-ment studies (e.g., Raghunandan et al., 2003; Kinney et al., 2004). However,the lack of significance for INDSPEC is inconsistent with evidence suggestingthat auditor industry specialization is positively related to financial reportingquality (e.g., Balsam et al., 2003; Krishnan, 2003).

18 One-tail p-values are reported for tests involving directional predictions with results in theexpected direction.19 A number of tests were conducted to identify the effects of possibly influential observations. For

example, we winsorized the continuous variables at the top and bottom one percent of the sampledistribution. All results were qualitatively similar using these modified samples in the univariate andmultivariate analysis. We also examined logistic regression diagnostic statistics (e.g., leverage valuesand DFBetas) and found no observations exerting undue influence on the hypothesis tests using theprocedures outlined by Neter et al. (1996).


4.2. Short tenure results

Table 3 provides the results for H2 and H3, which predict that the likeli-hood of restatement by a short audit tenure company is inversely related tothe audit firm’s industry specialization and audit fees, respectively. The uni-variate test results in Table 3, Panel A, show that the audit firms representedin the short tenure restatement sample have less industry specialization thanthe audit firms in the control sample (p < 0.05). Consistent with the full sam-ple analysis discussed previously, the short tenure restatement firms exhibitgreater financial distress than their control sample counterparts (p < 0.01).No significant univariate differences emerge for ADTFEE, NONADTFEE,AGE, or MERGER.

Table 3, Panel B, presents correlations among the test and control variablesincluded in Model 2. The largest correlations are between INDSPEC andADTFEE (Pearson q = �0.348, p < 0.05) and ZFC and ADFEE (Pearsonq = 0.366, p < 0.01). Analysis of VIFs for Model 2 indicates that the largestequals 1.29. Overall, this evidence suggests that multicollinearity is not aproblem.

The logit results in Table 3, Panel C, indicate a significant short tenuremodel (v2 = 15.666; p = 0.016). Consistent with H2 and the univariate results,the INDSPEC coefficient is negative and statistically significant (p < 0.05),suggesting the benefits of industry specialization for overcoming a lack of cli-ent-specific knowledge in initial audit engagement years.20 In addition, aftercontrolling for auditor industry specialization and financial distress, the resultsindicate a significantly negative ADTFEE coefficient (p < 0.05). This findingprovides support for the H3 prediction of an inverse relation between audit feesand likelihood of restatement, and is consistent with concerns that lowballaudit pricing strategies jeopardize auditor independence and audit quality onnew engagements.

4.3. Long tenure results

The results in Table 4 do not support our H4 prediction of a positive rela-tion between nonaudit fees and the likelihood of restatement for long audittenure companies. The t-test results in Panel A of Table 4 indicate the restate-ment companies’ mean nonaudit fee ($207,109) is not statistically differentthan the non-restatement companies’ mean nonaudit fee ($216,642;p > 0.10). In contrast, the results reveal that the restatement companies pay

20 One of the industries represented in our short tenure sample has fewer than 30 companies. Theresults are qualitatively similar when the one matched-pair within this industry is dropped,suggesting small industries do not influence the industry specialization results (Carcello and Nagy,2004a).

Table 3

Short tenure industry specialization and audit fee results




INDSPEC 0.189 0.188 0.061 0.213 0.207 0.068 (�) �1.88**

ADTFEE 12.328 12.201 0.849 12.391 12.420 0.805 (�) �0.52

NONADTFEE 11.134 12.031 3.260 11.397 12.364 3.648 (?) �0.40

ZFC �0.481 �2.201 4.332 �2.235 �2.726 2.167 (+) 2.76***

AGE 8.740 5.000 7.979 9.180 6.000 8.392 (�) �0.29

MERGER 0.280 0.000 0.454 0.280 0.000 0.454 (+) 0.00

Variable (1) (2) (3) (4) (5) (6)


(1) INDSPEC �0.348** �0.279** �.122 0.041 �0.064

(2) ADTFEE �0.309** 0.229 0.366*** 0.025 0.236*

(3) NONADTFEE �0.195 0.298** 0.121 0.072 0.028

(4) ZFC �0.203 0.307** 0.127 0.054 0.112

(5) AGE 0.068 0.037 �0.107 �0.088 0.258*

(6) MERGER �0.111 0.240* �0.072 0.038 .278*



INDSPEC H2 (�) �8.455 3.75**

ADTFEE H3 (�) �1.090 3.51**

NONADTFEE (?) �0.048 0.39

ZFC (+) 0.312 5.70***

AGE (�) �0.014 0.17

MERGER (+) 0.157 0.09

This table presents univariate and multivariate results from the short tenure (63 years) sample analysis. *,**,*** represent

significance at the .10, .05, and .01 level (one-tailed for results in the predicted direction), respectively. The variables are defined

as follows:







MERGER = 1 if the company was involved in merger activity, else 0.

Panel A presents the mean, median, and standard deviation for the test variables of interest, INDSPEC and ADTFEE, and

the control variables. The mean log audit fees equal $225,934 (restatement sample) and $240,626 (control sample) in mean

raw audit fees. The mean log nonaudit fees equal $68,460 (restatement sample) and $89,054 (control sample) in mean raw

nonaudit fees. The tests of differences in means are based on paired-sample t-tests. Nonparametric Wilcoxon rank sum tests

yield qualitatively similar results in all cases. Panel B presents Pearson (Spearman) correlations among the test and control

variables above (below) the diagonal. Panel C presents estimation results from the following matched-sample logistic

regression model (Model 2):

RSTMT ¼ b1INDSPECþ b2ADTFEEþ b3NONADTFEEþ b4ZFCþ b5AGEþ b6MERGERþ e

Model v2 = 15.666; p = 0.016. Max-rescaled R2 = 35.86%. n = 50 matched pairs.



higher mean audit fees ($329,062) than the non-restatement companies($268,606; p < 0.01).

The correlation results presented in Table 4, Panel B, show relatively smallassociations among the test and control variables included in Model 2, with theexception of ADTFEE and NONADTFEE (Spearman q = 0.408, p < 0.01).As with the other models, analysis of VIFs suggested that multicollinearitywas not a problem.21

The logit results in Table 4, Panel C, indicate that the long tenure nonauditfee model is significant (v2 = 14.295; p = 0.027). Similar to the univariateresults, the multivariate results do not show a significant coefficient for NON-ADTFEE (p > 0.10). The significant positive coefficients for ADTFEE(p < 0.01) and MERGER (p < 0.05) suggest higher audit fees and a greaterlikelihood of merger activity for long tenure restatement companies. Whilecontrary to the short tenure prediction and findings, the long tenure auditfee result is consistent with the results in Kinney et al. (2004). Specifically, Kin-ney et al. (2004) found that restatement firms paid larger audit fees than non-restatement firms and conjectured that the larger fees could reflect auditors’response to heightened ex ante misstatement risk (i.e., additional audit effortand/or fee premiums). When considered with the significant short tenure indus-try specialization (H2) result, the insignificant long tenure INDSPEC effecthelps highlight the importance of industry specialization in managing a lackof client-specific knowledge inherent in new audit engagements.

4.4. Sensitivity analysis

We conducted a series of sensitivity tests to evaluate the robustness of ourresults. We first examined the overall tenure results that support H1. To eval-uate whether the TENURE results are capturing client characteristics linked toboth auditor changes and financial reporting quality (e.g., DeFond and Subr-amanyam, 1998), we re-estimated Model 1 after removing restatement andcontrol companies with audit tenures of one year or less (i.e., first-year auditengagements). The results (not tabulated) show that TENURE remains nega-tive and significant (coefficient = �0.051, p < 0.05) after deleting the initial yearaudit engagement companies. We also dropped AGE from the model becauseof the correlation between TENURE and the number of years the companyhas been publicly traded. Again, we find that TENURE remains negativeand significant (coefficient = �0.054, p < 0.01).

21 Given concern about correlation between audit and nonaudit fees (e.g., Whisenant et al., 2003),we also alternatively dropped ADTFEE and NONADTFEE from the models to test whether feecorrelations affect the multivariate results reported throughout the paper. The revised NONADT-FEE (ADTFEE) results are qualitatively similar to those reported when ADTFEE (NONADT-FEE) is excluded.

Table 4

Long tenure nonaudit fee results




NONADTFEE 12.241 12.437 2.398 12.286 12.357 1.645 (+) �0.21

INDSPEC 0.217 0.196 0.081 0.214 0.219 0.070 (�) 0.31

ADTFEE 12.704 12.634 1.022 12.501 12.378 0.904 (?) 2.79***

ZFC �2.015 �2.261 2.519 �2.110 �2.748 3.469 (+) 0.22

AGE 12.913 10.000 8.473 14.038 11.000 8.859 (�) �1.17

MERGER 0.221 0.000 0.417 0.144 0.000 0.353 (+) 1.52*

Variable (1) (2) (3) (4) (5) (6)


(1) NONADTFEE 0.012 0.283*** 0.124 0.117 0.185*

(2) INDSPEC 0.022 �0.061 0.120 �0.164* �0.071

(3) ADTFEE 0.408*** 0.002 0.133 0.052 �0.122

(4) ZFC 0.141 0.164* 0.131 �0.046 �0.010

(5) AGE 0.096 �0.083 0.025 �0.104 �0.006

(6) MERGER 0.115 �0.142 �0.142 0.087 0.009



NONADTFEE H4 (+) �0.139 1.39

INDSPEC (�) 1.080 0.24

ADTFEE (?) 0.960 8.83***

ZFC (+) �0.007 0.02

AGE (�) �0.022 0.92

MERGER (+) 0.850 3.87**

This table presents univariate and multivariate results from the long tenure (P5 years) sample analysis. *,**,*** represent

significance at the .10, .05, and .01 level (one-tailed for results in the predicted direction), respectively. The variables are defined

as follows:







MERGER = 1 if the company was involved in merger activity, else 0. Panel A presents the mean, median, and standard

deviation for the test variable of interest, NONADTFEE, and the control variables. The mean log audit fees equal $329,062

(restatement sample) and $268,606 (control sample) in mean raw audit fees. The mean log nonaudit fees equal $207,109

(restatement sample) and $216,642 (control sample) in mean raw nonaudit fees. The tests of differences in means are based on

paired-sample t-tests. Nonparametric Wilcoxon rank sum tests yield qualitatively similar results in all cases, except for ZFC,

which is larger for the restatement sample (p < 0.10). Panel B presents Pearson (Spearman) correlations among the test and

control variables above (below) the diagonal. Panel C presents estimation results from the following matched-sample logistic

regression model (Model 2):

RSTMT ¼ b1NONADTFEEþ b2INDSPECþ b3ADTFEEþ b4ZFCþ b5AGEþ b6MERGERþ e

Model v2 = 14.295; p = 0.027. Max-rescaled R2 = 17.12%. n = 104 matched pairs.



We also assessed whether the reported short tenure and long tenure resultsare sensitive to alternative tenure cutoffs and alternative industry specializationand fee measures. For example, we investigated whether the three-year shorttenure industry specialization and audit fee effects remained significant usinga two-year short tenure cutoff. The literature (e.g., Loebecke et al., 1989;AICPA, 1992) provides some evidence that audit and financial reporting prob-lems are most likely to occur during the initial two years of the auditor–clientrelationship.22 The results in Table 5, Panel A, indicate that INDSPEC andADTFEE remain negative and significant at the .05 level using a matched sam-ple of 31 restatement and non-restatement companies with audit tenures of nomore than two years. Furthermore, the INDSPEC and ADTFEE coefficientsincreased by approximately 70% and 50% in the re-estimated model, respec-tively, when compared to the coefficients estimated using a sample with athree-year tenure cutoff. These results suggest that the positive effects of indus-try specialization and audit fees on financial reporting quality for short tenureengagements are not driven by audit firms with the longest tenure within thesample. In addition, we estimated the two-year and three-year models usingalternative industry specialization proxies based on total assets audited withinan industry (Carcello and Nagy, 2004a) and total number of clients within theindustry (Balsam et al., 2003). The results (not tabulated) are qualitatively sim-ilar using these alternative proxies.

Next, we evaluated whether the nonaudit fee (H4) results depend on the spe-cific long tenure threshold used. Specifically, although prior studies (e.g., Myerset al., 2003) have used five-year long tenure thresholds, the literature alsoincludes studies using thresholds of up to nine-years (e.g., Johnson et al.,2002; Carcello and Nagy, 2004b). Accordingly, we re-estimated the initialfive-year long tenure model (Model 2) using longer thresholds of seven andnine years. As the results in Table 5, Panel B, indicate, NONADTFEEremained insignificant in both cases, suggesting our reported results are notsensitive to long tenure threshold.

To assess whether our long tenure fee results are sensitive to using nonauditfees as a proxy for auditor independence, we conducted additional analysisusing the ratio of nonaudit fees to audit fees. Despite concerns that fee ratiosignore fee magnitude (Reynolds et al., 2004) and are difficult to interpret(Kinney et al., 2004), the SEC (2000) listed the ratio of nonaudit fees to auditfees as an important indicator for assessing audit firm independence. Consis-tent with the nonaudit fee results, the results in Table 5, Panel C, indicate that

22 The AICPA’s Quality Control Inquiry Committee found that allegations of audit failures occuralmost three times as often during this initial two-year period (AICPA, 1992). Similarly, Loebeckeet al. (1989) found that audit partners report that approximately one-third of accountingirregularities and management fraud encountered occur during the first two years of the auditengagement.

Table 5Supplemental logistic regression results


Panel A: Alternative short tenure definition (62 years)

INDSPEC H2 (�) �14.349 4.23**

ADTFEE H3 (�) �1.625 3.63**

NONADTFEE (?) �0.143 1.42ZFC (+) 0.345 3.49**

AGE (�) 0.054 0.98MERGER (+) �0.183 0.06

Model v2 = 14.715; p = 0.023Max-rescaled R2 = 50.39%n = 31 matched pairs,

Variable P7 years P9 years

Pred. Coefficient v2 Coefficient v2

Panel B: Alternative long tenure definitions (P7 years and P9 years)NONADTFEE H4 (+) �0.153 1.34 �0.183 1.06INDSPEC (�) 2.899 1.14 1.448 0.20ADTFEE (?) 0.880 6.73*** 0.784 3.46**

ZFC (+) �0.015 0.07 �0.042 0.30AGE (�) �0.012 0.24 �0.009 0.07MERGER (+) 0.962 3.32** 0.786 1.56

Model v2 (p-value): 11.033 (0.087) 5.729 (0.454)Max-rescaled R2: 18.02% 14.71%n matched pairs: 76 49

Variable P5 years P7 years P9 years

Pred. Coefficient v2 Coefficient v2 Coefficient v2

Panel C: Alternative long tenure independence proxy (fee ratio)

FEERATIO H4 (+) 0.039 0.37 0.004 0.00 �0.051 0.23INDSPEC (�) 0.406 0.04 2.039 0.62 0.943 0.09ZFC (+) 0.007 0.02 �0.002 0.00 �0.002 0.00AGE (�) �0.023 1.20 �0.012 0.21 �0.015 0.21MERGER (+) 0.600 2.26* 0.642 1.84 0.592 1.09

Model v2 (p-value): 4.100 (0.535) 2.802 (0.731) 1.680 (0.891)Max-rescaled R2: 5.15% 4.83% 4.49%n matched pairs: 104 76 49



Panel D: Alternative long tenure independence proxy (total fee)

TOTALFEE H4 (+) 0.501 4.70** 0.488 3.50** 0.366 1.53INDSPEC (�) 0.640 0.09 2.469 0.87 0.971 0.10ZFC (+) �0.007 0.02 �0.019 0.13 �0.010 0.02AGE (�) �0.025 1.40 �0.012 0.25 �0.011 0.11MERGER (+) 0.591 2.15* 0.591 1.52 0.478 0.69


Table 5 (continued)



Model v2 (p-value): 8.843 (0.116) 6.619 (0.251) 3.075 (0.689)Max-rescaled R2: 10.87% 11.12% 8.11%n matched pairs: 104 76 49

This table presents supplemental multivariate results. *,**,*** represent significance at the .10, .05,and .01 level (one-tailed for results in the predicted direction), respectively. The variables aredefined as follows:RSTMT = 1 if financial statements were restated, else 0;ADTFEE = natural log of total audit fees;NONADTFEE = natural log of total nonaudit fees;FEERATIO = ratio of total nonaudit fees to total audit fees;TOTALFEE = natural log of total fees;INDSPEC = audit firm’s industry marketshare based on total sales audited within 2-digit SICcode;ZFC = Zmijewski’s (1984) financial condition index; AGE = length of time as a publicly-tradedcompany (in years); andMERGER = 1 if the company was involved in merger activity, else 0.Panel A presents the estimation results from Model 2 (presented in Table 3) using the audit feeindependence proxy and an alternative short tenure sample, where short tenure is defined as lessthan or equal to two years. Panel B presents the estimation results from Model 2 (presented inTable 4) using the original nonaudit fee independence proxy and two alternative long tenuresamples, where long tenure is defined as at least seven and nine years. Panel C presents theestimation results from the augmented Model 2 using the ratio of nonaudit to audit fees as theindependence proxy and the three long tenure samples, where long tenure is defined as at least five,seven, and nine years. Panel D presents the estimation from the augmented Model 2 using total feesas the independence proxy and the three long tenure samples.


the ratio of total nonaudit fees to audit fees is not significantly related to thelikelihood of restatement for our five-, seven-, or nine-year samples. This find-ing further supports our conclusion that large nonaudit fees do not appear tobe linked to adverse financial reporting outcomes requiring subsequent correc-tion and restatement.

The magnitude of total fees also has been examined in previous studiesassessing auditor independence (e.g., Frankel et al., 2002; Ashbaugh et al.,2003). Several papers (e.g., Beck et al., 1988; Magee and Tseng, 1990; Bazer-man et al., 1997) suggest that a fee-based economic bond between auditorand client threatens auditor independence. This perspective posits that all clientpayments to the auditor (including audit and nonaudit fees) strengthen thisbond and undermine auditor independence. Accordingly, we use total fees asan alternative fee-based independence proxy for long tenure firms to facilitatecomparison with prior research. The results in Table 5, Panel D, indicate a sig-nificant positive association between total fees and the likelihood of restate-ment (p < 0.05) for the five-year and seven-year tenure samples. However, wehighlight that this total fee effect appears to be driven by the magnitude of


audit fees given the significant ADTFEE and insignificant NONADTFEEresults presented in Table 4, Panel C, and Table 5, Panel B. Audit fees arguablyhinder auditor independence less than nonaudit fees (SEC, 2000). Further-more, regulators do not appear to be concerned about the potential adverseeffect of large audit fees on the auditor’s independence (Kinney et al., 2004).Accordingly, we question whether auditor independence is the construct under-lying the total fee effect on the likelihood of restatement within our samplecompanies.23

5. Discussion and conclusion

This study provides some initial empirical evidence on the link betweenfinancial restatements, audit tenure, and tenure-related proxies for audit firmexpertise and independence. Consistent with prior audit tenure effect studies(e.g., Geiger and Raghunandan, 2002; Johnson et al., 2002; Carcello and Nagy,2004b; Ghosh and Moon, 2005), we find evidence of an inverse relationbetween audit tenure and financial restatement. Decomposition of the overalltenure effect reveals that the likelihood of restatement is inversely related tothe audit firm’s industry marketshare and audit fees for companies with shortaudit tenures. The long tenure results indicate no significant relation betweennonaudit fees and likelihood of restatement.

Collectively, these results have a number of research, policy, and practiceimplications. From a research perspective, the results extend the tenure effectsliterature in two primary ways. First, this study provides evidence that audittenure problems documented in other financial reporting domains (e.g., accrualaccounting) are robust and generalize to relatively objective financial restate-ment events. Second, this study provides an initial empirical examination ofunderlying expertise and independence factors that have only been suggestedto date. The short tenure industry specialization results are consistent with con-cerns about reduced audit quality due to a lack of client-specific knowledge onnew audit engagements. While this inference is supported further by the insig-nificant industry specialization effect in long tenure companies, future researchis needed to better distinguish between specialization and learning curve effectsin new audit engagements.

The short tenure audit fee results provide initial support for prior concernsabout adverse lowballing effects (e.g., Simon and Francis, 1988; Ettredge andGreenberg, 1990; Deis and Giroux, 1996). Specifically, our multivariate resultssupport regulator concern that lowballing impairs audit quality during the ini-

23 We also evaluated the roles of the nonaudit fee ratio and total fees in determining the likelihoodof restatement for the full sample. Neither variable is significant when evaluated individually in lieuof ADTFEE and NONADTFEE in Model 1. Otherwise, the results were qualitatively similar tothose reported in Table 2, Panel C.


tial years of an audit engagement (e.g., AICPA, 1978; SEC, 2000). This shorttenure result is particularly prominent given our findings of higher audit feesfor restatement firms in the full sample and long tenure sample. Given the rel-atively small short tenure sample, future research is needed to test whether thisaudit fee effect is generalizable to other settings. Other than the results pre-sented in this study, very little empirical data exists on the effects of lowballingon audit quality (Watkins et al., 2004). We also suggest the need for futureresearch to evaluate potential audit quality tradeoffs involving short tenureindustry specialization gains and lowballing losses.

From a policy perspective, the results do not support calls for mandatoryaudit firm rotation and regulatory concern that nonaudit services hinder auditfirm independence and audit quality in the later years of the auditor–client rela-tionship (e.g., Sarbanes-Oxley Act, 2002; SEC, 2003). In addition, the shorttenure industry specialization findings support concerns about the potentialcosts of mandatory audit firm rotation (e.g., PwC, 2002; GAO, 2003). Morespecifically, our results highlight the risk of decreased audit quality in forcedauditor changes where access to a new auditor with specialized knowledge islimited. These findings also support concerns among large public accountingfirms and Fortune 1000 companies that auditor changes increase the risk ofaudit failure in early audit years because auditors may fail to detect materialmisstatement while they are acquiring ‘‘the necessary knowledge of the com-pany’s operations, systems, and financial reporting practices’’ (GAO, 2003,p. 6). The short tenure audit fee results provide indirect support for the long-standing regulatory concern over the adverse effects of lowballing.

Finally, from a practice perspective, the findings of this study and priorstudies (e.g., Dunn and Mayhew, 2004; Carcello and Nagy, 2004a) emphasizethe importance of audit firm industry specialization. Collectively, our resultssuggest that specialization has the potential to compensate for a lack of cli-ent-specific knowledge during the initial years of the audit engagement. Whileseveral accounting studies suggest concern about the learning curve associatedwith new audit clients (e.g., Beck et al., 1988; Stice, 1991; Geiger and Raghun-andan, 2002; Johnson et al., 2002), future research should continue to evaluatethe extent that industry specialization at the firm and office level (e.g., Franciset al., 2005) can mitigate adverse learning curve effects.

The results should be evaluated in the context of the study’s limitations.First, the possibility of measurement error exists given our proxies and specificmeasures. For example, despite the SEC’s (2003) issuance of new fee disclosurerules designed to improve consistency and transparency, companies continueto have discretion when reporting and categorizing audit and nonaudit feesin annual proxy statements (Weil and Rapoport, 2003). Second, despite ourmatching process and use of various controls in the study, correlated omittedvariables may affect the results. Specifically, we recognize the possibility of end-ogeneity (e.g., DeFond et al., 2002; Whisenant et al., 2003) with respect to


auditor tenure. To the extent our tenure variable reflects underlying auditorchange decisions, consideration of the study’s implications should includethe possibility that audit tenure may respond to an unspecified omitted variableor simultaneously to changes in the likelihood of restatement.

Acknowledgements

We gratefully acknowledge the helpful comments and suggestions receivedfrom Debbie Archambeault, Mark Beasley, Dana Hermanson, Gary Hol-strum, Rich Houston, Rob Ingram, Karen Maguire, Mary Stone, Gary Taylor,and workshop participants at The University of Alabama and the 2004 Amer-ican Accounting Association Annual Meeting.

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Documents

Audit Firm Tenure and Financial Restatement_an Analysis of Industry Specialization n Fee Effects