asthana and boone - 2012 - abnormal audit fee and audit quality

BooneSUMMARY: This study tests the hypotheses that below-normal audit fees signalimportant nuances in the balance of bargaining power between the auditor and the client,and that such pow

Vol 31, No 3 DOI: 10.2308/ajpt-10294August 2012

pp 1–22

Abnormal Audit Fee and Audit Quality

Sharad C Asthana and Jeff P BooneSUMMARY: This study tests the hypotheses that below-normal audit fees signalimportant nuances in the balance of bargaining power between the auditor and the client,and that such power may ultimately influence audit quality We find that audit quality,proxied by absolute discretionary accruals and meeting or beating analysts’ earningsforecasts, declines as negative abnormal audit fees increase in magnitude, with theeffect amplified as proxies for client bargaining power increase We find that this effect isdampened in years following the Sarbanes-Oxley Act (SOX), suggesting that SOX waseffective in enhancing auditor independence

Keywords: abnormal audit fees; bargaining power; economic bonding

INTRODUCTION

U nderstanding the factors that lead auditors to compromise on audit quality is an important

issue of concern to scholars, investors, and regulators One possible factor that hasreceived significant research attention is economic bonding between the auditor andclient The basic idea in these studies is that positive abnormal audit fees reflect the extent ofeconomic bonding between the auditor and client, and greater economic bonding degrades auditquality by impairing auditor independence Based on this premise, studies have examined thelinkage between audit quality and positive abnormal audit fees, with such studies documenting anegative association

In this study, we reexamine the association between abnormal audit fees and audit quality, and

we do so in a way that allows our paper to offer two important contributions to the literature First,

we incorporate into our conceptual framework insights about client bargaining power(Casterella et

al 2004)in addition to the economic bonding story that forms the conceptual framework in priorstudies Expanding the framework to consider both bargaining power and economic bonding allows

us to offer a novel prediction that would not be meaningful within a framework based exclusively

on economic bonding That prediction is: audit quality will decline as negative abnormal audit feesincrease in magnitude, and the magnitude of the decline will increase as proxies for clientbargaining power increase The economic bonding literature that informs prior studies places thefocus on positive abnormal audit fees, predicting no association between negative abnormal audit

Sharad C Asthana and Jeff P Boone are both Professors at The University of Texas at San Antonio

Editor’s note: Accepted by Jean Bedard.

Submitted: December 2009Accepted: March 2012Published Online: August 2012

fees and audit quality, and a negative association between positive abnormal audit fees and auditquality.

Second, we include in our analysis data taken from the post-Sarbanes-Oxley (SOX) period(i.e., years 2004–2009), in addition to data from the pre-SOX period (i.e., years 2000–2003) Thepre-SOX period has been the data source for virtually all of the prior studies With data taken fromboth the pre- and post-SOX periods, we are able to probe for a dampened association betweenabnormal audit fees and audit quality that would be manifest if SOX reforms meaningfullyincreased auditor independence or strengthened the auditor’s bargaining power, leading to higheraudit quality To date, there is only limited empirical evidence that speaks to the issue of whetherSOX reforms increased audit quality

Consistent with prior research (e.g.,Choi et al 2010; Hope et al 2009;andHiggs and Skantz

2006), we decompose total audit fees into normal and abnormal components, and test for anassociation between audit quality and abnormal audit fees, conditioning our tests on the sign of theabnormal audit fee metric (i.e., above-normal audit fees and below-normal audit fees) Under thebargaining power story, we expect to find that audit quality declines as negative abnormal feesincrease in magnitude, with the effect amplified as proxies for client bargaining power increase.Under the economic bonding story (and consistent with prior studies), we expect to find that auditquality declines as positive abnormal fees increase in magnitude We also partition our analysis byregulatory regime (i.e., a pre-SOX reporting period or a post-SOX reporting period) in order toassess whether the sensitivity of audit quality to abnormal audit fees differs between these tworegimes Our two proxies for audit quality are absolute discretionary accruals and meeting orbeating analysts’ earnings forecasts, and our two proxies for client bargaining power reflect theimportance of the client to the local practice office

Our tests produce evidence consistent with both the economic bonding story and the bargainingpower story As predicted by the economic bonding story, we find that absolute discretionaryaccruals and the probability of meeting or beating earnings forecasts both increase as positiveabnormal audit fees increase As predicted by the client bargaining power story, we find thatabsolute discretionary accruals and the probability of meeting or beating earnings forecasts increasewith the magnitude of negative abnormal audit fees, with the effect amplified as client bargainingpower increases With respect to the effects of SOX, we find that the effects of economic bondingand client bargaining power are both dampened in the post-SOX regime, suggesting that SOX waseffective in enhancing auditor independence

The evidence presented in our paper is important in at least two respects First, our resultssuggest that investors, regulators, and others interested in assessing the effects of auditorremuneration on audit quality should be concerned with both above-normal and below-normalauditor remuneration, but for different reasons The potential effect of above-normal audit fees indegrading audit quality by economically bonding the auditor with the client is well recognized andextensively investigated Less recognized is the possibility that below-normal audit fees signalimportant nuances in the balance of power between the auditor and the client, and that such powermay ultimately influence audit quality Thus, our study highlights the importance of considering thebargaining power of the client when assessing audit quality Second, our study presents the firstevidence (of which we are aware) to suggest that reforms introduced by the Sarbanes-Oxley Actdampened the deleterious effects of economic bonding and client power on audit quality, and henceincreased audit quality Both of these important insights from our study increase understanding ofthe factors that may lead auditors to compromise on audit quality, and hence our paper should be ofinterest to accounting scholars, investors, and regulators

The remainder of the study is organized as follows The second section develops our theoreticalframework and presents the hypotheses that we test We present our research design in the third

section, followed by a discussion of our sample in the fourth section and our results in the fifthsection We offer concluding comments in the sixth section.

THEORETICAL FRAMEWORK AND HYPOTHESES

An audit firm is not a single person ‘‘auditor’’; rather, it is a decentralized organization in whichindividual audit partners act as agents for the audit firm (Liu and Simunic 2005) To the extent thepartnership profit-sharing plan does not effectively align the interests of the partner with that of theaudit firm partners as a whole, an uncontrolled moral hazard problem exists that might result in anindividual audit partner succumbing to client pressure for earnings management This is because theindividual partner captures a significant portion of the expected benefit from acquiescing to clientdemands, while passing to the partnership as a whole the expected cost (Trompeter 1994).What factors might lead an audit partner to compromise on audit quality? As described below,engagement profitability and client bargaining power are two possible explanations

Engagement Profitability and Economic Bonding

Engagement profitability should influence audit quality for the following reason Audit

start-up costs and client switching costs allow the auditor to price audit services at a price in excess ofthe avoidable cost of producing the audit, and thus create for the incumbent auditor client-specific quasi-rents (DeAngelo 1981a, 1981b) The client-specific quasi-rents economically bondthe auditor to the client, reduce auditor independence, and increase the likelihood that theauditor will acquiescence to a client’s demand for earnings management However, succumbing

to client pressure risks audit firm forfeiture of some or all of the quasi-rents from the firm’sentire client portfolio (if the earnings management is discovered), and additional economic lossthrough litigation and government penalties (DeAngelo 1981a, 1981b) The auditor willcompromise audit integrity only if the expected gain ( preserving the client-specific quasi-rent)exceeds the expected loss (forfeited quasi-rents from the overall client portfolio, litigation costs,and penalties), and thus the question of whether economic bonding undermines audit qualitydepends upon the relative magnitude of expected costs and benefits, which is an empiricalquestion.1

Bargaining Power

Bargaining power should influence audit quality for the following reason Audited financialstatements, and hence audit quality, are the joint effort of the auditor and the client (Antle andNalebuff 1991) that arise from a process of negotiation between the two(Gibbins et al 2001) Thenegotiation literature shows that when negotiators differ in bargaining power, the more powerfulparty expects greater concessions (e.g.,Pruitt and Carnevale 1993; Hornstein 1965; Michener et al.1975), and Barnes (2004) shows that audit quality may decrease as client bargaining powerincreases In an experimental auditing setting, Hatfield et al (2008)show that the effect of clientbargaining power on the audited financial statements depends upon the negotiation strategyemployed by the auditor, with a reciprocity negotiating strategy leading to more conservativefinancial statements Thus, the question of whether client bargaining power undermines auditquality depends upon whether the auditor is able to employ a negotiating strategy that weakens theadvantage held by a client with strong bargaining power

1

See Beck et al (1988), Magee and Tseng (1990), and Zhang (1999) for extensions of DeAngelo’s (1981a, 1981b ) idea that quasi-rents impair auditor independence.

Abnormal Audit Fees

Simunic (1980)shows that the auditor’s expected fee charged to the client is driven by the units

of audit resources expended, the per-unit cost of those resources, and the auditor’s expected futureloss arising from the engagement (e.g., litigation losses, government penalties) Empirically, extantresearch models the expected audit fee as a function of observable factors that proxy for theauditor’s cost in performing the audit, including auditor effort (i.e., resources expended and theircost), expected future litigation losses, and normal profit If the audit fee model is well specified, theresidual audit fee reflects abnormal profits from the audit engagement To the extent that somefactors are unobservable (and hence omitted from the audit fee model), the residual audit fee metricmeasures abnormal audit profitability with error

Abnormal audit profitability should be associated with both client bargaining power andeconomic bonding With respect to the former,Casterella et al (2004)show a negative associationbetween proxies for client bargaining power and audit fees earned by industry specialists Theirresearch suggests that, ceteris paribus, below-normal audit fees may reflect billing concessionsgranted by the auditor due to client bargaining power With respect to the later,Kinney and Libby(2002)note that ‘‘Unexpected fees may also better capture the profitability of the services provided more insidious effects on economic bond may result from unexpected nonaudit and audit feesthat may more accurately be likened to attempted bribes.’’

Although there is scant evidence on the association between abnormally low audit fees andaudit quality, a growing literature, described below, examines the association between abnormallyhigh audit fees (as a proxy for economic bond) and audit quality.DeFond et al (2002),Krishnan et

al (2005), Hoitash et al (2007), and Hribar et al (2010) test for a linear association betweenabnormal audit and/or engagement fees and audit quality (i.e., the curve relating audit quality toabnormal audit fees exhibits the same slope for both positive and negative abnormal audit fees).2DeFond et al (2002)find no association between abnormal engagement fees and auditors’ goingconcern opinions during 2000–2001, while Krishnan et al (2005) find that during year 2001,earnings response coefficients (a direct indicator of audit quality) decline as abnormal engagementfees increase Hoitash et al (2007)find during years 2000–2007 a positive association betweenabnormal engagement fees and two (inverse) audit quality metrics—theDechow and Dichev (2002)accrual quality metric and the absolute value of performance-adjusted discretionary accruals.Hribar

et al (2010)find during years 2000 to 2007 a positive association between abnormal audit fees andaccounting fraud, restatements, and SEC comment letters.3

Larcker and Richardson (2004), Higgs and Skantz (2006), Hope et al (2009), Mitra et al.(2009),andChoi et al (2010)test for a nonlinear association between abnormal audit fees and auditquality (i.e., the curve relating audit quality to abnormal audit fees exhibits different slope forpositive as compared to negative abnormal audit fees) Larcker and Richardson (2004)use datafrom 2000 and 2001 to examine absolute discretionary accruals (an inverse indicator of auditquality), and find that audit quality increases as abnormal engagement fees increase in absolutemagnitude.Higgs and Skantz (2006)find that during 2000–2002, earnings response coefficients (adirect indicator of audit quality) are greater in firms with positive abnormal audit fees.Hope et al.(2009)find that during 2000–2003, equity discount rates (an inverse indicator of audit quality)increase as positive abnormal engagement fees increase, but find no association with negative

2004, but no such association during 2000–2001.

abnormal engagement fees.Mitra et al (2009)find during years 2000–2005 a negative associationbetween positive abnormal audit fees, and both absolute discretionary accruals and income-increasing accruals, but find no association between negative abnormal audit fees and discretionaryaccruals Choi et al (2010) find during 2000–2003 a positive association between positiveabnormal audit fees and absolute discretionary accruals, but no association when abnormal auditfees are negative.

The weight of the preceding evidence suggests a negative association between audit qualityand positive abnormal audit fees, and no association between audit quality and negative abnormalaudit fees—findings consistent with the economic bonding hypothesis However, as discussedabove, negative abnormal audit fees may reflect client bargaining power that could degrade auditquality—with the degrading being larger in magnitude the greater the bargaining power of theclient Also as previously discussed, the question of whether client bargaining power underminesaudit quality ultimately depends upon whether the auditor is able to employ a negotiating strategythat weakens the advantage held by a client with strong bargaining power Thus, whether clientbargaining power affects audit quality remains an open empirical question, leading us to specify andtest the following client bargaining power hypotheses

H1a: Audit quality will decline as below-normal audit fee increases in magnitude

H1b: The association predicted in H1a will be amplified as proxies for client bargainingpower increase

For completeness, we also specify and test the following economic bonding hypothesis:

H2: Audit quality will decline as above-normal audit fees increase in magnitude

Post-Sox Abnormal Audit Fees

In addition to the question of client bargaining power, another as yet unanswered question iswhether the audit quality/abnormal audit fee association changed following SOX Passed in 2002following discovery of a series of high-profile financial reporting scandals, SOX seeks to improvecorporate governance and enhance auditor independence by mandating federal governmentoversight of auditors, enhancing audit committee auditor oversight, and limiting the opportunity forauditors to sell nonaudit services to clients (U.S House of Representatives 2002) If these reformsare sufficiently salient, they should manifest in a reduced association between abnormal audit feesand audit quality post-SOX relative to pre-SOX This leads to our final hypothesis:

H3: The association between audit quality and abnormal audit fees will be attenuated in thepost-SOX period as compared to the pre-SOX period

RESEARCH DESIGN

To test our hypotheses, we need to measure abnormal audit fee and audit quality We estimateabnormal audit fee (ABNAFEE) as the actual audit fee paid by the client to its auditor minus thepredicted (normal) audit fee, with the difference deflated by the total audit fee revenue of the auditoffice conducting the client’s audit

We deflate the abnormal audit fee by total audit fee revenues of the practice office conductingthe audit in order to capture the relative profitability of the engagement to the opining audit office.4

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We do not deflate this measure by the total abnormal audit fee for the practice office since this results in zero denominator problem.

near-We do so since prior research (e.g.,Reynolds and Francis 2001) suggests that economic incentivesimpacting audit quality are best measured at the local office level rather than at the national firmlevel For example, the Enron audit failure largely stemmed from decisions made in the Houstonoffice of Arthur Andersen (Chaney and Philipich 2002) We define two separate variables fromABNAFEE If ABNAFEE 0 then HIABNAFEE¼ ABNAFEE, and 0 otherwise If ABNAFEE  0thenLOABNAFEE¼ jABNAFEEj, and 0 otherwise This allows us to study the relationship of thedependent variables with the positive and negative abnormal audit fee, separately The predictedaudit fee is estimated from an audit fee model based on extant research.5All the variables used invarious tests are summarized in Table 1.

Audit quality is unobservable Consistent with prior research, we define audit quality as theclient’s earnings quality (Higgs and Skantz 2006; Lim and Tan 2008; Davis et al 2009; Francis and

Yu 2009; Reichelt and Wang 2010; Choi et al 2010) Following this research, we use twocommonly used proxies for earnings quality: absolute discretionary accruals and propensity to meet

or beat earnings expectations We also conduct additional tests using an earnings responsecoefficient The first two proxies are surrogates for actual earnings management, while the last one

is related to perceived earnings quality However, for the sake of brevity, we only report results forthe first two, since the conclusions are similar The tests for these proxies are discussed in moredetail below

Discretionary Accruals Model

The level of discretionary accruals has commonly been used as a surrogate for managers’exercise of discretion provide by GAAP To the extent the discretionary component of accruals isused by managers to opportunistically manage earnings and auditors allow the manipulation toremain uncorrected, discretionary accruals adversely reflect on the audit and earnings quality(Schipper 1989; Jones 1991; Levitt 2000; DeFond and Park 2001) Discretionary accruals can beused for increasing or decreasing earnings depending on the incentives of managers Since we arenot looking at any specific managerial incentives, we have no directional predictions for accruals

We therefore use the absolute value of discretionary accruals (jDACCj) as the independent variable

in our next test Discretionary accruals (DACC) are calculated using the cross-sectional modifiedversion of the Jones model(Jones 1991; Dechow et al 1995), deflated by total assets, and estimated

by year and for each industry We adjust discretionary accruals for performance as suggested byKothari et al (2005) Following Hribar and Collins (2002), we use the difference between netincome and cash from operations, deflated by lagged assets, as our measure of total accruals(TACC) Thus:

TACC¼ ðIBC  OANCFÞ=LagðATÞ;

whereIBC is the income before extraordinary items (Compustat cash flow item), OANCF is netcash flow from operating activities, and AT is total assets The model to estimate discretionaryaccruals is:

TACC¼ h1þ h2½1=LagðATÞ þ h3½ DSALE þ RECCHf g=LagðATÞ þ h4½PPEGT=LagðATÞ

þh5ROAþ error:

ð1Þ

5 Our audit fee model is based on models used in Ghosh and Lustgarten (2006 ), Craswell and Francis (1999), Craswell et al (1995), and Simon and Francis (1988) The adjusted-R 2 of this model is over 81 percent However, we do not report details for the sake of brevity Detailed specifications are available from the authors

on request.

TABLE 1Variable Definitions(In Alphabetical Order)

ABNAFEE Actual audit fee minus predicted (normal) audit fee deflated by the total revenue of the

auditor office that audits the client

ACQUIRED A dichotomous variable with value of 1 if the firm indulged in acquisition activities, and

0 otherwise

B2M Book-to-market equity ratio

BIG-N A dichotomous variable with value of 1 if the auditor is one of the Big 4 (or Big 5), and

0 otherwise

BUSSEG Number of business segments reported in Compustat segment file

CFFO Cash flow from operations divided by total assets

CITYLEADER FollowingFrancis and Yu (2009),a dichotomous variable with value of 1 if an audit

office has the highest total client audit fees in an industry within that city in a specificyear, and 0 otherwise

jDACCj Absolute discretionary accruals are calculated using the cross-sectional version of the

Jones (1991)model as inDechow et al (1995)with performance adjustment (Kothari

et al 2005),deflated by total assets and estimated by year and for each two-digit SICcode We use the difference between net income and cash from operations as ourmeasure of total accruals(Hribar and Collins 2002)

DELAY Number of calendar days from fiscal year-end to date of auditor’s report

DISTRESS Zmijewski’s (1984)financial distress measure

DSOX A dichotomous variable with value of 1 for fiscal years 2004–09, and 0 otherwise We

choose 2004 as the cutoff since this was the implementation year for SOX 404(b).FINANCED A dichotomous variable with value of 1 if number of outstanding shares increased by at

least 10 percent or long-term debt increased by at least 20 percent during the year(Geiger and North 2006)

GEOSEG Number of geographic segments reported in Compustat segment file

HIABNAFEE Equal toABNAFEE if ABNAFEE 0, and 0 otherwise

I_jDACCj Implies the instrumented variable forjDACCj fromMaddala’s (1988)2SLS estimation.I_MBEX Implies the instrumented variable forMBEX fromMaddala’s (1988)2SLS estimation.ICOPINION Number of material internal control weaknesses reported in Audit Analytics

INFLUENCE FollowingReynolds and Francis (2001),ratio of a client’s total fee relative to the total

annual fee of the practice office that audits the client

LAGROA Lagged value of return on asset

LARGEST A dichotomous variable with value of 1 if the client pays the highest audit fee in the

practice office that audits the client

LDELAY Natural logarithm ofDELAY variable plus one day

LEVERAGE Total debt deflated by total assets

LNUMFOR Natural logarithm of the number of analysts’ forecasts

LOABNAFEE Equal tojABNAFEEjifABNAFEE is less than or equal to 0, and 0 otherwise

LOFFICE FollowingFrancis and Yu (2009),the natural logarithm of total annual audit fee of the

practice office that audits the client

LOGMV Natural logarithm of the market value of equity (in $ million) at the end of the fiscal year.LOSS A dichotomous variable with value of 1 if client has a negative net income before

extraordinary items, and 0 otherwise

MBEX A dichotomous variable with value of 1 if the firm meets or beats the earnings

expectation (proxied by the most recent median consensus analyst forecast available onI/B/E/S file) by two cents or less, and 0 otherwise

(continued on next page)

whereLag(AT) is total assets of prior year; DSALE is change in revenue; RECCH is the decrease inaccounts receivables;PPEGT is property plant and equipment (gross total); and ROA is return onassets, calculated asIBC deflated by AT Equation (1) is estimated by year for each industry (two-digit SIC code) Then,TACC minus the predicted value from the above regression is our measure ofdiscretionary accruals.

Our test ofjDACCj is based on the following model:

jDACCj ¼ a0þ a1LOABNAFEEþ a2HIABNAFEEþ a3LOFFICEþ a4INFLUENCE

þ a5TENUREþ a6USLEADERþ a7CITYLEADERþ a8BUSSEGþ a9GEOSEG

þ a10LOGMVþ a11SGROWTHþ a12SDSALESþ a13CFFOþ a14SDCFFO

þ a15ICOPINIONþ a16LEVERAGEþ a17LOSSþ a18DISTRESSþ a19B2M

þ a20VOLATILITYþ a21FINANCEDþ a22ACQUIREDþ a23LAGROA

þ a24BIG-Nþ a25QUALIFIEDþ a26LDELAYþ a27RESTATEMENT

þ a28I MBEXþ error:

ð2ÞThe control variables are from extant research.Francis and Yu (2009)show that larger offices ofBig 4 auditors have higher audit quality The logarithm of total office-specific audit fee of all clients

in a given year (LOFFICE) is included to capture this effect.Reynolds and Francis (2001)provideevidence that auditors report more conservatively for larger clients Consistent with this research,the variableINFLUENCE, defined as the ratio of a client’s total fee relative to the total annual fee ofthe practice office that audits the client, is included as an independent variable TENURE (1/0dummy variable for audit tenures of three years or less) controls for potential effect of short auditor-client association on audit quality (Johnson et al 2002; Carey and Simnett 2006)

Balsam et al (2003) argue that industry expertise increases audit quality We includeUSLEADER and CITYLEADER, consistent withFrancis and Yu (2009),to control for national-leveland city-level auditor industry expertise.USLEADER is an indicator variable that is coded 1 if the

TABLE 1 (continued)

QUALIFIED A dichotomous variable with value of 1 if audit opinion is a qualified opinion, and 0

otherwise

RESTATEMENT A dichotomous variable with value of 1 if the client issues a restatement in the current

fiscal year, and 0 otherwise

SDCFFO Standard deviation of cash flow from operations deflated by total assets, calculated over

the current and prior four years

SDFOR Standard deviation of analysts’ earnings forecasts

SDSALES Standard deviation of sales deflated by total assets, calculated over the current and prior

four years

SGROWTH Sales growth rate

TENURE A dichotomous variable with value of 1 if auditor has been with the client for three years

or less, and 0 otherwise

TOP10%INFL A dichotomous variable with value of 1 ifINFLUENCE is in the top 10 percent, and 0

otherwise

USLEADER FollowingFrancis and Yu (2009),a dichotomous variable with value of 1 if an auditor

has the highest total client audit fees in an industry in the country in a specific year,and 0 otherwise

VOLATILITY Standard deviation of daily returns for the past year obtained from CRSP

auditor is the national audit fee leader in that industry.CITYLEADER is similarly defined at the citylevel BUSSEG (GEOSEG) is the number of business (geographic) segments reported in theCompustat segment file.LOGMV is the natural logarithm of market value of equity at the end of thefiscal year This variable controls for any size-related effects Prior research (Ashbaugh et al 2003;Butler et al 2004; Menon and Williams 2004; Geiger and North 2006) finds LOGMV to benegatively associated to discretionary accruals.SGROWTH is the annual growth in sales and hasbeen found to be positively related to discretionary accruals (Menon and Williams 2004).CFFO is the cash flow from operations deflated by total assets Previous researchers (Frankel et

al 2002; Chung and Kallapur 2003)find a negative association between discretionary accruals andCFFO Hribar and Nichols (2007) find that accrual volatility may be related to firm-specificoperating characteristics as measured by the volatility of the firm’s cash flows and sales Hence, weincludeSDSALES and SDCFFO (calculated as the standard deviations over the current and pastfour years of cash flow from operations and sales, respectively, deflated by the total assets) ascontrol variables.Doyle et al (2007)suggest that earnings quality may be a function of the quality

of the firm’s internal control.ICOPINION (number of material internal control weaknesses reported

in Audit Analytics in the post-SOX period) is, therefore, included as a control variable

Consistent withDeFond and Jiambalvo (1994), Reynolds and Francis (2001), andFrancis and

Yu (2009),LEVERAGE, LOSS, and DISTRESS are included to control for the effects of debt andfinancial distress.LEVERAGE is total debt deflated by total assets LOSS is a dichotomous variablewith a value of 1 if client has a negative net income before extraordinary items, and 0 otherwise.DISTRESS is Zmijewski’s (1984) measure of financial distress B2M is the book-to-market valueand captures the growth opportunities Ashbaugh et al (2003),Butler et al (2004),Menon andWilliams (2004), and Geiger and North (2006) suggest B2M and DACC to be negativelyassociated FollowingMatsumoto (2002),Hribar and Nichols (2007),andFrancis and Yu (2009),

we include stock-return volatility (VOLATILITY) to proxy for capital market pressures that canresult in increased earnings management.FINANCED and ACQUIRED are dichotomous variablesthat have values of 1 if the company was involved in significant financing activities or acquisitions,respectively, and 0 otherwise.Ashbaugh et al (2003)andChung and Kallapur (2003)find positivecoefficients on these two variables.LAGROA is the previous year’s return on assets and is included

to control for prior performance.BIG-N (a 0/1 dummy variable) and QUALIFIED (a 0/1 dummyvariable) capture the effect of auditor size and qualified opinions on earnings quality Naturallogarithm of 1 þ number of calendar days from fiscal year-end to date of auditor’s report(LDELAY) controls for the effect of extra effort by the auditor on earnings quality Sincerestatements can influence earnings management, the dichotomous variable RESTATEMENT isadded as a control variable.MBEX is a dichotomous variable with a value of 1 if the firm meets orbeats the earnings expectation (proxied by the most recent median consensus analysts forecastavailable on I/B/E/S file) by two cents or less, and 0 otherwise SincejDACCj and MBEX can bejointly determined, we use Maddala’s (1988) two-stage-least-squares estimation (2SLS) forEquations (2) and (3) to avoid any endogeneity problems I_MBEX denotes the instrumentedvariable forMBEX from the 2SLS.6

Meet-or-Beat Earnings Expectation Model

There is evidence in extant literature that managers are rewarded (penalized) for meeting(missing) earnings forecasts (Bartov et al 2002; Kasznik and McNichols 2002; Lopez and Rees2002)and this leads to incentives for managers to manage earnings If auditors’ incentives to curtailearnings management vary with abnormal audit fee, the propensity for meeting or beating analysts’

6

See Rusticus and Larcker (2010) for a more detailed discussion of instrumental variable estimation.

earnings forecasts will be a function of the abnormal audit fee We estimate the following logitmodel to test this conjecture:

ProbðMBEX ¼ 1Þ

¼ Fðb0þ b1LOABNAFEEþ b2HIABNAFEEþ b3LOFFICE

þ b4INFLUENCEþ b5TENUREþ b6USLEADERþ b7CITYLEADER

þ b8BUSSEGþ b9GEOSEGþ b10LOGMVþ b11SGROWTH

þ b12SDSALESþ b13CFFOþ b14SDCFFOþ b15ICOPINION

þ b16LEVERAGEþ b17LOSSþ b18DISTRESSþ b19B2M

þ b20VOLATILITYþ b21FINANCEDþ b22ACQUIREDþ b23LAGROA

þ b24BIG-Nþ b25QUALIFIEDþ b26LDELAYþ b27RESTATEMENT

þ b28IjDACCj þ b29SDFORþ b30LNUMFORÞ: ð3Þ

In Model (3),F() denotes the logistic cumulative probability distribution function.I_jDACCjdenotes the instrumented variable for jDACCj from the 2SLS Following Reichelt and Wang(2010), we include the standard deviation of analysts’ earnings forecasts (SDFOR) and naturallogarithm of number of analysts’ forecasts (LNUMFOR) to control for characteristics of theforecasts

Additional Tests

To test H1b, we further interactLOABNAFEE and HIABNAFEE with two measures of clients’bargaining powers in Models (2) and (3).LARGEST is a dichotomous variable with value of 1 if theclient pays the highest audit fee in the practice office that audits the client;TOP10%INFL is adichotomous variable with a value of 1 ifINFLUENCE is in the top 10 percent, and 0 otherwise Tomake the interpretations of the interactions easier, we use the dichotomous versions of abnormalaudit fees, DLOABNAFEE and DHIABNAFEE, where DLOABNAFEE (DHIABNAFEE) is adichotomous variable with a value of one ifLOABNAFEE (DHIABNAFEE) median value, and 0otherwise

To test our conjecture that SOX has dampened the association between abnormal audit fees andearnings management (H3), we rerun Models (2) and (3) with an additional independent variableDSOX and interaction terms, DLOABNAFEE  DSOX and DHIABNAFEE  DSOX, where DSOX is

a dichotomous variable with a value of 1 for the period 2004–2009, and 0 otherwise.7

Adjustment for Clustering

Since our data are pooled over time, the same firm may appear more than once in the sample,resulting in clustering Clustered samples can lead to underestimation of standard errors andoverestimation of significance levels (Cameron et al 2011) We therefore estimate the t-statisticsadjusted for clustering using robust standard errors corrected for firm-level clustering andheteroscedasticity, consistent withPetersen (2009)andGow et al (2010)

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One of the SOX provisions to affect the audit relationship was the requirement that auditors evaluate and report on management’s assessment of the effectiveness of the firm’s internal controls (SOX Section 404(b) [ U.S House of Representatives 2002 ]) Since SOX Section 404(b) was implemented for fiscal years ending on or after November 15,

2004 (per SEC Release No 33-8392, issued February 24, 2004), we classify 2000–2003 as the pre-SOX period and 2004–2009 as the post-SOX period However, using 2002 as the cutoff does not alter the conclusions.

SAMPLEThe sample selection procedure is outlined in Table 2 We start with 61,953 firm-yearobservations for the period 2000–2009 available in the Audit Analytics database for non-Andersenclients We exclude Andersen since the auditor-client relationship might be atypical, given the woes

of Andersen After merging with Compustat we are left with 35,081 observations We then excludethe financial (SIC codes 6000–6900) and utility (SIC codes 4400–4900) industries, since theincentives of managers from these regulated industries may be different This leaves us with 28,925observations Missing data for estimating the variables in a modified Jones (1991) model andEquation (2) further reduce our sample size to 18,873 observations (Sample 1) Finally, I/B/E/S andCRSP data are needed for Equation (3), which results in Sample 2 with 14,796 observations.Untabulated statistics show that the sample industry composition is very close to that of theCompustat population Across years, untabulated statistics generally show an even distribution ofobservations Sample characteristics, including measures of central tendency, are presented in Table

3 Mean (median)jDACCj and MBEX are 0.0655 (0.0418) and 0.2039 (0.0000), respectively MeanLOABNAFEE (HIABNAFEE) is 0.0259 (0.0267) Both variables have median values , 0.0001 Atypical client accounts for under 2 percent of the audit office’s revenue (median value ofINFLUENCE) A mean value of over 10 percent for this variable suggests some large influentialclients Over 23 percent of the clients have been with their auditors for three years or less Onaverage, firms have between two and three business and geographic segments Mean (median) log

of firm market value (in $ million) is 6.15 (6.14) Clients experienced a mean of 13 percent salesgrowth during the sample period The median firm had one internal control weakness reported inAudit Analytics On average, total debt was 19 percent of firm assets and 30 percent of thefirm-years reported losses Book value was around 59 percent of market value of the firm While 31percent of the firms financed during the year, 19 percent were involved in acquisition activities Asexpected, a large proportion (80 percent) of the clients are audited by Big 4 auditors

RESULTSResults of estimation for Models (2) and (3) are presented in Panel A of Table 4 For the sake

of comparison, regressions are reported with and without control variables The adjusted R2ofmodels with controls range from 18.39 percent to 20.39 percent.8 For the jDACCj regression(Equation (2)), 14 of the 26 control variables are significant (at 10 percent level or better)

TABLE 2Sample SelectionProcedure

ObservationsRemainingData available on 2010 Audit Analytics database for non-Andersen clients 61,953

Complete data available forMBEX analysis on I/B/E/S and CRSP files 14,796 Sample 2

8 Tests for outliers are conducted on all the regressions using Belsley et al.’s (1980) procedure Results (not reported) do not change qualitatively when influential outliers are removed Thus, our conclusions are not driven

by outliers.