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1 School of Accounting Seminar Session 1, 2012 The Effect of Audit Committee Member-Audit Parnet Interlocks on Audit Quality Sarowar Hossain University of New South Wales Date: Time: Venue: Friday 1 st June 3:00 to 4:30 pm Webster256

2 The Effect of Audit Committee Member Audit Partner Interlocks on Audit Quality Sarowar Hossain School of Accounting Australian School of Business University of New South Wales Sydney, NSW Australia 2052 Gary S Monroe School of Accounting Australian School of Business University of New South Wales Sydney, NSW Australia 2052 Mark Wilson School of Accounting and Business Information Systems & Research School of Business College of Business and Economics The Australian National University Canberra, ACT Australia 0200 Christine Jubb Australian National Centre for Audit and Assurance Research College of Business and Economics The Australian National University Canberra, ACT Australia 0200 Current Version, May 24, 2012 Acknowledgments: We thank Jean Bedard, Robert Knechel, Greg Trompeter, Neil Fargher, Lakshmanam Shivakumar, Andrew Jackson, Greg Shailer and participants at the 2010 AFAANZ and AAA conferences and the 2011 ANCAAR symposium for their valuable feedback on earlier versions of this paper. Contact author: Sarowar Hossain, Lecturer in Accounting, Australian School of Business, University of New South Wales, Sydney, NSW 2052, Australia s.hossain@unsw.edu.au. Tel: (612)

3 The Effect of Audit Committee Member Audit Partner Interlocks on Audit Quality ABSTRACT: We investigate the association between audit committee member audit partner interlocks and several proxies for audit quality. Audit committee member audit partner interlocks occur when an audit committee member of a company is also an audit committee member of other companies that are audited by a common audit firm and audit partner. Our results provide evidence of reduced audit quality as the number of these interlocks increases. Specifically, we find that the number of audit committee member audit partner interlocks is significantly and negatively associated with the likelihood of receiving a modified audit opinion, and positively associated with the likelihood of meeting or just beating analyst consensus forecasts, short-horizon analyst forecast accuracy and absolute value of discretionary accruals. Our analyses suggest that audit committee member and audit partner interlocks present challenges to auditor independence and audit quality. Key Words: audit quality, audit committee, audit partner, audit committee audit partner interlocks. Data Availability: All data used in this paper are publicly available. JEL codes: M4 2

4 The Effect of Audit Committee Member Audit Partner Interlocks on Audit Quality I. INTRODUCTION In the current regulatory environment, significant emphasis is placed on the audit committee s role in improving financial reporting quality, especially following the collapses of apparently healthy corporations that had received clean audit reports (Levitt 2002). The Sarbanes Oxley Act (SOX 2002) increased audit committees responsibilities and authority, requiring that audit committees oversee the auditor engagement and resolve disagreements with management on financial reporting. Both the academic literature (see Bédard and Gendron 2010) and regulatory pronouncements indicate that audit committees have the potential to play a crucial role in promoting and maintaining auditor independence and audit quality. For example, audit committee responsibilities require bi directional communication between parties whose independence is crucial to the credibility of financial reporting: audit committee members and audit engagement partners. We examine the association between audit quality and the existence of external professional relationships between an audit client s audit committee members and the audit partner. We use the number of interlocks (links) between audit committee members and audit partners as our variable of interest to investigate its association with audit quality. Audit committee member audit partner interlocks occur when an audit committee member of a company is also an audit committee member of other companies that are audited by a common audit firm and audit partner. Appendix I depicts diagrammatically the relationships important in the context of this study between audit committee member audit partner links and their expected association with audit quality. 1 When an individual sits on the audit committees of several companies audited by a common audit partner, the strength of any personal relationships that may develop between the 3

5 common audit committee member and common audit partner are likely to be relatively high due to their frequent meetings and interactions. We argue that these personal ties have the potential to erode auditor independence, and, as a consequence, reduce audit quality, and that higher numbers of such interlocks intensify any erosion of audit quality. Prior studies examining the association between audit committee effectiveness and audit quality have focused primarily on the characteristics of audit committees such as the incidence of outside directorships (DeZoort and Salterio 2001; Yang and Krishnan 2005); the proportion of non executive members (Baxter and Cotter 2009); expertise (Bédard et al. 2004); and diligence (Abbott et al.2004). Other studies suggest that the members of the audit committee who are interlocked with auditors are likely to have a greater impact on the client's decision making than other parties (such as board of directors) potentially involved in interlocking relationships with an auditor (Seabright et al. 1992; Jubb 2000). However, no prior research examines whether the effectiveness of audit committees is compromised by the presence of interlocking relationships between audit committee members and audit partners and the resulting effects on audit and financial statement quality. The dearth of directly relevant empirical evidence, and the fact that there are clear theoretical reasons to expect an association between audit quality and the number of audit committee member audit partner interlocks, is the primary motivation for the current study. Our contribution to the literature is that this is the first study to examine the effects of personal relationships created by audit committee member audit partner interlocks on audit quality. The results of this study should be important to academics, regulatory bodies, company directors and the accounting and auditing professions. This study has the capacity to inform policymakers, corporate boards, and academic researchers on the need to re consider the importance of the 4

6 composition of audit committees, specifically, in a circumstance when an audit committee member is a member of more than one company s audit committee and those companies have a common audit partner. The presence of interlocking relationships between audit committee members and audit partners is of interest to scholars and regulators because these relationships may impair auditor independence in fact and/or in appearance and thus the quality of audits and the resulting financial statements being audited. We use data from Australian listed companies to investigate the relationship between the number of audit committee member audit partner interlocks and audit quality due to the fact that, in Australia, the Corporations Act 2001 requires that the audit report must be signed in the name of the engagement partner as well as the firm. This requirement allows us to identify the engagement partner. The ASX Corporate Governance Council (2003) and the Corporate Law Economic Reform Program (CLERP 9 Act 2004) require the top 500 listed companies and any company that is included in the S&P/ASX All Ordinaries Index to have an audit committee. Australia represents a unique regulatory environment, in which listed companies have disclosed the names of audit committee members, audit firms and audit partners in their annual reports for several years, which enables us to determine the existence of interlocking relationships involving audit partners and audit committee members. Audit reports in other Anglo American jurisdictions do not allow systematic identification of engagement partners. The absence of publicly available data on audit partner identity means exploiting data from other jurisdictions is particularly valuable (Bamber and Bamber 2009). We use five proxies for audit quality. First, we measure audit quality in terms of the likelihood of issuing a modified 2 audit opinion (e.g., Carcello and Neal 2000; Reichelt and Wang 2009). In addition to our primary measure, which treats all types of modified opinions collectively, we 5

7 conduct additional analyses using going-concern modified opinions. We hypothesize that there is a negative relation between the number of audit committee member audit partner interlocks and audit quality, which may be reflected in a lower likelihood of issuing modified opinions. We argue that a significant negative association between audit committee member audit partner interlocks and the likelihood of receiving a modified opinion indicates lower audit quality arising from these interlocks. Our third and fourth proxies for audit quality relate to analyst forecasts of earnings per share (EPS). We hypothesize that the likelihood of meeting or beating analyst forecast consensus will have a positive association with the number of audit committee member-audit partner interlocks, since reduced audit quality will manifest as increased tolerance of manipulation to achieve this earnings threshold (e.g., Burgstahler and Eames 2006). Following Payne (2008), we argue that overall forecast accuracy will be positively associated with the number of audit committee member-audit partner interlocks since manipulation to meet the forecast is more likely with reduced audit quality. Our final proxy for audit quality is the client s absolute discretionary accruals, which represents the proportion of total accruals that cannot be explained by the client s economic fundamentals and is thus expected to be correlated with the client s earnings management behaviour (e.g., Jones 1991; DeFond and Jiambalvo 1994; DeFond et al. 2002; Chen et al. 2010; Chi and Chin 2011; Karjalainen 2011). The absolute value of discretionary accruals measure reflects the economic effect of management s accrual decisions regardless of direction (Francis et al. 2005). We posit that if the discretionary accruals of companies with audit committee member audit partner interlocks are indistinguishable from those of companies without such interlocks, then 6

8 the audit quality of companies with audit committee member audit partner interlocks is not likely to be different from the audit quality of companies without such interlocks. We find a significant and negative association between the number of audit committee member audit partner interlocks and the likelihood of receiving both a modified audit opinion of any type and a modified audit opinion for going concern issues. This result provides evidence that higher numbers of links between audit committee members and a common audit partner reduce the likelihood of a company receiving a modified opinion from its auditor. In terms of analyst forecasts, we find a significant and positive association between the number of audit committee member-audit partner interlocks and both meeting / beating analysts consensus EPS and forecast accuracy. We also find a significant and positive association between the number of audit committee member audit partner interlocks and the absolute value of discretionary accruals. These results provide evidence of reduced audit quality when there are more links between audit committee members and a common audit partner. Our results are robust to alternative samples and different models of estimating discretionary accruals. Our sensitivity analyses suggest that audit committee member and audit partner interlocks present more serious challenges to auditor independence and audit quality than simple director audit partner interlocks or audit committee member audit firm interlocks. These findings may inform future regulatory initiatives to discourage or prevent companies from appointing an audit committee member of a company with the same audit partner. Alternatively, the results may support a future move to impose a cooling off period before an audit committee member can serve as an audit committee member of another company with the same audit partner. 7

9 The remainder of the paper is organised as follows: Section II discusses the prior literature and development of the hypothesis. Section III provides the research method and definitions of variables. Section IV reports the findings followed by our conclusions in section V. II. PRIOR LITERATURE AND HYPOTHESIS DEVELOPMENT Traditional agency theory identifies external auditors as one of the primary monitoring mechanisms employed to reduce the costs of imperfect incentive alignment between managers and shareholders (Jensen and Meckling 1976). However, the effectiveness of auditing relies on the independence of those providing the audit service. 3 Regulators have expressed concerns that close relationships between auditors and their clients may have a detrimental effect on auditor independence and audit quality. 4 From an audit firm's perspective, a close relationship developed at both the firm and audit partner levels may enhance the likelihood of an auditor engaging in repeated dealings with a client (Myers et al. 2003; Huntley 2006; Ye et al. 2011). However, a relationship between a client s audit committee members and its auditor may lead to the development of personal relationships to the extent of developing bonds of loyalty, trust or emotive relationships (psychological dependence) so that truly independent auditor behavior becomes difficult (AICPA 1992; Arel et al. 2005). This is especially true at the audit partner level where close associations with audit committee members may create a familiarity threat to auditor independence. Several studies report that familiarity threats arising from longer auditor tenure impair audit quality (e.g., Ghosh and Moon 2005; Mansi et al. 2004; Ryken et al. 2007; Turner et al. 2008; Boone et al. 2008). Although their findings and concerns relate to auditor tenure, a similar reduction in audit quality could occur where audit committee-audit partner interlocks induce more frequent interactions between an audit partner and audit committee members. As the audit partner-audit committee member relationship deepens, auditors may 8

10 develop a learned confidence in the client (described in the IFAC Code of Ethics as a familiarity threat), which may result in the auditor not testing financial report assertions, anticipating results instead of being alert to anomalies, using less rigorous audit procedures or using static audit programs (Hoyle 1978; Shockley 1981; AICPA 1992; Arrunada and Paz Ares 1997; Johnson et al. 2002; GAO 2003). The consequences of diminished independence resulting from a close relationship between the auditor and the client include the increased likelihood of the auditor acceding to client pressure in relation to their choice and application of accounting policies and, at the extreme, the possibility that excessive familiarity may result in collusion between the auditor and the client (McLaren 1958). Although these arguments may apply to both the audit firm and the audit partner, the arguments are stronger for individual auditors because of the emphasis on individual incentives and personal relationships. For example, Bamber and Iyer (2007) provide evidence that the length of an individual auditor s tenure with a client is associated with the extent to which the auditors identify with a client, which in turn affects the independence of the auditors acceptance of clients preferred outcomes. Similar to the relationships created by long auditor tenure, the relationships created by interactions between an audit partner and audit committee members may affect the extent to which auditors identify with audit committee members, which may in turn affect their independence. Therefore, as the number of audit committee member audit partner interlocks increases, the familiarity threat to auditor independence can be expected to increase, which may result in lower audit quality. Hypothesis 1 reflects this prediction. H1: The number of audit committee member audit partner interlocks is negatively associated with audit quality. 9

11 This potential impairment of auditor independence and audit quality may be manifested in any or all of our proxies for audit quality (audit opinion type, meet/beat analyst forecast, forecast accuracy, earnings management) the rationale for each of which is explained next. Audit Opinion We define modified opinions to comprise all audit opinions other than a standard clean opinion and include emphasis of matter paragraph opinions attached to otherwise unqualified audit reports. The likelihood that an auditor will issue a modified opinion has been employed in the prior literature as a proxy for audit quality (Lennox 2000; Bradshaw et al. 2002; Chi and Chin 2011). If auditors independence is impaired, they may be less likely to issue modified opinions when such opinions are warranted. Prior studies report that companies with interlocking directorates tend to choose a common audit firm (e.g., Davison et al. 1984; Jubb 2000). Houghton and Jubb (2003) argue that the resulting director-audit firm interlocks may influence the auditor s decision regarding whether to issue a modified audit opinion for an interlocked company, because this may result in the loss of multiple clients. Rather than consider all interlocks between directors and audit firms, we follow the logic of Seabright et al. (1993) and focus on audit partners relationships with audit committee members due to the frequency of interaction between these parties, the partners direct influence on audit effort and quality and the audit committee s role in auditor appointment, removal and remuneration. 5 An auditor working on an engagement where there is at least one audit committee member who also fulfils this role for other(s) of the auditor's clients may believe that the issuance of a (justified) modified audit opinion will reduce the likelihood of retention of not only 10

12 this client's business, but also the business of other companies with audit committees on which the audit committee member is represented. The potential for auditor dependence on revenue from particular clients or groups of clients is not restricted to small audit firms. Regardless of the audit firm identity, audit partners service a limited number of clients concurrently, generally from a single office, and loss of a client implies potential personal costs to that partner. There are, however, circumstances in which these relationship links may actually enhance audit quality. Audit committee member audit partner interlocking may enhance auditor independence because the relationship may increase the likelihood that audit committee members defend the auditor where disagreement with management regarding reporting issues arises (DeZoort and Salterio 2001; DeZoort et al. 2002). Notwithstanding this, we argue that the potential agency effects, which imply a reduction in audit independence, are likely to dominate, for the simple reason that agency costs directly affect auditors expected financial remuneration. Thus we expect a negative association between audit committee member audit partner links and the likelihood of issuing a modified audit opinion by the auditor. We employ two empirical measures of the type of audit opinion issued. First, we identify modified audit opinions (MODOPINION) using a dummy variable equal to one if the auditor issues anything other than a clean opinion, and zero otherwise. 6 During our sample period, AUS 702 (AuASB 2002) prescribed the range of modified audit opinion types available, which comprise emphasis of matter paragraph opinions and qualified opinions. Emphasis of matter paragraph opinions may arise from inherent uncertainties (including going concern issues), inconsistent other information in the annual report, inappropriateness of the going concern assumption as a result of new conditions occurring after balance date, and subsequent events resulting in a new audit report on revised financial statements. Qualified opinions may be due to 11

13 restrictions of scope, disagreements with management (which may involve going concern issues), and conflicts between applicable reporting regimes. These opinions can take the form of except for, adverse, or limitation on scope opinions. Our second opinion-based proxy is GCOPINION, a dummy variable equal to one if the audit opinion is modified and the reason(s) cited includes going concern issues. When testing this proxy, we follow Carey and Simnett (2006) and restrict our sample to firms with current year losses or negative operating cash flows. Analyst Forecasts Recent studies have argued that analyst forecast errors proxy for audit quality (Behn et al. 2008; Payne 2008; Davis et al. 2009). The relation between analyst forecast errors and audit quality is examined through two main metrics: the likelihood of a client meeting or just beating analyst consensus forecast earnings, and the absolute value of analyst forecast errors. Meeting or Just Beating Consensus There is a significant literature documenting an abnormally large frequency of company-years for which earnings per share (EPS) equals or just exceeds the consensus analyst forecast EPS (McVay 2005; Burgstahler and Eames 2006; Davis et al. 2009). One explanation for this discontinuity is that there are market penalties for failing to meet analysts earnings expectations (Bartov et al. 2000), and that this induces managers to manipulate accruals to allow reported EPS to meet or just beat consensus. The resulting accrual manipulation may be income-increasing, in the case of firms where underlying earnings are below consensus, or income-decreasing for firms where underlying earnings comfortably exceed consensus, and which wish to preserve reporting flexibility for future periods. Payne (2008) and Davis et al. (2009) argue that high quality audits 12

14 are more likely to constrain such accrual manipulations, resulting in a lower probability of client firms meeting or just beating consensus. Payne (2008) reports a lower likelihood of client firms meeting or just beating consensus when audits are conducted by industry specialist auditors. Davis et al. (2009) report that the likelihood of using accruals management to meet or just beat consensus declines with audit firm tenure, where tenure is less than 14 years, but thereafter increases. We measure analysts consensus forecast as the median of individual analysts EPS forecast issued or confirmed as current in the 60 days prior to reporting. Forecast error is the difference between actual EPS and consensus forecast EPS. We use a dichotomous variable (MBE) to measure the incidence of small positive forecast errors. We classify a company as meeting or just beating consensus (MBE = 1) if the unscaled forecast error is between 0 and 0.5 cents inclusive, a range derived from histograms of earnings distributions and for which the proportion of observations within is similar to US studies (which employ a range of 0 1 cent). 7 Because we argue that audit committee-audit partner interlocks impair audit quality, we predict that higher numbers of these relationships existing for a given company increases the likelihood of meeting or just beating consensus. Analyst Forecast Accuracy In addition to the incentive for companies to meet or just beat analyst forecast earnings, Payne (2008) argues that lower audit quality increases the accuracy of consensus analyst earnings forecasts current at reporting date. Assuming that audit clients have broad incentives to manipulate earnings in the direction of analysts consensus, and that higher audit quality is more effective in constraining earnings manipulation, absolute forecast errors will increase with audit 13

15 quality. Why might companies seek to minimise absolute forecast errors aside from cases where reported earnings meet or just beat consensus? Companies where underlying earnings comfortably exceed consensus may manage earnings downwards to provide greater scope for future earnings manipulation and manage analyst expectations for the following year s earnings (Payne and Robb 2000; Payne 2008). Companies where underlying earnings are below consensus may manage earning upwards, even though such manipulations may not result in reported earnings reaching consensus. Income-increasing manipulations that fail to result in the client meeting or just beating consensus may occur for at least three reasons. First, the stock return penalty for missing the earnings benchmark is decreasing in the amount of the forecast error (Bartov et al. 2000). Second, analysts may revise their forecasts upwards after most or all accruals decisions are finalised. Finally, client attempts to bias a series of accrual decisions may be successful in some cases, but not in others, leaving reported earnings below consensus. Payne (2008) finds that several measures of auditor industry specialisation (proxying for audit quality) are associated with higher absolute forecasts errors, supporting his prediction. Behn et al. (2008) also use absolute analyst forecast errors as a proxy for audit quality, however, they interpret greater accuracy as an indicator of higher audit quality. While the argument that higher quality earnings make future earnings more easily predictable is appealing, this perspective applies most clearly to long-horizon forecast accuracy (the accuracy of forecasts issued immediately after prior year earnings announcements). In the case of short-horizon forecasts, Behn s approach ignores clients incentives to manage earnings in the direction of consensus. Given that our focus, and that of the extant literature, is on short-horizon forecasts (i.e., those made immediately before earnings are reported), we favour Payne s (2008) interpretation of the relation between audit quality and absolute forecast errors. 8 Consequently, 14

16 we predict a positive association between audit committee member audit partner links and analyst forecast accuracy. We define accuracy (ACCURACY) as the negative of the absolute value of consensus EPS forecast error, based on all forecasts current in the 60 days immediately prior to reporting. We apply the negative transformation so that ACCURACY increases as forecast errors become smaller. Earnings Management Earnings management refers to the use of accounting discretion to bias reported earnings away from the level that would be reported if accounting standards were applied objectively, either to affect contractual outcomes or to mislead stakeholders as to the firm s performance (Healy and Wahlen 1999). Consistent with prior literature, which argues that unsigned measures of earnings management are a more complete measure of managerial reporting discretion tolerated by the auditor (Becker et al. 1998; Frankel et al. 2002; Menon and Williams 2004; Hoitash et al. 2007), we use the absolute value of discretionary accruals as our fifth and final proxy for audit quality. Where audit quality is low, absolute discretionary accruals are likely to be greater, because managerial attempts to manipulate earnings are more likely to have been successful. There is mixed evidence regarding the relationship between audit committee independence and audit quality. Klein (2002) reports that firms whose audit committees comprise a majority of outside directors have significantly lower absolute value of discretionary accruals. Bédard et al. (2004) find that audit committees comprised entirely of independent directors reduce aggressive earnings management. Choi et al. (2004) find that firms whose audit committee members have lower shareholdings (which proxies for greater independence) have significantly lower absolute discretionary accruals. However, some studies find no relation between proxies for audit 15

17 committee independence and audit (earnings) quality. Peasnell et al. (2005) find no direct relationship between the independence of audit committees and abnormal current accruals associated with benchmark beating incentives in British firms. Similarly, Baxter and Cotter (2009) find no relation between absolute discretionary accruals and the proportion of independent directors on Australian firms audit committees. The literature summarized above focuses on the characteristics of the audit committee. Our hypothesis, however, focuses on personal, rather than firm level links, fundamentally because it is individuals who may derive utility (disutility) from the state of these relationships, and who make decisions accordingly. We focus on audit committee members and audit partners because these individuals are arguably in the strongest position to influence the audit outcome. The arguments underpinning the earnings management expectations mirror those discussed previously and for brevity we do not repeat them in detail in this section. In summary, interlocking audit committee-audit partner relationships increase both financial and personal incentives for the parties involved, which may impair audit quality as reflected in the absolute value of discretionary accruals. Consequently, we predict a positive relationship between the number of audit committee-audit partner links and absolute discretionary accruals. To estimate discretionary accruals, we use an adaptation of the modified-jones model that includes controls for current performance (Kothari et al. 2005) and the change in net external financing (Shan et al. 2011). 9 Subject to a minimum of 10 observations in each industry category for each year, this model is estimated cross sectionally for each 4 digit Global Industry Classification Standard (GICS) (6 digit for the Materials sector) industry group in each of the years as per Equation (1): 16

18 TACC it = α + 1 (ΔREV ΔREC) it,t PPE it + 3 ROA it + 4 ΔNETEX it,t-1 + ε it (1) Where for company i and time t: TACC = total accruals, equal to the difference between operating income (OI) and cash flow from operations (CFO); ΔREV = change in revenue from period t 1 to period t; ΔREC = change in net accounts receivables from period t 1 to period t; PPE = ROA = opening gross value of property, plant and equipment; return on assets for period t, defined as net operating profit divided by average total assets. ΔNETEX = change in net external financing, calculated as the net increase in contributed equity (after deducting dividends) plus the increase in non-interest debt cash flows. e = error term, the absolute value of which represents estimated discretionary accruals. The intercept and all variables, other than ROA, are scaled by the average value of total assets between t and t-1 to reduce heteroskedasticity. We expect a positive relationship between absolute discretionary accruals (DACC) and the number of audit committee-audit partner interlocks, because such relations are expected to impair audit quality. III. RESEARCH METHOD We now explain and describe our measures of audit committee-audit partner interlocks and the models used to test the association between this measure and our audit quality proxies. 17

19 Measuring Audit Committee-Audit Partner Interlocks We used company annual reports to identify all audit committee members who attended at least one audit committee meeting and then prepared a list of each individual s annual audit committee memberships. Cases of individuals apparently sitting on multiple audit committees were verified using additional sources, including company and stock exchange websites. We collected names of audit firms and their signing partners from each company s audit report. The lists of audit committee members, audit firms and audit partners, and the companies to which they were connected were then reconciled to identify cases in which firms shared a common audit committee-member and a common audit partner. From this data, we calculated the number of unique audit committee-audit partner interlocks (AC AP_Lks). For a given company, AC- AP_Lks is equal to the number of other companies that have a common audit partner AND at least one common audit committee member. Appendix II provides a detailed example of this calculation. Regression Models This section describes the models used to examine the association between the number of interlocks and our five proxies for audit quality. 10 Our first three models are logistic regressions of factors explaining the likelihood of receiving a modified audit opinion for any reason (Eqn. 2), a modified opinion for going concern reasons (Eqn. 3), and meeting or just beating consensus earnings forecasts (Eqn 4). The final two models are OLS regressions of forecast accuracy (Eqn. 5) and absolute discretionary accruals (Eqn. 6). The specification of the models is as below: 18

20 MODOPINION it = AC-AP_Lks it + 2 ACSIZE it + 3 INDEPAC it + 4 BIG4 it + 5 SIZE it + 6 LEVERAGE it + 7 LOSS it, t ROA it + 9 PMOD it ZSCORE it + 11 CATA it + 12 FEERATIO it + ε it (2) GCOPINION it = AC-AP_Lks it + 2 ACSIZE it + 3 INDEPAC it + 4 BIG4 it + 5 SIZE it + 6 LEVERAGE it + 7 LOSS it, t ROA it + 9 PGC it ZSCORE it + 11 CATA it + 12 FEERATIO it + ε it (3) MBE it = AC-AP_Lks it + 2 ACSIZE it + 3 INDEPAC it + 4 BIG4 it + 5 SIZE it + 6 LEVERAGE it + 7 LOSS it,it ROA it + 9 CHGINC it + 10 PERSIST it + 11 DISPERS it + 12 NUMEST it +ε it (4) ACCURACY it = AC-AP_Lks it + 2 ACSIZE it + 3 INDEPAC it + 4 BIG4 it + 5 SIZE it + 6 LEVERAGE it + 7 LOSS it, t ROA it + 9 ABSCHGINC it + 10 PERSIST it + 11 DISPERS it + 12 NUMEST it +ε it (5) DACC it = AC-AP_Lks it + 2 ACSIZE it + 3 INDEPAC it + 4 BIG4 it Where for company i and time t: + 5 SIZE it + 6 LEVERAGE it + 7 LOSS it, t ROA it + 9 MB it + 10 CFVOL it-1. t-5 + ε it (6) Dependent Variables MODOPINION = 1 if the auditor issues any form of modified (including emphasis of matter, except for, adverse or limitation on scope) opinion in the current year, 0 otherwise; 19

21 GCOPINION = 1 if the auditor issues any form of modified (including emphasis of matter, except for, adverse or limitation on scope) opinion for reasons pertaining to going concern issues; MBE = meet or beat earnings forecast, 1 if EPS forecast errors >=0 and <=0.5 cents, 0 otherwise; ACCURACY = negative of the absolute value of the forecast error, measured as the difference between actual EPS and the median forecast EPS; DACC = absolute value of discretionary accruals calculated as the residuals from Equation (1); Test Variable AC AP_Lks = number of unique audit committee member audit partner interlocks extant for the client; Control variables BIG 4 = ACSIZE = INDEPAC = 1 if company s incumbent auditor is a BIG 4 audit firm, 0 otherwise; number of audit committee members; 1 if the audit committee comprises a majority (fifty percent or more) of non executive directors, 0 otherwise; SIZE = LEVERAGE = natural log of total assets; ratio of total liabilities to total assets; LOSS = 1 if the company reported a loss either in the current year or previous year, 0 otherwise; ROA = operating income divided by average total assets; PMOD = 1 if the company s previous period audit report was modified for any 20

22 reason, 0 otherwise; PGC = 1 if the company s previous period audit report was modified for going concern reasons; ZSCORE = Zmijiewski s Z-score, a measure of financial distress; CATA = ratio of current assets to total assets; FEERATIO = ratio of fees paid for non-audit services to total audit and non-audit fees. PERSIST = 1 if the company-year lies between the 20 th and 80 th percentiles of the distribution of change in EPS; CHGINC = 1-year change in actual EPS deflated by beginning net assets per share ; ABSCHGINC = absolute value of the 1-year change in actual EPS deflated by beginning net assets per share; DISPERS = standard deviation of forecast EPS; NUMEST = number of analysts who have issued or confirmed as current an EPS forecast for the firm in the 60 days immediately prior to reporting. MB = end-of-year market value of equity divided by book value of shareholders equity; CFVOL = 5-year standard deviation of company s cash flow from operations (deflated by total assets) measured between t-5 and t-1. The control variables used in this study are drawn from the extant literature. We first describe the set of control variables that are common to all five audit quality proxies, before focussing on the controls specific to particular models. 21

23 We include a control for audit committee size (ACSIZE) in all models because this variable is likely to be correlated with our test variable and prior research reports an association between this measure and proxies for audit quality including discretionary accruals (Zhou and Chen 2004) and audit opinion (Carcello and Neal 2000; Monroe and Teh 2000). Audit committee independence (INDEPAC) has been previously found to be associated with audit opinion (Carcello and Neal 2000) and absolute discretionary accruals (Klein 2002). While we are not aware of research that directly relates ACSIZE or INDEPAC to forecast errors, we include this variable in our forecast error models to avoid the possibility of spurious correlation affecting our test results. We control for audit firm size (BIG4) because large audit firms may possess a technological advantage and because smaller audit firms may be less willing to issue modified audit opinions due to their greater financial dependence on individual clients (Monroe and Teh 1993; Jackson et al. 2008). Audit firm size has also been associated with the accuracy of analyst forecasts (Behn et al. 2008), and absolute discretionary accruals (Becker et al. 1998; Francis et al. 1999). The natural log of total assets (SIZE) is used to control for the effect of company size on the audit opinion because, for a large company, it is less likely that any uncertainties will be material enough to issue a modified opinion compared to a smaller entity (Monroe and Teh 1993; Chen et al. 2010; Chi et al. 2011). Company size has also been strongly associated with the accuracy of analyst forecasts (Lang and Lundholm 2006), the likelihood of meeting or beating consensus (Davis et al. 2009; Payne 2008) and absolute discretionary accruals (Dechow and Dichev 2002; Hribar and Nicholls 2007). Financial leverage (LEVERAGE) is a measure of long term solvency and financial risk which has been shown to be correlated with the likelihood of issuing a modified audit opinion (Chi and Chin 2011), the likelihood of meeting or just beating 22

24 consensus forecasts (Davis et al. 2009), forecast accuracy (Lang and Lundholm 1996; Hope 2003), and absolute discretionary accruals (Hribar and Nicholls 2007). The incidence of financial losses in the current or prior year (LOSS) increases the likelihood of a modified audit opinion because of increased bankruptcy and auditor litigation risk (Lai and Yim 2003; Chen et al. 2010; Chi e al. 2010). Losses are also associated with greater absolute discretionary accruals (Frankel et al. 2002), less accurate analyst forecasts (Payne 2008) and a lower probability of meeting or beating consensus forecasts (McVay et al. 2006). In addition to our LOSS dummy, we include a continuous control for performance in a company s return on assets (ROA). An auditor may consider return on assets (ROA) when assessing the going concern status of a client, which may affect the likelihood of issuing a going concern type modification (Monroe and Teh 2000, Chen et al 2010, Chi et al. 2011). Performance has also been associated with a higher probability of meeting or beating analyst forecasts (Davis et al. 2009), more accurate analyst forecasts (Payne 2008) and lower absolute discretionary accruals (Frankel et al. 2002). 11 We employ three control variables specific to our audit opinion model. The current year s audit opinion is likely to be influenced by the prior year s audit opinion (Mutchler 1985, Monroe and Teh 1993, Chen et al. 2010, and Chi et al. 2011). We use PMOD and PGC to control for this effect. Following Carey and Simnett (2006) and Chi and Chin (2011) we include a variant of Zmijiewski s (1984) Z-Score to control for the impact of the client s level of financial distress on audit opinion. 12 We include clients ratio of current assets to total assets as a proxy for the effect of liquidity on opinion (Chi and Chin 2011). Finally, we include the ratio of non-audit fees to the 23

25 sum of audit and non-audit fees (FEERATIO) to control incentive problems associated with auditor dependence on fees from non-audit sources (Carey and Simnett 2006). We include several control variables specific to our analyst forecast regressions. Consistent with prior literature we control for the impact of analyst forecast dispersion (DISPERS) on both the probability of meeting or beating consensus (Payne and Robb 2000; Davis et al. 2009), and forecast accuracy (Payne 2008). We also control for the 1-year change in earnings per share (CHGINC) in our benchmark beating model and the absolute change in earnings per share (ABSCHGINC) in our forecast accuracy model (Payne 2008). We include an indicator variable (PERSIST) identifying companies in the middle three quintiles of the distribution of changes in earnings per share, because companies with highly persistent earnings are associated with greater forecast accuracy and a higher probability of meeting or beating consensus forecasts (Payne 2008). Finally, we control for analyst coverage (NUMEST) in each of our analyst forecast models because the number of analysts covering a company may increase the importance of meeting or beating consensus (Davis et al. 2009), and is associated with greater forecast accuracy (Payne 2008). In our discretionary accrual model we include the 5-year cash flow volatility (CFVOL) to control for impact of operating volatility on absolute measure of discretionary accruals (Hribar and Nicholls 2007). We include the market to book ratio (MB) to control for the potential effects of growth options on earnings management. 24

26 IV. SAMPLE AND RESULTS Data Sources We use data from Australian-domiciled companies listed on the Australian Securities Exchange (ASX) during to investigate the relationship between the number of audit committee member audit partner interlocks and audit quality. Data regarding the identity of audit committee members and audit partners was hand collected from companies annual reports available in the AspectHuntley or Connect4 databases. Financial data was obtained from the AspectHuntley FinAnalysis database. Analyst forecasts and actual earnings per share were obtained from the I/B/E/S Detail History File. Sample Selection and Description Our sample period begins in 2003 because audit committees were not mandatory for Australian companies prior to that year. The ASX Corporate Governance Council (2003) and the CLERP 9 Act (2004) require audit committees for the Top 500 listed companies. The ASX amended its listing rules in 2003 to require any company included in the S&P/ASX All Ordinaries Index at the beginning of the financial year to have an audit committee during that year. These changes increased the rate of disclosure and made it easier to identify audit committee members and other corporate governance mechanisms, which may not have been disclosed in the earlier years. Our sample period concludes in 2006 to mitigate the potential for noise accompanying the global financial crisis and its antecedents. 13 Table 1, Panel A details the determination of the samples employed for models testing each of our audit quality proxies. Current and prior year financial data for ASX listed companies is available for 5,255 companies during Three sample restrictions are applied to all 25

27 models. First, we exclude companies that had no audit committee because such companies cannot, by definition, have audit committee-audit partner links, and their inclusion increases the chance of spurious correlation affecting our results. Second, we exclude companies with two audit firms/partners named in a given year, because it is difficult to determine influence in these cases. Finally, we exclude from all models companies that were technically insolvent at balance date, because audit committee-audit partner links that arise in these cases are likely to be the consequence of debt guarantees from related parties, and inferences drawn from these firm s behavior is unlikely to be generalizable. <Insert Table 1 about here> From our modified audit opinion sample we also exclude banks and insurance companies because traditional audit opinion models are not well specified for these entities. These sample criteria result in a final sample of 3,520 company-year observations for our modified audit opinion model. The sample used to test our going concern opinion model is further restricted, including only observations for which a going concern modification is plausible. Following Carey and Simnett (2006) we restrict the sample for this model to observations recording either (or both) a current year financial loss or negative cash from operations. We also exclude from this sample, audit clients that have modified audit opinions that do not involve going concern issues, because these add unnecessary noise to the estimation. Our final sample used to test the going concern model is 1,527 company-year observations. Our analyst forecasts sample is restricted to companies with analyst coverage available on I/B/E/S (1,420 company-year observations). We also exclude companies with missing lagged I/B/E/S data, resulting in a final sample of 1,270 company-year observations. 26

28 The data requirements of our Jones-type discretionary accruals models further reduce the sample available for estimating our absolute discretionary accrual regression. Because Jones type discretionary accrual models are unlikely to produce sensible estimates of earnings management for financial sector entities, we exclude these from our sample. To reduce the impact of outliers associated with companies undergoing significant structural change and extreme performance we also exclude observations where absolute total accruals exceed 100 percent of average total assets or absolute return on assets exceeds 100 percent because these outliers exert significant leverage on the regression models used to measure discretionary accruals. Additionally, we require at least 10 observations for each 4-digit GICS industry year sub sample in order to generate reliable estimated regression coefficients. The industry distribution of each sample is describe in Panel B of Table 1 In Table 2, we describe the frequency of audit committee-audit partner interlocks in each of our samples. Between 6 percent and 10 percent of firms in our samples have at least one audit committee-audit partner interlock. An untabulated analysis reveals that the incidence of audit committee-audit partner interlocks is greater in the smallest and largest firm size quartiles. Other distributional properties of these variables are provided in the descriptive statistics accompanying each regression model. <Insert Table 2 about here> We report the size distribution of firms with at least one audit committee-audit partner interlock in Table 3. While the incidence of interlocks is relatively evenly distributed across size quartiles for the going concern and discretionary accruals samples, there is a clear over-representation of interlocked firms in the largest size quartile in the modified opinion and analyst forecast samples. 27

29 While we include firm size as a control in all of our empirical tests, to the extent that this control is imperfect, it is possible that any observed correlation between AC-AP_LKS and our audit quality proxies could reflect a residual size effect. For this reason, we later test the sensitivity of our main results to sample variation conditioned on size. Descriptive statistics for our sample companies are provided in Table 4. The incidence of modified audit opinions (MODOPINION) in our first sample (11.8 percent) is lower than that of comparable studies such as Herbohn and Raganathan (2008), who observe modified opinions in 15.6 percent of Australian firms between 1999 and This difference largely reflects our exclusion of companies without audit committees, which tend to be smaller, riskier corporations (if we relax this restriction 16.6 percent of firms with available data have modified audit opinions). <Insert Table 2 about here> The incidence of going concern modifications (GCOPINION) in our sample of financially distressed firms (20.0 percent) is considerably higher than the 12.7 percent reported by Carey and Simnett (2006), who used data from Since their sample period, there has been a considerable increase in the number of smaller and riskier listed companies (largely dotcoms and exploration companies), which may explain this difference. The proportion of firms that meet or just beat consensus (0 <= forecast error r < 0.5) at 17.6 percent is slightly lower than US studies (which employ a 1 cent upper threshold). 14 Raw forecast accuracy (-0.026) is greater than that of Payne (2008) (equivalent to ), but this is likely due to differences between US and Australian mean earnings per share. Absolute discretionary accruals have a mean (median) of 7.7 percent (4.8%) and standard deviation of 8.9 percent, suggesting that our model of discretionary 28