jackson et al - 2008 - mandatory audit firm rotation and audit quality in australia [mafr]

Mandatory audit firm rotation and audit quality Andrew B. Jackson School of Accounting, The University of New South Wales, Sydney, Australia Michael Moldrich KPMG, Sydney, Australia, and Peter Roebuck School of Accounting, The University of New South Wales, Sydney, Australia Abstract Purpose – The purpose of this paper is to investigate the effect that a regime of mandatory audit firm rotation would have on audit quality. Design/methodology/approach – Using two measures of audit quality, being the propensity to issue a going-concern report and the level of discretionary accruals, the paper examines the switching patterns of clients in their current voluntary switching capacity, and the levels of audit quality. Findings – The main finding is that audit quality increases with audit firm tenure, when proxied by the propensity to issue a going-concern opinion, and is unaffected when proxied by the level of discretionary expenses. Given the additional costs associated with switching auditors, it is concluded that there are minimal, if any, benefits of mandatory audit firm rotation. Research limitations/implications – A limitation of this study is that only actual audit quality is examined. While the results suggest that actual audit quality is associated with the length of audit tenure, the perception of audit quality is not addressed, which may increase with audit firm rotation. Originality/value – The results go against the move towards mandatory audit firm rotation, and suggest that other initiatives may need to be considered to address concerns about auditor independence and audit quality. Keywords Auditing, Auditors, Laws and legislation, Australia Paper type Research paper Introduction Considerable research has examined the effect that the length of the auditor-client tenure has had on audit quality, but commonly fails to consider the financial characteristics of clients in the years preceding a switch. This study examines the financial attributes of clients in the years preceding and succeeding an audit firm switch, as well as voluntary auditor switching behaviour to determine whether such auditor movements would be favourable under a scheme of mandatory rotation. The ability of the top-tier audit firms and industry-specialists to provide consistently high levels of audit quality is also studied. The current issue and full text archive of this journal is available at www.emeraldinsight.com/0268-6902.htm The views expressed in this paper are not necessarily the views of KPMG. Financial assistance for this study was kindly provided by the Capital Markets and Co-operative Research Centre and the Australian School of Business, UNSW. The authors would also like to acknowledge the helpful comments of participants at the 2005 Faculty of Commerce and Economics UNSW National Honours Colloquium, Liz Carson, Jeff Coulton, Asher Curtis, Rob Czernkowski, Andrew Ferguson, Gerry Gallery, Caitlin Ruddock, Roger Simnett, Stephen Taylor, and two anonymous reviewers. All errors remain the authors’ responsibility. MAJ 23,5 420 Managerial Auditing Journal Vol. 23 No. 5, 2008 pp. 420-437 q Emerald Group Publishing Limited 0268-6902 DOI 10.1108/02686900810875271 Following recent legislative changes imposed on the auditing profession through the introduction of the Corporate Law Economic Reform Program (Audit Reform & Corporate Disclosure) Act 1999 (CLERP 9), there is a need to determine whether the current regulations are enough, or whether further regulatory changes, such as a system of mandatory audit firm rotation, are desirable. There has also been a call for further research on this topic by both the international standard setters and academics (Government Accountability Office – GAO, 2003; Nagy, 2005). This study is further motivated by a lack of research examining characteristics of the client in the years prior to the audit firm switch, which may have an impact on subsequent audit quality. The aim of this study is to understand whether the client’s financial characteristics under the predecessor auditor have an impact on audit quality under the incumbent auditor. An additional aim is to determine whether current voluntary switching patterns would be conducive to a system of forced rotation, and whether the top-tier audit firms and industry specialists are able to provide higher levels of audit quality over a period of time. We find that audit quality increases with audit firm tenure, when proxied by the propensity to issue a going-concern opinion, and is unaffected when proxied by the level of discretionary accruals (DA). Given our results, we conclude that mandatory audit firm rotation will not improve audit quality. Considering the costs involved during the early stages of an auditor-client relationship, requiring firms to rotate their auditors will place unnecessary costs on both the auditor and the client with minimal benefits. In order to address concerns that have arisen surrounding auditor independence issues, we conclude that other initiatives are more likely to have a greater impact than mandatory audit firm rotation. Background and empirical predictions Audit firm rotation A system of mandatory audit firm rotation would require companies to rotate their independent auditor periodically. Currently, listed companies in Italy and Brazil are required to rotate their independent auditor every nine and five years, respectively. In Australia, there is currently no legislative requirement for reporting entities to rotate their independent audit firm, although periodic rotation of lead audit partners is now obligatory under s324DA of the Corporations Act 2001 (Cth). Advocates of audit firm rotation believe a scheme of compulsory rotation would prevent auditors from becoming too aligned with managers, impacting on their independence. A client may be a significant source of revenue for an auditor, and the auditor may be reluctant to jeopardise this revenue stream (Hoyle, 1978). Firm rotation may also help to prevent large-scale corporate collapses. Morgan Stanley estimates the market capitalisation loss of the collapses of WorldCom, Tyco, Quest, Enron and Computer Associates to be $US460 billion. Firm rotation can help restore confidence in the regulatory system, which was found to be the case in Italy (Healey and Kim, 2003). Further, if a client seeks a new auditor, auditors will compete with other audit firms to win the tender and differentiate themselves in terms of service, improving audit quality (Hoyle, 1978). Despite the increased start-up costs which are involved with introducing a new auditor, supporters of audit firm rotation propose that the costs of corporate collapses, which may not have occurred had audit quality been higher, outweigh the increase in audit costs involved when introducing a new auditor. From this Audit firm rotation and audit quality 421 perspective, a new auditor brings in more objectivity as they are not familiar with the client, potentially improving the quality of the audit. On the contrary, mandating firm rotation would lead to a loss of client knowledge when the auditor is forced to resign. Auditors experience a significant learning curve with new clients (Knapp, 1991), and much of the knowledge acquired during an audit is client-specific (Kinney and McDaniel, 1996). Audit failures are generally higher in the first years of the auditor-client relationship as the new auditor becomes familiar with the client’s operations (Arel et al., 2005). Audit costs would also rise due to the additional work needed by the new audit firm. The GAO (2003) estimated that companies would incur additional auditor selection costs equal to 17 per cent of their first year audit fees (GAO, 2003). Opportunity costs would also arise because of a mismatch between the client’s needs and those which the auditor can offer (Arrun ˜ ada and Paz-Ares, 1997). Auditor resignations provide valuable signals to the market (Wells and Loudder, 1997). Under mandatory rotation, if a client is experiencing conflicts with its auditor over accounting treatments and the auditor is forced to rotate, the market misses out on valuable signals that would have taken place under voluntary rotation. The largest accounting firms may also increase their market share under mandatory rotation, as has been the case in Italy (Buck and Michaels, 2005), leading to a less-competitive environment. Even if research has generally not found significant positive effects of firm rotation on audit quality, rotation may nevertheless be effective in increasing perceived audit quality. Audit quality comprises actual and perceived quality (Taylor, 2005). Actual quality is the degree to which the risk of reporting a material error in the financial accounts is reduced, while perceived quality is how effective users of financial statements believe the auditor is at reducing material misstatements. Higher perceived audit quality may then help promote investment in audited clients. Related literature and empirical predi ctions It has been argued that companies switch auditors to avoid receiving qualified audit reports. This argument assumes that managers dislike qualified reports and that manager’s influence the appointment decision. The first assumption is relatively uncontroversial. A qualified report may signal to investors that managers are poor stewards of the company’s affairs, or that managers have attempted to present an over-favourable view of the company’s performance and/or position. In addition, qualified reports cause share prices to fall, reducing managerial utility if managers own shares or if their compensation is directly related to market value (Firth, 1978; Banks and Kinney, 1982; Fleak and Wilson, 1994; Chen and Church, 1996; Jones, 1996). The second assumption is more controversial. By law in Australia, auditors are appointed by shareholders. However, managers may exert considerable influence over auditor appointments. Incumbent auditors could be dismissed by managers without consulting shareholders, with the shareholders merely voting on whether to accept their recommendation regarding the appointment of a new auditor or the re-appointment of the incumbent. Secondly, managers have some influence over the appointment of a new auditor or the re-appointment of the incumbent auditor. Managers set meeting agendas when auditor appointments are proposed, and they MAJ 23,5 422 typically have the proxy votes of a large number of shareholders. Thus, managers have considerable influence over auditor hiring and firing. If managers dislike qualified reports and have some influence over auditor appointment, they may try to use auditor switching to avoid receiving qualified reports. Teoh (1992) usefully identifies two ways in which this could occur. First, a manager may actively use the auditor switch decision to avoid receiving a qualified report. If a new auditor is less likely to give a qualified report compared to the incumbent auditor, the manager may choose to switch. Similarly, if a new auditor is more likely to give a qualified report compared to the incumbent, the manager may choose not to switch. Second, if auditors earn client-specific rents, a manager may obtain a more favourable report from an incumbent auditor by threatening to switch to a new auditor. However, post-Enron, HIH and the CLERP Act 2004, the top 300 listed companies are required to have an audit committee, which limits the ability for managers to exercise such influence. Geiger and Raghunandan (2002) find that auditors are more likely to issue an unqualified audit opinion prior to a client filing for bankruptcy in the early years of the auditor-client relationship. Myers et al. (2003) on the other hand find that as auditor tenure increases, auditors place greater constraints on the degree of discretionary and current accruals allowed by management. These results suggest that mandatory audit firm rotation may have adverse effects on audit quality, as audit quality is lower in the earlier years of the auditor-client relationship. A number of other reasons have been proffered as to why clients decide to change auditors. Chow and Rice (1982) find that the incidence of a qualified report was a significant reason for clients to switch auditors. Schwartz and Menon (1985) find that failing clients had a greater propensity to switch auditors, while Williams (1988) argues that financially distressed clients have greater incentives to change auditors than healthy clients in order for managers to portray a good image ofthe company. Hence, there is some evidence that a large proportion of switching clients may be financially distressed. However, a change in auditor is not always initiated by the client, but rather may be initiated by the audit firm. Prior research indicates thataudit firms by virtue of their own internal quality procedures have a tendency to shed risky clients. An audit firm with a risky client may decide to drop the client from its portfolio in order to reduce their engagement risk ( Johnstone and Bedard, 2004). Auditors generally resign from clients with high-financial distress and in receipt of a modified (particularly going-concern) opinion (Krishnan and Krishnan, 1997). Shu (2000) also finds that an auditor resignation is positively related to client legal exposure. The preceding arguments suggest that as a result of risky clients deciding to change auditors, or auditors deciding to resign from risky clients, a large proportion of clients that do switch will be financially unsound. A large body of research underscores the higher levels of audit quality that the top-tier audit firms can provide to their clients. DeAngelo (1981) argues that audit firms with more clients have greater incentives to supply higher quality audits. Teoh and Wong (1993) find that clients of Big N audit firms generally have higher earnings response coefficients to audited earnings announcements, while Francis et al. (1999) find that Big N audit firms were able to reduce the level of DA reported by their clients, indicating a more effective assertion of independence. The prior literature suggests that firms with higher levels of DA are able to manage earnings which lead to lower audit quality. Audit firm rotation and audit quality 423 Some audit firms differentiate themselves from their competitors by specialising in auditing clients in particular industries. Craswell et al. (1995) find that industry-specialists command a fee premium of around 16 per cent over non-industry specialists, indicating that clients are willing to pay more for the services of such an auditor. Schauer (2002) finds that clients of industry specialists had lower bid-ask spreads, signifying lower levels of information asymmetry associated, and Krishnan (2003) observes that clients of industry-specialists reported lower levels of accruals. From the prior research, it appears that audit quality as measured by the propensity to issue a going-concern opinion (GCO) and the level of DA is impacted by a change in auditor. Therefore, we propose the following hypothesis, stated in the null: H0. Audit firm rotation does not affect audit quality. Sample selection and research design Sample selection This study examines auditor switches occurring between 1995 and 2003 for Australian listed entities. It was decided to study the period from 1995, as data were readily available for the year, and follows many of the Big N audit firm mergers. The period 1995-1999 also offers a comparable time period with 2000-2003. The period from 2000 has been marked by a number of considerable changes and events. The Ramsay Report, issued in 2001, highlighted a number of threats to auditor independence, including the provision of non-audit services along with recommendations for audit partner rotation, which is included in CLERP 9. In addition, international high-profile corporate collapses, including Enron, WorldCom, and HIH, brought auditor-client relationships under even greater examination. The initial sample consisted of 772 auditor switches for listed ASX entities between 1995 and 2003. Financial sector firms were excluded due to the inherent differences in their reporting nature. After excluding clients where DA data were not available, those with insufficient data, those reporting in a foreign currency, and for clients where a matched entity could not be found, a total of 205 auditor switches resulted. The total sample was used to measure changes in the level of DA with auditor tenure. Both switching client firm-year observations and non-switching client firm-year observations were included, yielding a total of 1,750 firm-year observations. Each listed entity’s independent auditor was identified from Craswell’s Who Audits Australia database from 1994 to 2003. The age of clients was obtained from the ASX web site and Aspect Huntley’s DatAnalysis. Financial statement balances were also obtained from Aspect Huntley’s DatAnalysis. Takeover announcements were collected from Connect 4, while debt and equity issues data were collected from Thompson’s SDC Platinum New Issues Database. Market capitalisation data were collected from CRIF. Any missing data were hand collected from relevant sources. Variables were winsorised at the fifth and 95th percentiles to remove the effect of significant outliers. Research design Audit quality has been defined in numerous ways, ranging from the relative degree to which the audit conforms to applicable auditing standards (Krishnan and Schauer, 2001; Tie, 1999; McConnell and Banks, 1998; Cook, 1987), the market-assessed probability that the financial statements contain material errors and that the auditor will discover and report them (DeAngelo, 1981), the accuracy of the information MAJ 23,5 424 reported on by auditors (Titman and Trueman, 1986; Beatty, 1989; Krinsky and Rotenberg, 1989), and a measure of the audit’s ability to reduce noise and bias and improve fineness in accounting data (Wallace, 1980). Any metric used to measure audit quality, however, are not perfect. Proxies for audit quality can only be devised in most cases using publicly available information, and not private information known to the auditor. The true audit quality is when the audit does not result in a Type I or II error – a failing company being given an unqualified report or a non-failing company being given a qualified report. In order to test our hypothesis that a change in audit firm has no effect on audit quality, we estimate the following model: AQ ¼ a þ b 1 TENURE þ b 2 FRISK þ b 3 SIZE þ b 4 LEV þ b 5 CLEV þ b 6 RETURN þ b 7 LDISTRESS þ b 8 INVEST þ b 9 FEERATIO þ b 10 SCFO þ b 11 PRIOR þ b 12 BIG_N þ b 13 LEADER þ b 14 INDUSTRY þ 1 ð1Þ where AQ is audit quality, TENURE is the number of continuous years the incumbent auditor has been with the client; FRISK is the client financial risk as measured by the Zmijewski (1984) financial distress score[1]; SIZE is measured as the natural log of total assets, LEV is the ratio of liabilities to assets, CLEV is the percentage change in LEV during the year, RETURN is the percentage change in the book value of net assets over the year, LDISTRESS is a dummy variable indicating if the client was financially distressed[2] in the previous year, INVEST is investment securities measured by current assets less-current debtors and inventory scaled by total assets, FEERATIO is fee dependence as measured by non-audit fees divided by non-audit and audit fees paid to the incumbent auditor, strong cash flows from operations (SCFO) is the net cash flows from operations scaled by lagged total assets, PRIOR is a dummy variable indicating if the client received a going-concern opinion in the prior year, BIG_N is a dummy variable indicating if the firm was audited by a Big N auditor, LEADER is a dummy variable indicating if the audit firm is a leader in the firm’s industry, and INDUSTRY is a dummy variable indicating if a firm is in the mining sector. Two measures of audit quality are employed within this study. First, audit quality is measured as the propensity of the auditor to issue a GCO after controlling for other factors that might affect this decision. A finding that auditors have a lower (higher) propensity to issue going-concern opinions with increased tenure would provide convincing evidence in favour of (in opposition to) mandatory rotation, i.e. if there is lower propensity to issue GCO with increased tenure, then independence becomes impaired. As the dependent variable in this measurement of audit quality is a dichotomous variable, being the propensity to issue a going-concern opinion, a logistic regression is run. Second, the level of DA is used. DA are accruals that do not relate to normal operating activities, and so a higher level of these accruals may indicate that management has been able to exert its power over the auditor by being able to report on terms favourable to management. As this second measurement of audit quality is a continuous variable, an OLS regression is sufficient. To measure DA, a performance-matched modified-Jones (1991) DA model was used. Dechow et al. (1995) find that the modified Jones model had the highest statistical Audit firm rotation and audit quality 425 power in detecting earnings management, while Kothari et al. (2005) suggest matching for performance helps to control for changes in accruals models associated with client performance levels. Performance matched firms are matched by year and industry. DA are estimated by: TACC ¼ a 1 þ a 2 ðDSales 2 DRecÞþ a 3 PPE þ a 4 LTACC þ a 5 Growth þ 1 ð2Þ where TACC is total accruals (operating net profit after tax – cash flows from operations), DSales is the change in sales for the year scaled by lagged total assets, DRec is the change in accounts receivable during the year scaled by lagged total assets, PPE is the gross property, plant and equipment scaled by lagged total assets, Growth is the ratio of next year’s sales to this years, and the residual from the regression, 1,is the measure of DA. The higher the level of the residual indicates a lower level of accrual quality. The model employed in this study is based closely on that used by DeFond et al. (2002) and Carey and Simnett (2006). The Zmijewski (1984) probability of bankruptcy score (FRISK) is included because clients closer to bankruptcy should have a higher chance of receiving a going-concern report. SIZE is included because larger clients will have more assets to sell in the event of financial difficulty, and should be less prone to receiving a going-concern report. LEV and CLEV are employed because higher levels of debt relative to total assets indicate higher risk, and greater changes in leverage may suggest that the client is close to violating a debt covenant. RETURN is included, because clients with higher levels of growth should be less likely to fail. Results Descriptive statistics Descriptive statistics are presented in Table I. Panel A provides the results for the full sample, with Panels B and C providing the results for the switching and non-switching firms, respectively. Means of the variables are consistent with prior research. Of the total sample, 4.06 per cent of firm-year observations result in a GCO being issued, which increases to 5.37 per cent for switching firms (3.88 per cent for non-switching firms). Table II outlines the correlation coefficients between the variables, using both Pearson and Spearman rank correlations. Firms that were financially distressed in the prior year have a high-negative correlation with both RETURN and SCFO. Going-concern opinion Table III presents the results of the logistic regression using the propensity to issue a going-concern audit opinion as a proxy for audit quality. Panel A provides the results for the full sample, with Panels B and C providing the results for the switching and non-switching firms, respectively. Results from Table III indicate that audit-client tenure increases the likelihood of the auditor issuing a going-concern audit opinion. This result is inconsistent with the results of Geiger and Raghunandan (2002) who found no statistically significant relationship, and with those of Choi and Doogar (2005) who found a significantly negative relationship between audit quality and tenure. As expected, FRISK was positively associated with the propensity to issue a going-concern opinion, indicating that firms with higher probabilities of bankruptcy are more likely to receive a going-concern opinion. SIZE was found to have a MAJ 23,5 426 Variable Mean Std Min Quartile1 Median Quartile3 Max Panel A: full-sample descriptive statistics (n ¼ 1,750) GCO 0.0406 0.1974 0.0000 0.0000 0.0000 0.0000 1.0000 DA 2 0.0239 0.1396 2 1.0476 2 0.0758 2 0.0168 0.0342 0.8606 TENURE 7.2954 5.4532 1.0000 3.0000 6.0000 10.0000 32.0000 FRISK 2 2.3819 1.6920 2 8.1190 2 3.3102 2 2.4805 2 1.6405 4.1519 SIZE 17.9659 1.8758 11.4616 16.6620 17.7435 19.1076 24.4907 LEV 5.8128 15.0874 0.0000 0.0086 0.1596 1.9684 63.0075 CLEV 0.3075 0.8741 2 0.6120 2 0.1122 0.0553 0.3602 3.5736 RETURN 0.1170 0.4600 2 0.6797 2 0.0869 0.0559 0.2149 1.5453 LDISTRESS 0.5754 0.4944 0.0000 0.0000 1.0000 1.0000 1.0000 INVEST 0.1389 0.1748 2 0.5415 0.0311 0.0713 0.1740 1.0000 FEERATIO 0.3238 0.2389 0.0000 0.1316 0.3078 0.4902 0.9779 SCFO 0.0376 0.2022 2 0.9795 2 0.0246 0.0647 0.1260 0.6041 PRIOR 0.0063 0.0791 0.0000 0.0000 0.0000 0.0000 1.0000 BIG_N 0.6983 0.4591 0.0000 0.0000 1.0000 1.0000 1.0000 LEADER 0.1977 0.3984 0.0000 0.0000 0.0000 0.0000 1.0000 INDUSTRY 0.5394 0.4986 0.0000 0.0000 1.0000 1.0000 1.0000 Panel B: switching clients descriptive statistics (n ¼ 205) GCO 0.0537 0.2259 0.0000 0.0000 0.0000 0.0000 1.0000 DA 2 0.0168 0.1549 2 0.9269 2 0.0710 2 0.0069 0.0427 0.6390 TENURE 2.1951 3.1593 1.0000 1.0000 1.0000 1.0000 18.0000 FRISK 2 2.2218 1.7884 2 5.4695 2 3.4345 2 2.5547 2 1.4187 4.1262 SIZE 17.6379 1.9665 11.4616 16.3290 17.4886 18.8584 24.4907 LEV 10.2942 19.0199 0.0000 0.0211 0.8149 7.7183 63.0075 CLEV 0.3610 0.9785 2 0.6120 2 0.1527 0.0789 0.4448 3.5736 RETURN 0.1534 0.5569 2 0.6797 2 0.1617 0.0555 0.3164 1.5453 LDISTRESS 0.6439 0.4800 0.0000 0.0000 1.0000 1.0000 1.0000 INVEST 0.1542 0.1871 0.0002 0.0371 0.0848 0.1964 1.0000 FEERATIO 0.2819 0.2548 0.0000 0.0228 0.2365 0.4762 0.9077 SCFO 2 0.0123 0.2277 2 0.9795 2 0.0815 0.0406 0.1154 0.6041 PRIOR 0.0537 0.2259 0.0000 0.0000 0.0000 0.0000 1.0000 (continued) Table I. Sample descriptive statistics Audit firm rotation and audit quality 427 Variable Mean Std Min Quartile1 Median Quartile3 Max BIG_N 0.6195 0.4867 0.0000 0.0000 1.0000 1.0000 1.0000 LEADER 0.1951 0.3973 0.0000 0.0000 0.0000 0.0000 1.0000 INDUSTRY 0.4634 0.4999 0.0000 0.0000 0.0000 1.0000 1.0000 Panel C: matched non-switching clients descriptive statistics (n ¼ 1545) GCO 0.0388 0.1933 0.0000 0.0000 0.0000 0.0000 1.0000 DA 2 0.0249 0.1375 2 1.0476 2 0.0767 2 0.0175 0.0332 0.8606 TENURE 7.9722 5.3343 1.0000 4.0000 7.0000 11.0000 32.0000 FRISK 2 2.4031 1.6783 2 8.1190 2 3.3043 2 2.4742 2 1.6757 4.1519 SIZE 18.0094 1.8598 11.9939 16.7108 17.7731 19.1437 23.5549 LEV 5.2182 14.3888 0.0000 0.0074 0.1427 1.5702 63.0075 CLEV 0.3004 0.8594 2 0.6120 2 0.1088 0.0521 0.3528 3.5736 RETURN 0.1121 0.4455 2 0.6797 2 0.0774 0.0560 0.2087 1.5453 LDISTRESS 0.5663 0.4957 0.0000 0.0000 1.0000 1.0000 1.0000 INVEST 0.1369 0.1731 2 0.5415 0.0309 0.0698 0.1722 0.9721 FEERATIO 0.3294 0.2363 0.0000 0.1440 0.3140 0.4940 0.9779 SCFO 0.0443 0.1977 2 0.9795 2 0.0163 0.0681 0.1274 0.6041 PRIOR 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 BIG_N 0.7087 0.4545 0.0000 0.0000 1.0000 1.0000 1.0000 LEADER 0.1981 0.3987 0.0000 0.0000 0.0000 0.0000 1.0000 INDUSTRY 0.5495 0.4977 0.0000 0.0000 1.0000 1.0000 1.0000 Notes: GCO is a dummy variable indicating if a firm received a going-concern opinion; DA is a measure of the level of discretionary accruals; TENURE is the number of continuous years the incumbent auditor has been with the client; FRISK is the client financial risk as measured by the Zmijewski (1984) financial distress score; SIZE is measured as the natural log of total assets; LEV is the ratio of liabilities to assets; CLEV is the percentage change in LEV during the year; RETURN is the percentage change in the book value of net assets over the year; LDISTRESS is a dummy variable indicating if the client was financially distressed in the previous year; INVEST is investment securities measured by current assets less-current debtors and inventory scaled by total assets; FEERATIO is fee dependence as measured by non-audit fees divided by non-audit and audit fees paid to the incumbent auditor; SCFO is the net cash flows from operations scaled by lagged total assets; PRIOR is a dummy variable indicating if the client received a going-concern opinion in the prior year; BIG_N is a dummy variable indicating if the firm was audited by a Big N auditor; LEADER is a dummy variable indicating if the audit firm is a leader in the firm’s industry; and INDUSTRY is a dummy variable for firms in the mining sector Table I. MAJ 23,5 428 GCO DA Tenure SIZE FRISK LEV CLEV RETURN LDISTRESS INVEST FEERATIO SCFO PRIOR GCO 0.0537 (0.0245) 2 0.0156 (0.5147) 2 0.2043 (, 0.0001) 0.2327 (, 0.0001) 0.1130 (, 0.0001) 0.0320 (0.1806) 2 0.1016 (, 0.0001) 0.1298 (, 0.0001) 0.0062 (0.7947) 2 0.0485 (0.0426) 2 0.1984 (, 0.0001) 0.0911 (0.0001) DA 0.0627 (0.0087) 2 0.0068 (0.7763) 0.0365 (0.1267) 0.0227 (0.3435) 2 0.0154 (0.5193) 0.0576 (0.0160) 2 0.0105 (0.6612) 0.0553 (0.0207) 2 0.1240 (, 0.0001) 0.0303 (0.2052) 2 0.5203 (, 0.0001) 0.0501 (0.0360) TENURE 2 0.0121 (0.6145) 2 0.0194 (0.4180) 0.2193 (, 0.0001) 2 0.0247 (0.3026) 2 0.1415 (, 0.0001) 2 0.0751 (0.0017) 2 0.0167 (0.4839) 2 0.0869 (0.0003) 2 0.0962 (, 0.0001) 0.0405 (0.0905) 0.0998 (, 0.0001) 2 0.0880 (0.0002) SIZE 2 0.2112 (, 0.0001) 0.0201 (0.4015) 0.1976 (, 0.0001) 0.0022 (0.9260) 2 0.3326 (, 0.0001) 2 0.0713 (0.0028) 0.0933 (, 0.0001) 2 0.2714 (, 0.0001) 2 0.3188 (, 0.0001) 0.2694 (, 0.0001) 0.3476 (, 0.0001) 2 0.0507 (0.0338) FRISK 0.1552 (, 0.0001) 0.0369 (0.1229) 0.0232 (0.3323) 0.1146 (, 0.0001) 0.1094 (, 0.0001) 0.0295 (0.2172) 2 0.3190 (, 0.0001) 0.1584 (, 0.0001) 2 0.1993 (, 0.0001) 2 0.0283 (0.2360) 2 0.1827 (, 0.0001) 0.0808 (0.0007) LEV 0.1157 (, 0.0001) 2 0.0005 (0.9822) 2 0.1671 (, 0.0001) 2 0.4679 (, 0.0001) 0.0184 (0.4415) 0.0028 (0.9085) 2 0.0694 (0.0037) 0.0409 (0.0874) 0.1075 (, 0.0001) 2 0.0977 (, 0.0001) 2 0.1722 (, 0.0001) 0.0310 (0.1950) CLEV 2 0.0124 (0.6028) 0.0331 (0.1665) 2 0.0949 (, 0.0001) 0.0357 (0.1349) 0.0987 (, 0.0001) 2 0.0225 (0.3467) 0.2598 (, 0.0001) 0.1015 (, 0.0001) 0.0417 (0.0814) 0.0162 (0.4996) 2 0.1065 (, 0.0001) 0.0177 (0.4583) RETURN 2 0.1151 (, 0.0001) 0.0366 (0.1255) 0.0071 (0.7652) 0.1639 (, 0.0001) 2 0.2973 (, 0.0001) 2 0.0950 (, 0.0001) 0.1467 (, 0.0001) 2 0.1847 (, 0.0001) 0.0595 (0.0127) 0.0805 (0.0007) 0.0920 (0.0001) 0.0474 (0.0475) LDISTRESS 0.1298 (, 0.0001) 0.0342 (0.1529) 2 0.0801 (0.0008) 2 0.2768 (, 0.0001) 0.1173 (, 0.0001) 2 0.0146 (0.5410) 0.0040 (0.8665) 2 0.2910 (, 0.0001) 0.1426 (, 0.0001) 2 0.0974 (, 0.0001) 2 0.3505 (, 0.0001) 0.0248 (0.2991) INVEST 2 0.0134 (0.5762) 2 0.1622 (, 0.0001) 2 0.0778 (0.0011) 2 0.2634 (, 0.0001) 2 0.1938 (, 0.0001) 0.1393 (, 0.0001) 2 0.0310 (0.1949) 0.0219 (0.3608) 0.1109 (, 0.0001) 0.0307 (0.1992) 2 0.1734 (, 0.0001) 2 0.0149 (0.5322) FEERATIO 2 0.0522 (0.0291) 0.0191 (0.4251) 0.0506 (0.0344) 0.2686 (, 0.0001) 0.0020 (0.9329) 2 0.0924 (0.0001) 0.0597 (0.0125) 0.0655 (0.0061) 2 0.0979 (, 0.0001) 0.0299 (0.2112) 0.0496 (0.0381) 2 0.0328 (0.1707) SCFO 2 0.2252 (, 0.0001) 2 0.5004 (, 0.0001) 0.1082 (, 0.0001) 0.3684 (, 0.0001) 2 0.1216 (, 0.0001) 2 0.1744 (, 0.0001) 0.0329 (0.1689) 0.2997 (, 0.0001) 2 0.3901 (, 0.0001) 2 0.0473 (0.0479) 0.0861 (0.0003) 2 0.0558 (0.0195) PRIOR 0.0911 (0.0001) 0.0513 (0.0320) 2 0.1159 (, 0.0001) 2 0.0511 (0.0325) 0.0528 (0.0270) 0.0187 (0.4339) 2 0.0238 (0.3191) 0.0238 (0.3189) 0.0248 (0.2991) 2 0.0013 (0.9557) 2 0.0362 (0.1301) 2 0.0601 (0.0120) Notes: Pearson (Spearman rank) correlation above (below) the diagonal; the two-tailed p-value is provided in parentheses with the correlation. GCO is a dummy variable indicating if a firm received a going-concern opinion; DA is a measure of the level of discretionary accruals; TENURE is the number of continuous years the incumbent auditor has been with the client; FRISK is the client financial risk as measured by the Zmijewski (1984) financial distress score; SIZE is measured as the natural log of total assets; LEV is the ratio of liabilities to assets; CLEV is the percentage change in LEV during the year; RETURN is the percentage change in the book value of net assets over the year; LDISTRESS is a dummy variable indicating if the client was financially distressed in the previous year; INVEST is investment securities measured by current assets less-current debtors and inventory scaled by total assets; FEERATIO is fee dependence as measured by non-audit fees divided by non-audit and audit fees paid to the incumbent auditor; SCFO is the net cash flows from operations scaled by lagged total assets; and PRIOR is a dummy variable indicating if the client received a going-concern opinion in the prior year Table II. Pearson and Spearman correlations Audit firm rotation and audit quality 429 [...]... only examines levels of actual audit quality While we conclude that actual audit quality does not improve for firms that rotate auditor, the perception of audit quality may indeed have increased Further research is required to investigate the perception of audit quality on mandatory audit firm rotation, as well as total audit quality combining both actual and perceived quality The proxies used in this... are minimal, if any, benefits of imposing mandatory audit firm rotation onto Audit firm rotation and audit quality 433 Table IV MAJ 23,5 434 Australian firms Further, given the costs involved in switching auditor, it does not appear that mandatory audit firm rotation would be beneficial to the market In order to address the concerns that have arisen recently around auditor independence and audit quality, ... (1995), “Temporal changes in bankruptcy-related reporting”, Auditing: A Journal of Practice & Theory, Vol 14 No 2, pp 13 3-4 3 Carey, P and Simnett, R (2006), Audit partner tenure and audit quality , The Accounting Review, Vol 81 No 3, pp 65 3-7 6 Carson, E., Ferguson, A and Simnett, R (2006), “Australian audit reports: 199 6-2 003”, Australian Accounting Review, Vol 16 No 3, pp 8 9-9 6 Chen, K and Church, B... (1996), “Going concern opinions and the market’s reaction to bankruptcy filings”, The Accounting Review, Vol 71 No 1, pp 11 7-2 8 Choi, J-H and Doogar, R (2005), “Auditor tenure and audit quality: evidence from going-concern qualifications issued during 199 6-2 001”, working paper, Hong Kong University of Science and Technology, Kowloon Chow, C and Rice, S (1982), “Qualified audit opinions and auditor switching”,... audit quality, other initiatives are more likely to have a greater impact than imposing mandatory audit firm rotation However, there are other potential benefits of mandatory audit firm rotation that we do not consider in this context which may detract from the generalisation of our results As indicated prior, audit quality can be divided into perceived audit quality and actual audit quality (Taylor, 2005)... variable indicating if the client received a going-concern opinion in the prior year; BIG_N is a dummy variable indicating if the firm was audited by a Big N auditor; LEADER is a dummy variable indicating if the audit firm is a leader in the firm’s industry; and INDUSTRY is a dummy variable for firms in the mining sector Myers et al (2003) and Blouin et al (2005) did not find any significant relationship between... going-concern audit opinion and the level of DA, we find that audit quality is not negatively affected by audit firm tenure Using the propensity to issue a going-concern opinion, the length of audit tenure actually increases audit quality However, when using the level of DA to measure audit quality there is neither an increase nor a decrease in audit quality conditional on the length of auditor tenure Given... variable indicating if the client was financially distressed in the previous year; INVEST is investment securities measured by current assets less-current debtors and inventory scaled by total assets; FEERATIO is fee dependence as measured by non -audit fees divided by non -audit and audit fees paid to the incumbent auditor; SCFO is the net cash flows from operations scaled by lagged total assets; PRIOR... Journal, January, pp 3 6-9 ˜ ada, B and Paz-Ares, C (1997), Mandatory rotation of company auditors: a critical Arrun examination”, International Review of Law and Economics, Vol 17 No 1, pp 3 1-6 1 Banks, D and Kinney, W (1982), “Loss contingency reports and stock prices: an empirical study”, Journal of Accounting Research, Vol 20 No 1, pp 24 0-5 4 Beatty, R.P (1989), “Auditor reputation and the pricing... of Accounting, Auditing and Finance, Vol 9 No 1, pp 14 9-6 6 Francis, J., Maydew, E and Sparks, H (1999), “The role of big-six auditors in the credible reporting of accruals”, Auditing: A Journal of Practice & Theory, Vol 18 No 2, pp 1 7-3 4 GAO (2003), “Required study on the potential effects of mandatory audit firm rotation , Report to the Senate Committee on Banking, Housing, and Urban Affairs and the . firm rotation on audit quality, rotation may nevertheless be effective in increasing perceived audit quality. Audit quality comprises actual and perceived quality (Taylor, 2005). Actual quality. perception of audit quality on mandatory audit firm rotation, as well as total audit quality combining both actual and perceived quality. The proxies used in this study to measure audit quality, however,. manage earnings which lead to lower audit quality. Audit firm rotation and audit quality 423 Some audit firms differentiate themselves from their competitors by specialising in auditing clients in particular