Auditing: A Journal of Practice & Theory Vol 29, No November 2010 pp 83–114 American Accounting Association DOI: 10.2308/aud.2010.29.2.83 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms Hsihui Chang, C S Agnes Cheng, and Kenneth J Reichelt SUMMARY: After the demise of Arthur Andersen, the public accounting industry has witnessed a significant migration of public clients to second-tier ͑Grant Thornton and BDO Seidman͒ and smaller third-tier accounting firms While prior literature documents that smaller auditors are perceived by the stock market as an inferior substitute for a Big auditor, this perception appears to have changed in recent years In this paper, we analyze market responses to auditor switching from Big to smaller accounting firms during 2002 to 2006 We break our sample period into two separate periods ͑Periods and 2͒ based on when regulatory changes occurred These changes included Sarbanes-Oxley ͑SOX͒ 404 implementation, Public Company Accounting Oversight Board ͑PCAOB͒ inspections, and a tightened Form 8-K filing deadline We find a relatively more positive stock market reaction to clients switching from a Big to a smaller third-tier auditor in Period This relatively more positive reaction in Period reflects companies seeking better services rather than a lower audit fee, when an audit quality drop is less likely Overall, our results suggest that companies and investors have become more receptive to smaller accounting firms Keywords: market reaction; auditor switching; Big 4; small accounting firms; audit quality Data Availability: Data are publicly available from the sources identified in the paper INTRODUCTION fter the failure of Arthur Andersen, regulators around the world were concerned about the degree of concentration in the audit profession by the Big In a speech at the American Institute of Certified Public Accountants ͑AICPA͒ annual national conference on December 11, 2006, Mark Olson, Chairman of the Public Company Accounting Oversight Board, ex- A Hsihui Chang is a Professor at Drexel University, and C S Agnes Cheng is a Professor and Kenneth J Reichelt is an Assistant Professor, both at Louisiana State University We gratefully acknowledge the comments and suggestions of Dan Simunic ͑the editor͒, two anonymous reviewers, Steven Lin, Kannan Raghunandan, Gordon Richardson, Sam Tiras, Angela Woodland, and workshop participants at Florida International University, Louisiana State University, National Cheng Kung University, the 2007 International Research Conference for Accounting Educators in Mexico City, and the 2008 Joint Journal of Contemporary Accounting and Economics and Auditing: A Journal of Practice and Theory Symposium, and in particular the discussant at that Symposium, Clive Lennox We thank Menghistu Sallehu for his excellent research assistance, and directEDGAR for the use of their data and software Editor’s note: Accepted by Dan Simunic Submitted: September 2007 Accepted: December 2009 Published Online: October 2010 83 84 Chang, Cheng, and Reichelt pressed his concerns of audit firm concentration, as well as his hope for improvement from the growth in the size and skill of smaller accounting firms ͑PCAOB 2006͒ Similar confidence had also been expressed by Christopher Cox, Chairman of the U.S Securities and Exchange Commission, on December 5, 2005 ͑SEC 2005͒, and by PCAOB Chairman William McDonough on October 17, 2005 ͑Civils 2005͒ Both officials encouraged smaller public companies to consider hiring smaller accounting firms Despite the regulators’ encouragement, and their belief that many smaller accounting firms have improved their competence, the audit market continues to be dominated by the Big auditors This is partly because investors have perceived that brand name auditors, i.e., the Big N ͑Big 8/6/5/4͒, provide higher quality audits than smaller accounting firms, as suggested by prior literature ͑DeAngelo 1981; Dopuch and Simunic 1982; Nichols and Smith 1983; Teoh and Wong 1993͒ Consequently, the stock market has perceived switches from a Big N auditor to a non-Big N as a “red flag” ͑Eichenseher et al 1989; Dunn et al 1999; Knechel et al 2007͒ Prior to 2002, some auditor switches, regardless of auditor type, involved companies that were experiencing going-concern and/or auditor disagreements These companies were considered riskier, evident from poorer economic performance ͑Dhaliwal et al 1993͒, higher auditor litigation risk ͑Krishnan and Krishnan 1997; Shu 2000͒, greater likelihood of violating debt-covenants ͑DeFond and Jiambalvo 1993͒, and greater likelihood of a going-concern audit opinion ͑Krishnan and Krishnan 1997; Geiger et al 1998͒ From a risk perspective, some of these studies suggest and show that the stock market responded negatively to the announcement of an auditor switch ͑e.g., Dhaliwal et al 1993; Shu 2000͒ From a beneficial reason perspective, recent studies ͑e.g., Ettredge et al 2007; Sankaraguruswamy and Whisenant 2004͒ document that auditor switches are undertaken for seeking audit fee savings and/or better services Under such circumstances, a nonnegative or even a positive market reaction could be expected for a switch from a Big to a non-Big auditor Specifically, if ͑1͒ investors can justify a net economic benefit from a tradeoff between a perceived downgrade in audit quality and a combined lower audit fee and better personalized services, or ͑2͒ the market has changed its perception about the lower audit quality of non-Big auditors If the first case is true, the market reaction will: ͑1͒ neither be negative nor positive when the market perceives an equivalent trade-off between higher audit quality and a combined lower audit fee and improved personalized services, and ͑2͒ be positive when the net economic benefit is significantly positive If the second case is true, however, it is likely that we will observe a positive market reaction due to a perceived positive net economic benefit arising from a combined lower audit fee and better services, without a compromise in audit quality We believe the market’s perception of switching from a Big to a Small auditor has changed in recent years ͑2004–2006͒ for the following three main reasons Increase in Seeking Better Services and a Lower Audit Fee from Smaller Auditors After the demise of Andersen and the enactment of the Sarbanes-Oxley Act ͑SOX͒, a temporary capacity constraint resulted This exogenous shock provided an opportunity for Big auditors to rebalance their client portfolios toward better-aligned former Andersen clients, evident from increased sensitivity to client mismatch ͑Landsman et al 2009͒ Consequently, for smaller clients Big audit services may have deteriorated and audit fees may have increased so much that smaller accounting firms appeared more attractive for better services and lower audit fees Consistent with this notion is a Wall Street Journal article that reports that after SOX, more IPOs are relying on Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 85 smaller accounting firms and investors are more receptive to smaller accounting firms ͑Reilly 2006͒.1 Decline in Perceived Audit Quality Differences between Big N and Non-Big N Auditors After the Big N’s involvement in a series of accounting scandals in the early 2000s, investors viewed a smaller difference in audit quality between Big N and non-Big N auditors This statement is consistent with the analysis by Choi et al ͑2008͒ that the audit quality of the Big N and non-Big N is expected to converge as the legal and regulatory regime becomes more onerous During 2004, more onerous legal and regulatory changes were introduced, including SOX 404 audit requirements, PCAOB inspections of auditors, and a tighter 8-K filing deadline Evidently, the initial PCAOB inspections of the Big reported disappointing news of the Big audit quality, since 21 of 64 clients examined eventually restated their financial statements.2 Thus, a non-Big auditor should be an optimal choice in order to avoid paying a brand-name audit fee premium, especially if the brand-name auditor does not provide higher audit quality Lack of Evidence of Opinion Shopping by Switching to a Small Auditor Prior studies indicate that opinion shopping is generally unsuccessful ͑e.g., Chow and Rice 1982; Krishnan 1994; Krishnan and Stephens 1995; Geiger et al 1998͒; nonetheless, companies are likely to switch to a non-Big auditor if they believe it will be successful Since PCAOB inspections create quality pressures for non-Big auditors, Small auditors are especially cautious to not provide a low-quality audit As a result, in recent years it is less likely that opinion shopping is the motivation for a switch from a Big to a Small auditor While these three reasons are intuitively appealing, whether investors have actually changed their perception remains an empirical issue If switching from a Big to a Small auditor is indeed for beneficial reasons and the stock market does not perceive a significant drop in audit quality, we should not see a negative market response Furthermore, assuming public companies can find a competent Small audit firm, and the company’s management believes that the market will not react negatively, we should see an increasing trend of switching from Big to Small audit firms In a recent report, Grant Thornton provides empirical evidence that the market does not respond negatively to auditor switches from the Big to Grant Thornton ͑Whisenant 2006͒ However, the Grant Thornton report does not examine Small audit firms, which are different from the Big and Medium in many respects; namely, Small audit firms are better adapted to local markets, are traditionally viewed as inferior, and are substantially smaller.3 Thus, the report’s findings may not be applicable to switches from the Big to Small audit firms Therefore, our study focuses on auditor switches from Big to Small audit firms We seek to empirically document the market response to these auditor switches and assess whether the evidence supports the regulators’ belief in the competence of Small audit firms Analyzing data on auditor changes for the period 2002–2006, we find that the ratio of switches to Small audit firms out of all the switches from the Big has been increasing More importantly, the market response to clients switching from a Big to a Small audit firm ͑BtS͒ is nonnegative and is relatively more positive for the period after August 23, 2004 This relatively On average, we believe Big auditors should provide better audit quality than smaller auditors However, if a Big auditor does not warrant higher audit quality ͑e.g., nonexpertise͒, then a switch to a smaller auditor may not be perceived by the market as a bad move Most of these restatements arose from the balance sheet classification of borrowings from revolving credit agreements ͑PCAOB 2004a, 2004b, 2004c, 2004d͒ Based on audit fees filed in 2006, the Big occupy about 92.6 percent of the total market share, followed by BDO Seidman ͑1.7 percent͒ and Grant Thornton ͑1.6 percent͒ The rest ͑about 643 firms reported in the audit fee data set from Audit Analytics͒ are Small audit firms, the highest occupying only 0.2 percent Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 86 Chang, Cheng, and Reichelt more positive market response occurs when the predecessor auditor’s quality is lower ͑the predecessor is a nonspecialist and accruals quality is more inferior͒, suggesting that there is less likelihood for audit quality to drop from switching to a Small auditor We find the relatively more positive response to a BtS switch is driven by better services,4 not by a lower audit fee, when there is less likelihood for audit quality to drop Our study extends the literature in several ways We find a relatively more positive market response to clients switching from a low-quality Big auditor to a Small auditor, particularly when the Small auditor provides better services, thus extending Sankaraguruswamy and Whisenant ͑2004͒, who find a relatively more positive response to service and fee reasons without examining the quality of the auditor switch We document a nonnegative market reaction to switches from a Big auditor to a Small auditor, as well as with switches from a Big to a Medium and to another Big in the post-SOX 404/PCAOB inspection era, thus extending Knechel et al ͑2007͒, who find a negative response to switches from a Big to a non-Big in the period 2000 to 2003 In addition, after intended improvements in financial reporting quality and audit quality ͑e.g., SOX 404 and PCAOB inspections͒ in recent years, we find that the market does not perceive an audit quality drop when companies switched from a “low-quality” Big auditor to a Small auditor Specifically, we find that the market responded relatively more positive ͑i.e., less negatively͒ to switches from a Big to a Small auditor, especially when the Small auditor is considered a specialist and when the client experienced low audit quality from the Big auditor This finding is consistent with our conjecture that the market is starting to perceive that Small auditors not necessarily deliver inferior audit quality Small auditors may even be able to improve audit quality ͑possibly as a specialist providing more personal attention͒ when the Big predecessor did not provide high audit quality The remainder of our paper is structured as follows The next section reviews prior literature of the market reaction to auditor switches and articulates our prediction of the market response to Big to Small auditor switches The third section presents and discusses our empirical results and the fourth section concludes the paper PRIOR LITERATURE In order to gain perspective as to the overall changes in investor attitudes regarding auditor switches, we must examine the results from both before and after the SOX/Andersen period Early studies of stock market reactions to auditor switches provide mixed results Fried and Schiff ͑1981͒ find a negative market reaction to auditor switches between 1972 and 1975 for companies that switched, based on a 21-week window However, Nichols and Smith ͑1983͒ find when using a shorter eight-week window, that there was no significant reaction to auditor switches between 1973 and 1979 Similarly, Johnson and Lys ͑1990͒ fail to find a significant stock price reaction for auditor switches from 1973 to 1982 using a three-day window around the time of the auditor change announcement In contrast, later studies tend to document a negative market reaction to auditor switches Smith ͑1988͒ examines auditor switches between 1975 and 1982, using a one-week event window, and finds a negative and significant reaction when a new auditor has not yet been appointed Eichenseher et al ͑1989͒ find a significant negative market reaction to auditor switches from Big to non-Big firms by OTC companies between 1980 to 1982, using a five-week event window DeFond et al ͑1997͒ find a significant negative market reaction to auditor resignations between 1982 and 1987, using three event windows: from the auditor resignation date to the 8-K filing receipt date, from the receipt of the 8-K filing through the following four business days, and the We use a relative measure of Small auditors’ expertise to reflect better services Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 87 sum of these two periods Wells and Loudder ͑1997͒ find a significant negative market reaction to auditor resignations between 1988 and 1991, using a two-day window Similarly, Dunn et al ͑1999͒ find a negative market reaction to auditor resignations between 1988 and 1993, on the date of the resignation letter, and the reaction is more negative from the loss of a Big auditor In addition, Shu ͑2000͒ finds a significant negative market reaction to auditor resignations between 1985 and 1996, using a three-day window Whisenant et al ͑2003͒ find a significant negative market response to auditor switches arising from weaknesses in internal controls and problems related to the reliability of management representations and/or financial statement reliability between 1993 and 1996, and their results are robust using a three-day window and a seven-day window Beneish et al ͑2005͒ extend Whisenant et al ͑2003͒ by controlling for confounding events around the time of the auditor change announcement ͑e.g., earnings and management changes͒ and by limiting the analysis to resignations Beneish et al.’s ͑2005͒ study uses a three-day window from 1994 to 1998 and only finds a negative market response to resignation announcements where a reason was provided for the change ͑disagreements over accounting treatment or over the adequacy of internal controls͒ Resignation announcements without a reason have an insignificant market response Recently, Knechel et al ͑2007͒ report that Big clients who switched to a non-Big auditor during the period 2000 to 2003 experienced a negative abnormal return While prior market studies have generally found a negative response to auditor change announcements, we have seen no studies that document a positive market reaction to the recent migration of clients from Big to smaller third-tier auditors Although Sullivan ͑2006͒ examines the trends and determinants of auditor switching behavior to explain that the migration arises from higher costs from the SOX Section 404 requirements, the analysis does not include an event study Louis ͑2005͒ provides indirect evidence from market reactions to merger announcements, finding that acquiring companies audited by non-Big firms outperform the market reaction to those audited by Big firms Louis ͑2005͒ suggests that non-Big audit firms have superior knowledge of local markets and they have a better relation with smaller clients However, since the time period studied ͑1980–2002͒ predates the SOX/Andersen era and the study does not examine auditor change announcements, the findings are less relevant to the more recent potential changes in market attitudes Sankaraguruswamy and Whisenant ͑2004͒ provide some evidence that the market response is relatively more positive for service and fee reasons, using a seven-day window, albeit the time period examined, 1993 to 1996, predates the SOX/Andersen era Whisenant ͑2006͒ examines whether the market responds negatively to auditor switches from a Big or Arthur Andersen to Grant Thornton, during the period 2002 to 2006 The author finds a significant positive market response ͑p ϭ 0.08͒, with an 11-day window, for auditor switches from a Big ͑excluding Arthur Andersen͒ to Grant Thornton However, the study is restricted to switches to Grant Thornton clients, so it does not include switches to Small ͑third-tier͒ firms, and it uses raw returns without controlling for the market movement and risk Recent literature suggests a nonnegative or even a positive market response to a switch from a Big to a Small auditor may be imminent when the Big predecessor does not provide high audit quality In recent years, anecdotal evidence in the financial press ͑e.g., Reilly 2006͒ suggests that investors are more receptive to companies using smaller auditors Evidence of a higher audit fee demanded by Big over Small auditors ͑Ho and Wang 2007͒ and service-related reasons ͑Louis 2005͒ suggest that Small accounting firms may be an attractive audit alternative When the switch is not likely to reduce audit quality, the market response should be nonnegative Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 88 Chang, Cheng, and Reichelt EMPIRICAL RESULTS Frequency and Trend of Switching from Big to Small Accounting Firms Based on 8-K filings compiled by Audit Analytics, we first analyze the frequency and trend of auditor switching for the years 2000 through 2006 Since this study focuses on switches from a Big to a Small accounting firm, we consider only clients that already have an auditor before the change and exclude initial public offerings Table summarizes the auditor switching frequency and trend.5 Panel A presents the number of switches between size categories of accounting firms Panel B reports the number of switches by year, across 2000 to 2006, and the number of switches from Big N to Small auditors Similar to Panel B, Panel C reports for publicly traded companies that have filed an auditor change Table 1, Panel A, reports that more auditor switches are from Small auditors ͑48 percent͒ than from Big auditors ͑33 percent͒, and more switches are to Small auditors ͑62 percent͒ than to Big auditors ͑30 percent͒ Panels B and C indicate that the total number of auditor switches was highest in 2002, when Arthur Andersen failed However, the number increased from 2003 to 2004, when the SOX Section 404 requirements became effective, and it further increased from 2004 to 2005 for publicly traded companies Panel C also reports that in 2006 most Big departures are to a Small auditor ͑52 percent͒, and the percentage has been increasing since 2002 Final Sample with Return Data To evaluate the market reaction to auditor switches, we collect daily returns from the Center for Research in Security Prices ͑CRSP͒ for each case of an auditor change filed after the demise of Arthur Andersen ͑January 2002͒.6 Our sample period contains two separate periods: Period is prior to August 23, 2004, and Period is post-August 23, 2004 Our choice of these two periods is motivated by three regulatory events: the implementation of the SOX Section 404 requirements on auditing of internal controls over financial reporting ͑ICOFR͒, the first PCAOB inspection reports, and the change in the Form 8-K filing deadline Auditing Standard No ͑for SOX 404 audits͒ was issued by the PCAOB and approved by the SEC on June 17, 2004 Accelerated filers ͑those in excess of $75M market capitalization͒ are required to engage an auditor to audit their ICOFR, beginning with fiscal years ending November 15, 2004 Since auditing of ICOFR is very costly, clients may switch auditors Hence, the reason for switching may differ when firms consider the Section 404 requirements The first PCAOB inspection reports were announced August 26, 2004 These inspections are required by Section 101 of the SOX to ensure a minimum ͑and a likely higher͒ level of audit quality The PCAOB is required to conduct inspections of firms with over 100 clients every year and inspections of firms with 100 or fewer clients every three years Hence, the market perception of audit quality of Small auditors may have changed due to the awareness that Small auditors are subject to the PCAOB’s tight inspections.7 Effective August 23, 2004, the SEC tightened its 8-K filing deadline from five to four business days for notifying an auditor change and several other events Studies have shown that the compliance rate was low under the five-day deadline requirement ͑Schwartz and Soo 1996; Carter and Soo 1999͒ After the SOX Section 404 requirements took effect, we suspect that the compliance rate improved, since auditors may consider compliance with filing deadlines part of ICOFR, and Data are from Audit Analytics as of January 2007 Grant Thornton’s study by Whisenant ͑2006͒ uses observations from January 1, 2002, to May 23, 2006 Our sample period is similar except we exclude January filings since they include switches to Arthur Andersen, and we extend our period to December 31, 2006 We not claim that the PCAOB has improved the audit quality of Small auditors We simply suggest that there may be a potential change in the market perception Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 89 TABLE Analysis of Auditor Switches Panel A: Number of Auditor Switches between Size Categories of Accounting Firms Years 2000–2006 Engaged Departed AA Small Medium Big Total AA Small Medium Big Total — 32 10 105 147 184 5,720 534 1,651 8,089 108 171 26 635 940 1,544 342 98 1,887 3,871 1,836 6,265 668 4,278 13,047 1% 62% 7% 30% % Engaged % Departed 14% 48% 5% 33% 100% Panel B: Companies Filing an Auditor Change Switches from Big to Small Year Total Changes Departed Engaged Ratio 2000 2001 2002 2003 2004 2005 2006 Total 961 1,553 2,947 1,615 2,070 2,033 1,868 13,047 460 573 456 599 790 775 625 4,278 83 171 175 244 338 348 292 1,651 18.0% 29.8% 38.4% 40.7% 42.8% 44.9% 46.7% 38.6% Panel C: Publicly Traded Companies Filing an Auditor Change Switches from Big to Small Total Year Changes Departed Engaged Ratio 2000 2001 2002 2003 2004 2005 2006 Total 9.4% 12.5% 0.0% 37.5% 43.1% 48.7% 52.4% 36.3% 343 632 1,495 914 1,274 1,356 1,290 7,304 139 256 186 349 480 505 418 2,333 13 32 — 131 207 246 219 848 Panel A reports the number of auditor switches between size categories of accounting firms for companies filing an auditor change Panels B and C report the trend of all auditor switches ͑Total Changes͒ to those departing from a Big accounting firm ͑Departed͒, and those departing from a Big and engaging a Small accounting firm ͑Engaged͒ Big accounting firms are Deloitte, Ernst & Young, KPMG, and PricewaterhouseCoopers Small accounting firms exclude Big 4, Medium ͑BDO Seidman and Grant Thornton͒, and Arthur Andersen ͑AA͒ penalties for noncompliance have increased Using August 23, 2004, as the cut-off date to separate our sample into two periods roughly coincides with the legislative events discussed in this and the two previous paragraphs To keep our observations homogenous, we use August 23, 2004, as our cut-off date Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 90 Chang, Cheng, and Reichelt Our final sample requires observations to have both departed and engaged auditors, a filing date, a return, and market value data.8 This limitation generates a total of 1,824 observations for our final sample This sample is used for our multiple regression analyses and is not limited to switches from a Big accounting firm, but includes all other categories of audit switches Table reports the number of switches by period, industry, and auditor switching category For Period 1, there are 1,121 switches; ignoring 666 mandatory switches from Arthur Andersen, there are only 455 switches For Period 2, there are 703 switches.9 From Table 2, Panel A, we observe that durable manufacturers, financial, and computerrelated firms account for approximately 50 percent of the final sample in both periods Panel B indicates that switches from the Big constitute the largest number of switches: 378 out of 455 non-Arthur Andersen switches in Period 1, and 571 out of 703 switches in Period Among the switches from Big auditors, the majority of the switches are from a Big to another Big auditor in Period However, in Period 2, switches to a Small auditor outnumber switches to a Medium and a Big auditor Univariate Analysis of Market Return during the Event Window To measure whether a company’s stock market return resulted from a triggering event and not from a change in the aggregate stock market level, we use the market-adjusted return10 for our univariate analysis Market-adjusted return is defined as the buy and hold daily return less the value-weighted market daily return, accumulated over the event window We focus our analyses of market responses using a five-day event window ͑Ϫ4,0͒, where day is the filing date Ideally, we should identify the first day that the market is aware of the auditor change ͑e.g., news announcement͒ and then design an event window surrounding the news announcement date ͑e.g., Ϫ1 to ϩ1 day͒ We searched the Form 8-K auditor change filings and find that a small number ͑n ϭ 152, or percent͒ had filed a press release We find that the mean filing date is 1.47 days after the news announcement date ͑standard deviation ϭ 2.48͒ Our event window ͑4,0͒ is based on the fact that four days after the news announcement falls within one standard deviation, and that the SEC requires that the 8-K should be filed within four business days of the auditor change.11,12 Table reports market responses to auditor switches from Big to Small auditors ͑BtS͒, Big to Medium ͑BtM͒, and Big to Big ͑BtB͒ for the two periods For each switch group, Table provides the number of observations, the mean daily return, the mean market-adjusted return, and their respective p-values Panel A indicates that in Period the market responded nonnegatively to switches from BtS, BtM, and BtB The mean daily return and the mean market-adjusted return are not significant at conventional levels, except for the BtB mean daily return ͑significant at 10 percent, one-tailed͒ Panel B indicates a nonnegative market response in Period BtS auditor switches earn a 0.8 percent mean daily return ͑significant at a 10 percent level, one-tailed͒, BtM earn 0.7 percent ͑not significant͒, and BtB earn 0.5 percent ͑significant at a 10 percent level, one-tailed͒; however, the mean market-adjusted return is not significant at conventional levels for all three groups As well, the BtS switch group reports a higher mean daily return and a higher mean market-adjusted return 10 11 12 We deleted one observation with the most extreme positive return When we drop switches from Arthur Andersen, our main conclusions not change We also use size-adjusted and market model-adjusted abnormal returns; our conclusions are not altered For robustness purposes, we use a longer event window ͑Ϫ11,0͒, and we find our results are stronger for Period but weaker for Period These findings are consistent with our conjecture that there is improved compliance in Period 2, which deserves further investigation When the news announcement date is substituted for the filing date of a smaller sample of Big to Small auditor switches ͑n ϭ 23͒, daily returns and market-adjusted returns are virtually unchanged Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 91 TABLE Analysis of Final Sample Panel A: Number of Observations by Industry and Period Period % Industry Group Descriptiona Agriculture Mining and Construction Food Textiles and Printing Chemicals Pharmaceuticals Extractive Durable Manufacturers Transportation 10 Utilities 11 Retail 12 Financial 13 Services 14 Computers 15 Other Total Number of Observations 23 49 18 55 70 209 75 56 97 202 107 141 1,121 0.4% 2.1% 0.8% 4.4% 1.6% 4.9% 6.2% 18.6% 6.7% 5.0% 8.7% 18.0% 9.5% 12.6% 0.5% 100.0% Panel B: Number of Observations by Switching Category and Period Switching Category Period % Big to Small Big to Medium Big to Big Period % 15 19 19 43 22 121 41 20 45 187 59 97 703 0.3% 2.1% 1.2% 2.7% 2.7% 6.1% 3.1% 17.2% 5.8% 2.9% 6.4% 26.6% 8.4% 13.8% 0.7% 100.0% Period % 71 81 226 6.3% 7.2% 20.2% 243 148 180 34.6% 21.0% 25.6% Medium to Small Medium to Medium Medium to Big 14 10 1.2% 0.1% 0.9% 39 19 5.5% 0.3% 2.7% Small to Small Small to Medium Small to Big 20 23 1.8% 0.8% 2.1% 45 11 16 6.4% 1.6% 2.3% 17 645 1,121 0.4% 1.5% 57.5% 100% — — — 703 Andersen to Small Andersen to Medium Andersen to Big Total Number of Observations — — — 100% Industry groups are based on the following SIC codes: Agriculture ͑0100–0999͒, Mining and Construction ͑1000–1999͒, Food ͑2000–2111͒, Textiles and Printing ͑2200–2799͒, Chemicals ͑2800–2824, 2840–2899͒, Pharmaceuticals ͑2830– 2836͒, Extractive ͑1300–1399, 2900–2999͒, Durable Manufacturers ͑3000–3999͒, Transportation ͑4000–4899͒, Utilities ͑4900–4999͒, Retail ͑5000–5999͒, Financial ͑6000–6999͒, Services ͑7000–8999͒, Computers ͑3570–3579, 3670–3679, 7370–7379͒, and Other is all other SIC groups Period is February 1, 2002, to August 23, 2004 Period is August 24, 2004, to December 31, 2006 Big accounting firms are Deloitte, Ernst & Young, KPMG, and PricewaterhouseCoopers Medium are BDO Seidman and Grant Thornton Small accounting firms are all other firms except Andersen a Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 92 Chang, Cheng, and Reichelt TABLE Market Responses to Auditor Switches—Univariate Analysis Event Window (؊4, 0) Panel A: Period (February 1, 2002 to August 23, 2004) BtS BtM BtB Number of Observations Mean Daily Return p-value Mean Market-Adjusted Return p-value 81 0.010 0.37 0.008 0.46 226 0.006 0.19 0.004 0.43 Panel B: Period (August 24, 2004 to December 31, 2006) BtS BtM BtB Number of Observations Mean Daily Return p-value Mean Market-Adjusted Return p-value 148 0.007 0.23 0.004 0.46 180 0.005 0.18 0.003 0.45 71 0.002 0.77 0.000 0.98 243 0.008 0.18 0.006 0.31 Event window ͑Ϫ4, 0͒ indicates the return starts to accumulate at four days prior to the 8-K filing and ends on the filing date BtS, BtM, and BtB indicate the switch from Big to Small, Big to Medium 2, and Big to Big firms, respectively Mean Daily Return is the mean buy-and-hold return cumulated over the event window Mean Market-Adjusted Return is the mean Daily Return less the mean CRSP value-weighted market return p-values are two-tailed tests of no difference from than the other groups, but the differences are not significant Results in Table suggest that the market response to switches from Big to other audit firms is nonnegative in our sample periods Our univariate analysis is restricted to a small sample and does not control for the underlying reasons for auditor switching We conduct multiple regression analyses by using the whole sample after we examine the underlying reasons and firm characteristics for the switches in Periods and Comparison of Reasons and Firm Characteristics Since most company 8-K auditor change filings not report the auditor change reasons,13 we employ observable measures as surrogates for our major reasons of interest ͑i.e., audit fee reduction and better services͒ We also select reported 8-K reasons that may imply opinion shopping if we find a significant number of observations ͑Ͼ5 percent͒ We propose that the market will not respond negatively to an auditor switch if it is not likely to imply a decrease in future audit quality Under this situation, the market may respond relatively more positive to BtS switches if the switch is associated with an audit fee reduction or better services 13 We find that 22 percent ͑Period 1: 13 percent, Period 2: 38 percent͒ of our sample observations report either clientrelated reasons ͑e.g., going-concern, internal controls, financial restatements, audit opinion concerns͒, auditor-related reasons ͑e.g., scope limitations, lack of independence, and auditor merger͒, or fee-related reasons in the auditor change 8-K filings Auditing: A Journal of Practice & Theory American Accounting Association November 2010 100 Auditing: A Journal of Practice & Theory American Accounting Association TABLE Correlation Analysis of Key Variables (n ‫)428,1 ؍‬ Daily_ Return Daily_Return Market_Return Non_Specialist Accruals_Inferiority Abs_Acc Fee_Decrease Small_Auditor_Expert GCAO AAIC AAFR Size Market_ Return 0.269 0.366 Ϫ0.049 Ϫ0.004 Ϫ0.014 Ϫ0.027 0.025 Ϫ0.007 0.043 0.038 0.087 Ϫ0.040 0.003 Ϫ0.037 Ϫ0.014 0.040 0.061 0.120 0.069 0.029 Non_ Specialist Accruals Inferiority Ϫ0.001 Ϫ0.037 Ϫ0.016 0.017 0.035 0.018 Ϫ0.006 Ϫ0.032 0.026 0.003 Ϫ0.027 Ϫ0.016 ؊0.155 Ϫ0.001 Ϫ0.036 0.000 0.007 Ϫ0.050 Ϫ0.045 0.103 Abs_Acc Ϫ0.016 0.001 0.068 0.222 Ϫ0.042 ؊0.148 0.065 0.019 Ϫ0.027 ؊0.079 Fee_ Decrease Ϫ0.021 Ϫ0.015 Ϫ0.032 0.004 Ϫ0.047 0.053 0.018 0.009 0.020 Ϫ0.024 Small_ Auditor_ Expert 0.051 0.026 0.026 Ϫ0.025 ؊0.082 0.053 0.015 Ϫ0.010 Ϫ0.002 0.003 GCAO 0.012 0.045 0.003 0.044 0.143 0.018 0.015 0.394 0.665 ؊0.103 AAIC AAFR Size 0.062 0.084 Ϫ0.027 0.016 0.044 0.009 Ϫ0.010 0.394 0.035 0.052 Ϫ0.016 Ϫ0.026 Ϫ0.005 0.020 Ϫ0.002 0.665 0.472 Ϫ0.004 Ϫ0.001 Ϫ0.054 0.077 Ϫ0.035 Ϫ0.024 Ϫ0.022 Ϫ0.029 Ϫ0.042 Ϫ0.022 0.472 ؊0.103 Ϫ0.037 Bold indicates significance at percent level Left lower corner reports Spearman correlation coefficients, upper right corner reports Pearson correlation coefficients See the Appendix for variable definitions Chang, Cheng, and Reichelt November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 101 TABLE Regression Analysis without Interaction of Reason Variables Period (n ‫)121,1 ؍‬ Adjusted R2 Intercept Market_Return BtS ͑Big to Small͒ BtM ͑Big to Medium͒ BtB ͑Big to Big 4͒ Fee_Decrease Non_Specialist Small_Auditor_Expert Accruals_Inferiority GCAO AAIC AAFR Size ͑log͒ F-test: Intercept ϩ ␤ ϭ Intercept ϩ BtS Intercept ϩ BtM Intercept ϩ BtB Period (n ‫)307 ؍‬ 0.075 0.073 0.075 0.068 0.068 Ϫ0.011 ** Ϫ0.022** Ϫ0.012* Ϫ0.011 Ϫ0.006* 0.795*** 0.787*** 0.784*** 1.379*** 1.389*** 0.006 0.004 0.008 0.017** 0.011 0.014* 0.015* 0.014 0.013 0.016* 0.015* 0.010 0.010 0.009 0.014* Ϫ0.007 Ϫ0.007 Ϫ0.003 0.001 0.002 0.002 0.000 Ϫ0.001 0.017* 0.002 0.002 Ϫ0.005 Ϫ0.029** 0.002 0.011 0.002 0.000 0.008 0.004 Ϫ0.007 0.002 Ϫ0.001 Ϫ0.014 Ϫ0.006 Ϫ0.013 0.005 0.002 0.002 0.000 0.004 0.004 0.069 Ϫ0.031** 1.316*** 0.009 0.013 0.011 Ϫ0.003 0.003 0.018* Ϫ0.005 0.019 0.010 Ϫ0.019 0.003 Ϫ0.022 Ϫ0.018 Ϫ0.020 *, **, *** Significant at 0.10, 0.05, and 0.01, respectively All tests are two-tailed, except the F-test of intercept ϩ ␤ ϭ All F-tests of intercept ϩ ␤ ϭ are not significant at a 10 percent level Period is from February 1, 2002, to August 23, 2004 Period is from August 24, 2004, to December 31, 2006 Dependent variable is Daily_Return ͑see the Appendix͒ Size ͑log͒ is the natural logarithm of market capitalization Accruals_Inferiority is the tercile rank of Accruals_Inferiority, defined in the Appendix Please see the Appendix for all other variable definitions Coefficients for missing Fee_Decrease and missing Accruals_Inferiority indicator variables are not reported for brevity Results are quantitatively similar without these indicator variables ͑i.e., less negative͒ market response for these switch groups The sum of the intercept and the coefficient is 0.005, 0.002, and 0.002 for BtS, BtM, and BtB, and are not significantly different from Consistent with univariate results reported in Table 3, these multiple regression results show a nonnegative market response to BtS, BtM, and BtB switches Without investigating the reasons, our results only reflect the mean effect of the switch In the second column of each Period, we add Fee_Decrease, Non_Specialist, Small_Auditor_Expert, and Accruals_Inferiority These variables are not significant in Period but the coefficient on Small_Auditor_Expert becomes positive and significant in Period Note that the coefficient on BtS in Period is still positive ͑0.011, reduced from 0.017͒ but is no longer significant, suggesting that the relatively more positive market response to BtS switches is partly explained by better services of the Small successor auditor.24 In the third column, the 8-K reasons that may imply opinion shopping, and size are added Only the GCAO coefficient is significant and negative ͑Ϫ0.029͒ in Period 1, implying that the 24 If we not include the Small_Auditor_Expert variable but include Fee_Decrease, Non_Specialist, and Accruals_Inferiority, then the coefficient on BtS is positive ͑0.016͒ and significant ͑p ϭ 0.04͒ in Period Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 102 Chang, Cheng, and Reichelt market responds negatively to companies with a going-concern or other audit opinion concern However, the coefficient sign changes and becomes insignificant in Period Also note that the intercept in both periods is significant and ranges in magnitude in Period from Ϫ0.012 to Ϫ0.031.25 If a switch from a Big has a low likelihood of an audit quality drop, ceteris paribus, then the response should be relatively more positive when compared to other switch groups For BtS switches, if the market perceives that the client also intends to seek an audit fee decrease without sacrificing audit quality or seek better services to improve audit quality, then the market should respond relatively more positive To test these hypotheses, we first interact the BtS, BtM, and BtB variables with a variable that surrogates a low likelihood of an audit quality drop ͑Non_Specialist ‫ ء‬Accruals_Inferiority͒ We then condition Fee_Decrease on these interaction variables For BtS switches, we further condition Small_Auditor_Expert on Non_Specialist ‫ ء‬Accruals_Inferiority Equation ͑4͒ below describes the model ͑firm subscripts are omitted for brevity͒: R = ␤0 + ␤1Market_Return + ␤2BtS + ␤3BtM + ␤4BtB + ␤5Fee_Decrease + ␤6Non_Specialist + ␤7Small_Auditor_Expert + ␤8Accruals_Inferiority + ␤9GCAO + ␤10AAIC + ␤11AAFR + ␤12Size͑log͒ + ␤13Non_Specialist ‫ ء‬Accruals_Inferiority + ␤14BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤15BtM ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤16BtB ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤17BtS ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤18BtM ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤19BtB ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␤20Small_Auditor_Expert ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority + ␧ ͑4͒ where R is the daily return culminated over the event window ͑Ϫ4,0͒ We also add Market_Return, the CRSP value-weighted return culminated over the ͑Ϫ4,0͒ event window, to control for market movement.26 Table reports the results To show whether BtS, BtM, or BtB switches generate a relatively more positive market response when the likelihood of an audit quality drop is low, Table 7, Panel A, first ignores the conditioning effects from an audit fee decrease and small auditor expertise Panel A reports that the coefficient on BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is positive in Period ͑0.037͒ and significant at the conventional level.27,28 Recall that the coefficient on BtS is 0.017, as previously 25 26 27 28 The significantly negative intercept in Period is explained by clients switching from Medium to Small auditors ͑MtS͒ Compared to Big to Small switchers, MtS switchers are smaller, have more nonspecialist predecessor auditors, higher accruals magnitude, and greater accruals inferiority Further investigation of the market response is left to future research We also find that the intercept decreases with the addition of variables with positive coefficient signs: Small_Auditor_Expert, AAIC, and Size ͑log͒ Instead of using a market-adjusted return which restricts the market beta ͑i.e., the correlation between firm return and market return͒ to 1, we include market return in the regression model For robustness, we also use the Fama-French three-factor return, size-adjusted return, and market-model beta risk-adjusted return, and our results are similar Note that the coefficients on the corresponding interaction term for both BtM and BtB are not significant at conventional levels in Period Our presumption is that BtM and BtS successors are not specialists, but for BtB successors this presumption may not hold We test and not find that BtB switches with a successor specialist generate a positive market response, suggesting that seeking expertise is not important for BtB clients We also drop the intercept terms Non_Specialist, Accruals_Inferiority, and Non_Specialist ‫ ء‬Accruals_Inferiority; we find that the coefficient on BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority ͑0.035͒ is still significant Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 103 TABLE Regression Analysis Interaction of Reason Variables Panel A: Interaction of Audit Quality Variables Period (n ‫)121,1 ؍‬ Adjusted R2 Intercept Market_Return BtS ͑Big to Small͒ BtM ͑Big to Medium 2͒ BtB ͑Big to Big 4͒ Fee_Decrease Non_Specialist Accruals_Inferiority Non_Specialist ‫ ء‬Accruals_Inferiority BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtM ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtB ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority Small_Auditor_Expert GCAO AAIC AAFR Size ͑log͒ Period (n ‫)307 ؍‬ 0.078 Ϫ0.020** 0.793*** 0.011 0.001 0.015** Ϫ0.006 0.001 0.001 0.005 Ϫ0.017 0.022** Ϫ0.016* 0.000 Ϫ0.026** 0.001 0.010 0.001 0.093 Ϫ0.023* 1.345*** Ϫ0.002 0.009 0.006 0.000 Ϫ0.005 Ϫ0.012*** 0.007 0.037*** 0.000 Ϫ0.007 0.027*** 0.007 0.007 Ϫ0.007 0.004** Panel B: Interaction of Audit Quality, Fee Decrease and Service Variables Period (n ‫)121,1 ؍‬ Adjusted R2 Intercept Market_Return BtS ͑Big to Small͒ BtM ͑Big to Medium 2͒ BtB ͑Big to Big 4͒ Non_Specialist Accruals_Inferiority Non_Specialist ‫ ء‬Accruals_Inferiority BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtM ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtB ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority Fee_Decrease BtS ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtM ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtB ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ء‬Accruals_Inferiority Small_Auditor_Expert Small_Auditor_Expert ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority GCAO AAIC AAFR Size ͑log͒ Period (n ‫)307 ؍‬ 0.076 Ϫ0.021** 0.791*** 0.012 0.001 0.015** 0.001 0.001 0.005 Ϫ0.018 0.022** Ϫ0.015* Ϫ0.004 Ϫ0.026 0.000 Ϫ0.006 Ϫ0.004 0.010 Ϫ0.025** 0.000 0.009 0.001 0.123 Ϫ0.023** 1.304*** 0.005 0.009 0.006 Ϫ0.003 Ϫ0.011 *** 0.006 0.020* 0.000 Ϫ0.007 0.001 Ϫ0.023 0.010 Ϫ0.005 0.003 0.097*** 0.004 0.008 Ϫ0.003 0.004** (continued on next page) Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 104 Chang, Cheng, and Reichelt *, **, *** Significant at 0.10, 0.05, and 0.01, respectively All tests are one-tailed Period is from February 1, 2002 to August 23, 2004 Period is from August 24, 2004 to December 31, 2006 Dependent variable is Daily_Return ͑see the Appendix͒ Size ͑log͒ is the natural logarithm of market capitalization Accruals_Inferiority is the tercile rank of Accruals_Inferiority, defined in the Appendix Please see the Appendix for all other variable definitions Coefficients for missing Fee_Decrease, missing Accruals_Inferiority indicator variables, and slope interactions between financial services and Non_Specialist, and among switching categories, financial services, and Non_Specialist are not reported for brevity Results are quantitatively similar without these indicator variables reported in Table 6, and in Table the coefficient on BtS is reduced to Ϫ0.002 ͑insignificant͒ These results imply that the relatively more positive market response to BtS switches is explained by a low likelihood of an audit quality drop In other words, the market views switches from a Big auditor to a Small auditor more favorably if they have a low likelihood of an audit quality drop Note that the Accruals_Inferiority coefficient is negative ͑Ϫ0.012͒ and significant at conventional levels.29 The negative coefficient implies that the market reacts more negatively in Period to switches from a non-Big auditor with higher accruals inferiority, possibly suggesting opinion shopping for those switches.30 To examine whether the relatively more positive market response to BtS switches, when the likelihood of an audit quality drop is low, reported in Table 7, Panel A, is due to clients seeking an audit fee decrease and/or better services from Small auditors, Table 7, Panel B, reports the estimation of Equation ͑4͒ Equation ͑4͒ further interacts Fee_Decrease and Small_Auditor_Expert with BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority With these additional interaction variables, the coefficient on BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is reduced from 0.037 to 0.020 ͑still significant͒ This decrease is explained by Small_Auditor_Expert ͑0.097 and significant͒ but not by Fee_Decrease ͑Ϫ0.023 but not significant͒ It is interesting to note that the coefficient on BtS ‫ء‬ Non_Specialist ‫ ء‬Accruals_Inferiority is still positive, which implies that reasons other than better expertise explain the relatively more positive response If we have controlled for an audit fee decrease and small auditor expertise adequately, this relatively more positive effect may be attributed to better services affects other than small auditor expertise.31 To check if our findings are robust to missing firm characteristics, we add the following variables: SG, BP, Segment, FORSA, Leverage, ∆Financing, Loss, and ROA, and also interact them with each switching category ͑BtS, BtM, and BtB͒ In untabulated analysis, we find that our main results still hold, that is, the coefficient on Small_Auditor_Expert ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is still positive We conclude that in Period 2, the market responds relatively more positively to clients switching from a Big to a Small auditor, who expect better services when the predecessor’s audit quality is low Robustness Checks This section provides a discussion of various robustness checks 29 30 31 The coefficient on Accruals_Inferiority from Table in Period becomes significant in Table once we control for the low likelihood of an audit quality drop ͑i.e., add Non_Specialist ‫ ء‬Accruals_Inferiority͒ The negative coefficient on Accruals_Inferiority in Table is due to switches from a non-Big auditor To confirm this conjecture, we add another variable to surrogate for better services: Capacity Small auditors with more capacity can focus greater personal attention on publicly traded clients Using the number of BtS switches to measure Capacity, we find Capacity ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is significantly positive; however, the coefficient on BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is still significantly positive, implying that either our measures of better services are weak or there are other positive reasons We leave this question to future research Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 105 Dismissals versus Resignations Prior research suggests that the market responds negatively when auditors resign ͑e.g., Shu 2000͒ If this is the case in our sample period ͑2002–2006͒, we should expect a relatively more positive market response for dismissals than for resignations To investigate if there are differences in market responses between dismissals and resignations, we add to Equation ͑4͒ an indicator variable for dismissals along with interactions of the Big to Small accounting firm switching category ͑BtS_Dismiss͒ and the other two switching categories We not find that the coefficients on BtS ‫ ء‬Dismiss, BtM ‫ ء‬Dismiss, and BtB ‫ ء‬Dismiss are significantly positive We conclude that our main results are not affected by whether the BtS switches are resignations or dismissals We conjecture two reasons First, prior literature indicates that auditors resign due to client risk ͑e.g., Krishnan and Krishnan 1997; Shu 2000͒, client misalignment ͑Shu 2000͒, and a low audit fee ͑Hackenbrack and Hogan 2005͒ However, Landsman et al ͑2009͒ suggest that in the post-SOX era, the Andersen supply and the SOX 404 demand shocks reduced the sensitivity of Big N switches to client risk reasons and increased the sensitivity to client misalignment In untabulated analysis, we find that the BtS rate of resignations increased from 17 percent of total switches in Period to 25 percent in Period The increased rate of BtS resignations suggests that the SOX 404 demand shocks provided an opportunity to improve client alignment, and hence, no negative market response Second, many of the dismissals may in principle be resignations ͑e.g., the auditor forced the dismissal by asking too high an audit fee for next year’s engagement͒ Control for Departure Return Many auditor resignation cases, and some dismissal cases, are announced so far before the successor auditor’s engagement date that our five-day event window may not include the market return of the resignation or dismissal Upon closer examination, resignations ͑n ϭ 288͒ on average are 35.45 days apart, from the departure date to the engagement date, and dismissals ͑n ϭ 1,536͒ are 2.47 days apart Consequently, our return variable may be biased since it may omit the market “correction” ͑i.e., a departure return͒ for the previous resignation and dismissal return that is outside our ͑Ϫ4,0͒ return window surrounding the engagement of the new auditor To control for the omitted departure return, we compute the departure return for any auditor switch which occurs outside the ͑Ϫ4,0͒ event window, and we add it to our regressions The departure return is the five-day market-adjusted return ͑0,4͒ estimated from the date of the departure through to the following four business days We find our main results are robust to controlling for the departure return Period Cut-Off As discussed before, we chose August 23, 2004, as the cut-off point between the two periods due to three regulatory events We further examine the market response for the period after October 17, 2005, when the SEC and the PCAOB encouraged companies to switch from a Big accounting firm Then-PCAOB Chairman William McDonough expressed views in a Wall Street Journal article published on October 17, 2005, stating that smaller clients are better off with a smaller auditor that fits, not necessarily a Big ͑Civils 2005͒ To examine whether the stock market response to Big to Small accounting firm switches is relatively more positive after October 17, 2005, we use this date to separate Period into two sub-periods We find that the mean market-adjusted return after October 17, 2005, is 0.008 ͑p ϭ 0.39͒, higher than 0.006 reported in Table Similarly, regressing returns on market returns and the three switching groups, BtS, BtM, and BtB, reveals a higher coefficient on BtS ͑0.023, p ϭ 0.06͒, compared to 0.017 reported in Table These results suggest that the relatively more positive market response to companies switching from a Big to a Small accounting firm occurred after the SEC and the PCAOB encouraged companies to switch Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 106 Chang, Cheng, and Reichelt Different Return Definitions Recall that the coefficient on market returns reported in Table differs between Period ͑0.795͒ and Period ͑1.379͒, suggesting that there may be systematic differences in the risk of the sample firms between the two periods To control for differences in risk for the sample firms, we employ the Fama and French ͑1993͒ three-factor abnormal return in our main results Table reports the results of estimating Equation ͑4͒ by replacing the dependent variable with the Fama and French ͑1993͒ abnormal return and dropping the market return as an explanatory variable In Period 2, the coefficient on Small_Auditor_Expert ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority is positive ͑0.101 versus 0.097 reported in Table 7, Panel B͒ and significant at the conventional level For further robustness purposes, we also use the market model-adjusted abnormal return and the size-adjusted return, and our results still hold TABLE Regression Analysis—Interaction of Reason Variables—Dependent Variable is Abnormal Return from Fama-French Three-Factor Model Interaction of Audit Quality, Fee Decrease, and Service Variables Period (n ‫)121,1 ؍‬ Adjusted R2 Intercept BtS ͑Big to Small͒ BtM ͑Big to Medium 2͒ BtB ͑Big to Big 4͒ Non_Specialist Accruals_Inferiority Non_Specialist ‫ ء‬Accruals_Inferiority BtS ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtM ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtB ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority Fee_Decrease BtS ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtM ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority BtB ‫ ء‬Fee_Decrease ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority Small_Auditor_Expert Small_Auditor_Expert ‫ ء‬Non_Specialist ‫ ء‬Accruals_Inferiority GCAO AAIC AAFR Size ͑log͒ 0.008 Ϫ0.022** 0.012 Ϫ0.009 0.013** 0.003 Ϫ0.001 0.005 Ϫ0.017 0.039*** Ϫ0.012 Ϫ0.002 Ϫ0.031 0.000 Ϫ0.013 Ϫ0.005 0.002 Ϫ0.015 0.001 0.012 0.002 Period (n ‫)307 ؍‬ 0.057 Ϫ0.022* 0.011 0.007 0.004 Ϫ0.003 Ϫ0.010** 0.004 0.019* 0.007 0.000 0.001 Ϫ0.026 0.001 Ϫ0.006 Ϫ0.005 0.101*** 0.015 0.008 Ϫ0.011 0.003* *, **, *** Significant at 0.10, 0.05, and 0.01, respectively All tests are one-tailed Period is from February 1, 2002, to August 23, 2004 Period is from August 24, 2004, to December 31, 2006 Dependent variable is the abnormal return from the Fama and French ͑1993͒ three-factor model Event Window is from four days before the 8-K filing date to the filing date ͑Ϫ4, 0͒ Size ͑log͒ is the natural logarithm of market capitalization Accruals_Inferiority is the tercile rank of Accruals_Inferiority defined in the Appendix Please see the Appendix for other variable definitions Coefficients for missing Fee_Decrease, missing Accruals_Inferiority indicator variables, and slope interactions between financial services and Non_Specialist, and among switching categories, financial services, and Non_Specialist are not reported for brevity Results are quantitatively similar without these indicator variables Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 107 Confounding Events Our results may be influenced by confounding events around the time of the 8-K filing announcement To control for these events, we add indicator variables for individual confounding event categories to the regression analysis Confounding events were searched from LexisNexis and Factiva nine days surrounding the 8-K filing date Knechel et al ͑2007͒ used a seven-day search window, but our five-day return window is greater than their three-day return window Search terms were based on Thompson et al ͑1987, Appendix A͒ and Knechel et al ͑2007͒ Search terms are: earnings, revis, restat, correct, dividend, repurchase, offer, issue, acquire, dispose, takeover, tender, r&d, capital expenditure, joint venture, forecast, analysis, analyst, enforcement, distress, litigation, settle, and SEC Total Confounding equals if a confounding event was found nine days surrounding the 8-K filing date, otherwise Individual confounding event categories and indicator variables are as follows Asset Change is an acquisition of a subsidiary, plant, or major asset; Distress is a company reorganization or restructuring of debt; Dividend is a declaration of a cash or stock dividend; Earnings is an earnings announcement for the year or quarter; Forecast is a sales forecast; Management Related is hiring, termination, or promotion of senior management ͑CEO, COO, or CFO͒; Other includes lawsuits, product recalls, plant closure, or risk of expropriation; Ownership Change is transactions related to stock offerings and stock repurchases; and Product Related is a product launch, licensing, patent grant, and R&D spending Table reports the results of adding these indicator variables Our results, controlling for confounding events, still hold.32 Other Tests We employ the following robustness tests and we find our main results from Equation ͑4͒ still hold These tests include using event windows ͑Ϫ4,1͒ and ͑Ϫ11,0͒, measuring accruals inferiority with abnormal accruals estimated from the performance-adjusted modified Jones model ͑Kothari et al 2005͒, restricting the audit quality measure exclusively to either Accruals_Inferiority or Non_Specialist, and adding a size interaction variable for each of the three switching groups ͑BtS, BtM, BtB͒ CONCLUSION We evaluate the market reaction to auditor switching from Big to Small accounting firms in the post-Arthur Andersen era Using data on auditor changes from Audit Analytics for the period 2002 to 2006, we find in the second period ͑after August 2004͒ that the market responded nonnegatively to auditor switches from Big to Small ͑third-tier͒ accounting firms ͑BtS͒, as well as to switches from Big to Medium and Big to Big 4, while the market reacted negatively to other switches We find this relatively more positive market reaction to BtS switches occurred when the Big predecessor did not warrant high audit quality ͑implying a low likelihood of an audit quality drop͒ We propose that seeking an audit fee decrease and/or seeking better services, when the likelihood of an audit quality drop is low, should induce a relatively more positive market response to a switch from a Big to a Small audit firm after August 2004 We find that the relatively more positive stock market response to a BtS switch is not explained by an audit fee decrease, but rather by a Small successor auditor who is likely to provide better services Results are robust to several tests such as confounding events, various market return measures, controls for firm characteristics of complexity, and need for external financing and profitability Our paper has important policy and managerial implications Our results suggest that the market has confidence in companies choosing Small audit firms to enhance the economic benefit 32 Our basic test results with interaction terms and reason variables ͑Equation ͑4͒͒ are unchanged by the addition of the confounding event indicator variables Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 108 Chang, Cheng, and Reichelt TABLE Regression Analysis Controlling for Confounding Events Period (n ‫)121,1 ؍‬ Adjusted R2 Intercept Market_Return BtS ͑Big to Small͒ BtM ͑Big to Medium 2͒ BtB ͑Big to Big 4͒ Total Confounding Asset Change Distress Dividend Earnings Forecast Management Related Other Ownership Change Product Related F-test: Intercept ϩ ␤ ϭ Intercept ϩ BtS Intercept ϩ BtM Intercept ϩ BtB 0.074 Ϫ0.006 0.795*** 0.006 0.014 0.010 0.000 Period (n ‫)307 ؍‬ 0.094 Ϫ0.005 0.816*** 0.005 0.012 0.008 Ϫ0.009 Ϫ0.391*** 0.007 0.014* Ϫ0.008 0.013 Ϫ0.007 0.017 Ϫ0.031 0.000 0.008 0.004 0.000 0.007 0.003 0.070 Ϫ0.016** 1.372*** 0.018** 0.014* 0.014* 0.009* 0.085 Ϫ0.014** 1.335*** 0.016** 0.015* 0.013 0.065*** 0.000 0.001 0.007 0.022 Ϫ0.015 Ϫ0.005 0.001 0.005 0.002 Ϫ0.002 Ϫ0.002 0.002 0.001 Ϫ0.001 *, **, *** Significant at 0.10, 0.05, and 0.01, respectively All tests are two-tailed, except the F-test of intercept ϩ ␤ ϭ All F-tests of intercept ϩ ␤ ϭ are not significant at 10 percent Period is from February 1, 2002, to August 23, 2004 Period is from August 24, 2004, to December 31, 2006 Dependent variable is Daily_Return ͑see Appendix͒ Confounding events were searched from Factiva and LexisNexis Total Confounding equals if a confounding event was found nine days around the 8–K filing date, and otherwise Individual confounding event categories and indicator variables are as follows Asset Change is an acquisition of a subsidiary, plant, or major asset; Distress is a company reorganization or restructuring of debt; Dividend is a declaration of a cash or stock dividend; Earnings is an earnings announcement for the year or quarter; Forecast is a sales forecast; Management Related is hiring, termination, or promotion of senior management ͑CEO, COO, or CFO͒; Other includes lawsuits, product recalls, plant closure, or risk of expropriation; Ownership Change is transactions related to stock offerings and stock repurchases; and Product Related is a product launch, licensing, patent grant, and R&D spending in terms of better services from the auditor This is consistent with the regulators’ encouragement of selecting Small audit firms to improve competition, and will help ease the reluctance that companies have in choosing a Small auditor Our paper also has implications for future research in auditor switching We caution that in order to observe market responses to positive reasons for audit switches ͑e.g., better services͒, the researcher should control for the likelihood of an audit quality drop ͑i.e., the interaction of the predecessor nonspecialist and accruals inferiority͒ in their study This methodology may be applied to future research of auditor switches when an audit quality drop is a concern Our results are limited by the appropriateness of our measures We not find that an audit fee decrease explains the relatively more positive market response to switches from a Big to a Small auditor The null result may be ascribed to the measurement error associated with our audit fee decrease variable since we use the ex post actual audit fee which may differ from the market’s Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 109 expectation The null result warrants future research Furthermore, our finding of a relatively more positive response to switches to Small auditors with industry expertise may only capture a partial factor of better services ͑i.e., expertise͒ Other measures, such as capacity constraint, professional services ͑e.g., web design͒, and customer satisfaction may also warrant more research APPENDIX VARIABLE DEFINITIONS Market Return Variables Daily_Return Market_Return ϭ the buy-and-hold return cumulated over four days prior to the 8-K filing and ending on the filing date ͑Ϫ4,0͒; and ϭ the CRSP value-weighted return cumulated over the event window ͑Ϫ4,0͒ Data Source: CRSP Nonexpertise of Predecessor Non_Specialist ϭ if the predecessor auditor does not have the number-one rank in market share of audit fees by two-digit SIC, city, and year, otherwise Data Source: Audit Analytics Accruals Inferiority Prior to Audit Switch Accruals_Inferiority ϭ the residual of ͑predicted͒ accruals quality, following Francis et al (Innate_Accruals_ ͑2005a͒, in the last year of the predecessor auditor ͑year t͒ from Inferiority) annually estimating the following OLS Equation ͑a͒ ͑firm subscripts omitted for brevity͒: AQt = ␭0 + ␭1lAssetst + ␭2␴͑CFO͒t + ␭3␴͑Sales͒t + ␭4OperCyclet + ␭5NegEarnt ͑a͒ + u t; AQt Note that higher values of Accruals_Inferiority indicate greater inferiority of accruals quality; ϭ accruals quality in year t, the standard deviation of the residual from estimating the following Equation ͑b͒ by year t and two-digit SIC for years t−4 to t ͑with at least three observations available͒: TACCt = b0 + b1CFOt−1 + b2CFOt + b3CFOt+1 + b4⌬REVt + b5 PPEt + ␧ t; lAssetst ␴͑CFO͒t ␴͑Sales͒t OperCyclet NegEarnt ut ͑b͒ ϭ the natural logarithm of total assets ͑#6͒ in year t; ϭ the standard deviation of operating cash flow ͑#308͒ divided by average assets over years t−9 to t ͑with at least five years͒; ϭ the standard deviation of sales revenue ͑#12͒ divided by average assets over years t−9 to t ͑with at least five years͒; ϭ the natural logarithm of the operating cycle length ͑sum of days receivables, and days inventory͒ in year t; ϭ the number of years out of the past ten in year t where net income before extraordinary items ͑#123͒ Ͻ 0; ϭ is the error term in Equation ͑a͒; (continued on next page) Auditing: A Journal of Practice & Theory November 2010 American Accounting Association 110 Chang, Cheng, and Reichelt ϭ total accruals ͑net income before extraordinary items ͑#123͒ less operating cash flow ͑#308͒͒ in year t, divided by average total assets ͑average of current and prior year #6͒ in year t; ϭ operating cash flow ͑#308͒ in year t divided by total assets ͑#6͒ in CFOt year t; ⌬REVt ϭ the change in sales revenue ͑#12͒ between year t−1 and t divided by total assets in year t; ϭ gross value of PPE ͑#7͒ in year t divided by total assets in year t; PPEt ϭ the error term for Equation ͑b͒; and ␧t Abs_Acc ϭ the absolute value of total accruals in year t Data Source: Compustat Annual TACCt Fee Decrease and Audit Fee Model Variables Fee_Decrease ϭ if the actual audit fee in the last year of the predecessor auditor is greater than predicted and the actual fee audit fee in the first year of the successor auditor is less than predicted, otherwise The predicted audit fee is annually estimated from the following OLS model ͑c͒ from public company data ͑firm subscripts omitted for brevity͒ in year t where: laf t = ␤0 + ␤1ltat + ␤2segmentt + ␤3 for_sales_pct + ␤4rect + ␤5invt + ␤6roat + ␤7losst + ␤8opiniont + ␤9ltdt + ␤10dect + ␤11opinion_lagt + industry dummiest ͑c͒ + e t; ϭ the natural logarithm of audit fee in year t; ϭ the natural logarithm of total assets ͑#6͒ in year t; ϭ the natural logarithm of the number of business segments in year t; ϭ foreign sales as a percentage of total sales in year t; ϭ total receivables ͑#2͒ divided by total assets in year t; ϭ inventory ͑#3͒ divided by total assets in year t; ϭ earnings before extraordinary items ͑#18͒ divided by total assets in year t; ϭ if net income ͑#172͒ in year t Ͻ 0, otherwise; losst ϭ if the auditor issues a going-concern opinion in year t, otherwise; opiniont ϭ long-term debt ͑#9͒ divided by total assets in year t; ltdt ϭ if the fiscal year t ends December 31, otherwise; dect ϭ the number of days between the fiscal year-end t and the audit report opinion_lagt date; ϭ indicator variables from two-digit SIC categories in year t; and industry dummiest ϭ the error term for Equation ͑c͒ et Data Sources: Audit Analytics, Compustat Annual, and Compustat Annual Segment data laf t ltat segmentt for_sales_pct rect invt roat Better Services (continued on next page) Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 111 ϭ if the client switched from a Big to a Small auditor and the Small successor auditor is an industry expert, otherwise, as defined as follows: if the Small successor auditor has between one and five clients that switched from a Big 4, and they indicate industry specialization on their website ͑or verbally otherwise͒; if the Small successor auditor has between six and ten clients that switched from a Big 4, the Small auditor is an industry expert in a particular industry if at least 50 percent of the clients switching are in the same industry Likewise, for between 11 and 20 clients switching, the threshold for an industry expert is at least 40 percent of clients switching are in the same industry, and for 21 or more clients switching the threshold is 35 percent Data Sources: Hand-Collection from Small Auditor Websites and Audit Analytics Small_Auditor_ Expert 8-K Reported Reasons GCAO ϭ if the 8-K filing for the auditor change indicated for the past two fiscal years there was not an unqualified financial statement opinion ͑adverse, disclaimer, qualified, or modified, including going-concern͒, otherwise; AAIC ϭ if the 8-K filing for the auditor change indicated that there was an internal control issue, otherwise; and AAFR ϭ if the 8-K filing for the auditor change indicated that a restatement of the financial statements occurred or will occur, otherwise Data Source: Audit Analytics Firm Characteristics Size ϭ market capitalization ͑$billions͒ during the auditor switch, the stock price per share times the number of shares outstanding ͑in billions͒; SG ϭ average sales growth for years t−2 to t ͑salest / salest−1 + salest−1 / salest−2 + salest−2 / salest−3͒ / where salest is sales revenue ͑#12͒ in year t; BP ϭ the book to price ratio, book value ͑#216͒/market value ͑#199 ‫,͒52# ء‬ in year t; Segment ϭ the natural logarithm of the number of business segments in year t; FORSA ϭ the ratio of foreign sales to total sales revenue in year t; Leverage ϭ long-term debt ͑#9͒ divided by total assets ͑#6͒ in year t; ∆Financing ϭ the change in total financing in year t, ͑͑equity issuest+1͑#108͒ + debt issuest+1͑#111͒͒ / total assetst+1͒ minus ͑͑equity issuest + debt issuest͒ 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American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms 111 ϭ if the client switched from a Big to a Small auditor and the Small. .. auditor change 8-K filings Auditing: A Journal of Practice & Theory American Accounting Association November 2010 Market Reaction to Auditor Switching from Big to Third-Tier Small Accounting Firms. .. 20 04? ? that the market responded nonnegatively to auditor switches from Big to Small ? ?third-tier? ? accounting firms ͑BtS͒, as well as to switches from Big to Medium and Big to Big 4, while the market