PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

Ran Zhang; Si Chen; Jianfeng Wang

doi:10.1080/21697221.2013.857816

PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

Zhang, Ran; Chen, Si; Wang, Jianfeng 2013-12-01 00:00:00 China Journal of Accounting Studies, 2013 Vol. 1, Nos. 3–4, 221–235, http://dx.doi.org/10.1080/21697221.2013.857816 PCAOB inspections, auditor reputation, and Chinese reverse merger frauds Ran Zhang*, Si Chen and Jianfeng Wang Guanghua School of Management, Peking University, People’s Republic of China This paper examines whether Public Accounting Oversight Board (PCAOB) inspections decrease fraud likelihood in the Chinese reverse merger ﬁrms’ accounting crisis and whether auditor reputation moderates this relationship. By analyzing Chinese ﬁrms listed in the US stock markets through reverse merger (RM) during 2001–2011, we ﬁnd that PCAOB inspections signiﬁcantly decrease accounting fraud likelihood for RM ﬁrms, especially for auditors with low reputation. But this relation- ship does not hold for Chinese initial public offering (IPO) ﬁrms listed in the US. The reason may be that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms, whose reputation substitutes for PCAOB inspections. Overall, our results indicate that PCAOB inspections help prevent ﬁnancial frauds, but only for ﬁrms hiring non-Big 4 auditors. Keywords: reverse merger; PCAOB inspections; auditor reputation; accounting fraud JEL Classiﬁcations: G34; L51; M41; M42; M49 1. Introduction The recent accounting crisis involving Chinese reverse merger ﬁrms has caused big losses to Chinese companies. In June 2010, Orient Paper Inc., a Chinese company listed in the US, was accused of ﬁnancial fraud by Muddy Waters Research, a short selling investment ﬁrm. The stocks of the company were heavily shorted and the company suffered a crisis with a sharply falling stock price. Other Chinese companies listed in the US, including Rino International Corp., Longtop Financial Technologies Limited, and China-Biotics Inc., experienced the same challenges soon afterwards. Investors and regulators became distrustful, the Securities and Exchange Commission (SEC) began to investigate the ﬁnancial disclosures of Chinese companies, and many Chinese ﬁrms listed in the US were either forced to halt trading or delisted owing to information disclosure problems. This crisis not only exposes the ﬂaws of some Chinese companies in the informa- tion disclosure process, but also raises concerns about reverse merger companies and their auditors. Reverse merger (RM) is a way to list overseas other than through initial public offering (IPO), and fraudulent ﬁrms involved in this crisis are mostly listed in the US through reverse mergers instead of IPOs. These ﬁrms either are not qualiﬁed to list through IPOs or cannot afford the large amount of money and time to implement IPOs and thus choose to acquire overseas listed companies, often called ‘shell’ *Corresponding author. Email: RZHANG@gsm.pku.edu.cn Paper accepted by Xi Wu. © 2013 Accounting Society of China 222 Zhang et al. companies, to achieve their goals instead. They are usually small, with relatively high ﬁnancial and operational risk, and tend to hire small accounting ﬁrms, most of which are based in China. Since auditing is important to ensure the reliability of information disclosed and to protect investors, the SEC blamed these auditing ﬁrms for the ﬁnancial scandals. The PCAOB suspended the registration of accounting ﬁrms from China in October 2010. In December 2012, the SEC charged the China branches of top accounting ﬁrms with securities violations, saying that their refusal to hand over audit working papers has hindered investigations into frauds at US-listed Chinese ﬁrms. One of the SEC’s strongest criticisms is that auditing ﬁrms based in China deny PCAOB inspections, on the grounds that these inspections constitute an intervention by the US government. The PCAOB is a nonproﬁt corporation established by Congress to oversee the audits of public companies in order to regulate the accounting service industry and to protect the interests of investors. According to the Sarbanes-Oxley Act, any auditor of a company listed in the US – whether a US auditor or a non-US auditor – must be registered with, and therefore subject to the jurisdiction of, the PCAOB. The PCAOB inspects registered accounting ﬁrms and prepares a written report on each inspection identifying deﬁciencies to help enhance audit quality. But in reality, because of the position taken by certain non-US authorities, the PCAOB currently is prevented from inspecting the US-related audit work and practices of PCAOB-registered ﬁrms in some countries such as China and certain European countries. China’s government prohibits PCAOB inspections because Chinese domestic law regards certain information as state secrets and does not permit access by foreign regulatory bodies to detailed documents such as audit work papers. The SEC and PCAOB believe that PCAOB inspections are sufﬁcient to ensure audit quality and that denial of inspection brings unknown risk to the capital market, but it remains an unresolved empirical question whether PCAOB inspections enhance audit quality in practice. Do accounting ﬁrms to which the PCAOB is denied inspection access have worse audit quality and higher audit risk than those inspected? Do PCAOB inspections help lower the risk of ﬁnancial scandals? The recent accounting crisis at Chinese reverse merger ﬁrms provides a unique opportunity to examine these questions. Among the auditors working for Chinese reverse merger companies, US-based auditors are inspected by the PCAOB while China-based ones are not. In addition, the exposure of fraudulent ﬁrms helps us identify risk and thus indicates audit failure. Auditor reputation is another mechanism to lower the risk of accounting frauds. Studies have found that big accounting ﬁrms tend to have higher audit quality. For example, Lennox (1999) ﬁnds that Big 6 auditors report with greater accuracy in the United Kingdom, and Francis and Krishan (1999) show that Big 6 auditors are more likely to issue modiﬁed audit reports, indicating greater reporting conservatism for a given set of client characteristics. If PCAOB inspections enhance audit quality and decrease the likelihood of ﬁnancial fraud, will auditor reputation moderate this relationship? This is also an interesting and unresolved question. We examine whether PCAOB inspections decrease the likelihood of accounting fraud, particularly for ﬁrms involved in the recent Chinese crisis, and whether auditor reputation moderates this relationship. Our results show that (1) in the RM sample, PCAOB inspections signiﬁcantly decrease fraud likelihood, especially for auditors with low reputation; and (2) compared with the RM sample, PCAOB inspections don’t decrease fraud likelihood for Chinese ﬁrms listed in the US via IPOs. A possible reason is that IPO ﬁrms tend to hire Big 4 accounting ﬁrms, and these ﬁrms’ care for their reputation ensures their audit quality, which substitutes for PCAOB inspections. China Journal of Accounting Studies 223 Our study not only extends the existing literature on reverse mergers but also has practical implications for audit quality regulation. First, we contribute to the growing literature about RMs, especially Chinese RMs. While previous research argues that RM ﬁrms are highly risky, we show that the risk is partly due to the auditors and is reduced by PCAOB inspections. Second, although previous studies have compared RM companies with IPO companies, only a few focus on the auditing perspective. Our study demonstrates that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms while only 6.02% of RM ﬁrms do so. This difference results in an audit quality gap. We conclude that PCAOB inspections are effective, and we suggest that Chinese regulators should extend cooperation with the PCAOB. 2. Background and case study 2.1. Background In China, accounting ﬁrms are regulated in a multifaceted way. There are several regulators, including the Ministry of Finance (MOF), the China Securities Regulatory Commission (CSRC), and the Chinese Institute of Certiﬁed Public Accountants (CICPA). All these authorities conduct inspections. Founded in November 1988, the CICPA is a special industrial self-regulatory organization under the guidance of the Ministry of Finance. It conducts inspections on practice quality of accounting ﬁrms every year, usually from June to July. Under the ‘Rules for Practice Quality Inspection of Accounting Firms,’ ﬁrms with securities qualiﬁcations must be inspected at least once every 3 years, while other accounting ﬁrms must be inspected at least once every 5 years. The inspections focus on compliance with business norms, quality control norms, code of professional ethics, and so on. And the CICPA takes disciplinary actions against ﬁrms found to have committed practice violations. MOF and CSRC inspections are similar, but are carried on by provincial bodies of the MOF and CSRC respectively. The responsibilities of three authorities thus overlap, resulting in an ineffective regulation as a whole. While the audit control system in China is comprehensive and multifaceted, in the US inspecting accounting ﬁrms is the duty of just one organization, namely the PCAOB. However, as we outline above, China does not permit PCAOB inspections, a major rift in China–US auditing regulation cooperation. If the SEC wins its current court case, Chinese accounting ﬁrms may be disqualiﬁed to audit in the US, and related Chinese companies will be forced to delist because they can’t meet the US requirements for information disclosure. This will be harmful to both China and the US. To solve this problem, China and the US are negotiating: in July 2011, PCAOB and SEC ofﬁcials arrived in Beijing and talked with the CSRC and the MOF. In July 2012, Mary L. Schapiro, former SEC president, visited China, and China and the US agreed that PCAOB investigators could observe the inspections and evaluations of Chinese accounting ﬁrms by the CSRC and the MOF. On May 7, 2013, the CSRC and the MOF entered into a memorandum of understanding with the PCAOB, and auditing cross-border enforcement cooperation between China and the US thus began. According to the memorandum of understanding, the PCAOB can request related audit documents from the CSRC and the MOF when investigating Chinese accounting ﬁrms that are registered with the PCAOB. This memorandum will lay a foundation for future cooperation. 224 Zhang et al. 2.2. Case study To help understand the effect of PCAOB inspections, consider one company, Universal Travel Group (OTC: UTRA), a travel service provider based in Shenzhen, China. In June 2006, it was listed in the US through reverse merger. In 2011, a short-seller, Glaucus Research Group, issued a report alleging that Universal Travel was fabricating its ﬁnancial statements ﬁled with the SEC, and that its underlying business was smaller than it reported in its SEC ﬁlings. Subsequently, on March 29, 2011, Universal Travel announced that it would postpone its earnings announcement for the ﬁscal year ending December 31, 2010. On April 12, 2011, the trading of Universal Travel’s stock was halted, and the company ﬁnally delisted from NYSE in April 2012. The company’s auditor is an accounting ﬁrm called Acquavella, Chiarelli, Shuster, Berkower & Co, LLP. It is based in New Jersey, and has seven partners, two ofﬁces, 32 professional staff, and 12 clients in 2010. This accounting ﬁrm is registered with the PCAOB and accepts its periodic inspections. In the 2010 inspection report, the PCAOB identiﬁed seven deﬁciencies in the three audits reviewed: (1) failure to perform sufﬁcient audit procedures to evaluate whether goodwill was impaired; (2) failure to perform sufﬁcient audit procedures to evaluate the accounting for a transfer of buildings and related land use rights; (3) failure to perform sufﬁcient audit procedures to test revenue; (4) failure to perform sufﬁcient audit procedures to test accounts receivable; (5) failure to perform sufﬁcient audit procedures regarding warrants; (6) failure to perform sufﬁcient audit procedures to test the valuation of stock-based compensation; and (7) failure to evaluate the effect of reported material weaknesses on the nature, timing, and extent of substantive procedures performed in the audit of the ﬁnancial statements. We can see from this case that the PCAOB effectively identiﬁes deﬁciencies in auditing and discloses the audit quality to the client companies as well as the whole market. On one hand, this helps accounting ﬁrms improve their audit process and achieve better audit quality; on the other hand, it provides relevant information to investors and helps them identify and control risk. 3. Literature review 3.1. Reverse merger Recently, as more companies have gone public through reverse merger, reverse merger has attracted much attention. Studies have addressed both the supply and the demand side of the market for reverse merger. On the supply side, there is a ‘shell’ market for reverse mergers. These shells are either established specially for merger without any operating history or substantial business, or are relics from previously failed businesses. Gleason, Rosenthal, and Wiggins (2005) examine 121 reverse mergers and ﬁnd that shell shareholders receive signiﬁcant wealth gains upon announcement of a reverse merger. Floros and Sapp (2011) reach a similar conclusion: when a takeover agreement is consummated, the shell company’s three-month abnormal returns are as high as 48.1%, which can be seen China Journal of Accounting Studies 225 as compensation to investors for shell stock illiquidity and the uncertainty of ﬁnding a reverse merger suitor. On the demand side, studies have largely focused on the motivation for using a reverse merger rather than an IPO. For example, Brau, Francis, and Kohers (2003) examine factors that inﬂuence the choice between IPO and reverse merger and show that industry concentration, high-tech industry afﬁliation, current cost of debt, relative ‘hotness’ of the IPO market, ﬁrm size, and insider ownership percentage are all related to this choice. Poulsen and Stegemoller (2008) show that ﬁrms that have fewer growth opportunities and face less capital constraint tend to go public through reverse merger. In the same spirit, Adjei, Cyree, and Walker (2008) suggest that RM ﬁrms are typically smaller and younger, with poorer ex ante performance. Within 3 years of listing, 42% of the reverse merger companies are delisted compared with 27% of matched IPOs. 3.2. PCAOB inspections and auditor reputation The Sarbanes-Oxley Act requires the PCAOB to conduct inspections annually of ﬁrms that regularly audit more than 100 issuers, and at least triennially of ﬁrms that regularly audit 100 or fewer issuers. The PCAOB prepares a written report on each inspection to identify the deﬁciencies in the auditing work. Researchers have drawn different conclusions about the effect of PCAOB inspections. Some maintain that PCAOB inspections do help auditors enhance audit quality and companies and investors value the information of inspections reports when they make decisions. For example, Gramling, Krishnan, and Zhang (2009) ﬁnd that reports of deﬁciencies for ﬁrms inspected triennially signal undetected or underreported going-concern problems. Abbott, Gunny, and Zhang (2011) show that registrants with high potential agency conﬂicts or effective audit committees have incentives to switch away from auditors that have received an adverse, GAAP-deﬁcient PCAOB inspection report. Others hold opposite opinions. Daugherty and Tervo (2010) argue that PCAOB inspections are useful for rebuilding investors’ conﬁdence, but do not enhance audit quality substan- tially. Lennox and Pittman (2010a) ﬁnd that audit clients do not perceive that PCAOB inspection reports are valuable for signaling audit quality, and audit ﬁrms’ market shares are insensitive to their PCAOB reports. The famous ‘Lemon Market’ theory by Akerlof (1970) has shown that reputation is a signal mechanism. Auditor reputation, as an important signal to measure audit quality, will signiﬁcantly affect the client ﬁrm’s stock price, information disclosure, and audit fees. Balvers, McDonald, and Miller (1988) and Beatty (1989) show that clients that hire more reputable accounting ﬁrms are less likely to be underpriced than clients that hire less reputable ones. Clarkson, Ferguson, and Hall (2003) ﬁnd that Big 6 auditors’ clients disclose more year 2000 remediation information in their annual reports than non-Big 6 auditor clients, which indicates that the Big 6 act more conservatively to protect their reputation. 4. Hypothesis development During the accounting crisis of China, auditing ﬁrms working for the reverse merger companies were widely criticized. Since some of these accounting ﬁrms were located in the US and thus were inspected by the PCAOB while others weren’t, we wonder whether PCAOB inspections decrease accounting fraud likelihood in practice. As mentioned above, prior literature provides mixed results on the effect of PCAOB 226 Zhang et al. inspections. Some studies document that the inspections help auditors enhance audit quality and disclose information regarding auditors and clients to the market (Abbott et al., 2011; Gramling et al., 2009), while others hold that the inspections don’t have a substantial effect and are not recognized by the market (Daugherty & Tervo, 2010; Lennox & Pittman, 2010a). Among all the auditors providing service for Chinese RMs, some received PCAOB inspections while others were denied. If PCAOB inspections enhance audit quality, we expect to see a signiﬁcantly lower likelihood of accounting fraud for those clients whose auditors received PCAOB inspections. We propose the following hypothesis to study the ﬁrst question: Hypothesis 1(a): PCAOB inspections signiﬁcantly enhance audit quality and thus decrease the likelihood of accounting fraud. Hypothesis 1(b): PCAOB inspections neither signiﬁcantly enhance audit quality nor decrease the likelihood of accounting fraud. According to reputation theory, clients will punish auditors by dismissing the auditor or reducing the audit fee if the auditor provides a poor audit. This mechanism will urge the auditor to keep improving audit quality to avoid the losses from damaged reputation. Since auditors with better reputation have more incentives to avoid risk and damage to reputation, they may provide better audits and better supervise listed companies. From this perspective, auditor reputation may moderate the relationship between PCAOB inspections and the likelihood of accounting fraud: Hypothesis 2: Auditor reputation moderates the relationship between PCAOB inspections and the likelihood of accounting fraud, and this relationship is more pronounced for auditors with low reputation. 5. Sample and data We obtained all the reverse merger events from DealFlow Media’s (DFM’s) Reverse Merger Report database. The original sample included 1799 RMs that became active on US stock markets between January 2000 and December 2011. Of the 1799 events, 428 were reverse mergers whose private ﬁrms were based in China. For each Chinese RM, we sought ﬁnancial information from the latest ﬁnancial report in the Worldscope database. Among the 428 Chinese RMs, 168 had such reports, including 83 in 2011. In addition, we hand-collected the fraudulent ﬁrm list from the Securities and Exchange Commission (SEC) website and the media to obtain 29 fraudulent ﬁrms out of the 428 Chinese RMs. Table 1 provides an overview of the RMs in our sample, distributed by year of merger. Table 1 shows that Chinese RMs increased signiﬁcantly after 2001, peaking at 36 in 2006 and falling slightly in 2007 and 2008. The decline was exacerbated by the fraud crisis. In 2011, only ﬁve Chinese companies listed in the US through reverse merger, and overseas listing hit bottom. Correspondingly, fraud mostly happened in 2006–2008, as reverse mergers were exploding and fraudulent ﬁrms mixed into the capital markets with good ones. The auditor information for the sample companies came from the SEC website. We hand-collected the 2011 ﬁnancial reports of all the companies and searched for the signature of the auditor by using the keywords ‘Report of Independent Registered Public Accounting Firm.’ China Journal of Accounting Studies 227 Table 1. Distribution by year of merger for reverse mergers. Non-fraudulent ﬁrms Fraudulent ﬁrms Year No. of RMs N Percentage（%） N Percentage（%） 2001 1 1 100.00 0 0.00 2002 0 0 0.00 0 0.00 2003 6 6 100.00 0 0.00 2004 15 13 86.67 2 13.33 2005 20 18 90.00 2 10.00 2006 36 29 80.56 7 19.44 2007 31 22 70.93 9 29.03 2008 29 24 82.76 5 17.24 2009 12 10 83.33 2 16.67 2010 13 11 84.62 2 15.38 2011 5 5 100.00 0 0.00 Total 168 139 82.74 29 17.26 This table presents an overview of the RMs in our sample, distributed by year of merger. Our sample includes all the reverse merger events from 2000 to 2011 in DealFlow Media’s (DFM’s) Reverse Merger Report data- base and we hand-collected the fraudulent ﬁrm list from the Securities and Exchange Commission (SEC) website and the media. Since accounting ﬁrms in countries that prohibit PCAOB inspections may have unknown risk, the PCAOB publishes and regularly updates a list identifying each ﬁrm whose PCAOB-registered auditor is located in such countries. We matched auditing ﬁrms in our sample with the list to determine whether an auditing ﬁrm was inspected by the PCAOB. If yes, then a variable ACCESS is coded 1, and 0 otherwise. For those that were inspected (ACCESS=1), we obtained their PCAOB inspection reports from the PCAOB website, from which we collected auditor’s information including number of ofﬁces (OFFICE), number of staff members (STAFF), and number of clients (CLIENT). For those ﬁrms that denied inspection (ACCESS=0), we collected the auditor’s information from the Chinese Institute of Certiﬁed Public Accountants Information System as well as the China Stock Market & Accounting Research Database (CSMAR). We used the Global Accounting Firm Top 100 to determine the rank of the auditor (RANK), and hand-collected the auditor’s tenure with a client (TENURE) from the client’s annual reports. 6. Empirical method and results 6.1. Model speciﬁcation First we compare fraudulent ﬁrms to non-fraudulent ﬁrms in size, leverage, ROA, audi- tor opinion, and ﬁnancial condition. After that we focus on the auditor characteristics in univariate tests to see whether there is a difference. We then use regression models to test Hypothesis 1 and Hypothesis 2, extending our research to the IPO sample for comparison. The regression models to be estimated are FRAUD ¼ a þ a ACCESS þ a SIZE þ a LEV þ a ROA þ a AUQ þ a ZSCORE þ e 0 1 2 3 4 5 6 (1) FRAUD ¼ a þ a ACCESS þ a Auditorreputatation þ a ACCESS Auditorreputatation 0 1 2 3 þ a SIZE þ a LEV þ a ROA þ a AUQ þ a ZSCORE þ e ð2Þ 4 5 6 7 8 228 Zhang et al. where FRAUD = 1 if the reverse merger company is a fraudulent ﬁrm exposed in the crisis, and 0 otherwise; ACCESS = 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise; SIZE = the natural log of total assets; LEV = the ratio of total debt to total assets; ROA = income before extraordinary items divided by total assets; AUQ = 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise; ZSCORE = Z value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). Auditor reputation is measured by four proxies, including RANK, OFFICE, STAFF, and CLIENT. 6.2. Empirical results 6.2.1. Comparison of ﬁrm characteristics between fraudulent and non-fraudulent ﬁrms Table 2 compares ﬁrm characteristics between fraudulent and non-fraudulent ﬁrms. Fraudulent and non-fraudulent ﬁrms are similar in size. The mean SIZE of non-fraudu- lent ﬁrms is 3.301, while the mean SIZE of fraudulent ones is 3.748; the difference is not statistically signiﬁcant (p-value = 0.33). Mean leverage, measured as the sum of short-term and long-term debts divided by total assets, is 0.679 for non-fraudulent ﬁrms and 0.385 for fraudulent ones; again, the difference is not statistically signiﬁcant (p-value = 0.72). We use ROA and ZSCORE to measure ﬁrms’ proﬁtability and ﬁnancial condition, and AUQ to measure audit opinions. None of these variables appears to differ signiﬁcantly across the two groups. In a word, non-fraudulent ﬁrms and fraudulent ones are similar in general characteristics. Table 2. Comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. Non-fraudulent ﬁrms Fraudulent ﬁrms (N=73) (N=10) Difference Variable Mean Median Mean Median Mean Median SIZE 3.301 3.541 3.748 3.567 –0.447 –0.026 　　　　　 (0.33) (0.56) AUQ 0.767 1.000 0.800 1.000 –0.033 0.000 　　　　　 (0.82) (0.82) LEV 0.679 0.415 0.385 0.367 0.293 0.047 　　　　　 (0.72) (0.96) ROA –0.173 0.116 0.129 0.110 –0.303 0.006 　　　　　 (0.62) (0.99) ZSCORE 2.268 5.313 7.039 5.154 –4.772 0.159 　　　　　 (0.77) (0.98) Table 2 presents the comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). p-values are in parentheses. ***, **, and * represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. China Journal of Accounting Studies 229 6.2.2. Comparison of auditor characteristics between fraudulent and non-fraudulent ﬁrms Table 3 presents univariate evidence on auditor characteristics for ﬁrms in 2011. We use four proxies to measure auditor reputation: RANK, OFFICE, STAFF, and CLIENT. The mean RANK of non-fraudulent ﬁrms is 0.753, while that of fraudulent ones is 1.400. The difference is statistically signiﬁcant (p-value = 0.04), suggesting that fraudu- lent ﬁrms hire auditors with higher reputation. We get similar results using STAFF and CLIENT, while the difference in OFFICE is not statistically signiﬁcant. Table 3 also shows that the mean ACCESS is 0.932 for non-fraudulent ﬁrms and only 0.600 for fraudulent ones, indicating that fraudulent ﬁrms’ auditors are substantially less likely to have been inspected by the PCAOB. There are two possible explanations for this. One is that PCAOB inspections enhance audit quality, so that the clients of inspected auditors are less prone to become fraudulent. The second is that fraudulent ﬁrms prefer auditors not inspected by the PCAOB to avoid being detected (a self-selection effect). Our hypothesis is consistent with the ﬁrst explanation, which we examine through regression models. And we rule out the second explanation below. 6.2.3. PCAOB inspections and accounting fraud likelihood in the RM sample The univariate tests above indicate that ﬁrms employing auditors inspected by the PCAOB are less prone to ﬁnancial fraud. We examine this relationship further using regression models. The results are presented in Table 4. We can see that in model (1) of Table 4, the regression coefﬁcient is –2.314, and is signiﬁcant at the 1% level, which indicates that ﬁrms whose auditors were inspected by the PCAOB suffer less risk of ﬁnancial fraud. This ﬁnding supports Hypothesis 1(a). To further examine the moderat- ing effect of auditor reputation, we build model (2) by adding the variable RANK as well as an interaction term RANK*ACCESS. The coefﬁcient of the interaction term is signiﬁcantly positive, indicating that the relationship between PCAOB inspections and Table 3. Comparison of auditor characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms. Non-fraudulent ﬁrms Fraudulent ﬁrms (N=73) (N=10) Difference Variable Mean Median Mean Median Mean Median ** * RANK　 0.753 　 1.000 　 1.400 　 2.000 　 –0.647 (0.04) –1.000 (0.06) OFFICE　 5.311　 2.000 　 9.875 　 2.000 　 –4.564 (0.30) 0.000 (0.65) *** ** STAFF　 203.017 　 47.000 　 593.000 　 61.000　 –389.983 (0.00) –14.000 (0.02) *** ** CLIENT　 34.177 　 24.000 　 105.375 　 33.000 　 –71.198 (0.00) –9.000 (0.02) *** *** ACCESS　 0.932 　 1.000 　 0.600 　 1.000 　 0.332 (0.00) 0.000 (0.00) BIG4 0.055 0.000 0.100 0.000 –0.045(0.58) 0.000(0.58) TENURE 2.342 2.000 2.100 2.000 0.242(0.66) 0.000(0.94) Table 3 presents the comparison of auditor characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 3 when in top 4. OFFICE is the ofﬁce number of auditor in total. STAFF is the staff number of auditor. CLIENT is the number of clients of the auditor. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. TENURE is the auditor’s tenure of a *** ** * client. p-values are in parentheses. , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. 230 Zhang et al. Table 4. The relationship between PCAOB inspections and accounting fraud likelihood in the reverse merger sample. 　 (1) (2) (3) Variables FRAUD FRAUD FRAUD *** ** *** ACCESS –2.314 –9.428 –4.337 (–2.71) (–2.53) (–3.77) RANK –2.709 (–1.85) RANK*ACCESS 2.910 (1.84) *** STAFF –0.001 (–3.28) STAFF *ACCESS 0.000 (0.00) SIZE 0.164 0.205 0.093 (0.36) (0.50) (0.50) AUQ –0.116 –0.303 –0.284 (–0.10) (–0.31) (–0.51) LEV –0.706 –0.869 –0.590 (–0.28) (–0.34) (–0.42) ** *** ROA 1.164 3.507 1.838 (1.45) (2.44) (3.32) ZSCORE –0.049 –0.112 –0.063 (–0.72) (–1.52) (–1.42) ** *** CONSTANT –0.048 7.027 3.445 (–0.02) (2.30) (2.91) OBS 80 80 65 R2 0.146 0.193 0.218 Table 4 presents the regression results for PCAOB inspections and accounting fraud likelihood. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 4 when in top 4. STAFF is the staff number of auditor. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z *** value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). , ** * , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. the likelihood of accounting fraud is more pronounced for auditors with low reputation. As a robustness test, we also use the number of staff (STAFF) as the proxy of auditor reputation and get similar results. In sum, the regression results of models (2) and (3) support Hypothesis 2. A potential concern with our ﬁndings is that there may be a self-selection bias stemming from two possible situations: the inspected audit ﬁrms may refuse to audit companies with a high propensity to engage in ﬁnancial fraud; or fraudulent ﬁrms may choose auditors that were not inspected by PCAOB to avoid being detected. If this self-selection bias does exist, it should be more severe when audit ﬁrm tenure is short. For example, suppose two companies commit accounting frauds in 2011 and are audited by the same uninspected ﬁrm. Company A initially hired this auditor in 2001, whereas company B switched to this auditor in 2010, either because its previous auditor resigned or because company B dismissed the previous auditor. In either situation, since the auditor choice decision of company B just occurred shortly before it began to perpetrate accounting fraud, the incentive is more questionable. On the other hand, since auditor tenure is relatively long for company A, it is less likely for China Journal of Accounting Studies 231 company A to choose the auditor to avoid being detected. Thus, we perceive that self-selection bias is more severe for company B than company A. We build model (3), following Lennox and Pittman (2010b), to check whether the association between accounting fraud and PCAOB inspections is weaker in a long-tenure sample owing to the self-selection bias. FRAUD ¼ a þ a ACCESS þ a LONG þ a ACCESS LONG þ a SIZE þ a LEV 0 1 2 3 4 5 þ a ROA þ a AUQ þ a ZSCORE þ e ð3Þ 6 7 8 where LONG is a dummy variable that equals 1 if the tenure of the auditor is above the median and 0 otherwise. The median of LONG is 2. The regression results for model (3) are presented in Table 5. Model (1) of Table 5 shows the relationship between accounting fraud likelihood and PCAOB inspections under the shorter tenure condition. The coefﬁcient of ACCESS is –1.859 and is statistically signiﬁcant at the 10% level, which again supports Hypothesis 1(a). We extend the model to model (2) of Table 5 to see whether there’sa self-selection problem. If there is self-selection bias in our sample, the interaction term LONG*ACCESS in model (3) will be signiﬁcantly positive. However, the results show that the coefﬁcient of ACCESS is still signiﬁcantly negative, while the coefﬁcient of the interaction term LONG*ACCESS is insigniﬁcant. That is to say, the self-selection problem is not severe in our sample and thus does not affect our conclusions. 6.2.4. PCAOB inspections and accounting fraud likelihood in the IPO sample Does the relationship between PCAOB inspections and accounting fraud likelihood in the RM sample hold for the IPO sample? Table 6 provides an overview of the IPO sample. Panel A presents the distribution by year, which is quite similar to that of RMs. But obviously the accounting fraud likelihood of IPOs is much lower than that Table 5. Endogenous test between PCAOB inspections and accounting fraud likelihood. 　 (1) (2) FRAUD FRAUD Variables COEF Z COEF Z * ** ACCESS –1.859 (–1.93) –1.945 (–2.00) LONG 2.759 (1.61) LONG*ACCESS –2.924 (–1.45) SIZE 0.632 (0.73) 0.212 (0.46) AUQ 0.702 (0.64) –0.288 (–0.26) LEV 0.315 (0.15) –0.247 (–0.10) ** ROA 1.331 (0.57) 1.720 (2.16) ZSCORE –0.039 (–0.43) –0.034 (–0.50) CONSTANT –3.364 (–0.86) –0.759 (–0.33) OBS 52 80 R2 0.167 0.163 Table 5 presents the results of endogenous test between PCAOB inspections and accounting fraud likelihood. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. LONG is a dummy variable which equals 1 if the tenure of the auditor is above the median, and 0 otherwise. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised model for non-manufacturers and *** ** * emerging markets in Altman (2002). , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. 232 Zhang et al. Table 6. Comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011 in the IPO sample. Panel A: Distribution by year of merger for the IPO sample Non-fraudulent ﬁrms Fraudulent ﬁrms Year N N Percentage（%） N Percentage（%） 2000 4 4 100.00 0 0.00 2001 2 2 100.00 0 0.00 2002 1 1 100.00 0 0.00 2003 2 2 100.00 0 0.00 2004 8 8 100.00 0 0.00 2005 8 6 75.00 2 25.00 2006 10 10 100.00 0 0.00 2007 35 30 85.71 5 14.29 2008 6 6 100.00 0 0.00 2009 15 12 80.00 3 20.00 2010 43 39 90.70 4 9.30 Total 134 120 89.55 14 10.45 Panel B: A comparison of ﬁrm characteristics between fraud ﬁrms and non-fraud ﬁrms in the IPO sample Non-fraudulent ﬁrms Fraudulent ﬁrms （N=94）（N=4） Difference Variable Mean Median Mean Median Mean Median ACCESS 0.149 0.000 0.000 0.000 0.149 0.000 (0.41) (0.41) BIG4 0.840 0.000 1.000 0.000 –0.160 0.000 (0.39) (0.39) SIZE 15.684 11.996 15.361 4.081 0.322 7.915 (0.85) (0.88) AUQ 0.615 1.000 0.333 1.000 0.282 0.000 (0.33) (0.33) LEV 0.377 0.323 0.418 0.367 –0.042 –0.044 (0.72) (0.69) ROA 0.058 0.081 0.249 0.110 –0.191** –0.029 (0.04) (0.70) ZSCORE 3.288 3.680 4.583 4.754 –1.295 –1.074 (0.25) (0.38) Panel A presents an overview of the IPO sample distributed by year. Panel B reports the comparison of key ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in the IPO sample. Our IPO sample consists of all available Chinese ﬁrms listed in the US capital markets between 2000 and 2010 and their ﬁnancial information comes from Thomson Reuters Worldscope database. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised *** ** * model for non-manufacturers and emerging markets in Altman (2002). , , and represent statistical sig- niﬁcance levels of 1%, 5%, and 10%, respectively. of RMs. Panel B compares key ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ones in the IPO sample. The two groups do not differ signiﬁcantly in SIZE, LEV, AUQ,or ZSCORE. The mean values of BIG4 are 0.840 for non-fraudulent ﬁrms and 1.000 for fraudulent ones, suggesting that both groups tend to hire Big 4 accounting ﬁrms. Compared to the RM sample in Table 2, companies using IPO are China Journal of Accounting Studies 233 Table 7. The association between PCAOB inspections and accounting fraud likelihood in the IPO sample. 　 (1) (2) (3) Variables FRAUD FRAUD FRAUD ACCESS –0.005 0.149 0.059 (–0.34) (0.88) (1.15) RANK 0.065 (0.80) ACCESS *RANK –0.062 (–0.96) STAFF 0.000 (1.32) ACCESS *STAFF –0.000 (–0.26) BIG4 0.033 –0.009 0.007 (1.25) (–0.14) (0.22) SIZE 0.003 0.003 0.003 (0.45) (0.47) (0.35) AUQ –0.044 –0.044 –0.075 (–0.95) (–0.93) (–1.38) LEV –0.007 –0.004 0.050 (–0.09) (–0.05) (0.55) ROA –0.122 –0.123 0.053 (–0.72) (–0.72) (0.78) ZSCORE 0.006 0.006 –0.004 (0.76) (0.80) (–0.81) CONSTANT –0.021 –0.181 –0.040 (–0.25) (–0.73) (–0.37) OBS 88 88 75 R2 0.029 0.030 0.075 Table 7 presents the regression results for PCAOB inspections and accounting fraud likelihood in the IPO sample. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 3 when in top 4. STAFF is the staff number of auditor. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value *** ** computed using the revised model for non-manufacturers and emerging markets in Altman (2002). , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. usually big and tend to employ Big 4 accounting ﬁrms. The results of further analysis regarding the PCAOB inspection effect are presented in Table 7, from which we can see that the coefﬁcients of ACCESS in the three models are all insigniﬁcant. In other words, PCAOB inspections do not decrease fraud likelihood in the IPO sample. Even if we add in the auditor reputation factor, we do not ﬁnd a moderating effect of auditor reputation on clients of auditors. This may be because for companies going public through IPO, the reputation of a Big 4 auditor ensures audit quality, substituting for PCAOB inspections. 7. Conclusions and implications The Chinese RM ﬁrms accounting crisis has caused big losses to Chinese companies. Access to overseas capital markets has been almost cut off since the crisis. This paper tries to analyze the crisis from the auditing perspective and examine whether PCAOB 234 Zhang et al. inspections decrease accounting fraud likelihood and whether auditor reputation moderates this relationship. Using Chinese ﬁrms listed in the US through reverse merger during 2001–2011 as our sample, we ﬁnd that PCAOB inspections signiﬁcantly decrease accounting fraud likelihood for RM ﬁrms, and this relationship is more pronounced for auditors with low reputation. Besides, although PCAOB inspections decrease fraud likelihood in the RM sample, this relationship does not hold for Chinese initial public offering (IPO) ﬁrms listed in the US. The reason may be that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms, whose reputation substitutes for PCAOB inspections. Although we are limited by the available data, and the small size and low volatility of our IPO sample weaken the robustness of our conclusions to some extent, our results show that the crisis is due at least partly to ﬂaws in the audit process. Auditors with relatively poor reputations are not able to provide high audit quality and thus do not prevent ﬁnancial fraud. For those ﬁrms, PCAOB inspections provide effective supervision and help improve corporate governance. Our study has several implications for audit quality regulations in China. While regulators such as the MOF, CSRC or CICPA mainly focus on the audit of companies listed on the Shanghai Stock Exchange or Shenzhen Stock Exchange, the audit of other companies, which may be listed overseas, is somehow neglected. Since more and more ﬁrms in China are seeking to list overseas through IPOs or RMs, a well-established audit inspection system is needed to ensure audit quality and to protect the reputation of Chinese companies in global capital markets. Chinese regulators should intensify audit supervision of ﬁrms listing overseas and pay more attention to small accounting ﬁrms. In addition, our results prove the effectiveness of PCAOB inspections; the CICPA and other related authorities should learn from the PCAOB and improve the quality of audit inspections. Finally, Chinese regulators should strengthen cooperation with US regulators to build a better environment for global economic prosperity. Acknowledgements We greatly appreciate the comments and suggestions from the editors, Jason Xiao and Xi Wu, and an anonymous reviewer. We also beneﬁted a lot from the discussion of the participants at the First CJAS conference, and our discussant, Min Zhang. We acknowledge ﬁnancial support from National Natural Science Foundation of China (Approval Numbers 71273013, 70802003, and 71132004), the support from China Ministry of Education Social Science and Humanities Research Planning Foundation (Approval No. 12YJA630186), and from Guanghua Leadership Institute (Approval No. 12-14). Notes 1. On June 20, 2011, the SEC announced a list of Chinese companies under investigation. Among the 34 companies, 30 were listed in the US through reverse merger, while the other four had gone public through IPOs. 2. Typically, the existing shell is a relic from a previously failed business. 3. In China, RM ﬁrms are not publicly traded and they follow tax and auditing rules as private ﬁrms do. They need to ﬁll tax and ﬁnancial reports to the tax authority and the local Administration for Industry and Commerce (AIC). If they hire Chinese auditors, those auditors are also under the inspection of China audit authorities. 4. Many RMs are traded on Pink Sheet or OTCBB. If a company does an IPO, it is subject to reporting requirements only for one year. After that year, the company can cease reporting and the stock can continue to trade on Pink Sheet or OTCBB. The only requirement is that certain basic information be provided to brokerage ﬁrms making a market in the company’s stock. Thus, not all the Chinese RMs reported in 2011. China Journal of Accounting Studies 235 5. http://www.sec.gov/ 6. Our original list of fraudulent ﬁrms included 40 companies; we excluded 11 companies because they were not in the DealFlow Media’s (DFM’s) Reverse Merger Report, went public through IPO, or implemented the reverse merger before 2000. 7. 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Publisher: Taylor & Francis
Copyright: © 2013 Accounting Society of China
ISSN: 2169-7221
eISSN: 2169-7213
DOI: 10.1080/21697221.2013.857816
Publisher site: See Article on Publisher Site

Abstract

China Journal of Accounting Studies, 2013 Vol. 1, Nos. 3–4, 221–235, http://dx.doi.org/10.1080/21697221.2013.857816 PCAOB inspections, auditor reputation, and Chinese reverse merger frauds Ran Zhang*, Si Chen and Jianfeng Wang Guanghua School of Management, Peking University, People’s Republic of China This paper examines whether Public Accounting Oversight Board (PCAOB) inspections decrease fraud likelihood in the Chinese reverse merger ﬁrms’ accounting crisis and whether auditor reputation moderates this relationship. By analyzing Chinese ﬁrms listed in the US stock markets through reverse merger (RM) during 2001–2011, we ﬁnd that PCAOB inspections signiﬁcantly decrease accounting fraud likelihood for RM ﬁrms, especially for auditors with low reputation. But this relation- ship does not hold for Chinese initial public offering (IPO) ﬁrms listed in the US. The reason may be that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms, whose reputation substitutes for PCAOB inspections. Overall, our results indicate that PCAOB inspections help prevent ﬁnancial frauds, but only for ﬁrms hiring non-Big 4 auditors. Keywords: reverse merger; PCAOB inspections; auditor reputation; accounting fraud JEL Classiﬁcations: G34; L51; M41; M42; M49 1. Introduction The recent accounting crisis involving Chinese reverse merger ﬁrms has caused big losses to Chinese companies. In June 2010, Orient Paper Inc., a Chinese company listed in the US, was accused of ﬁnancial fraud by Muddy Waters Research, a short selling investment ﬁrm. The stocks of the company were heavily shorted and the company suffered a crisis with a sharply falling stock price. Other Chinese companies listed in the US, including Rino International Corp., Longtop Financial Technologies Limited, and China-Biotics Inc., experienced the same challenges soon afterwards. Investors and regulators became distrustful, the Securities and Exchange Commission (SEC) began to investigate the ﬁnancial disclosures of Chinese companies, and many Chinese ﬁrms listed in the US were either forced to halt trading or delisted owing to information disclosure problems. This crisis not only exposes the ﬂaws of some Chinese companies in the informa- tion disclosure process, but also raises concerns about reverse merger companies and their auditors. Reverse merger (RM) is a way to list overseas other than through initial public offering (IPO), and fraudulent ﬁrms involved in this crisis are mostly listed in the US through reverse mergers instead of IPOs. These ﬁrms either are not qualiﬁed to list through IPOs or cannot afford the large amount of money and time to implement IPOs and thus choose to acquire overseas listed companies, often called ‘shell’ *Corresponding author. Email: RZHANG@gsm.pku.edu.cn Paper accepted by Xi Wu. © 2013 Accounting Society of China 222 Zhang et al. companies, to achieve their goals instead. They are usually small, with relatively high ﬁnancial and operational risk, and tend to hire small accounting ﬁrms, most of which are based in China. Since auditing is important to ensure the reliability of information disclosed and to protect investors, the SEC blamed these auditing ﬁrms for the ﬁnancial scandals. The PCAOB suspended the registration of accounting ﬁrms from China in October 2010. In December 2012, the SEC charged the China branches of top accounting ﬁrms with securities violations, saying that their refusal to hand over audit working papers has hindered investigations into frauds at US-listed Chinese ﬁrms. One of the SEC’s strongest criticisms is that auditing ﬁrms based in China deny PCAOB inspections, on the grounds that these inspections constitute an intervention by the US government. The PCAOB is a nonproﬁt corporation established by Congress to oversee the audits of public companies in order to regulate the accounting service industry and to protect the interests of investors. According to the Sarbanes-Oxley Act, any auditor of a company listed in the US – whether a US auditor or a non-US auditor – must be registered with, and therefore subject to the jurisdiction of, the PCAOB. The PCAOB inspects registered accounting ﬁrms and prepares a written report on each inspection identifying deﬁciencies to help enhance audit quality. But in reality, because of the position taken by certain non-US authorities, the PCAOB currently is prevented from inspecting the US-related audit work and practices of PCAOB-registered ﬁrms in some countries such as China and certain European countries. China’s government prohibits PCAOB inspections because Chinese domestic law regards certain information as state secrets and does not permit access by foreign regulatory bodies to detailed documents such as audit work papers. The SEC and PCAOB believe that PCAOB inspections are sufﬁcient to ensure audit quality and that denial of inspection brings unknown risk to the capital market, but it remains an unresolved empirical question whether PCAOB inspections enhance audit quality in practice. Do accounting ﬁrms to which the PCAOB is denied inspection access have worse audit quality and higher audit risk than those inspected? Do PCAOB inspections help lower the risk of ﬁnancial scandals? The recent accounting crisis at Chinese reverse merger ﬁrms provides a unique opportunity to examine these questions. Among the auditors working for Chinese reverse merger companies, US-based auditors are inspected by the PCAOB while China-based ones are not. In addition, the exposure of fraudulent ﬁrms helps us identify risk and thus indicates audit failure. Auditor reputation is another mechanism to lower the risk of accounting frauds. Studies have found that big accounting ﬁrms tend to have higher audit quality. For example, Lennox (1999) ﬁnds that Big 6 auditors report with greater accuracy in the United Kingdom, and Francis and Krishan (1999) show that Big 6 auditors are more likely to issue modiﬁed audit reports, indicating greater reporting conservatism for a given set of client characteristics. If PCAOB inspections enhance audit quality and decrease the likelihood of ﬁnancial fraud, will auditor reputation moderate this relationship? This is also an interesting and unresolved question. We examine whether PCAOB inspections decrease the likelihood of accounting fraud, particularly for ﬁrms involved in the recent Chinese crisis, and whether auditor reputation moderates this relationship. Our results show that (1) in the RM sample, PCAOB inspections signiﬁcantly decrease fraud likelihood, especially for auditors with low reputation; and (2) compared with the RM sample, PCAOB inspections don’t decrease fraud likelihood for Chinese ﬁrms listed in the US via IPOs. A possible reason is that IPO ﬁrms tend to hire Big 4 accounting ﬁrms, and these ﬁrms’ care for their reputation ensures their audit quality, which substitutes for PCAOB inspections. China Journal of Accounting Studies 223 Our study not only extends the existing literature on reverse mergers but also has practical implications for audit quality regulation. First, we contribute to the growing literature about RMs, especially Chinese RMs. While previous research argues that RM ﬁrms are highly risky, we show that the risk is partly due to the auditors and is reduced by PCAOB inspections. Second, although previous studies have compared RM companies with IPO companies, only a few focus on the auditing perspective. Our study demonstrates that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms while only 6.02% of RM ﬁrms do so. This difference results in an audit quality gap. We conclude that PCAOB inspections are effective, and we suggest that Chinese regulators should extend cooperation with the PCAOB. 2. Background and case study 2.1. Background In China, accounting ﬁrms are regulated in a multifaceted way. There are several regulators, including the Ministry of Finance (MOF), the China Securities Regulatory Commission (CSRC), and the Chinese Institute of Certiﬁed Public Accountants (CICPA). All these authorities conduct inspections. Founded in November 1988, the CICPA is a special industrial self-regulatory organization under the guidance of the Ministry of Finance. It conducts inspections on practice quality of accounting ﬁrms every year, usually from June to July. Under the ‘Rules for Practice Quality Inspection of Accounting Firms,’ ﬁrms with securities qualiﬁcations must be inspected at least once every 3 years, while other accounting ﬁrms must be inspected at least once every 5 years. The inspections focus on compliance with business norms, quality control norms, code of professional ethics, and so on. And the CICPA takes disciplinary actions against ﬁrms found to have committed practice violations. MOF and CSRC inspections are similar, but are carried on by provincial bodies of the MOF and CSRC respectively. The responsibilities of three authorities thus overlap, resulting in an ineffective regulation as a whole. While the audit control system in China is comprehensive and multifaceted, in the US inspecting accounting ﬁrms is the duty of just one organization, namely the PCAOB. However, as we outline above, China does not permit PCAOB inspections, a major rift in China–US auditing regulation cooperation. If the SEC wins its current court case, Chinese accounting ﬁrms may be disqualiﬁed to audit in the US, and related Chinese companies will be forced to delist because they can’t meet the US requirements for information disclosure. This will be harmful to both China and the US. To solve this problem, China and the US are negotiating: in July 2011, PCAOB and SEC ofﬁcials arrived in Beijing and talked with the CSRC and the MOF. In July 2012, Mary L. Schapiro, former SEC president, visited China, and China and the US agreed that PCAOB investigators could observe the inspections and evaluations of Chinese accounting ﬁrms by the CSRC and the MOF. On May 7, 2013, the CSRC and the MOF entered into a memorandum of understanding with the PCAOB, and auditing cross-border enforcement cooperation between China and the US thus began. According to the memorandum of understanding, the PCAOB can request related audit documents from the CSRC and the MOF when investigating Chinese accounting ﬁrms that are registered with the PCAOB. This memorandum will lay a foundation for future cooperation. 224 Zhang et al. 2.2. Case study To help understand the effect of PCAOB inspections, consider one company, Universal Travel Group (OTC: UTRA), a travel service provider based in Shenzhen, China. In June 2006, it was listed in the US through reverse merger. In 2011, a short-seller, Glaucus Research Group, issued a report alleging that Universal Travel was fabricating its ﬁnancial statements ﬁled with the SEC, and that its underlying business was smaller than it reported in its SEC ﬁlings. Subsequently, on March 29, 2011, Universal Travel announced that it would postpone its earnings announcement for the ﬁscal year ending December 31, 2010. On April 12, 2011, the trading of Universal Travel’s stock was halted, and the company ﬁnally delisted from NYSE in April 2012. The company’s auditor is an accounting ﬁrm called Acquavella, Chiarelli, Shuster, Berkower & Co, LLP. It is based in New Jersey, and has seven partners, two ofﬁces, 32 professional staff, and 12 clients in 2010. This accounting ﬁrm is registered with the PCAOB and accepts its periodic inspections. In the 2010 inspection report, the PCAOB identiﬁed seven deﬁciencies in the three audits reviewed: (1) failure to perform sufﬁcient audit procedures to evaluate whether goodwill was impaired; (2) failure to perform sufﬁcient audit procedures to evaluate the accounting for a transfer of buildings and related land use rights; (3) failure to perform sufﬁcient audit procedures to test revenue; (4) failure to perform sufﬁcient audit procedures to test accounts receivable; (5) failure to perform sufﬁcient audit procedures regarding warrants; (6) failure to perform sufﬁcient audit procedures to test the valuation of stock-based compensation; and (7) failure to evaluate the effect of reported material weaknesses on the nature, timing, and extent of substantive procedures performed in the audit of the ﬁnancial statements. We can see from this case that the PCAOB effectively identiﬁes deﬁciencies in auditing and discloses the audit quality to the client companies as well as the whole market. On one hand, this helps accounting ﬁrms improve their audit process and achieve better audit quality; on the other hand, it provides relevant information to investors and helps them identify and control risk. 3. Literature review 3.1. Reverse merger Recently, as more companies have gone public through reverse merger, reverse merger has attracted much attention. Studies have addressed both the supply and the demand side of the market for reverse merger. On the supply side, there is a ‘shell’ market for reverse mergers. These shells are either established specially for merger without any operating history or substantial business, or are relics from previously failed businesses. Gleason, Rosenthal, and Wiggins (2005) examine 121 reverse mergers and ﬁnd that shell shareholders receive signiﬁcant wealth gains upon announcement of a reverse merger. Floros and Sapp (2011) reach a similar conclusion: when a takeover agreement is consummated, the shell company’s three-month abnormal returns are as high as 48.1%, which can be seen China Journal of Accounting Studies 225 as compensation to investors for shell stock illiquidity and the uncertainty of ﬁnding a reverse merger suitor. On the demand side, studies have largely focused on the motivation for using a reverse merger rather than an IPO. For example, Brau, Francis, and Kohers (2003) examine factors that inﬂuence the choice between IPO and reverse merger and show that industry concentration, high-tech industry afﬁliation, current cost of debt, relative ‘hotness’ of the IPO market, ﬁrm size, and insider ownership percentage are all related to this choice. Poulsen and Stegemoller (2008) show that ﬁrms that have fewer growth opportunities and face less capital constraint tend to go public through reverse merger. In the same spirit, Adjei, Cyree, and Walker (2008) suggest that RM ﬁrms are typically smaller and younger, with poorer ex ante performance. Within 3 years of listing, 42% of the reverse merger companies are delisted compared with 27% of matched IPOs. 3.2. PCAOB inspections and auditor reputation The Sarbanes-Oxley Act requires the PCAOB to conduct inspections annually of ﬁrms that regularly audit more than 100 issuers, and at least triennially of ﬁrms that regularly audit 100 or fewer issuers. The PCAOB prepares a written report on each inspection to identify the deﬁciencies in the auditing work. Researchers have drawn different conclusions about the effect of PCAOB inspections. Some maintain that PCAOB inspections do help auditors enhance audit quality and companies and investors value the information of inspections reports when they make decisions. For example, Gramling, Krishnan, and Zhang (2009) ﬁnd that reports of deﬁciencies for ﬁrms inspected triennially signal undetected or underreported going-concern problems. Abbott, Gunny, and Zhang (2011) show that registrants with high potential agency conﬂicts or effective audit committees have incentives to switch away from auditors that have received an adverse, GAAP-deﬁcient PCAOB inspection report. Others hold opposite opinions. Daugherty and Tervo (2010) argue that PCAOB inspections are useful for rebuilding investors’ conﬁdence, but do not enhance audit quality substan- tially. Lennox and Pittman (2010a) ﬁnd that audit clients do not perceive that PCAOB inspection reports are valuable for signaling audit quality, and audit ﬁrms’ market shares are insensitive to their PCAOB reports. The famous ‘Lemon Market’ theory by Akerlof (1970) has shown that reputation is a signal mechanism. Auditor reputation, as an important signal to measure audit quality, will signiﬁcantly affect the client ﬁrm’s stock price, information disclosure, and audit fees. Balvers, McDonald, and Miller (1988) and Beatty (1989) show that clients that hire more reputable accounting ﬁrms are less likely to be underpriced than clients that hire less reputable ones. Clarkson, Ferguson, and Hall (2003) ﬁnd that Big 6 auditors’ clients disclose more year 2000 remediation information in their annual reports than non-Big 6 auditor clients, which indicates that the Big 6 act more conservatively to protect their reputation. 4. Hypothesis development During the accounting crisis of China, auditing ﬁrms working for the reverse merger companies were widely criticized. Since some of these accounting ﬁrms were located in the US and thus were inspected by the PCAOB while others weren’t, we wonder whether PCAOB inspections decrease accounting fraud likelihood in practice. As mentioned above, prior literature provides mixed results on the effect of PCAOB 226 Zhang et al. inspections. Some studies document that the inspections help auditors enhance audit quality and disclose information regarding auditors and clients to the market (Abbott et al., 2011; Gramling et al., 2009), while others hold that the inspections don’t have a substantial effect and are not recognized by the market (Daugherty & Tervo, 2010; Lennox & Pittman, 2010a). Among all the auditors providing service for Chinese RMs, some received PCAOB inspections while others were denied. If PCAOB inspections enhance audit quality, we expect to see a signiﬁcantly lower likelihood of accounting fraud for those clients whose auditors received PCAOB inspections. We propose the following hypothesis to study the ﬁrst question: Hypothesis 1(a): PCAOB inspections signiﬁcantly enhance audit quality and thus decrease the likelihood of accounting fraud. Hypothesis 1(b): PCAOB inspections neither signiﬁcantly enhance audit quality nor decrease the likelihood of accounting fraud. According to reputation theory, clients will punish auditors by dismissing the auditor or reducing the audit fee if the auditor provides a poor audit. This mechanism will urge the auditor to keep improving audit quality to avoid the losses from damaged reputation. Since auditors with better reputation have more incentives to avoid risk and damage to reputation, they may provide better audits and better supervise listed companies. From this perspective, auditor reputation may moderate the relationship between PCAOB inspections and the likelihood of accounting fraud: Hypothesis 2: Auditor reputation moderates the relationship between PCAOB inspections and the likelihood of accounting fraud, and this relationship is more pronounced for auditors with low reputation. 5. Sample and data We obtained all the reverse merger events from DealFlow Media’s (DFM’s) Reverse Merger Report database. The original sample included 1799 RMs that became active on US stock markets between January 2000 and December 2011. Of the 1799 events, 428 were reverse mergers whose private ﬁrms were based in China. For each Chinese RM, we sought ﬁnancial information from the latest ﬁnancial report in the Worldscope database. Among the 428 Chinese RMs, 168 had such reports, including 83 in 2011. In addition, we hand-collected the fraudulent ﬁrm list from the Securities and Exchange Commission (SEC) website and the media to obtain 29 fraudulent ﬁrms out of the 428 Chinese RMs. Table 1 provides an overview of the RMs in our sample, distributed by year of merger. Table 1 shows that Chinese RMs increased signiﬁcantly after 2001, peaking at 36 in 2006 and falling slightly in 2007 and 2008. The decline was exacerbated by the fraud crisis. In 2011, only ﬁve Chinese companies listed in the US through reverse merger, and overseas listing hit bottom. Correspondingly, fraud mostly happened in 2006–2008, as reverse mergers were exploding and fraudulent ﬁrms mixed into the capital markets with good ones. The auditor information for the sample companies came from the SEC website. We hand-collected the 2011 ﬁnancial reports of all the companies and searched for the signature of the auditor by using the keywords ‘Report of Independent Registered Public Accounting Firm.’ China Journal of Accounting Studies 227 Table 1. Distribution by year of merger for reverse mergers. Non-fraudulent ﬁrms Fraudulent ﬁrms Year No. of RMs N Percentage（%） N Percentage（%） 2001 1 1 100.00 0 0.00 2002 0 0 0.00 0 0.00 2003 6 6 100.00 0 0.00 2004 15 13 86.67 2 13.33 2005 20 18 90.00 2 10.00 2006 36 29 80.56 7 19.44 2007 31 22 70.93 9 29.03 2008 29 24 82.76 5 17.24 2009 12 10 83.33 2 16.67 2010 13 11 84.62 2 15.38 2011 5 5 100.00 0 0.00 Total 168 139 82.74 29 17.26 This table presents an overview of the RMs in our sample, distributed by year of merger. Our sample includes all the reverse merger events from 2000 to 2011 in DealFlow Media’s (DFM’s) Reverse Merger Report data- base and we hand-collected the fraudulent ﬁrm list from the Securities and Exchange Commission (SEC) website and the media. Since accounting ﬁrms in countries that prohibit PCAOB inspections may have unknown risk, the PCAOB publishes and regularly updates a list identifying each ﬁrm whose PCAOB-registered auditor is located in such countries. We matched auditing ﬁrms in our sample with the list to determine whether an auditing ﬁrm was inspected by the PCAOB. If yes, then a variable ACCESS is coded 1, and 0 otherwise. For those that were inspected (ACCESS=1), we obtained their PCAOB inspection reports from the PCAOB website, from which we collected auditor’s information including number of ofﬁces (OFFICE), number of staff members (STAFF), and number of clients (CLIENT). For those ﬁrms that denied inspection (ACCESS=0), we collected the auditor’s information from the Chinese Institute of Certiﬁed Public Accountants Information System as well as the China Stock Market & Accounting Research Database (CSMAR). We used the Global Accounting Firm Top 100 to determine the rank of the auditor (RANK), and hand-collected the auditor’s tenure with a client (TENURE) from the client’s annual reports. 6. Empirical method and results 6.1. Model speciﬁcation First we compare fraudulent ﬁrms to non-fraudulent ﬁrms in size, leverage, ROA, audi- tor opinion, and ﬁnancial condition. After that we focus on the auditor characteristics in univariate tests to see whether there is a difference. We then use regression models to test Hypothesis 1 and Hypothesis 2, extending our research to the IPO sample for comparison. The regression models to be estimated are FRAUD ¼ a þ a ACCESS þ a SIZE þ a LEV þ a ROA þ a AUQ þ a ZSCORE þ e 0 1 2 3 4 5 6 (1) FRAUD ¼ a þ a ACCESS þ a Auditorreputatation þ a ACCESS Auditorreputatation 0 1 2 3 þ a SIZE þ a LEV þ a ROA þ a AUQ þ a ZSCORE þ e ð2Þ 4 5 6 7 8 228 Zhang et al. where FRAUD = 1 if the reverse merger company is a fraudulent ﬁrm exposed in the crisis, and 0 otherwise; ACCESS = 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise; SIZE = the natural log of total assets; LEV = the ratio of total debt to total assets; ROA = income before extraordinary items divided by total assets; AUQ = 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise; ZSCORE = Z value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). Auditor reputation is measured by four proxies, including RANK, OFFICE, STAFF, and CLIENT. 6.2. Empirical results 6.2.1. Comparison of ﬁrm characteristics between fraudulent and non-fraudulent ﬁrms Table 2 compares ﬁrm characteristics between fraudulent and non-fraudulent ﬁrms. Fraudulent and non-fraudulent ﬁrms are similar in size. The mean SIZE of non-fraudu- lent ﬁrms is 3.301, while the mean SIZE of fraudulent ones is 3.748; the difference is not statistically signiﬁcant (p-value = 0.33). Mean leverage, measured as the sum of short-term and long-term debts divided by total assets, is 0.679 for non-fraudulent ﬁrms and 0.385 for fraudulent ones; again, the difference is not statistically signiﬁcant (p-value = 0.72). We use ROA and ZSCORE to measure ﬁrms’ proﬁtability and ﬁnancial condition, and AUQ to measure audit opinions. None of these variables appears to differ signiﬁcantly across the two groups. In a word, non-fraudulent ﬁrms and fraudulent ones are similar in general characteristics. Table 2. Comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. Non-fraudulent ﬁrms Fraudulent ﬁrms (N=73) (N=10) Difference Variable Mean Median Mean Median Mean Median SIZE 3.301 3.541 3.748 3.567 –0.447 –0.026 　　　　　 (0.33) (0.56) AUQ 0.767 1.000 0.800 1.000 –0.033 0.000 　　　　　 (0.82) (0.82) LEV 0.679 0.415 0.385 0.367 0.293 0.047 　　　　　 (0.72) (0.96) ROA –0.173 0.116 0.129 0.110 –0.303 0.006 　　　　　 (0.62) (0.99) ZSCORE 2.268 5.313 7.039 5.154 –4.772 0.159 　　　　　 (0.77) (0.98) Table 2 presents the comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). p-values are in parentheses. ***, **, and * represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. China Journal of Accounting Studies 229 6.2.2. Comparison of auditor characteristics between fraudulent and non-fraudulent ﬁrms Table 3 presents univariate evidence on auditor characteristics for ﬁrms in 2011. We use four proxies to measure auditor reputation: RANK, OFFICE, STAFF, and CLIENT. The mean RANK of non-fraudulent ﬁrms is 0.753, while that of fraudulent ones is 1.400. The difference is statistically signiﬁcant (p-value = 0.04), suggesting that fraudu- lent ﬁrms hire auditors with higher reputation. We get similar results using STAFF and CLIENT, while the difference in OFFICE is not statistically signiﬁcant. Table 3 also shows that the mean ACCESS is 0.932 for non-fraudulent ﬁrms and only 0.600 for fraudulent ones, indicating that fraudulent ﬁrms’ auditors are substantially less likely to have been inspected by the PCAOB. There are two possible explanations for this. One is that PCAOB inspections enhance audit quality, so that the clients of inspected auditors are less prone to become fraudulent. The second is that fraudulent ﬁrms prefer auditors not inspected by the PCAOB to avoid being detected (a self-selection effect). Our hypothesis is consistent with the ﬁrst explanation, which we examine through regression models. And we rule out the second explanation below. 6.2.3. PCAOB inspections and accounting fraud likelihood in the RM sample The univariate tests above indicate that ﬁrms employing auditors inspected by the PCAOB are less prone to ﬁnancial fraud. We examine this relationship further using regression models. The results are presented in Table 4. We can see that in model (1) of Table 4, the regression coefﬁcient is –2.314, and is signiﬁcant at the 1% level, which indicates that ﬁrms whose auditors were inspected by the PCAOB suffer less risk of ﬁnancial fraud. This ﬁnding supports Hypothesis 1(a). To further examine the moderat- ing effect of auditor reputation, we build model (2) by adding the variable RANK as well as an interaction term RANK*ACCESS. The coefﬁcient of the interaction term is signiﬁcantly positive, indicating that the relationship between PCAOB inspections and Table 3. Comparison of auditor characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms. Non-fraudulent ﬁrms Fraudulent ﬁrms (N=73) (N=10) Difference Variable Mean Median Mean Median Mean Median ** * RANK　 0.753 　 1.000 　 1.400 　 2.000 　 –0.647 (0.04) –1.000 (0.06) OFFICE　 5.311　 2.000 　 9.875 　 2.000 　 –4.564 (0.30) 0.000 (0.65) *** ** STAFF　 203.017 　 47.000 　 593.000 　 61.000　 –389.983 (0.00) –14.000 (0.02) *** ** CLIENT　 34.177 　 24.000 　 105.375 　 33.000 　 –71.198 (0.00) –9.000 (0.02) *** *** ACCESS　 0.932 　 1.000 　 0.600 　 1.000 　 0.332 (0.00) 0.000 (0.00) BIG4 0.055 0.000 0.100 0.000 –0.045(0.58) 0.000(0.58) TENURE 2.342 2.000 2.100 2.000 0.242(0.66) 0.000(0.94) Table 3 presents the comparison of auditor characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 3 when in top 4. OFFICE is the ofﬁce number of auditor in total. STAFF is the staff number of auditor. CLIENT is the number of clients of the auditor. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. TENURE is the auditor’s tenure of a *** ** * client. p-values are in parentheses. , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. 230 Zhang et al. Table 4. The relationship between PCAOB inspections and accounting fraud likelihood in the reverse merger sample. 　 (1) (2) (3) Variables FRAUD FRAUD FRAUD *** ** *** ACCESS –2.314 –9.428 –4.337 (–2.71) (–2.53) (–3.77) RANK –2.709 (–1.85) RANK*ACCESS 2.910 (1.84) *** STAFF –0.001 (–3.28) STAFF *ACCESS 0.000 (0.00) SIZE 0.164 0.205 0.093 (0.36) (0.50) (0.50) AUQ –0.116 –0.303 –0.284 (–0.10) (–0.31) (–0.51) LEV –0.706 –0.869 –0.590 (–0.28) (–0.34) (–0.42) ** *** ROA 1.164 3.507 1.838 (1.45) (2.44) (3.32) ZSCORE –0.049 –0.112 –0.063 (–0.72) (–1.52) (–1.42) ** *** CONSTANT –0.048 7.027 3.445 (–0.02) (2.30) (2.91) OBS 80 80 65 R2 0.146 0.193 0.218 Table 4 presents the regression results for PCAOB inspections and accounting fraud likelihood. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 4 when in top 4. STAFF is the staff number of auditor. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z *** value computed using the revised model for non-manufacturers and emerging markets in Altman (2002). , ** * , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. the likelihood of accounting fraud is more pronounced for auditors with low reputation. As a robustness test, we also use the number of staff (STAFF) as the proxy of auditor reputation and get similar results. In sum, the regression results of models (2) and (3) support Hypothesis 2. A potential concern with our ﬁndings is that there may be a self-selection bias stemming from two possible situations: the inspected audit ﬁrms may refuse to audit companies with a high propensity to engage in ﬁnancial fraud; or fraudulent ﬁrms may choose auditors that were not inspected by PCAOB to avoid being detected. If this self-selection bias does exist, it should be more severe when audit ﬁrm tenure is short. For example, suppose two companies commit accounting frauds in 2011 and are audited by the same uninspected ﬁrm. Company A initially hired this auditor in 2001, whereas company B switched to this auditor in 2010, either because its previous auditor resigned or because company B dismissed the previous auditor. In either situation, since the auditor choice decision of company B just occurred shortly before it began to perpetrate accounting fraud, the incentive is more questionable. On the other hand, since auditor tenure is relatively long for company A, it is less likely for China Journal of Accounting Studies 231 company A to choose the auditor to avoid being detected. Thus, we perceive that self-selection bias is more severe for company B than company A. We build model (3), following Lennox and Pittman (2010b), to check whether the association between accounting fraud and PCAOB inspections is weaker in a long-tenure sample owing to the self-selection bias. FRAUD ¼ a þ a ACCESS þ a LONG þ a ACCESS LONG þ a SIZE þ a LEV 0 1 2 3 4 5 þ a ROA þ a AUQ þ a ZSCORE þ e ð3Þ 6 7 8 where LONG is a dummy variable that equals 1 if the tenure of the auditor is above the median and 0 otherwise. The median of LONG is 2. The regression results for model (3) are presented in Table 5. Model (1) of Table 5 shows the relationship between accounting fraud likelihood and PCAOB inspections under the shorter tenure condition. The coefﬁcient of ACCESS is –1.859 and is statistically signiﬁcant at the 10% level, which again supports Hypothesis 1(a). We extend the model to model (2) of Table 5 to see whether there’sa self-selection problem. If there is self-selection bias in our sample, the interaction term LONG*ACCESS in model (3) will be signiﬁcantly positive. However, the results show that the coefﬁcient of ACCESS is still signiﬁcantly negative, while the coefﬁcient of the interaction term LONG*ACCESS is insigniﬁcant. That is to say, the self-selection problem is not severe in our sample and thus does not affect our conclusions. 6.2.4. PCAOB inspections and accounting fraud likelihood in the IPO sample Does the relationship between PCAOB inspections and accounting fraud likelihood in the RM sample hold for the IPO sample? Table 6 provides an overview of the IPO sample. Panel A presents the distribution by year, which is quite similar to that of RMs. But obviously the accounting fraud likelihood of IPOs is much lower than that Table 5. Endogenous test between PCAOB inspections and accounting fraud likelihood. 　 (1) (2) FRAUD FRAUD Variables COEF Z COEF Z * ** ACCESS –1.859 (–1.93) –1.945 (–2.00) LONG 2.759 (1.61) LONG*ACCESS –2.924 (–1.45) SIZE 0.632 (0.73) 0.212 (0.46) AUQ 0.702 (0.64) –0.288 (–0.26) LEV 0.315 (0.15) –0.247 (–0.10) ** ROA 1.331 (0.57) 1.720 (2.16) ZSCORE –0.039 (–0.43) –0.034 (–0.50) CONSTANT –3.364 (–0.86) –0.759 (–0.33) OBS 52 80 R2 0.167 0.163 Table 5 presents the results of endogenous test between PCAOB inspections and accounting fraud likelihood. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. LONG is a dummy variable which equals 1 if the tenure of the auditor is above the median, and 0 otherwise. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised model for non-manufacturers and *** ** * emerging markets in Altman (2002). , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. 232 Zhang et al. Table 6. Comparison of ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in 2011 in the IPO sample. Panel A: Distribution by year of merger for the IPO sample Non-fraudulent ﬁrms Fraudulent ﬁrms Year N N Percentage（%） N Percentage（%） 2000 4 4 100.00 0 0.00 2001 2 2 100.00 0 0.00 2002 1 1 100.00 0 0.00 2003 2 2 100.00 0 0.00 2004 8 8 100.00 0 0.00 2005 8 6 75.00 2 25.00 2006 10 10 100.00 0 0.00 2007 35 30 85.71 5 14.29 2008 6 6 100.00 0 0.00 2009 15 12 80.00 3 20.00 2010 43 39 90.70 4 9.30 Total 134 120 89.55 14 10.45 Panel B: A comparison of ﬁrm characteristics between fraud ﬁrms and non-fraud ﬁrms in the IPO sample Non-fraudulent ﬁrms Fraudulent ﬁrms （N=94）（N=4） Difference Variable Mean Median Mean Median Mean Median ACCESS 0.149 0.000 0.000 0.000 0.149 0.000 (0.41) (0.41) BIG4 0.840 0.000 1.000 0.000 –0.160 0.000 (0.39) (0.39) SIZE 15.684 11.996 15.361 4.081 0.322 7.915 (0.85) (0.88) AUQ 0.615 1.000 0.333 1.000 0.282 0.000 (0.33) (0.33) LEV 0.377 0.323 0.418 0.367 –0.042 –0.044 (0.72) (0.69) ROA 0.058 0.081 0.249 0.110 –0.191** –0.029 (0.04) (0.70) ZSCORE 3.288 3.680 4.583 4.754 –1.295 –1.074 (0.25) (0.38) Panel A presents an overview of the IPO sample distributed by year. Panel B reports the comparison of key ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ﬁrms in the IPO sample. Our IPO sample consists of all available Chinese ﬁrms listed in the US capital markets between 2000 and 2010 and their ﬁnancial information comes from Thomson Reuters Worldscope database. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value computed using the revised *** ** * model for non-manufacturers and emerging markets in Altman (2002). , , and represent statistical sig- niﬁcance levels of 1%, 5%, and 10%, respectively. of RMs. Panel B compares key ﬁrm characteristics between fraudulent ﬁrms and non-fraudulent ones in the IPO sample. The two groups do not differ signiﬁcantly in SIZE, LEV, AUQ,or ZSCORE. The mean values of BIG4 are 0.840 for non-fraudulent ﬁrms and 1.000 for fraudulent ones, suggesting that both groups tend to hire Big 4 accounting ﬁrms. Compared to the RM sample in Table 2, companies using IPO are China Journal of Accounting Studies 233 Table 7. The association between PCAOB inspections and accounting fraud likelihood in the IPO sample. 　 (1) (2) (3) Variables FRAUD FRAUD FRAUD ACCESS –0.005 0.149 0.059 (–0.34) (0.88) (1.15) RANK 0.065 (0.80) ACCESS *RANK –0.062 (–0.96) STAFF 0.000 (1.32) ACCESS *STAFF –0.000 (–0.26) BIG4 0.033 –0.009 0.007 (1.25) (–0.14) (0.22) SIZE 0.003 0.003 0.003 (0.45) (0.47) (0.35) AUQ –0.044 –0.044 –0.075 (–0.95) (–0.93) (–1.38) LEV –0.007 –0.004 0.050 (–0.09) (–0.05) (0.55) ROA –0.122 –0.123 0.053 (–0.72) (–0.72) (0.78) ZSCORE 0.006 0.006 –0.004 (0.76) (0.80) (–0.81) CONSTANT –0.021 –0.181 –0.040 (–0.25) (–0.73) (–0.37) OBS 88 88 75 R2 0.029 0.030 0.075 Table 7 presents the regression results for PCAOB inspections and accounting fraud likelihood in the IPO sample. ACCESS is a dummy variable that equals 1 if the company’s auditor was inspected by the PCAOB, and 0 otherwise. BIG4 is a dummy variable that equals 1 if the auditor is Big 4, and 0 otherwise. RANK is the rank of auditor on the Global Accounting Firm Top 100, and is 0 when behind 100, 1 when in top 100, 2 when in top 10, and 3 when in top 4. STAFF is the staff number of auditor. SIZE is the natural log of total assets. AUQ equals 0 if the auditor gives a modiﬁed audit opinion, and 1 otherwise. LEV is the ratio of total debt to total assets. ROA is income before extraordinary items divided by total assets. ZSCORE is Z value *** ** computed using the revised model for non-manufacturers and emerging markets in Altman (2002). , , and represent statistical signiﬁcance levels of 1%, 5%, and 10%, respectively. usually big and tend to employ Big 4 accounting ﬁrms. The results of further analysis regarding the PCAOB inspection effect are presented in Table 7, from which we can see that the coefﬁcients of ACCESS in the three models are all insigniﬁcant. In other words, PCAOB inspections do not decrease fraud likelihood in the IPO sample. Even if we add in the auditor reputation factor, we do not ﬁnd a moderating effect of auditor reputation on clients of auditors. This may be because for companies going public through IPO, the reputation of a Big 4 auditor ensures audit quality, substituting for PCAOB inspections. 7. Conclusions and implications The Chinese RM ﬁrms accounting crisis has caused big losses to Chinese companies. Access to overseas capital markets has been almost cut off since the crisis. This paper tries to analyze the crisis from the auditing perspective and examine whether PCAOB 234 Zhang et al. inspections decrease accounting fraud likelihood and whether auditor reputation moderates this relationship. Using Chinese ﬁrms listed in the US through reverse merger during 2001–2011 as our sample, we ﬁnd that PCAOB inspections signiﬁcantly decrease accounting fraud likelihood for RM ﬁrms, and this relationship is more pronounced for auditors with low reputation. Besides, although PCAOB inspections decrease fraud likelihood in the RM sample, this relationship does not hold for Chinese initial public offering (IPO) ﬁrms listed in the US. The reason may be that 84.68% of IPO ﬁrms hire Big 4 accounting ﬁrms, whose reputation substitutes for PCAOB inspections. Although we are limited by the available data, and the small size and low volatility of our IPO sample weaken the robustness of our conclusions to some extent, our results show that the crisis is due at least partly to ﬂaws in the audit process. Auditors with relatively poor reputations are not able to provide high audit quality and thus do not prevent ﬁnancial fraud. For those ﬁrms, PCAOB inspections provide effective supervision and help improve corporate governance. Our study has several implications for audit quality regulations in China. While regulators such as the MOF, CSRC or CICPA mainly focus on the audit of companies listed on the Shanghai Stock Exchange or Shenzhen Stock Exchange, the audit of other companies, which may be listed overseas, is somehow neglected. Since more and more ﬁrms in China are seeking to list overseas through IPOs or RMs, a well-established audit inspection system is needed to ensure audit quality and to protect the reputation of Chinese companies in global capital markets. Chinese regulators should intensify audit supervision of ﬁrms listing overseas and pay more attention to small accounting ﬁrms. In addition, our results prove the effectiveness of PCAOB inspections; the CICPA and other related authorities should learn from the PCAOB and improve the quality of audit inspections. Finally, Chinese regulators should strengthen cooperation with US regulators to build a better environment for global economic prosperity. Acknowledgements We greatly appreciate the comments and suggestions from the editors, Jason Xiao and Xi Wu, and an anonymous reviewer. We also beneﬁted a lot from the discussion of the participants at the First CJAS conference, and our discussant, Min Zhang. We acknowledge ﬁnancial support from National Natural Science Foundation of China (Approval Numbers 71273013, 70802003, and 71132004), the support from China Ministry of Education Social Science and Humanities Research Planning Foundation (Approval No. 12YJA630186), and from Guanghua Leadership Institute (Approval No. 12-14). Notes 1. On June 20, 2011, the SEC announced a list of Chinese companies under investigation. Among the 34 companies, 30 were listed in the US through reverse merger, while the other four had gone public through IPOs. 2. Typically, the existing shell is a relic from a previously failed business. 3. In China, RM ﬁrms are not publicly traded and they follow tax and auditing rules as private ﬁrms do. They need to ﬁll tax and ﬁnancial reports to the tax authority and the local Administration for Industry and Commerce (AIC). If they hire Chinese auditors, those auditors are also under the inspection of China audit authorities. 4. Many RMs are traded on Pink Sheet or OTCBB. If a company does an IPO, it is subject to reporting requirements only for one year. After that year, the company can cease reporting and the stock can continue to trade on Pink Sheet or OTCBB. The only requirement is that certain basic information be provided to brokerage ﬁrms making a market in the company’s stock. Thus, not all the Chinese RMs reported in 2011. China Journal of Accounting Studies 235 5. http://www.sec.gov/ 6. Our original list of fraudulent ﬁrms included 40 companies; we excluded 11 companies because they were not in the DealFlow Media’s (DFM’s) Reverse Merger Report, went public through IPO, or implemented the reverse merger before 2000. 7. After the eruption of the crisis, RM-listed ﬁrms might have been less likely to defraud. We further conducted a robustness test by excluding from our sample ﬁve RM ﬁrms that were listed in 2011, and the main results did not change. 8. http://pcaobus.org/International/Inspections/Pages/IssuerClientsWithoutAccess.aspx 9. http://cmis.cicpa.org.cn/cicpa2_web/public/query0/1/00.shtml 10. Financial condition is measured by ZSCORE, which is computed using the revised model for non-manufacturers and emerging markets in Altman (2002): 6.56*(current assets-current liabilities) / total assets + 3.26* retained earnings / total assets + 6.72* earnings before interest and taxes / total assets + 1.05* market value equity/book value of total liabilities. A ZSCORE below 1.1 indicates ﬁnancial distress. References Abbott, L. J., Gunny, K., & Zhang, T. (2011). When the PCAOB talks, who listens? Evidence from client ﬁrm reaction to adverse, seriously deﬁcient PCAOB inspection reports. 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China Journal of Accounting Studies – Taylor & Francis

Published: Dec 1, 2013

Keywords: reverse merger; PCAOB inspections; auditor reputation; accounting fraud; G34; L51; M41; M42; M49

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PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

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PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

PCAOB inspections, auditor reputation, and Chinese reverse merger frauds

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