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The consequence of audit failure on audit firms: evidence from IPO approval in China

The consequence of audit failure on audit firms: evidence from IPO approval in China CHINA JOURNAL OF ACCOUNTING STUDIES 2019, VOL. 7, NO. 2, 245–269 https://doi.org/10.1080/21697213.2019.1676064 ARTICLE The consequence of audit failure on audit firms: evidence from IPO approval in China a a b a Hongqi Yuan , Chujun Zhang , Desong Kong and Haina Shi a b School of Management, Fudan University, Shanghai, China; Accounting School, Shanghai University of International Business and Economics, Shanghai, China ABSTRACT KEYWORDS Audit failure; regulatory This paper examines a potential adverse consequence of audit sanction; audit firm; IPO failure. We study whether and how the audit firm’s audit failure impacts its client’s Initial Public Offering (IPO) rejection rate. Our empirical results show that the client’s IPO application rejection rates increases significantly after the audit failure. The significant increase in the IPO rejection rate holds regardless whether the audit firm is subject to regulatory sanctions on the audit failure or not. However, the sanctioned audit firm’s clients experience significantly higher IPO rejection rates than the non-sanctioned audit firm’s clients. Our further analysis reveals that the adverse outcome on clients’ IPO application varies by types of audit firm and by board of IPO listing. 1. Introduction Audit failure can significantly impairs audit firm reputation and results in various adverse consequences. We study one type of potential consequences of audit failure: whether and how audit failure impacts its clients’ IPO rejection rates. The existing literature on audit failure examines either the direct economic consequences in terms of a decrease in market share and audit fees (Davis & Simon, 1992; Dopuch & Simunic, 1982; Firth, 1990; Sami, Kim, Zhou, & Fang, 2012; Wilson & Grimlund, 1990), or the indirect consequences in terms of a decline in the client’s financial statements credibility, a decline in the client’s market value, and an increase in the client’s cost of capital (Asthana, Balsam, & Krishnan, 2010; Cahan & Zhang, 2006; Chaney & Philipich, 2002; Dechow, Ge, & Schrand, 2010; Dechow, Sloan, & Sweeney, 1996; Firth, 1990; Moreland, 1995; Nagy, 2005). However, the existing literature keeps silent on whether and how audit failure affects government decision. Based on the IPO approval system in China, the current study aims to fill this void in literature. Specifically, we provide empirical evidence on the impact of audit failure on IPO decisions which are made by the Stock Issuance Examination Committee (here- after the Examination Committee) of China Securities Regulatory Commission (hereafter the CSRC). CONTACT Hongqi Yuan yuanhq@fdsm.fudan.edu.cn School of Management, Fudan University, 670 Guoshun Road, Shanghai, China Paper accepted by Xi Wu. © 2019 Accounting Society of China 246 H. YUAN ET AL. In this study, an audit failure is identified if any client of an audit firm involves in accounting fraud We call the audit firm that experiences at least one audit failure as failed audit firms. If the failed audit firms are subsequently sanctioned by the CSRC, then these firms are at the same time sanctioned audit firms. In comparison, if the failed audit firms are exempted from regulatory sanction, then these firms are non-sanctioned audit firms. It is of great importance to study how audit failure affects the Examination Committee’s decision given the critical role played by the Examination Committee in the IPO approval process. While the quality of IPO applicants is crucial for the overall quality of the equity capital market, we need a better understanding on the factors that the Examination Committee considers in the decision-making process. We pay particular attention to the question of whether the Examination Committee conducts rigorous review towards IPO clients of failed audit firms. We also take a step further beyond the audit failure to study how regulatory sanctions affect the Examination Committee’s decision. While it is not surprising that regulatory sanctions result in adverse consequences, we are interested in whether the Examination Committee also takes into account of the audit failures that are not subject to regulatory sanctions. By doing so, we attempt to obtain a comprehensive understanding of how audit failure and regulatory sanctions affect the Examination Committee’s decision set during the IPO process. Based on a sample of IPO applications during the sample period of 2004 to 2016, we first document that audit failure by the audit firm adversely affect its clients’ IPO applica- tion outcomes, that is, the clients’ IPO rejection rates significantly increase after the audit firm experiences an audit failure. The adverse influence on the client’s IPO application holds regardless of whether the audit firm is subject to regulatory sanctions on the audit failure or not. However, the clients’ IPO rejection rates are significantly higher for audit firms that are subsequently sanctioned, compared with those that are not sanctioned. Our further analyses reveal the following cross-sectional differences on the relation between audit failure and clients’ IPO rejection rates: (i) for the Big N audit firms (including the international Big 4 and the domestic Big 10 audit firms) and for non-politically connected audit firms, the significant increase in the clients’ IPO rejection rates is found only when the Big N audit firms and the non-politically connected audit firms are sanctioned by the CSRC; (ii) for non-Big N audit firms and for politically connected audit firms, the clients’ IPO rejection rates increase significantly as long as the audit firm experiences an audit failure; and (iii) the adverse impact of audit failure is mainly driven by the IPO applicants on the Main board and the Small- and Medium-sized Enterprises board (hereafter the SME board). Our study contributes to the literature in the following ways. First, the existing literature on the consequences of audit failure typically investigates how the audit failure adversely impacts the audit firms(Davis&Simon, 1992;Dopuch& Simunic, 1982;Firth, 1990;Samietal., 2012;Wilson&Grimlund, 1990), or the informativeness of the clients’ financial statements (Asthana et al., 2010; Cahan & Zhang, 2006;Chaney& Philipich, 2002;Dechowetal., 2010, 1996;Firth, 1990;Moreland, 1995;Nagy, 2005). This study furthers our understanding on the adverse impact of audit failure on audit firms Existing literature either provides definition of audit failure (e.g. Arens, Elder, and Beasley, 2017; Francis, 2004) or lists the characteristics of audit failure (DeFond & Zhang, 2014). Based on the literature, an audit failure incurs if an auditor (i) fails to uncover or report the fact that the client did not properly follow the accounting standards, and (ii) issues an inappropriate audit opinion. Thus, client’s accounting fraud is a typical case of audit failure.. CHINA JOURNAL OF ACCOUNTING STUDIES 247 from the perspective of government decision-making. Second, we distinguish between the consequences of audit firms being sanctioned and not being sanctioned after an audit failure. Previous studies on audit failure in general focus on the audit firms that are subject to sanctions. In comparison, we document an adverse impact even when the audit firm is not subsequently sanctioned on the audit failure. Third, we provide evidence that the adverse impact of audit failure varies by types of audit firm and by board of IPO listing. The findings help the market participants better understand the roles played by audits. More importantly, the evidence helps evaluate the efficiency of the regulatory monitoring on audit failures. The remainder of this paper is organised as follows: Section 2 introduces the institutional background of the IPO system in China, Section 3 reviews relevant literature and develops the hypotheses. We describe our sample and descriptive statistics in Section 4. The research design and empirical results are discussed in Section 5. We conduct several cross-sectional analyses in Section 6 and the robustness tests in Section 7.Finally, Section 8 concludes. 2. Institutional background: the IPO system in China The IPO system in China has gone through two stages: the quota system and the approval system. The quota system was adopted before 2000. Under the quota system, the local government or an industrial department of the State Council, based on the pre-determined quota set by the central government, were delegated to choose and then recommend a particular company to get listed. The number of shares to be issued by the company was also pre-determined. Then, the stock issuance was directly approved by the CSRC. The quota system was replaced by an approval system in 2001. Under the approval system, the investment banks, rather than the local government or industrial departments of the State Council, play the role to select and to recommend potential IPO issuers. The approval system significantly strengthens the responsibilities of the investment banks as well as other market intermediaries. The decisions such as the number of shares to be issued and the amount of proceeds to be raised are made based on the capital demand of the IPO applicant. The Examination Committee of the CSRC conducts an independent review of the stock issuance. The Examination Committee of the CSRC has undertaken a decisive role in the stock issuance process since its establishment. We first briefly review the regulations related to the Examination Committee. It was set up by the CSRC based on the ‘Regulations of the CSRC for the Stock Issuance Examination Committee’ (hereafter the SIEC Regulations) which was issued on 16 September 1999. The SIEC Regulations clarified the rights and responsibilities of the Examination Committee. Since then, the Examination Committee has been delegated the right to decide whether an issuer can go public. On 24 November 2003, the CSRC announced the ‘Measures of CSRC for the Stock Issuance Examination Committee’ (hereafter the SIEC Measures). The main purpose of the SIEC Measures was to reform the stock issuance examination system to improve the transparency of the working procedures of the Examination Committee. To achieve this, the SIEC Measures specified that the committee members should be recommended by relevant administrative organisations, industry-wide self-regulatory organisations (such as the Chinese Institute of Certified Public Accountants Association), research institutions, and universities. Each term of the Examination Committee should be composed of 25 committee members, whose personal information 248 H. YUAN ET AL. is publicly available on the official website of the CSRC. On 13 May 2009, the CSRC set up another Examination Committee for the Growth Enterprise Market (the GEM) to support the establishment of the GEM board. The two Examination Committees operated together then, one for the main and SME boards and one for the GEM board, respectively. The SIEC Measures were amended by the CSRC on 7 July 2017. Given a convergence between the main and SME boards and the GEM board in terms of basic logics and criterion of stock issuance examination, the two Examination Committees merged based on the amended SIEC Measures. The merge was expected to optimise the allocation of administrative resources and to improve the work efficiency of the Examination Committee. Under the approval system, the Examination Committee is the critical player that represents the government’s interest. We next introduce another important player in the IPO process, the representative sponsors, who act as capital market intermediaries to help the issuers go through the IPO process. The sponsorship system refers to a system in which qualified sponsors recommend issuers that satisfy the listing requirements to issue and to publicly list their shares. The sponsorship system requires that the sponsors should provide continuous monitoring, supervision, guidance and credit guarantees to the issuers they recommend with respect to the issuers’ information disclosure quality and the commitment the issuers made. Under the sponsorship system, the investment bank and its representa- tive sponsors take the following crucial responsibilities. First, they are responsible for the recommendation and counselling of the share issuance and listing. Second, they carry out due diligence to verify the truthfulness, accuracy, and completeness of the issuers’ docu- ments. Third, they assist the issuers to establish a strict information disclosure system and assume joint and several liability regarding issuers’ information disclosure. Last but not least, they make a recommendation to the CSRC. The issuer needs to go through the following main examination procedures for a successful IPO according to the ‘Workflow for IPO Stock Issuance Examination by CSRC’: case acceptance by the supervision department of CSRC, preliminary feedback, preliminary examination meeting, formal review and approval meeting by the Examination Committee, closing the case, and final approval for public issuance by the CSRC. Among these procedures, one of the most critical step is the formal review and approval meeting. At the meeting, the Examination Committee assesses all the relevant documents, such as the issuer’s prospectus, and the preliminary review report by other functional departments of the CSRC. Then, the committee members vote on the IPO application and reach a review opinion on whether the issuer should be approved or not for a public listing. The review opinions by the Examination Committee are typically based on by the Securities Law, the Company Law and administrative regulations issued by various government departments and the CSRC. As the most important step in the stock issuance process, the Examination Committee is responsible for selecting high-quality issuers to enhance the quality of listed companies and thus the overall quality of the capital market. On the one hand, the regulatory authorities have issued a series of regulations to specify the listing requirements and to stipulate the information disclosure requirements. These requirements provide basis for the Examination Committee to reach a review opinion. On the other hand, the committee members also exercise professional judgement to comprehensively review the issuer’s prospectus and the preliminary review report. In reviewing a particular IPO application, the Examination Committee plays the following key roles: (i) reviews whether the CHINA JOURNAL OF ACCOUNTING STUDIES 249 application for stock issuance satisfies relevant regulations; (ii) reviews and assesses the statements and reports submitted by the professional intermediaries, including the spon- sors, the auditor, the attorney, and the asset appraiser; (iii) examines the preliminary review report prepared by other functional departments of the CSRC; and (iv) submits a review opinion on the IPO application. Given the critical roles of the Examination Committee in the IPO decision-making, the CSRC implements several bonding mechanisms on the commit- tee members to ensure the effective operation of the Examination Committee, including the performance evaluation system, requiring commitments before the review and approval meeting, the accountability system, reminder through conversation, and the whistle-blowing system. Although the CSRC makes the final decision of whether to approve or disapprove an issuer’s IPO application upon the review opinion submitted by the Examination Committee. In practice, the CSRC never rejects an IPO application that is approved by the Examination Committee. The final result of the IPO application is then publicly announced on CSRC’s official website after the CSRC makes the final decision. 3. Literature review and hypotheses development There is a large body of literature on whether and how regulatory sanctions after audit failures impacts the audit firms. Theliteraturedocuments significant impairment on the audit firm’s reputation by the regulatory sanctions. From the perspective of the audit firm’sexisting clients, Chaney and Philipich (2002) examine how the Enron event impacts Arthur Anderson and find significantly negative market reactions of Arthur Anderson’sother clientsonits investigation by the SEC. Fang, Xu, and Hong (2006) document a similar phenomenon in the Chinese context. They study how the accounting fraud conducted by Yinguangxia impacts its audit firm, Zhongtianqin. The market reacts significantly negative to Zhongtianqin’sother clients when the CSRC announced a regulatory sanction on Zhongtianqin. From the per- spective of the audit firm per se,Firth (1990) documents that regulatory sanction leads to decreases in the audit firm’smarketshare and audit fees,aswellasthe stockpricesofthe firm’s other clients. Sami et al. (2012) find a higher probability of audit firms being replaced and lower audit fees after the regulatory sanction. Davis and Simon (1992) document lowered audit fees charged to the new clients after the sanctions. Wilson and Grimlund (1990)show that sanctioned audit firms have more difficulties to retain existing clients as well as to attract new clients. From the perspective of informational consequences, Moreland (1995)docu- ments a decrease in the clients’ earnings response coefficient subsequent to audit firm’s sanction. The other stream of literature studies the relation between financial statement restate- ment and audit firm switch. While Hennes, Leone, and Miller (2014) document that the audit firm is more likely to be dismissed by the board of directors after a restatement of financial statement, Agrawal and Cooper (2017)failto find significant association between the likelihood of audit firm switch and restatement. Ma, Zhang, and Yang (2016)study this issue in the Chinese setting and find that audit firm switch is related to types of restatement. The listed company is likely to switch to a reputable audit frim if the restatement is a fraud- related one. However, if the restatement is related to misstatements, the listed company tends to switch to an audit firm that is more likely to agree with the listed company. 250 H. YUAN ET AL. The above literature discusses the reputational losses of audit firms after the audit failures from the perspectives of clients and investors of the clients. However, very few papers examine how the government, as one of the important users of audit information, reacts to audit failures. As introduced in Section 2, the Examination Committee plays a crucial role in the IPO process in China. The main responsibilities to review and decide the outcome of an IPO application lie on the Examination Committee. To ensure the quality of listed companies and to enhance the overall quality of the capital market, the Examination Committee needs to maintain relatively stringent criterion when reviewing the IPO applications. It is likely to take into account various information related to the IPO applicants during the review process. Audit firm, as one of the most important financial intermediaries during the IPO process, certifies the IPO applicant’s financial-related infor- mation. It is thus intuitive for the Examination Committee to take the auditing-related information into the decision-making process. We expect that the Examination Committee pays a lot of attention to the audit quality and keeps cautious to the clients of the failed audit firms due to the following reasons. First, according to the amended SIEC Measures, the CSRC implements an accountability system. The Examination Committee will be held accountable if it makes inappropriate review decisions. The committee members may be (i) reminded through conversation, (ii) criticised, (iii) open censured, or (iv) dismissed by the CSRC. The type of punitive measures depend on how serious the problem is in the decision-making process. Second, the CSRC adopts a performance evaluation system that scores the committee members. The score is directly related to whether a particular member’s contract will be renewed for the next term. Third, the Examination Committee is mainly composed of the regulatory officials in the CSRC and external professionals. These committee members tend to keep a high standard in reviewing the IPO applications to maintain their professional reputations. Thus, the Examination Committee may be particu- larly concerned about the potential risks underlying the audit failure and thus exerts more caution in reviewing the firm’s IPO clients. We therefore hypothesise that: H1: The IPO client’s rejection rate significantly increases after the audit firm experiences an audit failure. The above H1 compares the client’s IPO rejection rate in the pre- and post-audit failure period. However, an audit failure does not necessarily result in a regulatory sanction. Specifically, the Securities Law stipulates that ‘if the securities service institution has not diligently performed its duties, or if the documents prepared or issued by the institution have false or misleading statements or material omissions, the institution shall be (i) required to correct the documents, (ii) confiscated all the related revenues, (iii) suspended or disqualified the securities service business licence, and (iv) imposed a fine with an amount ranging from one time to five times of the revenue.’ The Securities Law also specifies that the person who is in charge of the business and those who are directly responsible for the business should be publicly warned and be disqualified from profes- sional practices, in addition to a fine ranging from 30,000 to 100,000 RMB. While some audit firms that experience audit failure are subject to regulatory sanctions (the sanctioned firms), others are exempted from regulatory sanctions (the non- sanctioned firms). A stream of literature thus examines the determinants of an audit firm being sanctioned (Chen, Qiu, & Xu, 2011; Firth, Mo, & Wong, 2005; Wu, 2007). This CHINA JOURNAL OF ACCOUNTING STUDIES 251 literature documents that the CSRC considers factors such as the inherent risks of the auditing tasks, the natures and types of accounting frauds conducted by the clients. The existing literature finds that the regulatory departments tend to selectively enforce the regulations towards accounting frauds (Chen, Jiang, Liang, & Wang, 2011). In terms of audit failures, one can similarly expect selective enforcement on the audit firms because the audit firms may try to be exempted from liability through rent seeking. However, the audit firm whose client is found to be fraudulent may still suffer a reputational loss even if it is not sanctioned. Committee may consider the potential risks and exert caution in reviewing the IPO clients of non-sanctioned audit firms. In practice, the sanction notices issued by the regulatory authorities on audit firms reveal that the main reasons for the audit firms being sanctioned include defective audit procedures and lack of professional scepticisms. That is, regulatory sanction serves as an indicator of weak audit quality. In the IPO application setting, the Examination Committee is thus likely to question the accounting information quality of the sanctioned audit firms’ clients due to the poor audit quality. As a result, the Examination Committee may conduct a more cautious scrutiny on the IPO applicants who are clients of the sanctioned audit firms, which in term affects the IPO rejection rates. We thus make the following two hypotheses on regulatory sanction that: H2a: The IPO client’s rejection rate significantly increases regardless of whether the audit firm is subject to regulatory sanction on an audit failure H2b: The IPO client’s rejection rate is significantly higher for a sanctioned audit firm, compared with a non-sanctioned audit firm. 4. Sample 4.1. Sample selection and distribution Our sample covers all the IPO applications in the Chinese A-share market for the period of 2004 to 2016. We start from 2004 because the IPO approval system experienced asignificant reform by the SIEC Measures in November 2003. The reform strengthened the role of the representative sponsors. Since then, the IPO system has been largely stable. On the other hand, financial data of the IPO applicants that were rejected by the CSRC was not publicly available before 2003. As a result, it was not possible to compare the successful IPOs with the failed ones before 2003. The data is obtained from the Wind database. Specifically, the CSRC announces the decision of each IPO application on its official website. Then, the Wind database collects all the IPO application outcomes. The database also provides financial data of the IPO applicants, which is disclosed in the prospectus. We are left with 1,605 IPO applications after dropping observations with missing values for necessary variables. Table 1 shows the distribution of the IPO applications by year and by industry, respectively. As shown, year 2010 has the largest number of IPO applications (311) while year 2004, 2006 and 2008 have relatively fewer IPO applications. More than 60% of the sample comes from the manufacturing industry (1,021), followed by the information technology industry. 252 H. YUAN ET AL. Table 1. Sample distribution – The IPO sample. Year N Industry N 2004 37 Manufacturing 1,021 2006 60 Information technology 217 2007 122 Business services 81 2008 62 Wholesale & retail 52 2009 130 Construction 47 2010 311 Sports & entertainment 35 2011 242 Financial & insurance 34 2012 105 Transportation, warehouse, & postal services 31 2014 94 Mining 30 2015 200 Electricity, heat, gas, & water supply 22 2016 242 Agriculture, forestry, animal husbandry, & fishery 21 Real estate 9 Conglomerate 5 Total 1,605 1,605 4.2. Distribution of the audit failures We first identify the audit firms that experienced audit failures (the failed audit firms) and those that did not experienced any failures (the non-failed audit firms). In 2001, the CSRC began to disclose all the sanctions and penalties on the listed companies that conduct accounting frauds. The corresponding audit firms are then defined as failed audit firms. At the same time, the CSRC also discloses the sanctions and penalties on the audit firm if the audit firm is held accountable to the accounting fraud. These audit firms are defined as the sanctioned audit firms. Thus, the sanctioned audit firms are sub-samples of the failed audit firms because some failed firms are not subject to regulatory sanctions. We hand-collect all the accounting frauds during 2001 to 2016 from the CSRC official website. An audit firm is defined as a failed audit firm if any of its client involves in accounting fraud during 2001 to 2016. We start to identify the failed audit firms three years earlier than the IPO sample because the Examination Committee is likely to take this information into account in reviewing a particular IPO application. With respect to the audit firms, audit failures incurred in the previous three years may have continuous influences on the reputation, which in turn affects the Examination Committee’s decision. On the other hand, the review and examination of an IPO application require the applicant to submit previous three years’ audited financial statements. That is, for those IPO applicants that submitted the application in 2004, the Examination Committee checks their financial statements that cover 2001 to 2003 fiscal years. Therefore, we start from year 2001 to deal with the audit failure sample. The distribution of the audit failure sample is reported in Table 2. A total of 116 failed audit firm-year (audit failures) are documented during 2001 to 2016. Note here the year in Table 2 corresponds to the year that the failed audit firm’s client is formally filed for a fraud by the CSRC. Since a particular listed company may conduct accounting fraud in multiple years, the 116 failed audit firm-year correspond to 296 clients’ fraud-year observations Half of the audit failures (58) are subject to regulatory sanctions. As shown in Panel A of Table 2, years 2004, 2008, 2010, and 2015 are filed with more than 10 audit failures while years 2001 and 2007 are associated with relatively high probabilities of failed audit firms being sanctioned. For example, if a listed company A involved in accounting fraud in years 2001, 2002 and 2003. The CSRC subsequently announced sanctions on the frauds in 2005. Then, 2005 is the year we identify the failed audit firm in Table 2. However, one failed audit firm-year corresponds to three fraud-years in this example.. CHINA JOURNAL OF ACCOUNTING STUDIES 253 Table 2. Distribution: Audit failure and audit sanction. Panel A: Audit failure by year Year Failed Audit firm Failed but Not Sanctioned Failed and Sanctioned % of Sanction 2001 7 1 6 85.71 2002 3 1 2 66.67 2003 8 5 3 37.50 2004 12 8 4 33.33 2005 7 3 4 57.14 2006 5 3 2 40.00 2007 5 1 4 80.00 2008 10 4 6 60.00 2009 8 3 5 62.50 2010 10 7 3 30.00 2011 5 3 2 40.00 2012 5 3 2 40.00 2013 6 2 4 66.67 2014 8 3 5 62.50 2015 11 9 2 18.18 2016 6 2 4 66.67 Total 116 58 58 50.00 Panel B: Audit failure: Big N VS. Non-Big N Failed Audit firm Failed but Not Sanctioned Failed and Sanctioned % of Sanction Audit Failure by Big N 27 14 13 48.15 Audit Failure by Non-Big N 89 44 45 50.56 Total 116 58 58 50.00 Panel C: Frequency of audit failure and audit sanction Audit Failure Audit Sanction Frequency of Audit Failure N of Audit Firms Frequency of Audit Sanction N of Audit Firms 144 0 23 210 1 36 38 2 4 62 3 1 82 5 1 Panel B of Table 2 reports the audit failures and regulatory sanctions by Big N audit firms and those by non-Big N audit firms, respectively. We observe that non-Big N audit firms experience more audit failures (89) than the Big N audit firms (27). However, once an audit failure incurs, the probability of failed audit firm being sanctioned is only slightly lower for the Big N audit firms (48.15%) than that for the non-Big N audit firms (50.56%). Panel C of Table 1 reports the frequencies of audit failures and regulatory sanctions by audit firms. Among the 66 failed audit firms in our sample, 44 firms only involve one audit failure while 22 firms involve multiple failures. Two firms experience eight audit failures. In terms of regulatory sanctions (the right two columns of Panel C), we find that 23 firms are exempted from sanction on audit failures while seven firms are sanctioned more than twice. Next, we check how the audit firms react to the accounting frauds by summarising the audit opinions. As described in Panel A of Table 3, we identify 289 fraud-year observations during 2001 to 2016. Among them, 231 (79.93%) fraud-years receive unqualified audit As mentioned in the previous paragraph, the 116 audit failures correspond to 296 fraud-year observations. However, seven accounting frauds conducted by two companies incur before IPOs. That is, the financial statements disclosed in the prospectus involve accounting frauds. No audit opinions are disclosed for these seven frauds. We are thus left with 289 fraud-year observations. 254 H. YUAN ET AL. Table 3. Distribution: Audit opinions on the listed companies. Panel A: Audit opinion by fraudulent companies Fraudulent Non-Fraudulent Audit Opinion Companies % Company % Unqualified opinion 231 79.93 27,320 91.91 Unqualified opinion with explanatory paragraphs 31 10.73 1,482 4.99 Qualified opinion 10 3.46 300 1.01 Qualified opinion with explanatory paragraphs 10 3.46 345 1.16 Adverse opinion 0 0.00 4 0.01 Disclaimer 7 2.42 275 0.93 Total 289 100 29,726 100 Panel B: Audit opinion by audit firms: Sanctioned VS. Non-Sanctioned Sanctioned Audit Non-Sanctioned Audit Opinion firms % Audit firms % Unqualified audit opinion 86 84.31 145 77.54 Unqualified audit opinion with explanatory paragraphs 9 8.82 22 11.76 Qualified audit opinion 1 0.98 9 4.81 Qualified audit opinion with explanatory paragraphs 5 4.91 5 2.67 Disclaimer 1 0.98 6 3.22 Total 102 100 187 100 opinions and 31 (10.73%) fraud-years receive unqualified opinions with explanatory para- graphs. That is, only about 10% of the accounting frauds receive modified audit opinions. In comparison, 3.11% of the companies that do not involve in accounting frauds also receive modified audit opinions. The high Type II error suggests large room for improvement in audit quality in the Chinese A-share market. Panel B of Table 3 reports the audit opinions on the accounting frauds issued by the sanctioned audit firms and those by the non-sanctioned audit firms, respectively. The non-sanctioned audit firms issue a total of 10.7% modified opinions to the frauds. In comparison, sanctioned audit firms issue only 6.87% modified opinions to frauds. 5. Research design and empirical results 5.1. Research design We employ a difference-in-difference (DID) approach (Bertrand & Mullainathan, 2003; Yang, 2013) to empirically examine the economic consequences of audit failure and regulatory sanction on the firm’s IPO audits. Specifically, we employ the following logit model on the IPO sample described in Table 1 to test H1 of whether and how audit failure affects the IPO clients’ rejection rate: Reject ¼ α þ β Auditfail þ β Auditfail Post þ Controls þ Year & Industry fixed effects 1 2 þ ε (1) The dependent variable, Reject, is a dummy variable that equals one if the IPO application is rejected by the CSRC and zero if the applicant successfully get listed. The variable Auditfail identifies an audit firm whose client is found to conduct accounting fraud during 2001–2016. Panel C of Table 2 identifies a total of 66 failed audit firms. The variable Auditfail takes a value of one if the IPO applicant is the client of one of the 66 failed audit firms and zero otherwise. It captures the differences in IPO rejection rates between the IPO CHINA JOURNAL OF ACCOUNTING STUDIES 255 clients of the failed audit firms and those of the non-failed audit firms. Our variable of interest, Auditfail_Post, captures how audit failure subsequently affects IPO rejection rate. It equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure and zero otherwise. A significantly positive β supports our H1. We include a set of control variables based on existing studies. First, the IPO applicant’s characteristics are controlled by size (Size), leverage (Lev), and profitability (ROA). An IPO application is more likely to be successful for large and profitable firms, and for firms with low leverage and thus less risky (Yang, 2013). We next control for existence of political connection by the nature of the applicant’s ultimate shareholder (SOE) because state- owned enterprises are less likely to be rejected by the CSRC (Li & Liu, 2012). We also control for the reputation of the two most important financial intermediaries during the IPO process: whether the applicant’s financial statements are audited by one of the Big N auditors (BigN) and whether one of the Top 10 investment banks underwrite the IPO application (Top10_IB). Reputable intermediaries are expected to increase the IPO pass rate (Chen, Zheng, & Li, 2014). Last but not least, the year and industry fixed effects are controlled for any unobservable year and industry factors that are not included in the empirical model. Table 4 provides a detailed definition of all the variables. All the continuous variables are winsorised at 1% level. Next, we investigate whether and how the regulatory sanctions on the audit firm influence its IPO client’s rejection rate. Similar to Equation (1), we employ the following logit model: Table 4. Data definitions. Dependent Variable Reject Dummy variable, equals one if the client’s IPO application is rejected and zero if it is successfully approved by the CSRC. Variables of Interest Auditfail_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure and zero otherwise. Sanc_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm is sanctioned on the audit failure by the CSRC and zero otherwise. NonSanc_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure without sanctions and zero otherwise. Control Variables Auditfail Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firms and zero otherwise. An audit firm is classified as a failed one if it audits at least one listed company that conduct fraud during 2001–2016. Sanc Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firm that is sanctioned by the CSRC due to the audit failure and zero otherwise. NonSanc Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firm that is not sanctioned by the CSRC due to the audit failure and zero otherwise. BigN Dummy variable, equals one if the IPO applicant is audited by one of the Big N audit firms and zero otherwise. Big N audit firms include international Big 4 and domestic Big 10. Size Natural logarithm of total assets of the IPO applicant. ROA Return on assets of the IPO applicant. Lev Leverage ratio of the IPO applicant, calculated as total liabilities divided by total assets. SOE Takes a value of one if the IPO applicant is a state owned enterprise, and zero oterhwise. Top10_IB Dummy variable, equals one if the IPO is underwritten by one of the top 10 investment banks and zero otherwise. Top 10 is calculated on the market share of the investment bank whereas market share is based on the clients’ total proceeds raised in the previous year. 256 H. YUAN ET AL. Reject ¼ α þ β Sanc þ β NonSanc þ β Sanc Post þ β NonSanc Post þ Controls 1 2 3 4 þ Year &; Industry fixed effects þ ε (2) Since some audit firms are subsequently sanctioned by the CSRC while others are not, we define two new variables, Sanc and NonSanc,todifferentiate the sanctioned firms and non- sanctioned firms. Specifically, Sanc equals one if the IPO applicant is the client of a failed audit firm that is sanctioned during our sample period and zero otherwise. The variable NonSanc takes a value of one if the IPO applicant is the client of a failed audit firm but is not sanctioned during our sample period and zero otherwise. That is, Auditfail is the sum of Sanc and NonSanc. Similar as the construction of Auditfail_Post in Equation (1), we construct two variables, Sanc_Post and NonSanc_Post to capture the impact of audit sanction on IPO client’s rejection rate. The variable Sanc_Post is a dummy variable that equals one if the client’s IPO is reviewed within three years after an audit firm is sanctioned on the audit failure by the CSRC and zero otherwise. The variable NonSanc_Post is a dummy variable that equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure without sanctions and zero otherwise. That is, Auditfail_Post is the sum of Sanc_Post and NonSanc_Post.The difference between β and β captures the 3 4 different impact on IPO rejection rate caused by audit sanction. Our H2a will be supported by positive β and β . And H2b will be supported if β is larger than β . 3 4 3 4 5.2. Descriptive statistics The logit models of Equations (1) and (2) are estimated based on the IPO sample described in Table 1.Panel Aof Table 5 summarises the descriptive statistics of the variables used in the logit models. The followings are noteworthy. First, the mean IPO rejection rate is Table 5. Descriptive statistics. Panel A: Descriptive statistics (N = 1,605) Mean Q1 Median Q3 Std. Dev. Reject 0.06 0.00 0.00 0.00 0.24 Auditfail 0.72 0.00 1.00 1.00 0.45 Auditfail_Post 0.37 0.00 0.00 1.00 0.48 Sanc 0.33 0.00 0.00 1.00 0.47 Sanc_Post 0.12 0.00 0.00 0.00 0.32 NonSanc 0.39 0.00 0.00 1.00 0.49 NonSanc_Post 0.25 0.00 0.00 0.00 0.43 BigN 0.46 0.00 0.00 1.00 0.50 Size 20.63 20.27 20.75 21.38 2.80 Lev 0.31 0.15 0.27 0.43 0.20 ROA 0.08 0.05 0.07 0.10 0.04 SOE 0.14 0.00 0.00 0.00 0.35 Top10_IB 0.31 0.00 0.00 1.00 0.46 Panel B: Univariate comparison of mean IPO rejection rate (Reject) Mean value of Reject Test for Difference Types of Audit firm Auditfail =0 Auditfail =1 Diff. t-value Failed audit firm (Auditfail = 1) 4.59% 6.38% 1.78% 1.91* Sanctioned audit firm (Sanc = 1) 5.20% 6.91% 1.71% 2.18** Non-sanctioned audit firm (NonSanc = 1) 5.15% 6.12% 0.96% 0.69 The superscripts * and ** indicate p < 0.1 and p < 0.05, respectively. CHINA JOURNAL OF ACCOUNTING STUDIES 257 6%. Second, on average, 72% of the IPOs are audited by audit firms that experienced at least one audit failure. Among the failed audit firms, 33% are subsequently subject to CSRC sanction while 39% are not sanctioned. Third, the mean value of Auditfail_Post is 0.37, suggesting that 37% of the IPO applicants are audited by firms that experienced an audit failure in the latest three years. Among them, 12% of the IPO applicants are audited by failed firms that are sanctioned in the latest three years and 25% are audited by failed firms but are not sanctioned in the latest three years. Fourth, with respect to the control variables, 46% of the IPO applicants are audited by one of the international Big 4 or the domestic Big 10 audit firms. 31% of the IPO applicants are underwritten by one of the top 10 investment banks. 14% of the IPO applicants are SOEs. Panel B compares the mean IPO rejection rate (Reject) for the sub-samples of pre- and post-audit failure. For the failed audit firms, the client’s mean IPO rejection rate in the post- failure period (Auditfail_Post = 1) is 6.38%, significantly higher than that in the pre-failure period (4.59%). With respect to the failed audit firms that are subsequently sanctioned, the mean IPO rejection rate in the post-sanction period (Sanc_Post=1) is 6.91%. As a comparison, the mean IPO rejection rate in the pre-sanction period for the sanctioned audit firms is significantly lower at 5.20%. In terms of the failed audit firms that are not subject to sanctions, the mean IPO rejection rate in the post- and pre-failure periods are 6.12% and 5.15%, respectively. The two mean rejection rates are not significantly different. The univariate comparison provides some preliminary evidence that the IPO client’srejec- tion rate increases after audit failures and regulatory sanctions on the audit failures. 5.3. Empirical results Table 6 reports the results for the logit models that investigates whether and how audit failures and regulatory sanctions adversely affect the client’s IPO application outcomes. Columns (1) and (2) are estimated on all the IPO applicants during our sample period and column (3) is estimated on the IPO clients of the failed audit firms Column (1) of Table 6 reports the regression results of Equation (1). As shown, the coefficient of Auditfail is −0.097 and is not significantly different from zero. The insignificant coefficient suggests that the IPO rejection rate does not differ between the clients of the failed audit firms and those of the non-failed audit firms before the audit failure incurs. More interestingly, the coefficient of Auditfail_Post is positive with a value of 1.159, significant at less than 5% level. It provides evidence to support our H1 that the client’s IPO rejection rate increases significantly after an audit firm experiences an audit failure. That is, audit failure adversely impacts its IPO client’s application outcome. Column (2) presents the regression results of Equation (2). Neither the coeffi- cient of Sanc nor that of NonSanc is significantly different from zero, showing that regulatory sanctions on the failed audit firms in the pre-sanction period do not affect the clients’ IPO rejection rates. This is expected given the insignificant The number of observations in Table 6 and the total number of observations for the three sub-samples tests in Tables 7– 9 are less than that in Table 1 (1,605) because STATA automatically drops some observations when we include the year and industry fixed effects.. 258 H. YUAN ET AL. Table 6. Regression results for the logit model of IPO rejection rate. (1) (2) (3) Auditfail −0.097 (−0.18) Auditfail_Post 1.159** (2.57) Sanc −0.574 −0.446 (−0.81) (−0.77) Sanc_Post 2.144*** 1.574** (2.91) (2.31) NonSanc 0.053 (0.09) NonSanc_Post 0.913* (1.81) BigN −0.589 −0.461 −0.806* (−1.43) (−1.02) (−1.67) Size −0.477*** −0.477*** −0.470*** (−6.17) (−6.22) (−5.14) Lev 4.074*** 3.954*** 3.684*** (3.83) (3.69) (3.00) ROA 1.748 2.077 1.104 (0.39) (0.45) (0.21) SOE −0.416 −0.444 −0.539 (−0.66) (−0.72) (−0.72) Top10_IB −0.628 −0.584 −0.541 (−1.43) (−1.32) (−1.05) Constant 6.378*** 5.971*** 7.184*** (3.08) (2.85) (2.95) Year Yes Yes Yes Industry Yes Yes Yes Pseudo R 0.39 0.40 0.39 N 1,600 1,600 1,080 [Sanc_Post]=[NonSanc_Post] 2.93* The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. coefficient of Auditfail in column (1). In comparison, the coefficient of Sanc_Post is 2.144 with a t-value of 2.91, significant at less than 1% level, showing a significant adverse impact on the client’s IPO application outcome after a failed audit firm is sanctioned by the CSRC. The coefficient of NonSanc_Post is also positive with a value of 0.913, significant at less than 10% level, suggesting that the IPO client’s rejection rate increases even if the failed audit firm is not subsequently sanctioned. That is, an audit firm encounters reputational loss when it experiences audit failure, regardless of being sanctioned or not. Next, we test whether the two coefficients differ significantly. We find that the coefficient of Sanc_Post is signifi- cantly larger than that of NonSanc_Post, providing evidence that the IPO client’s rejection rate is higher if the failed audit firm is sanctioned than if the failed audit firm is not sanctioned by the CSRC. Taken together, the results in column (2) lend support to H2a and show that audit failure does adversely impact the IPO client’s application outcome regardless of whether the audit firm is subsequently sanc- tioned or not. However, the sanctioned audit firm faces a more negative impact on the IPO client’s application outcome than the non-sanctioned audit firm does, as predicted by H2b. CHINA JOURNAL OF ACCOUNTING STUDIES 259 While columns (1) and (2) compare the failed audit firms with the non-failed audit firms as the benchmark, column (3) re-estimates Equation (2) on a reduced sample that includes only the IPO clients of the failed audit firms. By doing so, we effectively compare the sanctioned audit firms with the non-sanctioned audit firms among the failed firms group. Consistent with the finding in column (2), the coefficient of Sanc is not significantly different from zero, suggesting that the IPO rejection rate does not differ between the sanctioned and non-sanctioned audit firms in the pre-failure period. However, the coeffi- cient of Sanc_Post is positive with a value of 1.574, significant at less than 5% level, providing further support to our H2b. With respect to the control variables, we find that large firms (Size) and low-leveraged (Lev) firms are less likely to be rejected in the IPO applications. We also find some evidence in column (3) that Big N firm’s clients’ IPO applications (BigN) are less likely to be rejected. However, we do not find significant results on other control variables. 6. Further analyses In this section, we conduct several cross-sectional analyses to further investigate whether the audit failure-IPO rejection relation varies with different types of audit firms and IPO applicants. Specifically, we partition the sample by (i) the size of audit firms; (ii) whether the audit firm is politically connected; and (iii) the board of listing by an IPO applicant Then, Equations (1) and (2) are re-estimated on the sub-samples. We are interested in whether the coefficients of Auditfail_Post in Equation (1) and the difference in the coefficients of Sanc_Post and NonSanc_Post in Equation (2) differ between the sub-samples. 7. Effects of audit firm size on the rejection–failure relation Our first cross-sectional analysis examines whether the adverse consequence on client’s IPO application varies with the size of audit firms. One may expect that the Examination Committee is likely to adopt a more rigorous review on the clients of big audit firms. Firstly, through existing literature has well documented that big audit firms are associated with high audit quality (DeAngelo, 1981), big firms also suffer larger reputational losses. Li and Yuan (2017) examine the consequences of regulator sanctions on the sponsors and find that large investment banks experience larger decreases in the market share than small and medium ones do. Secondly, big audit firms may have stronger rent-seeking abilities than small audit firms to minimise the likelihood of being sanctioned after audit failures. The committee members may thus be more cautious in reviewing the IPO clients of big audit firms to take into account of the potentially understated sanctions on the big firms. In this sense, big audit firms’ IPO clients are likely to encounter more adverse consequences than small audit firms’. However, one can also argue that small audit firms face more rigorous review by the Examination Committee than big ones. Sami et al. (2012)show thatbig firms take measures We also follow Firth, Mo, and Wong (2014) approach to partition the sample by IPO clients of audit firms with only one failure and those with multiple failures. We do not find significant differences between the two sub-samples in terms of the IPO rejection rate-audit failure relation. We thus do not report this sub-sample test for brevity.. 260 H. YUAN ET AL. to improve audit quality in a timelier manner than small firms after the regulatory sanctions. The Examination Committee thus has more confidence in big firms than in small firms in the ability to restore audit quality after sanctions. Thus, IPO clients of small firms are likely to be reviewed more conservatively by the Examination Committee than those of big firms. Therefore, we partition the sample based on whether the IPO applicant is audited by one of the Big N audit firm or not. We follow the definition in our main test to define Big N as international Big 4 or the domestic Big 10 audit firms. Table 7 reports the results of the sub-sample test. Columns (1) and (2) investigate the consequence of audit failure on IPO application. As shown, the coefficient of Auditfail is not significant in either sub-sample. However, the coefficient of Auditfail_Post is significantly positive in column (2) (1.921 with a t-value of 2.82) while it is insignificantly different from zero in column (1). A Chow’s test shows that the coefficient of Auditfail_Post significantly differs between the two sub-samples with a p-value of 0.07. That is, the increase in the client’s IPO rejection rate is mainly driven by the IPO clients of the non-Big N firms. Audit failure does not adversely influence the Big N firms significantly. Columns (3) and (4) re-estimate Equation (2) to examine the consequence of audit sanction. We observe that the coefficients of Sanc and NonSanc are insignificant in both columns. In comparison, the coefficient of Sanc_Post is significantly positive in both columns while that of NonSanc_Post is significantly positive in column (4) only. That is, Table 7. Cross-sectional test: sample partitioned by Big N and Non-Big N audit firm. (1) (2) (3) (4) (5) (6) Big N Non- Big N Big N Non- Big N Big N Non- Big N Auditfail -0.310 0.003 (-0.33) (0.01) Auditfail_Post 0.113 1.921*** (0.16) (2.82) Sanc -0.090 -0.343 -0.105 -1.334 (-0.08) (-0.32) (-0.12) (-1.33) Sanc_Post 2.977* 2.699** 3.445** 2.442** (1.94) (2.41) (2.16) (2.13) NonSanc -0.107 0.171 (-0.09) (0.20) NonSanc_Post -0.814 1.531* (-0.79) (1.88) Size -0.590*** -0.429*** -0.663*** -0.422*** -0.710*** -0.369*** (-3.48) (-3.86) (-3.30) (-3.84) (-3.04) (-2.96) Lev 3.407* 4.083*** 3.694** 3.896*** 3.342 4.311** (1.88) (2.76) (1.96) (2.64) (1.64) (2.50) ROA 2.848 1.357 4.356 1.289 3.846 1.213 (0.37) (0.22) (0.58) (0.21) (0.48) (0.17) SOE 0.114 -0.899 -0.041 -0.809 -0.534 -0.305 (0.12) (-0.81) (-0.04) (-0.73) (-0.41) (-0.25) Top10_IB 0.084 -1.097* 0.127 -1.067* -0.558 -0.794 (0.11) (-1.72) (0.17) (-1.66) (-0.59) (-1.12) Constant -6.242 6.189** -7.550 6.336** -6.354 6.748** (-0.00) (2.25) (-0.00) (2.29) (-0.01) (2.13) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.51 0.36 0.54 0.37 0.52 0.35 N 592 624 592 624 512 405 [Sanc_Post]=[NonSanc_Post] 5.51** 0.77 The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. CHINA JOURNAL OF ACCOUNTING STUDIES 261 clients of both Big N and non-Big N audit firms experience declines in the IPO success rates after the audit firms are sanctioned. However, clients of Big N firms are not adversely affected in the IPO application if the audit firms experience audit failures but are not subsequently sanctioned. The test of difference in the two coefficients of Sanc_Post and NonSanc_Post in columns (3) and (4) confirms our findings. For clients of a Big N audit firm, the IPO rejection rates increase only when the audit firm is subsequently sanctioned on the audit failure. In comparison, for clients of a non-Big N audit firm, the IPO rejection rates increase as long as the audit firm experiences an audit failure, regardless of whether the audit firm is sanctioned or not. Columns (5) and (6) include only the failed audit firms. The results re-affirm that regulatory sanctions adversely affect both the Big N and non-Big N audit firms in terms of their clients’ IPO applications. In short, the results in Table 7 reveal that the negative impact by audit failure exists for small audit firms, regardless of whether the audit firm is sanctioned or not. However, big audit firms are adversely affected only when they are sanctioned on the audit failure. 7.1. Role of political connection on the rejection–failure relation Political connection is usually viewed as resources that can bring in future benefits. In this section, we test whether the adverse consequence on client’s IPO application can be attenuated by the audit firm’s political connection. We argue that it is ex ante unclear on the role of political connection on the audit failure-IPO rejection relation. On the one hand, Yang (2013) documents a decline in the IPO rejection rate of the client that is audited by a politically connected audit firm. In case of audit failure, politically connected firms are better able to minimise the adverse impact than non-connected firms. In this sense, political connection can attenuate the adverse consequence by audit failure and sanctions on client’s IPO application. On the other hand, however, the Examination Committee may realise that the exemption from being sanctioned is probably achieved by political con- nection, rather than not being accountable for the audit failure. Taking the potentially understated sanctions into consideration, the Examination Committee is likely to exert more rigorous review on the IPO clients of the politically connected firms. As a result, the IPO rejection rate in turn increases for clients of politically connected audit firms. To empirically test the role of political connection on the audit failure-IPO rejection relation, we partition the sample into two sub-samples based on whether the IPO applicant is audited by politically connected firms or not. To do so, we follow Yang (2013)approach to identify the political connection of audit firms. Specifically, if any auditor in a particular audit firm is elected as the committee member of the Examination Committee in a given year, then that audit firm is deemed to be politically connected from that year on. Table 8 reports the results of the sub-sample tests. We observe the following findings. First, the coefficient of Auditfail_Post is significantly positive in both column (1) and (2) with a value of 1.834 and 1.181, respectively. And a Chow’s test shows no significant difference between the coefficients in the two sub-samples. We thus conclude that the IPO rejection rate increases after audit failure, regardless of whether the audit firm has political connection or not. Second, column (3) reports significantly positive coefficients of both Sanc_Post and NonSacn_Post, suggesting that for politically connected audit firms, the client’s IPO application is adversely affected regardless of whether the audit firm is 262 H. YUAN ET AL. Table 8. Cross-sectional test: sample partitioned by politically connected and non-politically con- nected audit firm. (1) (2) (3) (4) (5) (6) Non- Non- Non- Politically Politically Politically Politically Politically Politically connected connected connected connected connected connected Auditfail 0.520 −0.020 (0.32) (−0.03) Auditfail_Post 1.834* 1.181** (1.85) (2.02) Sanc −1.318 −0.189 −1.326 −0.400 (−0.61) (−0.25) (−1.08) (−0.48) Sanc_Post 3.956** 1.822** 2.948* 1.727* (2.07) (2.10) (1.76) (1.71) NonSanc 0.316 0.038 (0.19) (0.05) NonSanc_Post 1.883* 0.884 (1.71) (1.31) BigN −0.151 −0.401 −0.096 −0.325 −0.685 −0.539 (−0.18) (−0.77) (−0.10) (−0.55) (−0.76) (−0.66) Size −0.906*** −0.402*** −0.940*** −0.402*** −0.849*** −0.390*** (−2.67) (−4.82) (−2.65) (−4.87) (−2.62) (−3.44) Lev 4.891** 3.935*** 5.171** 3.833*** 4.040* 4.450*** (2.15) (2.84) (2.16) (2.77) (1.78) (2.60) ROA 0.728 5.214 2.514 5.021 4.484 3.367 (0.07) (0.98) (0.23) (0.93) (0.43) (0.48) SOE −1.273 −0.385 −1.450 −0.426 −0.784 −0.647 (−0.90) (−0.50) (−1.00) (−0.55) (−0.57) (−0.63) Top10_IB −1.765* −0.480 −1.699 −0.412 −1.446 −0.378 (−1.70) (−0.91) (−1.61) (−0.77) (−1.35) (−0.53) Constant 6.096 5.076** 6.087 4.867** 6.921 6.278* (0.31) (2.11) (0.31) (2.02) (0.38) (1.8) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.58 0.33 0.59 0.33 0.57 0.30 N 545 744 545 744 466 505 [Sanc_Post]=[NonSanc_Post] 3.27* 5.89** The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. sanctioned or not after an audit failure. But the sanctioned firms are more adversely affected than the non-sanctioned firms, as indicated by the significant difference between the coefficients of Sanc_Post and NonSanc_Post. Third, column (4) reports a significantly positive (insignificant) coefficient of Sanc_Post (NonSanc_Post), showing that for audit firms without political connections, the IPO clients are negatively affected only when the audit firms are sanctioned. The IPO rejection rate is not impacted if the audit firm experiences an audit failure but is not sanctioned. Fourth, a Chow’s test shows significant difference between the coefficients of Sanc_Post in column (3) and column (4), supporting the argument that the Examination Committee exerts a more rigorous review on the clients of politically connected audit firms than those of non-connected audit firms after sanctions. Last but not least, when we exclude the non-failed audit firms, we find that the coefficient of Sanc_Post is significantly positive in both columns (5) and (6). That is, the IPO client is adversely affected by regulatory sanctions regardless of whether the audit firm is politically connected or not. CHINA JOURNAL OF ACCOUNTING STUDIES 263 In short, the results in Table 8 reveal that the IPO clients are adversely affected by both audit failure and regulatory sanctions on the failure, regardless of whether the audit firm has political connection or not. However, politically connected audit firms are more negatively affected if they are subsequently sanctioned than the non-connected counterparts. 7.2. The influence of the board of IPO listing on the rejection–failure relation The CSRC established the GEM board in 2009 to support the capital raising demands of innovative growth enterprises. As introduced in Section 2, two Examination Committees operated together before 2017 (within our sample period). One committee reviews IPO applicants for the main board and the SME board, and the other one reviews for the GEM board, respectively. In this section, we investigate whether the adverse consequence of audit failure on IPO clients differs between the clients’ board of listing. We argue that it is ex ante unclear of which board is more adversely affected. On the one hand, compared with IPO applications on the main board and the SME, those on the GEM are typically smaller sized, riskier, and associated with more uncertainties in the future operating performance. In addition, the GEM stocks are higher priced than those on the main board and the SME board The price premium may induce earnings management behaviour on the GEM board to inflate the stock prices. In this sense, the Examination Committee is likely to exercise more rigorous review on the IPO applicants on the GEM board than those on the main and SME boards to avoid risk. As a result, the adverse consequence by the audit failure is aggravated if the IPO applicant plans to list on the GEM board. On the other hand, due to the risky nature of the innovative growth enterprises, the CSRC imposes more stringent supervision on the companies that are listed on the GEM board than those on the main board. For example, the investment bank is required to make professional judgement on whether the IPO applicants on the GEM board can achieve sustainable profits and satisfy the listing requirements. The investment bank is also required to issue opinion on the IPO applicants’ growth potentials and innovative abilities. In addition, after the IPO applicant gets successfully listed, the investment bank should continuously supervise the applicant for three years, in comparison to two years’ supervision period as per required by the main and SME boards. These stringent requirements are expected to filter high-quality IPO applicants and serve as substitutes for the Examination Committee’s review. Thus, the Examination Committee may exer- cise less rigorous review on the IPO applicants on the GEM board than those on the main and SME boards. At the same time, among the 116 audit failures documented in Table 2, only six failures incurred on the GEM board The relatively low frequency of audit failure on the GEM board gives little information and references to the Examination Committee regarding the clients of the failed firms. In this sense, we expect that the adverse consequence by the audit failure is attenuated if the IPO applicant plans to list on the GEM board. For example, the median value of the price earnings (PE) ratio is 30.77 for main and SME boards while that for the GEM board is 50.80. On average, the PE ratio of the GEM board is 50% to 60% higher than that of the main and SME boards.. We observe relatively few audit failures on the GEM board probably because of the shorter history of the GEM board than the main and SME boards. Another possible reason may be because of the rigorous review mechanisms on the GEM board discourage accounting frauds by the IPO applicants.. 264 H. YUAN ET AL. Table 9. Cross-sectional test: sample partitioned by board of IPO listing. (1) (2) (3) (4) (5) (6) Main & SME GEM Main & SME GEM Main & SME GEM Auditfail −0.769 1.020 (−1.05) (0.93) Auditfail_Post 1.895*** 0.198 (2.91) (0.28) Sanc −1.246 0.801 −0.513 −0.182 (−1.32) (0.63) (−0.65) (−0.19) Sanc_Post 2.614** 1.316 1.486* 1.530 (2.56) (1.18) (1.69) (1.35) NonSanc −0.567 1.092 (−0.73) (0.94) NonSanc_Post 1.791** −0.354 (2.53) (−0.40) BigN −0.427 −0.773 −0.244 −0.885 −0.867 −1.056 (−0.77) (−1.12) (−0.39) (−1.19) (−1.32) (−1.32) Size −0.502*** −0.608*** −0.514*** −0.621*** −0.485*** −0.643*** (−4.49) (−3.47) (−4.48) (−3.58) (−3.79) (−2.91) Lev 6.271*** −0.708 6.169*** −0.839 5.525*** −0.151 (4.39) (−0.29) (4.24) (−0.34) (3.34) (−0.06) ROA −2.054 4.273 −1.621 4.926 −7.900 6.209 (−0.29) (0.72) (−0.23) (0.82) (−0.87) (0.95) SOE −0.699 0.000 −0.672 0.000 −0.846 0.000 (−1.01) (.) (−0.98) (.) (−1.01) (.) Top10_IB −0.434 −1.575 −0.375 −1.556 −0.054 −1.421 (−0.80) (−1.48) (−0.69) (−1.45) (−0.08) (−1.28) Constant 6.494** −2.739 6.479** −3.380 7.519** 0.962 (2.34) (−0.00) (2.31) (−0.00) (2.34) (0.00) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.44 0.42 0.45 0.43 0.46 0.38 N 791 462 791 462 607 350 [Sanc_Post]=[NonSanc_Post] 0.79 1.82 The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. Table 9 reports the regression results of the sub-samples that are partitioned by the IPO client’s board of listing. As shown, the coefficient of Auditfail_Post is significantly positive in column (1) while it becomes insignificant in column (2). That is, the IPO client is more adversely affected by audit failure if it is listed on the main or SME board. However, the client’s IPO application is not affected by audit failure if it plans to list on the GEM board. With respect to the influence of subsequent sanctions on audit failure, we find that both coefficients of Sanc_Post and NonSanc_Post are significantly positive in the sub-sample of IPO applicants on main and SME board (column 3). In addition, the two coefficients are not significantly different from each other. Thus, column (3) provides evidence that for IPO client to be listed on the main or SME board, it is adversely affected by audit failure regardless of whether the audit firm is subsequently sanctioned or not. In comparison, column (4) shows that neither coefficient of Sanc_Post or NonSanc_Post significantly differs from zero, suggesting that the IPO client on the GEM board is not affected by audit failure. Columns (5) and (6) re-affirm the results on regulatory sanctions. As indicated by the marginally significant coefficient of Sanc_Post in column (5) and the insignificant coeffi- cient of Sanc_Post in column (6), we do not find strong evidence on the adverse influence by audit sanction on either the IPO clients on main and SME boards or those on the GEM board. CHINA JOURNAL OF ACCOUNTING STUDIES 265 In short, Table 9 indicates that the adverse consequence by audit failure as well as regulatory sanction on IPO rejection rate exists only when the IPO applicants choose to list on the main and SME boards. 8. Robustness tests 8.1. Excluding the impact of appropriate audit opinions on the rejection–failure relation In our main test in Table 6, we identify an audit failure by a particular audit firm as long as the firm audits at least one listed company that is found to conduct accounting fraud. However, as described in Table 3, 9.34% of the accounting frauds receive modified audit opinions. That is, some audit firms issue appropriate audit opinions regarding clients’ accounting frauds. In this case, the audit firm should not be held accountable. That is, our definition of audit failure in the main test is likely to be overestimated. To address this issue, we identify the audit firms that issue modified audit opinions to all the fraud-years and exclude the IPO clients of these audit firms from our sample We then re-estimate Table 10. Robustness test: exclude IPO clients of audit firms that issue appropriate audit opinions. (1) (2) (3) Auditfail −0.097 (−0.177) Auditfail_Post 1.138** (2.522) Sanc −0.571 −0.475 (−0.811) (−0.819) Sanc_Post 2.123*** 1.576** (2.893) (2.317) NonSanc 0.066 (0.112) NonSanc_Post 0.887* (1.758) BigN −0.595 −0.468 −0.818* (−1.441) (−1.042) (−1.703) Size −0.473*** −0.473*** −0.467*** (−6.093) (−6.164) (−5.106) Lev 4.037*** 3.910*** 3.583*** (3.776) (3.627) (2.901) ROA 1.897 2.207 0.939 (0.424) (0.485) (0.178) SOE −0.408 −0.436 −0.555 (−0.648) (−0.689) (−0.750) Top10_IB −0.633 −0.587 −0.519 (−1.442) (−1.325) (−1.002) Constant 6.285*** 5.885*** 7.153*** (3.031) (2.816) (2.933) Year Yes Yes Yes Industry Yes Yes Yes Pseudo R 0.38 0.39 0.38 N 1,546 1,546 1,007 [Sanc_Post]=[NonSanc_Post] 2.99* The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. We examine the relation between audit opinions and accountability by the audit firm. Untabulated results show that the audit firm is more likely to be exempted from sanction if it issues modified audit opinions on all the fraud-years.. 266 H. YUAN ET AL. Equations (1) and (2) based on this reduced sample of 1,546 IPO applicants. The results are reported in Table 10.We find that the results are statistically similar as those reported in Table 6: the client’s IPO application is adversely influenced after an audit firm involves in audit failure, and the influence is aggravated if the audit firm is subject to regulatory sanctions. That is, our main findings are not unduly influenced by the potentially upward biased measurements of Auditfail and Auditfail_Post. 8.2. Placebo test In our main analysis, an audit failure is identified based on the CSRC announcement year as described in Table 2. To ensure that the impact on the IPO rejection rate is attributed to audit failure and audit sanctions, we conduct two placebo tests following Ke and Zhang (2019)’s approach. Specifically, rather than the CSRC announcement year, we define two pseudo-event years, three years before and three years after the CSRC announcement year. Then, Auditfail_Post, Sanc_Post,and NonSanc_Post are re-defined according to the pseudo- event years. Table 11. Robustness test: use of pseudo-event years. (1) (2) (3) (4) (5) (6) Pseudo-event Pseudo-event Pseudo-event Pseudo-event Pseudo-event Pseudo-event year = t-3 year = t + 3 year = t-3 year = t + 3 year = t-3 year = t + 3 Auditfail 0.275 0.559 (0.55) (1.18) Auditfail_Post 0.561 −0.489 (1.20) (−0.89) Sanc 0.064 0.699 −0.069 0.330 (0.11) (1.31) (−0.14) (0.72) Sanc_Post −0.559 −2.252 −0.572 −1.707 (−0.68) (−1.03) (−0.69) (−0.93) NonSanc 0.345 0.495 (0.65) (0.96) NonSanc_Post 0.297 −0.339 (0.57) (−0.59) BigN −0.698* −0.477 −0.493 −0.576 −0.724 −0.970** (−1.69) (−1.14) (−1.13) (−1.29) (−1.52) (−2.07) Size −0.450*** −0.456*** −0.450*** −0.463*** −0.456*** −0.474*** (−6.11) (−6.09) (−6.07) (−6.03) (−5.01) (−4.76) Lev 3.912*** 3.815*** 3.839*** 3.856*** 3.770*** 3.930*** (3.68) (3.57) (3.63) (3.61) (3.13) (3.21) ROA 1.397 1.699 1.174 1.559 0.308 0.562 (0.32) (0.39) (0.26) (0.35) (0.06) (0.11) SOE −0.400 −0.397 −0.464 −0.367 −0.566 −0.480 (−0.64) (−0.63) (−0.74) (−0.59) (−0.77) (−0.67) Top10_IB −0.600 −0.628 −0.606 −0.619 −0.567 −0.609 (−1.38) (−1.45) (−1.39) (−1.42) (−1.11) (−1.19) Constant 6.269*** 6.282*** 7.468*** 6.190*** 6.285*** 7.630*** (3.10) (3.09) (3.14) (3.04) (3.04) (3.05) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.38 0.38 0.39 0.38 0.39 0.38 N 1,600 1,600 1,600 1,600 1,080 1,080 *, ** The t-statistics are in parentheses. The superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. CHINA JOURNAL OF ACCOUNTING STUDIES 267 The results of the placebo test are reported in Table 11 with columns (1), (3) and (5) use three years before the CSRC announcement year as the pseudo-event and columns (2), (4), and (6) use three years after the CSRC announcement year as the pseudo-event. We find that none of the variables of interest (Auditfail_Post, Sanc_Post, and NonSanc_Post) significantly differs from zero. The results in Table 10 thus add our confidence that the findings on the adverse impact on client’s IPO application is attributed to audit failure and regulatory sanctions we identify in our main tests. 9. Conclusions and implications This study investigates one of the adverse consequences of audit failure. Specifically, we are interested in how audit failure adversely affects its client’s IPO application. We document the following findings. First, the client’s IPO rejection rate significantly increases within three years after the audit firm experiences an audit failure. Second, the client’s IPO application is adversely affected regardless of whether the audit firm is subsequently sanctioned on the audit failure. However, the client’s IPO rejection rate is significantly higher for sanctioned audit firms than that for failed but not sanctioned audit firms. Third, cross-sectional analyses suggest that the audit failure-IPO rejection rate relation varies across different types of audit firms. Specifically, the client’s IPO application is adversely affected as long as a non-Big N audit firm experiences an audit failure. However, in case of a Big N audit firm, the client’s IPO application is adversely affected only when the Big N audit firm is sanctioned on the audit failure. In terms of political connections, we find that the client’s IPO rejection rate increases significantly as long as a politically connected audit firm experiences an audit failure. However, in case of a non- politically connected audit firm, the client’s IPO rejection rate increases only when the audit firm is sanctioned after the audit failure. Fourth, the audit failure-IPO rejection rate relation also varies across the IPO applicant’s board of listing. We find that the adverse impact by audit failure and regulatory sanction is mainly driven by the IPO applicants on the main and SME boards. Last but not least, our results hold by various robustness tests including the use of a refined sample and the use of pseudo-event years. We enrich the literature on the consequences of audit failure. Our study also provides implications to regulatory bodies from the following two perspectives. First, given that China currently adopts the approval system for IPO applica- tion, the process of reviewing and filtering high-quality IPO applicants is especially important to ensure a well-functioned capital market and to protect the investors. Thus, it is meaningful to understand the decision process of the Examination Committee. Given our findings that the Examination Committee does take into account of the audit failure and regulatory sanctions when reviewing the audit firm’s IPO clients, we confirm the informativeness of audit failure to regulatory bodies. That is, besides the capital market participants, government agencies also utilise the signals sent by audit failure. Thus, we call for more timely and detailed disclosures on the audit failure and the audit firm’s liability in the audit failure. Second, our finding indicates that audit firms suffer reputational losses even if the audit firm is not sanctioned on the audit failure. On the one hand, this finding alerts the audit firms to be more cautious in screening high-quality clients. On the other hand, it calls for more detailed and unbiased disclosures on the reasons why the audit firm is exempted 268 H. YUAN ET AL. from sanctions so that investors and other information users can properly judge audit firm’s role in the audit failure. Acknowledgments Accepted by Xi Wu. We appreciate the insightful comments and suggestions of two anonymous referees and participants at China Journal of Accounting Studies Conference. All remaining errors and omissions are our own. This study is funded by the National Natural Science Foundation of China [No. 71772044]. Disclosure statement No potential conflict of interest was reported by the authors. References Agrawal, A., & Cooper, T. (2017). Corporate governance consequences of accounting scandals: Evidence from top management, CFO and auditor turnover. Quarterly Journal of Finance, 7(1), 1650014.1–1650014.41. 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(2011). On factors affecting the penalties of audit firms by regulatory authority: Evidence from auditing regulation of capital markets in China. Journal of Finance and Economics,(6), 67–78. In Chinese. Chen, Y., Zheng, D., & Li, L. (2014). Non-SOE ipo firm’s relationship with stock issuance examination and verification committee, IPO verification and future performance. China Journal of Accounting Studies, 2,12–19. In Chinese. Davis, L.R., & Simon, D.T. (1992). The impact of SEC disciplinary actions on audit fees. Auditing: A Journal of Practice & Theory, 11(1), 58–68. DeAngelo, L.E. (1981). Auditor size and audit quality. Journal of Accounting and Economics, 3(3), 183–199. Dechow, P.M., Ge, W., & Schrand, C. (2010). Understanding earnings quality: A review of the proxies, their determinants and their consequences. Journal of Accounting and Economics, 50(2–3), 344–401. Dechow, P.M., Sloan, R.G., & Sweeney, A.P. (1996). 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Firth, M., Mo, P.L.L., & Wong, R.M.K. (2014). Auditors’ reporting conservatism after regulatory sanctions: Evidence form China. Journal of International Accounting Research, 13(2), 1–24. Francis, J.R. (2004). What do we know about audit quality? The British Accounting Review, 36(4), 345–368. Hennes, K.M., Leone, A.J., & Miller, E.P. (2014). Determinants and market consequences of auditor dismissals after accounting restatements. The Accounting Review, 89(3), 1051–1082. Ke, B., & Zhang, X. (2019). How to make public enforcement work in weak investor protection countries? Evidence from China. Working Paper. Retrieved from https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=2606669 Li, M., & Liu, F. (2012). Social capital, property rights, and qualification of listing: Evidence from IPO on the SME board. Management World, 11, 110–123. In Chinese. Li, Y., & Yuan, H. (2017). Regulatory sanctions and reputation of investment bank. Working Paper. Fudan University and Shanghai University. 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The consequence of audit failure on audit firms: evidence from IPO approval in China

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The consequence of audit failure on audit firms: evidence from IPO approval in China

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This paper examines a potential adverse consequence of audit failure. We study whether and how the audit firm’s audit failure impacts its client’s Initial Public Offering (IPO) rejection rate. Our empirical results show that the client’s IPO application rejection rates increases significantly after the audit failure. The significant increase in the IPO rejection rate holds regardless whether the audit firm is subject to regulatory sanctions on the audit failure or not....
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© 2019 Accounting Society of China
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10.1080/21697213.2019.1676064
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CHINA JOURNAL OF ACCOUNTING STUDIES 2019, VOL. 7, NO. 2, 245–269 https://doi.org/10.1080/21697213.2019.1676064 ARTICLE The consequence of audit failure on audit firms: evidence from IPO approval in China a a b a Hongqi Yuan , Chujun Zhang , Desong Kong and Haina Shi a b School of Management, Fudan University, Shanghai, China; Accounting School, Shanghai University of International Business and Economics, Shanghai, China ABSTRACT KEYWORDS Audit failure; regulatory This paper examines a potential adverse consequence of audit sanction; audit firm; IPO failure. We study whether and how the audit firm’s audit failure impacts its client’s Initial Public Offering (IPO) rejection rate. Our empirical results show that the client’s IPO application rejection rates increases significantly after the audit failure. The significant increase in the IPO rejection rate holds regardless whether the audit firm is subject to regulatory sanctions on the audit failure or not. However, the sanctioned audit firm’s clients experience significantly higher IPO rejection rates than the non-sanctioned audit firm’s clients. Our further analysis reveals that the adverse outcome on clients’ IPO application varies by types of audit firm and by board of IPO listing. 1. Introduction Audit failure can significantly impairs audit firm reputation and results in various adverse consequences. We study one type of potential consequences of audit failure: whether and how audit failure impacts its clients’ IPO rejection rates. The existing literature on audit failure examines either the direct economic consequences in terms of a decrease in market share and audit fees (Davis & Simon, 1992; Dopuch & Simunic, 1982; Firth, 1990; Sami, Kim, Zhou, & Fang, 2012; Wilson & Grimlund, 1990), or the indirect consequences in terms of a decline in the client’s financial statements credibility, a decline in the client’s market value, and an increase in the client’s cost of capital (Asthana, Balsam, & Krishnan, 2010; Cahan & Zhang, 2006; Chaney & Philipich, 2002; Dechow, Ge, & Schrand, 2010; Dechow, Sloan, & Sweeney, 1996; Firth, 1990; Moreland, 1995; Nagy, 2005). However, the existing literature keeps silent on whether and how audit failure affects government decision. Based on the IPO approval system in China, the current study aims to fill this void in literature. Specifically, we provide empirical evidence on the impact of audit failure on IPO decisions which are made by the Stock Issuance Examination Committee (here- after the Examination Committee) of China Securities Regulatory Commission (hereafter the CSRC). CONTACT Hongqi Yuan yuanhq@fdsm.fudan.edu.cn School of Management, Fudan University, 670 Guoshun Road, Shanghai, China Paper accepted by Xi Wu. © 2019 Accounting Society of China 246 H. YUAN ET AL. In this study, an audit failure is identified if any client of an audit firm involves in accounting fraud We call the audit firm that experiences at least one audit failure as failed audit firms. If the failed audit firms are subsequently sanctioned by the CSRC, then these firms are at the same time sanctioned audit firms. In comparison, if the failed audit firms are exempted from regulatory sanction, then these firms are non-sanctioned audit firms. It is of great importance to study how audit failure affects the Examination Committee’s decision given the critical role played by the Examination Committee in the IPO approval process. While the quality of IPO applicants is crucial for the overall quality of the equity capital market, we need a better understanding on the factors that the Examination Committee considers in the decision-making process. We pay particular attention to the question of whether the Examination Committee conducts rigorous review towards IPO clients of failed audit firms. We also take a step further beyond the audit failure to study how regulatory sanctions affect the Examination Committee’s decision. While it is not surprising that regulatory sanctions result in adverse consequences, we are interested in whether the Examination Committee also takes into account of the audit failures that are not subject to regulatory sanctions. By doing so, we attempt to obtain a comprehensive understanding of how audit failure and regulatory sanctions affect the Examination Committee’s decision set during the IPO process. Based on a sample of IPO applications during the sample period of 2004 to 2016, we first document that audit failure by the audit firm adversely affect its clients’ IPO applica- tion outcomes, that is, the clients’ IPO rejection rates significantly increase after the audit firm experiences an audit failure. The adverse influence on the client’s IPO application holds regardless of whether the audit firm is subject to regulatory sanctions on the audit failure or not. However, the clients’ IPO rejection rates are significantly higher for audit firms that are subsequently sanctioned, compared with those that are not sanctioned. Our further analyses reveal the following cross-sectional differences on the relation between audit failure and clients’ IPO rejection rates: (i) for the Big N audit firms (including the international Big 4 and the domestic Big 10 audit firms) and for non-politically connected audit firms, the significant increase in the clients’ IPO rejection rates is found only when the Big N audit firms and the non-politically connected audit firms are sanctioned by the CSRC; (ii) for non-Big N audit firms and for politically connected audit firms, the clients’ IPO rejection rates increase significantly as long as the audit firm experiences an audit failure; and (iii) the adverse impact of audit failure is mainly driven by the IPO applicants on the Main board and the Small- and Medium-sized Enterprises board (hereafter the SME board). Our study contributes to the literature in the following ways. First, the existing literature on the consequences of audit failure typically investigates how the audit failure adversely impacts the audit firms(Davis&Simon, 1992;Dopuch& Simunic, 1982;Firth, 1990;Samietal., 2012;Wilson&Grimlund, 1990), or the informativeness of the clients’ financial statements (Asthana et al., 2010; Cahan & Zhang, 2006;Chaney& Philipich, 2002;Dechowetal., 2010, 1996;Firth, 1990;Moreland, 1995;Nagy, 2005). This study furthers our understanding on the adverse impact of audit failure on audit firms Existing literature either provides definition of audit failure (e.g. Arens, Elder, and Beasley, 2017; Francis, 2004) or lists the characteristics of audit failure (DeFond & Zhang, 2014). Based on the literature, an audit failure incurs if an auditor (i) fails to uncover or report the fact that the client did not properly follow the accounting standards, and (ii) issues an inappropriate audit opinion. Thus, client’s accounting fraud is a typical case of audit failure.. CHINA JOURNAL OF ACCOUNTING STUDIES 247 from the perspective of government decision-making. Second, we distinguish between the consequences of audit firms being sanctioned and not being sanctioned after an audit failure. Previous studies on audit failure in general focus on the audit firms that are subject to sanctions. In comparison, we document an adverse impact even when the audit firm is not subsequently sanctioned on the audit failure. Third, we provide evidence that the adverse impact of audit failure varies by types of audit firm and by board of IPO listing. The findings help the market participants better understand the roles played by audits. More importantly, the evidence helps evaluate the efficiency of the regulatory monitoring on audit failures. The remainder of this paper is organised as follows: Section 2 introduces the institutional background of the IPO system in China, Section 3 reviews relevant literature and develops the hypotheses. We describe our sample and descriptive statistics in Section 4. The research design and empirical results are discussed in Section 5. We conduct several cross-sectional analyses in Section 6 and the robustness tests in Section 7.Finally, Section 8 concludes. 2. Institutional background: the IPO system in China The IPO system in China has gone through two stages: the quota system and the approval system. The quota system was adopted before 2000. Under the quota system, the local government or an industrial department of the State Council, based on the pre-determined quota set by the central government, were delegated to choose and then recommend a particular company to get listed. The number of shares to be issued by the company was also pre-determined. Then, the stock issuance was directly approved by the CSRC. The quota system was replaced by an approval system in 2001. Under the approval system, the investment banks, rather than the local government or industrial departments of the State Council, play the role to select and to recommend potential IPO issuers. The approval system significantly strengthens the responsibilities of the investment banks as well as other market intermediaries. The decisions such as the number of shares to be issued and the amount of proceeds to be raised are made based on the capital demand of the IPO applicant. The Examination Committee of the CSRC conducts an independent review of the stock issuance. The Examination Committee of the CSRC has undertaken a decisive role in the stock issuance process since its establishment. We first briefly review the regulations related to the Examination Committee. It was set up by the CSRC based on the ‘Regulations of the CSRC for the Stock Issuance Examination Committee’ (hereafter the SIEC Regulations) which was issued on 16 September 1999. The SIEC Regulations clarified the rights and responsibilities of the Examination Committee. Since then, the Examination Committee has been delegated the right to decide whether an issuer can go public. On 24 November 2003, the CSRC announced the ‘Measures of CSRC for the Stock Issuance Examination Committee’ (hereafter the SIEC Measures). The main purpose of the SIEC Measures was to reform the stock issuance examination system to improve the transparency of the working procedures of the Examination Committee. To achieve this, the SIEC Measures specified that the committee members should be recommended by relevant administrative organisations, industry-wide self-regulatory organisations (such as the Chinese Institute of Certified Public Accountants Association), research institutions, and universities. Each term of the Examination Committee should be composed of 25 committee members, whose personal information 248 H. YUAN ET AL. is publicly available on the official website of the CSRC. On 13 May 2009, the CSRC set up another Examination Committee for the Growth Enterprise Market (the GEM) to support the establishment of the GEM board. The two Examination Committees operated together then, one for the main and SME boards and one for the GEM board, respectively. The SIEC Measures were amended by the CSRC on 7 July 2017. Given a convergence between the main and SME boards and the GEM board in terms of basic logics and criterion of stock issuance examination, the two Examination Committees merged based on the amended SIEC Measures. The merge was expected to optimise the allocation of administrative resources and to improve the work efficiency of the Examination Committee. Under the approval system, the Examination Committee is the critical player that represents the government’s interest. We next introduce another important player in the IPO process, the representative sponsors, who act as capital market intermediaries to help the issuers go through the IPO process. The sponsorship system refers to a system in which qualified sponsors recommend issuers that satisfy the listing requirements to issue and to publicly list their shares. The sponsorship system requires that the sponsors should provide continuous monitoring, supervision, guidance and credit guarantees to the issuers they recommend with respect to the issuers’ information disclosure quality and the commitment the issuers made. Under the sponsorship system, the investment bank and its representa- tive sponsors take the following crucial responsibilities. First, they are responsible for the recommendation and counselling of the share issuance and listing. Second, they carry out due diligence to verify the truthfulness, accuracy, and completeness of the issuers’ docu- ments. Third, they assist the issuers to establish a strict information disclosure system and assume joint and several liability regarding issuers’ information disclosure. Last but not least, they make a recommendation to the CSRC. The issuer needs to go through the following main examination procedures for a successful IPO according to the ‘Workflow for IPO Stock Issuance Examination by CSRC’: case acceptance by the supervision department of CSRC, preliminary feedback, preliminary examination meeting, formal review and approval meeting by the Examination Committee, closing the case, and final approval for public issuance by the CSRC. Among these procedures, one of the most critical step is the formal review and approval meeting. At the meeting, the Examination Committee assesses all the relevant documents, such as the issuer’s prospectus, and the preliminary review report by other functional departments of the CSRC. Then, the committee members vote on the IPO application and reach a review opinion on whether the issuer should be approved or not for a public listing. The review opinions by the Examination Committee are typically based on by the Securities Law, the Company Law and administrative regulations issued by various government departments and the CSRC. As the most important step in the stock issuance process, the Examination Committee is responsible for selecting high-quality issuers to enhance the quality of listed companies and thus the overall quality of the capital market. On the one hand, the regulatory authorities have issued a series of regulations to specify the listing requirements and to stipulate the information disclosure requirements. These requirements provide basis for the Examination Committee to reach a review opinion. On the other hand, the committee members also exercise professional judgement to comprehensively review the issuer’s prospectus and the preliminary review report. In reviewing a particular IPO application, the Examination Committee plays the following key roles: (i) reviews whether the CHINA JOURNAL OF ACCOUNTING STUDIES 249 application for stock issuance satisfies relevant regulations; (ii) reviews and assesses the statements and reports submitted by the professional intermediaries, including the spon- sors, the auditor, the attorney, and the asset appraiser; (iii) examines the preliminary review report prepared by other functional departments of the CSRC; and (iv) submits a review opinion on the IPO application. Given the critical roles of the Examination Committee in the IPO decision-making, the CSRC implements several bonding mechanisms on the commit- tee members to ensure the effective operation of the Examination Committee, including the performance evaluation system, requiring commitments before the review and approval meeting, the accountability system, reminder through conversation, and the whistle-blowing system. Although the CSRC makes the final decision of whether to approve or disapprove an issuer’s IPO application upon the review opinion submitted by the Examination Committee. In practice, the CSRC never rejects an IPO application that is approved by the Examination Committee. The final result of the IPO application is then publicly announced on CSRC’s official website after the CSRC makes the final decision. 3. Literature review and hypotheses development There is a large body of literature on whether and how regulatory sanctions after audit failures impacts the audit firms. Theliteraturedocuments significant impairment on the audit firm’s reputation by the regulatory sanctions. From the perspective of the audit firm’sexisting clients, Chaney and Philipich (2002) examine how the Enron event impacts Arthur Anderson and find significantly negative market reactions of Arthur Anderson’sother clientsonits investigation by the SEC. Fang, Xu, and Hong (2006) document a similar phenomenon in the Chinese context. They study how the accounting fraud conducted by Yinguangxia impacts its audit firm, Zhongtianqin. The market reacts significantly negative to Zhongtianqin’sother clients when the CSRC announced a regulatory sanction on Zhongtianqin. From the per- spective of the audit firm per se,Firth (1990) documents that regulatory sanction leads to decreases in the audit firm’smarketshare and audit fees,aswellasthe stockpricesofthe firm’s other clients. Sami et al. (2012) find a higher probability of audit firms being replaced and lower audit fees after the regulatory sanction. Davis and Simon (1992) document lowered audit fees charged to the new clients after the sanctions. Wilson and Grimlund (1990)show that sanctioned audit firms have more difficulties to retain existing clients as well as to attract new clients. From the perspective of informational consequences, Moreland (1995)docu- ments a decrease in the clients’ earnings response coefficient subsequent to audit firm’s sanction. The other stream of literature studies the relation between financial statement restate- ment and audit firm switch. While Hennes, Leone, and Miller (2014) document that the audit firm is more likely to be dismissed by the board of directors after a restatement of financial statement, Agrawal and Cooper (2017)failto find significant association between the likelihood of audit firm switch and restatement. Ma, Zhang, and Yang (2016)study this issue in the Chinese setting and find that audit firm switch is related to types of restatement. The listed company is likely to switch to a reputable audit frim if the restatement is a fraud- related one. However, if the restatement is related to misstatements, the listed company tends to switch to an audit firm that is more likely to agree with the listed company. 250 H. YUAN ET AL. The above literature discusses the reputational losses of audit firms after the audit failures from the perspectives of clients and investors of the clients. However, very few papers examine how the government, as one of the important users of audit information, reacts to audit failures. As introduced in Section 2, the Examination Committee plays a crucial role in the IPO process in China. The main responsibilities to review and decide the outcome of an IPO application lie on the Examination Committee. To ensure the quality of listed companies and to enhance the overall quality of the capital market, the Examination Committee needs to maintain relatively stringent criterion when reviewing the IPO applications. It is likely to take into account various information related to the IPO applicants during the review process. Audit firm, as one of the most important financial intermediaries during the IPO process, certifies the IPO applicant’s financial-related infor- mation. It is thus intuitive for the Examination Committee to take the auditing-related information into the decision-making process. We expect that the Examination Committee pays a lot of attention to the audit quality and keeps cautious to the clients of the failed audit firms due to the following reasons. First, according to the amended SIEC Measures, the CSRC implements an accountability system. The Examination Committee will be held accountable if it makes inappropriate review decisions. The committee members may be (i) reminded through conversation, (ii) criticised, (iii) open censured, or (iv) dismissed by the CSRC. The type of punitive measures depend on how serious the problem is in the decision-making process. Second, the CSRC adopts a performance evaluation system that scores the committee members. The score is directly related to whether a particular member’s contract will be renewed for the next term. Third, the Examination Committee is mainly composed of the regulatory officials in the CSRC and external professionals. These committee members tend to keep a high standard in reviewing the IPO applications to maintain their professional reputations. Thus, the Examination Committee may be particu- larly concerned about the potential risks underlying the audit failure and thus exerts more caution in reviewing the firm’s IPO clients. We therefore hypothesise that: H1: The IPO client’s rejection rate significantly increases after the audit firm experiences an audit failure. The above H1 compares the client’s IPO rejection rate in the pre- and post-audit failure period. However, an audit failure does not necessarily result in a regulatory sanction. Specifically, the Securities Law stipulates that ‘if the securities service institution has not diligently performed its duties, or if the documents prepared or issued by the institution have false or misleading statements or material omissions, the institution shall be (i) required to correct the documents, (ii) confiscated all the related revenues, (iii) suspended or disqualified the securities service business licence, and (iv) imposed a fine with an amount ranging from one time to five times of the revenue.’ The Securities Law also specifies that the person who is in charge of the business and those who are directly responsible for the business should be publicly warned and be disqualified from profes- sional practices, in addition to a fine ranging from 30,000 to 100,000 RMB. While some audit firms that experience audit failure are subject to regulatory sanctions (the sanctioned firms), others are exempted from regulatory sanctions (the non- sanctioned firms). A stream of literature thus examines the determinants of an audit firm being sanctioned (Chen, Qiu, & Xu, 2011; Firth, Mo, & Wong, 2005; Wu, 2007). This CHINA JOURNAL OF ACCOUNTING STUDIES 251 literature documents that the CSRC considers factors such as the inherent risks of the auditing tasks, the natures and types of accounting frauds conducted by the clients. The existing literature finds that the regulatory departments tend to selectively enforce the regulations towards accounting frauds (Chen, Jiang, Liang, & Wang, 2011). In terms of audit failures, one can similarly expect selective enforcement on the audit firms because the audit firms may try to be exempted from liability through rent seeking. However, the audit firm whose client is found to be fraudulent may still suffer a reputational loss even if it is not sanctioned. Committee may consider the potential risks and exert caution in reviewing the IPO clients of non-sanctioned audit firms. In practice, the sanction notices issued by the regulatory authorities on audit firms reveal that the main reasons for the audit firms being sanctioned include defective audit procedures and lack of professional scepticisms. That is, regulatory sanction serves as an indicator of weak audit quality. In the IPO application setting, the Examination Committee is thus likely to question the accounting information quality of the sanctioned audit firms’ clients due to the poor audit quality. As a result, the Examination Committee may conduct a more cautious scrutiny on the IPO applicants who are clients of the sanctioned audit firms, which in term affects the IPO rejection rates. We thus make the following two hypotheses on regulatory sanction that: H2a: The IPO client’s rejection rate significantly increases regardless of whether the audit firm is subject to regulatory sanction on an audit failure H2b: The IPO client’s rejection rate is significantly higher for a sanctioned audit firm, compared with a non-sanctioned audit firm. 4. Sample 4.1. Sample selection and distribution Our sample covers all the IPO applications in the Chinese A-share market for the period of 2004 to 2016. We start from 2004 because the IPO approval system experienced asignificant reform by the SIEC Measures in November 2003. The reform strengthened the role of the representative sponsors. Since then, the IPO system has been largely stable. On the other hand, financial data of the IPO applicants that were rejected by the CSRC was not publicly available before 2003. As a result, it was not possible to compare the successful IPOs with the failed ones before 2003. The data is obtained from the Wind database. Specifically, the CSRC announces the decision of each IPO application on its official website. Then, the Wind database collects all the IPO application outcomes. The database also provides financial data of the IPO applicants, which is disclosed in the prospectus. We are left with 1,605 IPO applications after dropping observations with missing values for necessary variables. Table 1 shows the distribution of the IPO applications by year and by industry, respectively. As shown, year 2010 has the largest number of IPO applications (311) while year 2004, 2006 and 2008 have relatively fewer IPO applications. More than 60% of the sample comes from the manufacturing industry (1,021), followed by the information technology industry. 252 H. YUAN ET AL. Table 1. Sample distribution – The IPO sample. Year N Industry N 2004 37 Manufacturing 1,021 2006 60 Information technology 217 2007 122 Business services 81 2008 62 Wholesale & retail 52 2009 130 Construction 47 2010 311 Sports & entertainment 35 2011 242 Financial & insurance 34 2012 105 Transportation, warehouse, & postal services 31 2014 94 Mining 30 2015 200 Electricity, heat, gas, & water supply 22 2016 242 Agriculture, forestry, animal husbandry, & fishery 21 Real estate 9 Conglomerate 5 Total 1,605 1,605 4.2. Distribution of the audit failures We first identify the audit firms that experienced audit failures (the failed audit firms) and those that did not experienced any failures (the non-failed audit firms). In 2001, the CSRC began to disclose all the sanctions and penalties on the listed companies that conduct accounting frauds. The corresponding audit firms are then defined as failed audit firms. At the same time, the CSRC also discloses the sanctions and penalties on the audit firm if the audit firm is held accountable to the accounting fraud. These audit firms are defined as the sanctioned audit firms. Thus, the sanctioned audit firms are sub-samples of the failed audit firms because some failed firms are not subject to regulatory sanctions. We hand-collect all the accounting frauds during 2001 to 2016 from the CSRC official website. An audit firm is defined as a failed audit firm if any of its client involves in accounting fraud during 2001 to 2016. We start to identify the failed audit firms three years earlier than the IPO sample because the Examination Committee is likely to take this information into account in reviewing a particular IPO application. With respect to the audit firms, audit failures incurred in the previous three years may have continuous influences on the reputation, which in turn affects the Examination Committee’s decision. On the other hand, the review and examination of an IPO application require the applicant to submit previous three years’ audited financial statements. That is, for those IPO applicants that submitted the application in 2004, the Examination Committee checks their financial statements that cover 2001 to 2003 fiscal years. Therefore, we start from year 2001 to deal with the audit failure sample. The distribution of the audit failure sample is reported in Table 2. A total of 116 failed audit firm-year (audit failures) are documented during 2001 to 2016. Note here the year in Table 2 corresponds to the year that the failed audit firm’s client is formally filed for a fraud by the CSRC. Since a particular listed company may conduct accounting fraud in multiple years, the 116 failed audit firm-year correspond to 296 clients’ fraud-year observations Half of the audit failures (58) are subject to regulatory sanctions. As shown in Panel A of Table 2, years 2004, 2008, 2010, and 2015 are filed with more than 10 audit failures while years 2001 and 2007 are associated with relatively high probabilities of failed audit firms being sanctioned. For example, if a listed company A involved in accounting fraud in years 2001, 2002 and 2003. The CSRC subsequently announced sanctions on the frauds in 2005. Then, 2005 is the year we identify the failed audit firm in Table 2. However, one failed audit firm-year corresponds to three fraud-years in this example.. CHINA JOURNAL OF ACCOUNTING STUDIES 253 Table 2. Distribution: Audit failure and audit sanction. Panel A: Audit failure by year Year Failed Audit firm Failed but Not Sanctioned Failed and Sanctioned % of Sanction 2001 7 1 6 85.71 2002 3 1 2 66.67 2003 8 5 3 37.50 2004 12 8 4 33.33 2005 7 3 4 57.14 2006 5 3 2 40.00 2007 5 1 4 80.00 2008 10 4 6 60.00 2009 8 3 5 62.50 2010 10 7 3 30.00 2011 5 3 2 40.00 2012 5 3 2 40.00 2013 6 2 4 66.67 2014 8 3 5 62.50 2015 11 9 2 18.18 2016 6 2 4 66.67 Total 116 58 58 50.00 Panel B: Audit failure: Big N VS. Non-Big N Failed Audit firm Failed but Not Sanctioned Failed and Sanctioned % of Sanction Audit Failure by Big N 27 14 13 48.15 Audit Failure by Non-Big N 89 44 45 50.56 Total 116 58 58 50.00 Panel C: Frequency of audit failure and audit sanction Audit Failure Audit Sanction Frequency of Audit Failure N of Audit Firms Frequency of Audit Sanction N of Audit Firms 144 0 23 210 1 36 38 2 4 62 3 1 82 5 1 Panel B of Table 2 reports the audit failures and regulatory sanctions by Big N audit firms and those by non-Big N audit firms, respectively. We observe that non-Big N audit firms experience more audit failures (89) than the Big N audit firms (27). However, once an audit failure incurs, the probability of failed audit firm being sanctioned is only slightly lower for the Big N audit firms (48.15%) than that for the non-Big N audit firms (50.56%). Panel C of Table 1 reports the frequencies of audit failures and regulatory sanctions by audit firms. Among the 66 failed audit firms in our sample, 44 firms only involve one audit failure while 22 firms involve multiple failures. Two firms experience eight audit failures. In terms of regulatory sanctions (the right two columns of Panel C), we find that 23 firms are exempted from sanction on audit failures while seven firms are sanctioned more than twice. Next, we check how the audit firms react to the accounting frauds by summarising the audit opinions. As described in Panel A of Table 3, we identify 289 fraud-year observations during 2001 to 2016. Among them, 231 (79.93%) fraud-years receive unqualified audit As mentioned in the previous paragraph, the 116 audit failures correspond to 296 fraud-year observations. However, seven accounting frauds conducted by two companies incur before IPOs. That is, the financial statements disclosed in the prospectus involve accounting frauds. No audit opinions are disclosed for these seven frauds. We are thus left with 289 fraud-year observations. 254 H. YUAN ET AL. Table 3. Distribution: Audit opinions on the listed companies. Panel A: Audit opinion by fraudulent companies Fraudulent Non-Fraudulent Audit Opinion Companies % Company % Unqualified opinion 231 79.93 27,320 91.91 Unqualified opinion with explanatory paragraphs 31 10.73 1,482 4.99 Qualified opinion 10 3.46 300 1.01 Qualified opinion with explanatory paragraphs 10 3.46 345 1.16 Adverse opinion 0 0.00 4 0.01 Disclaimer 7 2.42 275 0.93 Total 289 100 29,726 100 Panel B: Audit opinion by audit firms: Sanctioned VS. Non-Sanctioned Sanctioned Audit Non-Sanctioned Audit Opinion firms % Audit firms % Unqualified audit opinion 86 84.31 145 77.54 Unqualified audit opinion with explanatory paragraphs 9 8.82 22 11.76 Qualified audit opinion 1 0.98 9 4.81 Qualified audit opinion with explanatory paragraphs 5 4.91 5 2.67 Disclaimer 1 0.98 6 3.22 Total 102 100 187 100 opinions and 31 (10.73%) fraud-years receive unqualified opinions with explanatory para- graphs. That is, only about 10% of the accounting frauds receive modified audit opinions. In comparison, 3.11% of the companies that do not involve in accounting frauds also receive modified audit opinions. The high Type II error suggests large room for improvement in audit quality in the Chinese A-share market. Panel B of Table 3 reports the audit opinions on the accounting frauds issued by the sanctioned audit firms and those by the non-sanctioned audit firms, respectively. The non-sanctioned audit firms issue a total of 10.7% modified opinions to the frauds. In comparison, sanctioned audit firms issue only 6.87% modified opinions to frauds. 5. Research design and empirical results 5.1. Research design We employ a difference-in-difference (DID) approach (Bertrand & Mullainathan, 2003; Yang, 2013) to empirically examine the economic consequences of audit failure and regulatory sanction on the firm’s IPO audits. Specifically, we employ the following logit model on the IPO sample described in Table 1 to test H1 of whether and how audit failure affects the IPO clients’ rejection rate: Reject ¼ α þ β Auditfail þ β Auditfail Post þ Controls þ Year & Industry fixed effects 1 2 þ ε (1) The dependent variable, Reject, is a dummy variable that equals one if the IPO application is rejected by the CSRC and zero if the applicant successfully get listed. The variable Auditfail identifies an audit firm whose client is found to conduct accounting fraud during 2001–2016. Panel C of Table 2 identifies a total of 66 failed audit firms. The variable Auditfail takes a value of one if the IPO applicant is the client of one of the 66 failed audit firms and zero otherwise. It captures the differences in IPO rejection rates between the IPO CHINA JOURNAL OF ACCOUNTING STUDIES 255 clients of the failed audit firms and those of the non-failed audit firms. Our variable of interest, Auditfail_Post, captures how audit failure subsequently affects IPO rejection rate. It equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure and zero otherwise. A significantly positive β supports our H1. We include a set of control variables based on existing studies. First, the IPO applicant’s characteristics are controlled by size (Size), leverage (Lev), and profitability (ROA). An IPO application is more likely to be successful for large and profitable firms, and for firms with low leverage and thus less risky (Yang, 2013). We next control for existence of political connection by the nature of the applicant’s ultimate shareholder (SOE) because state- owned enterprises are less likely to be rejected by the CSRC (Li & Liu, 2012). We also control for the reputation of the two most important financial intermediaries during the IPO process: whether the applicant’s financial statements are audited by one of the Big N auditors (BigN) and whether one of the Top 10 investment banks underwrite the IPO application (Top10_IB). Reputable intermediaries are expected to increase the IPO pass rate (Chen, Zheng, & Li, 2014). Last but not least, the year and industry fixed effects are controlled for any unobservable year and industry factors that are not included in the empirical model. Table 4 provides a detailed definition of all the variables. All the continuous variables are winsorised at 1% level. Next, we investigate whether and how the regulatory sanctions on the audit firm influence its IPO client’s rejection rate. Similar to Equation (1), we employ the following logit model: Table 4. Data definitions. Dependent Variable Reject Dummy variable, equals one if the client’s IPO application is rejected and zero if it is successfully approved by the CSRC. Variables of Interest Auditfail_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure and zero otherwise. Sanc_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm is sanctioned on the audit failure by the CSRC and zero otherwise. NonSanc_Post Dummy variable, equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure without sanctions and zero otherwise. Control Variables Auditfail Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firms and zero otherwise. An audit firm is classified as a failed one if it audits at least one listed company that conduct fraud during 2001–2016. Sanc Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firm that is sanctioned by the CSRC due to the audit failure and zero otherwise. NonSanc Dummy variable, equals one if the IPO applicant is audited by one of the failed audit firm that is not sanctioned by the CSRC due to the audit failure and zero otherwise. BigN Dummy variable, equals one if the IPO applicant is audited by one of the Big N audit firms and zero otherwise. Big N audit firms include international Big 4 and domestic Big 10. Size Natural logarithm of total assets of the IPO applicant. ROA Return on assets of the IPO applicant. Lev Leverage ratio of the IPO applicant, calculated as total liabilities divided by total assets. SOE Takes a value of one if the IPO applicant is a state owned enterprise, and zero oterhwise. Top10_IB Dummy variable, equals one if the IPO is underwritten by one of the top 10 investment banks and zero otherwise. Top 10 is calculated on the market share of the investment bank whereas market share is based on the clients’ total proceeds raised in the previous year. 256 H. YUAN ET AL. Reject ¼ α þ β Sanc þ β NonSanc þ β Sanc Post þ β NonSanc Post þ Controls 1 2 3 4 þ Year &; Industry fixed effects þ ε (2) Since some audit firms are subsequently sanctioned by the CSRC while others are not, we define two new variables, Sanc and NonSanc,todifferentiate the sanctioned firms and non- sanctioned firms. Specifically, Sanc equals one if the IPO applicant is the client of a failed audit firm that is sanctioned during our sample period and zero otherwise. The variable NonSanc takes a value of one if the IPO applicant is the client of a failed audit firm but is not sanctioned during our sample period and zero otherwise. That is, Auditfail is the sum of Sanc and NonSanc. Similar as the construction of Auditfail_Post in Equation (1), we construct two variables, Sanc_Post and NonSanc_Post to capture the impact of audit sanction on IPO client’s rejection rate. The variable Sanc_Post is a dummy variable that equals one if the client’s IPO is reviewed within three years after an audit firm is sanctioned on the audit failure by the CSRC and zero otherwise. The variable NonSanc_Post is a dummy variable that equals one if the client’s IPO is reviewed within three years after an audit firm experienced an audit failure without sanctions and zero otherwise. That is, Auditfail_Post is the sum of Sanc_Post and NonSanc_Post.The difference between β and β captures the 3 4 different impact on IPO rejection rate caused by audit sanction. Our H2a will be supported by positive β and β . And H2b will be supported if β is larger than β . 3 4 3 4 5.2. Descriptive statistics The logit models of Equations (1) and (2) are estimated based on the IPO sample described in Table 1.Panel Aof Table 5 summarises the descriptive statistics of the variables used in the logit models. The followings are noteworthy. First, the mean IPO rejection rate is Table 5. Descriptive statistics. Panel A: Descriptive statistics (N = 1,605) Mean Q1 Median Q3 Std. Dev. Reject 0.06 0.00 0.00 0.00 0.24 Auditfail 0.72 0.00 1.00 1.00 0.45 Auditfail_Post 0.37 0.00 0.00 1.00 0.48 Sanc 0.33 0.00 0.00 1.00 0.47 Sanc_Post 0.12 0.00 0.00 0.00 0.32 NonSanc 0.39 0.00 0.00 1.00 0.49 NonSanc_Post 0.25 0.00 0.00 0.00 0.43 BigN 0.46 0.00 0.00 1.00 0.50 Size 20.63 20.27 20.75 21.38 2.80 Lev 0.31 0.15 0.27 0.43 0.20 ROA 0.08 0.05 0.07 0.10 0.04 SOE 0.14 0.00 0.00 0.00 0.35 Top10_IB 0.31 0.00 0.00 1.00 0.46 Panel B: Univariate comparison of mean IPO rejection rate (Reject) Mean value of Reject Test for Difference Types of Audit firm Auditfail =0 Auditfail =1 Diff. t-value Failed audit firm (Auditfail = 1) 4.59% 6.38% 1.78% 1.91* Sanctioned audit firm (Sanc = 1) 5.20% 6.91% 1.71% 2.18** Non-sanctioned audit firm (NonSanc = 1) 5.15% 6.12% 0.96% 0.69 The superscripts * and ** indicate p < 0.1 and p < 0.05, respectively. CHINA JOURNAL OF ACCOUNTING STUDIES 257 6%. Second, on average, 72% of the IPOs are audited by audit firms that experienced at least one audit failure. Among the failed audit firms, 33% are subsequently subject to CSRC sanction while 39% are not sanctioned. Third, the mean value of Auditfail_Post is 0.37, suggesting that 37% of the IPO applicants are audited by firms that experienced an audit failure in the latest three years. Among them, 12% of the IPO applicants are audited by failed firms that are sanctioned in the latest three years and 25% are audited by failed firms but are not sanctioned in the latest three years. Fourth, with respect to the control variables, 46% of the IPO applicants are audited by one of the international Big 4 or the domestic Big 10 audit firms. 31% of the IPO applicants are underwritten by one of the top 10 investment banks. 14% of the IPO applicants are SOEs. Panel B compares the mean IPO rejection rate (Reject) for the sub-samples of pre- and post-audit failure. For the failed audit firms, the client’s mean IPO rejection rate in the post- failure period (Auditfail_Post = 1) is 6.38%, significantly higher than that in the pre-failure period (4.59%). With respect to the failed audit firms that are subsequently sanctioned, the mean IPO rejection rate in the post-sanction period (Sanc_Post=1) is 6.91%. As a comparison, the mean IPO rejection rate in the pre-sanction period for the sanctioned audit firms is significantly lower at 5.20%. In terms of the failed audit firms that are not subject to sanctions, the mean IPO rejection rate in the post- and pre-failure periods are 6.12% and 5.15%, respectively. The two mean rejection rates are not significantly different. The univariate comparison provides some preliminary evidence that the IPO client’srejec- tion rate increases after audit failures and regulatory sanctions on the audit failures. 5.3. Empirical results Table 6 reports the results for the logit models that investigates whether and how audit failures and regulatory sanctions adversely affect the client’s IPO application outcomes. Columns (1) and (2) are estimated on all the IPO applicants during our sample period and column (3) is estimated on the IPO clients of the failed audit firms Column (1) of Table 6 reports the regression results of Equation (1). As shown, the coefficient of Auditfail is −0.097 and is not significantly different from zero. The insignificant coefficient suggests that the IPO rejection rate does not differ between the clients of the failed audit firms and those of the non-failed audit firms before the audit failure incurs. More interestingly, the coefficient of Auditfail_Post is positive with a value of 1.159, significant at less than 5% level. It provides evidence to support our H1 that the client’s IPO rejection rate increases significantly after an audit firm experiences an audit failure. That is, audit failure adversely impacts its IPO client’s application outcome. Column (2) presents the regression results of Equation (2). Neither the coeffi- cient of Sanc nor that of NonSanc is significantly different from zero, showing that regulatory sanctions on the failed audit firms in the pre-sanction period do not affect the clients’ IPO rejection rates. This is expected given the insignificant The number of observations in Table 6 and the total number of observations for the three sub-samples tests in Tables 7– 9 are less than that in Table 1 (1,605) because STATA automatically drops some observations when we include the year and industry fixed effects.. 258 H. YUAN ET AL. Table 6. Regression results for the logit model of IPO rejection rate. (1) (2) (3) Auditfail −0.097 (−0.18) Auditfail_Post 1.159** (2.57) Sanc −0.574 −0.446 (−0.81) (−0.77) Sanc_Post 2.144*** 1.574** (2.91) (2.31) NonSanc 0.053 (0.09) NonSanc_Post 0.913* (1.81) BigN −0.589 −0.461 −0.806* (−1.43) (−1.02) (−1.67) Size −0.477*** −0.477*** −0.470*** (−6.17) (−6.22) (−5.14) Lev 4.074*** 3.954*** 3.684*** (3.83) (3.69) (3.00) ROA 1.748 2.077 1.104 (0.39) (0.45) (0.21) SOE −0.416 −0.444 −0.539 (−0.66) (−0.72) (−0.72) Top10_IB −0.628 −0.584 −0.541 (−1.43) (−1.32) (−1.05) Constant 6.378*** 5.971*** 7.184*** (3.08) (2.85) (2.95) Year Yes Yes Yes Industry Yes Yes Yes Pseudo R 0.39 0.40 0.39 N 1,600 1,600 1,080 [Sanc_Post]=[NonSanc_Post] 2.93* The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. coefficient of Auditfail in column (1). In comparison, the coefficient of Sanc_Post is 2.144 with a t-value of 2.91, significant at less than 1% level, showing a significant adverse impact on the client’s IPO application outcome after a failed audit firm is sanctioned by the CSRC. The coefficient of NonSanc_Post is also positive with a value of 0.913, significant at less than 10% level, suggesting that the IPO client’s rejection rate increases even if the failed audit firm is not subsequently sanctioned. That is, an audit firm encounters reputational loss when it experiences audit failure, regardless of being sanctioned or not. Next, we test whether the two coefficients differ significantly. We find that the coefficient of Sanc_Post is signifi- cantly larger than that of NonSanc_Post, providing evidence that the IPO client’s rejection rate is higher if the failed audit firm is sanctioned than if the failed audit firm is not sanctioned by the CSRC. Taken together, the results in column (2) lend support to H2a and show that audit failure does adversely impact the IPO client’s application outcome regardless of whether the audit firm is subsequently sanc- tioned or not. However, the sanctioned audit firm faces a more negative impact on the IPO client’s application outcome than the non-sanctioned audit firm does, as predicted by H2b. CHINA JOURNAL OF ACCOUNTING STUDIES 259 While columns (1) and (2) compare the failed audit firms with the non-failed audit firms as the benchmark, column (3) re-estimates Equation (2) on a reduced sample that includes only the IPO clients of the failed audit firms. By doing so, we effectively compare the sanctioned audit firms with the non-sanctioned audit firms among the failed firms group. Consistent with the finding in column (2), the coefficient of Sanc is not significantly different from zero, suggesting that the IPO rejection rate does not differ between the sanctioned and non-sanctioned audit firms in the pre-failure period. However, the coeffi- cient of Sanc_Post is positive with a value of 1.574, significant at less than 5% level, providing further support to our H2b. With respect to the control variables, we find that large firms (Size) and low-leveraged (Lev) firms are less likely to be rejected in the IPO applications. We also find some evidence in column (3) that Big N firm’s clients’ IPO applications (BigN) are less likely to be rejected. However, we do not find significant results on other control variables. 6. Further analyses In this section, we conduct several cross-sectional analyses to further investigate whether the audit failure-IPO rejection relation varies with different types of audit firms and IPO applicants. Specifically, we partition the sample by (i) the size of audit firms; (ii) whether the audit firm is politically connected; and (iii) the board of listing by an IPO applicant Then, Equations (1) and (2) are re-estimated on the sub-samples. We are interested in whether the coefficients of Auditfail_Post in Equation (1) and the difference in the coefficients of Sanc_Post and NonSanc_Post in Equation (2) differ between the sub-samples. 7. Effects of audit firm size on the rejection–failure relation Our first cross-sectional analysis examines whether the adverse consequence on client’s IPO application varies with the size of audit firms. One may expect that the Examination Committee is likely to adopt a more rigorous review on the clients of big audit firms. Firstly, through existing literature has well documented that big audit firms are associated with high audit quality (DeAngelo, 1981), big firms also suffer larger reputational losses. Li and Yuan (2017) examine the consequences of regulator sanctions on the sponsors and find that large investment banks experience larger decreases in the market share than small and medium ones do. Secondly, big audit firms may have stronger rent-seeking abilities than small audit firms to minimise the likelihood of being sanctioned after audit failures. The committee members may thus be more cautious in reviewing the IPO clients of big audit firms to take into account of the potentially understated sanctions on the big firms. In this sense, big audit firms’ IPO clients are likely to encounter more adverse consequences than small audit firms’. However, one can also argue that small audit firms face more rigorous review by the Examination Committee than big ones. Sami et al. (2012)show thatbig firms take measures We also follow Firth, Mo, and Wong (2014) approach to partition the sample by IPO clients of audit firms with only one failure and those with multiple failures. We do not find significant differences between the two sub-samples in terms of the IPO rejection rate-audit failure relation. We thus do not report this sub-sample test for brevity.. 260 H. YUAN ET AL. to improve audit quality in a timelier manner than small firms after the regulatory sanctions. The Examination Committee thus has more confidence in big firms than in small firms in the ability to restore audit quality after sanctions. Thus, IPO clients of small firms are likely to be reviewed more conservatively by the Examination Committee than those of big firms. Therefore, we partition the sample based on whether the IPO applicant is audited by one of the Big N audit firm or not. We follow the definition in our main test to define Big N as international Big 4 or the domestic Big 10 audit firms. Table 7 reports the results of the sub-sample test. Columns (1) and (2) investigate the consequence of audit failure on IPO application. As shown, the coefficient of Auditfail is not significant in either sub-sample. However, the coefficient of Auditfail_Post is significantly positive in column (2) (1.921 with a t-value of 2.82) while it is insignificantly different from zero in column (1). A Chow’s test shows that the coefficient of Auditfail_Post significantly differs between the two sub-samples with a p-value of 0.07. That is, the increase in the client’s IPO rejection rate is mainly driven by the IPO clients of the non-Big N firms. Audit failure does not adversely influence the Big N firms significantly. Columns (3) and (4) re-estimate Equation (2) to examine the consequence of audit sanction. We observe that the coefficients of Sanc and NonSanc are insignificant in both columns. In comparison, the coefficient of Sanc_Post is significantly positive in both columns while that of NonSanc_Post is significantly positive in column (4) only. That is, Table 7. Cross-sectional test: sample partitioned by Big N and Non-Big N audit firm. (1) (2) (3) (4) (5) (6) Big N Non- Big N Big N Non- Big N Big N Non- Big N Auditfail -0.310 0.003 (-0.33) (0.01) Auditfail_Post 0.113 1.921*** (0.16) (2.82) Sanc -0.090 -0.343 -0.105 -1.334 (-0.08) (-0.32) (-0.12) (-1.33) Sanc_Post 2.977* 2.699** 3.445** 2.442** (1.94) (2.41) (2.16) (2.13) NonSanc -0.107 0.171 (-0.09) (0.20) NonSanc_Post -0.814 1.531* (-0.79) (1.88) Size -0.590*** -0.429*** -0.663*** -0.422*** -0.710*** -0.369*** (-3.48) (-3.86) (-3.30) (-3.84) (-3.04) (-2.96) Lev 3.407* 4.083*** 3.694** 3.896*** 3.342 4.311** (1.88) (2.76) (1.96) (2.64) (1.64) (2.50) ROA 2.848 1.357 4.356 1.289 3.846 1.213 (0.37) (0.22) (0.58) (0.21) (0.48) (0.17) SOE 0.114 -0.899 -0.041 -0.809 -0.534 -0.305 (0.12) (-0.81) (-0.04) (-0.73) (-0.41) (-0.25) Top10_IB 0.084 -1.097* 0.127 -1.067* -0.558 -0.794 (0.11) (-1.72) (0.17) (-1.66) (-0.59) (-1.12) Constant -6.242 6.189** -7.550 6.336** -6.354 6.748** (-0.00) (2.25) (-0.00) (2.29) (-0.01) (2.13) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.51 0.36 0.54 0.37 0.52 0.35 N 592 624 592 624 512 405 [Sanc_Post]=[NonSanc_Post] 5.51** 0.77 The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. CHINA JOURNAL OF ACCOUNTING STUDIES 261 clients of both Big N and non-Big N audit firms experience declines in the IPO success rates after the audit firms are sanctioned. However, clients of Big N firms are not adversely affected in the IPO application if the audit firms experience audit failures but are not subsequently sanctioned. The test of difference in the two coefficients of Sanc_Post and NonSanc_Post in columns (3) and (4) confirms our findings. For clients of a Big N audit firm, the IPO rejection rates increase only when the audit firm is subsequently sanctioned on the audit failure. In comparison, for clients of a non-Big N audit firm, the IPO rejection rates increase as long as the audit firm experiences an audit failure, regardless of whether the audit firm is sanctioned or not. Columns (5) and (6) include only the failed audit firms. The results re-affirm that regulatory sanctions adversely affect both the Big N and non-Big N audit firms in terms of their clients’ IPO applications. In short, the results in Table 7 reveal that the negative impact by audit failure exists for small audit firms, regardless of whether the audit firm is sanctioned or not. However, big audit firms are adversely affected only when they are sanctioned on the audit failure. 7.1. Role of political connection on the rejection–failure relation Political connection is usually viewed as resources that can bring in future benefits. In this section, we test whether the adverse consequence on client’s IPO application can be attenuated by the audit firm’s political connection. We argue that it is ex ante unclear on the role of political connection on the audit failure-IPO rejection relation. On the one hand, Yang (2013) documents a decline in the IPO rejection rate of the client that is audited by a politically connected audit firm. In case of audit failure, politically connected firms are better able to minimise the adverse impact than non-connected firms. In this sense, political connection can attenuate the adverse consequence by audit failure and sanctions on client’s IPO application. On the other hand, however, the Examination Committee may realise that the exemption from being sanctioned is probably achieved by political con- nection, rather than not being accountable for the audit failure. Taking the potentially understated sanctions into consideration, the Examination Committee is likely to exert more rigorous review on the IPO clients of the politically connected firms. As a result, the IPO rejection rate in turn increases for clients of politically connected audit firms. To empirically test the role of political connection on the audit failure-IPO rejection relation, we partition the sample into two sub-samples based on whether the IPO applicant is audited by politically connected firms or not. To do so, we follow Yang (2013)approach to identify the political connection of audit firms. Specifically, if any auditor in a particular audit firm is elected as the committee member of the Examination Committee in a given year, then that audit firm is deemed to be politically connected from that year on. Table 8 reports the results of the sub-sample tests. We observe the following findings. First, the coefficient of Auditfail_Post is significantly positive in both column (1) and (2) with a value of 1.834 and 1.181, respectively. And a Chow’s test shows no significant difference between the coefficients in the two sub-samples. We thus conclude that the IPO rejection rate increases after audit failure, regardless of whether the audit firm has political connection or not. Second, column (3) reports significantly positive coefficients of both Sanc_Post and NonSacn_Post, suggesting that for politically connected audit firms, the client’s IPO application is adversely affected regardless of whether the audit firm is 262 H. YUAN ET AL. Table 8. Cross-sectional test: sample partitioned by politically connected and non-politically con- nected audit firm. (1) (2) (3) (4) (5) (6) Non- Non- Non- Politically Politically Politically Politically Politically Politically connected connected connected connected connected connected Auditfail 0.520 −0.020 (0.32) (−0.03) Auditfail_Post 1.834* 1.181** (1.85) (2.02) Sanc −1.318 −0.189 −1.326 −0.400 (−0.61) (−0.25) (−1.08) (−0.48) Sanc_Post 3.956** 1.822** 2.948* 1.727* (2.07) (2.10) (1.76) (1.71) NonSanc 0.316 0.038 (0.19) (0.05) NonSanc_Post 1.883* 0.884 (1.71) (1.31) BigN −0.151 −0.401 −0.096 −0.325 −0.685 −0.539 (−0.18) (−0.77) (−0.10) (−0.55) (−0.76) (−0.66) Size −0.906*** −0.402*** −0.940*** −0.402*** −0.849*** −0.390*** (−2.67) (−4.82) (−2.65) (−4.87) (−2.62) (−3.44) Lev 4.891** 3.935*** 5.171** 3.833*** 4.040* 4.450*** (2.15) (2.84) (2.16) (2.77) (1.78) (2.60) ROA 0.728 5.214 2.514 5.021 4.484 3.367 (0.07) (0.98) (0.23) (0.93) (0.43) (0.48) SOE −1.273 −0.385 −1.450 −0.426 −0.784 −0.647 (−0.90) (−0.50) (−1.00) (−0.55) (−0.57) (−0.63) Top10_IB −1.765* −0.480 −1.699 −0.412 −1.446 −0.378 (−1.70) (−0.91) (−1.61) (−0.77) (−1.35) (−0.53) Constant 6.096 5.076** 6.087 4.867** 6.921 6.278* (0.31) (2.11) (0.31) (2.02) (0.38) (1.8) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.58 0.33 0.59 0.33 0.57 0.30 N 545 744 545 744 466 505 [Sanc_Post]=[NonSanc_Post] 3.27* 5.89** The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. sanctioned or not after an audit failure. But the sanctioned firms are more adversely affected than the non-sanctioned firms, as indicated by the significant difference between the coefficients of Sanc_Post and NonSanc_Post. Third, column (4) reports a significantly positive (insignificant) coefficient of Sanc_Post (NonSanc_Post), showing that for audit firms without political connections, the IPO clients are negatively affected only when the audit firms are sanctioned. The IPO rejection rate is not impacted if the audit firm experiences an audit failure but is not sanctioned. Fourth, a Chow’s test shows significant difference between the coefficients of Sanc_Post in column (3) and column (4), supporting the argument that the Examination Committee exerts a more rigorous review on the clients of politically connected audit firms than those of non-connected audit firms after sanctions. Last but not least, when we exclude the non-failed audit firms, we find that the coefficient of Sanc_Post is significantly positive in both columns (5) and (6). That is, the IPO client is adversely affected by regulatory sanctions regardless of whether the audit firm is politically connected or not. CHINA JOURNAL OF ACCOUNTING STUDIES 263 In short, the results in Table 8 reveal that the IPO clients are adversely affected by both audit failure and regulatory sanctions on the failure, regardless of whether the audit firm has political connection or not. However, politically connected audit firms are more negatively affected if they are subsequently sanctioned than the non-connected counterparts. 7.2. The influence of the board of IPO listing on the rejection–failure relation The CSRC established the GEM board in 2009 to support the capital raising demands of innovative growth enterprises. As introduced in Section 2, two Examination Committees operated together before 2017 (within our sample period). One committee reviews IPO applicants for the main board and the SME board, and the other one reviews for the GEM board, respectively. In this section, we investigate whether the adverse consequence of audit failure on IPO clients differs between the clients’ board of listing. We argue that it is ex ante unclear of which board is more adversely affected. On the one hand, compared with IPO applications on the main board and the SME, those on the GEM are typically smaller sized, riskier, and associated with more uncertainties in the future operating performance. In addition, the GEM stocks are higher priced than those on the main board and the SME board The price premium may induce earnings management behaviour on the GEM board to inflate the stock prices. In this sense, the Examination Committee is likely to exercise more rigorous review on the IPO applicants on the GEM board than those on the main and SME boards to avoid risk. As a result, the adverse consequence by the audit failure is aggravated if the IPO applicant plans to list on the GEM board. On the other hand, due to the risky nature of the innovative growth enterprises, the CSRC imposes more stringent supervision on the companies that are listed on the GEM board than those on the main board. For example, the investment bank is required to make professional judgement on whether the IPO applicants on the GEM board can achieve sustainable profits and satisfy the listing requirements. The investment bank is also required to issue opinion on the IPO applicants’ growth potentials and innovative abilities. In addition, after the IPO applicant gets successfully listed, the investment bank should continuously supervise the applicant for three years, in comparison to two years’ supervision period as per required by the main and SME boards. These stringent requirements are expected to filter high-quality IPO applicants and serve as substitutes for the Examination Committee’s review. Thus, the Examination Committee may exer- cise less rigorous review on the IPO applicants on the GEM board than those on the main and SME boards. At the same time, among the 116 audit failures documented in Table 2, only six failures incurred on the GEM board The relatively low frequency of audit failure on the GEM board gives little information and references to the Examination Committee regarding the clients of the failed firms. In this sense, we expect that the adverse consequence by the audit failure is attenuated if the IPO applicant plans to list on the GEM board. For example, the median value of the price earnings (PE) ratio is 30.77 for main and SME boards while that for the GEM board is 50.80. On average, the PE ratio of the GEM board is 50% to 60% higher than that of the main and SME boards.. We observe relatively few audit failures on the GEM board probably because of the shorter history of the GEM board than the main and SME boards. Another possible reason may be because of the rigorous review mechanisms on the GEM board discourage accounting frauds by the IPO applicants.. 264 H. YUAN ET AL. Table 9. Cross-sectional test: sample partitioned by board of IPO listing. (1) (2) (3) (4) (5) (6) Main & SME GEM Main & SME GEM Main & SME GEM Auditfail −0.769 1.020 (−1.05) (0.93) Auditfail_Post 1.895*** 0.198 (2.91) (0.28) Sanc −1.246 0.801 −0.513 −0.182 (−1.32) (0.63) (−0.65) (−0.19) Sanc_Post 2.614** 1.316 1.486* 1.530 (2.56) (1.18) (1.69) (1.35) NonSanc −0.567 1.092 (−0.73) (0.94) NonSanc_Post 1.791** −0.354 (2.53) (−0.40) BigN −0.427 −0.773 −0.244 −0.885 −0.867 −1.056 (−0.77) (−1.12) (−0.39) (−1.19) (−1.32) (−1.32) Size −0.502*** −0.608*** −0.514*** −0.621*** −0.485*** −0.643*** (−4.49) (−3.47) (−4.48) (−3.58) (−3.79) (−2.91) Lev 6.271*** −0.708 6.169*** −0.839 5.525*** −0.151 (4.39) (−0.29) (4.24) (−0.34) (3.34) (−0.06) ROA −2.054 4.273 −1.621 4.926 −7.900 6.209 (−0.29) (0.72) (−0.23) (0.82) (−0.87) (0.95) SOE −0.699 0.000 −0.672 0.000 −0.846 0.000 (−1.01) (.) (−0.98) (.) (−1.01) (.) Top10_IB −0.434 −1.575 −0.375 −1.556 −0.054 −1.421 (−0.80) (−1.48) (−0.69) (−1.45) (−0.08) (−1.28) Constant 6.494** −2.739 6.479** −3.380 7.519** 0.962 (2.34) (−0.00) (2.31) (−0.00) (2.34) (0.00) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.44 0.42 0.45 0.43 0.46 0.38 N 791 462 791 462 607 350 [Sanc_Post]=[NonSanc_Post] 0.79 1.82 The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. Table 9 reports the regression results of the sub-samples that are partitioned by the IPO client’s board of listing. As shown, the coefficient of Auditfail_Post is significantly positive in column (1) while it becomes insignificant in column (2). That is, the IPO client is more adversely affected by audit failure if it is listed on the main or SME board. However, the client’s IPO application is not affected by audit failure if it plans to list on the GEM board. With respect to the influence of subsequent sanctions on audit failure, we find that both coefficients of Sanc_Post and NonSanc_Post are significantly positive in the sub-sample of IPO applicants on main and SME board (column 3). In addition, the two coefficients are not significantly different from each other. Thus, column (3) provides evidence that for IPO client to be listed on the main or SME board, it is adversely affected by audit failure regardless of whether the audit firm is subsequently sanctioned or not. In comparison, column (4) shows that neither coefficient of Sanc_Post or NonSanc_Post significantly differs from zero, suggesting that the IPO client on the GEM board is not affected by audit failure. Columns (5) and (6) re-affirm the results on regulatory sanctions. As indicated by the marginally significant coefficient of Sanc_Post in column (5) and the insignificant coeffi- cient of Sanc_Post in column (6), we do not find strong evidence on the adverse influence by audit sanction on either the IPO clients on main and SME boards or those on the GEM board. CHINA JOURNAL OF ACCOUNTING STUDIES 265 In short, Table 9 indicates that the adverse consequence by audit failure as well as regulatory sanction on IPO rejection rate exists only when the IPO applicants choose to list on the main and SME boards. 8. Robustness tests 8.1. Excluding the impact of appropriate audit opinions on the rejection–failure relation In our main test in Table 6, we identify an audit failure by a particular audit firm as long as the firm audits at least one listed company that is found to conduct accounting fraud. However, as described in Table 3, 9.34% of the accounting frauds receive modified audit opinions. That is, some audit firms issue appropriate audit opinions regarding clients’ accounting frauds. In this case, the audit firm should not be held accountable. That is, our definition of audit failure in the main test is likely to be overestimated. To address this issue, we identify the audit firms that issue modified audit opinions to all the fraud-years and exclude the IPO clients of these audit firms from our sample We then re-estimate Table 10. Robustness test: exclude IPO clients of audit firms that issue appropriate audit opinions. (1) (2) (3) Auditfail −0.097 (−0.177) Auditfail_Post 1.138** (2.522) Sanc −0.571 −0.475 (−0.811) (−0.819) Sanc_Post 2.123*** 1.576** (2.893) (2.317) NonSanc 0.066 (0.112) NonSanc_Post 0.887* (1.758) BigN −0.595 −0.468 −0.818* (−1.441) (−1.042) (−1.703) Size −0.473*** −0.473*** −0.467*** (−6.093) (−6.164) (−5.106) Lev 4.037*** 3.910*** 3.583*** (3.776) (3.627) (2.901) ROA 1.897 2.207 0.939 (0.424) (0.485) (0.178) SOE −0.408 −0.436 −0.555 (−0.648) (−0.689) (−0.750) Top10_IB −0.633 −0.587 −0.519 (−1.442) (−1.325) (−1.002) Constant 6.285*** 5.885*** 7.153*** (3.031) (2.816) (2.933) Year Yes Yes Yes Industry Yes Yes Yes Pseudo R 0.38 0.39 0.38 N 1,546 1,546 1,007 [Sanc_Post]=[NonSanc_Post] 2.99* The t-statistics are in parentheses. Chi2 is reported for test of difference between Sanc_Post and NonSanc_Post. The *, ** superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. We examine the relation between audit opinions and accountability by the audit firm. Untabulated results show that the audit firm is more likely to be exempted from sanction if it issues modified audit opinions on all the fraud-years.. 266 H. YUAN ET AL. Equations (1) and (2) based on this reduced sample of 1,546 IPO applicants. The results are reported in Table 10.We find that the results are statistically similar as those reported in Table 6: the client’s IPO application is adversely influenced after an audit firm involves in audit failure, and the influence is aggravated if the audit firm is subject to regulatory sanctions. That is, our main findings are not unduly influenced by the potentially upward biased measurements of Auditfail and Auditfail_Post. 8.2. Placebo test In our main analysis, an audit failure is identified based on the CSRC announcement year as described in Table 2. To ensure that the impact on the IPO rejection rate is attributed to audit failure and audit sanctions, we conduct two placebo tests following Ke and Zhang (2019)’s approach. Specifically, rather than the CSRC announcement year, we define two pseudo-event years, three years before and three years after the CSRC announcement year. Then, Auditfail_Post, Sanc_Post,and NonSanc_Post are re-defined according to the pseudo- event years. Table 11. Robustness test: use of pseudo-event years. (1) (2) (3) (4) (5) (6) Pseudo-event Pseudo-event Pseudo-event Pseudo-event Pseudo-event Pseudo-event year = t-3 year = t + 3 year = t-3 year = t + 3 year = t-3 year = t + 3 Auditfail 0.275 0.559 (0.55) (1.18) Auditfail_Post 0.561 −0.489 (1.20) (−0.89) Sanc 0.064 0.699 −0.069 0.330 (0.11) (1.31) (−0.14) (0.72) Sanc_Post −0.559 −2.252 −0.572 −1.707 (−0.68) (−1.03) (−0.69) (−0.93) NonSanc 0.345 0.495 (0.65) (0.96) NonSanc_Post 0.297 −0.339 (0.57) (−0.59) BigN −0.698* −0.477 −0.493 −0.576 −0.724 −0.970** (−1.69) (−1.14) (−1.13) (−1.29) (−1.52) (−2.07) Size −0.450*** −0.456*** −0.450*** −0.463*** −0.456*** −0.474*** (−6.11) (−6.09) (−6.07) (−6.03) (−5.01) (−4.76) Lev 3.912*** 3.815*** 3.839*** 3.856*** 3.770*** 3.930*** (3.68) (3.57) (3.63) (3.61) (3.13) (3.21) ROA 1.397 1.699 1.174 1.559 0.308 0.562 (0.32) (0.39) (0.26) (0.35) (0.06) (0.11) SOE −0.400 −0.397 −0.464 −0.367 −0.566 −0.480 (−0.64) (−0.63) (−0.74) (−0.59) (−0.77) (−0.67) Top10_IB −0.600 −0.628 −0.606 −0.619 −0.567 −0.609 (−1.38) (−1.45) (−1.39) (−1.42) (−1.11) (−1.19) Constant 6.269*** 6.282*** 7.468*** 6.190*** 6.285*** 7.630*** (3.10) (3.09) (3.14) (3.04) (3.04) (3.05) Year Yes Yes Yes Yes Yes Yes Industry Yes Yes Yes Yes Yes Yes Pseudo R 0.38 0.38 0.39 0.38 0.39 0.38 N 1,600 1,600 1,600 1,600 1,080 1,080 *, ** The t-statistics are in parentheses. The superscripts , and *** indicate p < 0.1, p < 0.05, and p < 0.01, respectively. All the variables are defined in Table 4. CHINA JOURNAL OF ACCOUNTING STUDIES 267 The results of the placebo test are reported in Table 11 with columns (1), (3) and (5) use three years before the CSRC announcement year as the pseudo-event and columns (2), (4), and (6) use three years after the CSRC announcement year as the pseudo-event. We find that none of the variables of interest (Auditfail_Post, Sanc_Post, and NonSanc_Post) significantly differs from zero. The results in Table 10 thus add our confidence that the findings on the adverse impact on client’s IPO application is attributed to audit failure and regulatory sanctions we identify in our main tests. 9. Conclusions and implications This study investigates one of the adverse consequences of audit failure. Specifically, we are interested in how audit failure adversely affects its client’s IPO application. We document the following findings. First, the client’s IPO rejection rate significantly increases within three years after the audit firm experiences an audit failure. Second, the client’s IPO application is adversely affected regardless of whether the audit firm is subsequently sanctioned on the audit failure. However, the client’s IPO rejection rate is significantly higher for sanctioned audit firms than that for failed but not sanctioned audit firms. Third, cross-sectional analyses suggest that the audit failure-IPO rejection rate relation varies across different types of audit firms. Specifically, the client’s IPO application is adversely affected as long as a non-Big N audit firm experiences an audit failure. However, in case of a Big N audit firm, the client’s IPO application is adversely affected only when the Big N audit firm is sanctioned on the audit failure. In terms of political connections, we find that the client’s IPO rejection rate increases significantly as long as a politically connected audit firm experiences an audit failure. However, in case of a non- politically connected audit firm, the client’s IPO rejection rate increases only when the audit firm is sanctioned after the audit failure. Fourth, the audit failure-IPO rejection rate relation also varies across the IPO applicant’s board of listing. We find that the adverse impact by audit failure and regulatory sanction is mainly driven by the IPO applicants on the main and SME boards. Last but not least, our results hold by various robustness tests including the use of a refined sample and the use of pseudo-event years. We enrich the literature on the consequences of audit failure. Our study also provides implications to regulatory bodies from the following two perspectives. First, given that China currently adopts the approval system for IPO applica- tion, the process of reviewing and filtering high-quality IPO applicants is especially important to ensure a well-functioned capital market and to protect the investors. Thus, it is meaningful to understand the decision process of the Examination Committee. Given our findings that the Examination Committee does take into account of the audit failure and regulatory sanctions when reviewing the audit firm’s IPO clients, we confirm the informativeness of audit failure to regulatory bodies. That is, besides the capital market participants, government agencies also utilise the signals sent by audit failure. Thus, we call for more timely and detailed disclosures on the audit failure and the audit firm’s liability in the audit failure. Second, our finding indicates that audit firms suffer reputational losses even if the audit firm is not sanctioned on the audit failure. 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Journal

China Journal of Accounting Studies – Taylor & Francis

Published: Apr 3, 2019

Keywords: Audit failure; regulatory sanction; audit firm; IPO

References

  • Corporate governance consequences of accounting scandals: Evidence from top management, CFO and auditor turnover
  • Corporate governance, audit firm reputation, auditor switches, and client stock price reactions: The Andersen experience
  • Enjoying the quite life? Corporate governance and managerial preferences
  • After Enron: Auditor conservatism and Ex-Andersen clients
  • Shredded reputation: The cost of audit failure
  • Selective enforcement of regulation
  • On factors affecting the penalties of audit firms by regulatory authority: Evidence from auditing regulation of capital markets in China
  • Non-SOE ipo firm’s relationship with stock issuance examination and verification committee, IPO verification and future performance
  • The impact of SEC disciplinary actions on audit fees
  • Auditor size and audit quality
  • Understanding earnings quality: A review of the proxies, their determinants and their consequences
  • Causes and consequences of earnings manipulation: An analysis of firms subject to enforcement actions by the SEC
  • A review of archival auditing research
  • Competition in auditing research: An assessment
  • An empirical evaluation of economic consequences of shredded CPA reputation: Evidence from Yinguangxia
  • The impact of critical reports issued by government inspectors
  • Financial statement frauds and auditor sanctions: An analysis of enforcement actions in China
  • Auditors’ reporting conservatism after regulatory sanctions: Evidence form China
  • What do we know about audit quality?
  • Determinants and market consequences of auditor dismissals after accounting restatements
  • How to make public enforcement work in weak investor protection countries? Evidence from China
  • Social capital, property rights, and qualification of listing: Evidence from IPO on the SME board
  • Regulatory sanctions and reputation of investment bank
  • The effect of financial restatement on auditor dismissal
  • Criticisms of auditors and the association between earnings and returns of client firms
  • Mandatory audit firm turnover, financial reporting quality, and client bargaining power: The case of Arthur Andersen
  • Restoring trust among investors after shredded CPA reputation: Evidence from China
  • Examination of the importance of an auditor’s reputation
  • Regulatory propensity toward auditor liability in audit failures: An empirical analysis
  • Do political connections add value to audit firms? Evidence from IPO audits in China