Do Auditors Respond to Media Coverage? Evidence from China

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Do Auditors Respond to Media Coverage? Evidence from China Stephen X. GONG University of Auckland Business School New Zealand Tel: (64) 9 923 5105 E-mail: [email protected] Ferdinand A. GUL Department of Accounting, Deakin University, Burwood, Melbourne E-mail: [email protected]

Liwei SHAN Research Institute of Economics and Management Southwestern University of Finance and Economics Chengdu, Sichuan, China

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E-mail: [email protected]

accepted manuscript Xiaohong Liu, Bikki Jaggi, K.K. Raman, Agnes Cheng, Linda A. Myers, Mujtaba Mian, Jun-Koo Acknowledgements:

We thank Mark DeFond, Omrane Guedhami, Ole-Kristian Hope, Yongtae Kim, Dan Simunic,

Kang, Wei-ling Song, Ji-Chai Lin, Mark Bliss, Rui Ge, Jun Du, Nancy Su, Simon Fung, Steven Cahan, participants at the American Accounting Association Auditing Section Midyear Conference

2013

(especially

Nancy

Harp,

the

Discussant),

participants

at

the

XJTLU/Accounting Horizons conference 2017 (especially the Discussant), and seminar participants at The Hong Kong Polytechnic University and at Southwestern University of Finance and Economics for helpful discussions and comments. We also thank the Editor (Vernon Richardson) and the anonymous reviewers for their constructive comments. The work described in this paper was undertaken when Stephen Gong was with the Hong Kong Polytechnic University, and was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (PolyU 5427/09H, 5922/13H). Liwei Shan

acknowledges financial support from Ministry of Education of the People’s Republic of China (14XJC790007). All errors are our own.

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Do Auditors Respond to Media Coverage? Evidence from China ABSTRACT

This paper examines whether news coverage of client firms is associated with their audit fees. Using data from China listed firms during 2004-2013, we find that high coverage client firms are on average charged higher audit fees, irrespective of the media tone. This positive association is stronger for large auditors than for small auditors, and for bad news than for good news. The main results hold for both state-owned enterprises (SOEs) and non-SOEs, and for both politically connected and non-connected firms. The results are robust after controlling for the effects of information asymmetry, auditor choice, internal corporate governance, and alternative measurements of the key variables. Overall, our evidence is supportive of the view that auditors assess high coverage clients as higher risk audits requiring greater audit efforts. We conclude that the financial news media plays a disciplining role in China through its potential to trigger reputational sanctions and regulatory action.

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Keywords: Media coverage; public attention; reputational sanctions; regulatory action; audit fee; auditor size; audit risk; China.

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1. INTRODUCTION This paper examines whether auditors in China are affected by external information in their assessments of audit risk. More specifically, we examine whether news coverage affects auditors’ assessments of audit risk, the expected audit effort required, and hence the audit fees charged. The effect of media coverage on audit judgment is not new and has been documented in prior studies. Mutchler, Hopwood, and McKeown (1997) find that Wall Street Journal coverage of a client’s debt default is associated with an increased likelihood that auditors would issue modified audit opinions (MAOs), although the negative coverage does not increase the client’s probability of bankruptcy. Using an experimental design, Joe (2003) finds no evidence that negative media coverage increases auditors’ perception of legal liability; instead, negative media coverage increases auditors’ perception of a client’s bankruptcy probability and this, in turn, leads auditors to issue MAOs. Since by design the press coverage contained no new information, Joe concludes that the auditors in her experiment over-reacted to negative news coverage.1 While auditors are expected to build into their audit risk assessments both internal and external sources of information, an important source of external information that is potentially

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useful for assessing audit risk, but that has been neglected in the audit pricing literature is media coverage of client firms. This is somewhat surprising since it is argued that the media collects (sometimes through original investigation) and disseminates information that is new, relevant

accepted 2009; Bushee, Core, Guay, and Hamm 2010). The media is also known to report on corporate manuscript and useful to market participants (Bushman, Piotroski, and Smith 2004; Kothari, Li, and Short

frauds (Miller 2006; Dyck, Morse, and Zingales 2010) which, in turn, may implicate auditors. For example, Fortune’s role in uncovering the Enron scandal and causing the demise of Enron’s auditor Arthur Andersen is a US case in point.2 In China, a series of reports by Caijing magazine

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Auditor over-reaction to media coverage has important implications. If repetition of information leads auditors to conclude that the information has additional value or is more informative than it actually is, training may be necessary to overcome this effect. Furthermore, if exposure to redundant press coverage increases auditors’ propensity to issue more MAOs than is justified, policymakers might be concerned that unsophisticated users of audited financial statements may be misinformed and adversely affected. The results may also have implications for audit clients; for example, an MAO may increase the client’s financing difficulty and costs, or lead to “self-fulfilling prophecies” (Joe 2003). 2 See "Is Enron Overpriced?", Fortune, 5 March 2001.

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in 2000 about corporate frauds led to the downfall of several listed firms, including Yinguangxia and its auditor Zhongtianqin.3 We are motivated to examine the link between news coverage and audit fees of Chinese firms for a number of reasons. First, despite the increasing recognition of the role of the press as a key variable or an important control variable in accounting, finance and economic studies (Dyck and Zingales 2002; Miller 2006; Tetlock 2007), there is scant research on whether the amount or type of media information (e.g., positive versus negative coverage) is associated with auditors’ risk assessments and audit pricing. Second, although a relatively large number of studies have been conducted in the US on the role of the media in financial markets, to our knowledge there are few studies in developing economies such as China, especially in terms of the financial reporting process and auditing. Given the move towards harmonization and internationalization of auditing standards such insights would be useful for international policy makers. 4 Finally, China’s securities and exchange regulations require listed firms to publish material information in major newspapers and periodicals. In addition, China’s auditing standard (CICPA 2009, 520) requires that auditors consider media reports in their assessments of audit

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risk. Thus, auditors are expected to scrutinize news reports to assess the client’s financial condition and risk of financial misreporting.5

Using firm-level data from China’s stock market during 2004-2013, we find that client

accepted ceteris paribus. After controlling for the linguistic tone of news coverage, we find that large manuscript

firms with greater amounts of news coverage are on average associated with higher audit fees,

auditors charge higher audit fees for high coverage, irrespective of the media tone, though the high coverage audit fee premium tends to be higher in the case of bad news. By contrast, small auditors do not charge higher audit fees for high news coverage, irrespective of the media tone. The results hold for both state-owned enterprises (SOEs) and non-SOEs, and both politically connected and non-connected firms. They are also robust after controlling for the effects of

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http://www.economist.com/node/1049853. See also Caijing (2003). The institutional features surrounding media information production/dissemination and the audit market in China are different from those in the US-led developed economies. A distinct feature of the Chinese market is that the media and most of the listed firms are controlled by the state. This potentially leads to a lack of media independence, which is a critical determinant of the public monitoring role of the media (Dyck and Zingales 2002). Given this setting it is an interesting open question whether and how auditors in China respond to media coverage in assessing client audit risk. 5 Our conversations with industry practitioners confirm that they read news reports for signs of irregularity. 4

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information asymmetry, auditor choice, potential endogeneity in media coverage, internal corporate governance, and alternative measurements of the key variable. We test several alternative explanations for our findings. The first is that both audit fees and news coverage are driven by a third factor positively associated with audit efforts. We address this concern in a variety of ways. First, we control for the number of major corporate events (including right offerings, mergers and acquisitions, spinoffs, re-organization, new plants), to address the concern that firms experiencing more corporate events may have more complex accounting and operational decisions, require greater audit efforts and hence are charged higher audit fees. We also control for income and the number of employees (in addition to firm size) to rule out the possibility that these factors drive both media coverage and audit fees.6 In addition, we control for factors that prior studies find are associated with litigation risk (Stice 1991; Shu 2000; Seetharaman, Gul, and Lynn 2002).7 The positive association between news coverage and audit fees remains, so our results are unlikely to be driven by omitted correlated variable bias. A second explanation for our findings is that news coverage contains new negative signals about clients and such bad news increases auditors’ audit risk assessments which, in turn,

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increase audit fees (e.g., Pratt and Stice 1994). While the finding of a stronger association between negatively toned news coverage and audit fees is consistent with such an informationbased argument, it is inconsistent with the finding of a robust positive association between

accepted using lagged (by one year) news coverage manuscript in place of contemporaneous news coverage. The

positive news coverage and audit fees among large auditors. We further test this explanation by

positive association between news coverage and audit fees remains. Since the effect of any news coverage in the previous year should be reflected in the audit fee for that year, the positive association is unlikely to be primarily driven by news reports conveying new signals about the clients. The consistently positive association between news coverage and audit fees also does not mesh well with the hypothesis that high media coverage lowers the ex ante audit risk, which would predict a negative association between news coverage and audit fees for both large and small auditors, and irrespective of the media tone.

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We thank a reviewer for suggesting that we control for economic importance (proxied by income and number of employees). 7 In China, auditor's legal liability to investors is quite limited (Simunic and Wu 2009).

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Overall, our findings are more consistent with the view (“disciplining role” hypothesis) that news coverage increases auditors’ risk assessments and the expected audit effort because of a concern that higher media visibility increases public (including regulators’) attention, and thus the costs of making a Type II error, i.e., the auditor does not detect financial misreporting when in fact there is financial misreporting (Mutchler, Hopwood, and McKeown 1997). The stronger association between news coverage and audit fees for large auditors (especially in the case of bad news) is consistent with their greater reputation at stake (DeAngelo 1981), and their greater risk of being targeted for regulatory action in case of audit failure. The stronger association between news coverage and audit fees in the case of negative publicity is consistent with stronger aversion to bad news (Kahneman and Tversky 1979). The latter two findings are consistent with distinctive predictions of the “disciplining role” hypothesis. Our study contributes to the literature in several ways. First, as far as we know, our study is among the first to empirically examine the relation between news coverage and audit pricing. Our finding of a positive association between news coverage and audit fees is novel, and extends Joe’s (2003) experimental finding that negative news coverage heightens auditors’ perception of

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audit risk. Second, our paper adds to the growing literature on the role of the media in financial markets (Tetlock 2014). We extend this literature by focusing on whether media coverage affects the decisions of professional auditors, as opposed to individual traders/investors. Third, we focus

accepted market environments from the US, where most capital market-based media studies have been manuscript on the effects of media coverage on audit pricing in China, with very different institutional and

conducted. Our finding of a positive association between news coverage and audit fees suggests that auditors view higher coverage clients as requiring greater audit effort due to greater public and regulators’ attention embodied in higher news coverage, and consequently higher risks. This is consistent with a disciplinary role of the media. Such a finding is interesting because, although both the media and most of the listed firms are controlled by the state, auditors in China still perceive higher media visibility as representing higher audit risk. The finding is consistent with the view of Liebman and Milhaupt (2008) that the Chinese media can play a corporate governance role through reputational sanctions and by triggering regulatory actions. Section 2 discusses the institutional background of China’s audit environment and financial news media, followed by development of the hypotheses. Section 3 discusses the

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sample data and empirical method. Section 4 presents and discusses the results from the main and robustness tests. Section 5 concludes.

2. BACKGROUND AND HYPOTHESES China’s Audit Environment and Financial News Media Prior to 1997, China’s auditors were affiliated with the government. In an attempt to increase credibility in its capital markets, China initiated an auditor disaffiliation program in 1997-1998 (Gul, Sami, and Zhou 2009). However, to date auditors are still subject to significant political influence (Chan, Lin, and Mo 2006). China introduced a new set of accounting rules in the 1990s that are comparable to International Accounting Standards, and auditing standards that are patterned after the International Standards on Auditing (DeFond, Wong, and Li 2000). Despite this, there remain significant impediments to the demand for, and supply of, high quality audit service. These include the predominance of government ownership or effective control of both the majority of the listed firms and many of the audit firms, a special institutional feature which offers one fruitful avenue of accounting research not typically available in other market

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contexts (Chen and Schipper 2008; Simunic and Wu 2009). The effects of China’s audit environment on audit quality have been examined in several recent studies (e.g., DeFond, Wong, and Li 2000; Chan, Lin, and Mo 2006; Wang, Wong, and Xia 2008; Chen, Sun, and Wu 2010).

accepted media, but many areas have gradually opened up for relatively free reporting, especially in arts manuscript

Traditionally, the Chinese government has retained strong political control over the news

and leisure, and finance and economics (Chen 2003; Esarey 2006). Recent years have witnessed increased attention being paid to the role of the financial news media as a public monitoring mechanism (Chen 2005). Liebman and Milhaupt (2008) find that public criticisms have significant effects on Chinese listed companies, with the effects extending beyond the stock market to banks and regulators. They suggest that the Chinese media can play a potentially important corporate governance role through reputational sanctions and by triggering regulatory action.8 On the other hand, there are allegations and anecdotal evidence that China’s press lacks

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See Caijing (2003) for evidence on the role of the media in whistle-blowing on corporate frauds and causing the government to step up financial regulation in China.

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independence and credibility due to media censorship and conflicts of interest. 9 To our knowledge, no study has examined the issue of whether and how auditors in China are affected by media coverage of their clients. Effects of Media Coverage on Financial Market Participants Despite the increasing recognition of the role of the press in financial markets (Miller 2006), there is very limited evidence on whether and how auditors use media information (two exceptions are Mutchler, Hopwood, and McKeown 1997, and Joe 2003). In contrast, there is a large and growing literature on the impacts of media coverage on other financial market participants, especially traders (Tetlock 2014). On one hand, the media can impact corporate finance and corporate governance by disseminating information to investors (Merton 1987; Bushee et al. 2009; Fang and Peress 2009), and by placing public pressure on key decisionmakers (Dyck and Zingales 2002; Liu and McConnell 2013). On the other hand, however, news in the media are not linked to stock pricing/trading (Cutler, Poterba, and Summers 1989; Fair 2002) or governance choices (Core, Guay, and Larcker 2008; Bednar 2012). Yet another view indicates that media coverage lacks in-depth research, tends towards

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sensationalism, and thus may play a negative role (Jensen 1979; Miller 2006; Core, Guay, and Larcker 2008; Ahern and Sosyura 2015). Dyck and Zingales (2003) suggest that the press may encourage financial bubbles by adopting a company’s spin in return for private information.

accepted suggest that the media may mis-inform or unduly influence investors and cause mispricing. In manuscript Shiller (2005), Chen, Pantzalis, and Park (2013) and Engelberg, Sasseville, and Williams (2012)

the US market, Gurun and Butler (2012), Solomon (2012) and Ahern and Sosyura (2014) find that firms influence investor expectation and stock prices by actively influencing media coverage through advertising and the use of investor relations firms. Thus, the extant literature provides a rather mixed view of the roles, effects and micromechanisms of media coverage. An important unexplored question is whether, and how, media coverage affects decision-making by more sophisticated users, such as external auditors. Given 9

As evidence of media censorship, a Chinese magazine was recently closed down for publishing criticisms of a Central Government-controlled company (http://cn.wsj.com/big5/20100514/rec150518_ENversion.shtml). As another example, in 2009, Hu Shuli, Editor of Caijing magazine, resigned after a scuffle over editorial control with the publication's state-affiliated owner (see "Editor Departs China Magazine after High-Profile Tussle", The New York Times, 9 November 2009). For evidence of conflict of interest, see “In China Press, Best Coverage Cash Can Buy”, The New York Times, 4 April 2012. According to that report, some Chinese media regularly publish “paid news” that are essentially advertisements masquerading as news.

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that professional auditors have very different expertise, information sources and incentives compared to individual investors, conclusions from prior (primarily US-based) capital market studies need not to apply to auditors, either in general, or in China. News Coverage and Audit Fees Since the seminal work of Simunic (1980) numerous studies have examined issues related to the determinants of audit fees (e.g. Gul and Tsui 1998; Seetharaman, Gul and Lynn 2002; Gul, Khedmati, Lim, and Navissi 2018). Two stylized findings are that auditors price their services based on the size of the client, the complexity of the client’s operations and the level of assessed risks for the client (Hay, Knechel, and Wong 2006), and that clients with stronger corporate governance mechanisms demand for higher audit efforts which translates to higher audit fees (e.g., Carcello, Hermanson, Neal and Riley 2002; Srinidhi and Gul 2007; Cao, Myers and Omer 2012).10 In this paper, we examine whether media coverage affects the level of audit fees charged, controlling for other determinants identified in prior studies. Media coverage has the potential to impact audit fees for several reasons. First, media coverage may convey new information that is

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otherwise not accessible by auditors; for example, the media may uncover accounting irregularities (Miller 2006). This reasoning indicates that bad news coverage leads to higher audit fees, though good news coverage is likely to lead to lower audit fees (to the extent the

accepted information was known to the auditor). We call this the “information role” hypothesis. manuscript

information was not previously known to the auditor) or is not associated with audit fees (if the

Second, high media visibility increases public (including regulators’) attention and the cost and risk of being caught (i.e. the cost of type II error from the auditors’ perspective), and thus makes auditors work harder. Because large auditors have greater reputational capital at stake (DeAngelo 1981), they are likely to be more concerned about high media visibility. In addition, due to loss aversion (Kahneman and Tversky 1979) auditors are likely to expend even greater effort/resources if the media coverage is negative. This line of reasoning makes two distinct predictions: (1) a positive association between media coverage and audit fees on average; (2) the association is stronger for large auditors, and holds for both positive and negative coverage,

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See DeFond and Zhang (2014) for a comprehensive review.

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though the association may be stronger for bad news. 11 We call this the “disciplining role” hypothesis. Third, the media potentially improves the client firm’s information environment, by collecting, analyzing and disseminating information broadly to market participants (Bushman, Piotroski, and Smith 2004; Fang and Peress, 2009). This leads to lower information asymmetries and higher corporate transparency (Dyck, Volchkova, and Zingales 2008; Kothari, Li, and Short 2009; Bushee et al. 2010), in turn lowering the ex ante audit risk. Furthermore, the heightened public and regulatory scrutiny resulting from greater media coverage may reduce the ex ante audit risk because managers provide better financial reporting quality. Both of these arguments suggest a negative association between media coverage and audit fees, irrespective of the media tone. We call this (a simple version of) the “governance role” hypothesis. While the above arguments generally suggest an association between the amount/tone of media coverage and audit fees, a counter-argument is that the media in China is controlled by the government, which also controls the majority of the listed firms (as well as many of the auditors). This leads to potential conflicts of interest and a lack of media independence. In this view, media

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coverage in China does not play any of the roles mentioned above. As such, we can expect no relation between media coverage and audit fees. We call this the “captured media” hypothesis. Given the above conflicting arguments, a priori it is unclear whether media coverage is

accepted H1a (Information role hypothesis): Audit fees are positively (negatively) associated with manuscript

associated with audit fees in China. We state our first hypothesis as follows:

the amount of bad (good) news coverage of client firms. H1b (Disciplining role hypothesis): Audit fees are positively associated with the amount of news coverage of client firms, irrespective of the media tone. H1c (Governance role hypothesis): Audit fees are negatively associated with the amount of news coverage of client firms, irrespective of the media tone.

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Caijing (2003) chronicles stories regarding the role of the media in whistle-blowing on corporate frauds and causing the government to step up financial regulation in China. In many of these cases, media attention focused on firms with “good” news (e.g., Yinguangxia, one of the best performing stocks in the two years before its financial reporting fraud was uncovered) rather than those with poor performance. Such episodes suggest that auditors need to pay attention to both good and bad news.

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H1d (Captured media hypothesis): Audit fees are not associated with the amount of news coverage of client firms, irrespective of the media tone. Auditor Size Effect Prior research finds that large auditors are associated with higher audit quality (Palmrose 1988; Teoh and Wong 1993) and higher audit fees (Gul 1999; Hay, Knechel, and Wong 2006). In contrast, there is little prior research on whether the relation between news coverage of clients and their audit fees is moderated by auditor size. As large auditors have more reputational capital at stake (DeAngelo 1981), they generally demonstrate greater risk aversion, which is likely further heightened by greater client visibility in the media. Therefore, compared to small auditors, large auditors are likely to take news coverage more seriously, irrespectively of the media tone, though closer scrutiny may be even more likely if it represents bad news.12 By contrast, other than being in a weaker competitive position (vis-à-vis both clients and large auditors), small auditors are relatively resource-constrained.13 In the “information role” and the “governance role” arguments, auditors, no matter their size, should respond in a similar way to the assessed misreporting risk. Therefore, auditor size should matter only under the disciplining role

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hypothesis, but not under the other hypotheses. Thus, evidence on the moderating role of auditor size provides additional evidence on the relative validity of the competing hypotheses regarding

accepted stronger news coverage effect on audit fees manuscript for large auditors relative to small auditors, holding the effects of media coverage on audit fees and the underlying mechanism.14

This line of reasoning suggests that only the disciplining role hypothesis predicts a

constant the tone of the news coverage. 15 In addition, to the extent that auditors are more

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While auditors are more likely to be put on the alert by bad news, extra audit effort may still be required if the news coverage is positive, as positive coverage may be the result of selective publicity, media slant or “paid news” (Gurun and Butler 2012; Solomon 2012), which could be used to cover up corporate misdeeds, even frauds. See also footnote 11 for China evidence. 13 The greater the inherent risk, the more resources the auditor will have to devote to the audit to reduce detection risk to achieve a given level of audit risk (Gul and Tsui 1998). The need to compete for clients, coupled with the limited resources, may cause small auditors to be less concerned about media coverage of a client, or to be concerned only about negative news coverage. 14 We thank an anonymous reviewer for this point. 15 One counter argument is that large auditors are likely to be industry specialists (we control for industry specialization) and thus are less dependent on the media for information about clients. This would suggest no differential audit fee impact between large and small auditors. However, this argument still leaves open the distinct

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sensitive to bad news than to good news, one would expect negative news coverage to increase the audit fee premium for large auditors. We state our second hypothesis as follows: H2a: The impact of news coverage on audit fees is stronger for large auditors than for small auditors. H2b: Relative to positive news coverage, the impact of negative news coverage on audit fees is stronger for large auditors than for small auditors.

3. DATA AND METHOD Sample The data comprise all A-share companies listed in China’s two domestic stock exchanges in Shanghai and Shenzhen during the period 2004-2013. 16 We choose the year 2004 as the starting period because, although the disclosure of audit fees became mandatory in 2001, there is limited data (for audit fees, analyst coverage and some other variables) before 2004. IPO stocks trading for fewer than 200 days since listing are excluded to abstain from the well-documented

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IPO anomalies. Stock returns and financial statement data are obtained from the China Stock Market and Accounting Research (CSMAR) database. The identity of auditor and audit opinion data are obtained from CSMAR and are verified with annual reports to ensure accuracy. Other

accepted with valid data for news coverage, auditor information and financial variables. manuscript

data are from WIND. Our primary sample constitutes a total of 9,845 firm-year observations

News Coverage Measures To ensure that we capture independent media coverage rather than firm-initiated disclosures, we only retain media reports that are authored by staff reporters or non-company officials.17 Our first measure is a simple frequency count of news articles (in which a company’s full name or abbreviation or stock code is mentioned anywhere) that appear in the three major possibility that large auditors have more concerns about regulatory sanctions and reputational loss if caught in error auditing a client with high media visibility. 16 All Chinese-listed firms issue tradable shares, called A-shares, to domestic investors, while some of these firms also issue shares to foreign investors (e.g., B-shares, traded on the Shanghai or Shenzhen stock exchange, and Hshares, traded in Hong Kong). A-shares represent the lion’s share of China’s domestic stock market (see Gul, Kim, and Qiu 2010; Firth, Gong and Shan 2013). 17 Such reports normally indicate “staff reporter so and so”. The results are qualitatively the same if we exclude commentaries by analysts/brokerage houses. The media reports data (including various summary statistics and the full-text news articles), along with additional filtering and data processing services, are purchased from CSMAR.

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national securities newspapers (China Securities Journal, Securities Daily, and Shanghai Securities Journal) in each calendar year. We add the news counts from all sources on the assumption that news stories appearing in more publications convey more news (Bushee et al. 2010) and/or grab more attention (Barber and Odean 2008). Our second measure is the number of articles from the aforesaid newspapers in which a company’s full name/abbreviation/stock code appears in the headline or lead paragraph of the article. Our third measure is the number of days in which a news story about a listed company is published in the three securities newspapers (multiple news stories on the same day are counted once).18 The fourth measure is the number of news articles published in 98 Chinese newspapers including the aforesaid securities newspapers. By virtue of its wide inclusiveness, the last measure may overcome potential problems associated with use of the three national securities newspapers which are designated by China Securities Regulatory Commission (CSRC) as mandated corporate disclosure platforms. To the extent that newspaper coverage is positively correlated with overall coverage across media types, the number of newspaper articles or news days may reasonably proxy for overall media exposure (Fang and Peress 2009).

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Since it is unlikely that the impact of number of news articles or news days on audit fees follows a monotonic one-for-one relation, we divide the sample firms into a high coverage group and a low coverage group each year. All firms whose number of news articles (or news days)

accepted Since group affiliation is almost always the same for the four measures of news coverage, manuscript

falls in the top tercile are classified as High Coverage firms, and the remaining as Low Coverage firms.

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from this point on we simply refer to news coverage as being high or low, without referring to the specific measure of news coverage used. It is a major empirical challenge to determine the tone of news coverage of a given firm, especially when a large amount of news reports is involved. A frequently used approach in prior studies is content analysis (e.g., Tetlock 2007; Tetlock, Saar-Tsechansky, and Macskassy 2008; Kothari, Li, and Short 2009; Gong and Gul 2009). However, a major weakness and criticism of this method of classifying news (typically based on counting positive and negative words or information categories) is that it does not properly account for whether the linguistic content/tone 18

This measure of media coverage is similar to that used in Chan (2003) amongst others. This dummy variable approach also mitigates the concern that the raw count of news articles may be overstated due to duplicated reports (i.e., essentially the same news appearing in different newspapers) as there is no reason to believe that the publication of duplicated news reports will affect particular types of companies more than others.

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of the reports represents genuine news (i.e., incremental, new information) that is actually used by market participants (Dougal, Engelberg, Garcia, and Parsons 2012; Engelberg, Reed, and Ringgenberg 2012).20 It is also unclear what weighting scheme should be used when aggregating the linguistic content of different news reports. In this study follow Ge and Lennox (2011) and capture the linguistic content/tone of individual firm-specific news reports based on the market-adjusted cumulative abnormal return (CAR) during the 3-day window centered on the news report date. We aggregate the CARs within the fiscal year to obtain an overall CAR per firm per year. Firms whose overall CAR in a given year is positive (negative) are designated as “good news” (“bad news”) firms. We conducted a manual content analysis of individual news reports for a random sample of firm-year observations to verify that the return-based summary measure of news content is indeed associated with the linguistic content/tone of the news reports (see Appendix A).21 Empirical Model To test our hypotheses, we estimate the following equations (with firm and time subscripts suppressed for simplicity):

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LAF=b0+b1HighCoverage+b2Top10+Controls+Fixedeffects+e,

(1)

LAF=b0+b1HighCoverage+b2Top10+b3HighCoverage*Top10+Controls+Fixedeffects+e, (2) where:

accepted High Coverage = dummy variable coded 1 for High Coverage firm, and 0 otherwise; manuscript LAF = natural logarithm of audit fees (in thousands of yuan);

Top10 = dummy variable coded 1 if the firm is audited by a Top10 auditor, and 0 otherwise; HighCoverage*Top10 = the interaction between High Coverage and Top10; Control variables = these vary across different model specifications and are defined in each table; Fixedeffects = year and industry fixed effects; and e = random-error term.

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Loughran and McDonald (2010) find that content analysis software such as the General Inquirer often misclassifies the tone of financial terms (see also Li 2010). Additionally, there is no commercially available Chinese-language equivalent of the General Inquirer. A full manual content analysis is impracticable given the large-scale nature of this study. 21 Engelberg, Reed, and Ringgenberg (2012) using an approach similar to Ge and Lennox (2011) find qualitatively the same results whether using the return-based measure or the negative-positive word measure of linguistic content.

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We test the hypotheses by estimating Equation (1) and Equation (2) respectively for the whole sample, and by estimating the two equations for the "good news" and "bad news" subsamples separately. To alleviate concerns that the news coverage effect we document might be due to omitted correlated variable bias, in all the audit fee regressions we control for other client attributes, auditor attributes and engagement attributes found by prior studies to be related to audit fees (Francis, Reichelt, and Wang 2005; Hay, Knechel, and Wong 2006; Gul and Goodwin 2010; Fung, Gul, and Krishnan 2012).22 We control for whether a qualified audit opinion is issued, as this may indicate the existence of audit problems, which, in turn should increase the audit risk/effort and hence the audit fee (Johnson, Walker, and Westergaard 1995; Larcker and Richardson 2004; Lyon and Maher 2005). In addition, we control for internal governance variables (Tsui, Jaggi, and Gul 2001; Carcello et al. 2002) and industry- and year-fixed effects to further mitigate omitted variable bias.23 Appendix B contains the variable definitions.

4. EMPIRICAL RESULTS Preliminary Analysis

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Table 1, Panel A reports the summary statistics of select variables for the whole sample. On average the client firms have 22 news reports per year during the sample period, ranging

accepted rising trend over time. The average auditmanuscript fees also show a rising trend over time, and

from a maximum of over 600 news stories and a minimum of zero. News coverage shows a

demonstrate considerable inter-firm variation in any given year. The propensity of MAOs (untabulated) for our sample is very similar to the findings in prior studies (e.g., Chen, Sun, and Wu 2010). Panel B shows that client firms with high news coverage are larger in size and pay higher audit fees. Relative to low coverage firms, high coverage firms tend to have better accounting and stock performance, higher leverage, and shorter-tenure auditors. High coverage firms also

22

Our choice of client characteristics, auditor attributes and engagement characteristics also controls for the impact of litigation risk (Stice 1991; Shu 2000; Venkataraman, Weber, and Willenborg 2008) on audit fees. 23 In view of the fact that both audit fees and media coverage (specifically, the high versus low coverage group affiliation) do not vary significantly from year to year, following typical audit fee studies, we do not use firm fixed effects, to avoid “throwing out the baby along with the bath water” (Angrist and Pischke 2009).

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tend to be more complex (i.e., more corporate events and business segments), and are more likely to be SOEs under the Central Government. Panel C reveals that, relative to clients of small (non-Top10) auditors, clients of large (Top10) auditors on average are larger, receive more news coverage, pay higher audit fees, and have a lower propensity of MAOs. The clients of large auditors are more likely to be controlled by the Central Government, but less likely to be controlled by local governments, consistent with prior literature (e.g., Wang, Wong, and Xia 2008) which suggests that local firms are more likely to engage small auditors. [Insert Table 1 about here] Table 2 shows the correlation coefficients for the variables. The high and positive correlations between audit fees, news coverage, auditor size and auditee size are consistent with the results from Table 1.24 [Insert Table 2 about here] News Coverage, Auditor Size and Audit Pricing: Baseline Results [Insert Table 3 about here]

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Table 3 presents the results of estimating Equation (1). Column (1) shows the results for the whole sample. The coefficient on High Coverage is positive and statistically significant, suggesting that on average, high coverage firms pay approximately 5% higher audit fees than

accepted and number of employees), complexity, number of major corporate events, and a bunch other manuscript low coverage firms, controlling for auditor size, auditee size and economic importance (revenue

client and engagement characteristics.25 Thus, other things equal, auditors on average charge a higher audit fee for high coverage client firms.

Column 2 shows the results for the "good news" sub-sample. The coefficient on High Coverage continues to be positive and statistically significant. All else equal, clients with greater amounts of positive news pay approximately 3% higher audit fees than comparable firms with low amounts of positive news coverage. Column 3 shows the results for the "bad news" sub-sample. The coefficient on High Coverage is again positive and highly statistically significant. All else equal, clients with high 24

The variance inflation factor scores (untabulated) are all well below the threshold of 10, suggesting that multicollinearity is not a serious concern. 25 Since the dependent variable is in logarithm, the percentage change is computed as EXP(0.05)-1= 5.13%. We round up the percentage in the subsequent discussions.

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negative news coverage pay approximately 7% higher audit fees than do comparable firms with low negative news coverage. A Chi-square test indicates that the coefficient on High Coverage is larger for the "bad news" sub-sample compared to the "good news" sub-sample. We interpret the evidence as indicating that high news coverage is associated with higher audit fees, and that the positive association between news coverage and audit fees is stronger for bad news relative to good news. This provides tentative support for the “disciplining role” hypothesis (H1b). The positive and statistically significant coefficient on Top10 indicates that clients of large auditors on average pay approximately 20% higher audit fees than clients of small auditors. The presence of an auditor size premium is consistent with prior studies (e.g., DeFond, Wong, and Li 2000; Hay, Knechel, and Wong 2006; Wang, Wong, and Xia 2008). Several client attributes including auditee size and economic importance, receivables (scaled by total asset), loss, return volatility, tenure, modified audit opinion, number of business segments, number of major corporate events, and industry specialization are positively and statistically significantly related to audit fees. The coefficients on inventory (scaled by total asset), quick ratio, leverage and number of analysts following are negative and statistically

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significant in most cases. The results for these control variables are largely consistent with existing research (Hay, Knechel, and Wong 2006; Gul, Fung, and Jaggi 2009). Relative to privately owned firms (the omitted category), SOEs under the Central Government and SOEs

accepted and Xia (2008). Given the focus of our study, from this point on we omit the discussion of the manuscript

under the local government are associated with lower audit fees, consistent with Wang, Wong,

control variables. The adjusted R-square of about 0.60 indicates reasonable goodness of fit. Table 4 presents the results of estimating Equation (2) with the interaction term between High Coverage and Top10 added to test H2a and H2b. Column (1) is for the whole sample. The coefficient on High Coverage is statistically insignificant, so there is no evidence that clients of small auditors pay higher audit fees for high news coverage. The coefficient on Top10 (0.146) is positive and statistically significant. This indicates that for low news coverage clients, large auditors on average charge about 16% higher audit fees than small auditors do, all else equal. Our interest is in the coefficient on the interaction term, which is 0.131. This is significant both statistically and economically, suggesting that the Top10 audit fee premium increases by a further 14% if the client receives high news coverage. Thus, for high news coverage clients, large auditors charge approximately 30% higher audit fees in total than small auditors do. This 16

evidence is consistent with H2a that large auditors are particularly sensitive to high news coverage of their clients. We next investigate whether the effect of high news coverage on the auditor-size related audit fee premium varies depending on the tone of the news. The results for good news and bad news clients are reported in Column (2) and Column (3) respectively. The coefficient of High Coverage is statistically insignificant for both good and bad news. This indicates that small auditors do not charge their clients higher audit fees for high news coverage, irrespective of the tone of the coverage. This result is consistent with the “disciplining role” hypothesis that small auditors have less reputation at risk and therefore are not as sensitive to media coverage. In Column (2), the coefficient of Top10 is 0.134, significant at the 1% level. This indicates that large auditors charge low news coverage clients approximately 14% higher fees than small auditors do. This is again consistent with an audit fee premium for large auditors. Of particular interest, the coefficient of the interaction term High Coverage*Top10 is 0.122 (significant at the 1% level). This indicates that, relative to small auditors, large auditors charge their clients an extra 13% audit fee premium for high news coverage, even when the news

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coverage represents predominantly good news.

Column (3) reports results for bad news. The coefficient on Top10 is 0.157, significant at the 1% level. The coefficients on High Coverage*Top10 is 0.143 (significant at the 1% level), so

accepted news coverage. This effect is larger in magnitude compared to the case of positive news coverage manuscript

the large-auditor premium increases by a further 15% when their clients receive high negative

(the difference is statistically significant according to a Chi-square test). This indicates that large auditors further increase the audit fee premium when their clients receive high coverage that is predominantly bad news (compared to good news). The evidence is consistent with H2b. A comparison of the results in Table 3 and Table 4 suggests that the positive association between news coverage and audit fees documented for the whole sample is mainly attributed to large auditors, who charge higher audit fees for both good news and bad news coverage, but especially for bad news coverage. It seems that small auditors either do not worry about news coverage, or do not have the market power to charge a premium for high news coverage. While this finding is interesting, in the rest of this paper we focus on exploring possible explanations for the documented positive association between media coverage and audit fees for large auditors, which holds irrespective of the media tone, but is stronger for bad news. 17

Further Discussion of the Baseline Results Our finding of a positive relation between audit fees and amount of news coverage is novel. Since we have controlled for characteristics associated with litigation risk in the baseline tests, it cannot be attributed to, but instead is incremental to, concerns for litigation risk. By controlling for the number of major corporate events and firm complexity, we have also addressed the possibility that the higher audit fees are attributable to greater effort required for auditing client firms that are more complicated or have experienced more developments. Consistent with the “disciplining role” hypothesis, higher media coverage increases the expected audit effort due to the greater public (including regulators’) attention embodied in high news coverage. Although auditors are more likely to be concerned with negative news coverage (Mutchler, Hopwood, and McKeown 1997), extra audit efforts may still be required for “good news” clients, as positive news coverage could be the result of selective publicity, media slant, “paid news” (Gurun and Butler 2012; Solomon 2012; Bednar 2012) or cover-up (Caijing 2003). Thus, clients with high news coverage, be it positive or negative, may be viewed as higher risk audits requiring greater audit efforts and hence higher audit fees.26 Given that large auditors have

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more reputational capital at stake (DeAngelo 1981), their concern for triggering reputational sanctions and regulatory action is further heightened by greater client visibility in the media. The finding of a stronger media effect on audit fees for large auditors is consistent with this

accepted In contrast to the “disciplining role”manuscript explanation above, one may argue that auditors

“disciplining role” hypothesis.

charge higher fees for high coverage because the news reports are indeed informative, in the sense that auditors may learn something new about the clients from the news reports. The latter “information role” hypothesis predicts a positive audit fee-high coverage association for bad news, and a negative association for good news. In addition, the “information role” hypothesis

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In recent years, The Ministry of Finance (MoF) and the Chinese Institute of Certified Public Accountants (CICPA) regularly conduct inspections of audit firms in an effort to improve audit quality. While, to the best of our knowledge, there are no official guidelines on the specific criteria used for determining which audit firms are inspected, our reading of the various documents on the MoF and CICPA websites indicates that the focus is on key entities that involve high audit risk (e.g., SOEs, listed firms, financial institutions). It can be expected that, to the extent that media coverage grabs the regulators’ attention, auditors of high media coverage clients are more likely to be inspected, other things being equal. Ball (2009) discusses the role of the US press in exaggerating the accounting scandals during 2001-2002 and possibly contributing to political/regulatory overreaction to the scandals.

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does not predict any difference between large and small auditors. So far, our evidence is inconsistent with this view. In another effort to distinguish the “disciplining role” and “information role” explanations, we re-run the baseline regressions after substituting one-year lagged High Coverage for contemporaneous High Coverage. The untabulated results are qualitatively the same as those in Table 3 and Table 4. We interpret this as lending further support to the “disciplining role” explanation rather than the “information role” explanation—by using lagged High Coverage in lieu of contemporaneous High Coverage, we can significantly discount the possibility that auditors charge high coverage clients higher fees because they learn new information about their clients’ current financial situation by reading the news reports (the effects of any news in prior year media reports should have been reflected in that past year’s audit fees). 27 The consistently positive association between media coverage and audit fees irrespective of media tone is also inconsistent with a simple version of the “governance role” hypothesis which predicts a negative association between media coverage and audit fees. Thus, we interpret the positive association between news coverage and audit fees to be

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driven by auditors’ heightened risk aversion toward high coverage clients because high coverage reflects greater public (including regulators’) attention, and hence a higher risk and cost of being caught in error unless (or even if) greater audit efforts are expended. The audit fee premium is

accepted auditors, consistent with their higher reputational capital at stake (DeAngelo 1981). manuscript

higher for bad news, consistent with loss aversion (Kahneman and Tversky 1979), and for large

Additional Analyses and Robustness Tests Effect of Information Asymmetry on Auditor Response to News Coverage Compared to small firms, large firms generally have more information sources (e.g., conference calls and analyst following) and lower information asymmetries (Atiase 1985). Thus, news about large clients may be less informative compared to news about small clients. To investigate the effect of information asymmetry (proxied by the firm size) on auditors’ response

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Given the relatively high persistence in news coverage, however, auditors may be justified in viewing clients with high coverage in the prior year as high coverage clients in the current year. The correlation between lagged and contemporaneous High Coverage is 0.35, significant at the 0.01% level.

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to news coverage, we separate the client firms into large and small auditees, based on median firm size each year. 28 We re-run Equation (2) separately for large and small auditees. [Insert Table 5 about here] The first 3 columns in Table 5 show results for small auditees. Column 1 is for the entire small auditee sample. The coefficient on High Coverage is indistinguishable from zero, indicating that small auditors do not charge higher fees for high news coverage clients than for low news coverage clients. The positive and statistically significant coefficient on Top10 indicates that relative to small auditors, large auditors charge low coverage firms an audit fee premium of about 11%. This is again consistent with an auditor size audit fee premium. Interestingly, the coefficient on the interaction term High Coverage*Top10 is statistically insignificant. This suggests that large auditors do not charge small auditees a further audit fee premium for receiving high media coverage. Similar findings are documented for both good news (Column 2) and bad news (Column 3). Columns 4-6 report results for large auditees. We note that small auditors do not charge large auditees higher audit fees for high media coverage (Column 4) or high negative coverage

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(Column 6), but, all else equal they charge about 5% lower audit fees for large auditees that receive high amounts of good news. Importantly, large auditors not only charge higher audit fees relative to small auditors in all cases, but they also further increase the audit fee premium for

accepted Thus, the positive association between media coverage (irrespective of tone) and audit manuscript

large auditees that receive high amounts of media coverage, irrespective of the media tone. 29

fees for large auditors seems to be concentrated among large auditees, for which information asymmetry is lower and news coverage is potentially less informative (compared to small auditees). This is contrary to what would be expected if information asymmetry surrounding the audit clients, and hence the informativeness of the news reports, drives the positive association between news coverage and audit fees. However, this comes as no surprise, since all our evidence so far has been inconsistent with the “information role” hypothesis, but is consistent

28

The results are qualitatively the same if we use the median firm size within each industry each year. Large auditors’ differential sensitivity to news coverage of large versus small auditees may be due to a number of reasons, including competitive concerns (i.e., charging a premium for high news coverage may constitute double jeopardy for small clients and forces them to switch to small auditors), ability to pay (i.e., large clients can afford a premium for high news coverage whereas small clients cannot), or a combination of both. Future research may investigate these and other possible explanations more fully.

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with the “disciplining role” hypothesis. The additional evidence may be interpreted as lending further support to the “disciplining role” hypothesis--to the extent that large auditees are economically more important clients and large auditees with higher media coverage are more likely to attract public and regulators’ attention (in turn triggering reputational sanctions and regulatory action), auditors should assess such clients as having higher audit risk and expend greater effort in auditing them. Effects of Ownership Type and Political Connection on Auditor Response to News Coverage Two distinct characteristics of the China market are that many of the listed firms are SOEs, and many firms’ chairmen and CEOs are politically connected (Ding, Zhang and Zhang 2007; Fan, Wong and Zhang 2007). Prior studies document an effect of ownership type and political connections on various types of behavior and outcomes in China (Chen et al. 2011; Bailey, Huang and Yang 2011; Firth, Rui and Wu 2011). Given that SOEs, politically connected firms and many auditors are under significant government control or influence, it is of interest to see whether the disciplining role of the news media (in terms of heightening auditors’ risk assessments of clients with high media visibility) differs between SOEs and non-SOEs, and

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between politically connected and non-connected firms. To test this, we divide the sample based on ownership types and political connections and re-run Equation (2) separately for these partitions. The results are reported in Table 6.

accepted Panel A, Columns 1-3 show that while small auditors do not charge SOEs higher fees for manuscript [Insert Table 6 about here]

high media coverage, large auditors charge SOEs an audit fee premium (relative to small auditors) and the premium further increases in the level of media coverage, irrespective of the media tone. For non-SOEs (Columns 4-6), although large auditors continue to charge an audit fee premium (relative to small auditors, who do not charge non-SOEs higher fees for high coverage) and the premium also increases in the level of media coverage irrespective of the media tone, the coefficient on the interaction term High Coverage*Top10 is much smaller in magnitude compared to the case of SOEs. The evidence suggests that large auditors are comparatively more sensitive to media coverage of SOEs than media coverage of non-SOEs. We conjecture that this may be because SOEs typically have higher profiles (economically and politically) than nonSOEs, and thus an audit failure involving these firms may be more costly in terms of triggering reputational sanction and regulatory action. 21

Panel B reports the results for firms partitioned by political connections. Looking across the columns, we note a similar pattern as in the baseline findings: for both connected and nonconnected firms, large auditors charge higher audit fees for high media coverage, irrespective of the media tone (the coefficients on the interaction term High Coverage*Top10 are all positive and statistically significant). Two interesting points are also noteworthy. First, in the case of politically connected firms with high amounts of good news, small auditors tend to reduce the audit fee, and large auditors are also much less sensitive to such news coverage (the coefficient on High Coverage*Top10 is 0.074, which, though still statistically significant, is the lowest of all). We conjecture that this indicates that politically connected firms are able to convince auditors to lower their risk assessments and audit fees when they have a large amount of positive news. Second, large auditors are very sensitive to negative news of politically-connected firms: the coefficient on High Coverage*Top10 is the largest of all cases. We interpret this evidence as being consistent with the “disciplining role” hypothesis, since politically-connected firms with large amounts of bad news are particularly subject to public scrutiny and regulatory action.30 Overall, the results in Table 6 are inconsistent with the “information role” hypothesis and

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“governance role” hypothesis since these hypotheses do not predict the pattern of results document in Table 6. In contrast, the results are consistent with the “disciplining role” hypothesis, and, more importantly, while the partitions by ownership type and political connection have

accepted Addressing Selection Issue in Auditor Choice and Endogeneity in News Coverage manuscript

revealed some nuanced findings, the key results remain similar to the baseline results.

Recent research (e.g., Chaney, Jeter, and Shivakumar 2004; Lennox, Francis, and Wang 2012) shows that failure to control for selection issue in audit research can affect the inferences. To see if our main results are robust to possible endogeneity, we estimate a two-stage model of audit pricing following Lennox, Francis, and Wang (2012). Our first-stage model of auditor choice includes all controls in the second stage, plus discretionary accruals (DA).31 The inverse Mills ratio from the first-stage Probit regression is included as an additional explanatory variable (lambda) as well as its interaction with High Coverage in the second-stage OLS regression. The results are reported in Table 7. The first two columns are for good news, and the last two are for bad news. 30 31

See Chen, Cheng, Gong and Tan (2017) for evidence based on a high-profile corruption scandal in China. The discretionary accruals are calculated using the modified Jones model.

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[Insert Table 7 about here] The first-stage results in Column (1) and Column (3) indicate that larger and economically more important clients, clients that require industry specialist auditing services, and SOEs are more likely to select large auditors. Clients with lower financial reporting quality (proxied by discretionary accruals) and clients with higher leverage are less likely to select large auditors. The explanatory power of the auditor choice model is comparable to that of Wang, Wong, and Xia (2008) amongst others. Column (2) and Column (4) reports the second-stage results of re-estimating Equation (2) for good news and bad news firms, respectively. Of particular interest, the coefficient Top10 and the coefficient on High Coverage*Top10 are significantly positive, as in the baseline regression. The coefficient of inverse Mills (and on its interaction with High Coverage) is statistically insignificant, suggesting that self-selection is not a severe issue in our sample. In a further attempt to alleviate the concern that endogenous firm characteristics may drive both high news coverage and high audit fees, we re-classify firms into high and low coverage groups based on abnormal news coverage, which is obtained by regressing total

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number of news articles (or news days) each year against the determinants of news coverage in Fang and Peress (2009) and saving the residuals.32 Firms whose abnormal news coverage falls in

accepted manuscript the raw news coverage figures. Unsurprisingly, the untabulated results are qualitatively the same.

the top tercile are classified as High Coverage firms, and the remaining as Low Coverage firms. This grouping procedure results in essentially the same group affiliations as those obtained using

It is comforting that the results from the two-stage selection model and those from using abnormal media coverage are qualitatively similar to those in the baseline regressions, although, given the complex nature of endogeneity issues (Lennox, Francis, and Wang 2012), we cannot rule out the possibility that the results may still be affected by endogeneity. Controlling for Internal Corporate Governance In the baseline tests we did not include corporate governance variables, for three reasons. First, many past studies do not include these as control variables, so excluding these facilitates 32

The determinants include firm size, book-to-market ratio, analyst coverage, fraction of individual ownership, analyst dispersion, idiosyncratic volatility, past year absolute return, and past year return. The results are similar whether or not we include number of major corporate events and other firm-specific variables unique to China, e.g., ownership type, dual listing (H-share/B-share), and Special Treatment designation.

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comparison. Second, past studies that examine the relationship between corporate governance and audit fees indicate conflicting results (Hay, Knechel, and Wong 2006). Third, including all these variables along with the other control variables causes the sample size to drop significantly. Nevertheless, to see if the main results are sensitive to the inclusion of corporate governance variables, we re-run Equation (2) after including several corporate governance variables that some past studies suggest might be relevant.33 The results, which are not tabulated for brevity, remain qualitatively the same. The corporate governance variables are generally insignificant. Other Robustness Tests We conduct additional tests to check the robustness of our conclusions. First, following Simunic (1980) and Gul (2006) we deflate audit fees by total assets and use this in place of LAF. We also try adding the square root of auditee total assets and using audit fees instead of LAF to account for the possibility of a non-log-linear relation between auditee size and audit fees (Wang, Wong, and Xia 2008). Second, we follow Francis and Yu (2009) amongst others and compute discretionary accruals using the performance-adjusted Jones model of Kothari, Leone and Wasley (2005). We then add the absolute and raw value of discretionary accruals separately as an

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additional control. Third, Wang, Wong, and Xia (2008) find that Chinese SOEs are more likely to hire small local auditors, especially in regions with less developed institutions. To see if regional economic differences affect our results, we include the Marketization Index of Fan, Wang, and

accepted sensitive to the definition of Top10/non-Top10 auditors, we compute auditor size based on sales manuscript Zhu (2011) as an additional variable in the audit fee regressions. Finally, to see if our results are

instead of total assets (Chan, Ezzamel, and Gwilliam 1993). The results for all these additional tests remain qualitatively the same.

5. CONCLUSION Prior US-based studies (Mutchler, Hopwood, and McKeown 1997; Joe 2003) find that auditors’ propensity to issue modified opinions is unduly affected by news coverage of negative client events. It is unclear from these small number of studies whether and how audit pricing is 33

These include an indicator whether the firm issued H- or B shares, an indicator for CEO duality, percentage share ownership by the largest shareholder, combined percentage share ownership by the second to the tenth largest shareholders, percentage shares ownership by institutions, percentage of independent directors, natural log of the number of directors, and percentage share ownership by senior management.

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affected by the type of news coverage (e.g., positive versus negative) or the amount of news coverage of client firms, and whether the relation between media coverage and audit pricing is moderated by auditor size. We contribute to the literature by shedding light on this underexplored issue in China’s market setting. We find that Chinese auditees receiving high news coverage are on average charged higher audit fees, irrespective of the tone of the coverage. The positive association is stronger for large auditors relative to small auditors, consistent with large auditors having greater reputation protection concerns (DeAngelo 1981). For large auditors the positive association between news coverage and audit fees holds for both good news and bad news, and tends to be stronger for bad news. The latter evidence is consistent with loss aversion posited by prospect theory (Kahneman and Tversky 1979). The results are robust to controls for potential auditor selection bias and endogeneity in media coverage, information asymmetry, internal corporate governance, and alternative measurement of the key variables. Overall, the evidence indicates that auditors view high coverage clients as requiring greater audit effort due to the greater public and regulators’ attention embodied in high news coverage and consequently higher risks and costs of being caught in error.

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The body of evidence is consistent with the Chinese financial news media playing a disciplining role, through the potential to trigger reputational sanctions and regulatory action.

accepted backdrop of the move towards harmonization and internationalization of auditing standards, our manuscript

This finding is both novel and interesting, and has implications for policy-makers. Against the

evidence suggests that even in countries where the government controls the media and/or many of the listed companies, the media still has the potential to play a disciplining role, provided that public criticisms can affect key stakeholders (including the government).34 Our paper adds to a body of literature on how media coverage affects decision-making by sophisticated users (e.g., external auditors and analysts) and, to our knowledge, is among the first to examine the effects of news coverage on audit pricing. Further research is required to see if the positive association between news coverage and audit fees is due to the special characteristics of the news media and other institutional features in China, or if it also exists in other countries. Among the limitations, the lack of audit hour data does not allow us to test if auditors actually 34

This is a necessary though not sufficient condition.

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expend greater effort in auditing high coverage clients, though it can be expected that audit fees are positively associated with audit hours. The non-experimental nature of our research design does not allow us to directly address the issue of whether auditors, when pricing audit fees, overreact to information contained in news coverage. We leave these to future research. References Ahern, K., and D. Sosyura. 2014. Who writes the news? Corporate press releases during merger negotiations. Journal of Finance 69: 241–291. Ahern, K., and D. Sosyura. 2015. Rumor has it: Sensationalism in financial media. Review of Financial Studies 28: 2050-2093. Angrist, J.D., and S. Pischke. 2009. Mostly Harmless Econometrics – An Empiricist's Companion. Princeton University Press, Princeton. Atiase, R.K. 1985. Predisclosure information, firm capitalization, and security price behavior around earnings announcements. Journal of Accounting Research 23: 21-36. Bailey, W., W. Huang, and Z. Yang. 2011. Bank loans with Chinese characteristics: some evidence on inside debt in a state-controlled banking system. Journal of Financial and Quantitative Analysis 46: 1795–1830. Ball, R. 2009. Market and political/regulatory perspectives on the recent accounting scandals. Journal of Accounting Research 47: 277-390, Barber, B., and T. Odean. 2008. All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies 21: 785-817. Bednar, M.K. 2012. Watchdog or lapdog? A behavioral view of the media as a corporate governance mechanism. Academy of Management Journal 55: 131–150. Bushee, B.J, J.E. Core, W. Guay, and S.J.W. Hamm. 2010. The role of the business press as an information intermediary. Journal of Accounting Research 48: 1-19. Bushman, R., J. Piotroski, and A. Smith. 2004. What determines corporate transparency? Journal of Accounting Research 42 (Supplement): 207–52. Caijing. 2003. Hei Mu Yu Xian Jing (Inside Stories and Traps). Beijing: Social Sciences Documentation Publishing House (in Chinese). Cao, Y., L.A. Myers, and T.C. Omer. 2012. Does company reputation matter for financial reporting quality? Evidence from restatements. Contemporary Accounting Research 29: 956–990. Carcello, J.V., D.R. Hermanson, T.L. Neal, and R. Riley. 2002. Board characteristics and audit fees. Contemporary Accounting Research 19: 365-384. Chan, W. 2003. Stock price reaction to news and no-news: Drift and reversal after headlines. Journal of Financial Economics 70: 223-260. Chan, P., M. Ezzamel, and D. Gwilliam. 1993. Determinants of audit fees for quoted UK companies. Journal of Business Finance and Accounting 20: 765-786. Chan, K., K.Z. Lin, and P.L. Mo. 2006. A political-economic analysis of auditor reporting and auditor switches. Review of Accounting Studies 11: 21-48. Chan, K., and D. Wu. 2011. Aggregate quasi rents and auditor independence: Evidence from audit firm mergers in China. Contemporary Accounting Research 28:175-213. Chaney, P.K., D.C. Jeter, and L. Shivakumar. 2004. Self-selection of auditors and audit pricing in private firms. The Accounting Review 79: 51-72.

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Chen, J., X. Cheng, S.X.Gong, and Y. Tan. 2017. Implications of political patronage and political costs for corporate disclosure: Evidence from the Shanghai Pension corruption scandal. Journal of Accounting, Auditing and Finance 32: 92-122. Chen, C-W., C. Pantzalis, and J.C. Park. 2013. Press coverage and stock prices’ deviation from fundamental value. Journal of Financial Research 36: 175-214. Chen, Q., and K. Schipper. 2008. Future directions for Chinese accounting research. China Journal of Accounting Research 1: 1-10. Chen, S., S.Y.J. Sun, and D. Wu. 2010. Client importance, institutional improvements, and audit quality in China: An office and individual auditor level analysis. The Accounting Review 85: 127-158. Chen, S., Z. Sun, Z., S. Tang, and D. Wu. 2011. Government intervention and investment efficiency: Evidence from China. Journal of Corporate Finance 17: 259-271. Chen, Y., F. Gul, M. Veeraraghavan, and L. Zolotoy. 2015. Executive equity risk-taking incentives and audit pricing. The Accounting Review 90: 2205–2234. Chen, Z. 2003. Capital markets and legal development: The China case. China Economic Review 14: 451-472. Chen, Z. 2005. Mei Ti, Fa Lü Yu Shi Chang (Media, Law and Market). Beijing: China University of Politics and Law Press (in Chinese). Chinese Institute of Certified Public Accountants (CICPA). 2009. Auditing: A Supplemental Text for Preparing for the National Examination of Certified Public Accountants. Beijing: Economic Science Publishing House (in Chinese). Core, J.E., W. Guay, and D.F. Larcker. 2008. The power of the pen and executive compensation. Journal of Financial Economics 88: 1-25. Cutler, D.M., J.M. Poterba, and L.H. Summers. 1989. What moves stock prices? Journal of Portfolio Management 15: 4-12. DeAngelo, L. 1981. Auditor size and audit quality. Journal of Accounting and Economics 3: 183-199. DeFond, M.L., T.J. Wong, and S. Li. 2000. The impact of improved auditor independence on audit market concentration in China. Journal of Accounting and Economics 28: 269-305. DeFond, M.L., and J. Zhang. 2014. A review of archival auditing research.” Journal of Accounting and Economics 58: 275-326. Ding, Y., H. Zhang, and J. Zhang. 2007. Private vs state ownership and earnings management: Evidence from Chinese listed companies. Corporate Governance: An International Review 15: 223-238. Dougal, C., J. Engelberg, D. Garcia, and C.A. Parsons. 2012. Journalists and the stock market. Review of Financial Studies 25: 639-679. Dyck, A., A. Morse, and L. Zingales. 2010. Who blows the whistle on corporate frauds? Journal of Finance 65: 2213–2253. Dyck, A., N. Volchkova, and L. Zingales. 2008. The corporate governance role of the media: Evidence from Russia. Journal of Finance 63: 1093-1135. Dyck, A., and L. Zingales. 2002. The corporate governance role of the media. In The Right to Tell: The Role of the Media in Economic Development, edited by R. Islam, 107-137. Washington, D.C.: The World Bank. Dyck, A., and L. Zingales. 2003. The media and asset prices. Working paper, University of Chicago Booth School of Business.

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accepted manuscript

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Engelberg, J.E., A.V. Reed, and M.C. Ringgenberg. 2012. How are shorts informed? Short sellers, news, and information processing. Journal of Financial Economics 105: 260-278. Engelberg, J., C. Sasseville, and J. Williams. 2012. Market madness? The case of Mad Money. Management Science 58: 351–364. Esarey, A. 2006. Speak no Evil: Mass Media Control in Contemporary China. Freedom House Special Report. Available at: http://www.freedomhouse.org/uploads/special_report/33.pdf. Fair, R.C. 2002. Events that shook the market. Journal of Business 75: 713-732. Fan, G., X.L. Wang, and H. Zhu. 2011. NERI Index of Marketization in China by Province 2011 Report. Beijing: The Economic Science Press (in Chinese). Fan, J., T.J. Wong, and T. Zhang. 2007. Politically connected CEOs, corporate governance, and post-IPO performance of China's newly partially privatized firms. Journal of Financial Economics 84: 330–357. Fang, L., and J. Peress. 2009. Media coverage and the cross-section of stock returns. Journal of Finance 64: 2023-2052. Firth, M., S.X. Gong, and L. Shan. 2013. Cost of government and firm value. Journal of Corporate Finance 21:136-152. Firth, M., O.M. Rui, and W. Wu. 2011. The effects of political connections and state ownership on corporate litigation in China. Journal of Law and Economics 54: 573–607. Francis, J.R., K. Reichelt, and D. Wang. 2005. The pricing of national and city-specific reputations for industry expertise in the U.S. audit market. The Accounting Review 80:113-136. Francis, J.R., and M.D. Yu. 2009. Big 4 office size and audit quality. The Accounting Review 84:1521-1552. Fung, S.Y.K., F.A. Gul, and J. Krishnan. 2012. City-level auditor industry specialization, economies of scale, and audit pricing. The Accounting Review 87: 1281-1307. Ge, R., and C. Lennox. 2011. Do acquirers disclose good news or withhold bad news when they finance their acquisitions using equity? Review of Accounting Studies 16:183-217. Gong, S.X., and F.A. Gul. 2009. The quality and quantity of media coverage and its impact on stock price informativeness and trading activity: Evidence from China. Proceedings of European Financial Management Symposium on Corporate Governance and Control, Cambridge, UK, April 9-12. Gul, F.A., and J. Tsui. 1998. A test of the free cash flow and debt monitoring hypotheses: evidence from audit pricing.” Journal of Accounting and Economics 24: 219-237. Gul, F.A. 1999. Audit prices, product differentiation and economic equilibrium. Auditing: A Journal of Practice and Theory 18: 90-100. Gul, F.A. 2006. Auditors’ response to political connections and cronyism in Malaysia. Journal of Accounting Research 44: 931-963. Gul, F.A., H. Sami, and H. Zhou. 2009. Auditor disaffiliation program in China and auditor independence.” Auditing: A Journal of Practice and Theory 28: 29-51. Gul, F. A., S.Y.-K. Fung, and B. Jaggi. 2009 .Earnings quality: Some evidence on the role of auditor tenure and auditors’ industry expertise. Journal of Accounting and Economics 47: 265– 287. Gul, F.A., and J. Goodwin. 2010. Short-term debt maturity structures, credit ratings, and the pricing of audit services. The Accounting Review 85: 877-909. Gul, F.A., M. Khedmati, E. Lim, F. Navissi. 2018. Managerial ability, financial distress and audit fees. Accounting Horizons (forthcoming).

preprint

accepted manuscript

28

Gul, F.A., J-B. Kim, and A.A. Qiu. 2010. Ow wnership conncentration, foreign sharreholding, auudit quality, and a stock priice synchronnicity: Evideence from Chhina. Journaal of Financiial Economiics 95: 425-442. Gurun, U.G., U and A.W W. Butler. 2012. 2 Don’t believe b the hype: h local media m slant, local l advertiising, and firm value. Journ nal of Finannce 67: 561-5597. Hay, D.C C., W.R. Kneechel, and N. N Wong. 20006. Audit feees: A meta-aanalysis of thhe effects off supply annd demand attributes. a Coontemporaryy Accountingg Research 23: 2 141-191.. Jensen, M.C. M 1979. Toward T a theeory of the press. p In Economics and Social Instittutions, editeed by K. Brunnner, 267-287. Boston, MA: Martinuss Nijhoff. Joe, J.R. 2003. Why press coveraage of a cliennt influencess the audit oppinion. Jourrnal of Accountiing Research h 41: 109-133. Johnson, E.N., K.B. Walker, W andd E. Westergaard. 1995. Supplier conncentration and a pricing of o audit servvices in New w Zealand. Auditing: A A Journal J of Prractice and Theory T 14: 74-89. 7 Kahnemaan, D., and A. A Tversky. 1979. Prospeect theory: An A analysis of o decision under u risk. Economeetrica 37: 26 63-291. Kothari, S.P., A.J. Leeone, and C..E. Wasley. 2005. 2 Perforrmance matcched discretiionary accrual measuress. Journal off Accountingg and Econom mics 39: 1633-197. Kothari, S.P., X. Li, and J.E. Shoort. 2009. Thhe effect of disclosures d b managem by ment, analystss, and businness press on n cost of cappital, return volatility, v annd analyst forecasts: A sttudy using content analysis. a Thee Accountingg Review 84: 1639-1670.. Larcker, D.F., and S..A. Richardsson. 2004. Feees paid to audit a firms, accruals a choiices, and corporatee governancee. Journal off Accountingg Research 42: 4 625-658. Lennox, C.S., J.R. Frrancis, and Z. Z Wang. 2012. selectionn models in accounting a r research. Thee Accountiing Review 87: 8 589-616. Li, F. 2010. The info ormation conntent of forw ward-looking statements in i corporate filings—A naive Baaysian machiine learning approach. Joournal of Acccounting Reesearch 48: 1049-1102. 1 Liebmann, B.L., and C.J. C Milhauppt. 2008. Repputational saanctions in China’s C securrities markett. Columbiaa Law Revieew 108: 929--983. Liu, B., and a J.J. McC Connell. 2013. The role of o the mediaa in corporatee governance: Do the meedia influencee managers’ decisions too abandon accquisition atttempts? Jourrnal of Finanncial Econom mics 110: 1-177. Loughrann, T., and B. McDonald.. 2010. Whenn is a liabilitty not a liabiility? Textuaal analysis, dictionarries, and 10K Ks. Journal of o Finance 66: 6 35-65. Lyon, J.D D., and M.W W. Maher. 20005. The impoortance of buusiness risk in setting auudit fees: Evidencee from cases of client miisconduct. Joournal of Acccounting Reesearch 43:1333-151. Merton, R.C. R 1987. A simple moodel of capitaal market eqquilibrium wiith incompleete informatiion. Journal of o Finance 42: 4 483-510. Miller, G.S. G 2006. Th he press as a watchdog for f accountinng fraud. Jouurnal of Accounting Researchh 44: 1001-1033. Mutchlerr, J.F.,W. Ho opwood, andd J.M. McKeeown. 1997. The influence of contrarry and mitiggating factors onn audit opiniion decisionns on bankruppt companiees. Journal of o Accountinng Research 35: 295-310. Palmrosee, Z.V. 1988.. An analysiss of auditor litigation l andd audit serviice quality. The T Accountiing Review 63: 6 55-73.

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Pratt, J., and J.D. Stice. 1994. The effects of client characteristics on auditor litigation risk judgments, required audit evidence, and recommended audit fees. The Accounting Review: 639656. Seetharaman, A., F.A. Gul, F.A., and S.G. Lynn. 2002. Litigation risk and audit fees: Evidence from UK Firms cross-listed on US markets. Journal of Accounting and Economics 33: 91-115. Shiller, R.J. 2005. Irrational Exuberance. Princeton, N.J.: Princeton University Press. Shu, S.Z. 2000. Auditor resignations: Client effects and legal liability. Journal of Accounting and Economics 29: 173-205. Simunic, D.A. 1980. The pricing of audit services: Theory and evidence. Journal of Accounting Research 18: 161-190. Simunic, D.A., and X. Wu. 2009. China-related research in auditing: A review and directions for future research. China Journal of Accounting Research 2: 1-25. Solomon, D.H. 2011. Selective Publicity and Stock Prices. Journal of Finance 67: 599-637. Srinidhi, B.N., and F.A. Gul. 2007. The differential effects of auditors’ nonaudit and audit fees on accrual quality. Contemporary Accounting Research 24: 595-629, Stice, J. 1991. Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. The Accounting Review 66: 516-533. Teoh, S.H., and T.J. Wong. 1993. Perceived auditor quality and the earnings response coefficient. The Accounting Review 68: 346-366. Tetlock, P.C. 2007. Giving content to investor sentiment: the role of media in the stock market.” Journal of Finance 62: 1139-1168. Tetlock, P.C. 2010. Does public financial news resolve asymmetric information? Review of Financial Studies 23: 3520-3557. Tetlock, P. C. 2014. Information transmission in finance. Annual Review of Financial Economics 6: 365–384. Tetlock, P.C., M. Saar-Tsechansky, and S. Macskassy. 2008. More than words: Quantifying language to measure firms' fundamentals. Journal of Finance 63:1437-1467. Tsui, J.S.L.; B. Jaggi, and F.A. Gul. 2001. CEO domination, growth opportunities, and their impact on audit fees. Journal of Accounting, Auditing and Finance 16: 189-208. Venkataraman, R., J.P. Weber, and M. Willenborg. 2008. Litigation risk, audit quality, and audit fees: Evidence from initial public offerings. The Accounting Review 83: 1315-1345. Wang, Q., T.J. Wong, and L. Xia. 20058. State ownership, the institutional environment, and auditor choice: Evidence from China. Journal of Accounting and Economics 46: 112-134.

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Appendix A. Correspondence between the Return-Based Summary Measure of News Content and the Actual Content of Individual News Reports We report the results of a manual content analysis of news coverage, conducted with two objectives in mind: (1) to obtain an understanding of the typical contents of the news reports; and (2) to verify the extent of correspondence between the sign of CAR computed using our second approach (described in Section 3) and the contents of the individual news reports in given year. To make the task manageable, we focus on the firm-specific news reports (from 98 Chinese language newspapers) pertaining to the 20 firms with the highest (positive) CAR, and the 20 firms with the lowest (negative) CAR each year during the period 2008-2009. Thus there are a total of 80 firm-year observations. Two research assistants are trained to read the individual newspaper reports independently and classify the newspaper reports into one of three linguistic tones (positive, negative and neutral) and 13 information categories (the coding book, adopted from Gong and Gul 2009, is available on request). The newspaper reports are shuffled so that there is a mix of positive CAR and negative CAR firms for each assistant. While determination of the overall linguistic tone inevitably involves subjective judgment (which arguably is also

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more subtle and reliable than computer content analysis), it is not without (common sense) rules. For instance, negative tone is usually indicated by negatively colored words, or blocks of words that apparently indicate bad news. The assistants are told to be conservative and classify the

accepted the assistants seek the advice of the authors, who decide the coding after deliberation. manuscript

news reports as neutral unless they find fairly strong evidence to the contrary. In case of doubt,

The content analysis confirms that for many of the positive (negative) CAR firms, the associated news reports are predominantly positive (negative) in terms of both the linguistic tone and the implications of the news for firm value/performance/risk assessment.35 The Spearman rank correlation coefficient between the signed (raw) CAR and the proportion of positive news reports to the sum of positive and negative news reports is found to be 0.39. This is significant at the 5% level (one-tailed test), and confirms that there is a reasonable level of correspondence between the return-based summary measure of the good news-bad news nature of overall news coverage and the actual content of individual news reports. 35

We also notice that many news reports are the result of repackaging secondary information (from corporate announcements, analyst reports or market/trading data), consistent with the finding in Miller (2006). This casts some doubt as to whether auditors can learn a lot of new things about the clients from the news reports.

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Sample News Reports Positive News Coverage: Company: Longping Gaoke, Stock code: 000998 Headline: Quarterly profits up 200% for agriculture, forestry and fishery firm Body: According WIND statistics, 49 other listed companies in the agriculture, forestry and fishery sector recorded a gross turnover of 20.088 billion yuan, representing 50% increase yearon-year. Net profits (accruing to parent company) totaled 0.818 billion yuan, a 180% increase over last year. Among the 49 companies, 8 recorded a loss for the quarter. Among the remaining firms, 10 companies reported a primary EPS of above 0.1 yuan. Longping Gaoke leads the league with a primary EPS of 0.53 yuan. The company reported a quarterly net profit of 82.741 million yuan, representing a 552.17% increase year-on-year. (China Securities Journal, 2008-0526, author: Wang Jin) Negative News Coverage: Company: Tebian Diangong, Stock code: 600089 Headline: Mission impossible for Tebian Diangong

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Body: Despite reporting a net profit of 273 million yuan for shareholders of the listed firm and a turnover of 8.877 billion yuan in the first three quarters this year, Tebian Diangong is lagging far behind its target net profit of 500 million yuan stated in its 2007 Annual Report. “Judging from

accepted year’s annual report”, said Sun Qingzhou, anmanuscript analyst with Everbright Securities. Yet according to

the first three quarters, it is very difficult for the company to achieve the goal laid down in last

a recent announcement by the company, its Shenyang subsidiary has signed nuclear transformer contracts worth 245 million yuan with Zhongguang Nuclear Engineering Co Ltd. Sun indicated that, despite having a lot of contracts and orders, as a company Tebian Diangong cannot guarantee making a profit on every contract. “What they have signed are contracts worth 245 million yuan, not contracts delivering 245 millin yuan in profit. So while new contracts are welcome, they cannot guarantee realizing a profit of 230 millin in one single quarter.” As to the fact that the company has over-stated its performance, Hu Leilei, an analyst from Shenyin Wanguo, said that this may be due to three reasons. First, the company did plan to keep up its growth. Second, the plan however was outpaced by the rapid downward spiraling in the economic situation in 2008. Most companies were taken by surprise. Third, due to various considerations, such as a refinancing plan for 2008 and share option grants, the company has to 32

look for a shining spot in its performance. (Dongfang Zaobao [Oriental Morning Post], 2008-1206, author: Chen Jinyan) Neutral News Coverage: Company: Gaochun Ceramics, Stock code: 600562 Headline: Gaochun Ceramics receives SAMB approval for transfer of equity ownership Body: According to an announcement by Gaochun Ceramics today, the company was notified on 23 October by its controlling shareholder, Gaochun County State-owned Asset Operation (Holdings), that the State Asset Management Bureau (SAMB) has granted approval for its application for transferring its equity ownership. On 16 May 2009, Gaochun County State-owned Asset Operation (Holdings) had signed an Agreement on Transfer of Equity Ownership with Research Institute No. 14 of China Electronics Technology Group, under which the former would transfer its 22.9816 million state shares in Gaochun Ceramics to the latter. (Shanghai Securities Journal, 2009-10-26, author: Ying Youjia)

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Appendix B. Variable Definitions Main/Experimental variables #News = natural log of the number of news reports in 98 Chinese newspapers; High Coverage = client firms in the top tercile in terms of #News; Low Coverage = client firms in the bottom two terciles in terms of #News; Top10 =dummy variable coded 1 if the firm is audited by a Top10 auditor (based on total assets audited), and 0 otherwise; Non-Top10 = dummy variable coded 1 if the firm is audited by a non-Top10 auditor (based on total assets audited), and 0 otherwise; Audit fees = total audit fees ((in 1000s yuan) disclosed in annual report; LAF = natural log of total audit fees (in 1000s yuan) disclosed in annual report; Control variables Tenure = No. of years the auditor has provided auditing service to client; Auditee size = book value of a client’s total assets (in million yuan); Receivables/A= account receivables scaled by auditee’s total assets; Inventory/A = inventory scaled by auditee’s total assets; Quick ratio = current assets divided by current liabilities; ROA = net income divided by total assets; Leverage = total debt divided by total assets; Loss = dummy variable coded 1 if a loss is recoded, and 0 elsewhere. Ret = market-adjusted cumulative abnormal return during the year; SD(ret) = Standard deviation of daily stock returns; New audit = dummy variable coded 1 where the sample year is the first year with a new auditor, and 0 elsewhere; # corp. events = No. of major corporate events occurring within the year (e.g., right offerings, mergers and acquisitions, spinoffs, re-organization, new plants); # segments = No. of CSRC industry classifications in which the firm derives more than 5% of its revenues; MAO = dummy variable coded 1 for unqualified opinions with an explanatory paragraph, qualified opinions, disclaimers, and adverse opinions; otherwise 0; Central = dummy variable coded 1 where the controlling shareholder is the Central Government (ministries/departments), and 0 elsewhere; Local = dummy variable coded 1 where the controlling shareholder is a local government (i.e. local government departments or Bureau of State Assets Management), and 0 elsewhere; Age>=3 = dummy variable coded 1 where the firm has been listed for over 3 years, and 0 elsewhere; Tenure = No. of years the auditor has provided auditing service to client; Industry specialist = dummy variable coded 1 where the auditor has the largest market share in a particular industry, and 0 elsewhere; Ln(revenue) = The natural log of total revenue; Ln(employee #) = The natural log of the number of employee; UE =Earnings surprise, calculated as the earnings in the current year minus earnings in the previous year scaled by earnings in the year before; Ln(analyst #) =The natural log of the number of analysts following a firm;

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SOE = ultimate owners are a government, or a subsidiary or a division of a government; Non-SOE =ultimate owners are not affiliated with a government or subsidiaries of a government; PC = Firms with political connections, where political connections are defined as a chairman or CEO who satisfies any of the following three criteria: (1) a former government official; (2) a current or former member of the People's Congress; and (3) a current or former member of the People's Political Consultative Conference; Non-PC = Firms without political connections.

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Table 1 Descriptive Statistics Panel A. Whole sample Year Variable #news (obs.) 20042013

Mean

(9845) Std. Dev. Min Max

Audit fees Tenure

Auditee size

Receivabl Inventory Quick ROA Leverage Ret e /A ratio /A 21.76 0.1 0.18 1.97 0.04 0.48

22.24

794.63

5.6

30.12

1445.94

4.14

1.17

0.1

0.16

2.28

0.06

0

10

1

19.14

0

0

0.22

662

40500

22

26.02

0.58

0.79

25.8

New Audit

0.13

2.51

2.71

0.2

0.40

0.33

1.07

1.82

-0.33

0.04

-0.63

0

1

1

0.23

0.96

2.31

1

7

13

High Coverage (N=2253)

Variable

Mean

Std. Dev.

Mean

Std. Dev.

# news Ln(Auditee size) Audit fees (in 1000s) Tenure MAO Central Local Receivable/A Inventory/A Quick ratio ROA Leverage

11 21.47 596.09 5.69 0.03 0.17 0.30 0.11 0.17 2.71 0.03 0.47

6.5 0.99 408.67 4.21 0.18 0.37 0.46 0.10 0.16 4.43 0.06 0.20

44.5 22.35 1188.41 5.40 0.04 0.20 0.30 0.09 0.18 1.87 0.05 0.51

43 1.28 2382 3.99 0.19 0.40 0.46 0.10 0.17 3.00 0.08 0.20

-61.30 -37.65 -19.55 3.37 -1.28 -3.66 -0.03 5.46 -1.54 3.51 -10.68 -9.18

0.10 0.05 0.12 1.73 2.65

0.30 0.35 0.33 0.85 1.79

0.08 0.17 0.13 2.08 2.82

0.27 0.52 0.34 1.00 1.87

3.52 -13.96 -1.28 -18.18 -4.24

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# segments

0.09

Panel B. High Coverage versus Low Coverage groups Grouping by quantity of news coverage Low Coverage (N=4765)

Loss Ret New audit # corp events # segments

# corp events

T-test of diff. in mean

Panel C. Large (Top10) Auditor versus Small (non-Top10) Auditor groups Grouping by auditor size

Non-top10 auditors (N=4920)

Variable

Mean

Std. Dev.

Mean

Std. Dev.

# news Auditee size (in MM) Audit fees (in 1000s) Tenure

20 21.56 566 6.14

21 1.01 387 4.24

26 22.05 1107 4.85

39 1.30 2141 3.87

-10.08 -21.15 -18.67 15.53

MAO Central Local

0.04 0.14 0.32

0.20 0.35 0.47

0.03 0.22 0.28

0.16 0.42 0.45

3.85 -10.49 3.50

Receivable/A

0.10

0.10

0.10

0.10

1.51

Inventory/A

0.18

0.16

0.18

0.16

1.02

Quick ratio ROA Leverage

1.98 0.03 0.49

3.61 0.08 0.20

Loss Ret New audit

0.11 0.08 0.12

0.31 0.41 0.32

# corp events # segments

1.83 2.72

0.92 1.78

Top10 auditors (N=2098)

0.04 0.06 preprint 0.48 0.21 2.19

4.37

T-test of difference in mean

-2.57 -5.90 2.24

accepted 1.87 0.92 -2.11 manuscript 2.69 1.87 0.83 0.08 0.10 0.14

See Appendix B for variable definition.

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0.27 0.43 0.35

4.08 -1.81 -4.07

Table 2 Correlation Matrix High Audit Auditor tenure Total Central Local Receivable Inventory/ Quick Coverage fees size assets /A A ratio Audit fees 0.29 0.00 Auditor size 0.11 0.44 0.00 0.00 tenure -0.03 0.12 0.00 0.00 0.00 0.91 Auditee size 0.35 0.72 0.31 0.09 0.00 0.00 0.00 0.00 Central 0.04 0.08 0.09 -0.13 0.13 0.00 0.00 0.00 0.00 0.00 Local 0.00 0.04 0.03 0.17 0.17 -0.31 0.97 0.00 0.00 0.00 0.01 0.00 Receivable/A -0.06 -0.12 -0.05 -0.11 -0.25 0.06 -0.15 0.84 0.00 0.00 0.00 0.00 0.00 0.00 Inventory/A 0.00 0.05 -0.02 0.34 0.12 -0.03 -0.01 -0.11 0.47 0.00 0.05 0.17 0.00 0.00 0.48 0.00 Quick ratio -0.04 -0.15 -0.05 -0.12 -0.21 -0.05 -0.15 0.02 -0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 ROA 0.13 0.09 0.04 -0.00 0.12 -0.03 -0.04 -0.11 -0.06 0.22 0.00 0.00 0.00 0.82 0.00 0.01 0.00 0.00 0.00 0.00 Leverage 0.09 0.23 0.04 0.04 0.37 0.05 0.14 0.02 0.31 -0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.12 0.00 0.00 Loss -0.04 -0.07 -0.03 -0.02 -0.13 0.02 0.01 0.06 -0.04 -0.10 0.00 0.00 0.01 0.02 0.00 0.05 0.56 0.00 0.00 0.00 Ret 0.14 -0.02 -0.02 -0.02 -0.04 -0.02 -0.06 -0.00 0.01 0.05 0.00 0.05 0.03 0.00 0.00 0.01 0.00 0.93 0.43 0.00 New audit 0.01 -0.06 -0.02 -0.42 -0.03 0.07 -0.03 0.02 0.01 0.01 0.20 0.00 0.05 0.00 0.01 0.00 0.01 0.06 0.26 0.23 # corp events 0.18 0.18 0.03 -0.01 0.04 -0.08 -0.06 0.03 0.04 -0.10 0.00 0.00 0.00 0.62 0.20 0.00 0.00 0.01 0.00 0.00 # segments 0.04 0.17 0.06 0.14 0.16 0.00 0.08 -0.06 0.07 -0.13 0.00 0.00 0.00 0.00 0.00 0.95 0.00 0.00 0.00 0.00

ROA leverage loss

Ret

New audit

# corp events

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accepted -0.39 0.00 -0.63 manuscript 0.00

P-values (two-tailed) are reported below each entry in the table. See Appendix B for variable definition.

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0.22 0.00 -0.03 0.00 -0.01 0.48 -0.04 0.00

0.17 0.00 -0.06 0.00 0.01 0.21 0.15 0.00 0.14 0.00

-0.13 0.00 0.03 0.00 0.00 0.85 -0.08 0.03 0.00 0.00 -0.01 -0.03 0.38 0.01

0.00 0.92 -0.03 0.01

0.08 0.00

Table 3 Main Effects of News Coverage and Auditor Size on Audit Fees Dependent variable: LAF (1) (2) All Good news High Coverage 0.050*** 0.032** (5.29) (2.45) Top10 0.190*** 0.181*** (22.04) (14.86) Central -0.072*** -0.083*** (-6.16) (-4.95) Local -0.104*** -0.113*** (-10.97) (-8.18) Ln(Auditee size) 0.265*** 0.247*** (29.47) (18.83) Receivables/A 0.213*** 0.148** (4.33) (2.05) Inventory/A -0.144*** -0.181*** (-4.31) (-3.81) Quick ratio -0.008*** -0.009*** (-3.56) (-2.67) ROA -0.094 -0.136 (-0.75) (-0.78) Leverage -0.156*** -0.149*** (-4.84) (-3.28) Loss 0.085*** 0.068** (4.67) (2.45) Ret -0.026** -0.017 (-2.22) (-1.01) SD(ret) 0.327*** 0.289* (2.78) (1.83) Age>=3 -0.060** -0.060* (-2.39) (-1.68) Tenure 0.073*** 0.064*** (10.39) (6.55) MAO 0.108*** 0.127*** (4.74) (3.45) New audit 0.029* 0.017 (1.76) (0.71) # segments 0.041*** 0.024* (4.75) (1.94) # corp events 0.066*** 0.069*** (10.01) (7.61) Industry specialist 0.078*** 0.075*** (4.29) (2.86) Ln(revenue) 0.075*** 0.085*** (10.28) (8.06) Ln(employee #) 0.027*** 0.024*** (5.81) (3.72) UE 0.158** 0.051 (2.17) (0.46) Ln(analyst #) -0.015*** -0.007 (-3.05) (-1.01) N 9,845 4,916 Adjusted R2 0.60 0.57

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(3) Bad news 0.068*** (4.95) 0.200*** (16.08) -0.068*** (-4.17) -0.099*** (-7.48) 0.282*** (22.43) 0.270*** (4.00) -0.101** (-2.13) -0.007** (-2.33) -0.079 (-0.43) -0.162*** (-3.54) 0.103*** (4.19) 0.063 (1.36) 0.454** (2.43) -0.057 (-1.62) 0.083*** (8.16) 0.091*** (3.16) 0.044* (1.90) 0.058*** (4.72) 0.063*** (6.48) 0.081*** (3.16) 0.066*** (6.43) 0.031*** (4.61) 0.273*** (2.82) -0.022*** (-3.05) 4,929 0.63

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***,**,* Significance at the 1%, 5%, 10% level (two-tailed test). T-statistics calculated using standard errors clustered by firm and year are reported in parenthesis. Year and industry fixed effects are included in all regressions but not reported. See Appendix B for variable definition.

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Table 4 Interactive Effects of News Coverage and Auditor Size on Audit Fees Dependent variable: LAF (1) (2) All Good news High Coverage -0.006 -0.020 (-0.52) (-1.25) Top10 0.146*** 0.134*** (14.61) (9.51) High Coverage*Top10 0.131*** 0.122*** (7.45) (5.12) Central -0.071*** -0.082*** (-6.13) (-4.92) Local -0.103*** -0.111*** (-10.87) (-8.07) Ln(Auditee size) 0.260*** 0.243*** (28.99) (18.61) Receivables/A 0.210*** 0.147** (4.30) (2.05) Inventory/A -0.143*** -0.182*** (-4.29) (-3.84) Quick ratio -0.008*** -0.008** (-3.41) (-2.56) ROA -0.089 -0.132 (-0.71) (-0.76) Leverage -0.148*** -0.143*** (-4.62) (-3.15) Loss 0.084*** 0.067** (4.63) (2.43) Ret -0.025** -0.016 (-2.16) (-0.92) SD(ret) 0.319*** 0.277* (2.72) (1.77) Age>=3 -0.059** -0.062* (-2.40) (-1.72) Tenure 0.074*** 0.066*** (10.56) (6.73) MAO 0.109*** 0.128*** (4.79) (3.47) New audit 0.031* 0.020 (1.89) (0.85) # segments 0.042*** 0.026** (4.92) (2.13) # corp events 0.066*** 0.069*** (10.10) (7.68) Industry specialist 0.080*** 0.079*** (4.44) (3.04) Ln(revenue) 0.075*** 0.084*** (10.34) (8.00) Ln(employee #) 0.027*** 0.025*** (5.86) (3.79) UE 0.150** 0.042 (2.08) (0.38) Ln(analyst #) -0.014*** -0.006 (-2.85) (-0.91) N 9,845 4,916 Adjusted R2 0.61 0.57

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(3) Bad news 0.007 (0.40) 0.157*** (11.05) 0.143*** (5.47) -0.068*** (-4.20) -0.099*** (-7.46) 0.275*** (21.93) 0.267*** (3.98) -0.098** (-2.06) -0.007** (-2.21) -0.068 (-0.37) -0.151*** (-3.31) 0.102*** (4.16) 0.062 (1.34) 0.451** (2.42) -0.054 (-1.56) 0.082*** (8.18) 0.093*** (3.23) 0.044* (1.89) 0.058*** (4.78) 0.063*** (6.56) 0.080*** (3.15) 0.067*** (6.56) 0.031*** (4.63) 0.265*** (2.75) -0.021*** (-2.90) 4,929 0.64

***,**,* Significance at the 1%, 5%, 10% level (two-tailed test). T-statistics calculated using standard errors clustered by firm and year are reported in parenthesis. Year and industry fixed effects are included in all regressions but not reported. See Appendix B for variable definition.

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Table 5 Effect of Information Asymmetry on the Relations between News Coverage, Auditor Size, and Audit Fees (1)

High Coverage Top10 High Coverage*Top10 Central Local Ln(Auditee size) Receivables/A Inventory/A Quick ratio ROA Leverage Loss Ret SD(ret) Age>=3 Tenure MAO New audit # segments # corp events Industry specialist Ln(revenue) Ln(employee #) UE Ln(analyst #)

All 0.024 (1.63) 0.109*** (9.26) -0.007 (-0.28) -0.099*** (-7.08) -0.087*** (-6.81) 0.216*** (16.07) -0.012 (-0.22) -0.178*** (-3.99) -0.006** (-2.47) 0.282** (2.00) 0.031 (0.83) 0.057*** (2.78) -0.022 (-1.51) 0.312** (2.26) -0.024 (-0.96) 0.063*** (6.93) 0.057** (2.27) 0.024 (1.26) 0.034*** (3.14) 0.055*** (7.05) 0.048** (2.22) 0.047*** (5.29) 0.009 (1.62) -0.041 (-0.47) -0.020*** (-3.16)

(2) Small auditees Good news 0.026 (1.29) 0.094*** (5.71) 0.022 (0.66) -0.103*** (-5.22) -0.095*** (-5.07) 0.212*** (10.63) -0.050 (-0.59) -0.195*** (-3.05) -0.007** (-2.07) 0.258 (1.32) 0.031 (0.60) 0.060* (1.93) -0.025 (-1.17) 0.376** (2.03) -0.019 (-0.56) 0.049*** (3.88) 0.063* (1.72) -0.003 (-0.11) 0.023 (1.50) 0.049*** (4.60) 0.057* (1.77) 0.057*** (4.42) 0.005 (0.63) -0.069 (-0.54) -0.017* (-1.95)

(3)

(4)

Bad news 0.025 (1.12) 0.125*** (7.25) -0.054 (-1.48) -0.098*** (-4.86) -0.083*** (-4.66) 0.224*** (12.11) 0.027 (0.35) -0.144** (-2.29) -0.005 (-1.51) 0.316 (1.53) 0.039 (0.74) 0.056** (1.97) -0.006 (-0.10) 0.216 (0.97) -0.027 (-0.74) 0.079*** (5.94) 0.053 (1.55) 0.054** (1.98) 0.042*** (2.80) 0.059*** (5.19) 0.041 (1.38) 0.034*** (2.73) 0.014* (1.71) -0.012 (-0.10) -0.024*** (-2.58)

All -0.012 (-0.76) 0.202*** (12.11) 0.097*** (4.02) -0.075*** (-4.19) -0.099*** (-7.36) 0.334*** (22.21) 0.529*** (6.13) 0.002 (0.05) -0.029*** (-5.69) -0.159 (-0.73) -0.340*** (-6.09) 0.096*** (3.05) -0.019 (-1.04) 0.392** (2.07) -0.104 (-1.60) 0.095*** (9.27) 0.142*** (3.22) 0.056** (2.11) 0.057*** (4.46) 0.081*** (7.92) 0.038 (1.55) 0.096*** (8.52) 0.040*** (5.86) 0.167 (1.45) -0.010 (-1.36)

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(5) Large auditees Good news -0.046** (-2.01) 0.195*** (7.77) 0.090*** (2.63) -0.087*** (-3.27) -0.107*** (-5.44) 0.306*** (13.68) 0.498*** (3.87) -0.030 (-0.43) -0.028*** (-3.52) -0.248 (-0.81) -0.359*** (-4.30) 0.028 (0.51) -0.006 (-0.24) 0.273 (1.07) -0.162 (-1.12) 0.087*** (5.89) 0.133 (1.47) 0.048 (1.20) 0.035* (1.95) 0.093*** (6.32) 0.049 (1.38) 0.106*** (6.31) 0.041*** (4.20) 0.051 (0.30) 0.006 (0.53)

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(6) Bad news 0.015 (0.64) 0.208*** (9.20) 0.108*** (3.12) -0.073*** (-2.98) -0.094*** (-5.00) 0.350*** (16.84) 0.529*** (4.47) 0.028 (0.41) -0.029*** (-4.43) -0.174 (-0.55) -0.337*** (-4.38) 0.139*** (3.51) 0.129* (1.77) 0.693** (2.27) -0.075 (-1.03) 0.100*** (7.03) 0.137*** (2.85) 0.066* (1.82) 0.076*** (4.23) 0.070*** (4.84) 0.022 (0.66) 0.094*** (6.01) 0.037*** (3.89) 0.338** (2.13) -0.020* (-1.92)

N 4,926 2,564 2,362 4,919 2,352 2,567 Adjusted R2 0.33 0.30 0.35 0.59 0.55 0.62 ***,**,* Significance at the 1%, 5%, 10% level (two-tailed test). T-statistics calculated using standard errors clustered by firm and year are reported in parenthesis. Year and industry fixed effects are included in all regressions but not reported. See Appendix B for variable definition.

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Table 6 Regression Results by Ownership Types and Political Connections Panel A. State-owned enterprises (SOEs) vs Non-SOEs (1) (2) (3) SOE All Good news Bad news High Coverage -0.019 -0.043* 0.006 (-1.07) (-1.71) (0.23) Top10 0.132*** 0.116*** 0.148*** (8.70) (5.25) (7.02) High Coverage*Top10 0.179*** 0.192*** 0.156*** (6.75) (5.05) (4.13) Other controls N Adjusted R2

Yes 4,725 0.66

Yes 2,221 0.61

Yes 2,504 0.68

(4) All 0.001 (0.06) 0.155*** (12.07) 0.074*** (3.30)

(5) Non-SOE Good news -0.009 (-0.47) 0.142*** (7.89) 0.070** (2.32)

Bad news 0.010 (0.46) 0.166*** (8.95) 0.089*** (2.59)

Yes 5,120 0.54

Yes 2,695 0.53

Yes 2,425 0.55

Panel B. Politically connected (PC) vs non-politically connected (Non-PC) firms (1) (2) (3) (4) (5) PC Non-PC All Good news Bad news All Good news High Coverage -0.037* -0.052* -0.021 0.006 -0.008 (-1.78) (-1.86) (-0.63) (0.42) (-0.44) Top10 0.158*** 0.141*** 0.166*** 0.145*** 0.136*** (7.96) (4.96) (5.77) (12.57) (8.38) High Coverage*Top10 0.123*** 0.074* 0.176*** 0.132*** 0.138*** (3.79) (1.70) (3.53) (6.30) (4.80)

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(6) Bad news 0.020 (1.02) 0.153*** (9.33) 0.128*** (4.18)

Other controls Yes Yes Yes Yes Yes Yes N 2,871 1,481 1,390 6,909 3,406 3,503 Adjusted R2 0.61 0.57 0.64 0.60 0.57 0.63 ***,**,* Significance at the 1%, 5%, 10% level (two-tailed test). T-statistics calculated using standard errors clustered by firm and year are reported in parenthesis. Year and industry fixed effects are included in all regressions but not reported. Other controls are the same as those in Table 4 (in Panel A models 1-3 the local government SOE dummy is the omitted reference and only a Central Government SOE dummy is included; in Panel A models 4-6 both dummies are excluded). See Appendix B for variable definition.

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Table 7 Heckman two-step regressions (1) Good news 1st stage: Dep=Top10 High Coverage Top10 High Coverage*Top10 Central Local Ln(Auditee size) Receivables/A Inventory/A Quick ratio ROA Leverage Loss Ret SD(ret) Age>=3 Tenure MAO New audit # segments # corp events Industry specialist Ln(revenue) Ln(employee #) UE Ln(analyst #) DA

0.126** (2.16) 0.082* (1.67) 0.104** (2.30) 0.184 (0.69) 0.034 (0.19) -0.006 (-0.50) 0.953 (1.56) -0.326* (-1.93) 0.040 (0.40) 0.004 (0.06) 0.636 (1.13) 0.136 (0.93) -0.506*** (-14.21) 0.094 (0.71) -0.691*** (-8.49) -0.012 (-0.28) -0.011 (-0.34) 1.460*** (15.44) 0.062* (1.65) 0.042* (1.72) -0.214 (-0.63) -0.010 (-0.39) -0.463**

(2) Good news 2nd-stage: Dep= LAF 0.040 (0.99) 0.141*** (9.80) 0.105*** (4.04) -0.087*** (-4.51) -0.114*** (-7.68) 0.241*** (16.89) 0.145** (2.01) -0.178*** (-3.75) -0.008** (-2.49) -0.159 (-0.87) -0.136*** (-2.67) 0.066** (2.38) -0.016 (-0.92) 0.266* (1.65) -0.065* (-1.76) 0.081** (2.31) 0.122*** (3.24) 0.040 (0.79) 0.027** (2.19) 0.069*** (7.71) 0.047 (0.59) 0.083*** (7.07) 0.022*** (3.08) 0.052 (0.47) -0.007 (-0.98)

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(3) Bad news 1st stage: Dep=Top10

0.289*** (5.12) 0.013 (0.26) 0.188*** (4.22) 0.369 (1.46) -0.230 (-1.28) -0.018 (-1.50) -0.485 (-0.76) -0.524*** (-3.28) -0.045 (-0.53) -0.135 (-0.81) 0.213 (0.31) -0.066 (-0.52) -0.356*** (-9.95) 0.092 (0.87) -0.283*** (-3.49) -0.133*** (-3.04) -0.023 (-0.69) 1.556*** (15.34) 0.040 (1.10) -0.008 (-0.34) 0.108 (0.28) 0.036 (1.43) -0.435*

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(4) Bad news 2nd-stage: Dep= LAF 0.062 (1.51) 0.145*** (10.15) 0.098*** (3.80) -0.060** (-2.25) -0.110*** (-7.95) 0.256*** (14.59) 0.175** (2.32) -0.199*** (-3.91) -0.010*** (-2.84) -0.169 (-0.95) -0.189*** (-3.21) 0.065** (2.33) -0.026 (-1.33) 0.300* (1.91) -0.065* (-1.82) 0.036 (1.33) 0.133*** (3.53) -0.001 (-0.04) 0.015 (0.97) 0.067*** (7.37) 0.176** (1.96) 0.090*** (7.98) 0.023*** (3.42) 0.046 (0.42) -0.004 (-0.49)

(-2.32)

(-1.92) -0.025 0.153 (-0.25) (1.48) Lambda*High Coverage -0.054 -0.069** (-1.60) (-2.12) N 4,916 4,916 4,929 4,929 Pseudo/Adjusted R2 0.15 0.57 0.17 0.57 ***,**,* Significance at the 1%, 5%, 10% level (two-tailed test). T-statistics calculated using standard errors clustered by firm and year are reported in parenthesis. Year and industry fixed effects are included in all regressions but not reported. DA is signed discretionary accruals calculated using the modified Jones model. Lambda is inverse Mills ratio from the first-stage Probit regression. See Appendix B for definition of the other variables. Lambda

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