The Importance of Partner Narcissism to Audit Quality

Abstract
Relying on the size of partner signatures in audit reports to measure their narcissism, we findthat actual and perceived audit quality rises with partner narcissism. Reinforcing causal
inference, we show that changes in audit quality are positively associated with changes inpartner narcissism stemming from mandatory auditor rotation, and that audit quality does
not reversely affect partner signature size. We also find that the impact of auditor narcissismon audit quality is more pronounced when the client is larger and when the auditor sharesschool ties with client executives, although it does not vary with engagement complexity.
Collectively, this evidence implies that partner narcissism improves audit quality mainly
through increased auditor independence, rather than auditor competence. In additional
results consistent with expectations, we generally find that the role that partner narcissism
plays in audit quality is smaller in Big Four audit firms known to have robust quality control
structures and more standardized audit methodologies, which narrows the scope for partnerlevel characteristics to matter. We also document that although partner narcissism has noperceptible impact on the incidence of Type I going concern reporting errors, it reduces theprobability of making a Type II error, corroborating that more narcissistic partners are lesslikely to sacrifice their independence.

Key words: audit partner; narcissism; audit quality; auditor personality.
JEL Classifications: M40, M42
Data Availability: Data are available from public sources as identified in the text.

1

Introduction
We analyze the importance of partner narcissism to audit quality. Recent research at

the individual auditor level documents associations between audit quality and certain
acquired personal characteristics such as education and experience (e.g., Gul, Wu, and Yang,2013; Aobdia, Lin, and Petacchi, 2015; Cameran, Campa, and Francis, 2018). However, DeFond
and Zhang (2014) and Lennox and Wu (2018) call for more evidence on the impact ofindividual partner characteristics on audit quality. In particular, prior work seldom examines
whether auditors’ personality traits shape audit outcomes (Church, Davis, and McCracken,
2008; DeFond and Zhang, 2014), although research in management, finance, and accounting
has shown that corporate executives’ personalities influence their behavior (e.g., Haywardand Hambrick, 1997; Malmendier and Tate, 2008; Jia, van Lent, and Zeng, 2014). We focus on
narcissism given that this specific personality trait affects individual decision making andorganization outcomes (e.g., Chatterjee and Hambrick, 2007; Ham, Lang, Seybert, and Wang,2017). Although it is difficult to directly measure personality traits, recent research reliably
measures narcissism with the size of personal signatures in official filings (e.g., Davidson, Dey,and Smith, 2015; Ham et al., 2017; Zhou, 2017; Bushman, Davidson, Dey, and Smith, 2018;
Ham, Seybert, and Wang, 2018).
In examining economic outcomes stemming from narcissism in CEOs and CFOs,
recent research implies that narcissism significantly affects the choices made by these
executives (e.g., Aktas, de Bodt, Bollaert, and Roll, 2016; Ham et al., 2017, 2018). As a common
personality trait, narcissism is naturally neither localized to any specific country nor peculiar
to CEOs or CFOs (e.g., Kwan, Hui, and McGee, 2010; Young, Du, Dworkis, and Olson, 2016). 1

Narcissism is a personality trait that may exhibit rich within-region or within-culture variation.
Although some argue that perceived narcissism tends to be stronger within individualistic cultures
such as the U.S. (e.g., Miller et al. 2015), others find that Chinese, as a culture, region, and ethnic group
identified with our sample of auditors in Taiwan, have high levels of narcissism. Indeed, prior research
implies that some Chinese are more narcissistic than their American counterparts (Kwan, Kuang, andHui, 2009; Cai, Kwan, and Sedikides, 2012).
1

1

Auditors, like any other individuals, have varying personalities, including different degrees
of narcissism that may well become imprinted in their audit work. DeAngelo (1981)
formulates audit quality as the market-assessed joint probability that an auditor will discoveraccounting errors (i.e., auditor competence) and resist client pressure to waive their correction(i.e., auditor independence). It follows that partner narcissism may shape audit quality with
its impact potentially coming through the auditor competence and auditor independence
channels.
From a cognitive perspective, narcissism entails a belief in, and an exhibition of, one’s
superior intelligence and competence (Farwell and Wohlwend-Lloyd, 1998). Narcissists are
self-centered and devalue others (Nevicka, Ten Velden, De Hoogh, and Van Vianen, 2011).
This suggests that narcissistic partners are more likely to discount the value of importantclients because they tend to view themselves as the focal point in all settings. For more
narcissistic auditors, attracting respect and praise from their peers as a tough and independentgatekeeper may dominate striving to keep clients happy. Further, Maccoby (2003) argues thatnarcissists resist succumbing to a herd mentality and social pressure to conform. If retaining
important clients by compromising independence to some degree is fairly routine inmanaging engagements (e.g., Krishnan, 1994; Hopwood, McKeown, and Mutchler, 1989), thenmore narcissistic auditors are less likely to exhibit this behavior. Indeed, narcissists typicallychart their own course such that they are more apt to take risks in pursuing their vision
without serious fear of failure (Maccoby, 2003). This implies that although narcissistic auditors
risk losing important clients by not acquiescing to any pressure to waive corrections, such arisk or “failure” matters less to them. Finally, from a motivation perspective, the need forconstant recognition suggests that more narcissistic auditors are eager to develop a reputation
as the best in the profession (Raskin and Howard, 1988), which they presumably understandrequires them to be independent. Taken together, more narcissistic partners are more likely
to protect their independence from clients, which, in turn, translates into higher audit quality.
2However, the impact of narcissism on auditor competence is less clear. On one hand,
there may be a positive effect on competence through independent audit judgements andmotivation. Narcissistic individuals tend to arrive at their judgements independently as they
typically focus on their own thoughts and impressions at the expense of those of others (Byrne
and Worthy, 2013). Accordingly, once narcissistic auditors form their own opinions on theappropriateness of accounting policies and estimates as well as other audit evidence, theytend to resolutely stick to that opinion and are less likely to be persuaded to accept clients’potentially opportunistic financial reporting preferences. By making independent judgments(a quality labelled “field independence” in psychology) thus remaining vigilant against client
deception, narcissistic auditors are in a better position to identify accounting errors, implying
higher auditor competence. From a motivational standpoint, narcissism is associated with anunrelenting need to have one’s superior self-perception affirmed by others and to display
one’s superiority. Acquiring a reputation for conducting higher-quality audits provides
affirmation of a narcissist’s superiority. Given that a narcissistic partner is eager to deliver
high-quality audits, they expend more effort in order to detect financial reporting problems,
which, in turn, increases auditor competence.
On the other hand, narcissism is a double-edged sword that may actually undermine
audit quality. Prior research suggests that narcissists are self-centered, devalue others, react
aggressively to criticism, dominate the decision process, and inhibit information exchange
among group members (Nevicka et al., 2011). Consequently, even if other members of theaudit engagement team have insights that could help to identify any accounting problems,
those views may be taken lightly or dismissed outright by the narcissistic partner. As a result,more narcissistic auditors are less informed to the detriment of their competence. Additionally,a narcissistic partner’s inflated self-image can be associated with excessive optimism about
their ability to uncover financial reporting problems, leading to the undersupply of necessary
audit effort. Altogether, while we expect narcissism to improve partner independence, its
3

impact on auditor competence could run in either direction. In short, the link between auditor
narcissism and their performance remains an empirical issue.
We examine data from Taiwan in conducting our analysis. We follow extensive priorresearch by measuring narcissism with an individual’s signature size. Data constraints
prevent us from examining U.S. firms since there is no signature requirement there, although
the identity of the signing audit partner recently became publicly available. 2 The names ofthe signing audit partners of publicly listed firms in Taiwan have been mandatorily disclosed
since 1983. Importantly, the annual reports of listed companies in Taiwan display thesignatures of the partners who sign the audit reports. 3 After Ham et al. (2017, 2018), we
measure auditor narcissism with partner signature size. We focus on narcissism of the lead
auditor partner as the review partner is much less involved in the auditing process according
to extensive prior work (e.g., Chen, Lin, and Lin, 2008; Chin and Chi, 2009; Aobdia et al., 2015).
Using multiple measures, including absolute abnormal accruals, accrual quality,
restatements, and perceived audit quality evident in firms’ earnings response coefficients(ERCs) and borrowing costs, we find robust evidence implying that clients with partners
exhibiting narcissistic tendencies enjoy higher audit quality. To confront the endogeneity
threat to reliable inference that more narcissistic auditors are drawn to high-quality clients,

Another option would involve relying on U.K. data in analyzing our research questions since theengagement partner must sign the audit report in this country. However, at a practical level, this would
be exceedingly difficult given that although the engagement partner must sign the audit report in the
U.K., copies of the audit reports that are filed with the U.K. Companies House—where the generalpublic can observe filings similar to the SEC’s EDGAR system—do not have to be signed; i.e., audit
reports that are included in the annual report frequently simply identify the engagement partner byname (e.g., Carcello and Li, 2013).
3 DeFond and Francis (2005) suggest focusing on non-U.S. settings where audit partners’ names aredisclosed to study audit behavior at the individual auditor level. There have been a growing numberof studies using individual auditor data in various countries to address interesting research questions.
For example, Gul et al. (2013), Goodwin and Wu (2014), and Kallunki, Mikkonen, Niemi, and Nilsson(2017) rely on data from China, Australia, and Sweden, respectively. More relevant to our analysis,
extensive prior research on audit partners examines data from Taiwan (e.g., Chen et al., 2008; Chin andChi, 2009; Aobdia et al., 2015; and Chi et al., 2017). Although any single-country study involves someexternal validity threats, Chi et al. (2017), among others, stress the similarities between the audit andcapital markets in Taiwan and the U.S., implying that we focus on an opportune testing ground forproviding evidence relevant to other countries.
2

4

we estimate changes specifications in the context of mandatory partner rotation. Reinforcing
our core evidence, we find that a change in auditor narcissism stemming from mandatory
audit partner rotation is positively associated with changes in audit quality. Moreover, we do
not find any discernible difference in signature size between high- and low-quality clientsassigned to the same partner. This helps dispel the concern that reverse causality in the formof the quality of the audit work affecting signature size is spuriously responsible for our mainevidence. It also helps empirically validate that narcissism is a stable, enduring personality
trait. 4
Next, we deepen the analysis to explore the channel through which auditor narcissism
shapes audit quality. This involves examining whether partner narcissism plays a larger role
when auditor independence or auditor competence is particularly salient. We find that thepositive impact of auditor narcissism on audit quality is concentrated in situations whereauditor independence is more likely to be threatened. For starters, we provide evidence thatthe positive effect of auditor narcissism on audit quality is stronger for large clients that arepresumably more important than others. Second, we find that the impact of partner narcissismon audit quality intensifies when auditors and client executives have school ties. Additionally,
we document that the importance of auditor narcissism to audit quality does not varysystematically with engagement complexity. Altogether, these results suggest that althoughmore narcissistic partners have similar competence as their less narcissistic peers, they tend
to be more independent, which engenders higher audit quality.
We undertake extensive additional analysis, which corroborates our main evidence.
Since Big Four firms have developed more sophisticated quality control structures and more

Untabulated analyses reveal that our core results generally hold if we control for client CEO
narcissism using their signature size, despite the ensuing severe sample attrition stemming from poor
data availability. Similarly, our results are virtually identical when we restrict the samples to firms withthe same CFO, the same CEO, or both, in the years surrounding auditor rotation to hold executive-level
narcissism constant. This evidence helps dispel the possibility that client narcissism affects both auditor
narcissism and audit quality, improving identification.
4

5

standardized audit procedures (El Ghoul, Guedhami, and Pittman, 2016), we expect toobserve that partner narcissism matters more to audit quality in non-Big Four firms where
there are fewer constraints on personality characteristics playing a role. Lending support tothis intuition, we generally find that partner narcissism has a larger impact in non-Big Four
audit firms. We also find that while narcissism is irrelevant to the likelihood that the partner
renders a going concern opinion or makes a Type I (false positive) going concern reporting
error, partner narcissism does lower the incidence of Type II (false negative) errors. These
results suggest that overly conservative reporting by more narcissistic partners is not behind
their higher audit quality. 5 Instead, their outperformance likely stems from resisting clientpressure to issue an overly optimistic opinion. Finally, we find that more narcissistic auditors
are less likely to be sanctioned by regulators, and in the rare occasions that they are, thesanctions tend to be less serious.
We contribute to extant evidence in several ways. First, in initiating empirical researchon intrinsic personality characteristics of individual auditors, we report large-sample
evidence that the degree of partner narcissism shapes audit quality. Prior studies focusing on
abstract auditor fixed effects or observed demographic characteristics naturally struggle toestablish causality (Bertrand and Schoar, 2003). Many of the personal characteristics understudy in prior work such as education and experience are acquired by the auditors, anddecisions to acquire these characteristics may correlate with audit quality as well as thepairing between auditors and clients. 6 In this respect, examining a stable personality trait asopposed to acquired characteristics facilitates drawing causal inferences. Moreover, ourevidence is constructive given that Gul et al. (2013) and Cameran et al. (2018) find that
although some auditor demographic characteristics matter, the variation in audit outcomes
Both audit partners (e.g., Christensen, Glover, Omer, and Shelley, 2016) and the PCAOB (2015)
perceive that Type II reporting errors reflect lower audit quality.
6 In an exception, Kallunki et al. (2017) examine the relation between auditor intelligence and audit
quality. Although an intrinsic characteristic, intelligence reflects cognitive ability; i.e., it is not a
personality trait.
5

6

across individual auditors largely remains unexplained. As such, our analysis responds tocalls for research on the determinants responsible for inter-partner variation in audit quality(e.g., Cameran et al. 2018; Lennox and Wu, 2018).
Second, we introduce analyzing personality theories to empirical audit research.
Grounded in psychology, research in finance, management, and accounting relies on
personality theories to motivate their predictions on the role that executive narcissism playsin their decisions and corporate outcomes (e.g., Aktas et al., 2016; Ham et al., 2017, 2018). We
extend this research by examining whether audit quality is sensitive to partner narcissism.
Auditors’ work is considerably different from that of corporate executives. Auditors are
required to evaluate their clients’ compliance with accounting standards. Not only areauditors’ judgment processes bounded by accounting and auditing standards, but also they
are subject to discipline stemming from peer review, litigation, and reputation protection
forces (DeFond and Zhang, 2014). Consequently, the implications of narcissism for auditors
sharply diverge from those for corporate executives. Indeed, our evidence suggests thatnarcissism plays a positive role in audit quality in contrast to the largely negative impacts
arising from executive narcissism. Although narcissists may have a lower tolerance formonitoring (Young et al., 2016), narcissistic partners may outperform in monitoring theirclients’ financial reporting. In short, we broaden our understanding on how narcissism as apersonality dimension impacts economic behavior and outcomes.
Third, the PCAOB now requires the disclosure of the identities ofengagement

partners in the U.S. on the grounds that such disclosure would enable financial statement
users to better gauge partner and audit quality, improving investor decision-making (PCAOB,
2009, 2013). In the discourse surrounding this proposed policy shift, both public accounting
firms and societies of CPAs strenuously opposed divulging partner identities (Deloitte, 2009;
Ernst & Young, 2009; Grant Thornton, 2009; KPMG, 2009; PricewaterhouseCoopers, 2009),
while investor groups argued that this disclosure was valuable. Our study lends some support7

to the intuition that individual personality traits matter to assurance services. Together withexisting audit partner-level research, our analysis further implies that the public disclosure of
the identity of engagement partners is informative to capital market participants. Against the
backdrop of the PCAOB adopting rules requiring the disclosure of engagement partners’
names starting in 2017, our research helps to inform the continuing debate over the merits ofidentifying partners in the U.S. and elsewhere.
Finally, experimental research suggests that partner accountability rises when they are
required to actually sign the audit report (e.g., DeZoort, Harrison, and Taylor, 2006; PCAOB,
2009). 7 We provide evidence of another downside stemming from not requiring audit
partners to physically sign their reports: investors are deprived of the information value inthe signature size. Our evidence from examining ERCs and debt pricing implies thatshareholders and lenders consider the extent of partner narcissism evident in signature size
to be relevant to their evaluation of audit quality. Also, our research may benefit audit firms
eager to design optimal partner assignment policies (Lennox and Wu, 2018); e.g., they may
prefer to assign more narcissistic partners to clients known to undertake more aggressive
financial reporting positions. Similarly, our results may interest audit firms that consider
employees’ attributes, including their personalities, in making recruitment and promotion
decisions (Campbell, 2012).

2

Motivation

2.1

The Impact of Narcissism on Corporate Behavior and Performance
Although excessive narcissism is a clinical disorder, narcissism has become widely

accepted as a personality dimension on which individuals can be arrayed on a continuum
Carcello and Li (2013) explain that the PCAOB may later require engagement partners to sign theiraudit reports. Reinforcing this perspective, some investors and banking regulators have called for theimposition of a partner signature requirement in the U.S. (e.g., CalPERS 2009; Council of Institutional
Investors 2009; AFL-CIO 2011; Federal Housing Finance Agency 2011).

7

8

(e.g., Freud, 1957; Emmons, 1987; Chatterjee and Hambrick, 2007). The prevailing view inpsychology is that a person’s degree of narcissism is relatively enduring (Cramer, 1998;
Campbell, Foster, and Finkel, 2002). Highly narcissistic individuals consider themselves as
exceptional performers and need to have their elevated self-images continually reaffirmed byothers (Campbell, Goodie, and Foster, 2004). Feelings of entitlement and superiority, strong
self-esteem, and a need for constant admiration and attention are major manifestations of
narcissism.
Despite that narcissism is often framed as synonymous with a sense of superiority andentitlement, a lack of empathy, arrogance, and all sorts of self-centered behavior, it can also
make a person more productive, including by bringing transformative ideas and strong
leadership to an organization (e.g., Maccoby, 2000; Wallace and Baumeister, 2002). According
to Maccoby (2003), narcissists tend to be independent thinkers driven by a vision of changing
the world. They are also relatively uninhibited by internal constraints. For example, narcissists
are less susceptible to the temptation to be drawn toward a herd mentality and to conform tosocial pressure. Narcissists are also not closely governed by external constraints. In particular,
they chart their own course and are willing to take risks in pursuing their objectives without
fearing failure. Other productive attributes of narcissism include passion, charisma, andperseverance, which can help narcissists become outstanding performers.
Recent research examines how executive-level narcissism affects corporate behavior
and economic outcomes. For example, Chatterjee and Hambrick (2007) find that narcissistic
CEOs tend to take bold actions that attract attention such as undertaking acquisitions,
resulting in wide swings in firm performance. Ham et al. (2018) document that narcissistic
CEOs are more likely to engage in overinvestment, deliver worse returns on assets, and enjoy
higher compensation. Zhu and Chen (2015a) find that CEO narcissism limits directors’
influence over corporate strategy. Relatedly, Zhu and Chen (2015b) report that narcissistic
CEOs select directors who conform with their own personality given that these directors are9more supportive of the CEOs’ risk-taking activities. Aktas et al. (2016) provide evidence thatnarcissistic acquirer CEOs tend to initiate deals and, as acquirers, they negotiate faster in the
takeover process and experience lower announcement returns. Additionally, Ham et al. (2017)find that CFO narcissism is positively associated with earnings management and weakinternal control quality. In sum, while some evidence suggests that executive narcissism
negatively affects financial reporting and certain corporate outcomes, others researchsupports that narcissistic CEOs have a tighter grip on strategic control and a larger appetite
for risk.
2.2

Audit Quality at the Individual Auditor Level
Recent research at the individual auditor level provides valuable insights on thedeterminants of audit quality. Focusing on Taiwanese companies, Chen et al. (2008) examine
the role of partner tenure in shaping audit quality, while Chin and Chi (2009) analyze theimportance of audit partner industry expertise to the incidence of client restatements. Gul etal. (2013) and Cameran et al. (2018) document that audit quality in China and the U.K.,
respectively, varies with the auditor’s demographic background, including their educationand experience. Aobdia et al. (2015) find that Taiwanese companies audited by higher-quality
partners elicit larger earnings response coefficients, smaller IPO underpricing, and more
attractive debt contracting. However, prior research seldom examines whether audit quality
is sensitive to individual auditors’ intrinsic personality traits, as opposed to acquired
characteristics such as education, experience, expertise, or social networks.
Although recent research on CEO narcissism enriches our understanding of the
impacts of executives’ personalities, the arguments underlying its predictions do notnecessarily apply to auditor narcissism. Executive narcissism is associated with bold corporate
decisions, low financial reporting quality, and poor firm performance (Ham et al., 2017, 2018).
To garner admiration and affirmation, narcissistic CEOs may take risky actions detrimental

10

to the company or manage earnings in attempting to reach targets. These actions involve a
broad range of decision choices and are less subject to scrutiny by others. The personal
attributes of auditors can have different implications than those of CEOs (Gul et al., 2013). In
contrast to narcissistic CEOs who routinely dictate corporate policies, narcissistic auditors
must comply with auditing standards promulgated by professional regulators and follow
standardized auditing procedures. Key decisions such as tolerable risk levels and materiality
thresholds are also largely set by the audit firm. Partners’ work is also subject to explicit
internal and external peer reviews as well as discipline stemming from litigation institutions
and reputation protection forces. Consequently, one dimension of narcissism, the tendency toviolate explicit rules to benefit themselves, may be attenuated for auditors.
2.3

Auditor Narcissism and Audit Quality
We posit that narcissism may shape an auditor’s independence and competency,

which, in turn, determines audit quality. The auditing process involves evaluating accounting
records and practices, examining judgment, coordinating the audit engagement team, andcommunicating with client managers and its audit committee. The partner’s personality
attributes can affect all of these activities. Despite that consensus has emerged on thedefinition of narcissism as a compelling personality trait rooted in psychology theory,
narcissism is a complex concept that may affect auditor independence and competence inmultiple ways. Accordingly, it remains unclear ex ante whether narcissism benefits orundermines audit quality.
Narcissists are self-centered persons who routinely devalue others (Nevicka et al.,2011). This suggests that more narcissistic partners are more likely to discount the value ofmajor clients because self-centered narcissists perceive themselves as being the mostimportant consideration in any situation. Narcissistic individuals tend to focus on their own
perspectives, while ignoring those of others (Byrne and Worthy, 2013). As such, acquiring and11maintaining an image as a savvy gatekeeper to attract respect and praise from their peers may
matter more to narcissistic auditors than keeping their clients happy. Further, Maccoby (2003)
argues that narcissists are relatively free from internal constraints in that, among other things,
they resist both capitulating to a herd mentality and conforming to social pressure. Thisimplies that narcissistic partners are less likely to respond to pressure to keep importantclients by compromising their independence. Although they risk losing major clients, suchpotential defections are less of a concern to narcissists, who are typically more apt to take risks
in pursuing their objectives without worrying excessively about potential negative outcomes(Maccoby, 2003). Finally, narcissists’ need for constant recognition and attention (Raskin andHoward, 1988) implies that more narcissistic partners are eager to develop a reputation as thebest in the field which, as they presumably understand, requires them to protect their
independence. Taken together, prior research implies that more narcissistic auditors are more
likely to remain independent instead of succumbing to client pressure. It follows thatnarcissism improves partner independence, which translates into higher audit quality.
From a cognitive standpoint, narcissism entails a belief in one’s superior ability (e.g.,
Farwell and Wohlwend-Lloyd, 1998). Reflecting this self-perception, narcissistic partners are
more likely to adamantly stick to their own opinions and less likely to accept the client
manager’s justification when evaluating the appropriateness of accounting policies andestimates. The psychology literature also finds that people high in narcissism arrive at theirown judgments independent of those of others, and they outperform people low in narcissism
when misleading information is presented (e.g., Byrne and Worthy, 2013). The judgement
independence possessed by narcissistic partners implies that they are less likely to be deceived
by inaccurate information provided by clients. This, in turn, increases the probability thatpartners will detect a breach, implying greater auditor competence. Accordingly, auditor
narcissism may mitigate the potential for managers to exploit the discretion afforded under
GAAP to distort their firms’ financial reporting, resulting in higher audit quality.
12Narcissism is associated with enhanced self-perception and a need to have such views
reaffirmed by others (Judge, LePine, and Rich, 2006). Given that financial reporting failures
can severely tarnish an individual auditor’s reputation (e.g., He, Pittman, and Rui, 2016),
narcissistic partners have strong incentives to maintain high audit quality. Nevicka, Bass, and
Ten Velden (2016) find that narcissistic persons tend to react aggressively when they receive“ego-threat” information (i.e., information not conforming to their inflated self-views), which
they counter with outstanding performance that demonstrates their ability. Auditors facechallenges not only from clients, but also from peers or the general audit market. The
challenges could be in-house peer reviews or regulatory inspections of audit work that may
cast doubt on their competence and independence. Such a threat to their self-image can fuelthe performance of narcissistic auditors, resulting in stricter external monitoring of theirclients’ financial reporting. In sum, besides its impact on auditor independence, narcissism
could also motivate auditors to supply more audit effort to deliver high quality work, whichhelps to garner a reputation of superiority in auditing along with recognition. Thesearguments imply that the increased competence channel is partly behind more narcissistic
auditors conducting higher quality audits.
On the other hand, psychology research finds that narcissistic group leaders dominate
the decision process and tend to ignore input from others, leading to poor group decisionoutcomes (Nevicka et al., 2011). This implies that narcissistic partners tend to dismiss insightsfrom other members of the audit engagement team that could help identify accounting errors.
As a result, narcissistic partners become less informed and thus have a lower probability ofdetecting their clients’ financial reporting problems, undermining auditor competence. For
example, Trotman, Bauer, and Humphreys (2015) stress that the quality of engagement teamdiscussions affects decision quality. In addition, narcissistic partners’ elevated self-perception
may engender relative optimism concerning their ability and the likelihood of positive

13

outcomes. 8

This can lead narcissistic partners to optimistically conclude that they can easily

identify any problems in a client’s financial reporting system without a sufficiently diligent
collection and evaluation of audit evidence. Consequently, more narcissistic partners are less
apt to detect breaches of accounting standards, suggesting lower auditor competence. In short,personality theories drawn from psychology research yield opposite predictions on how
narcissism shapes partner competence.
To summarize, narcissism is expected to have a positive effect on auditor
independence, although it can have either a positive or a negative impact on auditor
competence. The overall effect of narcissism on audit quality can run in either direction,
depending on which forces dominate. Given that this remains an empirical issue, we do notformulate a directional prediction. Importantly, we rely on cross-sectional analysis to help
empirically clarify whether the role that narcissism plays in audit quality stems primarily
from its impact on auditor competence versus independence.

3

Measurement, Data, and Research Design

3.1

Measuring Auditor Narcissism
Empirical research naturally struggles to identify a valid proxy for an underlying

psychological construct such as a personality trait. Standard proxies used in the CEO
narcissism literature include the prominence of the CEO’s photograph in the firm’s annual
report (e.g., Zhu and Chen, 2015a, 2015b) or the number of personal pronouns used in press
releases (e.g., Chatterjee and Hambrick, 2007; Aktas et al., 2016). However, the prominence of
the CEO’s photograph can reflect suggestions by corporate communications specialists

Narcissism and overconfidence are distinct concepts from both psychological and behavioral
perspectives (Campbell et al., 2004). Although a narcissistic person may exhibit a certain degree ofoverconfidence, this is not a main attribute of narcissism. Narcissism reflects more behavioral issues
such as a need for constant recognition and attention, a lack of empathy, and a sense of entitlement.
Ham et al. (2018) demonstrate that the narcissism measure that we use, signature size, is not correlatedwith the traditional measure of overconfidence.

8

14

instead of CEO narcissism, admitting measurement error. Similarly, corporate disclosurecommittees and investor relations consultants influence the number of first pronouns used inannual reports and press releases. Accordingly, these measures suffer from construct validity
concerns of unknown severity (Koch and Beimann, 2014; Carey et al., 2015).
Recent studies show that signature size is a simple, unobtrusive measure of anindividual’s narcissism (Ham et al., 2017, 2018). Extensive prior research in psychology
stresses that the signature is a powerful symbolic representation of the self (e.g., Kettle andHaubl, 2011; Bryan, Adams, and Monin, 2013; Chou, 2015). Relevant to our purposes,
psychology research has long established a link between narcissism and signature size. In
particular, Zweigenhaft and Marlowe (1973) demonstrate that individuals with higher selfesteem have larger signatures. Subsequent evidence lends support to the intuition thatsignature size reliably measures ego and dominance (Zweigenhaft, 1977; Jorgenson, 1977) as
well as self-regard (Koole and Pelham, 2003). Self-esteem, ego, dominance, and self-regard are
all prominent attributes of narcissism, reinforcing that we are on solid ground in gauging
narcissism with signature size.
In another major upside, specifying narcissism with signature size ensures that themeasure under study is nonreactive and unobtrusive. Social science research has longadvocated measurement techniques involving an unobtrusive “physical trace” left behind by
subjects (Webb, Campbell, Schwartz, and Sechrest, 1966). Using signature size does not
require individuals to answer direct questions about narcissism in a survey, and participants
are likely to be unaware that their level of narcissism would be evident in their signatures(Rudman, Dohn, and Fairchild, 2007). 9To further validate this measure of narcissism, Ham et al. (2018) analyze a sample ofbusiness school graduate students and show that there is a monotonic relation between

Moreover, survey questions on issues as sensitive as narcissism are likely to generate very low
response rates and/or unreliable answers.

915

signature size and results from the 16-item Narcissistic Personality Inventory (NPI-16) scale
developed and validated by Ames, Rose, and Anderson (2006), where the NPI-16 is derived
from the earlier 40-item Narcissistic Personality Inventory (NPI-40) scale developed andvalidated by Raskin and Howard (1988). They also show that signature size is distinct fromoverconfidence. 10 Ham et al. (2017) undertake a similar validation test in a lab setting, which
corroborates the monotonic relation between signature size and the NPI-40 narcissism score.
Collectively, prior research has shown that signature size constitutes a reliable measure of
narcissism. We follow recent research in specifying a person’s signature size to reflect theirdegree of narcissism (e.g., Davidson et al., 2015; Ham et al., 2017, 2018; Zhou, 2017; Bushman
et al., 2018).
The annual reports for listed Taiwanese firms include the signatures of both the leadand review partners. After downloading the annual reports from 2006 to 2015 for each listedcompany, we locate the partners’ signatures in the audit report section. After obtaining imagesof the signatures, we use a custom software program called ImageJ to determine their size.
More specifically, we follow Ham et al. (2017, 2018) by using the program to draw a rectangle
tightly around each signature, so that each side of the rectangle touches the most extreme
endpoint of the signature. We multiply the length and width of the rectangle to determine thearea occupied by the signature. To control for the length of the auditor’s name, we divide thesignature area by the number of characters in the partner’s name. 11 For each partner, we thentake the average of this measure using all the signatures of the same partner across the entire
2006-2015 sample period to obtain the average signature size. 12 Finally, we use the natural
Ham et al. (2018) report that the Pearson correlation between signature size and narcissism is 0.36
with a p-value under 0.01. The correlation remains highly positive when they remove the six items in
the NPI-16 that are also most closely related to overconfidence whereas the correlation between
signature size and those six items is insignificant.
11 Our empirical results are virtually identical when we re-specify this variable by: (i) dividing thesignature area by the number of strokes in the partner’s name to obtain an alternative standardized
signature size; or (ii) using the raw signature area.
12 To the extent that narcissism is a fixed and enduring personality characteristic, it remains stable overtime or across settings for the same individual. However, an auditor’s signature size may vary slightly
10

16

logarithm of the average signature size as the measure of narcissism of an individual partner. 13
The data source has some distinct advantages. First, all signatures are signed by hand since
we delete the few cases where the signatures are electronically inserted. Second, all partners
provide the same attestation for the same purpose using the same form with the samestructure that did not substantially constrain the space available for the signature. Therefore,
the signatures are comparable across partners, across clients, and over time. Although Ham
et al. (2017, 2018) have validated that signature size measures narcissism, we further validate
whether it holds for signatures in our setting. For the 145 undergraduate accounting students
at a large public university in Taiwan who participated in the validation study, we find acorrelation coefficient of 0.39 (p-value < 0.001) between signature size and narcissism (NPI40), comparable to that reported in Ham et al. (2017, 2018). 14
The financial statements of public companies in Taiwan must be certified by two audit
partners: the lead and review partners. The lead partner handles planning and implementing
the audit engagement, whereas the review partner is primarily responsible for reviewing thefinal audit report (e.g., Aobdia et al., 2015). Chin and Chi (2009) find that restatement
likelihood in Taiwan is driven by the expertise of the lead partner; in contrast, the review
partner has no perceptible impact on this frequency. Consistent with Chin and Chi (2009) andChi and Chin (2011), Aobdia et al. (2015) document that in Taiwan review partner fixed effects
do not explain the magnitude of discretionary accruals incremental to lead partner fixed
effects, and that there is little or no link between review partner quality and capital market

and randomly across audit reports of different clients and/or over different years. We use the average
signature size of an individual auditor to reduce the noise in our narcissism measure. Later, we provide
evidence verifying that the signature size of an auditor does not vary significantly across clients or overtime.
13 Our core results are materially insensitive to using the natural logarithm of signature size or the raw
average signature size. Similarly, our evidence holds when we replace our main narcissism test variable(based on average signature size over 2006-2015) with the size of the most recent signature to capture
the narcissism construct.
14 Details of the validation study, including correlations between components of narcissism (i.e.,
subscales of NPI-40) and signature size, are available from the authors upon request.
17

outcomes. 15 Given that the lead (review) partner plays a relatively active (passive) role in theengagement, we follow prior research by focusing on lead partner narcissism in the analysis.
3.2

Other Data
We download the annual reports containing auditor signatures from the Taiwan Stock

Exchange’s Market Observation Post System, which stores all annual reports since acompany’s listing. Financial and accounting data as well as data on signing partner names,
audit firms, audit opinions, and accounting restatements are collected from the Taiwan
Economic Journal (TEJ) database, which covers all public companies in Taiwan. Our sample
contains 566 unique lead audit partners and 1,441 unique client firms covering the period from2006 to 2015. The maximum sample size used in our empirical analysis is 12,244 firm-year
observations; the sample shrinks for some estimations stemming from the loss of observations
with missing values or the construction of certain variables. 16
3.3

Research Design
To triangulate the analysis, we evaluate audit quality in multiple ways, capturing both

its actual and perceived aspects. We use three measures of actual audit quality based on clients’reported earnings and actual misstatements, all of which are commonly used in extant
research (e.g., Francis and Yu 2009; Reichelt and Wang 2010; Newton, Wang, and Wilkins2013). The first measure is ADACC, which is the absolute value of abnormal accruals using amodified Jones model controlling for ROA. 17 The second measure is STD_DD, which is thePrivate conversations with several audit partners in Taiwan also confirm that the lead partner
generally has more hands-on involvement in an engagement than the review partner.
16 We analyze a constant sample in our regressions (i.e., an observation is dropped if a cross-sectional
test variable is missing for it even if that variable never appears in, and thus does not affect, the main
regression). However, it is important to stress that our core evidence holds when we examine themaximum number of observations possible in each regression.
17 Some prior research implies that auditors focus more intently on constraining upward, rather than
downward, earnings management (Nelson, Elliot, and Tarpley, 2002; Lennox, Wu, and Zhang, 2014),
although other research (e.g., Myers, Myers, and Omer, 2003; Francis and Yu, 2009), including on
Taiwanese firms (e.g., Aobdia et al., 2015), suggests that high-quality auditors reduce both forms. In
results not reported in tables, we find that partner narcissism reduces both positive and negative
abnormal accruals.
15

18

standard deviation of firm-level residuals from the Dechow and Dichev (2002) model over a
five-year rolling window. Audit quality is inferred by examining abnormal accruals andaccruals quality which characterize client earnings properties. A higher value of ADACC or
STD_DD indicates lower audit quality. We run the following regression, where AQ is
specified as either ADACC or STD_DD:
AQit = α0 + α1AUD_NARi + ∑βkControlkit + Industry Effects + Year Effects + εit(1)

AUD_NAR is our measure of partner narcissism. As stressed earlier, AUD_NAR andall other variables at the individual auditor level reflect the lead audit partner. The choice andspecification of the control variables follows recent research (e.g., Chin and Chi, 2009;
Goodwin and Wu, 2014). This involves controlling for audit partner industry specialization(AUD_SPEC), tenure (AUD_TENURE), experience (AUD_EXP), and gender (AUD_FEMALE).
We also control for audit firm-level industry specialization (CPAFIRM_SPEC), tenure(CPAFIRM_TENURE), and reputation (BIG4). The remaining control variables represent acomprehensive set of client firm characteristics, including its size (SIZE), sales growth(SALEGROWTH), the volatility of sales growth (SALESVOLATILITY), operating cash flows(CFO), cash flow volatility (CFOVOLATILITY), financial leverage (LEV), loss status (LOSS),
financial distress (BANKRUPTCY), stock return volatility (VOLATILITY), the market-to-bookratio (MB), firm life cycle (AGE), and operating cycle (OPERCYCLE). Table 1 lists all regression
variable specifications.
The third actual audit quality measure under study is the incidence of restatements.
We code RESTATE equal to 1 if the financial statements are later restated, and 0 otherwise.
We estimate this logistic regression, where P is Prob(RESTATE=1) in the logit function:𝑃𝑃log[1−𝑃𝑃𝑖𝑖𝑖𝑖 ] = α0 + α1AUD_NARi + ∑βkControlkit + Industry Effects + Year Effects
𝑖𝑖𝑖𝑖

(2)

The other two measures capture perceived audit quality. The fourth measure is built

on the earnings response coefficient (ERC), reflecting the equity market’s audit quality
19perception after Teoh and Wong (1993) and Aobdia et al. (2015). 18 If investors conclude that
audit quality rises with partner narcissism, then ERCs will be higher for firms appointing
more narcissistic auditors. We estimate the following model, where CAR is the three-day
cumulative (market-adjusted) abnormal returns surrounding the semi-annual and annual
earnings announcements as these two earnings numbers are audited. UE is the corresponding
seasonally differenced earnings per share deflated by stock price at the end of the day, threedays before the corresponding earnings announcement. Control variables are similar to thosein model (1) and (2). Finally, we follow Aobdia et al. (2015) by including market-model Beta
(BETA), earnings persistence (PERSIST), and an indicator of annual earnings (ANNUAL) inthis model:
CARit = α0 + α1UEit*AUD_NARi + α2UEit+ α3AUD_NARi + ∑γkUEit*Controlkit + ∑βkControlkit +Industry Effects + ∑µUEit*Industry Effects+ Year Effects + ∑πUEit*Year Effects + εit(3)

In our fifth measure, we follow extensive prior research (e.g., Pittman and Fortin, 2004;
Mansi, Maxwell, and Miller, 2004; Dhaliwal, Hogan, Trezevant, and Wilkins, 2011), includingon Taiwanese companies (e.g., Aobdia et al., 2015; Chi et al., 2017), by capturing lender audit
quality perceptions with debt pricing in this model:
SPREADit+1 = α0 + α1AUD_NARi + ∑βkControlk + Industry Effects + Year Effects + εit(4)After Chi et al. (2017), we define SPREADit+1 as the weighted average interest rate of
new loans initiated in year t+1 for client firm i with loan amounts as weights minus theaverage of the 91-day Taiwan Treasury bill interest rates in year t+1. Besides the control
variables in models (1) and (2), we include the ratio of plant, property and equipment assets(TANGIBLE), high interest rate coverage ratio (DINTCOV), loan amounts (LNPROC) and loan
maturity (LNMAT) in the Controlk vector. All control variables are measured at year t, except

We continue to find supportive evidence that investors conclude that audit quality improves withpartner narcissism when we follow prior research (e.g., Hogan, 1997), including on Taiwanese firms(e.g., Aodbia et al., 2015), by gauging their perceptions with IPO underpricing.

18

20

for LNPROC and LNMAT which reflect year t+1. Like with SPREAD, LNPROC and LNMAT
are the weighted averages of loan facility level measures for firms with multiple loans in theyear. Therefore, regression (4) reflects the firm-year level. 19
In all regressions, we control for industry and year fixed effects. All of the continuous
variables used in the estimations are winsorized at the 1% and 99% percentiles to mitigate theinfluence of outliers and potential database coding errors. For all regressions, our test statistics
are based on standard errors clustered by firm. 20

4Main Results

4.1

Descriptive Statistics and Correlations
Table 1 presents descriptive statistics, which include that the mean of the absolutevalue of abnormal accruals (ADACC) is 0.057. The mean likelihood of future restatements(RESTATE) is 1.6%. These statistics are generally consistent with prior research analyzing the
Taiwanese setting (e.g., Chin and Chi, 2009; Aobdia et al., 2015). The correlation matrix inTable 2 indicates that auditor narcissism (AUD_NAR) is significantly negatively correlatedwith ADACC, STD_DD, RESTATE, and SPREAD, providing some preliminary empiricalsupport to the narrative that partner narcissism is positively associated with both actual andperceived audit quality. 21 Next, we analyze whether this evidence persists in a multivariate
framework.

In untabulated analyses, we also control for CEO narcissism measured with their signature size,
although this nearly decimates the samples—we lose over 80% of the observations in somespecifications—since data on CEO signatures suffers from poor availability. Nonetheless, we find that
our core evidence generally continues to hold in these drastically smaller samples.
20 Our inferences are robust to clustering the standard errors by audit partner (or double clustering bypartner and year, or firm and year).
21 We use both semiannual and annual earnings to conduct the ERC analysis. Only annual observations
are used in the correlation computations in Table 2.
19

21

4.2

Evidence on Actual Audit Quality
We begin by examining the links between partner narcissism and actual audit quality

by focusing on the absolute value of abnormal accruals (ADACC). In Table 3, we report in thefirst column that the coefficient on AUD_NAR is -0.010 and statistically significant at the 1%
level, implying that clients that hire more narcissistic partners benefit from higher audit
quality. The coefficient estimates on the control variables are largely consistent withexpectations formed based on prior research. In the second column, we report the leastsquares results when we specify STD_DD as the dependent variable. Again, the coefficient on
AUD_NAR is negative (-0.009) and significant at the 1% level. In short, evidence from these
regressions lends strong support that earnings quality is higher under more narcissistic
partners. Next, we shift gears by examining the role that partner narcissism plays in theshaping the frequency of restatements. 22 In the third column, we find that the coefficientestimate on AUD_NAR, -1.035, loads negatively at the 1% level, consistent with more
narcissistic partners constraining the incidence of misstatements. 23
4.3

Audit Quality Measured by Market Perceptions
Table 4 reports the results when we analyze ERCs and debt pricing that reflect investor

and lender perceptions, respectively. For the sake of brevity, we do not tabulate the results on
the interactions between UE and the control variables. In the first column, the coefficient on
UE*AUD_NAR loads positively at the 5% level, implying that auditor narcissism increases the

22 Analyzing restatements, which represent an egregious audit failure since a clean opinion was issued
on materially inaccurate financial statements, complements examining accruals-based audit quality
proxies that capture earnings management that may be within the confines of GAAP. DeFond andZhang (2014) outline the implications of focusing on accruals (e.g., continuous nature better suits small
samples, although such indirect proxies suffer from high measurement error) versus restatements (e.g.,
low measurement error, although their infrequency undermines statistically power).
23 While it is difficult to assess economic significance with respect to accruals related variables, it isrelatively straightforward to interpret the economic significance with respect to the probability of arestatement. Based on the standard deviation of AUD_NAR and the odds ratio from the logistic
regression, a one standard deviation increase in narcissism (AUD_NAR) is associated with a 23%
reduction in the odds of an accounting restatement.

22market reaction to unexpected earnings. This evidence suggests that investors perceive thatpartner narcissism improves earnings quality. In the second column, we find that thecoefficient on AUD_NAR enters negatively at the 1% level in the interest rate spread
regression, implying that firms relying on more narcissistic partners attract cheaper debt
financing. 24 Collectively, the results in Table 4 on audit quality perceptions complements ourearlier evidence that partner narcissism leads to higher actual audit quality.
4.4

Addressing Possible Selection and Reverse Causality Threats

4.4.1

Selection and Mandatory Auditor Rotation
There is always the concern that the audit quality proxies reflect the client firm’s innate

financial reporting quality instead of the auditor’s performance. In our case, narcissistic
auditors may prefer high-quality clients with a sound financial reporting reputation (Cisek etal., 2014). As such, our earlier results may reflect client characteristics instead of audit quality.
We address this threat by using the mandatory rotation of audit partners as an exogenous
pairing of auditors and clients. In other words, we focus on partner changes only but exclude
all voluntary partner rotations from this analysis. Although it is possible that narcissistic
partners who are rotated away from a client (client A) choose a new client (client B) similar infinancial reporting quality, it is more plausible that client B and client A are not necessarily of
the same type or at least partners have much less room to influence client assignment under
mandatory rotation. In addition, client A’s new auditor is likely to have a different level ofnarcissism than the predecessor. We estimate a changes model by restricting our sample tofirm-years with a change in auditors as a result of mandatory partner rotation. The dependent
variable is now the change in audit quality (except RESTATE), and the key independent
variable is the change in narcissism, ∆AUD_NAR, which is measured as the difference in
Our core evidence persists when we use facility-level, instead of firm-year level, data after Aobdia
et al. (2015). Similarly, our results are robust to using the raw interest rate instead of the interest rate
spread.
24

23

signature size between the incumbent auditor who is rotated away and the successor under
mandatory rotation.
The results are reported in Table 5. We find that the coefficient on ∆AUD_NAR isnegative and significant in the earnings quality and debt pricing regressions, although it fails

to load when we focus on restatements. In the ERC analysis in the last column,
UE*∆AUD_NAR enters positively, consistent with expectations. The within-firm analysis
generally reinforces that (the likely exogenous) increase in partner narcissism leads to higher
audit quality, helping to dispel the concern that omitted firm-level characteristics are
spuriously behind our earlier evidence. Additionally, in re-estimating the regressions after
restricting the samples to firms with the same CFO, the same CEO, or both, before and after
the auditor rotation to hold executive-level narcissism constant, we find nearly identicalevidence.
4.4.2

Reverse Causality
Although prior research provides ample empirical support that signature size

measures an individual’s narcissism (Ham et al., 2017, 2018), it is plausible that for somereason when auditors have more confidence in the quality of their work, they sign their names
in a larger size. In other words, variations in audit quality may cause variations in signaturesize. To tackle this concern, we perform the following analysis. For each auditor, we classify
the clients into those of high audit quality with respect to each of the audit quality measures(firms whose ADACC are in the lowest tercile, whose STD_DD are in the lowest tercile, withno restatements, or whose SPREAD are in the lowest tercile, respectively) and low audit
quality (firms whose ADACC are in the highest tercile, whose STD_DD are in the highest,
having restatements, or whose SPREAD are in the highest tercile, respectively). Then, we
compare the average signature size on audit reports of low audit quality clients with that ofhigh audit quality clients of the same partner. Note that we cannot partition clients using24

perceived audit quality based on ERC because we would need an ERC estimate for each firmyear. As indicated in Table 6, the differences, in both mean and median signature size, arestatistically insignificant. This evidence implies that a specific partner’s signature size does
not vary over time or across different clients (with potentially different innate quality); rather,signature size varies primarily across partners. Moreover, to the extent that signature size as
the measure of narcissism remains constant for each auditor, the results further confirm thatnarcissism is an enduring and fixed personality trait.

5

Cross-Sectional Tests: Auditor Independence and Auditor Competence
To provide more insight into the channels through which narcissism may affect audit

quality, we conduct cross-sectional analysis to isolate whether the impact of narcissism on
audit quality varies across settings where auditor independence or auditor competence isparticularly important to ensuring high audit quality.
5.1

Client Importance and Auditor Narcissism
Auditor independence is more apt to be compromised with important clients (e.g.,

Chen, Sun, and Wu 2010). We define client importance (CL_IMP) as the ratio of the client total
assets divided by the sum of total assets of all clients audited by the same partner in a given
year. We nest CL_IMP and the interaction term between CL_IMP and AUD_NAR in our audit
quality regressions (in the case of equity market audit quality perceptions, we use the threeway interaction UE*AUD_NAR*CL_IMP along with underlying two-way interactions). As
reported in Panel A of Table 7, the coefficients on AUD_NAR*CL_IMP and
UE*AUD_NAR*CL_IMP are statistically significant in the predicted directions. In addition,
they have opposite signs from the coefficients on CL_IMP and UE*CL_IMP, indicating that
although client importance negatively affects audit quality, partner narcissism mitigates this
impact. For smaller, less valuable clients, it is presumably easier for all auditors to remain25independent (Nelson et al., 2002), implying that narcissism plays hardly any role in thissituation. For larger and thus more important clients, partner narcissism translates into higher
audit quality, suggesting that auditor narcissism matters more when auditor independence ismore likely to be compromised. Next, we focus on auditor-client school ties to sharpen ourinferences related to partner independence.
5.2

Auditor-Client School Ties and Auditor Narcissism
Prior social network research implies that audit quality suffers when auditors andtheir clients have school ties (Guan, Su, Yang, and Wu 2016; He, Pittman, Rui, and Wu 2017).
Auditor independence is more likely to suffer when there is a social link between the auditor
and client managers stemming from sharing an alma mater. We learn each lead audit partner’s
educational background from the audit firm’s website. If such information is not available
there, then we determine the lead partner’s educational background through privateinterviews. We also collect the education background of the client firm’s CEO, CFO, and board
members from its annual report. We specify an indicator variable TIE, which equals 1 if thelead audit partner and the client CEO, CFO, or a board member went to the same university,and 0 otherwise.
In Table 7, we report the results in Panel B. The significant coefficients on theinteraction terms between AUD_NAR and TIE imply that partner narcissism improves audit
quality more when auditors and client share school ties. Although school ties generally
undermine audit quality evident in TIE (UE*TIE) entering positively (negatively) in the
regressions, school ties involving a narcissistic partner alleviates this adverse impact on audit

26

quality. 25 Collectively, this evidence reinforces that greater independence is behind more
narcissistic partners conducting better audits. 26
5.3

Audit Complexity and Auditor Narcissism
Next, we analyze engagement complexity in evaluating whether partner narcissism

improves audit quality through the competence channel. In our first proxy for audit
complexity, we follow Goncharov, Riedl, and Shellhorn (2014) by focusing on the number ofsegments in which the client operates. Specifically, we define NSEG as the natural logarithmof the number of segments that a client firm has and interact NSEG with AUD_NAR. As
reported

in

Panel

C

of

Table

7,

the

coefficientson

AUD_NAR*NSEG

andUE*AUD_NAR*NSEG fail to load.
Our second proxy for engagement complexity, INVREC, is the magnitude ofinventories and account receivables scaled by total assets (e.g., Carson, Simnett, Soo, andWright 2012). In Panel D, we report that the coefficients on the relevant interaction terms(AUD_NAR*INVREC or UE*AUD_NAR*INVREC for the ERC regression) are statisticallyindistinguishable from zero.
In our third proxy for engagement complexity, we specify the client’s number ofsubsidiaries (e.g., Hay, Knechel, and Wong, 2006), NSUB, measured as the natural logarithmof one plus the number of subsidiaries. In Panel E, we report that the coefficients on the
Another measure of social bonding that may undermine partner independence is auditor tenure.
However, given that mandatory audit partner rotation began in 2008 in Taiwan and our sample period,
2006-2015, starts only slightly earlier, this prevents us from meaningfully examining any moderatingrole that partner tenure plays.
26 The provision of non-audit services (NAS) to the client is another potential threat to auditor
independence. However, in Taiwan, only firms whose non-audit service fees exceed 25% of the total
fees were required to disclose NAS fees prior to 2009. Although all firms disclose NAS fees starting in
2009, nearly half of the sample firms only disclose fee ranges instead of specific amounts (this also
applies to pre-2009 observations). For example, if a firm discloses that the NAS fee is within the range
of zero to two million Taiwan dollars, then we cannot determine whether it purchases NAS (i.e.,
whether the non-audit fee is zero or some positive number less than two million). Despite thesecomplications, by deleting observations with fee ranges or using the midpoint of range as the NAS fee
amount, we generally find evidence consistent with our results using important clients and school ties
as conditioning variables. However, it is important to interpret the NAS-based evidence as only
suggestive given the data constraints.
25

27

interaction terms AUD_NAR*NSUB and UE*AUD_NAR*NSUB are statistically insignificant.
Taken together, the evidence in Panels C to E implies that the importance of partner narcissism
to audit quality does not hinge on engagement complexity. Overall, our research suggests thatenhanced auditor independence is the main channel through which auditor narcissism
improves audit quality.

6

Additional Analyses

6.1

Narcissism for Big Four vs. Non-Big Four Auditors
Our main evidence implies that actual and perceived audit quality is increasing in

partner narcissism. However, the role that narcissism plays in audit engagements could varysystematically across Big Four and non-Big Four audit firms for at least two reasons. First, Big
Four audit firms have more rigorous quality control structures designed to help them deliver
uniform audit quality across engagements (e.g., Gul et al., 2013; El Ghoul et al., 2016). 27 Suchstructures should constrain the impact of partner-specific characteristics on audit quality (e.g.,
Kallunki et al., 2017). Second, relative to the non-Big Four audit firms, the Big Four usuallyassign larger, well-structured engagement teams, potentially diluting the impact of partnerlevel narcissism. 28 To analyze this issue, we augment the regressions in Tables 3 and 4 withEl Ghoul et al. (2016) outline in detail many of the distinctions that imply that Big Four audit firms,
in comparison to the non-Big Four, employ stricter quality control structures and more standardized
audit techniques that reflect developments in professional standards and insights gathered frominternal quality control reviews and external inspection reports. More generally, extant research implies
that the Big Four are eager to supply uniform assurance services across engagements to protect theirvaluable reputations and to avoid becoming ensnarled in costly litigation (e.g., Cooper and Robson,
2006; Humphrey, Loft, and Woods, 2009). Additionally, DeAngelo (1981) holds that since no single
client is economically important to larger audit firms, they are less apt to compromise their
independence relative to smaller firms. Finally, some prior research argues that non-Big Four firms arecloser to their clients, leaving their independence more vulnerable (e.g., Louis, 2005; Lawrence, MinuttiMeza, and Zhang, 2011).
28 Prior research implies that the Big Four with vast resources at their disposal take steps to ensure thatthe engagement teams are staffed by highly competent and independent personnel, including by
cultivating an audit firm culture that shapes individual auditors’ values, ethics, and attitudes toward
the importance of conducting high-quality audits; providing professional development opportunities
and excellent technical support resources; developing networks to facilitate the sharing of state-of-theart audit methodologies; structuring engagement teams to ensure that they have appropriate industry27

28

interaction terms, AUD_NAR*BIG4 and UE*AUD_NAR*BIG4, and present the results in Table
8. Apart from the restatement regression where the coefficient on AUD_NAR*BIG4 fails toload, we find that the impact of partner narcissism on audit quality is less pronounced in Big
Four clients. At the bottom of the table, we report test statistics on the significance of the
combinedcoefficients

AUD_NAR+AUD_NAR*BIG4,

of

and

UE*AUD_NAR+UE*AUD_NAR*BIG4. We find that, except for the restatement regression,these coefficients are statistically significant, indicating that audit quality rises with partner
narcissism even in the Big Four. Consistent with expectations, our evidence suggests thatpartner narcissism leads to higher audit quality, although its impact is concentrated in nonBig Four engagements.
6.2

Type I and Type II Going Concern Reporting Errors
The likelihood of issuing going concern opinions on financially distressed clients, and,in particular, the likelihoods of making Type I and Type II going concern reporting errors, arealternative indicators of audit quality (e.g., DeFond, Raghunandan, and Subramanyam 2002;
Myers, Schmidt, and Wilkins 2014). We use these alternative measures to test the robustnessof the impact of partner narcissism. Moreover, the Type I (false positive) and Type II (false
negative) error tests may enable us to learn more about the type of audit mistakes thatnarcissism helps to reduce.
We follow prior research by classifying firms with negative operating cash flows as
experiencing financial distress (e.g., DeFond et al., 2002). We code an indicator variable GC
that equals 1 if a going concern opinion is issued to a client in financial distress, and 0
otherwise. A partner commits a Type I error by rendering a going concern opinion but theclient does not go bankrupt in the next year. We specify an indicator variable, TYPEI_GCE, tobased and transaction-based expertise; and providing all engagement team members with timely
evaluations and sound coaching to ensure that their practical work experience suitably complements
their formal training (e.g., Dopuch and Simunic, 1982; Jeppesen, 2007; Carson, 2009; Christensen et al.,2016).
29

indicate a Type I reporting error. An auditor makes a Type II error, denoted by the indicatorvariable TYPEII_GCE, if the client declares bankruptcy within one year of receiving a clean
audit opinion. Table 9 reports the logistic estimation results. We find that partner narcissism
has no perceptible impact on either the likelihood of issuing a going concern opinion or the
likelihood of committing a Type I error. In contrast, our evidence strongly supports thatpartner narcissism lowers the likelihood of making a Type II reporting error. In theory, an
auditor can reduce Type I errors by becoming exceedingly conservative in their reporting.
Our results suggests that more narcissistic auditors are not more conservative than lessnarcissistic auditors in issuing going concern opinions, as they are equally likely to make TypeI reporting errors. This result also helps explain why auditor narcissism does not increase thelikelihood of issuing going concern opinions. The evidence that auditor narcissism reducesType II errors implies that narcissistic partners are less likely to succumb to client pressure byissuing overly optimistic opinions. This corroborates our earlier evidence suggesting thatnarcissistic partners are less likely to compromise their independence.
6.3

Auditor Sanctions
Finally, we test whether partner narcissism affects the likelihood that they experience

regulatory sanctions, another ex post audit quality measure. Partner sanctions are indicativeof extremely low audit quality stemming from unethical and/or unprofessional behavior(Aobdia et al., 2015; He et al., 2016). A sanction can involve either a suspension or even the
revocation of permission to practice. We identify auditors sanctioned from 1998 to 2016 using
the TEJ Auditor Sanction database. There are 52 cases involving 41 auditors; some auditors
are sanctioned multiple times. We test whether auditor narcissism affects the likelihood of
being sanctioned (denoted with the indicator variable SANCTION), the number of times being
sanctioned (SANCTION_FREQ) and the length of suspension (SUSPENSION_LENGTH,
specified as the natural logarithm of one plus the number of months the sanctioned auditor is30

suspended) conditional on being sanctioned. Although this analysis suffers from low power
since sanctions are scarce, we report in Table 10 that the coefficients on AUD_NAR are
negative and statistically significant in all three regressions: the logistic regression involving
SANCTION, the ordered logit model involving SANCTION_FREQ, and the linear regression
involving SANCTION_LENGTH. Our results suggest that narcissistic partners are less likely
to be sanctioned, and, if they are, the sanctions are less frequent and less severe.

7

Conclusions
Set against recent evidence on the importance of executive-level narcissism tocorporate decisions and economic outcomes (e.g., Aktas et al., 2016; Ham et al., 2017, 2018),
we contribute to extant research by analyzing whether audit partner narcissism shapes audit
quality. More specifically, we examine how partner narcissism, as measured by the signaturesize in audit reports, affects audit quality.
We find that auditor narcissism engenders higher audit quality evident in lowering
the absolute value of abnormal accruals, increasing accrual quality, constraining the
likelihood of restatements, and improving perceived audit quality according to clients’earnings response coefficients and borrowing costs. The results hold when estimating changes
models where the changes in audit quality and auditor narcissism stem from mandatory audit
partner rotation. We also find that audit quality does not reversely affect signature size of thesame auditor, reinforcing the causal role of auditor narcissism.
The impact of narcissism is more pronounced when the clients are larger (andpresumably more important) and when auditors and client executives share school ties. In
contrast, we find no evidence that engagement complexity affects the impact of partner
narcissism on audit quality. Collectively, these results suggest that auditor narcissism
improves audit quality mainly through increased auditor independence instead of higher
auditor competence. In additional evidence consistent with expectations, we find that31

although partner narcissism translates into higher audit quality in both Big Four and non-Big
Four audit firms, it has a smaller impact in the Big Four that are known to have robust quality
control structures and more standardized audit methodologies, which narrows the scope forpartner-level characteristics to matter. We also document that although partner narcissism isirrelevant to the probability of rendering a going concern opinion or committing a Type I
going concern reporting error, it does reduce the likelihood of making a Type II error.
Altogether, these results imply that more narcissistic auditors are less likely to succumb toclient pressure by issuing an overly optimistic opinion. Finally, we find that more narcissistic
auditors are less likely to be sanctioned by regulators, and, in the rare cases that they are
sanctioned, the sanctions are less severe.
It is important to stress that our analysis is subject to several limitations. First, giventhat we cannot directly observe an auditor’s (or any individual’s) level of narcissism, we resort
to relying on signature size to proxy for this personality trait after extensive prior research.
However, this measure does have theoretical foundations in psychology and has beenvalidated in lab settings. Moreover, in all regressions, we control for individual auditor
characteristics such as gender, tenure, experience, and expertise that could potentially affectsignature size. Second, our sample is restricted to Taiwanese firms and auditors. Althoughexternal validity remains a concern with any single-country study, this testing groundprovides a fairly representative set observations given the similarity between Taiwan and the
U.S. in accounting and auditing standards as well as the institutions governing their capitaland audit markets. Indeed, prior research on audit partners focuses on Taiwan as anopportune setting when data constraints prevent analyzing questions using firms from the
U.S. or other major markets (e.g., Chin and Chi, 2009; Aobdia et al., 2015; Chi et al., 2017). Still,
we caution that our inferences may not generalize to audit partners practicing elsewhere.

32References
AFL-CIO. 2011. Comment on PCAOB Concept Release on Possible Revisions to PCAOB Standards
Related to Reports on Audited Financial Statements. PCAOB Release No. 2011-003(September 30). New York, NY: PCAOB.
Aobdia, D., C. Lin, and R. Petacchi. 2015. Capital market consequences of audit partner quality.
The Accounting Review 90: 2143-2176.
Aktas, N., E. Bodt, H. Bollaert, and R. Roll. 2016. CEO narcissism and the takeover process:From private initiation to deal completion. Journal of Financial and Quantitative Analysis
51: 113-137.
Ames, D., P. Rose, and C. Anderson. 2006. The NPI-16 as a short measure of narcissism. Journalof Research in Personality 40: 440-450.
Bertrand, M. and A. Schoar. 2003. Managing with style: The effects of managers on firm
policies. Quarterly Journal of Economics 118: 1169-1208.
Byrne, K. and D. Worthy. 2013. Do narcissists make better decisions? An investigation of
narcissism and dynamic decision-making performance. Personality and Individual
Differences 55: 112-117.
Bryan, C.J., Adams, G.S., and Monin, B. 2013. When cheating would make you a cheater:
Implicating the self prevents unethical behavior. Journal of Experimental Psychology 142:
1001-1005.
Bushman, R., R. Davidson, A. Dey, and A. Smith. 2018. Bank CEO materialism: Risk controls,
culture, and tail risk. Journal of Accounting and Economics 65:191-220.
Cai, H., V. Kwan, and C. Sedikides. 2012. A sociocultural approach to narcissism: The case ofmodern China. European Journal of Personality 26: 529-535.
CalPERS. 2009. Comment on PCAOB Concept Release on Requiring the Engagement Partner to Sign
the Audit Report. PCAOB Release No. 2009-005 (September 14). Available at:
http://pcaobus.org/Rules/Rulemaking/Docket029/022_CalPERS.pdf
Cameran, M., D. Campa, and J. R. Francis. 2018. How important are partner differences in
explaining audit quality? Working paper, Bocconi University, International Universityof Monaco (IUM), and University of Missouri at Columbia.
Campbell, D. 2012. Employee selection as a control system. Journal of Accounting Research 50:
931-966.
Campbell, W., J. Foster, and E. Finkel. 2002. Does self-love lead to love for others? A story of
narcissistic game playing. Journal of Personality and Social Psychology 83: 340-354.
Campbell, W. A. Goodie, and J. Foster. 2004. Narcissism, confidence, and risk attitude. Journalof Behavioral Decision Making 17: 297-311.
Carey, A., M. Brucks, A. Küfner, N. Holtzman, F. Deters, M. Back, M. Donnellan, J. Pennebaker,
and M. Mehl. 2015. Narcissism and the use of personal pronouns revisited. Journal of
Personality and Social Psychology 109: e1-e15.
33

Carcello, J. and C. Li. 2013. Costs and benefits of requiring an engagement partner signature:
Recent experience in the United Kingdom. The Accounting Review 88: 1511-1546.
Carcello, J. V., R. H. Hermanson, and N. T. McGrath. 1992. Audit quality attributes: The
perceptions of audit partners, preparers, and financial statement users. Auditing: A
Journal of Practice and Theory 11: 1-15.
Carson, E. 2009. Industry specialization by global audit firm networks. The Accounting Review:
84: 355-382.
Carson, E., R. Simnett, B. Soo, and A. Wright. 2012. Changes in audit market competition and
the Big N premium. Auditing: A Journal of Practice and Theory 31: 47-73.
Carlson, E. N., S. Vazire, and T. F. Oltmanns. 2011. You probably think this paper’s about you:
Narcissists’ perceptions of their personality and reputation. Journal of Personality andSocial Psychology 101: 185-201.
Chatterjee, A. and D. Hambrick. 2007. It’s all about me: narcissistic Chief Executive Officers
and their effects on company strategy and performance. Administrative Science Quarterly
52: 351-386.
Chen, C., C. Lin, and Y. Lin. 2008. Audit partner tenure, audit firm tenure, and discretionary
accruals: Does long auditor tenure impair earnings quality? Contemporary Accounting
Research 25: 415-445.
Chen, S., S. Y. J. Sun, and D. Wu. 2010. Client importance, institutional improvements, andaudit quality in China: An office and individual auditor level analysis. The Accounting
Review 85: 127-158.
Chi, W., L. Myers, T. Omer, and H. Xie. 2017. The effects of audit partner pre-client and clientspecific experience on audit quality and on perceptions of audit quality. Review of
Accounting Studies 22: 361-391.
Chin, C. and H. Chi. 2009. Reducing restatement with increased industry expertise.
Contemporary Accounting Research 26: 729-765.
Chou, E. 2015. What's in a name? The toll e-signatures take on individual honesty. Journal of
Experimental Social Psychology, 61: 84-95.
Christensen, B., S. Glover, T. Omer, and M. Shelley. 2016. Understanding audit quality:
Insights from audit professionals and investors. Contemporary Accounting Research 33:
1648–1684.
Church, B.K., S. M. Davis, and S. A. McCracken. 2008. The auditor’s reporting model: A
literature overview and research synthesis. Accounting Horizons 22: 69-90.
Cisek, S., C. Sedikides, C. Hart, H. Godwin, V. Benson, and S. Liversedge. 2014. Narcissism
and consumer behavior: A review and preliminary findings. Frontiers in Psychology 5:
1-9.
Cooper, D. J. and K. Robson. 2006. Accounting, professions and regulation: Locating the sitesof professionalization. Accounting, Organizations, and Society 31: 415-444.
34

Council of Institutional Investors. 2009. Comment on PCAOB Concept Release on Requiring theEngagement Partner to Sign the Audit Report. PCAOB Release No. 2009-005 (September 4).
Available at: http://pcaobus.org/Rules/Rulemaking/Docket029/004_CII.pdf
Cramer, P. 1998. Freshman to senior year: A follow-up study of identity, narcissism, anddefense mechanisms. Journal of Research in Personality 32: 156-172.
Davidson, R., A. Dey, ad A. Smith. 2015. Executives’ “off-the-job” behavior, corporate culture,and financial reporting risk. Journal of Financial Economics 117: 5-28.
Dhaliwal, D., C. Hogan, R. Trezevant, and M. Wilkins. 2011. Internal control disclosure,monitoring, and the cost of debt. The Accounting Review 86: 1131-1156.
DeAngelo, L. E. 1981. Auditor size and audit quality. Journal of Accounting and Economics 3:
183-199.
Dechow, P., and I. Dichev. 2002. The quality of accruals and earnings: The role of accrual
estimation errors. The Accounting Review 77: 35–59.
DeFond, M., K. Raghunandan, and K. R. Subramanyam. 2002. Do non-audit service fees
impair auditor independence? Evidence from going concern audit opinions. Journal of
Accounting Research 40: 1247-1274.
DeFond, M. and J. Francis. 2005. Audit research after Sarbanes-Oxley. Auditing: A Journal ofPractice & Theory 24: 5-30.
DeFond, M. and J. Zhang. 2014. A review of archival auditing research. Journal of Accounting
and Economics 58: 275-326.
Deloitte. 2009. Comment letter on: Concept release on requiring the engagement partner to
sign

the

audit

report.

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket029/020_DT.pdf.
Dopuch, N. and D. Simunic. 1982. Competition in auditing: An assessment. In Symposium on
Auditing Research IV. Urbana: University of Illinois: 403-450.
El Ghoul, S., O. Guedhami, and J. Pittman. 2016. Cross-country evidence on the importance of
Big Four auditors to equity pricing: The mediating role of legal institutions. Accounting,
Organizations, and Society 54: 60-81.
Emmons, R. 1987. Narcissism: theory and measurement. Journal of Personality and Social
Psychology 52: 11-17.
Ernst & Young. 2009. Comment letter on: Concept release on requiring the engagement
partner

to

sign

the

audit

report.

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket029/007_EY.pdf
Farwell, L. and R. Wohlwend-Lloyd 1998. Narcissistic processes: Optimistic expectations,favorable self-evaluations, and self-enhancing attributions. Journal of Personality 66: 6583.
Federal Housing Finance Agency. 2011. Comment on PCAOB Concept Release on Possible
Revisions to PCAOB Standards Related to Reports on Audited Financial Statements. PCAOB
35

ReleaseNo.

2011-003(September

30).

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket034/108.pdf
Foster, G. 1977. Quarterly accounting data: Time-series properties and predictive-ability
results. The Accounting Review 52: 1-21.
Francis, J. and M. Yu. 2009. The effect of Big Four office size on audit quality. The Accounting
Review 84: 1521–1552.
Freud, S. 1957. On narcissism: An introduction. In The Standard Edition of The Complete
Psychological Works of Sigmund Freud, Edited by J. Strachey, Hogarth Press, London, U.K.:
67-104.
Goncharov, I., E. J. Riedl, and T. Sellhorn. 2014. Fair value and audit fees. Review of Accounting
Studies 19: 210-241.
Goodwin, J. and D. Wu. 2014. Is the effect of industry expertise on audit pricing an office-levelor a partner-level phenomenon? Review of Accounting Studies 19: 1532-1578.
Guan, Y., N. Su, Z. Yang, and D. Wu. 2016. Do school ties between auditors and client
executives influence audit outcomes? Journal of Accounting and Economics 61: 506-525.
Grant Thornton. 2009. Comment letter on: Concept release on requiring the engagement
partner

to

sign

the

audit

report.

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket029/013_GT.pdf
Gul, F., D. Wu, and Z. Yang. 2013. Do individual auditors affect audit quality? Evidence fromarchival data. The Accounting Review 88: 1993-2023.
Ham, C., M. Lang, N. Seybert, and S. Wang. 2017. CFO narcissism and financial reporting
quality. Journal of Accounting Research 55: 1089-1135.
Ham, C., N. Seybert, and S. Wang. 2018. Narcissism is a bad sign: CEO signature size,
investment, and performance. Review of Accounting Studies, forthcoming.
Hay, D., R. Knechel, and N. Wong. 2006. Audit fees: A meta-analysis of the effect of supply
and demand attributes. Contemporary Accounting Research 23:141-191.
Hayward, M. and D. Hambrick. 1997. Explaining the premium paid for large acquisitions:
Evidence of CEO hubris. Administrative Science Quarterly 42: 103-127.
He, X., J. Pittman, and O. Rui. 2016. Reputational implications for partners after a major audit
failure: Evidence from China. Journal of Business Ethics 138: 703-722.
He, X., J. A. Pittman, O. M. Rui and D. Wu. 2017. Do social ties between external auditors andaudit committee members affect audit quality? The Accounting Review 92: 61-87.
Hogan, C. E. 1997. Costs and benefits of audit quality in the IPO market: A self-selection
analysis. The Accounting Review 72: 67-86.
Hopwood, A., J. McKeown, and J. Mutchler. 1989. A test of the incremental explanatory
power of opinions qualified for consistency and uncertainty. The Accounting Review 64:
28-48.
Humphrey, C., A. Loft, and M. Woods. 2009. The global audit profession and the international36

financial architecture: Understanding regulatory relationships at a time of financial
crisis. Accounting, Organizations and Society 34: 810-825.
Jeppesen, K.K. 2007. Organizational risk in large audit firms. Managerial Auditing Journal 22:590-603.
Jia, T., L. van Lent, and Y. Zeng. 2014. Masculinity, testosterone, and financial misreporting.
Journal of Accounting Research 52: 1195-1246.
Jorgenson, D. 1977. Signature size and dominance: A brief note. Journal of Psychology 97: 269270.
Judge, T., J. Lepine, and B. Rich. 2006. Loving yourself abundantly: Relationship of thenarcissistic personality to self-and other perceptions of workplace deviance, leadership,
and task and contextual performance. Journal of Applied Psychology 91: 762-776.
Kallunki, J, J Mikkonen, L. Niemi, and H. Nilsson. 2017. IQ and audit quality: Do smarter
auditors deliver better audits? Working paper, Stockholm School of Economics.
Kettle, K.L., and G. Haubl. 2011. The signature effect: Signing influences consumption related
behavior by priming self-identity. Journal of Consumer Research 38: 474-489.
Koch, I., and Biemann, T. 2014. Signs of narcissism of CEOs: Validating a widely used measure.
Academy of Management Proceedings.
Koole, S. L. and B. W. Pelham. 2003. On the nature of implicit self-esteem: The case of thename letter effect. In S. Spencer, S. Fein, & M. P. Zanna (Eds.), Motivated social
perception: The Ontario symposium (pp. 93–116). Hillsdale, NJ: Lawrence Erlbaum.
KPMG. 2009. Comment letter on: Concept release on requiring the engagement partner to sign
the

audit

report.

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket029/021_KPMG.pdf.
Krishnan, J. 1994. Auditor switching and conservatism. The Accounting Review 69: 200-215.
Kwan, V., L. Kuang, and N. Hui. 2009. Identifying the sources of self-esteem: The mixed
medley of benevolence, merit, and bias. Self and Identity 8: 176-195.
Kwan, V., C. Hui, and J. McGee. 2010. What do we know about the Chinese self? Illustrations
with self-esteem, self-efficacy, and self-enhancement. In Oxford Handbook of Chinese
Psychology, edited by M. Bond, Oxford University Press, Oxford, UK.
Lawrence, A., M. Minutti-Meza, and P. Zhang. 2011. Can Big 4 versus non-Big 4 differencesin audit-quality proxies be attributed to client characteristics? The Accounting Review 86:
259-286.
Lennox, C., X. Wu, and T. Zhang. 2014. Audit adjustments and measures of earnings quality.
Working paper, Nanyang Technological University.
Lennox, C. S., and Wu, X., 2018. A review of the archival literature on audit partners.
Accounting Horizons, forthcoming.
Louis, H. 2005. Acquirers’ abnormal returns and the non-Big 4 auditor clientele effect. Journalof Accounting and Economics 40: 75-99.
37

Maccoby, M. 2000. Narcissistic leaders: The incredible pros, the inevitable cons. Harvard
Business Review 78: 68-78.
Maccoby, M. 2003. The Productive Narcissist. Broadway Books, New York.
Malmendier, U. and G. Tate. 2008. Who makes acquisitions? CEO overconfidence and themarket’s reaction. Journal of Financial Economics 89: 20-43.
Mansi, S. A., W.F. Maxwell, and D. P. Miller. 2004. Does auditor quality and tenure matter toinvestors? Evidence from the bond market. Journal of Accounting Research 42: 755–-793.
Miller J., L. Maples, L. Buffardi, H. Cai, B. Gentile, Y. Kisbu-Sakarya, V. Kwan, A. LoPilato, L.
Pendry, C. Sedikides, L. Siedor, and W. Campbell. 2015. Narcissism and United States’
culture: The view from home and around the world. Journal of Personality and Social
Psychology 105: 1068-1089.
Myers, J., L. Myers, and T. Omer. 2003. Exploring the terms of the auditor-client relationshipand the quality of earnings: The case for mandatory auditor rotation? The Accounting
Review 78: 779-799.
Myers, L., J. Schmidt, and M. Wilkins. 2014. An investigation of recent changes in going
concern reporting decisions among Big N and non-Big N auditors. Review of Quantitative
Finance and Accounting 43: 155-172.
Nelson, M.W., J.A. Elliott, R.L. Tarpley. 2002. Evidence from auditors about managers’ andauditors’ earnings management decisions. The Accounting Review 77: 175–202.
Nelson, M. and H. Tan. 2005. Judgment and decision making research in auditing: A task,
person, and interpersonal interaction perspective. Auditing: A Journal of Practice & Theory
24: 41-71.
Nevicka, B., F. Ten Velden, A. De Hoogh, and A. Van Vianen. 2011. Reality at odds withperceptions: Narcissistic leaders and group performance. Psychological Science 22: 12591264.
Nevicka, B., M. Baas, and F. Ten Velden. 2016. The bright side of threatened narcissism:
Improved performance following ego threat. Journal of Personality 84: 809-823.
Newton, N., D. Wang, and M. Wilkins. 2023. Does a lack of choice lead to lower quality?
Evidence from auditor competition and client restatements. Auditing: A Journal ofPractice and Theory 32: 31-67.
Pittman, J. and S. Fortin. 2004. Auditor choice and cost of debt capital for newly public firms.
Journal of Accounting and Economics 37: 113-136.
PricewaterhouseCoopers. 2009. Comment letter on: Concept release on requiring theengagement

partner

to

sign

the

audit

report.

Availableat:

http://pcaobus.org/Rules/Rulemaking/Docket029/014_PwC.pdf
Public Company Accounting Oversight Board (PCAOB). 2009. Concept Release on Requiring theEngagement Partner to Sign the Audit Report. PCAOB Release No. 2009-005. Washington,
DC: PCAOB.
38

Public Company Accounting Oversight Board (PCAOB). 2013. Improving Transparency of
Audits: Proposed Amendments to PCAOB Auditing Standards to Provide Disclosure in the
Auditor’s Report of Certain Participants in the Audit. PCAOB Release No. 2013-009.
Washington, DC: PCAOB.
Raskin, R., and T. Howard. 1988. A principal-components analysis of the narcissistic
personality inventory and further evidence of its construct validity. Journal of Personality
and Social Psychology 54: 890-902.
Reichelt, K. and D. Wang. 2010. National and office-specific measures of auditor industry
expertise and effects on audit quality. Journal of Accounting Research 48: 647-686.
Rudman, L., M. Dohn, and K. Fairchild. 2007. Implicit self-esteem compensation: Automaticthreat defense. Journal of Personality and Social Psychology 93: 798-813.
Teoh, S. and T.J. Wong. 1993. Perceived auditor quality and the earnings response coefficient.
The Accounting Review 68: 346–366.
Trotman, K., T. Bauer, and K. Humphreys. 2015. Group judgement and decision making inauditing: Past and future research. Accounting, Organization and Society 47: 56-72.
Wallace, H. and R. Baumeister. 2002. The performance of narcissists rises and falls withperceived opportunity of glory. Journal of Personality and Social Psychology 82: 819-834.
Webb, E., Campbell, D., Schwartz, R., and Sechrest L. 1966. Unobtrusive Measures:
Nonreactive Research in the Social Sciences. Chicago: Rand McNally.
Young, S., F. Du, K. Dworkis, and K. Olsen. 2016. It’s all about all of us: The rise of narcissism
and its implications for management control system research. Journal of Management
Accounting Research 28: 39-55.
Zhou, Y. 2017. Narcissism and the art market performance. European Journal of Finance 23:
1197-1218.
Zhu, D. and G. Chen. 2015a. CEO narcissism and the impact of prior board experience on
corporate strategy. Administrative Science Quarterly 60: 31-65.
Zhu, D. and G. Chen. 2015b. Narcissism, director selection, and risk-taking spending. Strategic
Management Journal 36: 2075-2098.
Zweigenhaft, R., and D. Marlowe. 1973. Signature size: Studies in expressive movement.
Journal of Consulting and Clinical Psychology 40: 469-473.
Zweigenhaft, R. 1977. The empirical study of signature size. Social Behavior and Personality 5:
177-185.

39

Table 1
Pooled Firm-Year Descriptive Statistics
Variables
ADACC
STD_DDRESTATECAR
SPREAD
AUD_NARAUD_SPECAUD_TENURE
AUD_EXPAUD_FEMALE
CPAFIRM_SPEC
CPAFIRM_TENURE
BIG4
SIZE
SALESGROWTH
SALESVOLATILITY
CFO
CFOVOLATILITY
DEBT
LOSS
BANKRUPTCYVOLATILITYMB
AGE
OPERCYCLEUEBETAPERSISTTANGBILE
DINTCOVLNPROC
LNMAT
Variable Definitions:
ADACC

=

STD_DD=RESTATE=CAR=

SPREAD=

AUD_NARAUD_SPEC==AUD_TENURE
AUD_EXPAUD_FEMALE

=
=
=

n
11,867
10,335
12,244
11,252
3,209
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
12,244
11,252
11,252
11,252
3,209
3,209
3,209
3,209

Mean
0.057
0.068
0.016
-0.004
1.958
9.826
0.139
4.913
10.9600.342
0.367
10.0270.849
15.316
0.059
0.173
0.067
0.072
0.411
0.257
3.786
0.120
1.608
3.220
2.625
-0.006
1.053
0.210
0.331
0.500
12.952
7.089

Median
0.040
0.060
0.000
-0.005
1.856
9.808
0.000
4.000
11.000
0.000
0.000
9.000
1.000
15.116
0.023
0.114
0.066
0.052
0.412
0.000
2.772
0.106
1.246
3.258
2.468
0.000
0.998
0.200
0.325
1.000
12.916
6.999

Std.
Dev.
0.057
0.038
0.126
0.041
0.694
0.251
0.346
3.151
5.619
0.474
0.482
6.121
0.358
1.424
0.329
0.192
0.111
0.071
0.178
0.437
3.877
0.067
1.212
0.481
0.818
0.129
0.772
0.448
0.187
0.500
1.831
0.601

Min
0.000
0.002
0.000
-0.124
0.488
8.726
0.000
1.000
1.000
0.000
0.000
1.000
0.000
12.538-0.6540.006-0.330
0.004
0.057
0.000
-0.928
0.026
0.318
1.946
1.249
-0.608-0.968-0.870
0.001
0.000
8.582
5.919

Max
0.587
0.308
1.000
0.137
5.412
11.2221.000
23.00033.0001.000
1.000
33.0001.000
19.729
1.780
1.203
0.380
0.442
0.851
1.000
25.933
0.390
7.501
4.094
6.331
0.595
3.546
1.491
0.796
1.000
17.5198.611

absolute value of abnormal accruals derived from the modified Jones model adjusted for
performance (ROA);
standard deviation of firm-level residuals from the cross-sectional estimation of Dechow
and Dichev (2002) model over five-year rolling windows;
indicator variable that takes the value of 1 if a client’s annual financial statements is
misstated, and 0 otherwise.
three-day cumulative (market-adjusted) abnormal returns surrounding the semi-annual
and annual earnings announcements;
weighted average interest rate of new loans initiated in year t+1 for client firm i with loan
amounts as weights minus the average of the 91-day Taiwan Treasury bill interest rates
in year t+1.
natural logarithm of the average area per character of the auditor’s signature;indicator variable that takes the value of 1 if the auditor has the highest number of clientsin the client’s industry in a specific fiscal year, and 0 otherwise;
number of years that the auditor is retained by the client firm;
number of years since the auditor became a registered public accountant;indicator variable that takes the value of 1 if the auditor is female, and 0 otherwise;40

CPAFIRM_SPEC
CPAFIRM_TENURE
BIG4
SIZE
SALESGROWTH
SALESVOLATILITY
CFO
CFOVOLATILITY
DEBT
LOSS
BANKRUPTCYVOLATILITYMB
AGE
OPERCYCLEUEBETAPERSISTTANGIBLE
DINTCOVLNPROCLNMAT= indicator variable that takes the value of 1 if the client’s audit firm has the highest numberof clients in the client’s industry in a specific year, and 0 otherwise;= number of years an audit firm is retained by the client firm;= indicator variable that takes the value of 1 if a firm is audited by a Big 4 audit firm, and0 otherwise;= natural logarithm of a client’s total assets (in $ thousands);= one-year growth rate of the client firm’s sales revenue;= standard deviation of sales revenue of the client firm over three-year rolling windows;= operating cash flows deflated by lagged total assets of the client;= standard deviation of CFO. We use a rolling window and require three years of data toestimate;= client’s total liabilities deflated by total assets;= indicator variable that takes the value of 1 if the client’s income before extraordinary
items is negative, and 0 otherwise;= Altman Z-score of the client firm that measures of the probability of bankruptcy, with alower value indicating greater financial distress;= client’s stock volatility, calculated as the standard deviation of 12 monthly stock returns
for the current fiscal year;= ratio of a client’s market value of equity to its book value of equity;= natural logarithm of the number of years since the client firm’s incorporation;= natural logarithm of the same of account receivables turnover inventory turnover indays: ln{360/[Sales/Average Accounts Receivable] + 360/[Cost of Goods Sold/Average
Inventory]};= seasonally differenced semiannual and annual earnings per share deflated by stock priceat the end of the day, three days before the corresponding earnings announcement;= market-model beta, estimated over the 12 months preceding the earnings announcement
period;= autoregressive coefficient from Foster’s (1977) model estimated over the sixteen quarters
prior to the earnings announcement;= ratio of plant property and equipment to total assets;= indicator variable that takes the value of 1 if interest rate coverage is above median, and0 otherwise, where interest rate coverage is income before interest expenses and taxes
divided by interest expenses;= natural logarithm of loan amount. It is the weighted averages of loan facility levelmeasures for firms with multiple loans in the year;= natural logarithm of loan maturity. It is the weighted averages of loan facility levelmeasures for firms with multiple loans in the year.

Variables are based on data from the Taiwan Economic Journal (TEJ) database.

41

Table 2
Correlation Matrix
Variables(1) ADACC(2) STD_DD(3) RESTATE(4) CAR(5) SPREAD(6) AUD_NAR(7) AUD_SPEC(8) AUD_TENURE(9) AUD_EXP(10) AUD_FEMALE(11) CPAFIRM_SPEC(12) CPAFIRM_TENURE(13) BIG4(14) SIZE(15) SALESGROWTH(16) SALESVOLATILITY(17) CFO(18) CFOVOLATILITY(19) DEBT(20) LOSS(21) BANKRUPTCY(22) VOLATILITY(23) MB(24) AGE(25) OPERCYCLE(26) UE(27) BETA(28) PERSIST(29) TANGBILE(30) DINTCOV(31) LNPROC(32) LNMAT

(1)
0.196
0.019
0.002
0.149
-0.034-0.025-0.069-0.016-0.012-0.016-0.116-0.038-0.1120.047
0.175-0.048
0.353
0.037
0.018
0.058
0.121
0.103
-0.1290.046
0.022-0.0130.034-0.2400.001-0.041-0.008

(2)
0.238
0.009
-0.0220.186-0.049-0.083-0.129-0.036-0.020-0.034-0.240-0.048-0.200-0.0220.223-0.095
0.275
0.047
0.129
-0.0130.231
0.112-0.241-0.043-0.0230.038
0.029-0.195-0.120-0.136-0.032

(3)
0.024
0.025
-0.0270.064-0.0230.018-0.021-0.005-0.002-0.0350.000-0.0690.025-0.0020.013-0.025
0.022
0.056
0.042
-0.0700.068-0.0370.027-0.003-0.0040.007
0.001-0.034-0.025
0.027
0.003

(4)
0.001
-0.019-0.031-0.069
0.025
0.015
0.031
0.028
0.011
-0.012
0.032
0.011
0.027
0.049
-0.0240.110-0.004-0.055-0.1320.117-0.079
0.077
0.024
0.059
0.108
-0.0550.007-0.0620.129
0.042-0.021

(5)
0.132
0.206
0.052
-0.066-0.074-0.057-0.103-0.060-0.428-0.769-0.222-0.196-0.314-0.0060.111-0.316
0.140
0.242
0.265
-0.3330.207-0.108-0.112-0.108-0.0190.013
0.023-0.066-0.359-0.1750.049(6)-0.039-0.060-0.0280.023-0.0890.021-0.0160.070
0.089-0.253
0.015
0.057
0.008
0.013
0.006
0.019
0.020
0.031
-0.056-0.001-0.044
0.003
0.012
0.013
0.007
-0.034
0.006
0.009
0.028
-0.010-0.036(7)-0.019-0.0860.018
0.017-0.055
0.027
0.047
0.053
0.019
0.096
0.079
0.065
0.077
0.013
-0.017-0.025-0.023-0.006-0.0420.017-0.057-0.018
0.102
0.068
0.004
-0.007-0.008-0.0170.034
0.030-0.025(8)-0.084-0.140-0.0080.029-0.108-0.0140.060
0.480-0.0170.007
0.461-0.0850.155-0.020-0.103-0.011-0.0850.019-0.046-0.035-0.186-0.078
0.213
0.011
0.031
-0.018-0.030-0.0140.008
0.033-0.036(9)-0.004-0.011
0.002
0.023-0.074
0.090
0.054
0.499
-0.107-0.0120.114-0.0590.030-0.016-0.037-0.014-0.0070.003-0.0290.012-0.124
0.026
0.089
0.025
0.015
-0.0570.018-0.087-0.010-0.002-0.013(10)-0.017-0.028-0.0020.011-0.0460.072
0.019-0.029-0.121-0.006
0.074
0.151
0.037
0.003
-0.015-0.0140.002-0.004-0.0120.009-0.042-0.0200.031
0.023-0.011-0.0070.012
0.004-0.013-0.0140.022(11)-0.022-0.040-0.035-0.010-0.077-0.3000.096-0.009-0.024-0.006
0.046
0.314
0.048
0.016
-0.0330.049-0.040-0.038-0.0450.038-0.0480.011-0.0120.019-0.008
0.002
0.038
0.045
0.017
0.052
-0.003

Variables(1) ADACC(2) STD_DD(3) RESTATE(4) CAR(5) SPREAD(6) AUD_NAR(7) AUD_SPEC(8) AUD_TENURE(9) AUD_EXP(10) AUD_FEMALE(11) CPAFIRM_SPEC(12) CPAFIRM_TENURE(13) BIG4(14) SIZE(15) SALESGROWTH(16) SALESVOLATILITY(17) CFO(18) CFOVOLATILITY(19) DEBT(20) LOSS(21) BANKRUPTCY(22) VOLATILITY(23) MB(24) AGE(25) OPERCYCLE(26) UE(27) BETA(28) PERSIST(29) TANGBILE(30) DINTCOV(31) LNPROC(32) LNMAT(12)-0.133-0.2390.011
0.024-0.224
0.004
0.110
0.454
0.122
0.069
0.048
0.020
0.376
-0.069-0.210-0.032-0.2020.081-0.028-0.142-0.288-0.209
0.443
0.078
0.030
-0.006-0.103-0.019-0.0130.192-0.061(13)-0.044-0.057-0.0690.015-0.201
0.041
0.065-0.121-0.080
0.151
0.314
0.004
0.107
0.037
0.006
0.122
-0.036-0.037-0.0880.103-0.0240.065-0.1680.015-0.012
0.048
0.049
0.085
0.049
0.085
0.035

(14)
-0.122-0.2170.029
0.016-0.301-0.000
0.091
0.161
0.033
0.034
0.049
0.401
0.124
0.100
-0.0960.101-0.1620.321-0.215-0.203-0.233-0.135
0.270
0.177
0.006
0.108
-0.017-0.0150.124
0.618-0.045

Table 2 (Continued)
(15)
(16)
(17)
0.146
0.229
-0.1480.044
0.224-0.0980.014
0.025-0.0230.036-0.020
0.093
0.019
0.081
-0.288
0.018
0.021
0.023
0.004
0.005
-0.014-0.034-0.116-0.003-0.035-0.010-0.0160.001-0.010-0.0040.002-0.0150.051-0.079-0.197-0.0190.120-0.003-0.0080.054-0.078
0.113
0.122
0.067
-0.012-0.0690.138-0.0090.018
0.427-0.0500.075
0.150-0.239-0.323-0.005-0.412
0.189
0.110
0.401
0.028
0.176
-0.065
0.271
0.127
0.268
-0.047-0.252-0.101
0.148
0.109
0.078
0.386
-0.062
0.102
0.020
0.045
-0.043
0.053
0.023
0.074
-0.007-0.2510.251
0.188-0.0590.410
0.045-0.0830.106
0.037-0.002
0.011

43

(18)
0.473
0.297
0.037
0.002
0.145
0.002
-0.017-0.0960.012
0.004-0.030-0.184-0.057-0.1460.146
0.471-0.156
0.040
0.008
0.117
0.174
0.148
-0.2320.047-0.0350.016
0.025-0.309-0.056-0.042
0.022

(19)
0.057
0.036
0.059
-0.0600.245
0.037-0.0080.026
0.005-0.004-0.0410.080-0.043
0.310
0.069
0.134
-0.2330.064
0.080-0.6780.039-0.110
0.138
0.058
0.008
0.008
-0.019-0.111-0.4090.170-0.019

(20)
0.020
0.143
0.042
-0.1320.281-0.051-0.042-0.046-0.023-0.012-0.045-0.024-0.088-0.204-0.244-0.005-0.3590.009
0.087-0.371
0.200-0.216-0.032-0.083-0.1890.090-0.0540.085-0.455-0.164-0.013

(21)
0.052
0.081
-0.0370.070-0.281-0.0080.021-0.068
0.007
0.001
0.032
-0.1520.070-0.186
0.104
0.066
0.276
0.095
-0.598-0.160-0.0310.549-0.2430.119
0.110-0.0530.088-0.1670.552-0.058
0.025

(22)
0.144
0.236
0.069
-0.0660.233-0.039-0.047-0.179-0.100-0.040-0.050-0.278-0.040-0.2500.070
0.156-0.066
0.160
0.058
0.190
0.076
0.140
-0.260-0.071
0.039
0.476
0.046
0.030
-0.105-0.1190.044

Variables(1) ADACC(2) STD_DD(3) RESTATE(4) CAR(5) SPREAD(6) AUD_NAR(7) AUD_SPEC(8) AUD_TENURE(9) AUD_EXP(10) AUD_FEMALE(11) CPAFIRM_SPEC(12) CPAFIRM_TENURE(13) BIG4(14) SIZE(15) SALESGROWTH(16) SALESVOLATILITY(17) CFO(18) CFOVOLATILITY(19) DEBT(20) LOSS(21) BANKRUPTCY(22) VOLATILITY(23) MB(24) AGE(25) OPERCYCLE(26) UE(27) BETA(28) PERSIST(29) TANGBILE(30) DINTCOV(31) LNPROC(32) LNMAT

(23)
0.142
0.155
-0.0130.036-0.0680.008-0.003-0.0850.027-0.0320.018-0.1880.044-0.116
0.220
0.143
0.221
0.163
-0.068-0.1300.523
0.245-0.2390.081
0.185-0.0560.118-0.035
0.252
0.032
0.013

(24)
-0.127-0.2480.027
0.021-0.085
0.009
0.098
0.261
0.088
0.030
-0.0140.482-0.1680.240-0.062-0.232-0.094-0.1880.135-0.028-0.259-0.251-0.2340.012
0.034-0.071-0.1000.014-0.0580.157-0.070

Table 2 (Continued)
(26)
(27)
0.034
-0.024-0.0060.029-0.0070.006
0.095-0.039
0.001
0.029
0.011
-0.0330.007-0.0050.008-0.018-0.0430.013-0.013-0.007-0.003-0.0000.009-0.0040.043-0.008-0.003
0.070
0.243
0.015
-0.0360.021
0.054-0.026-0.008-0.015-0.0100.002-0.1780.096
0.063-0.004
0.041
0.418
0.096
-0.0190.019-0.0770.039-0.0680.070-0.022-0.052-0.025-0.0150.008-0.0060.005-0.054
0.024
0.086
0.148
-0.022
0.235
0.021
0.028
-0.015-0.006-0.019(25)
0.076-0.0170.001
0.038-0.070
0.007
0.055
0.005
0.028
0.028
0.013
0.052
-0.017
0.116
0.146
0.115
0.046
0.103
0.054
-0.0750.052-0.0530.104-0.003

(28)
0.031
0.022
0.000
0.009
-0.000-0.000-0.006-0.019
0.018
0.010
0.040
-0.1020.048-0.0120.034-0.001
0.071
0.015-0.013-0.049
0.071
0.037
0.131
-0.096-0.0100.027-0.001-0.036
0.063
0.003
0.061

(29)
-0.293-0.205-0.032-0.069-0.0410.016-0.025-0.023-0.093-0.0030.036-0.0260.079
0.000-0.093-0.2520.287-0.362-0.0980.089-0.1460.006
0.031-0.002-0.006-0.0470.029-0.037-0.046
0.037
0.072

(30)
-0.007-0.105-0.0260.124-0.350
0.035
0.034
0.002
-0.011-0.013
0.017
0.000
0.049
0.132
0.139
-0.0530.335-0.061-0.389-0.4550.365-0.0970.185-0.0620.083
0.120-0.0220.068-0.0520.087-0.019(31)-0.018-0.1330.029
0.032-0.198-0.011
0.037
0.049
0.002
-0.017
0.058
0.218
0.092
0.644
0.035
-0.051
0.080
0.006
0.186
-0.161-0.064-0.118
0.024
0.136
0.174
-0.001
0.006
0.004
0.044
0.085
0.259

(32)
-0.000-0.0190.005-0.016-0.010-0.044-0.027-0.045-0.0170.025
0.004-0.0800.038-0.0430.043-0.0120.011
0.015-0.026-0.018
0.048
0.041
0.016
-0.072-0.020-0.020-0.0300.063
0.056-0.0070.233

This table reports the Pearson (above diagonal) and Spearman (below diagonal) correlations of variables used in main regressions. Correlation coefficients inbold are statistically significant at the 5% level or better.

44

Table 3
Auditor Narcissism and Actual Audit Quality

Independent Variables
Intercept
AUD_NARAUD_SPECAUD_TENURE
AUD_EXPAUD_FEMALE
CPAFIRM_SPEC
CPAFIRM_TENURE
BIG4
SIZE
SALESGROWTH
SALESVOLATILITY
CFO
CFOVOLATILITY
DEBT
LOSS
BANKRUPTCYVOLATILITYMB
AGE
OPERCYCLE
Industry Fixed Effects
Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

ADACC
Coeff.
(t-stat)0.161***(7.73)-0.010***(-4.96)-0.003**(-2.37)-0.000**(-2.43)0.000(1.40)-0.001(-1.10)-0.002*(-1.68)0.000(1.02)-0.000(-0.08)-0.002***(-3.91)0.013***(5.62)-0.004(-0.95)-0.059***(-5.80)0.351***(23.48)0.006(1.23)-0.002(-1.43)-0.000(-0.48)0.012(1.18)
0.003***(4.29)-0.003**(-2.19)0.002***(2.72)

Dependent Variable
STD_DD
Coeff.
(t-stat)
0.210***(8.33)-0.009***(-3.89)-0.007***(-5.65)-0.001***(-2.89)0.000***(2.69)
0.000(0.25)-0.002(-1.26)-0.000(-1.62)-0.003(-1.49)-0.003***(-4.36)0.001(0.72)
0.013***(3.41)-0.009(-1.60)0.105***(9.54)
0.014***(2.60)
0.008***(5.74)
0.000(0.99)
0.039***(4.39)
0.002**(2.44)-0.010***(-5.50)-0.001(-1.43)RESTATE
Coeff.
(χ2-stat)-21.874(0.01)-1.035***(9.60)-0.247(0.80)-0.053*(3.48)
0.041***(7.42)
0.247(2.04)-0.397**(3.95)
0.020(1.54)-0.676***(10.98)0.214***(10.41)0.267(1.66)
0.523(1.61)-0.078(0.01)
2.001*(3.18)
1.349**(4.96)
0.670***(12.85)0.024(0.51)
4.254***(13.50)-0.036(0.20)
0.141(0.39)-0.095(0.72)

Yes
Yes
11,867
0.257

Yes
Yes
10,335
0.203

Yes
Yes
12,2440.243

This table reports the OLS estimation results. Test statistics are based on standard errors clustered byclient firm. *, **, and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively. Allvariables are defined in Table 1.

45

Table 4
Auditor Narcissism and Perceived Audit Quality

Independent Variables
Intercept
UE
AUD_NARUE*AUD_NAR
AUD_SPECAUD_TENURE
AUD_EXPAUD_FEMALE
CPAFIRM_SPEC
CPAFIRM_TENURE
BIG4
SIZE
SALESGROWTH
SALESVOLATILITY
CFO
CFOVOLATILITY
DEBT
LOSS
BANKRUPTCYVOLATILITYMB
AGE
OPERCYCLE
BETA

Dependent Variable
CAR
SPREAD
Coeff.
Coeff.
(t-stat)(t-stat)-0.0024.955***(-0.18)(9.27)-0.254***(-3.01)
0.003-0.145***(1.60)(-3.37)0.055***(3.67)
0.001-0.054*(0.69)(-1.75)0.000
0.001(1.16)(0.27)
0.000-0.005*(0.54)(-1.94)0.000-0.020(0.36)(-0.90)-0.001-0.013(-1.40)(-0.45)-0.000-0.005*(-0.94)(-1.73)0.001-0.163***(1.04)(-3.68)-0.000-0.080***(-0.19)(-5.85)0.030(1.23)
0.014(0.17)-0.361***(-3.43)0.021(0.13)-0.009***0.786***(-3.58)(5.57)***-0.0080.198***(-6.35)(6.30)-0.020(-1.53)-0.005***1.025***(-7.74)(4.53)
0.001**-0.048**(1.97)(-2.51)0.038(1.06)-0.028(-1.59)-0.001(-1.35)46

PERSISTANNUAL
ADACC-0.003(-1.07)-0.002(-0.57)TANGIBLE
DINTCOVLNPROCLNMATUE*Control Variables
Industry Fixed Effects
UE*Industry Fixed Effects
Year Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2

Yes
Yes
Yes
Yes
Yes
11,2520.056-0.035(-0.20)0.155(1.63)-0.167***(-6.81)-0.031***(-3.55)0.004(0.22)
No
Yes
No
Yes
No
3,209
0.496

This table reports the OLS estimation result. Test statistics are based on standard errors clustered byclient firm. *, **, and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively.
CAR is the three-day cumulative abnormal returns (market-adjusted) around the semi-annual andannual earnings announcements. UE is the corresponding seasonally differenced quarterly earnings per
share deflated by stock price at the end of the day three days before the corresponding earnings
announcement. BETA is market-model beta, estimated over 12 months prior to the earnings
announcement period. PERSIST is the autoregressive coefficient from Foster’s (1977) model estimatedover the sixteen quarters prior to the earnings announcement. ANNUAL is an indicator variable equal
to 1 for the annual earnings announcement and 0 otherwise. SPREAD is the weighted average interest
rate of new loans initiated in year t+1 for client firm i with loan amounts as weights minus the averageof the 91-day Taiwan Treasury bill interest rates in year t+1. TANGIBLE is the ratio of property, plantand equipment (PPE) to total assets. DINTCOV is an indicator variable equal to 1 if a firm’s interest
coverage ratio (income before interest expense and taxes divided by interest expense) is above themedian interest coverage ratio in a given year, and 0 otherwise. LNPROC is the natural logarithm of thesum of loan amounts by a firm in a given year. LNMAT is the natural logarithm of weighted average ofloan maturity by the facility amount. All other variables are defined in Table 1.

47

Table 5
Changes Models Stemming from Mandatory Auditor Rotation
Dependent Variable

Independent Variables∆AUD_NAR
UE*∆AUD_NAR∆ADACC
Coeff.
(t-stat)-0.016***(-3.35)∆STD_DD
Coeff.
(t-stat)-0.002*(-1.73)RESTATE
Coeff.
(χ2-stat)-0.873(2.10)

CAR
Coeff.
(t-stat)
0.002(0.96)
0.051**(2.33)
0.029***(2.86)∆SPREAD
Coeff.
(t-stat)-0.193***(-2.80)

Yes
Yes
Yes
No
No
No
1,574
0.143

Yes
Yes
Yes
No
No
No
1,366
0.024

Yes
Yes
Yes
No
No
No
1,599
0.141

Yes
Yes
Yes
Yes
Yes
Yes
1,410
0.063

Yes
Yes
Yes
No
No
No
374
0.131

UE

Control Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2This table reports the OLS and logistic estimation results from changes models. Test statistics are based on standard
errors clustered by client firm. *, **, and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively.
All variables are defined in Table 1.

48

Table 6
Auditor Signature Size Partitioned by Client Audit Quality of the Same Auditor
Partition
Mean AUD_NAR
Test of difference in Mean AUD_NAR:
Paired t-test

Low
9.761

Median AUD_NAR
Test of difference in Median AUD_NAR:
Wilcoxon signed rank test

9.750

ADACC
0.75
(0.455)2532.00(0.335)

STD_DD

High
9.769

Low
9.771

9.774

9.779
9.770
1231.50(0.597)-0.42(0.488)

High
9.766

RESTATE
No
Yes
9.694
9.679
0.33
(0.740)SPREAD
Low
High
9.774
9.797
1.46
(0.145)

9.662

9.795

36.00
(0.708)9.660

1358.50(0.323)

9.821

This table reports mean and median differences in signature size of the same auditor across the high audit quality clients (ADACC are in the lowest tercile, STD_DD are in the lowest
tercile, RESTATE=0, or SPREAD are in the lowest tercile) and low audit quality clients (ADACC are in the highest tercile, STD_DD are in the highest tercile, RESTATE=1, or SPREAD
are in the highest tercile) audited by the same audit partner. The p-values of the mean difference and median difference tests are reported in parentheses.

49

Table 7
Effects of Client Importance, Auditor-Client School Ties, and Audit Complexity
Panel A: Effect of Client ImportanceIndependent Variables
AUD_NAR
AUD_NAR*CL_IMP
CL_IMPUE

ADACC
Coeff.
(t-stat)-0.005**(-2.03)-0.021***(-3.01)0.204***(3.04)

UE*AUD_NAR
UE*AUD_NAR*CL_IMP
UE*CL_IMPControl Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

Yes
Yes
Yes
No
No
No
11,8670.258

Dependent Variable
STD_DDRESTATE
CAR
Coeff.
Coeff.
Coeff.
(t-stat)(χ2-stat)(t-stat)-0.006**-0.0960.003*(-2.02)(0.04)(1.71)-0.013**-2.672***(-2.10)(8.29)
0.132**
26.419***0.002(2.12)(8.60)(1.18)-0.138(-1.34)0.036**(2.02)
0.085*(1.71)-0.423*(-1.66)
Yes
Yes
Yes
No
No
No
10,3350.204

Panel B: Effect of Auditor-Client School Ties

Independent Variables
AUD_NAR
AUD_NAR*TIE
TIE
UE

Yes
Yes
Yes
No
No
No
12,244
0.249

Yes
Yes
Yes
Yes
Yes
Yes
11,252
0.056

Yes
Yes
Yes
No
No
No
3,209
0.497

CAR
Coeff.
(t-stat)0.003*(1.68)SPEARD
Coeff.
(t-stat)-0.117***(-2.60)-0.162**(-2.02)
1.564**(1.98)

Dependent Variable

ADACC
Coeff.
(t-stat)-0.009***(-3.97)-0.008*(-1.75)0.078*(1.76)

STD_DD
Coeff.
(t-stat)-0.008***(-3.09)-0.009**(-2.17)
0.093**(2.18)RESTATE
Coeff.
(χ2-stat)-0.724**(3.17)-2.174**(5.48)
21.325***(5.58)

Yes
Yes
Yes

Yes
Yes
Yes

Yes
Yes
Yes

UE*AUD_NAR
UE*AUD_NAR*TIE
UE*TIE
Control Variables
Industry Fixed Effects
Year Fixed Effects

SPREAD
Coeff.
(t-stat)-0.070(-1.28)-0.259**(-2.21)2.549**(2.21)

50

0.001(0.83)-0.204**(-2.23)0.044***(2.69)
0.071**(2.27)-0.374**(-2.32)
Yes
Yes
Yes

Yes
Yes
Yes

UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

No
No
No
11,8670.258

Panel C: Effect of Number of Segments

Independent Variables
AUD_NAR
AUD_NAR*NSEG
NSEG
UE

ADACC
Coeff.
(t-stat)-0.014***(-3.90)0.006(1.51)-0.063(-1.59)UE*AUD_NAR
UE*AUD_NAR*NSEGUE*NSEG
Control Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

Yes
Yes
Yes
No
No
No
11,8670.258

Panel D: Effect of Inventory and Receivables

Independent Variables
AUD_NAR
AUD_NAR*INVREC
INVRECUE
UE*AUD_NAR
UE*AUD_NAR*INVREC
UE*INVREC

ADACC
Coeff.
(t-stat)-0.024**(-2.41)-0.001(-0.40)0.266**(2.13)

No
No
No
10,335
0.203

No
No
No
12,244
0.247

Yes
Yes
Yes
11,252
0.056

Dependent Variable
STD_DDRESTATE
CAR
Coeff.
Coeff.
Coeff.
(t-stat)(χ2-stat)(t-stat)-0.011***-0.4600.003*(-2.55)(0.68)(1.78)
0.002-0.810(0.52)(1.69)-0.0278.213-0.004***(-0.58)(1.81)(-4.35)-0.321***(-2.80)0.067***(2.99)-0.021(-0.77)0.106(0.76)
Yes
Yes
Yes
No
No
No
10,335
0.205

Yes
Yes
Yes
No
No
No
12,244
0.246

Yes
Yes
Yes
Yes
Yes
Yes
11,2520.058

Dependent Variable
STD_DDRESTATE
CAR
Coeff.
Coeff.
Coeff.
(t-stat)(χ2-stat)(t-stat)****-0.013-1.7670.003*(-2.25)(7.34)(1.67)
0.009
2.249(0.64)(1.74)-0.100-23.591
0.007**(-0.69)(2.00)(2.23)-0.341**(-2.48)0.073***(2.80)-0.055(-0.77)0.278(0.75)
51

No
No
No
3,209
0.497

SPEARD
Coeff.
(t-stat)-0.178**(-2.27)0.013(0.44)-0.118(-0.40)

Yes
Yes
Yes
No
No
No
3,209
0.497

SPEARD
Coeff.
(t-stat)-0.198**(-2.33)0.155(0.81)-1.698(-0.91)

Control Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

Yes
Yes
Yes
No
No
No
11,8670.263

Panel E: Effect of Number of Subsidiaries

Independent Variables
AUD_NAR
AUD_NAR*NSUB
NSUB
UE

ADACC
Coeff.
(t-stat)-0.017***(-3.14)0.003(1.50)-0.034(-1.63)

UE*AUD_NAR
UE*AUD_NAR*NSUBUE*NSUB
Control Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
Number of Observations
Adjusted R2/Pseudo R2

Yes
Yes
Yes
No
No
No
11,867
0.259

Yes
Yes
Yes
No
No
No
10,335
0.204

Yes
Yes
Yes
No
No
No
12,244
0.250

Yes
Yes
Yes
Yes
Yes
Yes
11,252
0.056

Dependent Variable
STD_DDRESTATE
CAR
Coeff.
Coeff.
Coeff.
(t-stat)(χ2-stat)(t-stat)-0.020***-0.5490.003(-3.62)(0.66)(1.61)
0.003-0.249(1.17)(0.67)-0.056**2.469-0.003***(-2.41)(0.69)(-5.32)-0.475***(-2.69)0.096***(2.95)-0.022(-1.43)0.112(1.43)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
No
No
Yes
No
No
Yes
10,335
12,244
11,252
0.206
0.244
0.059

Yes
Yes
Yes
No
No
No
3,209
0.497

SPEARD
Coeff.
(t-stat)-0.146*(-1.71)-0.009(-0.20)0.100(0.23)

Yes
Yes
Yes
No
No
No
3,209
0.497

This table reports the OLS and logistic estimation results. Test statistics are based on standard errors clustered byclient firm. *, **, and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively. CL_IMP is theratio of the client’s total assets divided by the sum of total assets of all clients of the same audit partner in a given
year. TIE is an indicator variable that takes the value of 1 if the lead audit partner and the client CEO, CFO, or board
members went to the same school either as an undergraduate or a graduate student, and 0 otherwise. NSEG is thenatural logarithm of the number of segments that a client firm has. INVREC is the sum of a client firm’s inventories
and account receivables divided by its total assets. NSUB is the natural logarithm of one plus the number ofsubsidiaries. All other variables are defined in Table 1.

52

Table 8
Big Four versus Non-Big Four

Independent Variables
AUD_NAR
AUD_NAR*BIG4
BIG4
UE

ADACC
Coeff.
(t-stat)-0.020***(-3.77)0.012**(2.11)-0.116**(-2.11)

UE*AUD_NAR
UE*AUD_NAR*BIG4
UE*BIG4
Control Variables
Industry Fixed Effects
Year Fixed Effects
UE*Control Variables
UE*Industry Fixed Effects
UE*Year Fixed Effects
H0: AUD_NAR+AUD_NAR*BIG4=0
H0: UE*AUD_NAR+UE*AUD_NAR*BIG4=0
Number of Observations
Adjusted R2/Pseudo R2

Dependent Variable
STD_DDRESTATE
CAR
Coeff.
Coeff.
Coeff.
(t-stat)(χ2-stat)(t-stat)-0.022***-1.779***0.003(-3.80)(10.67)(1.62)
0.016**
1.210*(2.50)(3.03)-0.162**-12.491*0.001(-2.52)(3.39)(1.08)-0.500**(-3.43)0.103***(3.77)-0.065**(-2.06)0.331*(2.02)

Yes
Yes
Yes
No
No
No
-0.008***[0.001]

Yes
Yes
Yes
No
No
No
-0.006***[0.000]

Yes
Yes
Yes
No
No
No
-0.569[0.178]

11,8670.256

10,3350.204

12,244
0.245

Yes
Yes
Yes
Yes
Yes
Yes
0.038**[0.020]
11,252
0.051

SPREAD
Coeff.
(t-stat)-0.348***(-3.67)0.261**(2.39)-2.718**(-2.53)

Yes
Yes
Yes
No
No
No
-0.087**[0.043]
3,209
0.498

This table reports the OLS and logistic estimation results. Test statistics are based on standard errors clustered by client firm. *, **, and*** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively. The p-values for testing AUD_NAR+AUD_NAR*BIG4=0
and UE*AUD_NAR+UE*AUD_NAR*BIG4=0 are reported in brackets. All variables are defined in Table 1.

53

Table 9
Going Concern Tests
Dependent Variable

Independent Variables
Intercept
AUD_NARAUD_SPECAUD_TENURE
AUD_EXPAUD_FEMALE
CPAFIRM_SPEC
CPAFIRM_TENURE
BIG4
SIZE
SALESGROWTH
SALESVOLATILITY
CFO
CFOVOLATILITY
DEBT
LOSS
BANKRUPTCYVOLATILITYMB
AGE
OPERCYCLE
Industry Fixed Effects
Year Fixed Effects
Number of Observations
Pseudo R2

GC
Coeff.
(χ2-stat)
15.475*(3.64)-1.156(2.32)-0.002(0.00)
0.098(1.51)
0.046(2.11)-0.036(0.01)-0.696(1.77)-0.070(2.05)-0.508(1.42)-1.071***(27.12)-0.732*(3.42)
0.674(0.61)-1.462(0.37)-4.770*(3.61)
7.954***(43.31)2.116***(9.25)
0.081(2.45)
6.967***(13.19)0.076(0.59)
0.475(0.93)
0.128(0.51)TYPEI_GCE
Coeff.
(χ2-stat)
26.487***(7.58)-1.469(2.46)-0.214(0.07)
0.061(0.47)
0.056(2.53)-0.049(0.01)-0.948*(2.53)-0.050(0.79)
0.003(0.00)-1.751***(34.02)-0.553(1.62)
0.442(0.21)-1.200(0.20)-4.349(2.48)
8.902***(40.21)2.234**(6.41)
0.116**(5.41)
6.091***(8.08)
0.025(0.05)
0.770(1.67)
0.054(0.07)TYPEII_GCE
Coeff.
(χ2-stat)17.747(0.00)-4.009***(9.33)
0.332(0.11)
0.040(0.15)-0.024(0.21)
0.350(0.27)-1.706*(3.21)-0.075(2.22)-1.314**(4.47)
0.253(1.17)-1.762(2.65)-0.064(0.00)-7.107(2.16)-11.623*(3.21)
2.892(2.56)
2.483**(4.01)-0.137(0.37)-2.895(0.53)-0.421*(2.99)
0.113(0.02)
0.471(1.98)

Yes
Yes
2,550
0.631

Yes
Yes
2,550
0.661

Yes
Yes
2,550
0.495

54

This table reports the logistic estimation results. Test statistics are based on standard errors clustered by client firm. *, **,and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively. GC is an indicator variable thattakes the value 1 if an going concern opinion is issued for a client in financial distress in the year (defined as having
negative operating cash flows in the year), and 0 otherwise. TYPEI_GCE is an indicator variable that takes the value 1 if
a going concern opinion is issued but the client is not going bankruptcy in the following year, and 0 otherwise.
TYPEII_GCE is an indicator variable that takes the value 1 if the client declares bankruptcy within one year of a clean
audit opinion, and 0 otherwise. All other variables are defined in Table 1.

55

Table 10
Auditor Sanction Tests
Dependent Variable

Independent Variables
Intercept
AUD_NAR
AUD_FEMALE
BEGAUDYEAR
BIG4
Number of Observations
Pseudo R2/Adjusted R2

SANCTION_
FREQ
Coeff.
(χ2-stat)-20.100(2.17)-3.861**(3.76)-12.200(0.00)
0.146(2.38)
0.119(0.01)
41
0.233

SANCTION
Coeff.
(χ2-stat)
208.600***(20.39)-1.496**(4.99)-1.496**(5.80)-0.102***(19.72)-0.476(2.36)
566
0.170

SUSPENSION_LENGTH
Coeff.
(t-stat)-59.981(-0.99)-2.110***(-3.49)-1.170***(-3.16)0.036(1.21)
0.268(0.83)
41
0.283This table reports the logistic and OLS estimation results. Test statistics are based on standard errors clustered by clientfirm. *, **, and *** indicate significance (two-tailed) at the 10%, 5%, and 1% levels, respectively. SANCTION is anindicator variable that takes the value of 1 if the audit partner has ever been sanctioned by the regulators, and 0
otherwise. SANCTION_FREQ is the number of times that the audit partner has been sanctioned.
SUSPENSION_LENGTH is the natural logarithm of one plus the number of months the auditor is suspended as a resultof a sanction. The SANCTION regression is estimated with a logit model. The SANCTION_FREQ regression is estimatedwith an ordered logit model. The SUSPENSION_LENGTH model is estimated with OLS. BEGAUDYEAR is the year inwhich the partner begins to sign audit reports. All other variables are defined in Table 1.

56