Audit Firms’ Corporate Social Responsibility Activities and Auditor Reputation

Joshua L. Gunn
jlgunn@katz.pitt.edu
University of Pittsburgh
Chan Li*chanli@ku.edu
University of Kansas
Lin Liao
liaolin@swufe.edu.cn
Southwestern University of Finance and Economics
Center for China’s Governmental Auditing Research
Jinxuan Yangswufeyangjx@smail.swufe.edu.cn
Southwestern University of Finance and Economics
Shan Zhou
shan.zhou@sydney.edu.au
University of Sydney
September, 2019
Abstract
We find that audit firms can build trust and reputational capital in the market place by engaging in
corporate social responsibility (CSR). Audit firms that engage in CSR increase the size of theirclient base, on average, compared to audit firms that do not engage in CSR. The result is robust to
audit firm fixed effects as well as an alternate specification that relies on an exogenous shock tocharitable giving. The effect is stronger for audit firms without existing reputations from a Big 4
brand name or industry specialization. CSR is also associated with higher underlying audit quality
and higher audit fees, suggesting that CSR is reflective of the underlying quality of the audit firm
and is not “greenwashing.”
Acknowledgements: We thank the helpful comments from Clive Lennox, Shivaram Rajgopal,
Roger Simnett, Albert Tsang and workshop participants at University of Sydney, UNSW Sydney,
Southwestern University of Finance and Economics and conference participants at the 2nd Lixin
Accounting Annual Conference.
*Corresponding authorAudit Firms’ Corporate Social Responsibility Activities and Auditor Reputation

1.

Introduction
In this study, we examine whether engaging in corporate social responsibility (CSR) canserve as an effective reputation enhancing mechanism for public accounting firms. Following priorresearch (e.g., Lins, Servaes, and Tamayo 2017), we view CSR as activity that demonstrates “thecommitment of a business to contribute to sustainable economic development, working with
employees, their families, the local community, and society at large to improve the quality of life
(World Business Council for Sustainable Development).” CSR has become a popular tool for
corporations to promote and enhance their reputation. For example, 93% of the world’s largest 250
companies issued a report detailing their CSR activities in 2017, compared to 35% in 1999 (KPMG
2017). Moreover, a large body of literature has documented that CSR helps corporations build
social capital and enhance stakeholder trust (McWilliams and Siegel 2001; Dhaliwal, Li, Tsang,and Yang 2011; Tian, Wang, and Yang 2011; Christensen 2016; Christensen, Hail and Leuz 2019).
CSR can be especially important method for enhancing reputation for companies that
produce credence goods and services—goods and services where buyers make their decisions
based on their trust in the service provider (Flammer 2015; Lins et al. 2017). Auditing has several
features of a credence service. For example, audit firms are experts who recommend the level ofservice that they will provide to buyers, and buyers may have difficulty verifying the auditor’squality of service even after the service has been provided (Causholli and Knechel 2012). As such,
CSR could be an important way for audit firms to build trust and enhance their reputation in themarket place.
Understanding how auditors build reputation and trust is important because auditors’ rolein the capital markets is to certify financial statements, and public trust in auditors’ judgements is2

essential to this function (Harris 2015; Stevens 2017). Prior studies find consistent evidence thatnegative signals of audit quality play a vital role in how investors and clients perceive audit
services (Chaney and Philipich 2002; Krishnamurthy, Zhou, and Zhou 2006; Skinner andSrinivasan 2012; Swanquist and Whited 2015; Qi, Li, Robin, and Yang 2017). These studies
demonstrate that reputation damage has significant consequences to auditors, such as a higher rateof client turnover and reduced audit market share. In contrast, evidence on how auditors build apositive reputation is more limited, primarily focusing on audit firms that have already establishedreputations through either the size of the firm (e.g., Big N versus non-Big N) or industry expertise(DeAngelo 1981; Defond, Wong, and Li 2000; Knechel, Naiker, and Pacheco 2007; DeFond andZhang 2014). However, reputational capital embedded in auditor size and industry specialization
takes considerable time to build and can be very costly to establish. We add to the literature by
investigating an alternative way for audit firms to enhance reputational capital—engaging in CSR
activity. Because serving the public interest is an integral part of the auditing function, we argue
that audit firms’ engagement in CSR demonstrates their genuine concern for the public interest,
and therefore, leads to an increase in public trust and their reputational capital. If this is the case,
we expect to observe a positive association between an audit firm’s CSR activity and growth in
the audit firm’s client base (i.e., an increase in the number of clients served) as the audit firm isable to win new clients and less likely to lose existing clients in a competitive marketplace.
We hand-collect data on audit firms’ CSR activity between from 2008 to 2016. There areseveral advantages to using Chinese data to answer our research question. First, auditors’ litigation
risk in China is low compared to the U.S., which increases the importance of auditors’ reputation
as a motivation for producing high quality audits. Empirically, this allows us to focus on the3relationship between CSR and reputation without the confounding effects of litigation risk. 1
Second, compared to the U.S., the Chinese audit market has relatively low market concentrationand the Big 4 firms have less brand recognition. As a result, there are more audit firms competingfor public clients, which increases the power of our tests and makes it more likely that we will beable to observe an effect of CSR on auditors’ reputation, if it exists. Third, the local branches of
the Chinese Institute of Certified Public Accountants (CICPA) publicly report audit firms’ CSR
activities. Chinese audit firms themselves also disclose their CSR activities, and social media in
China frequently covers CSR activities. 2 This allows us to create a comprehensive dataset of CSR
activity for 408 audit firm-year observations that covers all audit firms in China that audit at least
one public company.
Using our hand-collected data, we create three proxies for the extent of audit firms’ CSR
engagement: (1) a binary variable indicating whether auditors engage in any CSR activities; (2)the number of CSR activities; and (3) the breadth of different types of CSR activities in which theaudit firm engages. 3 After controlling for various audit firm characteristics, we first document that
audit firms’ CSR activities in the prior year are associated with a significantly larger increase in
the number of clients they serve in the subsequent year. This association applies to all three CSR
activity measures. Economically, audit firms that engage in CSR activity experience a 4.7 netincrease in the number of clients they serve compared with audit firms that do not engage in any
CSR activity. To further mitigate the concern that unobserved differences between audit firms
explain our results, we also control for audit firm fixed effects and the results hold.

1

CSR related studies using Chinese data produce results consistent with U.S. studies. For example, Chinese consumers
show a high level of awareness and trust of corporate CSR activity, which leads to more positive images of companies
that engage in CSR activity and a higher likelihood of purchasing goods and services from them (Tian et al. 2011).
2
There are no rules in China that require audit firms to conduct CSR or report their CSR activity to the CICPA.
However, audit firms may voluntarily disclose their CSR activity to the CICPA or on their firms’ own websites. We
acknowledge that if audit firms conduct CSR activities but do not disclose them, we will not include them in our CSR
sample and this will likely to bias against our findings.
3
As discussed in Section 3.1, we categorize CSR activities in four types: Donation, Environment Protection,
Employee Welfare, and Other Activities.

4

Because Big 4 auditors and industry expert auditors have already built their reputations
through other means, we next examine whether the effect of CSR activity on auditor reputation ismore pronounced for non-Big 4 auditors and non-industry expert auditors. We find that the positive
association between CSR and the increase in the number of clients served is more significant for
non-Big 4 firms and non-industry expert auditors, suggesting that audit firms without international
brand recognition and auditors who do not have industry expertise benefit more from engaging in
CSR.
To provide additional evidence of a causal relationship, we exploit the 2013 Ya’an Lushan
Earthquake as a natural experiment because it caused a large, exogenous surge of corporate
donations. Using a differences-in-differences (DID) methodology, we find that audit firms thatengage in new CSR activities after the earthquake experience higher growth in the number ofclients than those without new CSR activities. Since audit firms’ engagement in new CSR activity
initiated after the earthquake is less likely to be endogenously determined, this test provides further
support for our main analysis that CSR is an effective strategy to attract clients and build
reputational capital.
A related question that emerges is whether audit firms’ engagement in CSR is associatedwith the underlying audit quality delivered by the firms. If audit firms’ engagement in CSR showstheir genuine concern in safeguarding public interest as we argue, we should observe that auditors
engaging in CSR deliver higher quality audits. 4 On the other hand, CSR could simply be used as
an impression management tool, an advertising strategy to increase media coverage, or a politicaltactic to manage relationships with the government (Prior, Surroca, and Tribó 2008; Lyon andMaxwell 2011; McWilliams and Siegel 2001; Marquis, Toffel, and Zhou 2016). If this is the case,4

Consistent with this view, prior research finds that corporate CSR is often used as a signalling device for reliability,
trustworthiness, or superior product quality for corporations (McWilliams and Siegel 2001; Elfenbein, Fisman, andMcmanus 2012).

5

we should observe no association between audit firms’ CSR and their underlying audit quality.
Using both modified audit opinions and restatements as proxies for audit quality, we find someevidence that audit firm CSR activity is positively associated with modified audit opinions andnegatively associated with accounting restatements. As prior research finds that an auditor’s
reputation for quality is associated with higher fee premiums (Ferguson, Francis, and Stokes 2003),
we further examine whether clients pay higher audit fees to audit firms that engage in CSR
activities and find confirming evidence. Overall, these results are consistent with the view that
audit firms’ CSR engagement is reflective of the underlying audit quality delivered by the firms,
rather than a “greenwashing” tool.
In additional analysis, we also examine whether auditors engage in CSR activities after areputation damaging event. The results suggest that audit firms are more likely to engage in CSR,
and engage in more and diversified CSR activities, after they are sanctioned by the Chinese
government for audit failures. Moreover, engaging in CSR activities after audit failures leads to alower likelihood of subsequent auditor dismissals. This finding indicates that audit firms may use
CSR to rebuild their reputation after it has been damaged, consistent with research in the corporate
sector that investment in social capital helps repair reputation damage (Chakravarthy, deHaan, andRajgopal 2014; Lins et al. 2017).
Our study makes several important contributions to the literature. First, while a
considerable number of studies in the marketing, management and accounting domain havedocumented a positive effect of corporate CSR activity on consumers’ and investors’ perceptionsof the corporation, whether CSR has a similar effect for audit firms is unknown given the different
nature of the public accounting market and the role that auditing firms play in the capital markets.
Unlike many corporations, audit firms do not generate obvious negative externalities, such aspollution, that CSR can help remedy (Christensen et al. 2019). Thus, the effect of corporate CSR
6may not hold for auditors. We provide robust evidence that auditors’ CSR engagement can also
serve as a reputation enhancing strategy by reinforcing the role of audit firms in safeguarding
public interest, which helps audit firms attract more clients.
Second, although it is well-documented that auditor reputation damage has significant
consequences to auditors, audit firms are not just interested in avoiding negative reputation. They
are also actively engaged in building positive reputations (Brozovsky and Richardson 1998).
Extant literature provides two mechanisms through which audit firms build positive reputation:
brand name and industry specialization. However, these strategies may be too costly to adopt,
especially for small audit firms in a competitive audit market with low supplier concentration. For
example, there are only limited number of large audit firms and investing in the expertise of certain
industries may forgo clients in other industries. We provide evidence that small audit firms andnon-industry expert auditors can use CSR activity to build their reputations.

2.

Literature review and Hypothesis Development

2.1.

CSR as a method for building reputation
Theoretical work has established that civic engagement, activities through which agents

contribute positively to the community and social life (e.g., volunteering, political participation,
donations), can lead to positive outcomes by fostering trust (Carlin, Dorobantu, and Viswanathan
2009; Sapienza, Toldra-Simats, and Zingales 2013). CSR is a type of civic engagement that
promotes shared beliefs and disposition towards cooperation between a company and its
stakeholders, which maps directly to the theoretical foundations of social capital (Lins et al. 2017).
A large body of research supports the view that CSR helps companies build social capital andenhance stakeholder trust.

7

Studies in the marketing and management domain document that CSR has a positive effecton consumers’ perceptions. Marketing survey results suggest that CSR influences consumers’
overall assessment of a company’s reputation (Brown and Dacin 1997), and CSR creates an image
that a company is reliable and honest, characteristics that are typically linked to high quality byconsumers (Flammer 2015; Siegel and Vitaliano 2007). In addition, because attributes such as
quality, reliability, and honesty are important but difficult to determine by search alone, CSR isviewed as an effective differentiation strategy to create new demand or to command a premium
price for an existing product or service (McWilliams and Siegel 2001).
In the accounting literature, CSR disclosures provide value-relevant information
complementary to financial information when evaluating the company. CSR disclosures are found
to attract more analysts and institutional investors and reduce analyst forecast errors, resulting ina reduction in the cost of equity capital (Dhaliwal et al. 2011; Dhaliwal, Radhakrishnan, Tsang,and Yang 2012; El Ghoul, Guedhami, Kwok, and Mishra 2011). Companies’ CSR engagement
also has a positive effect on firm performance as reflected in higher firm value (Matsumura,
Prakash, and Vera-Muñoz 2013; Ferrell, Liang, and Renneboog 2016), higher stock market returns(Flammer 2015; Lys, Naughton, and Wang 2014) and better accounting performance (Lev,
Petrovits, and Radhakrishnan 2010; Flammer 2015).
Prior research also argues that CSR’s effects are more significant for companies offering
credence goods and to relatively new sellers that have limited alternative means of assuring quality(McWilliams and Siegel 2001; Elfenbein et al. 2012). Credence goods and services are those where
the market does not have perfect ex-ante information about quality. Prior studies note that auditing
services have several attributes of credence goods. For example, audit firms are experts in the fieldthat determine the appropriate level of service, labor mix, and total audit hours that are required tomeet professional standards. Client firms may have limited ability to assess the appropriateness of8the audit firm’s conclusion on these issues, and as a result, must place a certain amount of trust in
the audit firm that the audit is performed appropriately. As a result, client firms infer audit quality
information from audit firms’ established reputations (McWillams and Siegel 2001).
Prior literature generally uses auditor size (e.g., Big N versus non-Big N) as a proxy for
positive reputation as larger auditors have more quasi rents at stake and, therefore, stronger
incentives to perform high-quality audits (DeAngelo 1981). Studies have also examined audit
firms’ investment in industry expertise as another differentiation strategy, which helps build up
reputational capital. These studies generally conclude that large auditors and industry expert
auditors are associated with better audit quality and a fee premium (Defond et al. 2000; Casterella,Francis, Lewis, and Walker 2004; Balsam, Krishnan, and Yang 2003; Knechel et al. 2007; Fung,
Gul, and Krishnan 2012; DeFond and Zhang 2014). However, reputational capital embedded in
auditor size and industry specialization takes considerable time to build and can be very costly toestablish. Even though positive reputational capital is difficult to build, economic theories suggestthat in markets with unobserved quality and asymmetric information, sellers benefit from credible
signals of trustworthiness that may substitute for reputation and speed the rate of reputation
development (Milgrom and Roberts 1986; Elfenbein et al. 2012).
The growing awareness towards CSR makes investing in CSR activities a potentially
important reputation enhancing mechanism for audit firms. However, no empirical evidence exists
on the effect of CSR on audit firms. The purpose of this study is to fill this void in the literatureand examine whether audit firms’ engagement in CSR activities serves as an effective reputation
enhancing mechanism. As noted above, CSR can be an effective signal of trustworthiness,particularly for organizations offering credence services such as audit firms that want to enhancetheir reputation, brand, and trust in the market place (Barney 1991; Hart 1995; Porter and Kramer
2011; Russo and Fouts 1997; Flammer 2015; Siegel and Vitaliano 2007). Thus, engaging in CSR
9reinforces the role of audit firms in safeguarding the “public interest”, which is beneficial ingenerating public trust regarding the auditor’s reputation.
If CSR engagement serves as a reputation enhancing mechanism for audit firms, we expect
it will help auditors win new client contracts and reduce the likelihood of losing existing clients,
resulting in a net increase in the number of clients compared to audit firms that do not engage in
CSR. Thus, our first hypothesis is stated in the following alternative form:
H1a: Audit firms engaging in CSR activities experience a larger
subsequent net increase in the number of clients served comparedto audit firms not engaging in CSR activities.
Although there are strong reasons to expect that CSR will help audit firms build a positive
reputation, this is ultimately an empirical question because there are also two arguments for thenull hypothesis. First, because CSR activity is not directly linked to the core business of audit firmsof assuring financial statements, clients and potential clients may not view it as relevant to theauditor’s reputation compared to other observable signals, such as regulator sanctions, audit firmsize, or industry expertise. Second, Becker-Olsen, Cudmore, and Hill (2006) point out that
consumers may perceive CSR as a negative signal if they view it as “greenwash” that companies
only engage in to cover up other misdeeds rather than genuine interest in social or environmental
concerns. These arguments indicate that CSR may not be related to auditors expanding theirclientele base, and thus, the question warrants empirical investigation.
If CSR engagement indeed works as an effective reputation enhancing mechanism for audit
firms, as hypothesized in H1a, the effect should be more pronounced among small audit firms andnon-industry expert auditors as these firms have limited alternative means to build up theirreputation. Hence, we further hypothesize that:
H1b: The positive association between audit firm’s engagement in CSR activities and theincrease in the number of clients is more significant for non-Big 4 audit firms.

10H1c: The positive association between audit firm’s engagement in CSR activities and theincrease in the number of clients is more significant for non-industry expert audit firms.
2.2 Audit firm CSR activity and audit quality
While engagement in CSR activities can potentially be used as an effective reputation
enhancement mechanism for audit firms to attract more clients, it is not clear whether the CSR
activity is reflective of the underlying audit quality that the firm delivers. Prior studies suggest that
corporate’ CSR engagement is associated with less short-term opportunistic behavior fromexecutives (Bénabou, and Tirole 2010). For example, Gao, Lisic, and Zhang (2014) find that
executives of companies that engage in CSR profit significantly less from insider trading and areless likely to trade prior to future news than executives of companies that do not engage in CSR
activities. They conclude that a company's investment in CSR builds a positive image of caring
for social good and imposes additional costs on executives' informed trading, which is widely
perceived as self-serving. Kim, Park, and Wier (2012) show that companies that engage in CSR
are less likely to manage earnings through discretionary accruals, less likely to manipulate real
operating activities, and less likely to be subject to SEC investigations.
Similarly, auditors that engage in CSR activities may be more concerned with the public
interest and care more about society as a whole. Because serving public interest is an integral partof the audit function, auditors engaging in CSR could be more likely to act ethically and conduct
a more rigorous audit that reduces the likelihood that investors are misled by the financial
statements. In this way, engagement in CSR could reflect a high level of underlying audit quality.
These arguments lead to the following hypothesis, stated in alternative form:
H2: The audit quality of audit firms engaging in CSR activities ishigher than the audit quality of audit firms not engaging in CSR
activities.
However, there are important arguments for the null hypothesis ultimately making theassociation between audit firm CSR and audit quality an empirical question. Audit firms could use
11CSR as an impression management tool, an advertising strategy to attract more media coverage,
or a political tactic without any substance or connection to underlying audit quality (Lyon andMaxwell 2011; Marquis et al. 2016). Auditors might pursue a favorable media image and lessscrutiny from the public and government regulators by engaging in CSR. If this is the case, CSR
activities should have no association with audit quality.

2.3 Audit firm CSR activity and audit fees
Economic theory predicts that establishing a positive reputation allows firms to charge ahigher price that can potentially cover the cost of establishing the reputation (Klein and Leffler
1981). Companies that are able to make credible representations of their quality are able to charge
a premium because it increases stakeholders’ confidence in the quality of the company’s goods orservices. Similarly, the auditing literature documents that the reputation of an audit firm, such as
Big N brand name and industry specialization is positively associated with fee premiums (Beatty
1989; Knechel et al. 2007; Fung et al. 2012). If CSR initiatives serve as a reputation-enhancing
strategy and credibly reflect underlying audit quality, auditors should be able to charge higher
audit fees. We state the third hypothesis in the following alternative form:
H3: Audit fees charged by audit firms engaging in CSR activities
are higher than audit fees charged by audit firms not engaging in
CSR activities.
Again, there are arguments for the null hypothesis that there will be no association between
audit firms’ CSR activities and audit fees. CSR may be insufficient to improve an auditor’s
reputation in a meaningful way compared to other observable signals. Further, prior researchsuggests that charging higher prices while investing in CSR can backfire, as it potentially signalsthat the company only invests in CSR for opportunistic reasons (Fosfuri, Giarratana, and Roca
2015; Gneezy, Gneezy, Nelso, and Brown 2010; Xia, Monroe, and Cox 2004). If that is the case,
we may not observe the positive association between audit firm CSR activity and audit fees.
12

3.

Empirical design and Sample Selection

3.1

Empirical Design for test of H1 – Change in number of clients audited
To investigate whether audit firms engaging in CSR experience a larger increase in thenumber of clients (H1a), we estimate the following OLS model:
ΔClient Numbert = β0 + β1AUD_CSRt-1 + β2NonBig4 + β3NonAud_Expi.t-1 +β4 Aud_Sani.t-2,t-1 + β5Client_SIZEt-1 + β6Client_MTBt-1 + Year FE + εi,t(1)

The analysis is conducted at the audit firm level. The dependent variable, △Client Number,is the net change in the number of clients audited, calculated as the number of clients of the audit

firm in year t minus the number of clients in year t-1 for the same audit firm. Thus, △Client Number
can increase when new clients are gained or decrease when existing clients are lost.

Our test variable is audit firms’ CSR activities in year t-1 (AUD_CSRt-1). We use a lagged
measure of CSR because auditor selection decisions are typically made at the beginning of the
fiscal year when only prior year information is available. We use three measures of AUD_CSRt-1.
The first is Aud_CSRt-1, an indicator variable equal to one if an audit firm participates in any CSR
activity in year t-1, and zero otherwise. The second measure is CSR_Numbert-1, which is the log
value of one plus the number of unique CSR activities engaged in by an audit firm in year t-1. Thisvariable intends to capture the extent of audit firm’s CSR engagement so that audit firms thatengage in multiple CSR activities receive a higher value compared to firm’s that only engage in
one or a few CSR activities. The third measure is CSR_Type t-1, which is the number of total
different categories of CSR activities in which an audit firm has participated. This measure intends
to capture the breadth of an audit firm’s CSR activities as firms that engage in a variety of typesof activities might be viewed as having a greater commitment to CSR than firms that are only
involved in one type of activity. We categorize CSR activities into the following four groups: (1)Donation, which includes charitable donations to the community, scholarships to universities, ormonetary commitments to orphanage and aged care homes; (2) Environmental Protection, which13

includes activities related to afforestation, environmental campaigns, or low carbon commuting
and lifestyle; (3) Employee Welfare, which includes investments in occupational health, employee
recreation, amusement and sport, and family planning services or maternity assistance; and (4)Other Activities, which includes activities engaged in blood donation, disabled care, or othercommunity volunteer work. If an audit firm’s CSR engagement serves as a reputation enhancing
strategy that can be used to attract new clients, β1 should be positive in equation (1).
With respect to control variables, we first control for audit firm’s reputation that can affecttheir client retention and new client attraction decisions. NonBig4 is one if the audit firm is not oneof the Big 4 firms. With regard to industry specialization, we first define an audit firm as an expert
if it has a market share based on audit fees greater than 30% in a particular industry in year t-1,
and define NonAud_Exp t-1 as one if the audit firm is not an industry expert in any industry (Reichelt
and Wang 2010). 5 Aud_Sani.t-2,t-1 is the ratio of total number of sanctions against the audit firm
divided by the auditor’s total number of clients during the previous two years. Audit firms
experiencing a negative reputation event, such as a sanction from a regulator, are expected to lose
more clients.
Furthermore, we include several control variables for client characteristics, which weaggregate to the audit firm-year level. Client_Size t-1 equals the median value of the natural log of
total assets across all clients audited by the audit firm in a given year; Client_MTB t-1 is the medianvalue of the market to book ratio across all clients audited by the audit firm in a given year. We
also control for year fixed effects in case there is variation in CSR activities over time during oursample period.
To further mitigate the concern that unobserved audit firm characteristics explain CSR
engagement and client attraction, we also run a separate model by excluding NonBig4 and

5The results remain similar if we use 20% market share cutoff.

14

controlling for audit firm fixed effects. All continuous variables for the audit firm level measures
are winsorized at the top and bottom one percent. Appendix 1 provides detailed variable
descriptions.
H1b and H1c examine whether the positive effect of CSR engagement on client attraction
is more pronounced for Non-Big 4 firms and non-industry expert auditors. We modify model (1)by adding an interaction between CSR and Nonbig4 or NonAud_Exp t-1:
ΔClient Numbert = β0 + β1NonBig4t + β2AUD_CSRt-1 + β3AUD_CSRt-1 * NonBig4t+ β4NonAud_Expi.t-1+β5 Aud_Sani.t-2,t-1 + β6Client_SIZEt-1 + β7Client_MTBt-1 +Year FE + εi,t(2)ΔClient Numbert = β0 + β1NonAud_Expt-1 + β2AUD_CSRt-1 + β3AUD_CSRt-1 * NonAud_Expt-1+ β4NonBig4+β5 Aud_Sani.t-2,t-1 + β6Client_SIZEt-1 + β7Client_MTBt-1 + Year(3)
FE + εi,tConsistent with model (1), the proxy for CSRt-1 is Aud_CSR, CSR_Number and CSR_Type,
respectively. Our variable of interest is the interaction between CSRt-1 and Nonbig4 as well as theinteraction between AUD_CSRt-1 and NonAud_Exp t-1. We expect the interactions to besignificantly positive according to H1b and H1c. The control variables remain the same as Model
(1).
3.2

Empirical design for test of H2 – CSR and Audit Quality
Our next hypothesis examines the association between CSR engagement and audit quality.

We employ the following audit quality model:
Audit_Qualityt = β0 + β1AUD_CSRt + β2Sizet + β3LEVt + β4INVt + β5RECt + β6LIQt+β7CFOt+ β8ROAt + β9BTMt + β10DAt +β11LOSSt +β12INSTSHSt+β13BOARDt+β14INDt+β15SOEt+β16LARGSHSt+β17NonAud_Expertt+β18NonBIG4t+YearFE+IndustryFE+ εi,t(4)
Since the dependent variable in equation (4) is measured at the client-year level (as opposed to theaudit firm-year level in equations (1) to (3)), we also estimate the right-hand variables in equation(4) at the client-year level. Because the amount of assurance provided by auditors cannot be
explicitly observed by market participants (Defond and Zhang, 2014; He, Pan, and Tian 2017), we
15

use two common proxies for audit quality. The first proxy is modified audit opinion (MOA), which
is an indicator variable equal to one if an auditor issues a modified financial statement opinion inyear t, and zero otherwise. The second measure is client restatement (Restatement), an indicatorvariable equal to one if a client’s financial statements in year t are ultimately restated, and zerootherwise. The client restatement data is obtained from the DIB Internal Control and Risk
Management Database. As the dependent variables FMOA and Restatement are dichotomous, weestimate logistic regressions for equation (4). We control for year and client industry fixed effects(a lack of variation in the dichotomous dependent variables prevents us from using client fixed
effects as we do in the audit fee model below). The variable of interest is audit firm CSR activity(AUD_CSRt) in year t. If audit firms that engage in CSR have higher audit quality than non-CSR
audit firms, we expect the coefficient on AUD_CSRt to be significantly positive in the MOA modeland significantly negative in the Restatement model.
3.3

Empirical design for test of H3 – CSR and Audit Fees
We test H3 with the following audit fee model:
Audit_Feet = β0 + β1AUD_CSRt + β2Sizet + β3LEVt + β4INVt + β5RECt + β6LIQt+β7CFOt+ β8ROAt + β9BTMt + β10DAt +β11LOSSt +β12INSTSHSt+β13BOARDt +β14INDt +β15SOEt +β16LARGSHSt + β17FMOAt+β18NonAud-Expertt+ β19NonBIG4t +Year FE + Client Firm FE + εi,t(5)The dependent variable Audit_Feet is the natural logarithm of audit fees for client i in year
t. Similar to equation (4), we estimate the right-hand variables in equation (5) at the client-yearlevel. The variable of interest, AUD_CSRt, is the same three CSR measures described above. If
CSR activities reflect higher audit quality, audit firms should be able to charge a price premium.
Thus, we expect β1 to be significantly positive in equation (5). Control variables are included
following prior audit fee studies (Simunic 1980; Hay, Knechel, and Wong 2006; Boone, Khurana,and Raman 2015; Huang, Raghunandan, Huang, and Chiou 2015) and are defined in Appendix 1.
We include year fixed effects. In addition, because equation (5) is estimated at the client-level and16audit fee is a continuous variable, we estimate equation (5) using OLS and control for client fixed
effects to account for the time-invariant unobservable client characteristics. All continuous
variables for the client level measures are winsorized at the top and bottom one percent.
3.5

Sample Selection and Descriptive Statistics
We utilize the audit firm CSR data in China to investigate our hypotheses. Audit firms’

CSR activities are publicly reported by audit firms, the local branches of the Chinese Institute ofCertified Public Accountants (CICPA), and social media. In order to conduct our empiricalanalyses, we focus on audit firms that have public clients so we can observe client financial data. 6
There are a total of 408 audit firm-year observations from 2008 to 2016. We manually collect the
CSR data from the audit firms’ websites, the local CICPA websites, and using the online searchengine Baidu.com to search news media coverage of audit firms’ CSR activities during our sample
period. We count the number of unique CSR activities reported from these sources to calculate ourcontinuous measure of CSR (CSR_Number). For each CSR activity identified, we read thedisclosure and classify it into one of four categories: Donation, Environment Protection, Employee
Welfare and Others as described earlier. We then count the number of different categories for our
measure of CSR breadth (CSR_Type).
Table 1 presents the number and percentage of audit firms participating in CSR activities
by year. On average, 27.5% of audit firms engage in at least one CSR activity in a given year. Out
of audit firms that engaged in at least one CSR activity, the average number of CSR activities is7.84, with a minimum value of one and a maximum value of 93. Because this variable is highly
skewed, we take the log transformation for CSR_Number t-1. Audit firms participate in, on average,

6

According to the regulation released by Ministry of Finance on June 10, 2000, an audit firm that is able to obtain theservice license to serve listed clients must be established for at least three years, with capital of no less than 2 million
RMB for a limited liability firm and 1 million RMB for partnerships with revenues of at least 8 million RMB in theprevious year. In addition, the audit firm must have at least 20 CPAs and at least 40 CPAs under the age 60 (MOF,
Regulation 56 2000).

17

two types of CSR activities a year. The most frequent type of CSR activity is Donation,
representing 83.9% of all CSR activities.
<Insert Table 1 here>
Client financial data are obtained from the China Stock Market Trading Database(CSMAR). We start with all publicly listed Chinese firms on the Shanghai and Shenzhen
exchanges over the sample period 2008-2016. The initial sample consists of 21,358 client-year
observations. This sample is used to construct the client portfolio data at the audit firm level.
For client-level analyses on audit quality and audit fees, consistent with prior literature(Huang et al. 2015; He et al. 2017; Li, Qi, Tian, and Zhang 2017), we delete 381 financial
institutions, 803 special treatment companies and 5,680 observations with missing values. This
results in a final sample of 14,494 client-year observations. Table 2 details the sample attrition
process.
<Insert Table 2 here>
Table 3 presents the descriptive statistics for the audit firm-year variables used in equation(1) separately for audit firms that engage in CSR activities (Aud_CSRt-1 = 1) compared to thosethat do not engage in CSR activities (Aud_CSRt-1 = 0). The dependent variables (△Client Number)and the clientele control variables are audit firm level change variables from year t-1 to year t,which reduces the sample size to 344 (compared to 408 in Table 1). Table 3 presents preliminary
univariate evidence supporting H1, as audit firms that engage in CSR activity experienced anaverage increase in the number of clients of 7.58, compared 4.32 for audit firms that do not engage
in CSR, and the difference in means is statistically significant at the p<0.01 level. Big 4 andindustry expert audit firms are more likely to engage in CSR activity, which reinforces our needto include audit firm fixed effects in our multivariate analyses since audit firm type is correlatedwith CSR activity.
18

<Insert Table 3 here>

4.

Regression Results

4.1

Auditor CSR and audit clientele base growth
Table 4 presents the regression results for equation (1) using the 344 audit firm-year

observations described in Table 3. There is a separate column for each of our three measures ofaudit firms’ CSR engagement: Aud_CSRt-1, CSR_Number t-1 and CSR_Type t-1. Column (1) showsthat the coefficient on Aud_CSRt-1 is significantly positive (p-value=0.006), suggesting thatcompared to audit firms without CSR activities in the prior year, those engaging in CSR activities
experience a significantly larger increase in the number of clients in the subsequent year.
Economically, audit firms gain 4.7 more clients if they engage in CSR activities in the prior year
compared to audit firms that did not engage in CSR in the prior year. This effect is significant
considering the average value of change in client number for an audit firm is 5, so CSR audit firms
added twice as many clients as non-CSR audit firms on average. Column (2) shows that thecoefficient on CSR_Numbert-1 is significantly positive (p-value=0.053), suggesting that the
number of CSR activities also has a positive effect on the change in the number of clients for theaudit firm. Finally, Column (3) presents the result for CSR breadth. The significantly positivecoefficient on CSR_Typet-1 (p-value=0.008) indicates that the more variety of CSR activities theaudit firm engages in year t-1, the larger increase in the client numbers in year t. This is consistent
with clients appreciating audit firms’ multi-dimensional CSR strategies.
In untabulated tests, we also separately examine the number of new clients gained and thenumber of existing client lost for the audit firm in year t. Consistent with the reputation effect of
CSR activities, we find that when audit firms engage in CSR activities in year t-1, they gain19

significantly more new clients as well as experience significantly fewer losses on the existingclients in the subsequent year, and these results hold for all three CSR measures.
With respect to control variables, we find non-Big4 firms and industry specialists gain
more clients. Additionally, the coefficient on Aud_San is negatively significant, suggesting that
audit firms that have more sanctions in the prior two years experience a net reduction in the numberof clients, all else equal. The coefficients on Client_MTB are also significantly negative.
The right-hand columns report results after controlling for audit firm fixed effects andexcluding NonBig4 (which does not vary within audit firms and is therefore subsumed by the fixed
effects). The results for our CSR variables still hold, providing evidence that our results are notdriven by unobserved audit firm characteristics. When audit firm fixed effects are included in themodel, none of the control variables is significant, suggesting that audit firm fixed effects absorb
much of the heterogeneity across audit firms. Taken together, the results in Table 4 demonstratethat audit firms’ CSR engagement is associated with a net increase in the number of clients servedby the audit firm. This supports our first hypothesis that CSR helps audit firms build reputationand trust, and thus, attracting relatively more clients.
<Insert Table 4 here>
4.2 Exogenous shock to auditor CSR and client base growth
One concern is that CSR activity and audit firm attributes are endogenously determined.
For instance, better audit firms or audit firms with more social capital are more likely to engage in
CSR activity, and these firms are also good at attracting clients. Although we find our results inTable 4 are robust to audit firm fixed effects, there could still be a concern that some unobserved
factor within audit firms correlates over time with CSR and audit quality. In this section, we further
address this issue with a difference-in-difference research design that exploits the exogenous shockof the 2013 Ya’an Lushan Earthquake. On April 20th, 2013, a serious earthquake with 7.0
20magnitude occurred at Ya’an Lushan in China. This earthquake resulted in 196 deaths and 11,470
people injured. We utilize the earthquake as an exogenous shock to audit firm’s incentive to engage
in CSR, as the equilibrium of cost-benefit analyses to engage in CSR during normal times is
disrupted during such a disastrous time. Therefore, audit firms’ decision to engage in CSR after
the earthquake is less likely to be endogenously determined.
We apply the differences-in-differences (DID) methodology and identify treatment audit
firms to be those that only engage in CSR after the earthquake and the control audit firms to be
those that do not engage in CSR before or after the earthquake. The DID regression model we use
is as follows:
ΔClient Numbert = β0 + β1Treatment +β2Post +β3Treatment*Post +β4NonBig4+β5NonAud_Expi.t-1+β6 Aud_Sani.t-2,t-1 + β7Client_SIZEt-1 + β8Client_MTBt-1 +Year FE + εi,t(6)Where Treatment is a dummy variable indicating the audit firm has only engaged in CSR after
the earthquake. We delete audit firms that engage in CSR both before (year 2012) and after theearthquake (year 2013) (12 observations), those that engage in CSR only in year 2012 before theearthquake (2 observations), and observations that do not exist in both years (11 observations).
Thus, the comparison group is the audit firms that do not engage in CSR activities in both pre andpost the earthquake. Post equals one if the year is 2013. The coefficient of interest is β3, which
captures whether this is a net gain in client number for audit firms with CSR activities after theearthquake. The final sample is 60 audit firm-year observations in 2012 and 2013. The empiricalresult is reported in Table 5.
<Insert Table 5 here>
Table 5 shows that the interaction is positively significant at the 1% level (p value=0.009),
suggesting that audit firms having CSR activities after the earthquake experience a significantly
larger increase in the number of clients than those without CSR engagement. Since engagement in
21

CSR for this group of audit firms is less likely to be endogenously determined after the earthquake,
this test provides additional support for a causal interpretation that CSR increases audit firms’
reputational capital, which in turn leads to attracting and retaining more clients.
4.3

Auditor CSR and change in client number for small audit firms and non-industry expert
auditors
We find CSR engagement works as an effective reputation enhancing mechanism for audit

firms as hypothesized in H1a. In H1b and H1c, we predict that this effect should be more
pronounced among non-Big 4 audit firms and non-industry experts, as these firms have limited
resources and strategies to compete against large international audit firms or industry expert firms. 7
The results are presented in Table 6. In Panel A, we find that the coefficient on theinteraction between Nonbig4 and each of the CSR engagement variables (Aud_CSR, CSR_Number
and CSR_Type) is significantly positive (p-value=0.014, 0.001 and 0.001, respectively). These
results provide support that CSR is a more effective brand-enhancing strategy for small audit firms
compared to large, international Big 4 audit firms. The coefficients on the CSR engagement
variables are not significant, indicating CSR activities do not enhance Big 4 auditors’ ability toincrease the number of clients.
<Insert Table 6 here>
Table 6 Panel B reports the results for CSR activities and non-industry expert audit firms.
We find that the coefficients on the interaction between NonAud_Exp and CSR_Number as well as
CSR_Type are significantly positive (p-value=0.001 and 0.088, respectively), suggesting thatengagement in more CSR activities and more diversified CSR activities helps non-industry expert
audit firms attract and retain clients.

7

The results remain similar if we use Big 6 accounting firms in China, which are PricewaterhouseCoopers, Deloitte,
Ernst & Young, KPMG, Lixin and Ruihua. Specifically, the coefficient on the interaction between Nonbig6 and eachof the CSR engagement variables (Aud_CSR, CSR_Number and CSR_Type) is significantly positive with pvalue=0.013, 0.000 and 0.006, respectively.

22

4.4

Auditor CSR and Audit Quality
H2 tests whether audit firms engaging in CSR have higher audit quality. As discussed

previously, we use FMOA and Restatement as proxies for audit quality. The analyses are conductedat the client-year level. Table 7 presents the descriptive statistics for our client-year regressions forboth CSR auditors and non-CSR auditors. It shows that the clients audited by auditors engaging in
CSR in year t are more likely to restate their financial statements (Restatement) and pay higher
audit fees (Aud_Feet). Clients of CSR auditors are also larger, have fewer inventory but more
receivables, have larger book to market ratio, have more shares held by the largest shareholders,
are more likely to be Big 4 and industry expert audit firm clients. Because many of these client
characteristics affect audit fees and audit quality as well, we draw our conclusions frommultivariate analyses after controlling for these variables.
<Insert Table 7 here>
The regression results for H2 are reported in Table 8. 8 Column (1) in Table 8 shows thatthe coefficient on Aud_CSRt is positively significant (p-value =0.065), suggesting that audit firmsthat participate in CSR activity are more likely to issue modified audit opinions in year t.
Economically, CSR auditors are 0.7 percent more likely to issue modified audit opinions, which
represents a 24% increase in the mean likelihood of modified audit opinions. Additionally, thecoefficients on CSR_Numbert and CSR_Typet are also positively significant (p-value=0.050 and
0.034, respectively). With respect to Restatement, we find in column (4) that the coefficient on
Aud_CSRt is negative but statistically insignificant (p-value =0.444). Columns (5) and (6) showthat CSR_Numbert and CSR_Typet are negatively and significantly associated with Restatement(p-value=0.069 and 0.024, respectively), which suggests that client companies are less likely to

8

The number of observations is reduced to 14,428 when FMOA is used as the dependent variable (column 1 to 3)
because there is no variation in FMOA in the Scientific Research and Technology Service industry, which has 66
observations and these observations are dropped out from the analyses.

23restate their financial statements when they are audited by audit firms that engage in more unique
CSR activities and a broader variety of CSR activity types. Overall, the results presented in Table
8 provide some evidence that audit firms engaging in CSR deliver higher audit quality, as
evidenced by the tendency to issue more modified audit opinions and the lower likelihood of clientcompanies restating their financial statements.
<Insert Table 8 here>
4.5

Auditor CSR and Audit Fees
Table 9 presents the regression results for H3 that examine whether audit firms engaging

in CSR charge higher audit fees. Columns (1) to (3) show that the coefficients on Aud_CSRt,
CSR_Numbert, and CSR_Typet are all significantly positive (p-values = 0.052, 0.010, and 0.002,
respectively). The results suggest that audit firms with a higher number of CSR activities and morediversified activities charge significantly higher audit fees, consistent with audit firms that engage
in CSR having a higher reputation for quality.
<Insert Table 9 here>

5. Additional Analyses
5.1 CSR as a mechanism to rebuild a damaged reputation
Previous studies on auditor reputation have mostly focused on damage to an auditor’s
reputation. These studies find consistent evidence across a number of countries that the market
place punishes auditors who are involved in reputation damaging events (Chaney and Philipich
2002; Krishnamurthy et al. 2006; Skinner and Srinivasan 2012; Swanquist and Whited 2015; He,
Pittman, and Ruui 2016). While these studies demonstrate that auditor reputation damage hassignificant consequences to auditors, there is scarce evidence on what audit firms can do to repair
their reputation after it has been tarnished. As noted by Brozovsky and Richardson (1998), “firms
24are not merely interested in avoiding negative reputation … but are actively engaged in pursuinga positive one. A positive reputation may be inherently different from the absence of a negative
one.” (p768). 9
We posit that CSR could be an effective way for audit firms to rebuild their reputation after
it has been tarnished. Previous research on corporate CSR activities supports this view. For
example, Chakravarthy et al. (2014) find that reputation-repairing actions directed toward thecompany’s customers, employees, and communities generate positive abnormal returns andimprove investors’ perception about the company’s financial reporting credibility after a scandal
such as a serious accounting restatement. Christensen (2016) documents that companies that report
CSR activities experience a less negative stock price reaction following high-profile misconduct.
Lins et al. (2017) find companies that are involved in CSR activities experience higher stock
returns, profitability, growth, and sales per employee relative to companies that engage in low CSR
activities during the 2008-2009 financial crisis. This suggests that the trust between a company
and its stakeholders built through investments in CSR initiatives pays off when the overall levelof trust suffers a negative shock.
To test this conjecture, following Dhaliwal et al. (2011), we estimate the following lead-lag
model:
CSRt = β0 + β1AUD_SANt-1 +β2NonBig4 +β3NonAud_Expt-1+ β4Client_SIZEt-1+β5Client_MTBt-1 + Year FE + εi,t(7)where the dependent variable CSRt measures audit firms’ CSR engagement in year t. It includes
three variables as discussed above, Aud_CSR, CSR_Number and CSR_Type. The variable ofinterest is in this analysis is AUD_SANt-1, which is an indicator variable equal to one if the audit
firm has been sanctioned in year t-1. We measure reputation damage using sanctions issued by the9Using an experiment, Brozovsky and Richardson (1998) find evidence that auditors’ investment to establish positive
reputations via the purchase of non-salvageable productive assets (e.g. training) leads to more client contracts.

25

government regulator in China – the China Securities Regulatory Commission (CSRC) to audit
firms for audit failures. 10 Prior studies find that government sanctions to audit firms causes severe
reputation damage for those firms in China (Qi et al. 2017; Fung, Jiang, and Raman 2018). We
predict β1 in equation (6) will be positive. We manually collect data on audit firm sanctions fromgovernment websites during the same sample period 2008-2016. 11 Other control variables are as
defined in in the description of equation (1) and are measured at the end of year t-1.
Table 10 Panel A presents the regression results of estimating model (6). The coefficient on
AUD_SANt-1 is positive and significant in column (1) (p-value=0.006), indicating that audit firms
are significantly more likely to engage in CSR activities after they are sanctioned by thegovernment due to an audit failure. Columns (2) and (3) present OLS results with CSR_Numbertand CSR_Typet as dependent variables and with the control for audit firm fixed effects. We
continue to find positive and statistically significant coefficients (p-value=0.023 and 0.002,
respectively). Thus, audit firms appear to engage in more CSR activities and a larger variety of
CSR activities to rebuild their reputation after they suffer reputation damage from government
sanctions due to an audit failure.
<Insert Table 10 here>
Because prior studies find clients are more likely to dismiss auditors after an audit failure(e.g. Skinner and Srinivasan 2012; Swanquist and Whited 2015), we further test whether CSR
activities can help reduce the negative impact of an audit failure by estimating the following
logistic regression model:

10

Lawsuits against auditors are rare in China (Firth, Phyllis, Mo, and Wong 2005; Lisic, Silveri, Song, and Wang2015). Instead, CSRC plays a significant role in the oversight of capital market participants, including publicly listed
firms, investors, security service firms and auditors. The CSRC enforces sanctions against audit firms if they fail todetect the clients’ fraudulent financial reporting, fail to comply with audit standards, gather insufficient audit evidence,omit necessary and sufficient audit procedures, or engage in collusion with the client to commit fraud. The
punishments for auditor sanctions include a warning, monetary fine, or suspension or termination of the auditor’s
service license (Firth et al. 2005; Sun, Cahan, and Xu 2016)11
See http://www.csrc.gov.cn/pub/zjhpublic/index.htm?channel=3300/3313

26

Dismisst = β0 + β1AUD_Sanctiont-1 +β2AUD_CSRt+β3AUD_Sanctiont-1* AUD_CSRt +β4Sizet + β5LEVt + β6INVt + β7RECt + β8LIQt +β9CFOt+ β10ROAt+β11BTMt+β12DAt+β13LOSSt+β14INSTSHSt+β15BOARDt+β16INDt++β17SOEt+β18LARGSHSt+β19NonAud_Expertt+β20NonBIG4t+YearFE+IndustryFE +
(8)
εi,t

Table 10 Panel B presents the results of the likelihood of auditor dismissals after the audit
firm has been sanctioned by the government. The coefficient on Aud_Sanctiont-1 is significantly
positive, which is consistent with prior literature that clients are more likely to dismiss theirauditors after an audit failure. More importantly, the interactions between Aud_Sanctiont-1 and all
three CSR measures are negative and significant, which provides support that engaging in CSR
activities after an audit failure event can actually help reduce the likelihood of auditor dismissals.
Taken together, these results suggest that auditors are more likely to engage in CSR
activities after a reputation damaging event, and these CSR engagements seem to be an effective
way to reduce the negative impact of the event and rebuild auditors’ reputation.
5.2 New Client characteristics and CSR audit firm
Our main analyses reveal that audit firms engaging in CSR activities attract more clients.
In this section, we explore the type of firms that are more likely to hire CSR auditors. To do so,
we restrict our sample to new clients and perform logistic regressions to see what the client
characteristics are that are associated with hiring audit firms that engage in CSR activities in theprior year. The untabulated results show that new clients of CSR audit firms are more likely to befrom environmentally sensitive industries, such as mining, transportation, water conservancy andenvironmental protection. This suggests that clients from the environmentally sensitive industries
especially value auditors’ CSR initiatives. State Owned Enterprises (SOE) clients are also more
likely to hire audit firms with CSR activities, which is consistent with previous studies that CSR
could work as a relationship cultivation mechanism with local government authorities to ease27

access to sociopolitical legitimacy and resources (Zhang, Rezaee, and Zhu 2010; Wang and Qian
2011; Gao, Farr, and Navissi, 2012).

6.

Conclusion
A large body of literature has documented that CSR helps corporations build social capitaland enhance stakeholder trust, as a result, CSR activity has become a popular and powerful tool topromote reputation for corporations, especially for those providing credence goods where themarket does not have perfect ex-ante quality information (McWilliams and Siegel 2001; Dhaliwal
et al. 2011; Tian et al. 2011; Christensen 2016). However, there is no evidence on whether CSR
can build reputation and trust, and signal quality for public accounting firms. Using hand-collected
audit firm CSR activity data in China, we empirically examine this issue. We first document that
audit firms’ CSR activity in the prior year leads to a significantly larger increase in the number ofclients in the subsequent year, and this effect is mainly driven by smaller accounting firms andnon-industry expert audit firms, which have limited alternative means to build up reputation.
We next examine whether auditors engaging in CSR activities are associated with higher
audit quality, and find some supporting evidence. Finally, we document that auditors enhancing
reputation through CSR engagement are able to charge higher audit fees. In additional analysis,
we also find that audit firms are more likely to engage in CSR activities to rebuild their reputation
after suffering reputation damage because of Chinese government sanctions, and engagement in
CSR helps to reduce the negative impact (i.e., client dismissal) from the damage. Our study
provides initial evidence that auditors’ CSR engagement could serve as a reputation enhancing
strategy, especially for smaller audit firms and non-industry expert audit firms, and should have
implications to public accounting firms, client companies and investors.

28

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32

Table 1 Descriptive Statistics on Auditor CSR Activities
Panel A: Year distribution
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
Total

CSR Audit Firms
19
6
11
8
9
17
15
14
13
112

Percentage
35.849%11.765%22.000%16.327%20.000%42.500%37.500%35.000%32.500%27.451%

non-CSR Audit Firms
34
45
39
41
36
23
25
26
27
296

Percentage
64.151%88.235%78.000%83.673%80.000%57.500%62.500%65.000%67.500%72.549%

Total
53
51
50
49
45
40
40
40
40
408

Panel B Auditor CSR activities
Variables
AUD_CSR
CSR_Number*
CSR_Type
Donation
Environmental Protection
Employee Welfare
Other Activities

N
408
112
112
112
112
112
112

mean
0.275
7.839
1.741
0.839
0.330
0.098
0.473

p50
0
2
1
1
1
0
0

sd
0.447
15.514
0.898
0.369
0.472
0.299
0.502

min
0
1
1
0
0
0
0

max
1
93
4
1
1
1
1

*for CSR number and CSR types, descriptive statistics are only presented for the 112 firms that engaged
in at least one CSR activity.

Table 2 Sample Attrition for Client Year Analyses
All observations from 2008 to 2016
Delete:Financial institutions
Special Treatment firms
Observations with missing values for control variables
Final Sample

33

21,358
381
803
5,680
14,494

Table 3 Descriptive Statistics
Descriptive statistics for the audit firm-year variables used in model.

Variables△Client Number
Nonbig4
NonAud_Exp t-1
Aud_San t-2, t-1
Client_Size t-1
Client_MTB t-1

Aud_CSRt-1 = 1
N
Mean
96
7.583
96
0.740
96
0.750
96
0.782
96
22.348
96
0.948

34

Aud_CSRt-1 = 0
N
Mean
248
4.315
248
0.972
248
0.931
248
0.798
248
21.618248
0.702

MeanDiff3.269***-0.232***-0.181***-0.016
0.731***
0.246***

Table 4 Auditor CSR Activity and Change in Clientele portfolio size+/-

AUD_CSR t-1+

CSR_Number t-1+

CSR_Type t-1+

NonBig4
NonAud_Exp t-1
Aud_San t-2, t-1
Client_Size t-1
Client_MTB t-1
Constant
Year FE
Audit Firm FE
Nadj. R2(1)△Client(2)△Client(3)△Client(4)△Client(5)△Client(6)△Client

Number4.735***(2.545)

NumberNumberNumber4.200***(2.377)

NumberNumber

1.768*(1.622)
15.637***(3.641)-14.868***(-4.038)-0.505**(-1.991)
1.706(1.371)-5.341**(-2.459)-29.265(-1.067)
Yes
No
344
0.162

16.686***(3.456)-14.842***(-3.898)-0.436*(-1.805)
1.709(1.359)-5.176**(-2.368)-29.524(-1.063)
Yes
No
344
0.144

1.753*(1.429)2.386***(2.419)17.085***(3.754)-14.103***(-3.792)-0.494**(-2.009)
1.776(1.397)-5.307**(-2.470)-32.282(-1.148)
Yes
No
344
0.156

1.952**(1.743)-3.652(-0.993)
0.284(0.814)1.554(0.963)-2.195(-1.001)-28.570(-0.862)
Yes
Yes
344
0.424

-3.735(-1.010)0.314(0.910)1.635(1.028)-2.226(-1.037)-29.680(-0.908)
Yes
Yes
344
0.414

-3.207(-0.889)
0.284(0.817)1.577(0.963)-2.049(-0.932)-29.264(-0.873)
Yes
Yes
344
0.419

The dependent variable in the three columns, △Client Number, is the change in client number. AUD_CSR t-1 equals
one if the audit firm engaged in CSR in year t-1; CSR_Number t-1 is the natural log of the number of CSR activities
engaged by an audit firm in year t-1; CSR_Type t-1 is the number of CSR categories engaged by an audit firm inyear t-1. See Appendix 1 for other variable definition. Robust t statistics in parentheses. * p < 0.1, ** p < 0.05, ***p < 0.01. One-tailed p is for signed expectations and two-tailed p is for unsigned expectations.

35

Table 5 Exogenous Shock – 2013 Ya’an Lushan Earthquake△Client Number-2.141(-0.987)-4.682**(-2.505)
6.599***(2.450)9.200***(4.637)-19.425**(-2.386)
9.054(0.236)
0.258*(1.803)0.297(0.095)8.345(0.827)
60
0.374

Treat
Post
Treat*Post+

Nonbig4
NonAud_Exp t-1
Aud_San t-2, t-1
Client_Size t-1
Client_MTB t-1
Constant
Observations
Adj. R2

Treat equals one if the audit firm engaged in CSR in year 2013 and zero otherwise; Post equals one if the year is2013 and zero otherwise. See Appendix 1 for other variable definition. Robust z and t statistics in parentheses. * p< 0.1, ** p < 0.05, *** p < 0.01. One-tailed p is for signed expectations and two-tailed p is for unsigned expectations.

36

Table 6 Interactions between CSR and Audit Firm Characteristics
Panel A Interaction between CSR and non-Big 4 audit firms

NonBig4t
AUD_CSR t-1
AUD_CSR t-1* NonBig4 t+(1)△Client Number
8.318*(1.787)-4.124(-1.026)
9.686**(2.224)

CSR_Numt-1
CSR_Numt-1* NonBig4t(2)△Client Number
7.468*(1.728)-1.785(-1.484)
6.182***(3.336)+

CSR_Typet-1
CSR_Typet-1* NonBig4t
NonAud_Exp t-1
Aud_San t-2, t-1
Client_Size t-1
Client_MTB t-1
Constant
Year FE
N
Adj. R2(3)△Client Number
5.709(1.297)+-15.257***(-4.127)-0.522**(-2.074)
1.342(1.115)-4.383**(-2.125)-15.290(-0.572)
Yes
344
0.168

-15.162***(-4.024)-0.523**(-2.148)
1.168(0.976)-3.798*(-1.889)-11.104(-0.417)
Yes
344
0.167

-2.442(-1.604)
6.213***(3.372)-14.947***(-3.976)-0.546**(-2.235)1.010(0.845)-3.690*(-1.845)-6.222(-0.233)
Yes
344
0.180

The dependent variable, △Client Number, is the change in client number. AUD_CSR t-1 equals one if the audit firm
engaged in CSR in year t-1; CSR_Number t-1 is the natural log of the number of CSR activities engaged by an audit
firm in year t-1; CSR_Type t-1 is the number of CSR categories engaged by an audit firm in year t-1. NonBig4
equals one if the audit firm is a non-big4, and zero otherwise. See Appendix 1 for other variable definition. Robustt statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. One-tailed p is for signed expectations and twotailed p is for unsigned expectations.

37

Table 6 (continued)
Panel B Interaction between CSR and Non-Industry Expert

NonAud_Exp t-1-

AUD_CSR t-1
AUD_CSR t-1* NonAud_Exp t-1

+

(1)

(2)

(3)

△Client Number△Client△Client Number

Number
-19.429***(-4.324)-17.105***(-3.760)-14.909***(-3.527)4.656(0.736)0.090(0.014)

CSR_Numt-1
CSR_Numt-1* NonAud_Exp t-1-1.316(-0.861)5.242***(3.357)+

CSR_Typet-1
CSR_Typet-1* NonAud_Exp t-1
NonBig4
Aud_San t-2, t-1
Client_Size t-1
Client_MTB t-1
Constant
Year FE
N
Adj. R2+
15.614***(3.238)-0.505**(-1.981)1.702(1.349)-5.335**(-2.413)-29.134(-1.015)
Yes
344
0.159

13.915***(3.020)-0.502**(-2.038)
0.983(0.810)-4.155*(-1.954)-8.880(-0.329)
Yes
344
0.169

0.379
(0.170)2.971*(1.358)15.444***(3.150)-0.522**(-2.103)
1.461(1.145)-4.790**(-2.192)-22.057(-0.759)
Yes
344
0.163

The dependent variable, △Client Number, is the change in client number. AUD_CSR t-1 equals one if theaudit firm engaged in CSR in year t-1; CSR_Number t-1 is the natural log of the number of CSR activities
engaged by an audit firm in year t-1; CSR_Type t-1 is the number of CSR categories engaged by an audit firmin year t-1. NonAud_Exp t-1 equals one if the audit firm is not an industry expert, and zero otherwise. See
Appendix 1 for other variable definition. Robust t statistics in parentheses. * p < 0.1, ** p < 0.05, *** p <0.01. One-tailed p is for signed expectations and two-tailed p is for unsigned expectations.

38

Table 7 Descriptive Statistics for client firm-year variables for audit fee and audit quality
analyses
Variables
Audit_Feet
FMOAt
Restatementt

Sizet
LEVt
INVt
RECt
LIQt
CFOt
ROAt
BTMt

DAt
LOSSt
INSTSHSt
BOARDtINDt
SOEt
LARGSHSt
NonAud_Expert
NonBIG4t

CSR Audit Firms
N
Mean
5656
13.615
5656
0.025
5656
0.198
5656
22.208
5656
0.443
5656
0.153
5656
0.114
5656
2.414
5656
0.044
5656
0.039
5656
0.913
5656
0.443
5656
0.088
5656
0.046
5656
8.792
5656
3.225
5656
0.441
5656
0.362
5656
0.559
5656
0.907

Non-CSR Audit Firms
N
Mean
8838
13.408
8838
0.031
8838
0.186
8838
21.877
8838
0.447
8838
0.165
8838
0.105
8838
2.439
8838
0.042
8838
0.038
8838
0.824
8838
0.446
8838
0.086
8838
0.045
8838
8.779
8838
3.216
8838
0.419
8838
0.347
8838
0.858
8838
0.974

39

MeanDiff
0.207***-0.006**0.012*
0.332***-0.004-0.012***0.009***-0.0250.002
0.001
0.089***-0.003
0.002
0.000
0.013
0.010
0.022***
0.014***-0.299***-0.067***

Table 8 Auditor CSR Activity and Audit Quality+/AUD_CSRt+

CSR_Numbert+

CSR_Typet

+

Sizet
LEVt
INVt
RECt
LIQt
CFOt
ROAt
BTMt
DAt
LOSSt
INSTSHSt
BOARDtINDt
SOEt
LARGSHSt
NonAud_Expertt
NonBIG4t
Constant
Year FE
Industry FE
NPseudo R2
Model Chi-sqr
Area ROC(1)
FMOAt
0.247*(1.513)

(2)
FMOAt

(3)
FMOAt

0.177**(1.645)-0.823***(-5.407)32.661**(2.445)-1.874**(-2.306)-1.960*(-1.944)-0.010(-0.229)-1.659*(-1.706)-4.440***(-3.138)
0.029(0.147)-28.615**(-2.099)0.622***(3.020)-5.930***(-3.377)
0.085(1.119)0.131(0.633)0.021(0.117)-1.551**(-2.296)0.301*(1.721)-0.789(-1.523)
12.592***(3.782)
Yes
Yes
14428
0.311
707.8480.869+/--0.823***(-5.422)32.487**(2.422)-1.851**(-2.283)-1.965*(-1.950)-0.010(-0.233)-1.663*(-1.712)-4.457***(-3.154)0.029(0.147)-28.448**(-2.078)
0.623***(3.033)-5.908***(-3.378)0.087(1.151)0.129(0.624)0.019(0.103)-1.551**(-2.298)
0.349*(1.952)-0.613(-1.160)
12.385***(3.732)
Yes
Yes
14428
0.311
703.4540.869(4)Restatementt-0.007(-0.143)(6)
Restatementt-0.049*(-1.486)

0.136**(1.827)-0.824***(-5.429)32.664**(2.448)-1.857**(-2.292)-1.983**(-1.974)-0.010(-0.239)-1.660*(-1.711)-4.479***(-3.165)0.030(0.153)-28.624**(-2.102)0.620***(3.023)-5.911***(-3.381)0.087(1.156)0.128(0.616)0.020(0.110)-1.555**(-2.305)
0.384**(2.113)-0.731(-1.435)
12.494***(3.774)
Yes
Yes
14428
0.311
701.3250.868(5)Restatementt-0.070**(-2.064)-5.396(-1.058)-0.359(-1.613)-0.563**(-2.041)-0.001(-0.110)-1.075***(-3.043)-1.171*(-1.810)-0.011(-0.224)
6.115(1.195)-0.001(-0.006)-0.138(-0.249)-0.007(-0.308)-0.009(-0.138)-0.189***(-3.192)-0.245(-1.318)
0.022(0.376)
0.523***(3.255)-0.569(-0.761)
Yes
Yes
14494
0.035
404.5500.631-0.070**(-2.065)-5.487(-1.077)-0.376*(-1.684)-0.550**(-1.995)-0.001(-0.089)-1.083***(-3.065)-1.149*(-1.774)-0.009(-0.182)
6.208(1.214)0.003(0.032)-0.137(-0.248)-0.007(-0.322)-0.009(-0.138)-0.185***(-3.122)-0.242(-1.303)-0.018(-0.285)
0.471***(2.873)-0.481(-0.642)
Yes
Yes
14494
0.035
406.226
0.632-0.043**(-1.979)-0.070**(-2.062)-5.518(-1.083)-0.377*(-1.693)-0.546**(-1.980)-0.001(-0.084)-1.089***(-3.082)-1.134*(-1.751)-0.009(-0.175)
6.240(1.220)0.005(0.050)-0.143(-0.259)-0.008(-0.340)-0.009(-0.125)-0.185***(-3.123)-0.242(-1.304)-0.036(-0.580)0.500***(3.113)-0.496(-0.663)
Yes
Yes
14494
0.036
406.586
0.632

Two dependent variables: (1) Modified audit opinions (FMOA) equals one if the auditor issues a modified audit opinion in yeart, and zero otherwise; (2) Restatement equals one if the client restates their financial statements in year t, and zero otherwise.
AUD_CSR t equals one if the audit firm engaged in CSR in year t; CSR_Number t is the natural log of the number of CSR
activities engaged by an audit firm in year t; CSR_Type t is the number of CSR categories engaged by an audit firm in year t.
See Appendix 1 for other variable definition. Robust z statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. One-tailed p
is for signed expectations and two-tailed p is for unsigned expectations. Standard errors are clustered at the client firm level.
The number of observations is reduced to 14,428 in column 1 to 3 because there is no variation in FMOA in the Scientific
Research and Technology Service industry, which has 66 observations and these observations are dropped out from the analyses.

40

Table 9 Auditor CSR Activity and Audit fees+/AUD_CSRt+

CSR_Numbert+

CSR_Typet

+

Sizet
LEVt
INVt
RECt
LIQt
CFOt
ROAt
BTMt
DAt
LOSSt
INSTSHSt
BOARDtINDt
SOEt
LARGSHSt
FMOAt
NonAud_Expertt
NonBIG4t
Constant
Year FE
Client FEN
adj. R2(1)
Audit_FEEt
0.008*(1.626)(2)
Audit_FEEt(3)
Audit_FEEt

0.008***(2.344)0.319***(33.606)-0.243(-0.334)-0.020(-0.477)
0.103*(1.700)-0.008***(-6.488)0.038(1.175)0.150*(1.869)-0.022***(-3.465)0.308(0.421)0.026***(2.745)-0.128**(-2.312)0.006*(1.693)-0.005(-0.623)-0.006(-0.260)-0.075(-1.605)
0.065***(3.954)-0.021***(-3.450)-0.180***(-4.313)
6.531***(31.486)
Yes
Yes
14494
0.903

0.319***(33.612)-0.234(-0.321)-0.019(-0.459)
0.104*(1.701)-0.008***(-6.472)
0.039(1.190)0.148*(1.844)-0.022***(-3.464)0.298(0.408)0.026***(2.727)-0.129**(-2.326)
0.006*(1.704)-0.005(-0.626)-0.006(-0.260)-0.075(-1.608)
0.065***(3.948)-0.019***(-3.078)-0.173***(-4.105)
6.522***(31.446)
Yes
Yes
14494
0.903

0.007***(2.990)0.319***(33.641)-0.228(-0.312)-0.019(-0.451)
0.104*(1.702)-0.008***(-6.461)
0.039(1.208)0.146*(1.817)-0.022***(-3.466)
0.291(0.398)0.026***(2.706)-0.129**(-2.337)
0.006*(1.729)-0.005(-0.636)-0.006(-0.253)-0.075(-1.603)
0.065***(3.946)-0.018***(-2.986)-0.177***(-4.250)
6.525***(31.495)
Yes
Yes
14494
0.903

The dependent variable, Audit_FEEt, is the natural log of audit fees in year t. AUD_CSRt equals one if the audit firm engaged
in CSR in year t; CSR_Numbert is the natural log of the number of CSR activities engaged by an audit firm in year t; CSR_Typetis the number of CSR categories engaged by an audit firm in year t. See Appendix 1 for other variable definition. Robust t
statistics in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. One-tailed p is for signed expectations and two-tailed p is for
unsigned expectations.

41

Table 10 Audit Firm Sanctions and CSR Activities
Panel A the relationship between audit firm sanctions and CSR activities+/AUD_SANt-1
NonBig4t
NonAud_Expt-1
Clientele_SIZEt-1
Clientele_MTBt-1
Constant
Year FE
N
Pseudo / Adjusted R2
Model Chi-sqr
Area under ROC Curve+(1)
AUD_CSRt
0.803***(2.516)-2.468**(-2.266)-1.148***(-2.706)-0.345(-0.806)
0.847(1.376)7.364(0.771)
Yes
344
0.177
47.0400.767(2)
CSR_Numbert
0.166**(2.006)-1.643***(-5.452)-0.470***(-2.656)-0.070(-0.706)
0.287*(1.834)3.256(1.501)
Yes
344
0.494

(3)
CSR_Typet
0.310***(2.890)-1.515***(-4.510)-0.747***(-3.250)-0.151(-1.436)0.250(1.590)5.209**(2.252)
Yes
344
0.369

Three dependent variables: (1) AUD_CSR t equals one if the audit firm engaged in CSR in year t; (2) CSR_Number
t is the natural log of the number of CSR activities engaged by an audit firm in year t; (3) CSR_Type t is the numberof CSR categories engaged by an audit firm in year t. AUD_SANt-1 equals one if the audit firm has been sanctioned
in year t-1. See Appendix 1 for other variable definition. Robust z and t statistics in parentheses. * p < 0.1, ** p <0.05, *** p < 0.01. One-tailed p is for signed expectations and two-tailed p is for unsigned expectations.

42

Table 10 (continued)
Panel B: Audit firm CSR activities and the likelihood of auditor dismissals after sanctions+/-(1)
Dismisst
0.178**(2.294)0.040(0.382)-0.281**(-2.142)

Aud_Sanctiont-1
Aud_CSRt
Aud_Sanctiont-1* Aud_CSRt-

CSR_Number t
Aud_Sanctiont-1*CSR_Number t(2)
Dismisst
0.192**(2.562)0.011(0.188)-0.190***(-2.588)-

CSR_Typet
Aud_Sanctiont-1*CSR_Typet(3)
Dismisst
0.178**(2.402)-0.162***(-4.043)-3.867(-0.430)-0.312(-1.085)
0.605*(1.876)
0.034***(2.830)-0.698(-1.566)-0.873(-1.036)-0.023(-0.386)4.680(0.518)-0.063(-0.476)-0.138(-0.197)
0.008(0.297)0.007(0.093)0.313***(4.453)0.220(0.987)-0.050

Sizet
LEVt
INVt
RECt
LIQt
CFOt
ROAt
BTMt
DAt
LOSSt
INSTSHSt
BOARDtINDt
SOEt
LARGSHSt
NonAud_Expertt

43-0.163***(-4.061)-3.876(-0.431)-0.326(-1.130)
0.609*(1.889)0.034***(2.833)-0.714(-1.602)-0.858(-1.018)-0.023(-0.381)4.694(0.520)-0.064(-0.484)-0.149(-0.213)0.007(0.258)0.009(0.117)0.314***(4.470)0.222(0.993)-0.0880.023(0.384)-0.133**(-2.027)-0.163***(-4.071)-3.807(-0.424)-0.317(-1.104)
0.606*(1.882)0.034***(2.831)-0.713(-1.598)-0.852(-1.011)-0.024(-0.400)
4.625(0.513)-0.064(-0.484)-0.163(-0.231)0.006(0.234)0.011(0.138)0.313***(4.454)0.220(0.987)-0.097

(-0.702)-0.496***(-3.575)
1.206(1.377)
Yes
Yes
14494
0.031
318.473
0.636

NonBIG4t
Constant
Year FE
Industry FE
NPseudo R2
Model Chi-sqr
Area under ROC Curve(-1.193)-0.519***(-3.134)
1.278(1.441)
Yes
Yes
14494
0.031
318.6200.635(-1.299)-0.480***(-3.144)1.247(1.416)
Yes
Yes
14494
0.031
318.693
0.635

The dependent variable Dismisst equals one if the audit firm has been dismissed in year t; AUD_SANt-1 equals one
if the audit firm has been sanctioned in year t-1; Three CSR variables: (1) AUD_CSR t equals one if the audit firm
engaged in CSR in year t; (2) CSR_Number t is the natural log of the number of CSR activities engaged by an audit
firm in year t; (3) CSR_Type t is the number of CSR categories engaged by an audit firm in year t. See Appendix 1
for other variable definition. Robust z statistics in parentheses. Standard errors are clustered at the client firm level.
* p < 0.1, ** p < 0.05, *** p < 0.01. One-tailed p is for signed expectations and two-tailed p is for unsigned
expectations.

44

Appendix: Definition of Variables
Variable NameAUD_CSRt-1
CSR_Num t-1
CSR_Type t-1
Donation t-1
Environment t-1
Employee t-1
Others t-1△Client Number
Nonbig4

Definition
Audit Firm Level Variables
A dummy variable coded 1 if an audit firm engaged in CSR in year t-1
Log value of the total number of CSR activities engaged by an audit
firm in year t-1, calculated as log (1+ CSR_Num t-1)
The number of CSR categories engaged by an audit firm in year t-1
A dummy variable coded 1 if an audit firm engaged in donation in year
t-1
A dummy variable coded 1 if an audit firm engaged in environment
protection in year t-1
A dummy variable coded 1 if an audit firm engaged in employee
welfare in year t-1
A dummy variable coded 1 if an audit firm engaged in other social
activities in year t-1
Change in client number
A dummy variable coded 1 if an audit firm is not a Big4 firm and zerootherwise.

NonAud_Exp t-1

A dummy variable coded 1 if an audit firm is not an industry
expert. The industry expert is measured based on the market
share of audit fees greater than 30%.

Aud_San t-2, t-1

The number of sanctions against audit firms divided by the total
number of clients during the previous two years, times 100
The median value of natural log of total assets of clienteles in year t-1.
The median value of market value of equity scaled by book value ofequity of clientele in year t-1.

Client_Size t-1
Client_MTB t-1

Audit Client Level Variables
FS_Feest
FMOAt
Restatementt
Dismisst
Sizet
LEVt
INVt
RECt
LIQt
CFOt
ROAt
BTMt
DAt
LOSSt
INSTSHSt

Log value of financial statement audit fees in year t
A dummy variable coded 1 if the auditor issues an adverse or modified
financial statements audit opinion in year t and 0 otherwise.
A dummy variable coded 1 if the client restates their financial
statement in year t, and 0 otherwise.
A dummy variable coded 1 if the audit firm has been dismissed in yeart, and 0 otherwise.
Log value of total assets in year t
Total liabilities/total assets in year t
Inventory/total assets in year t
Total receivables/total assets in year t
Current assets/current liabilities in year t
Cash from operations/total assets in year t
Return on assets in year t
Book-to-market ratio in year t
Debt/total assets in year t
A dummy variable coded 1 if the company has incurred a negative net
income and 0 otherwise.
Percentages of shares held by institutional shareholders

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BOARDt
INDt
SOEt
LARGSHSt
NonAud_Expertt
NonBIG4t

The number of directors on the board
The number of independent directors on the board
A dummy variable coded 1 if the company is a State-owned-enterpriseand 0 otherwise
Percentages of shares held by the largest shareholder
A dummy variable coded 1 if an audit firm is not an industry expert
and zero otherwise.
A dummy variable coded 1 if an audit firm is not a Big4 firm and zerootherwise.

46