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Asia Pacific Management Review 20 (2015) 219e233

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Lower audit fees for women audit partners in Taiwan and why

Ting-Chiao Huang a, *, Jeng-Ren Chiou b, 1, Hua-Wei Huang b, 1, Jeng-Fang Chen b, 1

a Department of Accounting, Monash University, Australiab Department of Accountancy, National Cheng Kung University, Taiwan, ROC

a r t i c l e i n f o

Article history:Received 27 November 2014Accepted 11 February 2015Available online 19 June 2015

Keywords:Sex discriminationAuditing industryAudit feesTaiwan

* Corresponding author. Department of AccountingCampus, Wellington Road, Clayton, Victoria 3800, Au

E-mail addresses: [email protected](T.-C. Huang).

Peer review under responsibility of College of MKung University.

1 No. 1, University Road, Tainan City 701, Taiwan, R

http://dx.doi.org/10.1016/j.apmrv.2015.02.0011029-3132/© 2015 College of Management, National

a b s t r a c t

We investigate whether women audit partners earn lower audit fees than their men colleagues. Byexamining 2002e2011 fee data for audit engagements in Taiwan, where the names of signing auditpartners are disclosed, we find that audit engagements with women audit partners are related tosignificantly lower audit fees than those with men counterparts. Furthermore, we document that suchfee difference is aggravated in the industries with fewer women audit partners, cannot be explained bythe differences in audit quality and audit reporting lags, and is robust to controlling for firm fixed effects.Our finding provides evidence to support the existence of fee discrimination against women auditpartners in Taiwan's auditing industry. Our results should be of interests to audit firms with regard tohuman resource decisions.

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1. Introduction

The auditing profession around the world came under intensepublic scrutiny after the collapse of Enron and the subsequentdemise of its auditor, Arthur Andersen. In the United States, thegovernment and the regulator have taken unprecedented steps torestore stability and investors' confidence in the capital markets.For example, the U.S. Congress enacted the Sarbanes-Oxley Act of2002, a stringent rules-based system widely considered to be themost comprehensive economic regulation since the New Deal.

Yet it would be wrong to think that the auditing industry hashad its day, or to underplay its importance to the capital markets.The audit firms still need to provide independent and objectivetests of the accounting policies, procedures, and subjective judg-ment used bymanagement in preparing the financial reports and toissue audit opinions for the companies. Without the opinionsprovided by the audit firms, creditors, bankers, investors, andothers cannot use the financial reports with sufficient confidence.In addition to auditing services, the audit firms also provide a widerange of tax, advisory, and other professional services. In 2012,

, Monash University, Claytonstralia., [email protected]

anagement, National Cheng

OC.

Cheng Kung University. Production

revenues for the four largest global audit firms rose to a recordhistoric high level of $110 billion, up 6% from 2011. By service line,auditing services accounted for 45% of total revenues and grew by2.9% between 2011 and 2012. Tax-related services represented 23%of total revenues and also rose by 5.6% between 2011 and 2012.Advisory services have been the fastest growing service line,however, and grew strongly by 12.2% between 2011 and 2012.

Because of the great demand for auditing services, the profes-sion continues to attract talent from around the world, and has thepotential to continuously play an important role in the capitalmarkets. However, if that potential is to be realized, reform iscrucial. Regulators are debating newmethods of oversight to stop asecond audit failure, and to allow the auditing industry to developand prosper sustainably.

However, some believe that the process of reform in theauditing industry will be a wasted opportunity if it does not largelyaddress the persistent and marked discrimination against womenthat seems to permeate this industry. According to the surveyconducted by Schaefer and Zimmer (1995), the average income ofmen accountants and auditors exceeds that of their women coun-terparts by approximately 49%. In addition, the American Instituteof Certified Public Accountants (AICPA) reports that managing di-rectors are also predominately men, despite the fact that womenhave entered the auditing profession in record numbers in recentdecades. In 2009, women made up 55% of newly-hired graduatesand 61.8% of all accountants and auditors. Despite comprising halfthe workforce at audit firms, women account for only 23% of all

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T.-C. Huang et al. / Asia Pacific Management Review 20 (2015) 219e233220

audit partners industry-wide. The statistics suggest that, across theauditing industry, women are still facing the trials of discriminationthat take the form of unequal pay and lack of advancement in thejob place.

Likewise, the presence of women audit partners in auditengagement is low in Taiwan. Within our sample, only 30% of theleading auditors and 30% of the accompanying auditors arewomen. This low presence of women audit partners is more severein the early period. For example, only 14% of the leading auditorsare women in 2002, and the number increases to 36% in 2011.Based on the statistics provided by the Taiwan Financial Supervi-sory Commission, the average salaries of the top 30 audit firms inTaiwan are $904,769 NTD for women signing auditors and$1,156,658 NTD for men signing auditors in self-owned audit firms,and are $510,353 NTD for employed women auditors and $550,680for employed men auditors. Overall, these statistics suggest thatboth the presence and the salaries of women are low in Taiwan'saudit market.

Relatedly, Yang, Chen, and Yang (2013) show that in Taiwanman-owned audit firms outperform woman-owned audit firms infinancial performance, and even the formers without professionaltrainings on auditors have higher financial performance than thelatters with professional trainings. The authors interpret thesefindings as suggesting “the Chinese cultural values in social rolesagainst women”. Their results further reinforce that Taiwan's auditindustry is masculine and there exists discrimination againstwomen.

In this study, we try to extend prior research by further inves-tigating whether the audited client pays lower audit fees to itswomen audit partners. This issue is important because if womenaudit partners cannot charge more for the quality services theyprovide to a client, it would be hard for a woman to become apartner or to be promoted. Similarly, if women partners cannotmakemore profits for the audit firm, theywill have less negotiationflexibility or room to maneuver in regard to salaries. Therefore, thediscrimination against women in relation to audit fees maypartially explain why women face unequal pay or opportunities forpromotion in an audit firm. Moreover, if the audited client payslower audit fees to its women audit partners, women would havefewer resources that can be devoted to audit procedures, whichmay in turn influence audit quality.

To address this issue, we employ a sample of publicly-listedfirms in Taiwan to examine our research questions. The auditreport in Taiwan contains the names of two signing audit partnersas well as the name of the audit firm, in contrast to the U.S., wherethe audit report only contains the audit firm's name. This providesan opportunity to investigate the difference in audit fees betweenmen and women partners. By using a sample for the 2002e2011period in which audit fees and audit partners' names wereobservable, we find that audit engagements with women signingaudit partners are related to significantly lower audit fees thanthose with men counterparts, suggesting the existence ofdiscrimination against women on audit fees in Taiwan's auditingindustry. Furthermore, we document evidence that such discrimi-nation is more severe in the industries where the presence ofwomen audit partners is low. Further analyses suggest that thedifference in audit fees cannot be explained by the superior auditquality of men auditors or by fewer audit hours of women auditpartners. In contrast, we find that women audit partners areassociated with better client earnings quality and longer auditreporting lags. The relation between women audit partners andaudit fees continues to be significantly negative when we controlfor client earnings quality and audit reporting lags. Finally, thedocumented lower audit fees for women in this paper are robust tocontrolling for firm fixed effects.

In 2011, the PCAOB proposed an auditing standard about thedisclosure of the audit engagement partner (PCAOB, 2005). Theunderlying reason would be the belief in that this would enhanceauditor accountability and audit quality. Since auditor sex is a sig-nificant auditor characteristic, this paper provides insightful infor-mation about the association between auditor sex and audit fees(audit quality) to global regulators. We also contribute to theliterature examining the sex effects such as CEO, CFO, director, andauditor sex. Finally, the results in the current study should be ofinterest to audit firms in human resource decisions.

2. Related research

Sex discrimination has caught the eye of researchers in recentdecades. Many studies have emphasized the impact of sexdiscrimination on pay, which is traditionally a vital social welfareand equality issue (Berik, Rodgers, & Zveglich, 2004; Blinder, 1973;Corcoran & Duncan, 1979; Goldin, 1990; Jarrell & Stanley, 2004;Stanley & Jarrell, 1998). To reduce sex discrimination, the CivilRights Act of 1964 was enacted by the U.S. Senate and House ofRepresentatives to eliminate employment discrimination,including discrimination according to sex, color, and race. More-over, the Equal Pay Act of 1963 was also enacted with a view toprohibiting sex differences in wages. However, the 2004 salarysurvey conducted by the Institute of Management Accountantsshows that women earn lower wages than men regardless of workexperience. Although Adams and Harte (2000) posited that thefield of accounting has the potential by which to discover sexdiscrimination, many studies have argued that the accountingprofession itself also has the same concern (Anderson-Gough, Grey,& Robson, 2005; Marlow & Carter, 2004; Tinker & Fearfull, 2007;Whiting & Wright, 2001). White and White (2006) also suggestedthat women auditors are more likely to be devalued by their clients.

Researchers have indicated that sex influences auditors' jobsatisfaction and employment, and that the glass ceiling preventswomen from moving higher up the hierarchy in audit firms. Forinstance, while around 35%e50% of entrants into the field arewomen (Lehman, 1992), only 5% of partners in Big 6 accountingfirms are women (Telberg, 1993). Likewise, 96% of the partners andmanagement in Australian accounting firms are men (Perera,Fatseas, & Luckett, 1997), and only 3% of partners in the largestaccounting firms were found to be women in the 1980s (Hooks &Cheramy, 1989). Although women entrants exceed men ones(AICPA, 2008), sex discriminationmay still be present in accountingfirms. Examining Swedish audit industry, Måsson, Elg, andJonnergård (2013) indicate that women auditors are less likely tobe promoted. Moreover, they find that having children increasesthe likelihood for men auditors to be promoted but decreases thelikelihood for women auditors. Similarly, Jonnergård, Stafsudd, andElg (2010) show that in the Swedish audit industry, 50% of the newemployees and 92% of the audit partners are men, and that womenauditors have greater intentions to leave the audit firm.

Outside the auditing profession, researchers have also showedthat women executives are likely under-paid. For example, Lam,McGuinness, and Vieito (2013) suggest that women CEOs receiveless favorable compensation terms than their men colleagues, andMohan and Ruggiero (2007) conclude that women CEOs are under-paid even after controlling for performance. Kulich, Trojanowski,Ryan, Haslam, and Renneboog (2011) examine the sex effect onthe compensation portfolio, and find that men managers receivemore bonus and performance-sensitive compensation thanwomen. They interpret these findings as suggesting that comparedto women, men would be more risk-taking. In contrast, Bugeja,Matolcsy, and Spiropoulos (2012) find insignificant relation be-tween CEO sex and compensation.

T.-C. Huang et al. / Asia Pacific Management Review 20 (2015) 219e233 221

Recent studies suggest that the differences in career promotionand salaries between men and women auditors cannot beexplained by the differences in performance or independence. Forexample, Niskanen, Karjalainen, Niskanen, and Karjalainen (2011)show that in Finland, clients of women auditors report highermagnitude of income-decreasing discretionary accruals than thatof men, suggesting that women are more conservative than theirmen colleagues.

Recent studies outside the auditing industry also provide noevidence that men executives outperform women. For example,Huang and Kisgen (2013) indicate that men CEOs are more over-confident than women, and the announcement returns to the ac-quisitions made by men CEOs are 2% lower than that by women.Khan and Vieito (2013) also show that firms managed by womenCEOs are less risky than those by men, consistent with Faccio,Marchica, and Mura (2012) that firms with women CEOs havelower leverage and less volatile earnings, and are more likely tosurvive than firms with men CEOs. Similarly, Rose (2007) fails tofind significant difference in firm performance between firms withand without the presence of women directors.

Related business studies indicate that women are likely moreconservative, less risk-taking, and more ethical than men. Thesestudies generally show that firms aremore conservative in financialreporting when they have women CEOs, CFOs, or directors. Forexample, Gul, Hutchinson, and Lai (2013) find a positive associationbetween the presence of women directors and the accuracy ofanalyst earnings forecasts, while Abbott, Parker, and Presley (2012)show a negative relation between the presence of women directorsand the likelihood of financial restatement. Consistently, Srinidhi,Gul, and Tsui (2011) find that women directors improve a firm'searnings quality, and Barua, Davidson, Rama, and Thiruvadi (2010)document that a firm's accruals quality is better when the CFO iswoman. Francis, Hasan, Park, andWu (2009) also show that womenCFOs are associatedwithmore conservative financial reporting, andPeni and V€ah€amaa (2010) find that firms with women CFOs exhibitmore income-decreasing discretionary accruals than firms withmen CFOs. Gul, Srinidhi, and Ng (2011) find that a firm's stock pricereflects more firm-specific information and a firm's earnings ismore informative under the monitoring of a sex-diverse board,especially for firms with weak corporate governance. Finally, Sun,Liu, and Lan (2011) fail to find evidence that women directors onaudit committees constrain earnings management, and Ye, Zhang,and Rezaee (2010) also fail to document significant difference inearnings quality between firms with and without women topexecutives.

Overall, the prior studies generally suggest that women areunder-paid and there is no evidence that men outperform women.We contribute to the literature by providing evidence from Tai-wan's audit industry that women audit partners earn lower auditfees than men. Further analyses suggest that such difference inaudit fees cannot be attributed to the differences in audit qualityand audit efforts. Combined together, these results would suggestthat discrimination against women exist in Taiwan's audit industry.

3. Description of data

3.1. Taiwan auditing market

In Taiwan, the financial reports (including the audit opinions) ofpublic firms are currently required to be signed by two individualaudit partners. The Taiwanese Securities and Futures Bureau (TSFB,similar to the U.S. Securities and Exchange Commission) amendedArticle II of the Criteria Governing Approval for Auditing and Cer-tification of Financial Reports of Public Companies by CertifiedPublic Accountants (CGAAC) in 1982, which took effect in 1983, and

required that the financial reports of listed firms be audited andsigned by two practicing certified public accountants as well as bythe audit firm (Chin & Chi, 2009). In addition, the Statement ofAuditing Standards No. 33, “Auditor Report on Financial State-ments,” requires that audit reports be signed by two independentauditors and also by the audit firm (Accounting and ResearchDevelopment Foundation, ARDF, 1999). In contrast to the U.S.,where the audit reports of public firms only disclose the name ofthe audit firm and its location, the data from Taiwan identify thenames of the two engaged audit partners and that of the audit firm.

We use data from all public firms with audit fee information inTaiwan for the period from 2002 to 2011. Financial data, audit firmdata, and individual audit partner names are all obtained from theTaiwan Economic Journal (TEJ) database. The initial sample withavailable audit fee data consists of 6052 firm-year observations. Weexclude observations with missing auditor information (3), finan-cial firms (448), and firms with missing financial data (658). Finally,we have 4943 firm-year observations and 1511 unique firms for ourregression analysis.

It should be noted that firms in Taiwan are not mandated todisclose the audit fee information. Only when non-audit fees arehigher than 25% of audit fees (Reason 1), when auditors are changedwith a reduction in audit fees (Reason 2), and when audit fees aredecreased by more than 15% compared to the fee for the previousyear (Reason 3) are firms required to disclose audit fees. Firms canalso disclose audit fees voluntarily (Reason 4). In the robustnesscheck, we divide our sample into firms that disclose audit fees dueto requirements (Reasons 1e3) or voluntarily (Reason 4).

The sample distribution across years and industries is presentedin Table 1. There is an increase in sample representation during oursample period (Panel A). For instance, the number of observationsincreases from 236 in 2002 to 1015 in 2011. Liao, Wang, and Chi(2012) indicate that because of the need for audit firms in theadoption of IFRS and because of the encouragement of voluntarilydisclosing audit fee information, the number of firms with audit feedata increases after 2009. In the robustness checks, we restrict oursample period to 2002e2008 and find consistent results. Liao et al.(2012) suggest that there is no significant structural differencebetween the sample period 2002e2008 and 2009e2010, and thatthe sample selection bias is less likely to be large. Our results alsoremain unchanged when we restrict the sample period to2002e2009. Panel B of Table 1 presents the sample distribution byindustry. About 14.48% of the observations (716) operate in theelectronics components industry (TSE Industry Code ¼ 28), and theremainder are evenly distributed in other industries. In theregression analyses, we include year and industry indicators tocontrol for year and industry effects.

3.2. Measure of audit partner sex

We classify the audit partners' sex based on their names, ormake direct contact with audit firms to accurately identify auditorsex sampled in this study. The results are robust to excluding thoseobservations for which audit partners' sex is unclear. Four in-dicators are used to proxy for the sex effects of the signing auditpartners: (1) WOMEN equals 1 if at least one of the engaged auditpartners is woman, and 0 otherwise; (2) WOMENNUM denotes thenumber of women audit partners engaged with a client, and isdistributed between 0 and 2; (3) CPA1WOMEN equals 1 if theleading audit partner is woman, and 0 otherwise; (4) CPA2WOMENequals 1 if the accompanying audit partner is woman, and0 otherwise. In the sensitivity test, we employ three additionalmeasures to capture audit partners' sex after considering the dif-ferential effects of the leading partners and accompanying partnersand obtain similar results.

Table 1Distribution of women audit partners.

Panel A: Distribution by year

Year N WOMEN WOMENNUM CPA1WOMEN CPA2WOMEN

2002 236 0.43 0.46 0.14 0.322003 240 0.45 0.49 0.20 0.292004 191 0.50 0.58 0.26 0.322005 171 0.53 0.63 0.34 0.292006 477 0.49 0.57 0.26 0.312007 520 0.51 0.61 0.28 0.332008 505 0.50 0.59 0.30 0.292009 707 0.51 0.60 0.32 0.282010 881 0.54 0.63 0.33 0.312011 1015 0.57 0.66 0.36 0.30Total 4943 0.52 0.60 0.30 0.30

Panel B: Distribution by industry

TSE Industry N WOMEN WOMENNUM CPA1WOMEN CPA2WOMEN

01: Cement 22 0.68 0.77 0.45 0.3202: Foods 73 0.53 0.55 0.26 0.2903: Plastics 101 0.60 0.66 0.34 0.3304: Textiles 151 0.49 0.55 0.26 0.2805: Electric and Machinery 254 0.37 0.45 0.19 0.2606: Electrical 47 0.36 0.36 0.23 0.1308: Glass and Ceramics 19 0.79 0.89 0.58 0.3209: Paper and Pulp 13 0.23 0.23 0.15 0.0810: Steel and Iron 141 0.61 0.76 0.29 0.4711: Rubber 43 0.81 0.95 0.44 0.5112: Automobile 24 0.71 0.71 0.38 0.3313: Miscellaneous Electronic 112 0.38 0.41 0.21 0.2114: Constructions 229 0.62 0.72 0.32 0.4015: Transportations 76 0.47 0.59 0.34 0.2516: Tourism 41 0.51 0.54 0.34 0.2018: Trading 69 0.58 0.70 0.41 0.2920: Others 224 0.53 0.63 0.31 0.3221: Chemicals 148 0.53 0.62 0.37 0.2522: Biotechnology 228 0.50 0.66 0.36 0.3123: Oil and Gas 32 0.78 0.91 0.53 0.3824: Semiconductor 492 0.49 0.57 0.29 0.2825: Computer 369 0.59 0.70 0.36 0.3526: Photoelectric 488 0.47 0.53 0.27 0.2627: Communication Network 245 0.60 0.69 0.40 0.3028: Electronics Components 716 0.47 0.55 0.26 0.2929: E-Channel Industry 150 0.61 0.69 0.37 0.3230: Information Services 160 0.56 0.61 0.35 0.2631: Other Electronics 250 0.50 0.58 0.23 0.3580: Management of Stock 26 0.54 0.58 0.08 0.50

Total 4943 0.52 0.60 0.30 0.30


3.3. Distribution of women audit partners in Taiwan auditingmarket

Table 1 also presents the distribution of women audit partnersacross years and industries. We find that 52% of the observationshave at least one women auditors, the average number of womenauditors is 0.60, and 30% of the leading auditors and the accom-panying auditors arewomen. There is an increase in the presence ofwomen audit partners across years. For example, the averagenumber of women auditors increases from 0.46 in 2002 to 0.66 in2011, and the presence of women leading auditors increases from14% in 2002 to 0.36 in 2011. We also find that, in most industries,the presence of women audit partners is relatively low anddispersed. Exceptions are the glass and ceramics industry, therubber industry and the oil and gas industry, where more than 75%of firms engage with at least one women audit partner.

In contrast, lower than 40% of firms in the electric and ma-chinery industry, the electrical industry, the papers and pulps in-dustry, and the miscellaneous electronic industry engage with atleast one women audit partners. Overall, Table 1 suggests that the

presence of women audit partners in Taiwan is low and disperseacross years and industries, and reinforces the importance of con-trolling for year and industry effects.

3.4. Firm characteristics

Descriptive statistics are presented in Table 2. The mean and themedian values of audit fees (LNAF) are 14.63 and 14.64, respectively,and that of total assets (LNTA) are 21.76 and 21.57, respectively. Oursample includes both young and old companies, and the meanvalue of age since a firm was established (AGE) is 22 years. Onaverage, the receivables and the inventories account for 34% of totalassets (RECINV), and total liabilities account for 44% of total assets(LEV). The mean ratio of foreign sales (FOREIGN) is 25%, and onaverage current assets are 2.44 times of current liabilities (CUR-RENT). Among the sample firms, 6% are newly listed firms (IPO), 36%are traded over-the-counter (OTC), 8% are emerging stocks (ROTC),and the remainders are publicly listed firms. In our sample, 26% ofsample firms suffer from net losses (LOSS), 3% receive going-concern opinions (GC), 63% receive unclean audit opinions

Table 2Descriptive statistics (N ¼ 4943).

Variables Mean STD Q1 Median Q3

Logarithm of audit fees (LNAF) 14.63 0.61 14.25 14.64 15.01Logarithm of total assets (LNTA) 21.76 1.56 20.68 21.57 22.63Firm age since setup (AGE) 22.22 12.70 12.00 20.00 31.00Percentage of receivables and inventories (RECINV) 0.34 0.19 0.20 0.33 0.46Square root of related parties (RELATE) 3.14 1.47 2.00 2.83 3.87Foreign sales (FOREIGN) 0.25 0.37 0.00 0.00 0.57Loss (LOSS) 0.26 0.44 0.00 0.00 1.00Current ratio (CURRENT) 2.44 2.35 1.26 1.74 2.68Leverage (LEV) 0.44 0.21 0.29 0.44 0.57Returns on assets (ROA) 0.29 1.51 0.00 0.02 0.14Going concern opinion (GC) 0.03 0.17 0.00 0.00 0.00Unclean audit opinion (UNCLEAN) 0.63 0.48 0.00 1.00 1.00Restatement (RESTATE) 0.04 0.19 0.00 0.00 0.00Initial public offerings (IPO) 0.06 0.24 0.00 0.00 0.00Over the counter (OTC) 0.36 0.48 0.00 0.00 1.00Emerging stock (ROTC) 0.08 0.27 0.00 0.00 0.00Big 4 audit firms (BIG4) 0.85 0.36 1.00 1.00 1.00CPA1 experience (CPA1EXP) 11.59 5.88 7.00 11.00 16.00CPA2 experience (CPA2EXP) 11.13 6.25 6.00 11.00 16.00Initial audit engagements (INITIAL) 0.07 0.26 0.00 0.00 0.00Number of new auditors (NEWCPA) 0.51 0.67 0.00 0.00 1.00Logarithm of non-audit fees (LNNAF) 11.35 4.82 11.70 13.30 14.00Client importance for audit firm (CIFIRM) 0.02 0.09 0.00 0.00 0.00Client importance for CPA1 (CICPA1) 0.11 0.20 0.01 0.03 0.10Client importance for CPA2 (CICPA2) 0.11 0.21 0.01 0.02 0.09Audit firm tenure (AFTENURE) 10.25 6.71 5.00 9.00 15.00CPA1 tenure (CPA1TENURE) 3.07 1.80 2.00 3.00 4.00CPA2 tenure (CPA2TENURE) 2.64 1.57 1.00 2.00 4.00Audit firm industry specialization (EXPERT_FIRM) 0.31 0.46 0.00 0.00 1.00CPA1 industry specialization (EXPERT_CPA1) 0.02 0.15 0.00 0.00 0.00CPA2 industry specialization (EXPERT_CPA2) 0.02 0.14 0.00 0.00 0.00Non-audit fees higher than 25% of audit fees (REASON1) 0.51 0.50 0.00 1.00 1.00Auditors are changed with a reduction in audit fees (REASON2) 0.02 0.14 0.00 0.00 0.00Reduction in audit fees more than 15% (REASON3) 0.05 0.22 0.00 0.00 0.00Voluntary disclosure of audit fees (REASON4) 0.45 0.50 0.00 0.00 1.00


(UNCLEAN), and 4% restate financial statements (RESTATE). Similarto other developed countries, most (85%) sample firms in Taiwanare audited by Big4 audit firms (BIG4). On average, leading andaccompanying audit partners have 11 years of audit experience(CPA1EXP and CPA2EXP) and have continuously served the client for3 years (CPA1TENURE and CPA2TENURE). Each client's total assetsare on average 2% of the sum of the total assets of the audit firm'sclients (CIFIRM) and 11% of the sum of the total assets of the leadingpartner's and the accompanying audit partner's clients (CICPA1 andCICPA2). There are 7% of sample firms changing their engaged auditfirm in the current year (INITIAL), and the average number of newaudit partners is 0.51 (NEWCPA). The mean and the median valuesof the logarithm of non-audit fees (LNNAF) are 11.35 and 13.30,respectively. Among the sample firms, 31% are audited by industryspecialized audit firms (EXPERT_FIRM), and 2% are audited by in-dustry specialized leading or accompanying audit partners(EXPERT_CPA1 and EXPERT_CPA2). Regarding the reason for auditfee disclosure, 51% of sample firms disclose audit fees because non-audit fees are higher than 25% of audit fees (REASON1), 2% becausethere is an audit firm change with a reduction in audit fees(REASON2), 5% because the reduction in audit fees is more than 15%(REASON3), and 45% disclose audit fees voluntarily (REASON4). Notethat Reason 1 to 3 are not mutually exclusive. All continuous vari-ables are winsorized at 1% and 99% to alleviate the problem ofoutliers.

We further compare the differences in firm characteristics be-tween firms with and without women audit partners (untabu-lated). It shows that the clients audited by women audit partners(WOMEN ¼ 1) are older (AGE), are more complex in the number ofrelated parties (RELATE), consist of fewer IPO firms (IPO), are more

likely to be audited by the Big 4 audit firms (BIG4) and by lessexperienced accompanying auditors (CPA2EXP), involve in fewerinitial audit engagements (INITIAL), have longer audit firm tenure(AFTENURE), and are less likely to be audited by industry specializedaudit firms (EXPERT_FIRM) than those by men audit partners(WOMEN ¼ 0). Coupled with the fact that we find no significantdifferences in size (LNTA), auditor specialization (EXPERT_CPA1 andEXPERT_CPA2), and the reasons for audit fee disclosure (REASON1 toREASON4), we conclude that our results of the difference in auditfees between women and men auditors are unlikely driven by thesize effects, the premiums for the Big 4 audit firms and industryspecialized auditors, or the underlying reasons for firms to discloseaudit fees. Nevertheless, we control these firm and audit charac-teristics in our regression analyses to alleviate such concerns.

4. Women audit partners and audit fees

The main question addressed by this study is whether there isany evidence that women audit partners are discriminated againstupon providing and charging for their professional services. Thisquestion is important, because women audit partners would be at adisadvantage in terms of receiving higher compensation and pro-motion in audit firms if they contribute less to audit firm earnings.We do not assume that higher audit fees equal higher profits, sinceprofits are determined by audit fees, audit efforts, auditor'scompensation for risk, and other factors. However, we have dis-cussedwith audit partners about this issue, and they suggest that tosome extent audit fees are associated with profits. Therefore, westudy the association betweenwomen audit partner and audit fees,after controlling for other determinants.


4.1. Women audit partner and audit fees

We first investigate the relationship between women auditpartners and audit fees. Both uni-variate analysis and regressionanalysis are used to examine this association. First, the full sampleobservations are classified into two groups: (1) firms with zerowomen audit partners and (2) firms with at least one women auditpartners. We then examine the mean and median differences fortwo of the three groups, respectively. Based on t test and Wilcoxonrank sum test, the untabulated results show that firms with zerowomen audit partners and firms with at least one women auditpartners are close in audit fees. The mean and the median values ofthe logarithm of audit fees are $14.62 and $14.63 for firmswith zerowomen audit partners and are $14.65 and $14.65 for firms with atleast one women audit partners. The difference in mean is insig-nificant under the t test, while the difference in median is signifi-cant under the Wilcoxon rank sum test.

Second, we follow prior audit pricing studies (e.g., Huang,Raghunandan, & Rama, 2009; Kim, Liu, & Zheng, 2012; Dao,Raghunandan, & Rama, 2012; Fung, Gul, & Krishnan, 2012) toconstruct the audit pricing regression model as follows:

LNAF ¼ b0 þ b1GENDERþ b2LNTAþ b3AGE þ b4RECINV þ b5RELATEþb6FOREIGN þ b7LOSSþ b8CURRENT þ b9LEV þ b10ROAþ b11GCþb12UNCLEAN þ b13RESTATE þ b14IPOþ b15OTC þ b16ROTC þ b17BIG4þb18CPA1EXP þ b19CPA2EXP þ b20INITIALþ b21NEWCPAþ b22LNNAFþb23CIFIRM þ b24CICPA1þ b25CICPA2þ b26AFTENUREþb27CPA1TENURE þ b28CPA2TENURE þ b29EXPERT FIRMþb30EXPERT CPA1þ b31EXPERT CPA2þ b32REASON1þ b33REASON2þb34REASON3þ YEARþ INDUSTRY þ 3

(1)

The dependent variable is the logarithm of audit fees (LNAF).GENDER is the indicators of women audit partner sex discussedabove (WOMEN, WOMENNUM, CPA1WOMEN, and CPA2WOMEN).We predict that b1 is negative under the sex discriminationassumption. That is, if women audit partners suffer from inequity,they are remunerated with lower audit fees.

The model also includes several firm-specific control variables,which account for the effects of factors on the cross-sectional dif-ferences in audit fees. Accordingly, we control for the client sizeeffect by including the logarithm of total assets (LNTA) and thenumber of years since the firm was established (AGE) and controlfor client complexity by including the percentage of receivables andinventories over total assets (RECINV), the square root of thenumber of related parties (RELATE), and the percentage of foreignsales (FOREIGN) (Chi, Huang, Liao, & Xie, 2009; Francis, 1984; Funget al., 2012; Simunic, 1980). Following Dao et al. (2012) and Kimet al. (2012), client-specific litigation risks and financial condi-tions are controlled by including an indicator of reporting net loss(LOSS), the ratio of current assets to current liabilities (CURRENT),the debt-to-asset ratio (LEV), the return on assets (ROA), an indi-cator of receiving a going concern opinion (GC), and an indicator ofreceiving unclean audit opinions (UNCLEAN), which include un-qualified audit opinions with explanatory notes, and an indicator offinancial restatements in the current year (RESTATE). Similar toAshbaugh, LaFond, and Mayhew (2003) and Kim et al. (2012), weinclude an indicator of initial public offerings (IPO), an indicator of

the over-the-counter market (OTC), and an indicator of theemerging stockmarket (ROTC) to control for the needs of additionalaudit and consulting services. An indicator of a Big 4 client (BIG4) isincluded, since previous studies have documented a Big 4 audit feepremium (Choi, Kim, Liu, & Simunic, 2008; DeFond, Francis, &Wong, 2000). In addition to the Big 4 indicator, we also includethe years of the leading audit partner's and the accompanying auditpartner's work experience (CPA1EXP1 and CPA2EXP). The priorliterature suggests an audit fee discount for an initial auditengagement (Huang et al., 2009; Simon & Francis, 1988;Whisenant, Sankaraguruswamy, & Raghunandan, 2003), so weinclude an indicator of initial audit engagement (INITIAL) andcontrol for the number of new audit partners engaged (NEWCPA).Similar to Huang, Liu, Raghunandan, and Rama (2007, 2009) andChen, Sun, and Wu (2010), we include the logarithm of non-auditfees (LNNAF), the ratio of the audited client's total assets over thesum of the total assets of all the audit firm's clients (CIFIRM), theratio of the audited client's total assets over the sum of the totalassets of all the leading audit partner's clients (CICPA1) and theaccompanying audit partner's clients (CICPA2), the number of yearsof audit firm tenure since 1983 (AFTENURE), and the number of

continuous years that the leading audit partner and the accompa-nying audit partner have been engaged with the client (CPA1TE-NURE and CPA2TENURE) to capture client importance and theclient-auditor relationship. We also control for audit firm's andauditor's industry specialization (EXPERT_FIRM, EXPERT_CPA1 andEXPERT_CPA2) given the audit fees premiums for industry special-ized documented in the prior literature (Francis, Reichelt, & Wang,2005; Zerni, 2012). Finally, we control for the potential effects ofmandatory audit fee disclosure on audit pricing by including threeindicators of mandatory audit fee disclosure. That is, a firm isrequired to disclose audit fee information if non-audit fees exceed25% of audit fees (REASON1), a firm changes audit partners leadingto a reduction in audit fees (REASON2), or audit fees are reduced bymore than 15% of the fee for the previous year (REASON3). We alsoinclude year and industry dummies to control for the potential timeand industrial effects on audit fees.

Table 3 reports the main regression analyses. Our audit feeregression models have suitable explanatory power, and theadjusted R-squared is around 54%. We find that women auditpartners charge significantly lower audit fees. Specifically, auditfees are lower if there is at least one women audit partner in theengagement (WOMEN: �0.032, p < 0.01). Similarly, audit fees arenegatively related to the number of women audit partners(WOMENNUM: �0.026, p < 0.01). Consistent with Chin and Chi(2009) and Chi and Chin (2011) that leading auditors are likelymore important than accompanying auditors in audit decisions, we

Table 3Regression results of audit fees and women auditors.

Model Model 1 Model 2 Model 3

Dependent variable LNAF LNAF LNAF

Variables Coefficient p-value Coefficient p-value Coefficient p-value

INTERCEPT 13.620 0.00 13.620 0.00 13.618 0.00WOMEN �0.032 0.01WOMENNUM �0.026 0.01CPA1WOMEN �0.036 0.01CPA2WOMEN �0.016 0.23LNTA �0.008 0.08 �0.008 0.07 �0.008 0.07AGE 0.004 0.00 0.004 0.00 0.004 0.00RECINV �0.073 0.03 �0.074 0.02 �0.075 0.02RELATE 0.110 0.00 0.110 0.00 0.110 0.00FOREIGN 0.092 0.00 0.091 0.00 0.090 0.00LOSS �0.024 0.10 �0.025 0.10 �0.025 0.09CURRENT �0.004 0.27 �0.004 0.29 �0.004 0.29LEV 0.054 0.17 0.055 0.17 0.056 0.16ROA 0.004 0.35 0.004 0.35 0.004 0.36GC 0.205 0.00 0.206 0.00 0.207 0.00UNCLEAN 0.042 0.00 0.042 0.00 0.042 0.00RESTATE 0.110 0.00 0.109 0.00 0.110 0.00IPO �0.357 0.00 �0.358 0.00 �0.358 0.00OTC �0.107 0.00 �0.106 0.00 �0.106 0.00ROTC �0.322 0.00 �0.321 0.00 �0.321 0.00BIG4 0.474 0.00 0.475 0.00 0.476 0.00CPA1EXP 0.004 0.00 0.004 0.00 0.004 0.00CPA2EXP 0.002 0.11 0.002 0.12 0.002 0.08INITIAL �0.051 0.14 �0.051 0.14 �0.051 0.14NEWCPA 0.018 0.16 0.018 0.16 0.019 0.16LNNAF 0.027 0.00 0.027 0.00 0.027 0.00CIFIRM �0.774 0.00 �0.776 0.00 �0.772 0.00CICPA1 0.566 0.00 0.567 0.00 0.568 0.00CICPA2 0.360 0.00 0.359 0.00 0.357 0.00AFTENURE 0.007 0.00 0.007 0.00 0.007 0.00CPA1TENURE 0.000 0.93 0.000 0.95 0.000 0.96CPA2TENURE 0.001 0.84 0.001 0.83 0.001 0.83EXPERT_FIRM 0.003 0.82 0.003 0.82 0.003 0.85EXPERT_CPA1 0.118 0.00 0.117 0.00 0.117 0.00EXPERT_CPA2 0.062 0.11 0.063 0.10 0.063 0.10REASON1 �0.150 0.00 �0.150 0.00 �0.150 0.00REASON2 0.054 0.29 0.053 0.30 0.053 0.31REASON3 �0.005 0.86 �0.006 0.86 �0.006 0.84Year Effects Controlled Controlled ControlledIndustry Effects Controlled Controlled ControlledClustering Firm-Year Firm-Year Firm-YearAdjusted R-Square 54.06% 54.07% 54.07%N 4943 4943 4943


find that when the leading audit partner is women, there is a sig-nificant reduction in audit fees (CPA1WOMEN: �0.036, p < 0.01). Inturns of economic significance, Table 3 suggests that the audit feediscounts for women audit partners are 3.2% when there is at leastone women audit partner, 5.2% when there are two women auditpartners, and 3.6% when the leading audit partner is women.Overall, the results provide consistent evidence to support the viewthat women audit partners are significantly associated with loweraudit fees as compared to men partners.

The results of our control variables are mostly consistent withthe findings of prior studies. The significantly positive coefficientsof AGE, RELATE, and FOREIGN suggest that older and larger firmswith higher complexity pay higher audit fees (p < 0.01), consistentwith the prior studies (Chi et al., 2009; Francis, 1984; Fung et al.,2012; Simunic, 1980). We also find that firms receiving going-concern opinions (GC) and unclean audit opinions (UNCLEAN) andfirms restating financial statements (RESTATE) pay higher audit fees(p < 0.01), consistent with the positive relation between audit riskand audit fees (Simunic, 1980). BIG4 is significantly positive(p < 0.01), which reflects an existing audit fee premium of BIG4auditors (e.g., Francis& Simon,1987; Ferguson& Stokes, 2002), andthe significantly positive coefficient of EXPERT_CPA1 (p < 0.01) also

corresponds to the audit fee premiums for industry specializedauditors (Francis et al., 2005; Zerni, 2012). DeAngelo (1981) sug-gested that incumbent auditors are likely to low-ball initial-yearaudit fees in order to earn future quasi-rents from clients. Likewise,this initial audit fee discount is also discovered in our sample firms,which is supported by a negatively coefficient of INITIAL (p < 0.15)and a positive coefficient of AFTENURE (p < 0.01). Auditor experi-ence is so valuable that it increases the demand for higher qualityaudits (Craswell, Francis, & Taylor, 1995; Ward, Elder, & Kattelus,1994). As we expected, both CPA1EXP and CPA2EXP are signifi-cantly positive (p < 0.15). As expected, when a firm discloses auditfees because of audit firm change and reduction in audit fees(REASON1), audit fees are lower (p < 0.01). We are surprised thatthe coefficient of LNTA is negative, and interpret this finding assuggesting that larger firms are less risky and have higher bargai-ning power, resulting in lower audit fees. However, it is hard toexplain why the coefficient of LOSS is negative.

4.2. Audit fee range

In 2009, Taiwanese firms can decide to report audit fee rangeinstead of the exactly amount of audit fees. To examinewhether our


results are robust to reporting audit fee as ranges, we use orderedlogistic regression models to re-examine the association betweenaudit fees and women audit partners. Audit fee ranges are coded asfollows: 1 for audit fees lower than $2 million, 2 for audit feesbetween $2 million and $4 million, 3 for audit fees between $4million and $6 million, 4 for audit fees between $6 million and $8million, 5 for audit fees between $8 million and $10 million, and 6for audit fees higher than $10 million (NTD). We continue to findthat women audit partners charge lower audit fees than mencounterparts. In particular, the coefficients of WOMEN, WOMEN-NUM, CPA1WOMEN are �0.147, �0.118, and �0.130, respectively,significant at the 0.10 level (untabulated). The untabulated resultsare available from the authors.

4.3. Masculine industries

Because discrimination against women would vary with theextent to which an organization or an industry is masculine or not(Eagly & Carli, 2003; Eagly, Makhijani, & Klonsky, 1992), we alsostudy whether the discrimination against women audit partners ismore severe in traditionally masculine industries. We identifymasculine industries as those where lower than 40% of the firms inthat industry engage with at least one women audit partner,including the electric and machinery industry, the electrical in-dustry, the paper and pulp industry, and the miscellaneous elec-tronic industry. Our results remain unchanged when we identifymasculine industries as those where lower than 50% of the firms in

jDCACCj ¼ b0 þ b1GENDERþ b2LNTAþ b3LOSSþ b4ROAþ b5LEV þ b6CURRENTþb7AGE þ b8ZMJSCORE þ b9OCF þ b10TACC þ b11PE þ b12MBþ b13RAISE þ b14IPOþb15OTC þ b16ROTC þ b17INITIALþ b18NEWCPAþ b19BIG4þb20EXPERT FIRM þ b21EXPERT CPA1þ b22EXPERT CPA2þb23AFTENURE þ b24CPA1TENURE þ b25CPA2TENURE þ b26CIFIRMþb27CICPA1þ b28CICPA2þ b29CPA1EXP þ b30CPA2EXP þ b31RESTATEþb32UNCLEAN þ b33GC þ YEARþ INDUSTRY þ 3

(2)

LNRLAG ¼ b0 þ b1GENDERþ b2LNTAþ b3LOSSþ b4ROAþ b5LEV þ b6CURRENTþb7AGE þ b8ZMJSCORE þ b9OCF þ b10TACC þ b11PE þ b12MBþ b13RAISE þ b14IPOþb15OTC þ b16ROTC þ b17INITIALþ b18NEWCPAþ b19BIG4þb20EXPERT FIRM þ b21EXPERT CPA1þ b22EXPERT CPA2þb23AFTENURE þ b24CPA1TENURE þ b25CPA2TENURE þ b26CIFIRMþb27CICPA1þ b28CICPA2þ b29CPA1EXP þ b30CPA2EXP þ b31RESTATEþb32UNCLEAN þ b33GC þ YEARþ INDUSTRY þ 3

(3)

that industry engage with at least one women audit partner. Theproxies for women auditors are interacted with the indicator ofmasculine industries, MIND. MIND equals one if a firm operates inone of the masculine industries discussed above. If discriminationis more severe in masculine industries, the interaction term of theproxies for women partners and masculine industry is expected tobe negative.

The results are presented in Table 4.We find significant evidencethat the negative relation between women audit partner and auditfees is more severe in masculine industries. Specifically, the audit

fees are further lower in the masculine industries discussed abovewhen there is at least onewomenaudit partner,when thenumberofwomen audit partner increases, andwhen the leading audit partneris women. The coefficient of WOMEN*MIND, WOMENNUM*MIND,and CPA1WOMEN*MIND are �0.095, �0.075, and �0.169, respec-tively (p < 0.05). To illustrate the economic significance, Table 4suggests that the audit fee discounts for women audit partners in-crease around 9.5%e16.9% in masculine industries. In sum, the re-sults indicate that women audit partners charge further lower auditfees in masculine industries.

4.4. Women audit partner and audit quality

There are at least three reasons why women audit partnerscharge lower audit fees than men audit partners, including (1)discrimination against women auditors, (2) the poor audit qualityprovided by women audit partners and (3) the efficiency ofwomen audit partners. To analyze the possibility that the lattertwo reasons explain our findings, we examine the associationbetween audit quality, measured as client earnings quality andaudit efficiency, and women audit partners. We follow priorstudies (e.g. Al-Ajmi, 2008; Bamber, Bamber, & Schoderbek, 1993;Chen et al., 2010, 2011; Chi & Chin, 2011; Chin & Chi, 2009;Henderson & Kaplan, 2000; Knechel & Payne, 2001; Lee,Mande, & Son, 2008; Leventis & Weetman, 2004; Reichelt &Wang, 2010) construct the audit quality regression models asfollows.

jDCACCj is the absolute value of discretionary current accruals(DCACC). As in Chi and Chin (2011), we measure DCACC by esti-mating the following model for each year-industry grouping.

CACC ¼ b0 þ b1INVERSEAT þ b2DSALE þ b3ROAþ 3 (4)CACC is current accruals, defined as net income before extraor-

dinary items plus depreciation and amortization minus operatingcash flow, divided by lagged total assets. INVERSEAT is 1 divided bylagged assets. DSALE is the change in sales divided by lagged assets.ROA is net income divided by lagged assets. We do not deduct the

Table 4Regression results of audit fees, women auditors, and industrial effects.


Dependent variable LNAF LNAF LNAF


INTERCEPT 13.616 0.00 13.614 0.00 13.611 0.00WOMEN �0.031 0.02WOMEN*MIND �0.095 0.03WOMENNUM �0.026 0.01WOMENNUM*MIND �0.075 0.03CPA1WOMEN �0.031 0.03CPA1WOMEN*MIND �0.169 0.00CPA2WOMEN �0.021 0.14CPA2WOMEN*MIND 0.009 0.85MIND �0.029 0.28 �0.032 0.22 �0.032 0.22LNTA �0.008 0.09 �0.008 0.08 �0.008 0.08AGE 0.002 0.00 0.002 0.00 0.002 0.00RECINV �0.088 0.01 �0.089 0.01 �0.089 0.01RELATE 0.112 0.00 0.112 0.00 0.112 0.00FOREIGN 0.197 0.00 0.196 0.00 0.195 0.00LOSS �0.031 0.05 �0.031 0.04 �0.031 0.05CURRENT �0.005 0.10 �0.005 0.11 �0.005 0.12LEV 0.055 0.18 0.056 0.17 0.059 0.15ROA 0.003 0.46 0.003 0.46 0.003 0.46GC 0.113 0.01 0.115 0.01 0.115 0.01UNCLEAN 0.048 0.00 0.048 0.00 0.048 0.00RESTATE 0.076 0.04 0.076 0.04 0.076 0.04IPO �0.377 0.00 �0.378 0.00 �0.377 0.00OTC �0.143 0.00 �0.141 0.00 �0.141 0.00ROTC �0.377 0.00 �0.375 0.00 �0.374 0.00BIG4 0.511 0.00 0.513 0.00 0.515 0.00CPA1EXP 0.003 0.01 0.003 0.01 0.003 0.01CPA2EXP 0.002 0.09 0.002 0.10 0.002 0.07INITIAL �0.066 0.06 �0.065 0.07 �0.065 0.07NEWCPA 0.024 0.08 0.024 0.08 0.024 0.07LNNAF 0.029 0.00 0.029 0.00 0.029 0.00CIFIRM �0.788 0.00 �0.788 0.00 �0.787 0.00CICPA1 0.563 0.00 0.564 0.00 0.568 0.00CICPA2 0.379 0.00 0.378 0.00 0.374 0.00AFTENURE 0.005 0.00 0.005 0.00 0.005 0.00CPA1TENURE 0.000 0.93 0.000 0.96 0.000 1.00CPA2TENURE 0.005 0.27 0.005 0.27 0.005 0.27EXPERT_FIRM �0.003 0.84 �0.003 0.83 �0.003 0.83EXPERT_CPA1 0.122 0.00 0.121 0.00 0.120 0.00EXPERT_CPA2 0.071 0.08 0.071 0.08 0.071 0.08REASON1 �0.144 0.00 �0.144 0.00 �0.145 0.00REASON2 0.092 0.09 0.091 0.10 0.092 0.09REASON3 �0.001 0.98 �0.001 0.97 �0.003 0.93Year Effects Controlled Controlled ControlledIndustry Effects Controlled Controlled ControlledClustering Firm-Year Firm-Year Firm-YearAdjusted R-Square 51.56% 51.56% 51.61%N 4943 4943 4943


change in receivables fromDSALE, andwe control for current ROA asKothari, Leone, & Wasley (2005). Discretionary current accruals(DCACC) are the residual values derived (4). LNRLAG is auditreporting lags, defined as the logarithm of the number of days be-tween the fiscal year end and the ending date of auditor field work(e.g. Al-Ajmi, 2008; Lee et al., 2008; Leventis & Weetman, 2004). Ifthe lower audit fees forwomen audit partners are resulted from thatwomen audit partners provide poor audit quality or that womenaudit partners are more efficient, we predict b1 to be positive in (2)and negative in (3).

We control for many firm and audit characteristics influencingclient earnings quality and audit reporting lags. We control for firmsize effects by including the logarithm of total assets (LNTA) and thenumber of years since the firm was established (AGE) as in Myers,Myers, and Omer (2003) and Menon and Williams (2004). Firmperformance and the likelihood of financial distress are controlledby including an indicator of net loss (LOSS), returns on assets (ROA),

leverage (LEV), current ratio (CURRENT), and financial risk scores(ZMJSCORE) as in Chin and Chi (2009) and Chi and Chin (2011).Following Carcello, Hermanson, and Huss (1995) and Liu andWang(2005), ZMJSCORE is computed as �4.803 � 3.6 � (net income/totalassets) þ 5.4 � (total debt/total assets) � 0.1 � (current assets/current liabilities). Higher ZMJSCORE indicates higher likelihoodof bankruptcy. Lagged total accruals divided by total assets (TACC)and operating cash flows divided by total assets (OCF) arecontrolled because of their negative association with the currentaccruals (Ashbaugh et al., 2003; Sloan, 1996). Firm growth, marketvaluation, and financing activities are controlled by includingprice-earnings ratio (PE), market-to-book ratio (MB), and thefinancing cash flows divided by total assets (RAISE) as in theprior literature (e.g. Chin & Chi, 2009; Jagadison, Aier, Gunlock, &Lee, 2005; Richardson, Tuna, & Wu, 2003). The superior auditquality of the Big 4 audit firms (BIG4) and industry specialists(EXPERT_FIRM, EXPERT_CPA1, and EXPERT_CPA2) are controlled

Table 5Descriptive statistics of audit quality model (N ¼ 3872).

Variables Mean STD Q1 Median Q3

Absolute value of discretionary current accruals (jDCACCj) 0.09 0.13 0.02 0.05 0.09Logarithm of audit reporting lags (LNRLAG) 4.19 0.39 4.04 4.30 4.44Logarithm of total assets (LNTA) 21.75 1.53 20.70 21.56 22.59Loss (LOSS) 0.25 0.43 0.00 0.00 0.00Returns on assets (ROA) 0.28 1.46 0.00 0.02 0.14Leverage (LEV) 0.44 0.21 0.29 0.44 0.57Current ratio (CURRENT) 2.46 2.33 1.27 1.76 2.71Firm age since setup (AGE) 23.63 12.29 14.00 22.00 32.00Financial distress scores (ZMJSCORE) �2.73 1.55 �3.73 �2.74 �1.89Operating cash flows (OCF) 0.07 0.12 0.01 0.07 0.13Lagged total accruals (TACC) 0.00 0.10 �0.04 0.01 0.05Price-to-earnings ratio (PE) 36.04 149.78 0.13 6.67 23.54Market-to-book ratio (MB) 2.94 3.05 1.13 2.02 3.55Funds raised (RAISE) 0.02 0.16 �0.06 �0.01 0.07Initial public offerings (IPO) 0.01 0.11 0.00 0.00 0.00Over the counter (OTC) 0.33 0.47 0.00 0.00 1.00Emerging stock (ROTC) 0.07 0.26 0.00 0.00 0.00Initial audit engagements (INITIAL) 0.06 0.23 0.00 0.00 0.00Number of new auditors (NEWCPA) 0.53 0.67 0.00 0.00 1.00Big 4 audit firms (BIG4) 0.84 0.36 1.00 1.00 1.00Audit firm industry specialization (EXPERT_FIRM) 0.30 0.46 0.00 0.00 1.00CPA1 industry specialization (EXPERT_CPA1) 0.02 0.15 0.00 0.00 0.00CPA2 industry specialization (EXPERT_CPA2) 0.02 0.14 0.00 0.00 0.00Audit firm tenure (AFTENURE) 11.28 6.71 6.00 11.00 16.00CPA1 tenure (CPA1TENURE) 3.02 1.77 2.00 3.00 4.00CPA2 tenure (CPA2TENURE) 2.66 1.57 1.00 2.00 4.00Client importance for audit firm (CIFIRM) 0.02 0.09 0.00 0.00 0.00Client importance for CPA1 (CICPA1) 0.12 0.20 0.01 0.03 0.12Client importance for CPA2 (CICPA2) 0.12 0.21 0.01 0.03 0.11CPA1 experience (CPA1EXP) 11.85 5.96 7.00 12.00 16.00CPA2 experience (CPA2EXP) 11.26 6.27 6.00 11.00 16.00Restatement (RESTATE) 0.03 0.17 0.00 0.00 0.00Unclean audit opinion (UNCLEAN) 0.66 0.47 0.00 1.00 1.00Going concern opinion (GC) 0.03 0.16 0.00 0.00 0.00


(e.g. Reichelt & Wang, 2010). Audit firm (AFTENURE) andauditor tenure (CPA1TENURE and CPA2TENURE) as well asinitial audit engagement (INITIAL) and the number of newaudit partners (NEWCPA) are also controlled given the fact thataudit quality would be improved by longer client-auditor rela-tionship (Carey & Simnett, 2006; Davis, Soo, & Trompeter, 2009).We control for client importance (CIFIRM, CICPA1, and CICPA2)since Chen et al. (2010) suggest that client importance may influ-ence auditor independence and thus audit quality. As in the auditfee models, we control for auditor experience (CPA1EXP andCPA2EXP), financial restatement (RESTATE), unclean audit opinions(UNCLEAN), going-concern opinions (GC), and a firm's listing status(IPO, OTC, and ROTC). Year and industry effects are also controlledfor. Likewise, all the continuous variables are winsorized at 1%and 99%.

In Table 5, we provide the descriptive statistics of the variablesused in (2) and (3). The sample size decreases to 3872 because ofmissing necessary data. The mean and median values of discre-tionary current accruals (DCACC) are 0.09 and 0.05, and that of theaudit reporting lags in logarithm (LNRLAG) are 4.19 and 4.30. Onaverage, ZMJSCORE is �2.73, operating cash flows (OCF) account for7% of total assets, PE is 36.04, MB is 2.94, and the cash flows fromfinancing activities (RAISE) are 2% of total assets. Other variables aresimilar as in Table 2.

We then classify our sample firms into (1) firms with no womenaudit partners (N ¼ 1832) and (2) firms with at least one womenaudit partners (N ¼ 2040), and compare their differences in firmand audit characteristics (untabulated). We find that the clientswith at least one women audit partner (WOMEN ¼ 1) have lowerabsolute value of discretionary current accruals (jDCACCj) thanclients with no women audit partners (WOMEN ¼ 0), and that

women audit partners are associated with longer audit reportinglags (LNRLAG). These findings provide preliminary evidence thatour previous results of the negative association between audit feesand women auditors are less likely driven by the poor audit qualityand shorter reporting lags by women audit partners. With respectto control variables, we find that clients with at least one womenaudit partners are older (AGE), involve in fewer initial audit en-gagements (INITIAL), have longer audit firm tenure (AFTENURE), andare less likely to be audited by industry specialized accompanyingauditors (EXPERT_CPA2).

Table 6 reports the regression analyses of audit quality andwomen audit partner. The dependent variable is the absolute valueof discretionary current accruals (jDCACCj) in Panel A and is thelogarithm of audit reporting lags (LNRLAG) in Panel B. The explan-atory power of these regression models (26% in Panel A and 23% inPanel B) is comparable to that in the prior studies (e.g. 16% in Chi &Chin, 2011 and 27% in Krishnan & Yang, 2009). In Panel A, we findthat clients audited bywomen audit partners report better earningsquality. In particular, the absolute value of discretionary currentaccruals (jDCACCj) is lower if there is at least one women auditpartner in the engagement (WOMEN: �0.007, p < 0.05). Likewise,the number of women audit partners is associated with betterearnings quality (WOMENNUM:�0.005, p < 0.05). As the findings inTable 2, we find that when the leading audit partner is women, theclient earnings quality is higher (CPA1WOMEN: �0.011, p < 0.01),suggesting the importance of the leading auditors in audit en-gagements. These results indicate that women auditors may pro-vide better audit quality, in terms of higher client earnings quality,than men auditors, and suggest that the negative relation betweenaudit fees and women auditors may not be explained by the su-perior audit quality of men auditors.

Table 6Regression results of audit quality and women auditors.

Panel A: Earnings quality and women auditors


Dependent variable jDCACCj jDCACCj jDCACCjVariables Coefficient p-value Coefficient p-value Coefficient p-value

INTERCEPT 0.046 0.23 0.045 0.23 0.044 0.25WOMEN �0.007 0.04WOMENNUM �0.005 0.04CPA1WOMEN �0.011 0.00CPA2WOMEN 0.000 0.95LNTA 0.003 0.05 0.003 0.04 0.003 0.04LOSS 0.002 0.66 0.002 0.68 0.002 0.68ROA �0.001 0.22 �0.001 0.21 �0.001 0.19LEV �0.029 0.28 �0.029 0.28 �0.029 0.28CURRENT �0.001 0.18 �0.001 0.19 �0.001 0.20AGE 0.000 0.02 0.000 0.02 0.000 0.02ZMJSCORE 0.001 0.76 0.001 0.75 0.001 0.75OCF �0.045 0.18 �0.045 0.18 �0.045 0.17TACC �0.012 0.69 �0.012 0.69 �0.012 0.68PE 0.000 0.12 0.000 0.11 0.000 0.11MB 0.005 0.00 0.005 0.00 0.005 0.00RAISE 0.132 0.00 0.133 0.00 0.133 0.00IPO 0.068 0.03 0.068 0.03 0.067 0.03OTC 0.017 0.00 0.017 0.00 0.017 0.00ROTC 0.002 0.78 0.002 0.79 0.002 0.79INITIAL 0.024 0.07 0.024 0.07 0.024 0.07NEWCPA �0.002 0.66 �0.002 0.66 �0.002 0.67BIG4 �0.014 0.08 �0.014 0.08 �0.013 0.10EXPERT_FIRM �0.011 0.01 �0.010 0.01 �0.011 0.01EXPERT_CPA1 0.004 0.79 0.004 0.80 0.005 0.78EXPERT_CPA2 �0.009 0.49 �0.009 0.50 �0.009 0.50AFTENURE 0.000 0.50 0.000 0.48 0.000 0.48CPA1TENURE �0.002 0.05 �0.002 0.06 �0.002 0.06CPA2TENURE 0.000 0.76 0.000 0.75 0.000 0.74CIFIRM 0.017 0.61 0.017 0.61 0.020 0.56CICPA1 �0.032 0.01 �0.032 0.01 �0.032 0.01CICPA2 �0.004 0.76 �0.004 0.75 �0.006 0.68CPA1EXP 0.000 0.98 0.000 0.97 0.000 0.73CPA2EXP 0.000 0.99 0.000 0.99 0.000 0.70RESTATE �0.007 0.62 �0.007 0.61 �0.007 0.62UNCLEAN �0.009 0.04 �0.009 0.04 �0.009 0.04GC 0.028 0.20 0.028 0.20 0.028 0.20

Year Effects Controlled Controlled ControlledIndustry Effects Controlled Controlled ControlledClustering Firm-Year Firm-Year Firm-YearAdjusted R-Square 26.20% 26.20% 26.24%N 3872 3872 3872

Panel B: Audit reporting lags and women auditors


Dependent variable LNRLAG LNRLAG LNRLAG


INTERCEPT 4.202 0.00 4.211 0.00 4.214 0.00WOMEN 0.046 0.00WOMENNUM 0.027 0.00CPA1WOMEN 0.042 0.00CPA2WOMEN 0.012 0.33LNTA 0.004 0.29 0.004 0.30 0.004 0.31LOSS �0.013 0.46 �0.012 0.50 �0.012 0.50ROA �0.005 0.23 �0.005 0.26 �0.004 0.27LEV �0.098 0.25 �0.097 0.25 �0.097 0.26CURRENT 0.001 0.71 0.001 0.79 0.001 0.80AGE 0.005 0.00 0.005 0.00 0.005 0.00ZMJSCORE 0.008 0.54 0.007 0.57 0.007 0.58OCF �0.415 0.00 �0.417 0.00 �0.415 0.00TACC 0.009 0.90 0.009 0.90 0.010 0.88PE 0.000 0.04 0.000 0.04 0.000 0.04MB �0.009 0.00 �0.009 0.00 �0.009 0.00RAISE 0.024 0.58 0.022 0.62 0.021 0.63IPO 0.039 0.50 0.039 0.50 0.040 0.49OTC 0.026 0.05 0.026 0.05 0.027 0.05ROTC 0.157 0.00 0.158 0.00 0.158 0.00

(continued on next page)


Table 6 (continued )

Panel B: Audit reporting lags and women auditors


Dependent variable LNRLAG LNRLAG LNRLAG


INITIAL �0.022 0.51 �0.022 0.50 �0.022 0.50NEWCPA 0.008 0.50 0.009 0.49 0.008 0.50BIG4 0.123 0.00 0.123 0.00 0.121 0.00EXPERT_FIRM �0.101 0.00 �0.102 0.00 �0.101 0.00EXPERT_CPA1 �0.082 0.07 �0.082 0.08 �0.083 0.07EXPERT_CPA2 �0.023 0.65 �0.023 0.64 �0.023 0.64AFTENURE 0.000 0.72 0.000 0.72 0.000 0.72CPA1TENURE 0.000 0.98 0.000 0.98 0.000 0.96CPA2TENURE 0.000 0.99 0.000 0.97 0.000 0.97CIFIRM 0.059 0.54 0.060 0.53 0.053 0.58CICPA1 �0.063 0.13 �0.063 0.13 �0.065 0.12CICPA2 0.025 0.49 0.026 0.47 0.030 0.41CPA1EXP �0.002 0.04 �0.002 0.04 �0.002 0.08CPA2EXP 0.000 0.71 0.000 0.70 �0.001 0.46RESTATE 0.144 0.00 0.145 0.00 0.145 0.00UNCLEAN 0.060 0.00 0.060 0.00 0.060 0.00GC 0.261 0.00 0.261 0.00 0.261 0.00

Year Effects Controlled Controlled ControlledIndustry Effects Controlled Controlled ControlledClustering Firm-Year Firm-Year Firm-YearAdjusted R-Square 22.94% 22.79% 22.83%N 3872 3872 3872


In Panel B, we find that women audit partners are more con-servative in that they take more time to collect audit evidence,resulting in longer audit reporting lags (LNRLAG). Specifically, theaudit reporting lags are significantly longer when there is at leastone women audit partners (WOMEN: 0.046, p < 0.01). Similarly, theassociation between audit reporting lags and the number ofwomen audit partners is also positive and significant (WOMEN-NUM: 0.027, p< 0.01).We further find that the leading auditors playa more important role in determining audit reporting lags (CPA1-WOMEN: 0.042, p < 0.05). These findings show that women audi-tors are related to longer audit reporting lags, and suggest that thenegative correlation between audit fees and women auditors is notdriven by shorter audit reporting lags required by women auditpartners.

With respect to control variables, we find that firms audited bythe Big 4 audit firms (BIG4) and industry specialized audit firms(EXPERT_FIRM), firms with longer audit firm tenure (AFTENURE),and firms receiving non-going-concern opinions (GC) are associ-ated with higher earnings quality (jDCACCj), consistent with Chiand Chin (2011). We also find that firms audited by the industryspecialized audit firms (EXPERT_FIRM) and leading auditors(EXPERT_CPA1), and firms audited by more experienced leadingauditors (CPA1EXP) have shorting audit reporting lags, whereasfirms restating financial statements (RESTATE) and receiving un-clean audit opinions and going-concern opinions (GC) have longeraudit reporting lags, consistent with the previous studies (e.g. Leeet al., 2008; Krishnan & Yang, 2009; Habib & Bhuiyan, 2011).

Overall, the results in Table 6 suggest that it is unlikely that thedifferences in audit quality andaudit reporting lags betweenwomenandmenaudit partners drive ourfinding thatwomen audit partnerscharge lower audit fees than men colleagues. Instead, we find thatwomen audit partners are associated with better client earningsquality and longer audit reporting lags, which should increase theaudit fees chargedbywomenaudit partners. Therefore,weconcludethat the reasons whywomen audit partners charge lower audit feesthan men audit partners in Taiwan are likely due to the masculineaudit industry and the discrimination againstwomen. Nevertheless,we acknowledge that there would be other explanations for the

negative relation between women audit partners and audit fees,which deserve further research in the future.

As an additional analysis, we augment our audit fee models bycontrolling for client earnings quality and audit reporting lags. Wefind that the negative relation between women audit partners andaudit fees remains significant when we include jDCACCj andLNRLAG in the regression models (untabulated). In particular, thecoefficients of WOMEN, WOMENNUM, and CPA1WOMENare �0.031, �0.025, and �0.033, respectively (p < 0.05). Therefore,it is less likely that the negative correlation between audit fees andwomen auditors is driven by the differences in audit quality andaudit efficiency between women and men audit partners.

4.5. Differences between firms with and without audit fee data

Because audit fees are required under certain situations inTaiwan, it is likely that there is sample bias in this paper, whichmayhave great influence on our results. However, we argue that as longas there is no significant difference between clients with andwithout women audit partners, such bias should not significantlyinfluence our findings. Moreover, it is unclear ex ante whether suchsample bias will lead to a positive or a negative relation betweenwomen audit partners and audit fees. As discussed above, there arefew differences in firm and audit characteristics between clientswith and without women audit partners. Rather, untabulated re-sults suggests that clients with women audit partners are older,more complex, more likely to be audited by the Big 4 audit firms,involve in fewer initial audit engagements, and have longer auditfirm tenure, which should lead to higher audit fees. Furthermore,there are no significant differences in firm size, auditor speciali-zation, and the reasons for audit fee disclosure. Consistently, Liaoet al. (2012) indicate that there is an increase in the number ofTaiwanese firms disclosing audit fees after 2009 because of thedemand for the IFRS adoption service provided by audit firms andbecause of the encouragement of voluntarily disclosing audit fees.They compare the differences in several firm and audit character-istics between firms disclosing audit fees under certain situations(2002e2008) and firms disclosing audit fees voluntarily


(2009e2010), and conclude that there is no significant structuralchange in the determinants of audit fees and that the problem ofselection bias is less likely to be severe. Therefore, it is less likelythat our results are significantly biased by the sample bias. Never-theless, we construct a sample consisting of firms with (N ¼ 4943)and without (N ¼ 7447) audit fee data, and compare their firm andaudit characteristics.

The untabulated results show that there are significant differ-ences in firm and audit characteristics between firms with andwithout audit fee data. In particular, firms with audit fee data aremore likely to be audited by women auditors (WOMEN, WOMEN-NUM, CPA1WOMEN, and CPA2WOMEN), older (AGE), more complex(RELATE) and export-oriented (FOREIGN), stronger in financialconditions (CURRENT and LEV), less likely to restate financialstatements (RESTATE), more likely to receive unclean audit opinions(UNCLEAN), consist of more newly listed firms (IPO, OTC, and ROTC),are more likely to be audited by the Big 4 audit firms (BIG4) andmore experienced auditors (CPA1EXP and CPA2EXP), consists offewer initial audit engagements (INITIAL) and new audit partners(NEWCPA), have higher non-audit fees (LNNAF), have longer auditfirm tenure (AFTENURE) but shorter leading auditor tenure (CPA1-TENURE), and are more likely to be audited by industry specializedaudit firms (EXPERT_FIRM).

As a robustness check, we control for firm fixed effects in ouraudit fee models to alleviate the concern that our results are drivenby some omitted variables. The adjusted R-square increases sub-stantially to 90% when we control for firm fixed effects, and wecontinue to find that women audit partners are associated withlower audit fees (untabulated). Specifically, audit fees are signifi-cantly lower when there is at least one women auditor in theengagement (WOMEN: �0.019, p < 0.10). Similarly, audit fees aresignificantly and negatively related to the number of women auditpartners (WOMENNUM: �0.016, p < 0.10). We also continue to findthat the leading auditors are more important in audit engagements.Audit fees are significantly lower when the leading auditor iswomen (CPA1WOMEN: �0.028, p < 0.05). Therefore, we concludethat it is less likely that the sample bias and the omitted variablesresult in our findings that women audit partners charge lower auditfees thanmen audit partners. Nevertheless, we cannot fully rule outthese possibilities, and acknowledge that our results should beexplained with cautions.

4.6. Sensitivity analysis

Our results are robust to several sensitivity analyses. First, inorder to totally exclude the influence of Big 4 audit fee premiums,we exclude non-Big 4 clients in additional regression tests. All co-efficients of our women audit partner proxies continue to benegative, and mostly significant. Second, as discussed earlier, firmspublicly disclose audit fees for different reasons. Firms that arerequired to disclose audit fees (Reasons 1, 2, and 3) may havedistinct characteristics from firms that disclose audit fees volun-tarily (Reason 4). To prevent our results from being driven by thesedifferent characteristics, we conduct separate regression analysesfor the two types of firms, and obtain consistent results. Third, weexclude observations from the electronics industry and obtainrobust evidence. Finally, we employ additional measures of womenaudit partners. Specifically, these measures consider (1) the dif-ferential effect between the leading and accompanying auditpartners, (2) the composition of women audit partners, and (3) thedifferential effect between one and twowomen audit partners. Ourresults are robust to these different measures. Overall, we findrobust evidence that audit fees are significantly lower for womenaudit partners, and this discrimination against women audit part-ners is more pronounced in masculine industries and cannot be

explained by the differences in audit quality and audit reportinglags between women and men audit partners.

5. Conclusion

This paper examines whether women audit partners earn loweraudit fees by using a sample of public companies in Taiwan.We finda significant association between women audit partner and auditfees, after controlling for the client attributes. This suggests thatdiscrimination against women audit partners currently exists inTaiwan. In addition, the discrimination against women is moresevere in masculine industries. Moreover, we provide evidence thatit is unlikely that our results are driven by the differences in auditquality and audit reporting lags between women and men auditpartners and by the sample bias and omitted variables. The resultsprovide exploratory insights into the question of how the auditpartner's sex may affect audit pricing. Our results should be of in-terest to audit firms in designing human resource programs andcompensation packages and to regulators in setting labor policies.

Two relevant studies investigating companies in Belgium and inthree Nordic countries found that women audit partners earnhigher audit fees, perhaps due to higher independence (Hardies,Breesch, & Branson, 2010), better diligence, and less over-confidence (Ittonen and Peni, 2012). These findings suggest that sexstereotypes may vary across cultures and that discriminationagainst women in the workplace is less severe in Northern Euro-pean countries as compared to Taiwan, where Confucianism ad-vocates the masculine social value that women should stay at homeand be responsible for the household, while men are the bread-winners and leaders of the family (Chan et al., 2002; Yang et al.,2013). For example, Penner and Paret (2008) suggested that Asiankindergarten boys perform best on entering kindergartens, whileLatino kindergarten girls perform better than Latino boys. WithU.S., U.K. and German data, Schein and Mueller (1992) supportedthe view that sex differences differ across cultures. They found thatGerman women and German men were considered to have almostthe same ability to become managers, while, compared to Germanwomen, British women were found to be considered to be lesslikely to serve as managers. Besides, this study indicated that U.S.residents do not express such sex stereotypes in regard to mana-gerial positions, and both women and men are viewed as equallycapable of becoming managers.

Research related to audit fee differentials in the public ac-counting profession is likely to impact public policy in the yearsahead. One important question is whether women audit partnersearn less just because they are discriminated. Our results indicatethat, while a pay gap between women and men clearly exists, theextent of discrimination is neither consistent from industry to in-dustry, nor from audit partner to audit partner. Since the pattern ofaudit fee differences appears to be sufficiently complex, policy-makers will find it necessary to approach the problem more ho-listically. Clearly, there is a need for additional research on thisissue.

Our study is subject to a number of limitations. First, caution isneeded when applying the findings in this paper to other countries,since the culture and the development of welfare will differ inter-nationally. However, our results suggest that international regula-tors should consider mandatory disclosure of audit partnerinformation including sex, whichmay effectively signal the severityof discrimination against women. Second, the explanatory power ofaudit fee models in Taiwan is usually lower (Chen & Wu, 2004)when compared to the adjusted R-square of U.S. audit fee studies. Itcannot be ruled out that our regressions can be made significantlybetter by the inclusion of some other omitted variables. Finally,although we have shown some evidence that the lower audit fees


for women auditors should not be driven by the differences in auditquality and audit reporting lags, we cannot fully rule out the pos-sibility that other factors explain our findings.

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HOSTED BY Asia Paciﬁc Management Reviewir.lib.ncku.edu.tw/bitstream/987654321/166526/1/6010515015-0000… · article info Article history: Received 27 November 2014 Accepted 11