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Abstract
We examine the relation between the scale and scope of an individual auditor’s client portfolio and audit quality. Using a sample of auditor-years for the period of 2001–2016 from China, where the personal identities of signing auditors are publicly disclosed, we find that auditors with large client portfolio scale (measured by an auditor’s total audit fees from clients) provide higher quality audits (measured by discretionary accruals and the likelihood of issuing modified audit opinions). However, auditors with large client portfolio scope (measured by the number of industries where clients are located) provide lower quality audits. Further analyses indicate that auditors of higher ability and reputation tend to have larger client scales and wider client scopes. Overall, our results suggest that, at the individual auditor level, the scale of the client portfolio conveys the auditor’s ability, and given the scale, the industry and geographic scope of clients reflects the auditor’s workload.
JEL:
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 We find little evidence that auditors engaging with clients located in different cities also provide lower quality audits.
2 An alternative explanation could be that the sample size for Big N auditors is relatively small, so we may not observe the effects due to lack of power. We thank an anonymous reviewer for providing this insight.
3 While in our main analyses, we measure the scope of an auditor’s client portfolio by the number of industries and geographic locations served by the auditor, we also use the number of public clients as an alternative proxy (in unreported analyses). The average number of public clients audited by an auditor is two. Similar to Goodwin and Wu (Citation2016) and Burke et al. (Citation2019), we find no significant association between the number of public clients of each auditor and quality.
4 In some models or subsamples, they find a positive association between the number of engagements and compensation, while in other models or subsamples they find a negative association. They conclude that it is the client type, rather than the number of clients, that influences compensation.
5 Zerni (Citation2012) includes a partner’s client portfolio size as a control variable (in models to test for the effect of partner specialisation), measured either by the natural log of audited total assets or the number of engagements, and finds its coefficient to be insignificant. A key difference is that Zerni’s Swedish sample comprises individual auditors from Big N audit firms, whereas our Chinese sample is predominantly made up of auditors from non-Big N firms. As mentioned above, our results are primarily driven by non-Big N audit firms.
6 In related fields, studies investigating the director busyness similarly reach inconsistent conclusions. One stream of research supports the reputation hypotheses, arguing that busyness is viewed as a good signal, while the other stream supports the overwork hypotheses, where busyness is viewed as a bad one (e.g. Ferris et al. Citation2003).
7 Knechel et al. (Citation2013) similarly recognise that it is the type rather than the number of clients per se that influences compensation.
8 Anecdotal evidence through informal interviews with partners in Chinese audit firms and online search also suggest that similar to audit fee structure in western countries, audit fees of most audit firms in China are also based on the billing rates and budgeted hours.
9 Based on informal conversations with auditors of a large Chinese audit firm, partners at the firm receive 2% of the fees from each contract they secure, and engagement auditors who perform the audit receive about 8%.
10 Carrera et al. (Citation2003) posit that audit firms diversify their client bases due to (1) concern about litigation risk, (2) market saturation and the search for new clients, (3) the unwillingness of clients to share auditors with competitors, and (4) a reduction in the cost of entering new client industries because of the resource sharing within international accounting networks.
11 Discretionary accruals are the residual from the modified Jones model, adjusted by a performance-matched firm (Dechow et al. Citation1995, Kothari et al. Citation2005).
12 We take the natural log transformation because the proportion of clients receiving modified audit opinions for each auditor is a number between 0 and 1. Results do not change if we use the raw proportion.
13 We add one here since some auditors have no clients receiving modified audit opinions, so the proportion is zero.
14 This is only based on nonfinancial clients of each auditor because accrual models do not apply to the financial industries well.
15 This information is not available after 2015. For year 2016, we get the auditor’s birth date from prior-year’s data we collected.
16 In China, one may get a CPA license without a degree in accounting as long as he or she passes the CPA examination and has some industry experience.
17 In China, a signing auditor is not necessarily a partner but is a CPA meeting certain criterion; Untabulated information based on audit firm ranking data in China document that Big N firms have a much higher staff-to-CPA ratio (STAFF_CPA: 5.616 versus 2.150) than non-Big N firms, indicating that Big N firms have more resources than do non-Big N firms. Information about the rankings of Chinese accounting firms is on the website http://cmispub.cicpa.org.cn/cicpa2_web/public/queryofficezhpj.shtml.
18 RMB is the Chinese currency.
19 Our measure of the industry scope of an auditor’s client portfolio (CPA_SCOPE_INDNUM) does not merely capture the (opposite) effect of auditor industry specialisation. First, we have already controlled for individual auditors’ industry specialisation (CPA_INDSPE) in the regression. Second, these two variables actually have a positive correlation (r = 0.104) in our sample. A positive correlation could be possible because capable auditors who specialize in more than one industry may also tend to have clients in multiple industries at the same time.
20 The original proportion and log transformed proportion are quite similar here.
21 We thank an anonymous reviewer for suggesting this alternative measure.
22 We thank an anonymous reviewer for suggesting this analysis.