Audit office client portfolios and misstatements. Erik L. Beardsley University of Notre Dame

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1 Audit office client portfolios and misstatements Erik L. Beardsley University of Notre Dame Nathan C. Goldman University of Texas at Dallas Thomas C. Omer* University of Nebraska-Lincoln September 2016 *Corresponding author School of Accountancy University of Nebraska-Lincoln Lincoln, NE Phone: Acknowledgments: We thank Brant Christensen, Katharine Drake, Matthew Ege (Discussant), Kathleen Harris, Matthew Josefy, Phil Lamoreaux, Sean McCarthy, Richard Scoresby, Kecia Smith, Dechun Wang, Rob Whited, and workshop participants at the University of Toronto, Arizona State University, Florida State University, Texas A&M University, and the 2015 Audit Midyear Meeting for helpful comments. Erik Beardsley gratefully acknowledges financial support from Mays Business School and the AICPA through the Accounting Doctoral Scholarship. Nathan Goldman acknowledges financial support from the Eller College of Management at the University of Arizona. Thomas Omer acknowledges funding from the Delmar Lienemann Sr. Chair of Accounting at the University of Nebraska-Lincoln.

2 Audit office client portfolios and misstatements Abstract: This study examines whether, and under what circumstances, the composition of audit office client portfolios is related to audit quality. To do so, we examine the likelihood of client financial statement misstatements for audit offices with a homogenous client base ( focused client portfolios), a heterogenous client base ( diverse client portfolios) and a mixed client base. Our results indicate that audit offices with diverse client portfolios provide higher audit quality than audit offices with mixed client portfolios, but audit offices with focused client portfolios do not provide different audit quality than audit offices with mixed client portfolios. However, we also find that we also find that audit quality varies by task complexity. We find that audit offices with focused client portfolios have higher service quality related to complex audit tasks, while the higher audit quality observed for audit offices with diverse client portfolios relates to less complex audit tasks. In cross-sectional analyses, we examine the importance of the availability of knowledgeable professionals, competition among audit clients, and the geographic dispersion of the audit client. Overall, our study provides insight regarding the association between the composition of audit office client portfolios and audit quality. Keywords: Audit quality; knowledge management; industry expertise; professional service firm; restatements

3 1. Introduction We investigate whether the composition of audit office client portfolios is related to audit quality. Research suggests that the performance of audit offices depends on their ability to manage their knowledge resources effectively (Morris & Empson 1998; Argote et al., 2003; Ofek & Sarvary, 2001; von Nordenflycht, 2010). However, successful knowledge management depends on the nature of the services provided and the ability to transfer knowledge to other engagements (Chase & Tansik, 1983; O Keefe et al., 1994; Malhortra & Morris, 2009). Because successful service provision depends on multiple facets, service quality may vary because of the composition of the clientele served. Prior research has examined the association between some audit office characteristics, such as industry market share (e.g., Reichelt & Wang, 2010), and audit quality. Our approach is unique because we examine the association between the composition of audit offices client portfolios and audit quality because audit quality depends on effectively managing all facets of service provision. We examine audit quality for audit offices that have a homogenous client base (a focused client portfolio), a heterogenous client base (a diverse client portfolio), or a hybrid client base (a mixed client portfolio). It is important to understand how audit office client portfolios affect audit quality for several reasons. First, audit services provide credibility to accounting information, used for resource allocation and contracting efficiency (DeFond & Zhang, 2014). Likewise, prior research has emphasized the importance of understanding the determinants of audit firm performance because of their role as knowledge engines for business (Lorsch & Tierney, 2002; Greenwood et al. 2005). Second, audit firms are a large and growing segment of the worldwide economy (Greenwood et al. 2005; von Nordenflycht 2010). Third, the type of knowledge management required likely varies among audit offices because of the composition of client portfolios and the 1

4 needs of the individual clients (Morris and Empson 1998). Consequently, service quality also likely differs by the composition of client portfolios and prior research has not fully considered how the type of client portfolio may affect audit quality. We acknowledge that variation in audit office client portfolios arises for a variety of reasons. Audit office client portfolios are a function of factors such as client acquisition and retention, competition, and geographic clustering of industries. For example, although audit offices attempt to build a reputation as specialists in specific industries (e.g., Francis et al., 2005), our discussions with Big 4 audit partners suggest that clients often prefer an audit office different than the one serving their competitors. This makes client retention in an industry more difficult. These factors result in audit office client portfolios ranging from homogenous to heterogeneous. However, regardless of the factors that determine the audit office portfolio, each office seeks to manage its resources to provide high quality service to all its clients, and it is an empirical question whether there is an association between the composition of audit office client portfolios and audit quality. We draw from theories developed in the accounting and management literature to offer a specific mechanism through which the composition of client portfolios might affect audit quality. Prior studies suggest that audit offices invest in knowledge resources that potentially transfer to other engagements (O Keefe et al., 1994; Morris & Empson, 1998; Cahan et al., 2008). Transferring knowledge between engagements critically depends on the type of knowledge transferred, as well as the applicability of that knowledge to other engagements in the portfolio. For example, O Keefe et al. (1994) suggest that audit quality is a function of industry-specific knowledge and general audit knowledge, both of which could transfer to other engagements 2

5 depending on the composition of the portfolio. 1 Thus, the composition of the client portfolio may directly affect the ability of the audit office to develop and transfer knowledge between engagements. Audit offices that have a homogenous portfolio of clients (i.e., a focused client portfolio) invest in industry-specific knowledge that transfers to other engagements in the industry (O Keefe et al., 1994; Cahan et al., 2008). Prior research suggests that audit offices with a focused client portfolio collect and organize the knowledge using manuals, databases, and standardized training and techniques to record and transfer the specialized knowledge (Morris & Empson 1998). 2 Because this type of knowledge management improves the transfer of specialized knowledge among engagements (i.e., audits), we expect that audit offices with a focused client portfolio have improved service quality, particularly for more complex issues that require specialized knowledge. Audit offices that provide services to a heterogeneous portfolio of clients (i.e., a diverse client portfolio) invest in general audit knowledge used for a broad range of engagements with different audit issues (O Keefe et al., 1994). Clients in diverse portfolios are dissimilar from each other; thus, industry-specific procedures do not transfer well from one audit engagement to another. Instead, diverse offices rely on individual judgment, experience, and the ability to respond in unique situations (Morris & Empson, 1998). Because this type of client portfolio transfers general audit knowledge to its diverse set of engagements, we expect that improved service quality, if any, occurs for less specialized, less complex issues. 1 Included in the production function are client-specific knowledge, which by definition cannot be transferred to other clients in the portfolio, and client-specific characteristics, which we control for in our analysis. 2 In prior audit literature, this knowledge type is comparable to industry expertise where the office investments are intended to increase industry knowledge and build a reputation for quality audits in a particular industry. See, for example, Solomon et al. (1999), Owhoso et al. (2002), Lim and Tan (2008), and Reichelt and Wang (2010). In Section 2.1 we discuss potential issues with the measure of industry expertise currently used in the literature. 3

6 We recognize that it is unlikely that audit offices have a completely focused or completely diverse client base. Thus, many audit offices likely invest in specialized, industryspecific knowledge for a subset of select audit engagements but rely more on general audit knowledge to serve other clients. An audit office with a "mixed" client portfolio requires a balance between general and specialized knowledge management to serve client needs. Miles et al. (1978) suggest that, although they can be difficult to implement effectively, firms can follow a mixed approach to providing services. However, straddling two approaches could result in lost advantages in both directions (Hansen et al., 1999; Porter, 1985; Gibbins & Jamal, 2001). The extent to which a mixed client portfolio affects the quality of service likely differs by the type of knowledge management emphasized, which could lead to variability in audit quality. 3 We classify audit office portfolios into three types: focused, diverse, and mixed. Focused audit offices have industry clustering in their portfolio (high concentration of clients in the same industry) and low industry diversity outside the industry clustering. Diverse audit offices have high industry diversity, but limited industry clustering. Finally, a mixed audit office is one where the client portfolio does not clearly align with either a focused or diverse portfolio. We require that an audit office classified as either focused or diverse to keep that classification for at least 75 percent of our sample period. This restriction is to ensure that the portfolio type follows an observable pattern (e.g., Miles & Snow, 1978; Mintzberg, 1978; Hambrick, 1981, 1983) and is consistent with strategy research that suggests a pattern of behavior over time is necessary to infer business strategy (e.g., Bentley et al., 2012; Higgins et al., 2015). 4 3 Based on our discussions with Big 4 audit partners (i.e., Deloitte, KPMG, Ernst & Young, and PwC), audit offices will employ different resources to provide quality audits to its clients. For example, an office focused on industry specialization (i.e., a focused office) will train its staff within that industry and segment its staff into groups based on industry. However, an office that audits a wide variety of industries (i.e., a diverse office) is less able to dedicate its staff to particular industry groups. These offices will instead train staff in using general decision aids and efficiently using professional judgment. 4 In Section 5.1 we examine the importance of having a consistent client portfolio type. 4

7 Our results suggest that audit offices with diverse client portfolios have a lower client misstatement rate than audit offices with mixed client portfolios, even after controlling for other previously-examined audit office and client characteristics. Additional analyses suggest that the improved audit service quality among offices with diverse client portfolios occurs only among offices that consistently have diverse client portfolios, rather than offices that only intermittently have diverse client portfolios. In our primary tests, audit offices with focused client portfolios do not have fewer misstatements than audit offices with mixed client portfolios. This result contrasts with prior research suggesting that industry specialization, measured using audit office revenues, improves audit service quality. 5 However, because audit offices manage their portfolio based on engagement needs (i.e., specialized versus general audit knowledge), we extend our analyses by examining whether the observed relations between client portfolios and audit quality are task-specific. Audit offices with a focused client portfolio likely have better performance related to complex tasks because they emphasize specialized knowledge. In contrast, audit offices with a diverse client portfolio likely have better performance related to more routine, less complex issues because these offices focus on general audit knowledge applicable to a variety of tasks. Our results are consistent with expectations. We find that audit offices with a focused client portfolio have lower client misstatement rates for complex financial statement accounts while audit offices with diverse client portfolios have lower client misstatement rates for less complex financial statement accounts. 6 These results suggest that audit quality varies by the 5 We note that prior research has shown that industry specialization is associated with lower abnormal accruals (Reichelt & Wang, 2010) as a proxy for audit quality; however, other studies (e.g., Francis et al., 2013; Seetharaman et al., 2011) do not find a significant association between industry specialization and client misstatements. The later results are consistent with our finding. 6 Complex accounts are identified as those for which the Public Company Accounting Oversight Board (PCAOB) consistently finds higher error rates (Acito et al., 2014). 5

8 client portfolio type and the knowledge necessary to complete the task. We find no evidence that offices with mixed client portfolios provide better audit service quality than offices with focused or diverse client portfolios in any of our analyses. Thus, we provide evidence that audit offices having neither focused or diverse client portfolios do not provide higher-quality audit services. In additional analyses, we examine whether the association between client portfolio types and service quality vary cross-sectionally with the availability of knowledgeable professionals, the level of audit competition, or the geographic dispersion client business segments. Compared to smaller cities, our results indicate that audit offices with a focused client portfolio have higher audit quality in larger cities, where more highly-skilled, specialized professionals are available. Our results also suggest that audit offices with a focused client portfolio have lower audit quality in settings where the competition among audit offices is higher or when the clients have geographically disperse operations. Our study makes several contributions to the literature. First, we provide a broader perspective on audit office client portfolios than other studies that examine individual audit office characteristics. In particular, we find that audit offices with diverse client portfolios provide higher audit quality than audit offices with mixed client portfolios, a result not in the prior literature. Second, our study demonstrates an association between industry clustering (i.e., a focused client portfolio) and misstatements related to complex financial accounts. Thus, we provide an explanation that reconciles our results with mixed results found in prior studies. Our results suggest that it is important to consider the interaction of client portfolio type (focused, diverse, or mixed) and the complexity of the accounts (complex versus non-complex) when examining audit quality. Third, our cross-sectional analyses provide evidence regarding contexts in which audit offices are more effective in managing their client portfolios. 6

9 The remainder of this paper is as follows. In Section 2, we provide background and develop our hypotheses. In Section 3, we discuss our research design and sample. Section 4 presents our empirical results. We include supplemental analyses in Section 5, and Section 6 concludes. 2. Background and hypotheses 2.1 Audit office characteristics and audit quality Numerous studies find an association between audit office characteristics and audit service quality. For example, prior research suggests that large audit offices have more peers to consult, are less economically dependent on clients, and are less likely to acquiesce to client pressure. These advantages result in higher quality earnings (Francis & Yu, 2009; Choi et al., 2010) and fewer client financial statement restatements (Francis et al., 2013). As noted by Francis et al. (2013, p. 1627), these findings also emphasize the relevance of research that focuses on the engagement office as the unit of analysis in audit research. Similarly, Gibbins & Jamal (2006) note that the majority of audit partners view the firm primarily at the local office level, and Lee & Van den Steen (2010) suggest it may be optimal to disseminate know-how at the plant level but not at the firm level. Additionally, the prior literature examines audit office industry expertise or specialization, frequently measured as the audit offices local market share in a particular industry. 7 This literature suggests that industry expertise or specialization provides economies of scale (e.g., Deltas & Doogar, 2003; Cahan et al., 2008) and improves audit quality (e.g., 7 Other studies provide evidence that national industry experts provide higher quality audits (Balsam et al., 2003; Krishnan, 2003). Ferguson et al. (2003) and Francis et al. (2005) argue that expertise has both national (firm-wide) and local (office-specific) dimensions. Reichelt & Wang (2010) extend this line of research and find that audit firms that are both national and city-specific industry specialists have the highest audit quality. Our study focuses on differences in audit office client portfolios and how management of knowledge and resources could affect audit quality. 7

10 Ferguson et al., 2003; Francis et al., 2005). In an experimental setting, Owhoso et al. (2002) conclude that auditor industry specialization improves error detection. Despite these findings, Francis (2011, p. 137) calls for more research on industry expertise to understand the source of industry expertise and its relation to office-specific operations, as well as a triangulation of evidence among experimental and archival research approaches. Our study directly contributes to this research by examining the association between audit office client portfolios and audit quality. While prior studies suggest a positive association between industry expertise and audit quality, they find no difference in the likelihood of misstatement for clients of industry experts. For example, when examining the association between audit office size and restatements, Francis et al. (2013) control for both national and city industry expertise but find no associations between either measure of expertise and restatements. Material misstatements and subsequent restatements are a clear sign of lower audit quality (DeFond & Zhang, 2014; Christensen et al., 2015) and, therefore, the lack of evidence warrants further examination. Concurrent literature also finds errors in determining the industry expertise of an audit firm or audit office using market share. For example, using a propensity-score matched research design, Minutti-Meza (2013) finds no difference in audit quality between expert and non-expert audit firms. Gaver & Utke (2015) suggest that dominant market share is not a sufficient condition for industry expertise. They find that audit firms only recently gaining the expertise designation are no different from non-experts, and they indicate that the seasoning process for new experts to produce higher quality audits is approximately three years. These studies suggest it is necessary to consider not just audit office expertise but also how audit offices manage knowledge to service their client portfolios. We examine the variability of an audit office s client 8

11 portfolio, rather than expertise in isolation, because theory suggests that clients require different knowledge management to provide quality service (e.g., Morris and Empson 1998). 2.2 Hypotheses Our hypotheses draw from the management and accounting literature suggesting that knowledge management of professional service firms (PSFs), such as audit firms, varies with clients served. Morris & Empson (1998) indicate that the knowledge which is of value to the firm is frequently derived from the product or client market, and because of knowledge heterogeneity, firms develop different types of knowledge management strategies. They suggest two knowledge management types for PSFs: codified and tacit. Audit offices use codified (i.e., standardized) knowledge to disseminate knowledge about specific industry sectors to help staff working on related engagements. In the context of prior auditing research, this type of knowledge management is comparable to industry expertise where audit offices invest in industry-specific knowledge that transfers to engagements in the same industry (O Keefe et al., 1994; Cahan et al., 2008; Reichelt & Wang 2010). Because audit offices with numerous clients in the same industry (i.e., industry clustering) can transfer this industry-specific knowledge to other engagements in an industry cluster, we suggest that offices with an industry-focused client base tend to emphasize industry-specific knowledge management. Audit offices using tacit knowledge management rely on personal judgment, experience, and ability to respond in unique situations (Morris & Empson, 1998). In the context of prior auditing research, this knowledge management type is comparable to general audit knowledge because it applies to most engagements (e.g., O Keefe et al., 1994). Audit offices with an industry-diverse (i.e., heterogeneous) client portfolio likely emphasize tacit knowledge management because it applies to engagements in a variety of industries. We also note that many 9

12 audit offices, either by choice or because of exogenous client market factors, likely use both industry-specific and general audit knowledge to serve their client portfolio. Because they can have both an industry focus and a diverse portfolio outside their industry focus, we refer to an audit office as mixed if it does not clearly align with either a focused or diverse portfolio type. We suggest that audit quality likely varies depending on the composition of the client portfolio. For example, audit offices with substantial clustering in a single industry and low industry diversity outside the cluster likely manage knowledge resources differently than an office with no industry clustering but substantial industry diversity. Importantly, industry clustering and industry diversification represent distinct dimensions of audit office portfolios; that is, the portfolio may include both high industry clustering and industry diversity (i.e., numerous firms in a single industry cluster and numerous industry clients outside the cluster). Because the composition of the client portfolio imposes different demands on knowledge management resources, different combinations of both general audit knowledge and industryspecific knowledge exist in a single audit office Focused client portfolios Prior research suggests that audit offices that focus on a particular industry will invest more heavily in the industry-specific knowledge that transfers within industry cluster(s) (O Keefe et al., 1994). Also, the literature provides evidence that offices invest in technology and increase industry-specific knowledge through experience serving clients in their industry specialization (Simunic & Stein, 1987; Maletta & Write, 1996; Dunn & Mayhew, 2004; Gul et al., 2009). Industry specialists spread knowledge acquisition costs and training across their industry engagements creating economies of scale (Eichenseher & Danos, 1981; Danos & Eichenseher, 1982; Cahan et al., 2008). Because of these advantages, we expect that these offices 10

13 provide higher quality service to their clients and are more likely to identify material misstatements in their specialization(s). Therefore, we state our hypothesis related to audit offices with a focused client portfolio in the alternative form: H1. Audit offices that have focused client portfolios provide higher audit service quality compared to audit offices that have mixed client portfolios Diverse client portfolios Because general audit knowledge can be applied to most engagements regardless of industry, audit offices with diverse client portfolios likely emphasize general audit knowledge more than specialized, specific knowledge (Gibbins & Jamal, 2006). Prior research suggests that audit offices invest in general audit knowledge that applies to most clients regardless of industry and also rely on individual judgment and experience (O Keefe et al. 1994; Morris and Empson 1998). This type of approach can affect audit quality in several ways. Investments in general audit knowledge could result in higher quality audit procedures provided to all clients, not just those within a particular industry. Prior research suggests that diverse teams bring differing viewpoints that can have a positive effect on task performance (Williams and O Reilly, 1998). Increasing general audit knowledge and gaining experience with different viewpoints can provide auditors with a broader perspective and improve risk assessment for fraud detection. Schippers et al. (2003) find that diverse teams have higher quality team communication. 8 Closely related to our study, Schilling et al. (2003) conclude that the group learning rate under conditions of related variation is greater than under conditions of specialization, suggesting that groups performing related but different tasks may improve learning processes. Also, Griffith et al. (2015) suggest that incorporating information from a variety of sources helps professionals think 8 We note that the definition of diversity in this team-specific study is based on gender, age, education, and tenure and differs from our definition of diversity; however, our definition of diversity results in auditors having varying knowledge, skills, and experiences that could have similar effects on information processing and decision making. 11

14 more broadly and improve service quality. They also provide evidence that the improvement in service quality is attributable to thinking differently; this result suggests that the approach to applying knowledge to provide services influences service quality. In the context of an audit office, these arguments suggest that auditing a diverse client portfolio could improve identification of material misstatements through increased general audit knowledge, differing viewpoints, improved group learning rates, and thinking differently about audit issues. Given these arguments, we state our second hypothesis as follows: H2. Audit offices that have diverse client portfolios provide higher audit service quality compared to audit offices that have mixed client portfolios. 3. Research Design 3.1 Identifying audit office portfolio types To examine the relation between audit office client portfolios and audit quality, we separate audit offices based on characteristics of their client portfolios. We begin by identifying audit offices with industry clusters. We define an industry cluster as having, at least, three clients in the industry, based on the Fama-French 17 industry classifications. 9 We divide the total number of clients in the industry cluster by the total number of clients in the audit office portfolio. This measure of industry clustering ranges from zero to one, with larger numbers indicating greater industry clustering and, therefore, a greater likelihood that the audit office focuses on select industries. Next, we identify audit offices with a high level of industry diversity in their client portfolio. We follow concurrent research to measure audit office industry diversity (Beardsley et al., 2015). Using the Fama-French 17 industry classifications to determine the client s industry, 9 In conversations with Big 4 audit partners, they indicated that an office will generally dedicate staff and resources to industry-specific teams when the office has 3 or more clients in a related industry, 12

15 we assign each client a diversity weight. The diversity weight assigned to each client is the number of clients audited by that audit office that are in a different industry from the client, divided by the total number of clients audited by the office. Intuitively, the industry diversity weight provides a client-specific measure of how many clients in the audit office portfolio are in different industries and, therefore, compete for audit office s knowledge resources. For each audit office, we sum the diversity weights and divide by the total number of clients in the office. This measure of audit office industry diversity (DIVERSITY) also ranges between zero and one, with larger numbers indicating greater industry diversity for that audit office. 10 This approach allows us to differentiate between audit offices that are similar in size and number of industries, but are more or less focused on select industries in their client portfolio. Importantly, it indicates the need for different knowledge resources to serve clients. See Appendix A for additional explanation and examples to illustrate the computation. 11 Next, we identify audit offices with a focused or diverse client portfolio. Our first step is to determine whether the audit office is in the top quartile of industry clustering or industry diversity. We then determine whether the audit office was in this category for at least 75 percent of the sample period. We classify an audit office as a having a focused client portfolio (FOCUSED) if it is in the high industry cluster group and not in the high industry diversity group for at least 75 percent of the sample period. We classify an audit office as having a diverse client portfolio (DIVERSE) if it is in the high industry diverse group but not in the high industry cluster group for at least 75 percent of the sample period. We note that industry clustering and industry 10 As noted in Beardsley et al. (2015), scaling by the total number of clients differentiates between DIVERSITY and office size because the measure captures the extent to which clients differ from one another, regardless of office size. 11 Harrison & Klein (2007) discuss the concept of diversity as variety of members across qualitatively different categories (e.g., industries). They point out a similar measurement of diversity proposed by Simpson (1949) as a measure of species diversity in an ecosystem. 13

16 diversity are not necessarily mutually exclusive in an audit office, and we recognize that many audit offices have both industry clustering as well as industry diversity in their portfolio. Therefore, we classify audit offices that do not have a focused or diverse client portfolio as mixed (MIXED). In our analyses, we use the MIXED audit offices as our reference category. 3.2 Research design Consistent with prior research (e.g., Christensen et al., 2015; DeFond & Zhang, 2014; Francis et al., 2013; Kinney et al., 2004; Palmrose & Scholz, 2004; Seetharaman et al., 2011), we assume that financial statement misstatements indicate lower audit quality. We examine whether there is an association between misstatements (identified by subsequent restatements) and audit offices with focused, diverse, and mixed client portfolios. 12 We estimate the following probit model: Pr(MISSTATE it = 1) = β 0 + β 1 FOCUSED it + β 2 DIVERSE it + β k CONTROLS it + YEAR t + INDUSTRY i + ε (1) MISSTATE is an indicator variable equal to one if company i s financial statements related to year t were misstated and subsequently restated, and zero otherwise. FOCUSED and DIVERSE are indicator variables equal to one if we classified an audit office having a focused or diverse client portfolio, as discussed in section 3.1, respectively, and zero otherwise. Audit offices classified as mixed knowledge management type (MIXED) serve as our reference group. Consistent with H1, we predict a negative coefficient on β1, indicating a lower likelihood of misstatements for audit offices with focused client portfolios when compared to audit offices with mixed client portfolios. For H2, we predict a negative coefficient on β2, indicating a lower 12 We use the fact that a client restated its financial statements in a subsequent year to identify misstatements. Importantly, we use the year the misstatement occurred (and therefore the year of audit failure), not the year the misstatement was identified and restated, which is often several years later. 14

17 likelihood of misstatement for audit offices with diverse client portfolios compared to audit offices with mixed client portfolios. Following the prior literature, we control for variables that may be related to the likelihood of misstatement (Francis et al., 2013; Seetharaman et al., 2011). First, we control for audit office-level characteristics using Big 4 (BIG4), office size (OFFICE), audit fees (AUDIT), auditor provided tax services (APTS), non-audit fees (NAS), client importance (INFLUENCE), auditor tenure (TENURE) and auditor change (AUDITOR_CHANGE). We also control for clientlevel characteristics using client size (SIZE), negative income (LOSS), market-to-book ratio (MTB), absolute value of discretionary accruals (ABSDA), changes in receivables, inventory, cash sales, and earnings (CHG_REC, CHG_INV, CHG_CASH_SALES, CHG_EARN, respectively), new debt or equity (ISSUANCE), mergers and acquisitions (M&A), and litigious industries (LIT). We winsorize all continuous variables at the 1st and 99th percentiles. We also include year and industry fixed effects in our model. 13 Appendix B provides all variable definitions. 3.3 Sample selection Our sample includes observations from 2004 through We begin our sample in 2004 because of the changes in financial reporting and auditing regulations following the Sarbanes- Oxley Act of 2002 and the transition of clients to new audit firms after the end of Arthur Andersen. Our sample period stops in 2012 to allow adequate time for misstatements to be identified and restated. We require audit office information and restatement data from Audit 13 Because of the unbalanced nature of the observations per company, we do not cluster standard errors by company (Petersen, 2009). When clustering by company we find that our results are slightly stronger for the coefficient on DIVERSE. We chose to present the more conservative estimates. 15

18 Analytics and company-level financial statement data from Compustat. 14 We first delete observations with missing data needed to classify audit offices by knowledge management type. Using the remainder of the sample, we then remove company-years with less than $10 million in total assets, audit offices with fewer than 3 clients, audit offices that are not Big 4 or Second Tier, companies in regulated industries, and observations without data needed to calculate control variables. Our final sample consists of 15,273 company-year observations. Table 1 summarizes our sample selection procedure. [Insert Table 1 here] 4. Results 4.1 Descriptive statistics and univariate results Table 2 presents the descriptive statistics for the variables used to estimate our regression model. Approximately nine percent of company-year financial statements are misstated and subsequently restated, which is the approximate rate reported in Francis et al. (2013, p. 1636). The sample has 19 percent of company-years audited by audit offices with focused client portfolios, and about 12 percent of company-years audited by audit offices with diverse client portfolios. Big 4 audit offices audit approximately 93 percent company-years. In an untabulated analysis, we find that misstatement rates do not differ between audit offices with focused client portfolios and audit offices with mixed client portfolios. However, we do find that audit offices with diverse client portfolios have significantly lower misstatement rates than audit offices with mixed client portfolios (p-value < 0.05). These univariate results provide preliminary evidence consistent with the H2 alternative hypothesis that audit offices with diverse client portfolios provide higher audit quality than audit offices with mixed client portfolios. However, we do not 14 While we make several data cuts, our definitions of FOCUSED and DIVERSE are generated using all Big 4 and Second Tier firms that have COMPUSTAT and Audit Analytics data. 16

19 find support consistent with the H1 alternative hypothesis that audit offices with focused client portfolios provide higher quality audit services than audit offices with mixed client portfolios in this univariate analysis. [Insert Table 2 here] 4.2 Multivariate results Table 3 presents the results of estimating Equation (1). In column (1), the coefficient on DIVERSE is negative and significant (p-value < 0.10). This result suggests that audit offices with diverse client portfolios have significantly fewer misstatements than audit offices with mixed client portfolios, even after controlling for other previously-examined determinants of audit quality such as office size. Thus, we find support for H2. The coefficient on FOCUSED is negative but not significant; thus, we do not find support for H1. This result is consistent with the prior literature that finds no association between industry specialization and restatements. [Insert Table 3 here] Column (2) presents results of estimating the marginal effects from Equation (1). The coefficient for DIVERSE is , which suggests that audit offices with diverse client portfolios have a 1.2 percent lower likelihood of misstatement compared to audit offices with mixed client portfolios. Because the sample mean restatement rate is 8.5 percent, these results suggest that audit offices with diverse client portfolios have a 14.1 percent (1.2 percent/8.5 percent) lower likelihood of misstatement. Overall we find support for H2 but do not find support for H1. However, as indicated in the discussion above, theory in the management and accounting literature suggests that the knowledge management associated with different client portfolio types are likely more effective in specific settings. In the next section, we examine 17

20 whether the association between misstatements and client portfolios depends on the complexity of the financial statement accounts. 4.3 Task complexity Because audit offices with a focused client portfolio emphasize different types of knowledge than audit offices with a diverse client portfolio (i.e., specialized knowledge versus general audit knowledge), any improvement in service quality attributable knowledge management between the portfolio types likely varies by type of knowledge required for the task. Based on the prior literature, we expect that industry-specific knowledge improves service quality for more specialized, complex tasks, whereas general audit knowledge improves service quality for more general, less specialized tasks (e.g., O Keefe et al., 1994; Morris & Empson, 1998). Thus, an improvement in audit quality for focused client portfolios is more likely among the most complex financial statement issues where specialized knowledge is needed, while an improvement in audit quality for diverse client portfolios is more likely among less complex issues, where general audit knowledge applies to most clients in the portfolio. To test this possibility, we consider the association between audit office portfolio types and the complexity of misstated financial statement accounts. We split our misstatements into complex and non-complex categories, where complex categories are defined as those the PCAOB finds to be the most common Part I report deficiencies (Acito et al., 2014). Thus, we classify a misstatement as complex if it pertains to revenue, taxes, derivatives, goodwill valuation, mergers and acquisitions, or leases. These financial statement accounts are very complex, and auditing the accounts requires specialized accounting and auditing knowledge. 15 Thus, improvements in service quality for audit offices with a focused client portfolio may be 15 Our conversations with audit professionals verify that these financial statement accounts are among the most complex and require specific accounting and auditing knowledge. 18

21 more likely when auditing these complex financial statement accounts, but improvements in service quality for audit offices with diverse client portfolios may be more likely in other, less complex, financial statement accounts. Our base group continues to be audit offices with mixed client portfolios. Because misstatements in complex and non-complex accounts are not independent, the likelihood of both types of misstatements should be estimated jointly (Woolridge 2010, p ). We use a seemingly unrelated bivariate probit regression, which jointly models both types of misstatements and controls for the correlation between them. Our two dependent variables are COMPLEX_MISSTATE and NONCOMPLEX_MISSTATE, and we include all the independent variables from Equation (1). We present the results in Table 4. The likelihood ratio test of independence rejects the null hypothesis that the two models are independent (p-value <0.01). [Insert Table 4 here] Column (1) presents the results where COMPLEX_MISSTATE is the dependent variable. In contrast to our primary analysis, the coefficient for FOCUSED is negative and significant (p < 0.10), while the coefficient for DIVERSE is insignificant. These results suggest that compared to audit offices with a mixed client portfolio, audit offices with a focused client portfolio have better audit quality for complex audit issues while audit offices with diverse client portfolios do not have better audit quality for complex audit issues. Column (2) presents the results where NONCOMPLEX_MISSTATE is the dependent variable. Consistent with the primary analysis, the coefficient on DIVERSE is negative and significant (p < 0.10) while the coefficient on FOCUSED is insignificant. This result suggests that compared to audit offices with mixed client portfolios, audit offices with diverse client portfolios have better service quality for more general, less specialized tasks that apply to most clients regardless of industry. Because non- 19

22 complex restatements tend to be general issues that apply more broadly to clients in different industries, the general audit knowledge associated with audit offices with diverse portfolios appears to improve identification of these general issues. In summary, our main empirical analyses suggest that compared to audit offices with mixed client portfolios, audit offices with diverse client portfolios have better audit service quality for more general, less complex financial statement accounts that require less specialized knowledge. In contrast, we find that compared to audit offices with a mixed client portfolio, audit offices with focused client portfolios have better audit service quality, but only when auditing more complex financial statement accounts requiring more specific specialized knowledge. Thus, consistent with our expectations, the stronger service quality from differences in client portfolio types vary by by task complexity. 5. Supplemental analyses 5.1 Consistent knowledge management We extend our primary analysis by examining the consistency of an audit office's client portfolio. Although we categorize audit offices as one of three portfolio types in our primary analyses, this analysis allows us to examine audit offices that must react to changes in their client portfolios that occur more than those offices that exhibit stability in the clustering and diversity of their portfolios. We create two additional variables, SOMETIMES_FOCUSED, and SOMETIMES_DIVERSE. We assign these variables a value of 1 if the audit office is classified as FOCUSED or DIVERSE but less often than our earlier 75 percent of the sample period constraint (i.e., at least 1 year, but less than 75 percent of the sample period), and 0 otherwise. By examining offices that intermittently exhibit one of the client portfolio types, we can test the value of having a client base that requires consistency in knowledge management versus reacting 20

23 to the needs of a changing client base. We re-estimate Equation (1) after including these indicator variables and present the results in Table 5. Our results for FOCUSED and DIVERSE remain the same as our primary analysis; the coefficient for FOCUSED is negative but insignificant, and the coefficient for DIVERSE is negative and significant (p-value < 0.10). The coefficient estimates for SOMETIMES_FOCUSED and SOMETIMES_DIVERSE are both insignificant (p-values = 0.38 and 0.79, respectively). These results suggest that as audit offices portfolios shift from one type to another, the association between focused or diverse portfolios does not differ from audit offices that have mixed portfolio types. Thus, the better service quality of a diverse client base is only achieved by offices that consistently have a diverse client portfolio, rather than offices that frequently change their client base. 16 [Insert Table 5 here] 5.2 Availability of knowledgeable professionals Prior literature suggests that the availability of knowledgeable professionals influences the structure of professional service firms (PSFs), affects the ability of PSFs to leverage capabilities of multiple individuals and facilitates PSFs resource allocation (Morris & Empson, 1998; Malhotra & Morris, 2009; Neuman et al., 2015). When knowledgeable professionals are more available and accessible, audit offices of different types may effectively leverage their knowledge resources to improve audit quality. Therefore, when more knowledgeable professionals are available, we expect the benefits of knowledge management related to client portfolios to be more pronounced. We conduct two tests of this possibility. 16 These results complement the results in Gaver & Utke (2015), who find that audit firms who are newly considered experts have no different audit quality from non-experts. 21

24 First, we investigate whether the audit office location (city size) moderates the association between client portfolio type and misstatements. Prior research suggests that larger cities have higher quality resources related to accounting quality (Francis et al., 2013). Thus, to the extent that larger cities have higher-quality resources available (i.e., more and better quality human capital) than smaller cities, we expect that audit offices in larger cities are better able to implement knowledge management strategies that specifically complement their client portfolio. To test this, we create an indicator variable (LARGE_CITY) equal to one if the audit office is in one of the twenty largest metropolitan statistical areas (MSAs), and zero otherwise. We then reestimate a modified Equation (1) by including LARGE_CITY and its interaction with both FOCUSED and DIVERSE. For our second test, we examine the effect of professional knowledge availability by investigating the moderating effect of office size on the association between audit office portfolio type and audit service quality. Prior literature suggests that larger audit offices have greater knowledge resources available (e.g., Francis & Yu, 2009; Francis et al., 2013). Thus, to the extent that larger offices are better able to use their available knowledge resources to develop and effectively implement knowledge management strategies that complement their client portfolio, the size of the office may moderate the association between portfolio type and misstatements. We test this by creating an indicator variable (LARGE_OFFICE) equal to 1 if the office is in the top quartile of office size, as measured by the number of clients, and zero otherwise. We then estimate Equation (1) after modifying it by including LARGE_OFFICE and its interaction with both FOCUSED and DIVERSE. We present the results of these analyses in Table 6. In Panel A, we find that the association between the focused client portfolios and client misstatements varies cross- 22

25 sectionally with city size. The coefficient on FOCUSED is not significant, consistent with our primary analysis; however, the coefficient on the interaction of FOCUSED and LARGE_CITY is negative and significant (p < 0.05). This result suggests that compared to audit offices with mixed client portfolios, audit offices with focused client portfolios are more effective with greater available knowledge resources. This result is consistent with the notion that audit offices are better able to allocate knowledge resources related to specialized knowledge when greater professional knowledge is available in the geographic area (e.g., Francis et al., 2013). The result is also consistent with the notion that audit offices with mixed client portfolios are not more effective even with greater available professional knowledge. We do not find evidence that large cities have a moderating effect on offices that have diverse client portfolios. Consistent with our primary analyses, the coefficient on DIVERSE remains negative and significant. [Insert Table 6 here] In contrast to our large city analysis, we do not find that office size moderates the association between client portfolios and client misstatements. In Panel B of Table 6, we find that both interactions with LARGE_OFFICE are insignificant. However, the coefficient on LARGE_OFFICE is negative and significant, consistent with prior research (Francis et al., 2013). Because of the significant main effect and insignificant interactions, these results suggest that larger audit offices provide higher audit quality because of the greater resources available in a large office, but the benefits do not vary by client portfolio type. 5.3 Competition Prior academic research finds that audit offices consistently compete on price and that the level of competition in the audit market is positively associated with client restatements (Numan and Willekens, 2012; Newton et al., 2013). These results suggest that audit offices operating in 23