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Diversification by the audit offices in the US and its impact on audit quality

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Abstract

Audit offices in the US exhibit a wide variation in the number of industries they service. Strategic management theory suggests that diversification can affect the quality of output, depending on the nature and circumstances of diversification. This paper examines the effect of diversification at the audit office level on audit quality. Five proxies of audit quality are examined, mainly, absolute discretionary accruals, propensity to meet-or-beat earnings expectations by a cent, propensity to restate financial statements, propensity to receive a comment letter after an SEC review and propensity to issue a going concern opinion. Results suggest that diversification has detrimental effects on audit quality. On the other hand, when the diversification is part of the audit firm level strategy, the detrimental effects on audit quality are dampened. Moreover, when the diversification at the office level is part of a revenue expansion strategy, the audit quality is adversely affected. However, there is no detrimental effect on the audit quality when revenue expansion is not the objective. Also, diversification across dissimilar industries leads to more adverse effect on audit quality than diversification to similar industries. Results also suggest that when the audit office is located in a market with more (less) diversified client base, the adverse effects of diversification on audit quality are weaker (stronger). Finally, the offices of big-4 audit firms handle diversification better with less adverse effect on audit quality. The findings are important since they identify additional factors that explain audit quality at the audit office level.

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Notes

  1. For example, the Cleveland and San Diego offices of Ernst & Young both had 17 clients in 2009. However, The Cleveland office had clients from 10 industries while the San Diego office only had clients from 5 industries.

  2. According to Asthana and Boone (2012), only 26.23 % of clients are audited by national-level industry experts.

  3. Deltas and Doogar (2003) examine diversification strategy of Big N audit firms in the context of mergers.

  4. Growth leads to larger audit offices. Larger audit offices are known to have better audit quality (Francis and Yu 2009; Choi et al. 2010; Francis et al. 2013). Larger audit offices may also be more diversified (Palepu 1985). However, holding office size constant, the role of diversification in defining audit quality is unknown.

  5. Hiring an industry specialist auditor is not without risks, though. Ettredge et al. (2009) cautions that clients could shy away from industry specialists due to the risk of loss of competitive advantage through information leaks.

  6. Offices could add new clients from existing industries only without diversifying. However, this would limit the number of target clients. A more likely approach would be to sacrifice concentration in limited industries and attract clients from a broader spectrum of industries.

  7. Lustgarten and Shon (2013) show that large positive (negative) abnormal accruals lead to a higher likelihood of auditors (clients) terminating the engagement.

  8. Data for this variable is obtained from the Comment Letter database in Audit Analytics.

  9. Using Eq. 2 instead of Eq. 3 to define the diversification measure does not affect the conclusions. Results with Eq. 2 measure are reported in Panel A of Table 7. The two measures are very similar and the means (1.7209 vs 1.7044) are not significantly different and the Pearson Correlation is 0.86, significant at <1 % level. However, since the Eq. 3 measure is more intuitive and easier to interpret, I report that in the main tables.

  10. Velury et al. (2003) and Lim et al. (2013) show that institutional ownership affects audit quality and the choice of industry specialist auditors. Institutional ownership data is not available in this paper. However, Lim et al. (2013) show (Table 2, page 353) that institutional ownership is highly correlated to client size (67 %), non-audit fees (47 %), cash flow from operations (30 %), and market-to-book ratio (30 %). Since all these 4 variables are used as control variables in this paper, the effect of institutional holdings should be adequately controlled.

  11. Myers et al. (2014) show that in the post-SOX period, the propensity to issue a going concern opinion depends on auditor size (big-4 versus non-big 4). Inclusion of BIG-4 as an independent variable will control for this.

  12. Kim et al. (2013) show that auditor size and tenure are both incremental risk-reducing factors. These two variables are included as independent variables to control for this effect.

  13. Jaggi et al. (2015) provide empirical evidence that presence of internal control weaknesses affects the audit quality of industry specialist and non-specialist auditors differentially. The inclusion of ICOPINION controls for this effect.

  14. Krishnan (2003) suggests that industry expertise can be measured in two ways: the market share approach and the portfolio share approach. In the market share approach, the audit fees from clients in the industry at the office level is deflated by the total audit fees in that industry for all audit offices in that city. In the portfolio share approach, the audit fees from clients in the industry at the office level is deflated by the total audit fees of the office. Both measures of CITYEXPERT yield very similar results. The two measures are highly correlated (Pearson correlation coefficient = 0.78; p = 0.01). Since most recent research (Francis and Yu 2009; Asthana and Boone 2012), uses the market share approach, for the sake of brevity, I report that measure only.

  15. Replacing LOFFICE with the natural log of total clients at the office does not alter conclusions.

  16. Including these industries does not alter the conclusions.

  17. The results are qualitatively similar for the period 2000–2012 and for 2000–2012 sans 2002 (the year of SOX implementation).

  18. The sample selection process requires the client to be available on 4 data bases. This results in a large size bias. This is typical in such research. For example, Asthana and Boone (2012) have similar data requirements and have an average LMV of 6.15, compared to our LMV of 6.25. To the extent the results are specific to large clients only; they should be applied to smaller clients with caution.

  19. According to Chatterjee and Price (1977), VIFs under 10 imply that the model does not have significant multicollinearity problem.

  20. The audit firm can diversify into industries not serviced by an audit office. To check if this affects the conclusions, I add the natural log of the total 2-digit SIC at the national firm level into my regressions and it loads insignificantly and all conclusions remain unchanged.

  21. Choi et al. (2012) show that for a typical office, more than 90 % of the clients are local. Thus, there is a tendency among clients to hire the local auditor, rather than a distant one.

  22. On the contrary, Table 8 shows that a larger office does not always have to be more diversified.

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Acknowledgments

I am thankful to Henri Akono, Matt Behrend, Jeff Boone, Dana Forgione, Mark Greenwald, Jun (Maggie) Hao, Carlos Jiminez, Sarfraz Khan, Shiyou Li, Cheryl Linthicum, Emeka Nwaeze, Sung-Jin Park, Benedikt Quosigk, K. K. Raman, and Claire Veal, along with participants at the University of Texas at San Antonio workshop, the AAA Auditing Midyear Conference 2015 and the AAA Annual Conference 2015 for their helpful comments. I am also thankful to the UTSA College of Business for summer financial support for this project. This project supports the COB mission of creating and sharing knowledge.

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Asthana, S. Diversification by the audit offices in the US and its impact on audit quality. Rev Quant Finan Acc 48, 1003–1030 (2017). https://doi.org/10.1007/s11156-016-0576-y

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