Do Client Characteristics Really Drive the Big N Audit Quality Effect? New Evidence from Propensity Score Matching

Mark DeFond (), David H. Erkens () and Jieying Zhang ()
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Mark DeFond: Marshall School of Business, University of Southern California, Los Angeles, California 90089
David H. Erkens: Marshall School of Business, University of Southern California, Los Angeles, California 90089
Jieying Zhang: University of Texas at Dallas, Richardson, Texas 75080

Management Science, 2017, vol. 63, issue 11, 3628-3649

Abstract: A large auditing literature concludes that Big N auditors provide higher audit quality than non-Big N auditors. Recently, however, a high-profile study suggests that propensity score matching (PSM) on client characteristics eliminates the Big N effect [Lawrence A, Minutti-Meza M, Zhang P (2011) Can Big 4 versus non-Big 4 differences in audit-quality proxies be attributed to client characteristics? Accounting Rev. 86(1):259–286]. We conjecture that this finding may be affected by PSM’s sensitivity to its design choices and/or by the validity of the audit quality measures used in the analysis. To investigate, we examine random combinations of PSM design choices that achieve covariate balance, and four commonly used audit quality measures. We find that the majority of these design choices support a Big N effect for most of the audit quality measures. Overall, our findings show that it is premature to suggest that PSM eliminates the Big N effect.

Keywords: accounting; auditing; simulation: statistical analysis; statistics: pattern analysis; propensity score matching (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (33)

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