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

• 成果类型: Article
• 署名作者: DeFond, Mark; Erkens, David H.; Zhang, Jieying
• 署名单位: University of Southern California; University of Texas System; University of Texas Dallas
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2016.2528
• 发表日期: 2017
• 页码: 3628-3649
• 关键词: accounting; auditing simulation: statistical analysis; statistics: pattern analysis; Propensity score matching

摘要

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.