The 'Big N' Audit Quality Kerfuffle

William M. Cready
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引用次数: 5

Abstract

In a highly influential analysis, Lawrence, Minutti-Meza, and Zhang (2011), LMZ henceforth, report that statistically significant relations between a firm’s choice of a Big N auditor and three audit quality metrics (discretionary accruals, cost equity capital, and analyst forecast accuracy) turn “insignificant” after application of matching (propensity score and size) designs. LMZ,
however, in interpreting these outcomes mistakenly identify the difference between statistically significant and statistically insignificant as significant (Gelman and Stern, 2006). This analysis re-examines the LMZ evidence descriptively. It finds that little descriptive support exists in the LMZ evidence for conclusive assertions regarding the “insignificance” of audit quality proxy level differences between Big N and non-Big N auditors. Nor does its evidence provide a reliable basis for thinking that propensity score matching based assessment of these differences produces substantially closer to zero inferences about them relative to inferences obtained from existent (inclusive of LMZ provided estimates) conventional non-matching design based multiple
regression assessments. Indeed, the LMZ evidence is most appropriately interpreted as providing broad robustness support for the insights provided by such models.
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“大N”审计质量混乱
Lawrence、Minutti-Meza和Zhang(2011)在一项极具影响力的分析中报告称,在应用匹配(倾向得分和规模)设计后,公司选择大N审计师与三个审计质量指标(可支配应计利润、成本权益资本和分析师预测准确性)之间的统计显著关系变得“不显著”。然而,LMZ在解释这些结果时错误地将统计显著和统计不显著之间的差异识别为显著(Gelman和Stern, 2006)。该分析对LMZ证据进行了描述性的重新检验。研究发现,对于大N和非大N审计师之间审计质量代理水平差异“不显著”的结论性断言,LMZ证据中几乎没有描述性支持。它的证据也没有提供一个可靠的基础,让我们认为基于倾向得分匹配的这些差异评估相对于从现有的(包括LMZ提供的估计)传统的基于非匹配设计的多元回归评估中获得的推断,产生的推断基本上接近于零。事实上,LMZ的证据被最恰当地解释为为这些模型提供的见解提供了广泛的鲁棒性支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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