Exploring the Relationship Between Corporate Governance Practices and Audit Quality in Public Companies

Posted: Oct 21, 2007

• Finnley Torres
• Addie Parker
• Reese Morgan

Abstract

The relationship between corporate governance practices and audit quality represents a critical intersection in financial regulation and corporate oversight. While extensive literature has examined various aspects of this relationship, existing research often suffers from methodological limitations that obscure the complex, multi-dimensional nature of governance-audit interactions. Traditional approaches typically employ linear regression models that assume simple, direct relationships between governance variables and audit outcomes, failing to capture the nuanced interdependencies and threshold effects that characterize real-world corporate environments. This research addresses these limitations by developing an innovative computational framework that integrates machine learning techniques with traditional econometric analysis to provide a more comprehensive understanding of governance-audit dynamics. Our study makes several distinctive contributions to the literature. First, we introduce a novel multi-dimensional governance quality index that moves beyond conventional binary measures of governance attributes. This index incorporates both structural characteristics, such as board composition and committee structures, and behavioral aspects, including meeting frequency and director engagement patterns. Second, we develop a comprehensive audit quality metric that combines traditional financial indicators with qualitative assessments of audit processes and outcomes. This integrated approach allows for a more holistic evaluation of audit quality than previously available measures. Third, and most significantly, we employ advanced machine learning algorithms to identify complex, non-linear relationships and interaction effects between governance mechanisms and audit quality.