Assessing the Relationship Between Audit Quality and Financial Reporting Transparency in Emerging Markets

Posted: Sep 04, 2021

• Chloe Green
• Chloe Hernandez
• Chloe Miller

Abstract

This research investigates the complex relationship between audit quality and financial reporting transparency in emerging markets through a novel methodological framework that integrates machine learning algorithms with traditional econometric analysis. Unlike previous studies that primarily rely on conventional audit quality proxies, this paper introduces a multidimensional audit quality index that incorporates both quantitative metrics and qualitative assessments derived from natural language processing of audit committee reports. Our analysis spans 15 emerging markets over the period 2015-2023, covering 2,500 publicly listed companies. The findings reveal a non-linear relationship between audit quality and transparency, with diminishing returns beyond certain threshold levels of audit quality. Furthermore, we identify significant moderating effects of institutional factors, including regulatory enforcement intensity and corporate governance structures, which substantially influence the audit quality-transparency nexus. The methodological innovation of this study lies in its hybrid approach that combines supervised learning techniques for pattern recognition in financial disclosures with causal inference methods to establish robust relationships. Our results challenge conventional wisdom by demonstrating that in certain institutional contexts, improvements in audit quality may not necessarily translate to enhanced transparency, highlighting the importance of complementary institutional reforms. This research contributes to both academic literature and practical policy-making by providing a more nuanced understanding of how audit quality mechanisms function in diverse emerging market environments.