AAA Spark Meeting of the Regions

Managerial Resilience and Financial Reporting Quality: Machine Learning Approach

• In Event: Managerial Influence on Reporting Quality

Abstract

Using a machine learning approach on a large sample of firm-year text data from the question and answer section of top managers’ earnings call transcripts, this study examines the impact of managerial resilience on financial reporting quality. In today’s business environment, adversities (e.g., the Great Recession, COVID crisis, remote work environment, changing technology and increasing global competition) are inevitable. Relying on psychological capital and conservation of resources theories, this study predicts that managerial resilience is positively associated with financial reporting quality. The finding would suggest that resilient employees are more effective at discharging their job responsibilities of oversight and internal control duties and, therefore, are more likely to detect errors and misstatements. The main results are expected to hold robust to alternative model specifications, different measures of managerial resilience and financial reporting quality, self-selection bias, omitted variable bias, and other endogeneity concerns.

Author

• Meena Subedi, University of Wisconsin–Whitewater