This study investigates how firm-specific exposure to COVID-19 influences capital structure choices, a topic of significant importance due to the pandemic’s unprecedented economic disruption. We leverage a novel text-based measure of firm-specific COVID exposure to explore these dynamics.
Our research adopts an innovative text-based approach to measure firm-specific COVID exposure, developed by prior studies, which analyzes earnings conference call transcripts using advanced machine learning algorithms. The analysis is based on a comprehensive sample of US firms spanning over 20 years. Various statistical techniques, including firm-fixed effects, propensity score matching, entropy balancing and instrumental-variable analysis, are employed to ensure robust results.
Our findings indicate that firms with higher COVID exposure significantly alter their leverage, favoring debt financing over equity financing. This effect is less pronounced in larger and more profitable firms as well as those more vulnerable to climate change risk. The unique impact of COVID on leverage is contrasted with other infectious diseases, which do not exhibit similar effects.
Our study’s originality lies in its application of a novel text-based metric, borrowed from existing research, to measure firm-specific COVID exposure, marking a significant advancement in the field. This method provides a timely and precise assessment of exposure, offering insights that traditional metrics cannot capture. It is the first study to document the significant role of COVID exposure in determining corporate leverage, enhancing the understanding of capital structure dynamics in the context of unprecedented global disruptions.
