DP14573 Firm-Level Exposure to Epidemic Diseases: Covid-19, SARS, and H1N1

Author(s): Tarek Alexander Hassan, Stephan Hollander, Markus Schwedeler, Ahmed Tahoun, Laurence van Lent
Publication Date: April 2020
Date Revised: November 2020
Keyword(s): Epidemic diseases, exposure, firms, Machine Learning, Pandemic, sentiment, uncertainty, virus
JEL(s): D22, E0, F0, G15, I15, I18
Programme Areas: Financial Economics, International Macroeconomics and Finance, Monetary Economics and Fluctuations, Macroeconomics and Growth
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=14573

We introduce a new word pattern-based method to automatically classify firms' primary concerns related to the spread of epidemic diseases raised in their quarterly earnings conference calls. We construct text-based measures of the costs, benefits, and risks listed firms in the US and over 80 other countries associate with the spread of Covid-19 and other epidemic diseases. We identify which firms and sectors expect to lose/gain from a given epidemic and which are most affected by the associated uncertainty. Our new automatic pattern-based method shows how firms' primary concerns (varying from the collapse in demand and disruptions in their production facilities or supply chain, to financing concerns) are changing over time and varying geographically as epidemics spread regionally and globally. We find that the Covid-crisis manifests itself at the firm-level as a simultaneous shock to both demand and supply. In prior epidemics, in contrast, firm discussions center more on shortfalls in demand. In 2020, supply and financing-related concerns are relatively more salient in regions where the spread of Covid-19 is less contained.