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Abstract
The global spread of Covid-19 has caused major economic disruptions. Governments around the world provide considerable financial support to mitigate the economic downturn. However, effective policy responses require reliable data on the economic consequences of the corona pandemic. We propose the CoRisk-Index: a real-time economic indicator of corporate risk perceptions related to Covid-19. Using data mining, we analyse all reports from US companies filed since January 2020, representing more than a third of the US workforce. We construct two measures—the number of ‘corona’ words in each report and the average text negativity of the sentences mentioning corona in each industry—that are aggregated in the CoRisk-Index. The index correlates with U.S. unemployment rates across industries and with an established market volatility measure, and it preempts stock market losses of February 2020. Moreover, thanks to topic modelling and natural language processing techniques, the CoRisk data provides highly granular data on different dimensions of the crisis and the concerns of individual industries. The index presented here helps researchers and decision makers to measure risk perceptions of industries with regard to Covid-19, bridging the quantification gap between highly volatile stock market dynamics and long-term macroeconomic figures. For immediate access to the data, we provide all findings and raw data on an interactive online dashboard.
Highlights
The Covid-19 pandemic has caused the largest global economic disruption of the twenty-first century (Fernandes, 2020; Zhang et al, 2020; Ozili and Arun, 2020)
Governments aim to counterbalance the global economic crisis induced by the Covid-19 pandemic with cyclical and fiscal policy packages of enormous volumes
The CoRisk-Index represents an attempt to contribute to the pressing demand for empirical data on the economic impact of the ongoing pandemic
Summary
The Covid-19 pandemic has caused the largest global economic disruption of the twenty-first century (Fernandes, 2020; Zhang et al, 2020; Ozili and Arun, 2020). Traditional macroeconomic research relies on metrics based on past economic shocks, such as economic simulations (del Rio-Chanona et al, 2020; Ludvigson et al, 2020) Another stream, following the paradigm of computational social science (Lazer et al, 2009), explores alternative data sources, such as stock market prices and returns (Ramelli and Wagner, 2020; Keogh-Brown et al, 2010; Buetre et al, 2006; Davis et al, 2020), news articles (Baker et al, 2020), website content (Kinne et al, 2020), search queries (Goodell and Huynh, 2020) or trade and transportation statistics as indicators of economic activity (Cerdeiro et al, 2020; Deb et al, 2021). This paper illustrates how to transform data from a publicly accessible source into an economically meaningful measure of industry-specific business risk perceptions related to the Covid-19 pandemic: the CoRisk-Index.
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