Abstract

Abstract We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual U.S. firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is captured neither by the interaction of sector and time fixed effects nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.

Keywords

Political riskPoliticsVolatility (finance)EarningsEconomicsVariance (accounting)Stock (firearms)Systematic riskConstruct (python library)Risk measureFinancial economicsStock marketMarket riskAggregate (composite)Monetary economicsFinancePolitical scienceAccounting

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Publication Info

Year
2019
Type
article
Volume
134
Issue
4
Pages
2135-2202
Citations
1170
Access
Closed

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Social Impact

Social media, news, blog, policy document mentions

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1170
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Cite This

Tarek A. Hassan, Stephan Hollander, Laurence van Lent et al. (2019). Firm-Level Political Risk: Measurement and Effects*. The Quarterly Journal of Economics , 134 (4) , 2135-2202. https://doi.org/10.1093/qje/qjz021

Identifiers

DOI
10.1093/qje/qjz021