Text analysis made simple.

This article uses text analysis on corporate documents to gain unique insights into how companies and markets react to major economic events, offering new ways to monitor economic changes in real-time that often elude traditional data sources.

The authors use textual analysis of earnings conference calls held by listed firms around the world to measure the amount of risk managers and investors at each firm associated with each country at each point in time.

The authors propose a text-based method for measuring the international propagation of uncertainty shocks at the firm level and apply it to estimate the impact of Brexit-related uncertainty.

The authors construct text-based measures of the primary concerns listed firms associated with the spread of COVID-19 and decompose its effect on firms' demand and supply.

The authors identify phrases associated with novel technologies using textual analysis of patents, job postings, and earnings calls, enabling us to identify four stylized facts on the diffusion of jobs relating to new technologies.

The authors 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.