We construct a text-based measure of firms' forward-looking attention from earnings calls and show that it predicts subsequent investment, R&D, and innovation while contracting ahead of financial distress. Studying how corporate governance shapes firm horizons, we find that within-firm attention to the future rises with the level and breadth of institutional ownership, but falls when ownership concentrates in a single blockholder. We rationalize these empirical patterns in a model of managerial attention nesting price discipline from informed trading and the control–initiative tradeoff under blockholder intervention.

We construct a firm-year measure of revealed planning horizons from explicit future time references in corporate earnings calls, documenting large and persistent cross-firm heterogeneity. Combining this measure with high-frequency monetary policy shocks across the yield curve, we show that longer-horizon firms cut investment more in response to forward-guidance tightening but less in response to current-rate tightening. A calibrated New Keynesian investment model with heterogeneous finite planning horizons rationalizes these findings and implies that forward guidance is most potent one to two years ahead.

This article discusses how to apply computational linguistics techniques to analyze largely unstructured corporate-generated text for economic analysis. As a core example, we illustrate how textual analysis of earnings conference call transcripts can provide insights into how markets and individual firms respond to economic shocks, such as a nuclear disaster or a geopolitical event: insights that often elude traditional non-text data sources. This approach enables extracting actionable intelligence, supporting both policy-making and strategic corporate decision-making. We also explore applications using other sources of corporate-generated text, including patent documents and job postings. By incorporating computational linguistics techniques into the analysis of economic shocks, new opportunities arise for real-time economic data, offering a more nuanced understanding of market and firm responses in times of economic volatility.

We 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 associate with each country at each point in time. Flexibly aggregating this firm-country-quarter-level data allows us to systematically identify spikes in perceived country risk ("crises") and document their source and pattern of transmission to foreign firms. While this pattern usually follows a gravity structure, it often changes dramatically during crises. For example, while crises originating in developed countries propagate disproportionately to foreign financial firms, emerging market crises transmit less financially and more to traditionally exposed countries. We apply our measures to show that elevated perceptions of a country's riskiness, particularly those of foreign and financial firms, are associated with significant falls in local asset prices, capital outflows, and an increased likelihood of a sudden stop.

We construct text-based measures of the primary concerns listed firms associated with the spread of COVID-19 and other epidemic diseases. We identify which firms perceive to lose or gain from a given epidemic and textually decompose the epidemic's effect on the firm's demand and supply. We find that the effects of COVID-19 manifest as a simultaneous shock to demand and supply, with both shocks affecting firms' market valuations in equal measure on average. By contrast, demand-related impacts appear more important in accounting for the observed collapse in firm-level investment during the COVID-19 crisis.