Search Results
Working Paper
The Diffusion of New Technologies
CORRECT ORDER OF AUTHORS: Aakash Kalyani, Nicholas Bloom, Marcela Carvalho, Tarek Hassan, Josh Lerner, and Ahmed Tahoun. We 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. First, the development of economically impactful new technologies is geographically highly concentrated, more so even than overall patenting: 56% of the most economically impactful technologies come from just two U.S. locations, Silicon Valley and the ...
Working Paper
Economic Surveillance using Corporate Text
Full and correct order of authors: Tarek A. Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler, and Ahmed Tahoun. This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms respond to economic shocks, such as a nuclear disaster or a geopolitical event---insights that often elude traditional data sources. This method enhances our ...
Working Paper
Theory Meets Textual Analysis: Measuring Firm-Level Labor Cost Pressures and Inflation Pass-Through
We develop a novel measure of firm-level marginal labor cost and investigate its inflation pass-through. We apply textual analysis to earnings calls to identify labordiscussions. Leveraging cost-minimization theory that firms equate marginal revenue products across variable inputs, we regress intermediate input revenue shares on labor discussion intensity to recover marginal labor cost shocks. This theory-based approach aggregates multidimensional qualitative information into a single measure. Our aggregate index outperforms conventional slack variables in forecasting inflation. Industry ...
Does Worker Scarcity Spur Investment, Automation and Productivity? Evidence from Earnings Calls
An analysis suggests labor issues like higher wages and hiring difficulties have prompted some firms to invest in automation, leading to productivity growth.
Can Earnings Calls Be Used to Gauge Labor Market Tightness?
An index that uses textual analysis of earnings calls to track labor issues appears to be highly correlated to one measure of labor market tightness.
Journal Article
Real-Time Discovery of Corporate Risks
We propose a new methodology to discover emerging corporate risks in real time by analyzing the text of quarterly earnings conference calls from 2008 to 2025. Our approach identifies bigrams (two-word phrases) within risk-related sentences whose usage surges significantly and then groups them into thematic topics. The method successfully recovers a timeline of major economic events, from the credit crisis in 2008 to macroeconomic and tariff uncertainty in 2025. We find that firms manage these risks differently. While macroeconomic uncertainty is associated with reductions in investment and ...
AI Hype or Reality? Shifts in Corporate Investment after ChatGPT
An analysis of earnings calls shows a sharp rise in AI-related chatter among U.S. corporate executives. But this increase doesn’t appear to be matched by a similar rise in capital and R&D spending.
Working Paper
Text as Data in Economic Analysis
FULL AND CORRECT ORDER OF AUTHORS: Tarek A. Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler, and Ahmed Tahoun. 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 ...
Journal Article
Uneven Innovation in the U.S.
The San Jose and San Francisco areas don’t make the U.S. top 10 in terms of population, and they each contain merely 1% of the national workforce. But jointly they produce about 20% of all innovation output.
Working Paper
Economic Surveillance using Corporate Text
FULL AND CORRECT ORDER OF AUTHORS: Tarek A. Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler, and Ahmed Tahoun. This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms respond to economic shocks, such as a nuclear disaster or a geopolitical event---insights that often elude traditional data sources. This method enhances our ...