Search Results
AI Optimism and Uncertainty: What Can Earnings Calls Tell Us Post-ChatGPT?
An analysis of earnings calls shows that America’s corporate leaders are talking much more about AI. It also reveals an increase in perceived risk in this new technology.
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.
AI and Productivity Growth: Evidence from Historical Developments in Other Technologies
An analysis of the diffusion of PCs, smart devices, cloud computing and 3D printing suggests that AI may spread in a pattern similar to those of PCs and cloud computing.
Working Paper
The Diffusion of New Technologies
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 Northeast Corridor. Second, as the technologies mature and the number of related jobs grows, hiring spreads geographically. ...
Journal Article
The Innovation Puzzle: Patents and Productivity Growth
Understanding the pace and nature of technological progress is key for evaluating innovation policy and projecting economic growth.
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
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 ...
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.
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.
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 ...