程式化事实
收益
新兴技术
扩散
产业组织
业务
劳动经济学
经济地理学
经济
计算机科学
营销
数据科学
会计
宏观经济学
物理
人工智能
热力学
作者
Aakash Kalyani,Nicholas Bloom,Marcela Carvalho,Tarek A. Hassan,Josh Lerner,Ahmed Tahoun
摘要
We identify novel technologies using textual analysis of patents, job postings, and earnings calls.Our approach enables us to identify and document the diffusion of 29 disruptive technologies across firms and labor markets in the U.S. Five stylized facts emerge from our data.First, the locations where technologies are developed that later disrupt businesses are geographically highly concentrated, even more so than overall patenting.Second, as the technologies mature and the number of new jobs related to them grows, they gradually spread geographically.While initial hiring is concentrated in high-skilled jobs, over time the mean skill level in new positions associated with the technologies declines, broadening the types of jobs that adopt a given technology.At the same time, the geographic diffusion of low-skilled positions is significantly faster than higher-skilled ones, so that the locations where initial discoveries were made retain their leading positions among high-paying positions for decades.Finally, these pioneer locations are more likely to arise in areas with universities and high skilled labor pools.
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