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The diffusion of disruptive technologies

Author

Listed:
  • Nicholas Bloom
  • Tarek Alexander Hassan
  • Aakash Kalyani
  • Josh Lerner
  • Ahmed Tahoun
Abstract
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 across space. 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 technology hubs are more likely to arise in areas with universities and high skilled labor pools.

Suggested Citation

  • Nicholas Bloom & Tarek Alexander Hassan & Aakash Kalyani & Josh Lerner & Ahmed Tahoun, 2021. "The diffusion of disruptive technologies," CEP Discussion Papers dp1798, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp1798
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    4. Barbara Biasi & Song Ma, 2022. "The Education-Innovation Gap," CESifo Working Paper Series 9653, CESifo.
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    6. Charles Hoffreumon & Chris Forman & Nicolas van Zeebroeck, 2024. "Make or buy your artificial intelligence? Complementarities in technology sourcing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 452-479, March.
    7. Fischer, Bruno & Meissner, Dirk & Vonortas, Nicholas & Guerrero, Maribel, 2022. "Spatial features of entrepreneurial ecosystems," Journal of Business Research, Elsevier, vol. 147(C), pages 27-36.
    8. Sanjay Kumar SINGH & Vijay Lakshmi SINGH, 2023. "Internet diffusion in India: A study based on Growth Curve modelling," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 15(2), pages 29-42, June.
    9. Tarek A. Hassan & Stephan Hollander & Aakash Kalyani & Markus Schwedeler & Ahmed Tahoun & Laurence van Lent, 2024. "Economic Surveillance using Corporate Text," Working Papers 2024-022, Federal Reserve Bank of St. Louis.
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    11. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    12. Trouvain, Florian, 2024. "Technology Adoption, Innovation, and Inequality in a Global World," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302377, Verein für Socialpolitik / German Economic Association.
    13. Petralia, Sergio & Kemeny, Thomas & Storper, Michael, 2023. "The transformative effects of tacit technological knowledge," LSE Research Online Documents on Economics 120154, London School of Economics and Political Science, LSE Library.
    14. Matthias Niggli & Christian Rutzer, 2023. "Digital technologies, technological improvement rates, and innovations “Made in Switzerland”," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-31, December.

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    More about this item

    Keywords

    disruptive technologies; technological change; firms; labor markets ;
    All these keywords.

    JEL classification:

    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J1 - Labor and Demographic Economics - - Demographic Economics

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