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Immigration and Regional Specialization in AI

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  • Gordon H. Hanson
Abstract
I examine the specialization of US commuting zones in AI-related occupations over the 2000 to 2018 period. I define AI-related jobs based on keywords in Census occupational titles. Using the approach in Lin (2011) to identify new work, I measure job growth related to AI by weighting employment growth in AI-related occupations by the share of job titles in these occupations that were added after 1990. Overall, regional specialization in AI-related activities mirrors that of regional specialization in IT. However, foreign-born and native-born workers within the sector tend to cluster in different locations. Whereas specialization of the foreign-born in AI-related jobs is strongest in high-tech hubs with a preponderance of private-sector employment, native-born specialization in AI-related jobs is strongest in centers for military and space-related research. Nationally, foreign-born workers account for 55% of job growth in AI-related occupations since 2000. In regression analysis, I find that US commuting zones exposed to a larger increases in the supply of college-educated immigrants became more specialized in AI-related occupations and that this increased specialization was due entirely to the employment of the foreign born. My results suggest that access to highly skilled workers constrains AI-related job growth and that immigration of the college-educated helps relax this constraint.

Suggested Citation

  • Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28671
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    Cited by:

    1. Hanson, Gordon & Liu, Chen, 2023. "Immigration and occupational comparative advantage," Journal of International Economics, Elsevier, vol. 145(C).
    2. Kim, Gueyon, 2022. "Trade-Induced Adoption of New Work," IZA Discussion Papers 15165, Institute of Labor Economics (IZA).
    3. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia & Ioannis Papadakis, 2023. "Artificial Intelligence and Jobs: Evidence from US Commuting Zones," CESifo Working Paper Series 10685, CESifo.
    4. Rude, Britta & Giesing, Yvonne, 2022. "Technological Change and Immigration - A Race for Talent or of Displaced Workers," VfS Annual Conference 2022 (Basel): Big Data in Economics 264093, Verein für Socialpolitik / German Economic Association.
    5. Gueyon Kim, 2022. "Trade-Induced Adoption of New Work," Working Papers 2022-007, Human Capital and Economic Opportunity Working Group.
    6. Alex Chernoff & Gabriela Galassi, 2023. "Digitalization: Labour Markets," Discussion Papers 2023-16, Bank of Canada.
    7. Yvonne Giesing, 2023. "The Impact of Technological Change on Immigration and Immigrants," CESifo Working Paper Series 10876, CESifo.

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    More about this item

    JEL classification:

    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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