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来源类型Working Paper
规范类型报告
DOI10.3386/w28671
来源IDWorking Paper 28671
Immigration and Regional Specialization in AI
Gordon H. Hanson
发表日期2021-04-12
出版年2021
语种英语
摘要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.
主题Labor Economics ; Unemployment and Immigration ; Regional and Urban Economics ; Regional Economics
URLhttps://www.nber.org/papers/w28671
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/586344
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GB/T 7714
Gordon H. Hanson. Immigration and Regional Specialization in AI. 2021.
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