| 来源类型 | Working Paper
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| 规范类型 | 报告
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| DOI | 10.3386/w28671
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| 来源ID | Working Paper 28671
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| Immigration and Regional Specialization in AI |
| Gordon H. Hanson
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| 发表日期 | 2021-04-12
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| 出版年 | 2021
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| 语种 | 英语
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| 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
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| URL | https://www.nber.org/papers/w28671
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| 来源智库 | National Bureau of Economic Research (United States)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/586344
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推荐引用方式
GB/T 7714 |
Gordon H. Hanson. Immigration and Regional Specialization in AI. 2021.
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文件名：
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w28671.pdf
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格式：
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Adobe PDF
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