The Labor Market Impact of Artificial Intelligence: Evidence from US Regions

Yueling Huang

No 2024/199, IMF Working Papers from International Monetary Fund

Abstract: This paper empirically investigates the impact of Artificial Intelligence (AI) on employment. Exploiting variation in AI adoption across US commuting zones using a shift-share approach, I find that during 2010-2021, commuting zones with higher AI adoption have experienced a stronger decline in the employment-to-population ratio. Moreover, this negative employment effect is primarily borne by the manufacturing and lowskill services sectors, middle-skill workers, non-STEM occupations, and individuals at the two ends of the age distribution. The adverse impact is also more pronounced on men than women.

Keywords: Artificial intelligence; technology; labor; local labor markets; shift share; middle-skill worker; labor market impact; impact of artificial intelligence; employment effect; low-skill services sectors; Employment; Employment rate; Labor markets; Global; employment share; industry classification; classification scheme; AI adoption data; industry AI adoption; robot penetration; AI production; employment impact; employment outcome (search for similar items in EconPapers)
Pages: 53
Date: 2024-09-13
New Economics Papers: this item is included in nep-ain, nep-ipr, nep-tid and nep-ure
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.imf.org/external/pubs/cat/longres.aspx?sk=554845 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:imf:imfwpa:2024/199

Ordering information: This working paper can be ordered from
http://www.imf.org/external/pubs/pubs/ord_info.htm

Access Statistics for this paper

More papers in IMF Working Papers from International Monetary Fund International Monetary Fund, Washington, DC USA. Contact information at EDIRC.
Bibliographic data for series maintained by Akshay Modi ().