Pre-AI Sorting, Post-AI Inequality: Generative AI and the Gender Wage Gap

Malin Gardberg (), Fredrik Heyman (), Martin Olsson () and Joacim Tåg ()
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Malin Gardberg: Research Institute of Industrial Economics (IFN), Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden, https://www.ifn.se/en/researchers/ifn-researcher/malin-gardberg/
Fredrik Heyman: Research Institute of Industrial Economics (IFN), Postal: Stockholm, and Lund University, Sweden, https://www.ifn.se/en/researchers/ifn-researcher/fredrik-heyman/
Martin Olsson: Research Institute of Industrial Economics (IFN), Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden, https://www.ifn.se/en/researchers/ifn-researcher/martin-olsson/
Joacim Tåg: Research Institute of Industrial Economics (IFN), Postal: Stockholm, Sweden, and Hanken School of Economics, Helsinki, Finland, https://www.ifn.se/en/researchers/ifn-researcher/joacim-tag/

No 1534, Working Paper Series from Research Institute of Industrial Economics

Abstract: We examine how gender-based occupational sorting before the release of ChatGPT relates to predicted exposure to generative AI and its potential implications for the gender wage gap. Using Swedish administrative data, we find that women are overrepresented in occupations predicted to be more affected by generative AI. Simulations based on deviations from the 2021 occupational and wage distribution—incorporating predicted AI exposure and task complementarity—show that generative AI can widen the gender wage gap through existing patterns of occupational sorting.

Keywords: Generative AI; Gender wage gap; Technological change; Occupational sorting; Complementarity (search for similar items in EconPapers)
JEL-codes: J16 J24 J31 O33 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2025-09-25
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:iuiwop:1534

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