The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets

Susan Athey, Lisa Simon, Oskar Skans, Johan Vikstrom and Yaroslav Yakymovych

Papers from arXiv.org

Abstract: Using rich Swedish administrative data, we apply causal machine learning methods to study how earnings losses after job displacement vary with observable characteristics that may be relevant for targeting policy interventions for workers. Heterogeneity in effects is as large within as across worker groups defined by age and schooling, and as large within as across establishments. A substantial portion of cross-establishment heterogeneity can be explained by industry and local labor market characteristics, suggesting a role for place- and industry-based targeting. The largest losses are concentrated among already vulnerable workers, indicating that well-designed targeting policies can improve both efficiency and equity.

Date: 2023-07, Revised 2026-03
New Economics Papers: this item is included in nep-eur
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Related works:
Working Paper: The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets (2026)
Working Paper: The heterogeneous earnings impact of job lossacross workers, establishments, and markets (2024)
Working Paper: The Heterogeneous Earnings Impact of Job Loss across Workers, Establishments, and Markets (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2307.06684

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