Labour-saving automation and occupational exposure: a text-similarity measure

Fabio Montobbio, Jacopo Staccioli, Maria Enrica Virgillito and Marco Vivarelli ()

No 987, GLO Discussion Paper Series from Global Labor Organization (GLO)

Abstract: This paper represents one of the first attempts at building a direct measure of occupational exposure to robotic labour-saving technologies. After identifying robotic and LS robotic patents retrieved by Montobbio et al. (2022), the underlying 4-digit CPC definitions are employed in order to detect functions and operations performed by technological artefacts which are more directed to substitute the labour input. This measure allows to obtain fine-grained information on tasks and occupations according to their similarity ranking. Occupational exposure by wage and employment dynamics in the United States is then studied, complemented by investigating industry and geographical penetration rates.

Keywords: Labour-Saving Technology; Natural Language Processes; Labour Markets; Technological Unemployment (search for similar items in EconPapers)
JEL-codes: J24 O33 (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-big, nep-lma and nep-tid
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Citations: View citations in EconPapers (1)

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https://www.econstor.eu/bitstream/10419/246813/1/GLO-DP-0987.pdf (application/pdf)

Related works:
Working Paper: Labour-saving automation and occupational exposure: a text-similarity measure (2021)
Working Paper: Labour-Saving Automation and Occupational Exposure: A Text-Similarity Measure (2021)
Working Paper: Labour-saving automation and occupational exposure: a text-similarity measure (2021)
Working Paper: Labour-saving automation and occupational exposure: A text-similarity measure (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:987

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