Labour-saving automation and occupational exposure: a text-similarity measure
Fabio Montobbio,
Jacopo Staccioli,
Maria Enrica Virgillito and
Marco Vivarelli ()
LEM Papers Series from Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy
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 labour-saving 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)
Date: 2021-11-23
New Economics Papers: this item is included in nep-big, nep-lab and nep-tid
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.lem.sssup.it/WPLem/files/2021-43.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) 
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:ssa:lemwps:2021/43
Access Statistics for this paper
More papers in LEM Papers Series from Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy Contact information at EDIRC.
Bibliographic data for series maintained by ( this e-mail address is bad, please contact ).