Labour-saving heuristics in green patents: A natural language processing analysis

T. Rughi, Jacopo Staccioli, Maria Enrica Virgillito

Risultato della ricerca: Contributo in rivistaArticolo in rivista

Abstract

This paper provides a direct understanding of the labour-saving threats embedded in decarbonisation pathways. It starts with a mapping of the technological innovations characterised by both climate change mitigation/adaptation (green) and labour-saving attributes. To accomplish this, we draw on the universe of patent grants in the USPTO since 1976 to 2021 reporting the Y02-Y04S tagging scheme and we identify those patents embedding an explicit labour-saving heuristic via a dependency parsing algorithm. We characterise their technological, sectoral and time evolution. Finally, after constructing an index of sectoral penetration of LS and non-LS green patents, we explore its correlation with employment share growth at the state level in the US. Our evidence shows that employment shares in sectors characterised by a higher exposure to LS (non-LS) technologies present an overall negative (positive) growth dynamics.
Lingua originaleEnglish
pagine (da-a)N/A-N/A
RivistaEcological Economics
Volume230
DOI
Stato di pubblicazionePubblicato - 2025

Keywords

  • Climate change mitigation
  • Labour markets
  • Search heuristics
  • Natural language processing
  • Labour-saving technologies

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