 Labour-saving heuristics in green patents: A natural language processing analysisTommaso Rughi, Jacopo Staccioli and Maria Enrica Virgillito Ecological Economics, 2025, vol. 230, issue C 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. Keywords: Climate change mitigation; Labour-saving technologies; Search heuristics; Natural language processing; Labour markets (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:230:y:2025:i:c:s092180092400394x DOI: 10.1016/j.ecolecon.2024.108497 Access Statistics for this article Ecological Economics is currently edited by C. J. Cleveland More articles in Ecological Economics from Elsevier |
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