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.
Rughi, T., Staccioli, J., Virgillito, M. E., Labour-saving heuristics in green patents: A natural language processing analysis, <<ECOLOGICAL ECONOMICS>>, 2025; 230 (NA): N/A-N/A. [doi:10.1016/j.ecolecon.2024.108497] [https://hdl.handle.net/10807/306197]
Labour-saving heuristics in green patents: A natural language processing analysis
Staccioli, Jacopo;Virgillito, Maria Enrica
2025
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.