Work

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

Year: 2024

Type: article

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.

Source: Ecological Economics

DOI: 10.1016/j.ecolecon.2024.108497

Authors: Tommaso Rughi, Jacopo Staccioli, Maria Enrica Virgillito

Institutions: Scuola Superiore Sant'Anna, Università Cattolica del Sacro Cuore

Language: English

Topic: Sustainable Development and Policies

Subfield: Management, Monitoring, Policy and Law

Field: Environmental Science

Domain: Physical Sciences

SDGs: Decent work and economic growth, Industry, innovation and infrastructure, Climate action

Open Access status: hybrid

Estimated APC paid: $3,690