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

B-Tier
Journal: Ecological Economics
Year: 2025
Volume: 230
Issue: C

Authors (3)

Rughi, Tommaso (not in RePEc) Staccioli, Jacopo (not in RePEc) Virgillito, Maria Enrica (Scuola Superiore Sant'Anna)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:ecolec:v:230:y:2025:i:c:s092180092400394x
Journal Field
Environment
Author Count
3
Added to Database
2026-01-29