2023/11 | LEM Working Paper Series | ||||||||||||||||
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Climate change and labour-saving technologies: the twin transition via patent texts |
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Tommaso Rughi, Jacopo Staccioli and Maria Enrica Virgillito |
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Climate change mitigation technologies; Labour-saving technologies; Search heuristics; Natural
Language Processing; Labour markets.
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JEL Classifications | |||||||||||||||||
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C38, J24, O33, Q55
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Abstract | |||||||||||||||||
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This paper provides a direct understanding of the twin transition from the innovative activity domain.
It starts with a technological mapping of the technological innovations characterised by both climate
change mitigation/adaptation (green) and labour-saving attributes. To accomplish the task, 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 impact on employment share
growth at 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.
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