Speaker: Aurélien Saussay

Title: The social and environmental consequences of the twin energy-digital transition

Abstract: We analyze the labor market and environmental impacts of the concurrent diffusion of green and automation technologies using a novel dataset linking patent data to establishment-level job postings from 2010 to 2023. We develop a new measure of establishment-level technology adoption by constructing semantic similarity links between patent content and skill requirements in online job advertisements. We contribute three novel findings. First, we document substantial heterogeneity in the labor market impacts across green technology types: innovations in green ICT and buildings technologies appear labor-augmenting, while advances in green transportation and smart grids tend to be labor-saving. Over time, green innovation as a whole has become increasingly labor-saving. Second, using a shift-share instrumental variable (SSIV) empirical design, we find that increased green technology adoption leads to job creations, which are moderately skill-biased.  Finally, despite potential concerns, we find no evidence that automation technology adoption weakens emissions reductions at the establishment level. Our results suggest that the twin green-digital transition may support both employment and environmental goals.