Knowledge spillovers between clean and dirty technologies: Evidence from the patent citation network

Abstract:

Can dirty incumbents leverage their existing knowhow to transition to clean technologies? To address this question, we systematically measure direct and indirect knowledge spillovers between clean and dirty technologies using the patent citation network. We assume citations reflect pathways of learning and knowledge proximity. We first examine the proportion of citations in clean patents that directly refer to dirty technologies. Secondly, we investigate how clean and dirty technologies are indirectly linked in the citation network and which sectors most frequently bridge these two fields. We find that less than one-tenth of clean patents contain a direct citation to prior dirty patents, but nearly two-thirds are indirectly linked. Significant sectoral heterogeneity exists. Patents related to control technologies, data processing and optimization, and the management of heat and waste, frequently serve as bridges between clean and dirty technologies in the citation network. Our results have implications for: firm-level diversification strategies, green industrial policy, and the modelling of directed technical change, where lower knowledge spillovers between clean and dirty technologies correspond to higher path dependencies.