The Clean Transition in a Network Economy

Clean technologies are expected to play an important role in the transition to a low carbon economy (International Energy Agency, 2021). In this paper, I develop a theoretical model to study the development and adoption of these technologies, and the optimal intervention to manage the transition to a low carbon economy taking into account the damages from carbon emissions.

I first investigate the adoption of clean technologies and their effect on emissions by developing an endogenous production network model. Sectors can be described as "dirty" (e.g., oil) if their usage generates emissions or "clean" if otherwise. Each sector features a "dirty" technology that uses inputs from "dirty" sectors and a "clean" technology that does not. Competition between these technologies determines their adoption and the structure of the network. This model captures the interdependence of clean technologies across sectors as their adoption depends on the price of intermediate inputs, while their effect on emissions depends on the use of clean technologies in their direct and indirect inputs. I characterise the equilibrium of the model, show how total emissions relates to the centrality of the dirty sectors, and find that the total benefit from switching to a clean technology in a given sector depends on its indirect links to the dirty sector.

I then introduce endogenous technical change into this framework to study the development and adoption of clean technologies, the time path of emissions, and their welfare implications. This approach captures the feedback between adoption and development as higher adoption increases market size and innovation incentives, while more productive technologies increases adoption. In later work, I will use computational methods to study optimal policy in a stylised version of the steel industry.