ETS and Technological Innovation: A Random Matching Model
Angelo Antoci, Simone Borghesi, Mauro Sodini
C62, C63, C73, C78, O33, Q55, Q58
Emissions Trading, Technological Innovation, Random Matching, Evolutionary Game, Penalty System, Strategic Behaviour
Climate Change and Sustainable Development
The present paper investigates the functioning of an Emission Trading System (ETS) and its impact on the diffusion of environmental-friendly technological innovation in the presence of firms’ strategic behaviours and sanctions to non-compliant firms. For this purpose, we study an evolutionary game model with random matching, namely, a context in which a population of firms interact through pairwise random matchings. We assume that each firm has to decide whether to adopt a new clean technology or keep on using the old technology that requires pollution permits to operate and that the strategy whose expected payoff is greater than the average payoff spreads within the population at the expense of the alternative strategy (the so-called replicator dynamics). We investigate the technological dynamics and the stationary states that emerge from the model. From the analysis of the model, we show that by properly modifying the penalty on non-compliant firms, it is possible to shift from one dynamic regime to another and that an increase in permits trade can promote the diffusion of innovative pollution-free technologies.