Green Transition and Environmental Policy in Imperfectly Competitive Markets: Insights from Agent-Based Modelling

The debate on environmental policy increasingly focuses on aligning private incentives with social objectives in imperfectly competitive markets. While traditional literature has centred on public-based mechanisms like taxes and subsidies, a growing strand emphasizes private-based mechanisms, particularly green consumerism, where consumer preferences can drive firms’ adoption of clean technologies. Recent game-theoretic analysis shows that consumers’ willingness-to-pay can lead to various market equilibria, from all-green to all-brown outcomes. This paper complements this analytical approach by developing an agent-based model (ABM) to study the dynamic evolution of a spatial market where firms, based on relative performance, decide whether to supply brown or green products to heterogeneous consumers. Our computational simulations confirm that all three market structures—all-brown, all-green, and mixed—can endogenously emerge depending on average green consumer preferences. Furthermore, we evaluate the effectiveness of three policy instruments: an environmental tax, a subsidy to green firms, and a subsidy to green consumers. We find that supply-side policies are more effective than demand-side subsidies. Specifically, an environmental tax ensures the fastest convergence to an all-green market, while a production subsidy is most effective at reducing the share of brown firms and consumers in mixed-market scenarios. By bridging game-theoretic insights with agent-based computational analysis, this paper provides a dynamic and policy-relevant perspective on the transition to sustainable markets.