Mixing innovation policies for low-carbon transitions? An agent-based approach

This study examines whether combining climate policy instruments outperforms single instruments in promoting low-carbon innovation while preserving economic performance. The analysis employs an agent-based model that links heuristic search on a two-dimensional NK landscape with oligopolistic competition and boundedly rational demand. The paper simulates all combinations of five policy instruments at two intensities —R&D subsidies, adoption subsidies, carbon taxes, command-and-control, and a research park. Policy mixes are evaluated based on their economic and environmental impacts across alternative technological assumptions concerning the search complexity and features distribution of the technologies. Across scenarios, mixes that include carbon taxes and regulation deliver the largest emission reductions, while adding research-support instruments mitigates output losses at a modest fiscal cost. While multiple instruments tailored to specific technological possibilities minimize the economic losses caused by emission reductions, single instruments outperform policy mixes under technological uncertainty.