Balancing Technology-Push and Demand-Pull Policies for Accelerating the Diffusion of Clean Energy

The urgency of reducing CO2 emissions to mitigate climate change requires simultaneous efforts for fostering clean energy innovation and for accelerating their deployment. This poses a challenge for policymakers who need to allocate resources into different policy instruments, in particular, between technology-push and demand-pull policies. Both types of policies have proven important elements for accelerating the clean energy transition. Technology-push policies aim to enhance the supply of technologies by providing incentives that reduce the costs of their development (e.g., through direct subsidies to research and development efforts). Demand-pull policies, on the other hand, pursue the acceleration of technological change by stimulating the demand for innovations (e.g., through fiscal and financial incentives for adopters). Research in policy mixes have highlighted the relevance of and inter-dependences between these two types of policies. However, we still lack a sufficient understanding of how to balance these policies within a socio-technical system in transition in order to maximize the efficiency and effectiveness of the policy interventions. In this paper, we use agent-based modelling to simulate how the relative focus on technology-push vs. demand-pull policies affects the outcome of policy interventions. Based on historical data, we simulate the evolution of the solar photovoltaic industry in Germany over the past few decades. Over this period, solar photovoltaics in Germany transitioned from a small niche technology into a threat to incumbents of the electricity system. At the same time, the balance between technology-push and demand-pull policies shifted strongly towards interventions aimed at stimulating demand. Using an agent-based model, this research provides a unique look into the effect of the policy balance upon the behavior of individual firms (e.g., decisions on R&D budgets, number of employees) and adopters of the technologies (e.g., farmers and households). We develop a set of policy scenarios that implement alternative balances between technology-push and demand-pull policies. Our results suggest that whether a focus on technology-push or demand-pull policies is more effective depends on two important factors: (1) the priorities of policymakers and (2) the relative weight policymakers put on present against future outcomes. A focus on technology-push provides an effective intervention if policymakers pursue industry policy goals (e.g., number of jobs) and put a stronger weight on future outcomes. A focus on demand-pull is more effective if policymakers prioritize emission reduction targets and strongly value short-term outcomes. Our study contributes to the literature on policy mixes and the political economy of the global energy transition by quantitatively exploring the importance of balancing technology-push and demand-pull policy instruments. Moreover, by stressing the relevance of policy goals, our research helps more closely integrate the literature on policy mixes and politics. These results are highly relevant to the current discussion in multiple countries into how to balance policy interventions in the battery storage or electric vehicle industries.