Causal inference analysis reveals synergistic policy mixes drive low-carbon innovation takeoffs across 18 major nations, highlighting sector-specific instrument combinations for climate action.
Climate policy is a critical driver of low-carbon technology (LCT) innovation; however, prior studies pay insufficient attention to the combined effects of multiple policies. Addressing this deficiency, we combine machine learning with causal inference to endogenously detect sector-specific LCT ‘takeoffs’ in 18 major LCT nations from 2001–2022, systematically evaluating the impacts of over 1,600 policy interventions. Results show that some climate policy interventions act as key triggers for takeoffs in LCT innovation, with synergistic policy mixes forming the primary impact mechanism. In aggregate, market-based instruments (MBI), especially subsidies, serve as the foundational lever for innovation; non-market-based instruments (NMBI), notably performance standards, provide essential complementarity; and targets & governance (T&G) enhance long-run credibility and implementation capacity. At the sectoral level, the buildings sector exhibits the highest responsiveness to policy; its dispersion of agents yields a more diffuse and diverse composition of effective interventions. Electricity tends to favour complex ‘MBI + NMBI + T&G’ packages tailored to its capital-intensive, incumbent-dominated structure. Industry displays the mildest response, with cost sensitivity leading to a profile dominated by pricing and subsidies. In transport, the most effective interventions are dominated by ‘subsidy + targets’ combinations. This study suggests a general policy synergy pathway defined as ‘MBI as drivers + differentiated NMBI aligned with sectoral characteristics as complements + T&G as amplifiers’, which provides strong empirical evidence and practical guidance for designing LCT innovation policies.
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Yan et al. (2026) studied this question.
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