Optimizing subsidy trajectory for carbon-mitigation technologies

Lei Zhu, Junqi Liu, Qin Li and Yuan Xu ()
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Lei Zhu: Beihang University
Junqi Liu: Beihang University
Qin Li: Beihang University
Yuan Xu: The Chinese University of Hong Kong

Mitigation and Adaptation Strategies for Global Change, 2025, vol. 30, issue 4, No 4, 30 pages

Abstract: Abstract Governments worldwide have implemented various subsidies for carbon-mitigation technologies, both on supply and demand sides, to accelerate their commercialization. This approach has become increasingly crucial as nations strengthen their climate commitments in response to the growing climate crisis. However, these subsidies can place significant financial burdens on public funds and consumers. Our study assesses how China could have optimized its development and subsidy strategies for major carbon-mitigation technologies in electricity generation. We develop an analytical framework for optimal subsidies that aims to support technological development while either minimizing subsidy costs or shortening the time to commercialization. Using a multiperiod dynamic programming model, we explore the relationships between technology adoption and subsidies, considering adopters' willingness to adopt. Our findings reveal the existence of an optimal subsidy trajectory for commercializing emerging technologies, which can be phased out based on learning rates and benchmark prices. Empirically, we demonstrate that China's feed-in tariff trajectories for wind and solar PV technologies could be improved, potentially reducing subsidy budgets by 18.76% and 20.07%, respectively, while still meeting the same deployment targets. Given the constraints on subsidy budgets and carbon neutrality timelines, our research offers insights to enhance the efficiency and effectiveness of technological development and deployment at both national and global levels.

Keywords: Carbon-mitigation technology; Dynamic programming; Willingness to adopt; Optimal subsidy (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11027-025-10215-y

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