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R&D in Clean Technology: A Project Choice Model with Learning

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  • Koki Oikawa

Abstract

In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for clean technology and a Pigouvian tax on a dirty technology on environmental R&D when it is uncertain how long the research takes to complete. The model is formulated as an optimal stopping problem, in which the number of successes required to complete the R&D project is finite and which incorporates learning about the probability of success. We show that the optimal R&D subsidy with the consideration of learning is higher than that without it. We also find that an R&D subsidy performs better than a Pigouvian tax unless the government can induce suppliers to make cost reduction efforts even after the new technology successfully replaces the old one. Moreover, by a two-project model, we show that a uniform subsidy is better than a selective subsidy.

Suggested Citation

  • Koki Oikawa, 2015. "R&D in Clean Technology: A Project Choice Model with Learning," Working Papers e093, Tokyo Center for Economic Research.
    • Handle: RePEc:tcr:wpaper:e93
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    Cited by:

    1. Koji Kotani & Makoto Kakinaka, 2017. "Some implications of environmental regulation on social welfare under learning-by-doing of eco-products," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(1), pages 121-149, January.
    2. Xiaobo Han & Yin Han & Rong Ke & Jinghua Zhao, 2022. "Research on the Cooperation Model of New Energy Vehicle Supply Chain under the Background of Government Subsidies Declining," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    3. Zhu, Min & Dong, Peiwu & Ju, Yanbing & Li, Jiajun & Ran, Lun, 2023. "Effects of government subsidies on heavy-duty hydrogen fuel cell truck penetration: A scenario-based system dynamics model," Energy Policy, Elsevier, vol. 183(C).
    4. Gao, Xiang & He, Xixi & Sun, Chuanwang & Wu, Dongmei & Zhang, Jie, 2025. "Innovation in shouldering green responsibility: ESG performance and green technology innovation," Energy Economics, Elsevier, vol. 142(C).
    5. Shao, Yanmin & Chen, Zhongfei, 2022. "Can government subsidies promote the green technology innovation transformation? Evidence from Chinese listed companies," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 716-727.
    6. Halkos, George E. & Papageorgiou, George J., 2018. "Pollution, environmental taxes and public debt: A game theory setup," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 111-120.

    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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