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

Koki Oikawa

No e093, Working Papers from Tokyo Center for Economic Research

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.

Pages: 43 pages
Date: 2015-04
New Economics Papers: this item is included in nep-env, nep-ino and nep-ppm
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Citations: View citations in EconPapers (5)

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Journal Article: R&D in clean technology: A project choice model with learning (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:tcr:wpaper:e93

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