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- W3126137448 abstract "In this study, we investigate the qualitative and quantitative effects of an R&D subsidy for a 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 learning about the probability of success is incorporated. 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 suppliers have sufficient incentives to continue cost-reduction efforts after the new technology successfully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy." @default.
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- W3126137448 date "2015-09-01" @default.
- W3126137448 modified "2023-10-18" @default.
- W3126137448 title "R&D in clean technology: A project choice model with learning" @default.
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- W3126137448 doi "https://doi.org/10.1016/j.jebo.2015.06.015" @default.
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