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

41 Pages Posted: 28 Feb 2015

See all articles by Koki Oikawa

Koki Oikawa

Waseda University

S. Managi

Tokohu University - Graduate School of Environmental Studies

Multiple version iconThere are 2 versions of this paper

Date Written: February 27, 2015

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.

Keywords: Environmental technology, Learning, R&D subsidy, Pigouvian tax

JEL Classification: D83, O33, Q55, Q58

Suggested Citation

Oikawa, Koki and Managi, Shunsuke, R&D in Clean Technology: A Project Choice Model with Learning (February 27, 2015). Available at SSRN: https://ssrn.com/abstract=2571310 or http://dx.doi.org/10.2139/ssrn.2571310

Koki Oikawa (Contact Author)

Waseda University ( email )

1-104 Totsukamachi, Shinjuku-ku
tokyo, 169-8050
Japan

Shunsuke Managi

Tokohu University - Graduate School of Environmental Studies

Sendai, Miyagi
Japan

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