R&D in clean technology: A project choice model with learning

Oikawa, Koki & Managi, Shunsuke (2015) R&D in clean technology: A project choice model with learning. Journal of Economic Behavior and Organization, 117, pp. 175-195.

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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 success-fully replaces the old one. Moreover, by using a two-project model, we show that a uniform subsidy is better than a selective subsidy.

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ID Code: 95233
Item Type: Journal Article
Refereed: Yes
Keywords: Environmental technology, Learning, R&D subsidy, Pigouvian tax
DOI: 10.1016/j.jebo.2015.06.015
ISSN: 0167-2681
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
Copyright Owner: Copyright 2015 Elsevier B.V.
Deposited On: 28 Apr 2016 00:16
Last Modified: 29 Apr 2016 00:03

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