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.
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.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Keywords:||Environmental technology, Learning, R&D subsidy, Pigouvian tax|
|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|
Repository Staff Only: item control page