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.
| Original language | English |
|---|---|
| Pages (from-to) | 175-195 |
| Number of pages | 21 |
| Journal | Journal of Economic Behavior and Organization |
| Volume | 117 |
| DOIs | |
| Publication status | Published - 2015 Sep 1 |
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Keywords
- Environmental technology
- Learning
- Pigouvian tax
- R&D subsidy
ASJC Scopus subject areas
- Organizational Behavior and Human Resource Management
- Economics and Econometrics
Cite this
R&D in clean technology : A project choice model with learning. / Oikawa, Koki; Managi, Shunsuke.
In: Journal of Economic Behavior and Organization, Vol. 117, 01.09.2015, p. 175-195.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - R&D in clean technology
T2 - A project choice model with learning
AU - Oikawa, Koki
AU - Managi, Shunsuke
PY - 2015/9/1
Y1 - 2015/9/1
N2 - 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.
AB - 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.
KW - Environmental technology
KW - Learning
KW - Pigouvian tax
KW - R&D subsidy
UR - http://www.scopus.com/inward/record.url?scp=84936944964&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84936944964&partnerID=8YFLogxK
U2 - 10.1016/j.jebo.2015.06.015
DO - 10.1016/j.jebo.2015.06.015
M3 - Article
AN - SCOPUS:84936944964
VL - 117
SP - 175
EP - 195
JO - Journal of Economic Behavior and Organization
JF - Journal of Economic Behavior and Organization
SN - 0167-2681
ER -