LAPSE:2023.17805
Published Article
LAPSE:2023.17805
How Much Should We Spend to Fight against Climate Change? The Value of Backstop Technologies in a Simplified Model
Carlos Pretel, Pedro Linares
March 6, 2023
Abstract
The estimation of the social cost of climate change is typically carried out with complex, difficult to interpret, integrated assessment models (IAMs). Instead, this paper presents a simple, tractable model with which to estimate the willingness to pay of societies against climate change. The model is based on an already comprehensive and intuitive one developed by Besley and Dixit, which has been modified by including a backstop technology (e.g., a renewable energy technology). This improved formulation allows for a more realistic representation of the climate change problem in that it is able to include the decoupling of economic growth and GHG emissions. The model allows us to understand the implications of different assumptions, such as the rate of growth of the economy, or the damages expected from climate change, on the willingness to pay against it. Our results show that, for a baseline scenario, the willingness to pay (WTP) is 0.52% of annual GDP, lower than that obtained by Besley and Dixit, which shows the significant benefits of developing competitive mitigation technologies. Our results also show the benefits of international collaboration, or of devoting more resources to R&D, as efficient ways to fight against climate change.
Keywords
adaptation, climate change, mitigation
Suggested Citation
Pretel C, Linares P. How Much Should We Spend to Fight against Climate Change? The Value of Backstop Technologies in a Simplified Model. (2023). LAPSE:2023.17805
Author Affiliations
Pretel C: Instituto de Investigación Tecnológica (IIT), ICAI, Universidad Pontificia Comillas, 28015 Madrid, Spain
Linares P: Instituto de Investigación Tecnológica (IIT), ICAI, Universidad Pontificia Comillas, 28015 Madrid, Spain [ORCID]
Journal Name
Energies
Volume
14
Issue
22
First Page
7781
Year
2021
Publication Date
2021-11-19
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14227781, Publication Type: Journal Article
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LAPSE:2023.17805
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https://doi.org/10.3390/en14227781
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