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Declining CO(2) price paths
Pricing greenhouse-gas (GHG) emissions involves making trade-offs between consumption today and unknown damages in the (distant) future. While decision making under risk and uncertainty is the forte of financial economics, important insights from pricing financial assets do not typically inform stan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800385/ https://www.ncbi.nlm.nih.gov/pubmed/31575747 http://dx.doi.org/10.1073/pnas.1817444116 |
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author | Daniel, Kent D. Litterman, Robert B. Wagner, Gernot |
author_facet | Daniel, Kent D. Litterman, Robert B. Wagner, Gernot |
author_sort | Daniel, Kent D. |
collection | PubMed |
description | Pricing greenhouse-gas (GHG) emissions involves making trade-offs between consumption today and unknown damages in the (distant) future. While decision making under risk and uncertainty is the forte of financial economics, important insights from pricing financial assets do not typically inform standard climate–economy models. Here, we introduce EZ-Climate, a simple recursive dynamic asset pricing model that allows for a calibration of the carbon dioxide ([Formula: see text]) price path based on probabilistic assumptions around climate damages. Atmospheric [Formula: see text] is the “asset” with a negative expected return. The economic model focuses on society’s willingness to substitute consumption across time and across uncertain states of nature, enabled by an Epstein–Zin (EZ) specification that delinks preferences over risk from intertemporal substitution. In contrast to most modeled [Formula: see text] price paths, EZ-Climate suggests a high price today that is expected to decline over time as the “insurance” value of mitigation declines and technological change makes emissions cuts cheaper. Second, higher risk aversion increases both the [Formula: see text] price and the risk premium relative to expected damages. Lastly, our model suggests large costs associated with delays in pricing [Formula: see text] emissions. In our base case, delaying implementation by 1 y leads to annual consumption losses of over 2%, a cost that roughly increases with the square of time per additional year of delay. The model also makes clear how sensitive results are to key inputs. |
format | Online Article Text |
id | pubmed-6800385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-68003852019-10-24 Declining CO(2) price paths Daniel, Kent D. Litterman, Robert B. Wagner, Gernot Proc Natl Acad Sci U S A Social Sciences Pricing greenhouse-gas (GHG) emissions involves making trade-offs between consumption today and unknown damages in the (distant) future. While decision making under risk and uncertainty is the forte of financial economics, important insights from pricing financial assets do not typically inform standard climate–economy models. Here, we introduce EZ-Climate, a simple recursive dynamic asset pricing model that allows for a calibration of the carbon dioxide ([Formula: see text]) price path based on probabilistic assumptions around climate damages. Atmospheric [Formula: see text] is the “asset” with a negative expected return. The economic model focuses on society’s willingness to substitute consumption across time and across uncertain states of nature, enabled by an Epstein–Zin (EZ) specification that delinks preferences over risk from intertemporal substitution. In contrast to most modeled [Formula: see text] price paths, EZ-Climate suggests a high price today that is expected to decline over time as the “insurance” value of mitigation declines and technological change makes emissions cuts cheaper. Second, higher risk aversion increases both the [Formula: see text] price and the risk premium relative to expected damages. Lastly, our model suggests large costs associated with delays in pricing [Formula: see text] emissions. In our base case, delaying implementation by 1 y leads to annual consumption losses of over 2%, a cost that roughly increases with the square of time per additional year of delay. The model also makes clear how sensitive results are to key inputs. National Academy of Sciences 2019-10-15 2019-10-01 /pmc/articles/PMC6800385/ /pubmed/31575747 http://dx.doi.org/10.1073/pnas.1817444116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Social Sciences Daniel, Kent D. Litterman, Robert B. Wagner, Gernot Declining CO(2) price paths |
title | Declining CO(2) price paths |
title_full | Declining CO(2) price paths |
title_fullStr | Declining CO(2) price paths |
title_full_unstemmed | Declining CO(2) price paths |
title_short | Declining CO(2) price paths |
title_sort | declining co(2) price paths |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6800385/ https://www.ncbi.nlm.nih.gov/pubmed/31575747 http://dx.doi.org/10.1073/pnas.1817444116 |
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