Adapting to Climate Change: an Analysis under Uncertainty

David García-León

No 2016.10, Working Papers from Fondazione Eni Enrico Mattei

Abstract: Climate change is a phenomenon beset with major uncertainties and researchers should include them in Integrated Assessment Models. However, including further dimensions in IAM models comes at a cost. In particular, it makes most of these models suffer from the curse of dimensionality. In this study we benefit from a state-reduced framework to overcome those problems. In an attempt to advance in the modelling of adaptation within IAM models, we apply this methodology to shed some light on how the optimal balance between mitigation and adaptation changes under different stochastic scenarios. We find that stochastic technology growth hardly affects the optimal bundle of mitigation and adaptation whereas uncertainty about the value of climate sensitivity and the possibility of tipping points hitting the system change substantially the composition of the optimal mix as both persuade the risk-averse social planner to invest more in mitigation. Overall, we identify that including uncertainty into the model tends to favour (long-lasting) mitigation with respect to (instantaneous) adaptation. Further research should address the properties of the optimal mix when a stock of adaptation can be built.

Keywords: Climate Change; Adaptation; Mitigation; Dynamic Programming; Uncertainty; Integrated Assessment; DICE (search for similar items in EconPapers)
JEL-codes: C61 D58 D90 O44 Q01 Q54 Q56 (search for similar items in EconPapers)
Date: 2016-01
New Economics Papers: this item is included in nep-env and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://feem-media.s3.eu-central-1.amazonaws.com/w ... oads/NDL2016-010.pdf (application/pdf)

Related works:
Working Paper: Adapting to Climate Change: an Analysis under Uncertainty (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fem:femwpa:2016.10

Access Statistics for this paper

More papers in Working Papers from Fondazione Eni Enrico Mattei Contact information at EDIRC.
Bibliographic data for series maintained by Alberto Prina Cerai (alberto.prinacerai@feem.it this e-mail address is bad, please contact repec@repec.org).