Optimal Climate Policy When Damages are Unknown

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dc.contributor.author Rudik, Ivan
dc.contributor.author Rudik, Ivan
dc.contributor.department Economics
dc.date 2019-07-18T06:38:31.000
dc.date.accessioned 2020-06-30T02:14:02Z
dc.date.available 2020-06-30T02:14:02Z
dc.date.embargo 2016-12-23
dc.date.issued 2016-11-13
dc.description.abstract <p>Integrated assessment models (IAMs) are economists' primary tool for analyzing the optimal carbon tax. Damage functions, which link temperature to economic impacts, have come under fire because of their assumptions that may produce significant, and ex-ante unknowable misspecifications. Here I develop novel recursive IAM frameworks to model damage uncertainty. I decompose the optimal carbon tax into channels capturing parametric damage uncertainty, learning, and misspecification<br />concerns. Damage learning and using robust control to guard against potential<br />misspecifications can both improve ex-post welfare if the IAM's damage function is misspecified. However, these ex-post welfare gains may take decades or centuries to arrive.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/econ_workingpapers/16/
dc.identifier.articleid 1011
dc.identifier.contextkey 9499862
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath econ_workingpapers/16
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/22634
dc.relation.ispartofseries 16011
dc.source.bitstream archive/lib.dr.iastate.edu/econ_workingpapers/16/SSRN_id2516632.pdf|||Fri Jan 14 20:52:11 UTC 2022
dc.subject.disciplines Agricultural and Resource Economics
dc.subject.disciplines Climate
dc.subject.disciplines Natural Resources Management and Policy
dc.subject.disciplines Public Economics
dc.title Optimal Climate Policy When Damages are Unknown
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 4f2be8b1-765f-496e-b56f-c5ae8b0d74d0
relation.isOrgUnitOfPublication 4c5aa914-a84a-4951-ab5f-3f60f4b65b3d
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