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Bootstraps for meta-analysis with an application to the total economic impact of climate change

journal contribution
posted on 2023-06-08, 22:25 authored by Richard TolRichard Tol
Abstract Bootstrap and smoothed bootstrap methods are used to estimate the uncertainty about the total impact of climate change, and to assess the performance of commonly used impact functions. Kernel regression is extended to include restrictions on the functional form. Impact functions do not describe the primary estimates of the economic impacts very well, and monotonic functions do particularly badly. The impacts of climate change do not significantly deviate from zero until 2.5–3.5 ?C warming. The uncertainty is large, and so is the risk premium. The ambiguity premium is small, however. The certainty equivalent impact is a negative 1.5 % of income for 2.5 ?C, rising to 15 % (50 %) for 5.0 ?C for a rate of risk aversion of 1 (2).

History

Publication status

  • Published

Journal

Computational Economics

ISSN

0927-7099

Publisher

Springer Verlag

Issue

2

Volume

46

Page range

287-303

Department affiliated with

  • Economics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2015-09-08

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