Bootstraps for Meta-Analysis with an Application to the Impact of Climate Change

Research output: Contribution to JournalArticleAcademicpeer-review

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 $$^{\circ }\hbox {C}$$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 $$2.5\,^{\circ }\hbox {C}$$2.5C, rising to 15 % (50 %) for $$5.0\,^{\circ }\hbox {C}$$5.0C for a rate of risk aversion of 1 (2).
LanguageEnglish
Pages287-303
JournalComputational Economics
Volume46
Issue number2
DOIs
Publication statusPublished - 2015

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Climate change
Economics
Bootstrap
Meta-analysis
Uncertainty

Bibliographical note

PT: J; NR: 42; TC: 0; J9: COMPUT ECON; PG: 17; GA: CQ9CS; UT: WOS:000360909100007

Cite this

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title = "Bootstraps for Meta-Analysis with an Application to the Impact of Climate Change",
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 $$^{\circ }\hbox {C}$$∘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 $$2.5\,^{\circ }\hbox {C}$$2.5∘C, rising to 15 {\%} (50 {\%}) for $$5.0\,^{\circ }\hbox {C}$$5.0∘C for a rate of risk aversion of 1 (2).",
author = "R.S.J. Tol",
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Bootstraps for Meta-Analysis with an Application to the Impact of Climate Change. / Tol, R.S.J.

In: Computational Economics, Vol. 46, No. 2, 2015, p. 287-303.

Research output: Contribution to JournalArticleAcademicpeer-review

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