Tol, Richard S J (2014) Bootstraps for meta-analysis with an application to the total economic impact of climate change. Computational Economics, 46 (2). pp. 287-303. ISSN 0927-7099

Full text not available from this repository.

Abstract

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).

Item Type:	Article
Schools and Departments:	School of Business, Management and Economics > Economics
Subjects:	H Social Sciences > HB Economic theory. Demography
Depositing User:	Richard Tol
Date Deposited:	08 Sep 2015 11:44
Last Modified:	08 Sep 2015 11:44
URI:	http://srodev.sussex.ac.uk/id/eprint/56592

📧 Request an update