Chang, Jun-Jie;
Mi, Zhifu;
Wei, Yi-Ming;
(2023)
Temperature and GDP: A review of climate econometrics analysis.
Structural Change and Economic Dynamics
, 66
pp. 383-392.
10.1016/j.strueco.2023.05.009.
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Abstract
Climate econometric analysis of the relationship between temperature and gross domestic product (GDP) is increasingly being used to evaluate climate risks and understand economic impacts caused by climate change. We review the literature on growth and level effects (i.e., temperature rise respectively affects the growth and level of economic output), the setting of temperature variables’ forms and functional forms, and the inherent model specification of climate econometrics. Additionally, we introduce an approach for combining empirical findings with climate change integrated assessment models (IAMs) to improve damage modelling. Our findings show that estimates of damage through growth effects are generally much larger than those through level effects. Diverse impact mechanisms and adaptation effects can be revealed by changing the time resolution of temperature variables, introducing non-linearity into econometrics functions, and specifying temperature deviation. Combing the cross-sectional and panel model would enable us to examine the economic impacts at different future times.
Type: | Article |
---|---|
Title: | Temperature and GDP: A review of climate econometrics analysis |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.strueco.2023.05.009 |
Publisher version: | https://doi.org/10.1016/j.strueco.2023.05.009 |
Language: | English |
Additional information: | © 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Climate change, Temperature, GDP, Climate econometrics, Integrated assessment model |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
URI: | https://discovery.ucl.ac.uk/id/eprint/10172279 |
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