Consistent and replicable estimation of bilateral climate finance

Item Type Journal paper
Abstract International climate finance is key to achieving the goals of the Paris Agreement. Here we develop a machine learning classifier to identify international climate finance from 2.7 million official development assistance projects between 2000 and 2019, resulting in a consistent and replicable inventory of 82,023 bilateral climate finance projects (US$80 billion). Our findings reinforce concerns that the actual numbers may be much lower than current estimates made with Rio markers.
Authors Toetzke, Malte; Stünzi, Anna & Egli, Florian
Journal or Publication Title Nature Climate Change
Language English
Subjects social sciences
political science
other research area
Responsibility and Sustainability e.g. SDGs
HSG Classification contribution to scientific community
Refereed Yes
Date 22 September 2022
Number 12
Page Range 897-900
Publisher DOI https://doi.org/10.1038/s41558-022-01482-7
Depositing User Dr. Anna Stünzi
Date Deposited 02 Dec 2022 15:37
Last Modified 02 Dec 2022 15:37
URI: https://www.alexandria.unisg.ch/publications/268238

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Citation

Toetzke, Malte; Stünzi, Anna & Egli, Florian (2022) Consistent and replicable estimation of bilateral climate finance. Nature Climate Change, (12). 897-900.

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https://www.alexandria.unisg.ch/id/eprint/268238
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