Work

Improving economic impact assessment of climate change with machine learning

Year: 2026

Type: article

Abstract: Hybrid modelling using machine learning can help improve the robustness and comprehensiveness of economic impact assessments of climate change by combining data with theory, bridging silos across social, economic, and financial systems, and linking micro- and macroeconomic scales.

Source: Nature Communications

DOI: 10.1038/s41467-026-73956-7

Authors: Anton Orlov, Jana Sillmann

Institutions: CICERO Center for International Climate Research, Universität Hamburg

Language: English

Topic: Climate Change Policy and Economics

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $6,990