Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/305588 
Year of Publication: 
2024
Series/Report no.: 
CESifo Working Paper No. 11346
Publisher: 
CESifo GmbH, Munich
Abstract: 
There is a rapidly advancing literature on the macroeconomics of climate change. This review focuses on developments in the construction and solution of structural integrated assessment models (IAMs), highlighting the marriage of state-of-the-art natural science with general equilibrium theory. We discuss challenges in solving dynamic stochastic IAMs with sharp nonlinearities, multiple regions, and multiple sources of risk. Key innovations in deep learning and other machine learning approaches overcome many computational challenges and enhance the accuracy and relevance of policy findings. We conclude with an overview of recent applications of IAMs and key policy insights.
Subjects: 
climate change
integrated assessment model
dynamic stochastic general equilibrium
JEL: 
C61
E27
Q50
Q51
Q54
Q58
Document Type: 
Working Paper
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