Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/315014 
Authors: 
Year of Publication: 
2025
Series/Report no.: 
Discussion Papers No. 25-03
Publisher: 
University of Bern, Department of Economics, Bern
Abstract: 
I use Bayesian VARs with stochastic volatility to forecast global temperatures and sea level and ice cover in the Northerin emisphere until 2010, by exploiting (i) their long-run equilibrium relationship with climate change drivers (CCDs) and (ii) the relationship between world GDP and anthropogenic CCDs. Assuming that trend GDP growth will remain unchanged after 2024, and the world will fully decarbonize by 2050, global temperatures and the sea level are projected to increase by 2.3 Celsius degrees and 38 centimeters respectively compared to pre-industrial times. Further, uncertainty is substantial, pointing to significant upward risks. Because of this, bringing climate change under control will require a massive programme of carbon removal from the atmosphere, in order to bring anthropogenic CCDs back to the levels of the XX century.
Subjects: 
Climate change
Bayesian VARs
stochastic volatility
cointegration
forecasting
conditional forecasts
JEL: 
E2
E3
Creative Commons License: 
cc-by Logo
Document Type: 
Working Paper

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