Forecasting Global Temperatures by Exploiting Cointegration with Radiative Forcing

Luca Benati

Diskussionsschriften from Universitaet Bern, Departement Volkswirtschaft

Abstract: I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a no change scenario, the most favorable median forecast predicts the land temperature anomaly to reach 5.6 Celsius degrees in 2100. Forecasts conditional on alternative paths for the JRF show that, given the extent of uncertainty, bringing climate change under control will require to bring the JRF back to the level reached in the early years of the XXI century. From a methodological point of view, my evidence suggests that previous cointegration-based studies of climate change suffer from model mis-specification.

Keywords: Climate change; Bayesian VARs; cointegration; forecasting; conditional forecasts (search for similar items in EconPapers)
JEL-codes: E2 E3 (search for similar items in EconPapers)
Date: 2023-05
New Economics Papers: this item is included in nep-agr and nep-env
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Persistent link: https://EconPapers.repec.org/RePEc:ube:dpvwib:dp2308

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