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Forecasting the Price of Carbon with Macroeconomic and Financial variables∗

Andrea Bastianin (), Elisabetta Mirto (), Yan Qin () and Luca Rossini ()
Additional contact information
Andrea Bastianin: University of Milan, Italy and Fondazione Eni Enrico Mattei (FEEM)
Elisabetta Mirto: Study Center Gerzensee, https://www.szgerzensee.ch/people/people-detail/cyril-monnet
Yan Qin: ClearBlue Markets
Luca Rossini: University of Milan, Italy and Fondazione Eni Enrico Mattei (FEEM)

No 26.03, Working Papers from Swiss National Bank, Study Center Gerzensee

Abstract: We tackle the issue of producing point, sign, and density forecasts for the monthly real price of carbon within the European carbon market, EU ETS. We show that a Bayesian Vector Autoregressive (BVAR) model, augmented with factors based on macroeconomic and financial variables, yields accuracy gains over a set of benchmark forecasts in both point and density forecasts. We also provide a qualitative comparison of model-based forecasts with survey expectations and forecasts released by data providers. Moreover, we consider verified emissions and demonstrate that adding stochastic volatility can further improve the forecasting performance of a single-factor BVAR model. Lastly, we rely on forecasts to build market monitoring tools that track demand and price pressure in the EU ETS.

Pages: 85 pages
Date: 2026-06
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