Effects of COVID-19 vaccination programs on EU carbon price forecasts: Evidence from explainable machine learning

Cai Yang, Hongwei Zhang and Futian Weng

International Review of Financial Analysis, 2024, vol. 91, issue C

Abstract: The COVID-19 pandemic continues to destroy the carbon market. To alleviate the situation, governments launched vaccination program campaigns. This study aims to predict two carbon pricing features––return and volatility––considering the impacts of the COVID-19 vaccination program. The present study applies the SHAPley Additive exPlanations method of model analysis and interpretability to determine the forces that predict carbon pricing. Our results show that compared with the volatility of the carbon market, the number of daily vaccinations has better predictive performance in terms of carbon pricing. However, compared with other related control factors, the predictive contribution of the COVID-19 vaccination program to volatility is greater than the return of the carbon market. In addition, a smaller number of daily vaccinations correspond to higher carbon market volatility and lower returns. Our results have crucial implications for investors and policymakers in stabilizing and promoting the carbon market during the COVID-19 pandemic; moreover, our results provide a reference for formulating new COVID-19 vaccination-related policies.

Keywords: EU carbon prices; SHAPley additive exPlanations; COVID-19 vaccination (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:91:y:2024:i:c:s1057521923004696

DOI: 10.1016/j.irfa.2023.102953

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