A holistic comparison of European climate policies according to the data, not opinions

The question of how best to address climate change is fraught with uncertainty. Instead of relying on often conflicting expert opinions or incomparable assessments of isolated policies, we employ a data driven approach to holistically evaluate all climate policies at the same time. We also explicitly account for model uncertainty, which is ignored in most policy analysis. We test how effectively 23 different types of climate policies reduced emissions across 16 European countries between 2012 and 2023. We find that carbon taxes were the most effective tool to reduce economy-wide emissions, but sector-level results show significant heterogeneity. Regulations combined with taxes were more effective in the energy sector, subsidies were more effective in agriculture, subsidies complemented taxes in the industrial sector, and regulatory policies reduced emissions most in waste management. Policy mixes appear to be more effective than individual, isolated policies. We use Bayesian Model Averaging (BMA) as a natural method for dealing with model uncertainty.