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Abstract

Policymakers combine many different policy tools to achieve emission reductions. However, there remains substantial uncertainty around which mixes of policies are effective. This uncertainty stems from the predominant focus of ex post policy evaluation on isolating effects of single, known policies. Here we introduce an approach to identify effective policy interventions in the EU road transport sector by detecting treatment effects as structural breaks in CO2 emissions that can potentially occur in any country at any point in time from any number of a priori unknown policies. This search for ‘causes of effects’ within a statistical framework allows us to draw systematic inference on the effectiveness of policy mixes. We detect ten successful policy interventions that reduced emissions between 8% and 26%. The most successful policy mixes combine carbon or fuel taxes with green vehicle incentives and highlight that emissions reductions on a magnitude that matches the EU zero emission targets are possible.