Data for "Policy Mixes and Major Emission Reductions in European Agriculture"

Greenhouse gas (GHG) emissions from agriculture are a major driver of climate change. Although various policies have been implemented to reduce agricultural GHG emissions, there is limited understanding of the effectiveness of existing climate policies. Existing ex-post evaluations have mainly focused on establishing causal evidence for specific policies in isolation, potentially overlooking the interactions and combined effects of policy mixes. This paper aims to address this limitation by applying a reverse causal approach to analyze how policy mixes drive major GHG emission reductions in agriculture. We identify policy-induced structural changes in agricultural GHG emissions across the 27 European Union (EU) member states between 2000 and 2021. The detected breaks are then systematically linked to associated policy mixes. To characterize these mixes in more detail, we employ a large language model (LLM) classifier to identify specific policy instruments within the relevant legislative texts. In total, we considered more than 100,000 individual policy measures, spanning regulatory, market‐based, and voluntary instruments, to improve the plausibility that every detected change could be attributed to the potentially most relevant combination of policies. The analysis identifies ten successful policy interventions in seven EU member states, which reduced emissions between 5% and 24%. Our results reveal that successful reductions are rarely driven by single instruments but by policy mixes where regulatory baselines are reinforced by financial incentives and informational measures. Our findings emphasize the importance of policy combinations for effectively reducing agricultural GHG emissions and highlight the need for further efforts in the EU to improve climate change mitigation.