Conference Agenda

Agri-environment schemes (AES) are a key instrument of EU biodiversity policy, yet their effectiveness remains contested due to selection bias and limited outcome measurement. This study provides the first nationwide, field-level evaluation of AES in the Czech Republic using a complete administrative census (2015–2022; almost 1.3 million field-year observations) linked to a robust, species-distribution-model-based biodiversity potential index. We estimate AES impacts at both the extensive margin (enrollment) and intensive margin (payment intensity, measure stacking) using farmer and year fixed effects and instrumental-variable strategies. Results show negligible average effects of enrollment once selection is addressed, modest positive elasticities for subsidy intensity (0.4–0.6 %), and gains from stacking measures without evidence of diminishing returns. Policy allocation is heavily skewed toward permanent grassland, where baseline biodiversity potential is already high, while high-contrast measures on arable land remain rare and underfunded. These findings highlight that ecological additionality depends less on binary participation and more on targeting, measure type, and landscape context. We conclude that reallocating resources toward high-contrast arable prescriptions and piloting results-based payments could improve biodiversity outcomes per unit of public spending.