This paper proposes an approach for assessing the effectiveness of those agri-environmental schemes and rural development measures aimed at enhancing the natural value of farmland and, more generally, aimed at releasing the pressure on the environment due to agriculture. First, based on fine scale data, indicators derived from the High Nature Value farmland concept are tested at different scales, resolutions and situations: LAU2 for The Netherlands and LAU1 for France. The effect of rural development measures on the evolution of these indicators is then explored. Significant cause-effect relationships are found in the French cases, while only relationships of correlations are observed from the Dutch case study, obviously caused by a lack of data. Using fine scale data on rural development measures related to both 2000–2006 and 2007–2013 programming periods of the Common Agricultural Policy, a spatial econometrics methodology is applied to France, at national level on the one hand, and at a selected NUTS2 level on the other. The results indicate that agri-environmental schemes and specific rural development measures affect the changes in the indicators, and that the spatial scale of the analyses matters. In particular, results indicate that trends observed at the national scale do not necessarily apply at the regional scale (e.g. impacts of conversion to organic farming, the grassland premium, payments for water and biodiversity protection) underlining the importance of multi-scale assessments. Interestingly, delayed effects of the measures implemented in the 2000–2006 programming period, such as machinery investment aids and less-favoured area payments, are detectable. As regards the 2007–2013 rural development measures, the most significant positive effects on the farm nature value indicator are found, at the national level, for locally targeted agri-environmental schemes focused on biodiversity and water issues and, at the NUTS2 level, for supporting organic farming schemes. Given that the farm nature value indicator is built from three different indices (addressing crop diversity, grassland share, and wooded and afforested farmland) the effect of rural development measures on each of these individual indices is also explored. This enables the main structure and the magnitude of policy impacts to be captured and helps with the understanding of why certain objectives were not met. Key findings are relevant in the context of policy monitoring and evaluation, while the methodology proposed, that incorporates spatial effects, is an important contribution to the implementation of the Common Monitoring and Evaluation Framework by Member States to account for national, regional or local characteristics.