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Development and application of new methodological frameworks for the evaluation of environmental impacts of rural development programmes in the EU (ENVIEVAL)
Project
Project code: 312071, TI-BW-08-PID1479
Contract period: 01.01.2013
- 29.02.2016
Budget: 1,738,444 Euro
Purpose of research: Basic research
How can the provision of public goods such as biodiversity be effectively supported through the Common Agricultural Policy? This is one of the core questions in political and scientific debates of the future Common Agricultural Policy in the EU. To be able to answer this question requires the establishment of robust causal linkages between support measures and the desired environmental impacts and consistent methodological frameworks to assess environmental impacts across different scales and levels. Evaluations of environmental impacts of RDPs are characterized by a number of methodological challenges. However, recent methodological developments have improved the understanding and capacity of analysing the impacts of farming and forestry on the provision of public goods. Against this background, the main aim of ENVIEVAL is to develop and test improved tools for the evaluation of environmental impacts of rural development measures and programmes in EU Member States. The cost-effective application of new indicators and evaluation methods for environmental evaluations will be tested in a set of public good case studies and validated through close collaboration with evaluators monitoring organisations, managing authorities and the EU-Commisssion. The case studies pay particular attention to different data requirements of the evaluations methods and consider differences in data availabilities across different member states and regions. The results of the case studies will inform the methodological handbook for the evaluation of environmental impacts of RDPs. A large number of different data types and sources can be used for the case study testing including environmental monitoring data (e.g. biodiversity monitoring programmes, gross nutrient balances and landscape character data), FADN, agricultural census and policy support data. A range of different methods has been selected for case study testing for counterfactuals (e.g. propensity score matching, inclusions of multiple comparison groups considering different support intensities and changes in participation status over time), micro level (e.g. biophysical models, footprint method, and landscape metrics) and macro level (e.g. spatial econometrics, scaling methods, footprint method and landscape metrics) assessments.
Section overview
Subjects
- Agroeconomics