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Spatial Analysis of Rural Development Measures

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Improving rural development programming

The strategic importance placed on rural development (RD) demonstrates the EU's commitment to facing the challenges of food security, climate change, and growth and jobs in rural areas. An EU initiative has developed a tool to assist stakeholders in creating and implementing enhanced programmes.

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Rural Development Programmes (RDPs) have played a major role in successfully addressing the specific needs and challenges facing rural areas. However, with EU funding down, there was a need to make RDPs more accountable. As a result, the EU introduced the Common Monitoring and Evaluation Framework (CMEF) to monitor and evaluate all RD actions during the period 2007–2013. These statistics, together with data compiled by national managing authorities and other stakeholders, lacked an integrated, systematic analysis effective on any level. The overall aim of the EU-funded project 'Spatial analysis of rural development measures' (SPARD) was to determine if territory and immediate surroundings affect the success of RD measures and to what degree. Activities began by capturing all CMEF information and other statistical and economic data related to RD to create a user-friendly infrastructure for remote data access and storage. This warehouse harmonises data from all sources. Researchers developed a conceptual framework establishing coherent links between political aims, RD measures and outcomes. This analytical framework devised theories about the causal relationships between spending, requirements, features and policy consequences. It also identified target areas and target groups of RD measures. The team applied spatial econometric modelling approaches and developed different models for specific broadly applied RD measures to better understand the links between RD measures, their uptake and their outcomes. Results provide policymakers at EU, national and regional levels with insights on determinants for successful measure uptake and its spatial dimension and hence for better policy targeting. Finally, researchers designed an information system that integrates the data warehouse and all project findings. It enables end users to carry out horizontal and vertical evaluations to clarify CMEF indicators and causal relationships. More efficient RDP and RD instruments will give farmers the flexibility to deal with pressing issues within a given territory that reflect their particular economic, natural and structural circumstances. SPARD will ultimately lead to enhanced competitiveness, as well as rural and environmental sustainability.

Keywords

Rural development, Rural Development Programmes, rural areas, Common Monitoring and Evaluation Framework, spatial analysis, spatial econometric modelling, rural development measures, remote data access, policy targeting

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