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Territorial Impacts of the CAP ESPON Project 2.1.3 Deborah Roberts Arkleton Centre for Rural Development Research University of Aberdeen, Scotland Partners: •Federal Institute for Less-Favoured and Mountainous Areas, Austria •Institute of Spatial Planning, University of Dortmund, Germany •National Institute for Regional and Spatial Analysis, Ireland Background • CAP is a key sectoral policy • Gradual CAP reform (from Pillar 1 to Pillar 2) Aim of Project: To provide new knowledge, concepts and indicators of the territorial impact of agricultural and rural development policy (across EU27 at NUTS3) • Assessed against higher level EU objectives • Networking with other TPGs and Common Platform Methods Territorial Impact Assessment (TIA) method Stage 1: • Development of hypotheses • Statistical analysis of incidence of support • Initial statistical analysis of impact • Literature search • Apportionment and analysis of output from CAPRI model of MTR proposals Stage 2: • Case studies plus…. Data sources and coverage • EU sources • National sources for apportionment data • Policy data from OECD, FADN, RDP budgets CAP and cohesion (Pillar 1) Single variable regression analysis: Pillar 1 per AWU Pillar 1 per ha GDP per inhabitant - Unemploy rates -** Pop. change 95-99 +** +** -** +** Note: ** means significant at the 5% level •Pillar 1 support works strongly against cohesion •Distribution of direct income payments more consistent with cohesion objectives (esp. crops) •Level of Pillar 1 support favours core as against periphery (EU level) Total Pillar 1 Support per AWU CAP and cohesion (Pillar 2) Single variable regression analysis: GDP per inhabitant Unemp. rate Pop. change 95-99 +** +** -** -** - -** -** -** +** + Based on FADN data: Pillar 2 per AWU Pillar 2 per ha Based on RDF data: Pillar 2 per AWU (RD) Pillar 2 per ha (RD) Note: ** means significant at the 5% level •At EU level, pillar 2 support does not seem to be consistent with cohesion objectives •Distribution of Pillar 2 support positively associated with peripherality (EU level) Differences in territorial application of Pillar 2 Dwyer et al analysed use of Pillar 2 measures across EU15 and SAPARD in CEECs. • Very uneven allocation of RDR funds • Difficulties of co-financing in poorer regions • Richer regions use Pillar 2 to promote environmental land management, while poorer regions seek to modernise agriculture. LFA support per AWU Agri-environmental subsidies per AWU Percentage change in Farm Incomes resulting from MTR Proposals Policy implications • Increase switch from Pillar 1 to Pillar 2 and broaden focus of RD policies. •Allocate RDF according to criteria of relative needs for rural development and environmental management. • Need for a coherent framework for horizontal and vertical integration of policies. •Polycentricity: the RDF could be used to offset centralising forces at regional level, targeting rural hinterlands. •Database should be improved so as to enable comparable European wide analysis. Main challenges for next phase Development of TIA method • Further statistical analysis of Nuts 3 database – CAP and Polycentricity – CAP and environmental sustainability – Panel data analysis • Micro-scale analysis based on FADN • Case studies in farm household adaptation and good practice in territorial rural development – Cluster analysis to help inform choice of case studies.