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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.