A Mixed Geographically Weighted Approach to Decoupling and Rural Development in the EU-15 Commission of the UE Genedec project (FP6-502184) Francesco Pecci University of Verona - Italy Maria Sassi University of Pavia - Italy 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Importance of the analysis Rural development reform (2007-13) CAP reform (2003-04) Interventions locally based Agricultural policy Identification of areas where the use of support for Rural developmet creates the most value added at the EU level The need for …. Where…. Is a priority for the EU. Integration with Health Check communication broad development policy for rural areas 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Two issues for the agricultural sector 1. Importance of the analysis Identification of a set of policy sensitive indicators Policy decisions can be spatially varied across regions Territorial dimension of their impact on agricultural sector Recognition of spatial heterogeneity 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Spatial heterogeneity Sevilla, Spain, January 29th -February 1st, 2008 1. Importance of the analysis OLS Location specific A global parameters DXki As the understanding of spatial heterogeneity of agricultural productivity marginal respnses is desirable for policy decision I want to make this point more cliar. Dbki Dyi Cov(xki,bki,) 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Spatial heterogeneity Sevilla, Spain, January 29th -February 1st, 2008 1. Importance of the analysis OLS MGWR Some spatial non stationary As the understanding of spatial heterogeneity of agricultural productivity marginal respnses is desirable for policy decision I want to make this point more cliar. Global parameters Local papameters 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Outline Selection of a set of policy sensitive indicators 1. Importance of the analysis 2. Outline Selection of a set of policy sensitive indicators Key components of the reform of the I & II pillar of the CAP Estimation of the spatial non-stationary parameters affecting agricultural productivity Mixed Geographically Weighted Regression Identification of groups of regions with homogeneous values of SNS parameters Kohonen SOM

Sevilla, Spain, January 29th -February 1st, 2008 Indicators 1. Importance of the analysis Demographic features Innovation (R&D and human capital) Regional socio- economic attraction capacity 2. Outline 3. Indicators 164 EU-15 regions NUTSII Regio, FADN Infrastructure Agricultural diversification Agricultural productivity Labour market Farm Structure Economic development Environmental sustainability EU intervention 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Sevilla, Spain, January 29th -February 1st, 2008 Data processing chain 1. Importance of the analysis 3. MGWR empirical model 2. VIF 1. Initial data set 2. Object of the analysis 3. Indicators 6. GWR 4. Monte Carlo test 4. Data processing chain 7. SVD 5a. Global parameters 5b. Local parameters 8. Spatial non-stationary parameters 10. Kohonen SOM classification 11.Regionalization results 9. Spatial NS parameters for classification 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Spatial Non-stationary Parameters Results Spatial Non-stationary Parameters 1. Importance of the analysis Demographic features Innovation (R&D and human capital) Regional socio- economic attraction capacity 2. Object of the analysis 3. Indicators 164 regions EU-15 Infrastructure 4. Data processing chain Diversification Agricultural productivity 5. Results: Non-stationary parameters Labour market The variables affecting only locally the agricultural productivity are not only agricultural but also socio-economic and environmental variables Farm Structure Economic development Environmental sustainability EU intervention 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Results: Cluster analysis EU-15 1. Importance of the analysis 2. Object of the analysis 3. Indicators 4. Data processing chain 5. Results: Non-stationary parameters 5.1. Results: Cluster analysis EU-25 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Results: Cluster analysis EU-15 Farm structure, environmental sustainability, physical infrastructures 1. Importance of the analysis Cluster 5 Diversification in inseparable activities, agric. Sustainability, physical inf. 2. Object of the analysis Cluster 1 Physical infrastructure 3. Indicators 4. Data processing chain 5. Results: Non-stationary parameters Cluster 4 Farmers diversification in other gainful act., unemployment, physical infrastructure, total subsidies 5.1. Results: Cluster analysis EU-25 Cluster 6 Diversification, agric. Sustainability, social infrastructures Cluster 3 Agricultural diversification and sustainability, social infrastructure 107th EAAE Seminar "Modeling of Agricultural and Rural Development Policies". Sevilla, Spain, January 29th -February 1st, 2008

Conclusions Data sources Modulation, regionalization 1. Importance of the analysis Spatial non-stationarity matters Modulation, regionalization multi-sector and multi-region interventions 2. Object of the analysis 3. Indicators 4. Data processing chain Role of the EU (Health Check) and of the Member States and Regions (policy design capacity, Political will, establishing networks) Approaches to agricultural and rural development policy assessment: a better integration between partial and GE approaches 5. Results: Non-stationary parameters Data sources 5.1. Results: Cluster analysis EU-25 6. Conclusions