Key Findings and Policy Briefs No. 2 SPATIAL ANALYSIS OF RURAL DEVELOPMENT MEASURES

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1 SPATIAL ANALYSIS OF RURAL DEVELOPMENT MEASURES Key Findings and Policy Briefs No. 2 RDP expenditures and their objectives from a spatial perspective: Does funding correspond to needs?

2 RDP expenditures and their objectives from a spatial perspective: Does funding correspond to needs? What we did to answer this question: Explored the EU-27 CMEF (Common Monitoring and Evaluation Framework) database regarding impacts of RDP (measured as change of objective related baseline indicators) Identified neighbourhood effects between regions by Exploratory Spatial Data Analysis (ESDA) Economic objectives Economic growth Related axes 1, 3 and 4 Spatial Regions with high expenditure rates for the axes 1, 3 and 4 together tend to have neighbours with high rates as well, and vice versa (Moran s I value of ) High-high clusters: Eastern Europe (North-east, Poland, Lithuania, Hungary, parts of Romania, Bulgaria), part of North France and the Netherlands Low-low clusters: UK & Ireland, parts of Scandinavia, South of Spain, South of (?) France and South of (?) Italy, Greece Overall Relative expenditure for the axes related to this indicator is slightly positively correlated with "Change in Economic Development", "Share of primary sector in total GVA", and "Average annual growth rate of GVA in secondary and tertiary sectors", and slightly negatively correlated with "Total GDP per capita" (in convergence regions) and "Share of secondary and tertiary sectors in total GVA". This means that regions with high expenditure for the axes 1, 3 and 4 (>50% in total RDP expenditure) tend to have higher GDP growth rates (convergence regions) or at least a lower decrease in rates (non-convergence regions) compared to regions that allocate less than 50% of their RDP expenditure to these axes. Expenditure therefore seems to be appropriately targeted, if we assume that GDP is an effect of RDP expenditures. However, we also can assume many regions in which GDP develops independently from RDP expenditures. In those cases the judgement is not valid. Regions with high expenditure also tend to have a higher share of the primary sector in total GVA (only convergence regions) and a lower (convergence regions) or equal (non-convergence regions) importance of the secondary and tertiary sectors in terms of share in total GVA, while the annual growth rates in these sectors are higher compared to regions with less than 50% expenditure for related axes (both convergence and non-convergence regions).

3 Employment creation Related axes 3 and 4 Spatial Regions with high expenditure for the axes 3 and 4 together tend to have neighbours with high rates as well, High-high clusters: North/middle and the Netherlands, Bulgaria Low-low clusters: Portugal, South Spain, parts of France, South Italy, Greece Overall Combined expenditure for axes 3 and 4 slightly correlates positively with "Employment Rate, Employed persons/total population" and "Change in Employment Rate, Employed persons/total population (15_64 y.o.)". Thus, regions with higher expenditure rates for these two axes (>25% of RD total budget) tend to have a higher employment rate and a more positive employment development than regions with lower expenditure rates (both convergence and nonconvergence regions). Labour productivity Related axes 1 Spatial Regions with high expenditure for axis 1 tend to have neighbours with high rates as well, High-high clusters: Spain, North France, and in Eastern Europe (Poland, Lithuania, Latvia, Hungary, Slovakia, parts of Romania and Bulgaria). Low-low clusters: UK and Ireland, South and parts of Austria, in South Italy, and Scandinavia). Overall Expenditure is slightly positively correlated with "Change in Labour Productivity in Agriculture, average annual growth rate in nominal terms" (+0.25**), while absolute Labour Productivity showed no significant correlation. For the other objective-oriented baseline indicators assigned to axis 1, data is not yet available through the CMEF (no analyses possible). Convergence regions with higher axis 1 expenditure rates (>50%) are characterized by similar (low) absolute values for labour productivity but have higher annual growth rates than other EU-12 regions with below 50% expenditure rates for axis 1. Nonconvergence regions with higher axis 1 expenditure rates have on average a higher absolute labour productivity than regions with lower expenditure rates, but slightly lower annual growth rates. It is difficult to attribute higher labour productivity values to the presence of axis 1 expenditure, given that baseline dynamics occur and that rural development funding based on the EAFRD and national contribution is but one of a variety of instruments at EU and national scales. Higher values in regions with more axis 1 funding may also be an indication for a two-fold strategy pursued with axis 1. In non-convergence regions, axis 1 funding may contribute to stabilizing already competitive regions - the objective is "maintenance of competitiveness", which would also be in line with the fact that not the most "needy" but rather the most "viable" areas are the target of this aid. In convergence regions, the objective of axis 1 funding is more "increase of competitiveness". However, higher changes in labour productivity in regions with higher axis 1 funding rates, as observed, may again not necessarily be the result of the aid. It is also possible that priority is given to the most dynamic areas, where transitional structural change, for example, after EU accession is high anyway

4 (e.g. reduction of farm numbers, dropping out of non-competitive farms) thus resulting in positive labour productivity dynamics.

5 Environmental objectives Reversing biodiversity decline Policy message Data published yet are insufficiently complete, therefore no analyses possible Spatial Regions with high axis 2 expenditure tend to have neighbours with high rates as well, Low-low clusters: North Spain, North France/Netherlands, parts of, Poland, Maintenance of high nature value farming and forestry areas Policy message Data published yet are insufficiently complete, therefore no analyses possible Spatial Regions with high axis 2 expenditure tend to have neighbours with high rates as well, Low-low clusters: North Spain, North France/Netherlands, parts of, Poland, Improvement in water quality Policy message Data published yet are insufficiently complete, therefore no analyses possible Spatial Regions with high axis2 expenditure tend to have neighbours with high rates as well, Low-low clusters: North Spain, North France/Netherlands, parts of, Poland, Contribution to combating climate change Policy message Data published yet are insufficiently complete, therefore no analyses possible Spatial Regions with high axis2 expenditure tend to have neighbours with high rates as well, Low-low clusters: North Spain, North France/Netherlands, parts of, Poland,

6 Where can I find related maps, correlation coefficients and more detailed information on evidence? Visit the SPARD-IS at