EUROPEAN COMMISSION Brussels, 10.12.2021 SWD(2021) 394 final COMMISSION STAFF WORKING DOCUMENT



EVALUATION

of the impact of the Common Agricultural Policy on territorial development of rural areas {SWD(2021) 398 final}



Table of contents 1.INTRODUCTION 2.BACKGROUND OF THE INTERVENTION 2.1Description of the intervention and its objectives 2.2Baseline and points of comparison 3.IMPLEMENTATION/STATE OF PLAY 4.METHODOLOGY 5.ANALYSIS 5.1Effectiveness 5.2Efficiency 5.3Coherence 5.4 Relevance 5.5 EU added value 6.CONCLUSION 4.ANNEX 1: PROCEDURAL INFORMATION 5.ANNEX 2: STAKEHOLDER CONSULTATION 6.ANNEX 3: METHODOLOGY 7.ANNEX 4: TABLES AND GRAPHS SUPPORTING THE STUDY





Glossary BPS Basic Payment Scheme CAP Common agricultural policy CATS Clearance of accounts audit trail system CLLD Community-led local development CMEF Common Monitoring and Evaluation Framework EAGF European Agricultural Guarantee Fund EAFRD European Agricultural Fund for Rural Development EFA Ecological focus area EIP European Innovation Partnership ESIF European structural and investment funds EU European Union EUR Euro, Eurozone currency FADN Farm Accountancy Data Network FAO Food and Agriculture Organization of the United Nations GDP Gross domestic product GVA Gross value added ITI Integrated territorial investments

LAGs Local action groups NGOs Non-governmental organisations SAPS Single Area Payments Scheme Definitions Balanced territorial development refers to territorial cohesion and convergence (a complementary policy objective), aiming to address the development gaps between economically flourishing regions and those falling behind, through targeted policy interventions and investments. It also refers to the policy aim to improve the working and living conditions and economic factors of all Member States and regions. Social inclusion refers to the living and working conditions of people in situations of vulnerability, such as the rural poor (farmers and non-farmers) populations living in remote rural areas (isolation issue), rural women, young people, older people, people with disabilities, people with a Roma or migration background.

1.1. INTRODUCTION One of the EU’s main objectives is to strengthen its economic, social and territorial cohesion. The Treaty on the functioning of the European Union requires it to promote harmonious development and seek to reduce disparities, with special attention to rural areas. The Treaty also calls for ensuring a fair standard of living for the agricultural community, particularly by increasing the individual earnings of people engaged in agriculture. The common agriculture policy (CAP) aims to contribute to balanced territorial development. It seeks to achieve this by maintaining a diversified agricultural sector on the EU territory, by reducing the gap between agricultural incomes and those in other sectors, and by supporting economic development, poverty reduction and social inclusion in rural areas, partially financed by the EU rural development policy. The purpose of this evaluation is to assess the extent to which CAP instruments and measures have contributed to balanced territorial development in rural areas. The focus here is on socio-economic aspects, including social inclusion. The evaluation is relevant for the long-term vision for the EU’s rural areas. This vision aims to enable rural areas to make the most of their potential and support them in facing their own unique set of issues, from demographic change to connectivity, the risk of poverty and limited access to services. In this regard, the objective of balanced territorial development is as relevant as ever. In addition, the findings of the evaluation are important to assess the relevant measures of the future CAP. The evaluation will be a source of information for Member States in the ongoing development of their national strategic plans for the next CAP period, and for the Commission in approving the strategic plans. The scope of this evaluation covers the full spectrum of relevant instruments set out in the basic regulations of the CAP 2014-2020: direct payments , rural development , the common market organisation and the Horizontal Regulation. These all target the aforementioned objectives. The overall theoretical framework and reference points of this evaluation rely on a causal analysis, which serves as a scoping exercise. The causal analysis encompassed three key elements: (i) the development of intervention logics for the CAP measures and instruments; (ii) a theory-based impact assessment (via an impact assessment grid); and (iii) a territorial distribution analysis to assess the regional allocation of CAP funding across Member States. The geographical scope of the evaluation is the European Union of 28 Member States, including the United Kingdom as it was a member of the EU at the time of the evaluation. The evaluation covers the period following the implementation of the 2013 CAP reform, notably after 1 January 2015 for direct payments and after 1 January 2014 for other measures. The evaluation encompasses all five evaluation criteria, namely effectiveness, efficiency, coherence, relevance and EU added value. This Commission staff working document is primarily based on the corresponding external evaluation support study, but also draws from additional analysis carried out by the Commission and external sources. 2.2. BACKGROUND OF THE INTERVENTION

3.2.1 Description of the intervention and its objectives The main aim of the 2013 CAP reform was to address the economic, environmental and territorial challenges, therefore it proposed three general objectives for the CAP 2014-2020: 1. Viable food production, with a focus on agricultural income, agricultural productivity, and price stability; 2. Sustainable management of natural resources and climate action, with a focus on greenhouse gas emissions, biodiversity, soil, and water; 3. Balanced territorial development, with a focus on rural employment, growth, and poverty in rural areas . The three general objectives align with the more general Europe 2020 goals of Smart, Sustainable, and Inclusive Growth. The general objectives are reflected in specific objectives and several measures under both Pillar I (direct payments and common market organisation (CMO)) and Pillar II (rural development) of the CAP, as well as within the six priorities defined for the EU’s rural development policy for 2014-2020. Priority 6 of the latter on social inclusion, poverty reduction and economic development is particularly relevant to balanced territorial development. Pillar I specific objectives contributing to balanced territorial development are to: ·maintain market stability on both supplier and demand sides; ·improve competitiveness of agricultural sector and enhance share in food chain; ·enhance farm incomes; ·maintain agricultural diversity across the EU. All Pillar II priorities and focus areas are contributing to balanced territorial development: ·Priority 1: Knowledge Transfer and Innovation, with focus areas 1A: Fostering innovation, cooperation and the development of the knowledge base in rural areas; 1B: Strengthening the links between agriculture, food production and forestry and research and innovation; 1C: Fostering lifelong learning and vocational training in the agricultural and forestry sectors. ·Priority 2: Farm Viability and Competitiveness, with focus areas 2A: Improving the economic performance of all farms and facilitating farm restructuring and modernisation; 2B: Facilitating the entry of adequately skilled farmers into the agricultural sector and generational renewal. ·Priority 3: Food Chain Organisation and Risk Management, with focus areas 3A: Improving competitiveness of primary producers by better integrating them into the agri-food chain; 3B: Supporting farm risk prevention and management. ·Priority 4: Restoring, Preserving and Enhancing Ecosystems, with focus areas 4A: Restoring, preserving and enhancing biodiversity; 4B: Improving water management; 4C: Preventing soil erosion and improving soil management. ·Priority 5: Resource-efficient, Climate-resilient Economy, with focus areas 5A: Increasing efficiency in water use by agriculture; 5B: Increasing efficiency in energy use in agriculture and food processing; 5C: Facilitating the supply and use of renewable sources of energy; 5D: Reducing greenhouse gas and ammonia emissions from agriculture; 5E: Fostering carbon conservation and sequestration in agriculture and forestry. ·Priority 6: Social Inclusion and Economic Development, with focus areas 6A: Facilitating diversification, creation and development of small enterprises, as well as job creation; 6B: Fostering local development in rural areas; 6C: Enhancing the accessibility, use and quality of information and communication technologies (ICT) in rural areas. The CAP delivers concrete actions to address balanced territorial development, including the support to social inclusion. Together with the cohesion policy funds, including the European Regional Development Fund, it has a particularly important role in remote areas (including outermost regions or areas with permanent natural or demographic handicaps). In addition, the CAP acts as the only fund in certain remote areas. Table 1 presents the list of socio-economic aspects of balanced territorial development addressed directly or indirectly by the CAP, as well as those aspects better addressed by other funds. It has a particularly important role, as well as the ERDF, in remote areas (including outermost regions or areas with permanent natural or demographic handicaps), where it may act as the only fund

Figure 1 presents the intervention logic of the relevant CAP 2014-2020 instruments and measures addressing the general objective of balanced territorial development based mainly on the assessment of the relevant evaluation support study. It presents simplified versions and assumptions of the ability of the CAP instruments and measures to address balanced territorial development. Figure 1 details both: oPillar I instruments, the purpose of the intervention/the expected patterns of balanced territorial development-relevant impacts and the potential significance or scale of these impacts, and oPillar II specific objectives (priority), focus areas and measures, starting with the most relevant priority, namely priority 6. Table 1. The CAP’s role in addressing balanced territorial development - socioeconomic aspects Direct impact Indirect impact No or limited impact – interventions under other funds Depopulation/abandonment Rural areas as shock absorber in times of crisis; Repopulation/in–migration Income, growth, poverty reduction, employment, business creation/maintenance /diversification, investments (farming) income, growth, poverty, jobs, employment, business creation/maintenance/ diversification, investments (non-farming), labour market Evolution of social rights and systems (e.g. occupational safety, pension schemes and transfers). Reducing economic disparities between farmers and between farmers and other economic actors Reducing economic disparities between rural and urban areas Generational renewal, ageing. Social inclusion: vulnerable groups, such as women, specific ethnic groups, other EU nationals and third country nationals*. Gender disparities. Access to social and economic infrastructure. Supporting small investments in remote areas, but not the core action of the CAP. Remoteness, commuting, housing, availability Availability and taking care of social capital/fabric: building local governance/capacities and bottom–up participation/approaches (e.g. cooperation). Availability and access to research, innovation and training/advice. Promoting natural (including landscape) heritage. Promoting qquality of life; cultural aspects of ‘feeling left behind’/discontent’ Source: DG Agriculture and Rural Development * The CAP 2014-2020 did not have as objective to address the needs of all vulnerable groups. Source: DG Agriculture and Rural Development. Note: further details on the intervention logic are presented in Annex 4 . 4.2.2 Baseline and points of comparison In time of the 2013 CAP reform, an impact assessment accompanied the regulation , which described the situation preceding the reform and included medium-term projections comparing no policy change with policy alternatives. This impact assessment was considered inappropriate for a baseline, because the options assessed did not correspond to the final outcome of the reform after negotiations with the European Parliament and Council. There was no other objective and quantitative projection that could have been used as a baseline. Thus where relevant, the pre-2013 reform situation was used as a benchmark. The lack of EU targets or any binding legislative framework, specific to socio-economic aspects in rural areas, further prevented the measurement of any concrete achievements. In addition, social inclusion was not at the heart of the CAP objectives at the time of developing the CAP 2014-2020. Nevertheless, where relevant, the evaluation takes into account the targets on result indicators set by Member States to reflect the expected coverage of their CAP interventions programmed under Priority 6 (Promote social inclusion, poverty reduction and economic development in rural areas). Other dimensions of balanced territorial development are not covered by quantified targets in the CAP 2014-2020. The next CAP will fill in this gap, notably adding quantified targets on the direct support redistribution and the support to areas in needs.



5.3. IMPLEMENTATION/STATE OF PLAY The instruments and measures here described are those selected in the study and considered to have a direct impact on the general objective of balanced territorial development and socioeconomic aspects including social inclusion in rural areas following a theory-based impact assessment and territorial distribution analysis. Budgetary framework The design of the CAP 2014-2020 was influenced by the multiannual financial framework 2014-2020, with implications on the implementation of the various CAP instruments, including:

·external convergence, to reduce the differences in the level of income support per hectare based on historical differences between Member States; ·degressivity, to improve the distribution of direct payments by reducing the basic payment above a certain level; ·flexibility between the two pillars of the CAP, allowing Member States to better target the available financial resources in accordance with their particular objectives. The implementation choices of Member States in relation to the flexibility mechanism result in a net transfer of EUR 3.76 billion to Pillar II. A transitional Commission Regulation (EU) No 2220/2020 ensures continuity of the CAP implementation until the new legal framework including the future Strategic Programme Regulation enters into force by the beginning of 2023. Pillar I measures targeting the general objective of balanced territorial development Pillar I measures include income support via direct payments, which is the core instrument of the CAP contributing to its objective of enhancing farm income. Direct payments under the CAP 2014-2020 came into force on 1 January 2015, following notification from Member States to the European Commission on their implementation decisions. Basic payments contribute to balanced territorial development by ensuring a basic income support for farmers engaged in agricultural activities, on the basis of a basic payment scheme (BPS) or a single area payment scheme (SAPS). Basic payments are compulsory and account for approximately 50% of the total available support, with variable shares at Member State level (see Figure 2). The 10 Member States (Bulgaria, Czechia, Estonia, Cyprus, Latvia, Lithuania, Hungary, Poland, Romania and Slovakia) applying single area payment scheme until 2014 maintain the scheme until the end of 2020. A 30% share of the budget for direct payments is provided for farmers respecting agricultural practices beneficial to the climate and the environment, notably crop diversification, maintenance of existing permanent grassland, and having an area of ecological interest. This ‘green payment’ is obligatory for Member States and granted as a flat-rate payment per eligible hectare declared under the single area payment scheme or according to the value of entitlements activated under the basic payment scheme. The young farmer payment is a compulsory scheme providing support for farmers up to 40 years of age who begin their agricultural activities, with an additional 25% of direct payment for a maximum of five years. Member States may use up to 2% of their national envelope to this scheme and most have utilised this maximum rate (or close to that). However, six Member States assigned a very small share of up to 0.5% of their national envelope to this payment. Member States can also allocate 8% to 13% of the their national ceiling for direct payments to voluntary coupled support in certain sectors or regions where specific types of farming or specific agricultural sectors that are particularly important for economic, environmental and/or social reasons undergo certain difficulties. Funding can be increased by a further 2% to support protein crops in order to maintain the plant protein supply necessary for the feed sector. In claim year 2019, the most supported sectors at EU-28 level were: (i) beef and veal (23 Member States, about 40% of total voluntary coupled support envelope), (ii) milk and dairy products (19, 21%), (iii) sheep and goat meat (21, 13%), (iv) protein crops (16, 11%), (v) sugar beet (11, 4.4%), (vi) fruit and vegetables (19, 4.1%),. Germany was the only Member State not applying voluntary coupled support in 2019. The CAP 2014-2020 introduced a voluntary redistributive payment, which allows a higher payment for the first 30 hectares of a farm (or more if the average farm size of a Member State is greater than 30 hectares). The purpose is to ensure a redistribution of income support towards smaller farms as their income support needs tend to be higher. Although Member States can use up to 30% of their national ceiling for this payment, the actual uptake ranges from 2% to 15%. Nine Member States/Regions (Belgium-Wallonia, Bulgaria, Germany, France, Croatia, Lithuania, Poland, Romania and UK-Wales) have applied the redistributive payment since 2014/2015 and Portugal as of 2017. Source: European Commission (2020), CAP Output Indicators - Financing the Common Agricultural Policy Member States could implement a voluntary small farmers’ scheme, which is a simplified direct payment scheme replacing all other direct payments and exempts beneficiaries from greening obligations and cross-compliance penalties to ensure a support specifically designed to the smallest farms. Sixteen Member States applied the small farmers’ scheme in financial year 2019. Source: European Commission, Information System for Agriculture Refund Expenditure (AGREX) and Clearance Audit Trail System (CATS) databases. Pillar I instruments also include measures under the common organisation of the markets . Market measures address specific issues in certain EU agricultural markets to help producers adapt to market conditions and increase competitiveness and sustainability. Market measures are structured along product types (i.e. products eligible for intervention ), and programmes and areas of intervention. They contribute to enhance the value added of primary producers and the sustainability of the agri-food chain (e.g. fruit and vegetable sector) and income to farmers, to their households and exports (e.g. wine). The market expenditure reached EUR 2.41 billion in 2018, out of which 40% went to the wine sector and 35% to fruit and vegetables. The CMO funding is concentrated in the southern regions of Spain, and in several regions in France and Italy.

In the 2014-2019 period the total expenditure for the Pillar I instruments amounts to around EUR 300 billion (about EUR 44 billion per year). Single area payment scheme/basic area payment scheme, greening and voluntary coupled support have the highest total amount. In this period the funding available for EU market policies (including the crisis reserve fund) was planned to account for approximately 4% (EUR 17.5 billion) of the total CAP budget. Pillar II measures targeting the general objective of balanced territorial development The rural development policy of the CAP is implemented over a seven-year period, via rural development programmes designed by national or regional Managing Authorities. A total of 118 programmes are implemented in the 28 Member States, with an EU funding of EUR 99.6 billion over the 2014-2020 period. Adding the co-funding by national, regional and private resources, the total amount of funding for the rural development policy of the CAP reaches EUR 161 billion for 2014-2020. The CAP provides Member States flexibility regarding the type of measures implemented under Pillar II, as well as the budget allocated to the various measures. The major difference thus stems from the various programming among Member States. On social aspects, the only obligation for all Member States was the ring-fencing on LEADER (minimum 5% of rural development fund) and most Member States went beyond this minimum. The implementation of other rural development measures affecting social sustainability was voluntary for Member States. The way in which the CAP Pillar II measures are structured and implemented vary also significantly between Member States resulting in an array of different approaches and detailed operations available to beneficiaries. As described in chapter 2.1, the rural development policy of the CAP 2014-2020 includes a number of priorities and focus areas targeting balanced territorial development of rural areas. The most relevant EAFRD measures contributing to balanced territorial development are: M01: Knowledge transfer and information actions. The measure aims to improve the access for farmers, forest holders, persons engaged in the food sector and rural small and medium-sized enterprises to technical and economic knowledge and information. M02: Advisory services, farm management and farm relief services. Farm advisory services help farmers and other actors of rural areas to enhance their sustainable management and overall performance of their holding. M04: Investments in physical assets. The investment grant is designed to improve the economic and environmental performance of holdings, notably in a context of short supply chains and local markets. M06: Farm and business development. The main aims of the measure are to encourage the restructuring of the agricultural sector and ensure the viability of new activities (e.g. by means of business start-up aid for young farmers; non-agricultural activities in rural areas and the development of small farms etc.). M07: Basic services and village renewal in rural areas. Investments under this measure focus on rural settlements and surrounding cultural and natural heritage. M09: Setting up of producer groups and organisations. Supports producer groups and organisations (qualifying as small and medium-sized enterprises) in order to face market challenges (adapting production to market requirements, placing goods on the market etc.). M10: Agri-environment-climate. This measure aims to preserve and promote ‘agricultural practices that make a positive contribution to the environment and climate’, by compensating beneficiaries for all or part of the additional costs and income foregone. M11: Organic farming. The measure foresees a support to farms that convert or maintain organic farming activity, in order to encourage organic farming practices by groups of farmers through collective contracts or co-operation between farmers. M12: Natura 2000 and Water Framework Directive. The measure provides annual per hectare compensation payments to farmers and foresters for the additional costs and income foregone when implementing the Birds and Habitats Directives or (for farmers only) the Water Framework Directive. M13: Payments to areas facing natural or other specific constraints (ANC). The measure intends to encourage farming activity in mountain areas and other areas facing natural or other specific constraints (as designated in Article 32 of Regulation (EU) 1305/2013). The support compensates farmers for the relevant additional costs and income foregone. M15: Forest-environmental and climate services and forest conservation. Under this measure Member States may support public and private forest owners who undertake forest-environment and climate commitments on a voluntary basis. M16: Cooperation. Encourages cooperation involving two entities, creation of clusters or networks, as the establishment of operational groups of the European Innovation Partnership (EIP). These can for instance take the form of pilot projects; development of new products, practices, processes or technologies. M17: Risk management. This measure may cover economic losses caused by external market effects, outbreak of an animal or plant disease or weather events. M19: Support for LEADER and local development. The LEADER (links between the rural economy and development actions) approach is a compulsory feature of all rural development programmes. It is an area-based, bottom-up method of delivering support to local communities that design and implement local development strategies themselves. As regards in particular the measures in the scope of this evaluation, the declared expenditure for the period 2014-2019 amounts to EUR 73.6 billion, i.e. 91% of the total EAFRD public expenditure. The measures with the higher expenditure are M13 – ANC, M10 – Agri-environmental commitments, M11 – Organic and M04 – Investments (see Figure 3). The majority of Pillar II measures are targeted on farmers and foresters needs, however some of them have broader targets i.e.: M07 – basic services, M19 – LEADER, M04 – investments and M06 – farm and business development.

Source: European Commission, DG Agriculture and Rural Development Priority 6, targeting more specifically social inclusion and economic development, covered 10% of the expenditure in 2014-2018. The Pillar II amount spent on broader rural development is modest compared to spending on other priorities (close to 57% on natural resources – Priority 4 and 19% on competitiveness – Priority 2). In addition, by comparison to 2007-2013, the 2014-2020 rural development programmes generally offer much smaller allocations of funds towards Measure 7 on ‘Basic services and village renewal’, but increased funding to LEADER. Total public funding between both periods is similar. In view of the planned expenditure, over 2014-2019, the realised expenditure is particularly low for Priority 6 (34%) and for the measures very relevant to balanced territorial development: M19 – LEADER (30%), M16 – cooperation (18%) and M02 – advice (21%) (see Table 14 in Annex 4). The implementation of these more complex instruments take more time than annual payments (83% of the planned expenditure is realised for M13 – ANC). The rate of realisation is similar for M07 – basic services and M.04 – investments around 40%. The reporting after the projects are completed explain in part these low figures. In their rural development programmes, Member States set targets for a number of social aspects beyond farming. These targets relate to the rural population covered with LEADER strategies, job creation, and the development of improved infrastructure and services (including information and communication technology). The targets cover: (i) local development, notably via LEADER (Focus area 6B); (ii) economic diversification; (iii) the development of small and medium-sized enterprises; and (iv) job creation (Focus area 6A). Member States must spend a minimum of 5% of Pillar II on LEADER. In 2014-2020, 11% of total planned rural-development public expenditure was allocated to local development notably via LEADER (focus area 6B). Member States also set a target to cover more than 50% of the rural population with local-development strategies by 2023. This target has already been achieved. By contrast, only 3% of public expenditure was allocated to job creation under diversification (focus area 6A). On job creation in supported CAP projects, EU targets are relatively small (120 500 jobs in total by 2023) and progress towards the target is slow. This is partly because Member States only notify the jobs created once projects are completed. However, the various quantitative analyses showed a higher impact from the CAP on jobs. Few Member States rely on EAFRD support to develop rural access to broadband, hence the low target value at EU level (16% of rural population covered by improved information and communication technology supported with the CAP). Nevertheless, where countries make use of EAFRD support, there is a direct link between the funded operations and their impact (see Chapter 5.1). Target indicator Target Progress to target T21: Percentage of rural population covered by local-development strategies (Focus area 6B) 53% 118% T20: Jobs created in supported projects (Focus area 6A) 76 430 23% T23: Jobs created in supported projects (LEADER) (Focus area 6B) 44 110 51% T22: Percentage of rural population benefiting from improved services/infrastructure (Focus area 6B) 16% 139% T24: Percentage of rural population benefiting from new or improved services/infrastructure (ICT) (Focus area 6C) 5.8% 66% Note: Data are notified by Member States when projects are completed. For long-term investments such as for ICT, progress to target is slow. Source: DG Agriculture and Rural Development 6.4. METHODOLOGY The evaluation is primarily based on the external evaluation support study on territorial development, complemented with internal (DG Agriculture and Rural Development) analysis based on more recent data and information (2019 expenditure). It is also supported with relevant findings of available external analyses. The methodological approach combines theoretical and empirical analysis and includes a variety of quantitative and qualitative methods to deal with the complexity and the range of topics under the evaluation (see Annex 3 for more information). The evaluation tools and methods included, but were not limited to: documentary research, literature reviews, statistical data analysis, case studies surveys and interviews with stakeholders, public consultations, etc. The collected data was analysed through both quantitative and qualitative methods. The quantitative analysis in the evaluation support study was based on the use of clusters, grouping regions along common characteristics and needs, allowing for a targeted discussion of the effects of CAP funding on differentiated regions’ balanced territorial development, characteristics, and socio-economic factors. This analysis produced a set of four clusters (see Map 2 ): ·Cluster 1 – Diversified rural and intermediate regions, featuring ageing societies within structurally well-developed regions. These regions are more often associated with high labour costs and strong inter-sectoral competition;

·Cluster 2 – Peripheral rural and intermediate regions, featuring very low degrees of accessibility. The agricultural sector is important in these regions. These regions are lagging in terms of productivity and standards of living. Population outflows to wealthier regions negatively impact human capital endowments; ·Cluster 3 – Dynamic rural and intermediate regions, having stronger development patterns, however, farming in these regions faces pressure from the neighbouring urban centres by means of land value for purposes other than agriculture; ·Cluster 4 – Traditional rural and intermediate regions, which are generally younger and feature high employment growth. The regions retain a strong rural character, with large NATURA 2000 areas, a large share of the population in rural areas. These regions retain a strong and viable agricultural sector. Additionally, also in the framework of the support study various quantitative analyses were carried out: regression and correlation analyses that included spatial socioeconomic variables; an input-output analysis to identify the effectiveness of Pillar I funding with respect to generating jobs and income within the primary and upstream sectors; an efficiency analysis of CAP funding. The methodological approach taken in the JRC study for the elaboration of a counterfactual impact evaluation study provides causal estimates of the CAP’s impact on a set of regional economic (GDP per capita, total gross value added (GVA) and employment) and agri-sector related economic outcomes (GVA in the agri-sector, employment in agriculture, land and employment productivity). The analysis addresses the CAP’s performance at regional level and in particular the convergence of rural regions using the Generalised Propensity Score method. The JRC analysis is based on a NUTS3 level description of the regional dimension of the CAP in the period 2011-2018. This implies a characterisation of: (i) the rural regions, according to their economic aspects and in particular of their agri-sector and; (ii) of the regional CAP mixes (of Pillar 1 and Pillar 2 groups of measures) in time intervals characterised by the implementation of relevant CAP reforms. The evaluation benefits as well from various consultations, including, as part of the case study, interviews that have been carried out in the context of case studies and addressing various types of key stakeholders. The interviews conducted gathered also information from DG AGRI representatives, concerned with Pillar I and Pillar II, on the administrative burden possibly generated by the implementation of CAP instruments and measure. Additionally, an online public consultation on A long term Vision for the EU’s Rural Areas, was carried out to gather and analyse the perceptions of Europeans (citizens, companies, NGOs, etc.). A specific section on the CAP and balanced territorial development was added to contribute to this evaluation. This section was answered by 864 respondents. A homonym Staff Working Document was also published . Other European Institutions, the Committee of Regions, and the European Economic and Social Committees, also launched consultations, which results are also relevant for this evaluation. See Annex 2 to know more on the stakeholder consultations launched and their outcome. Limitation and robustness of findings CAP instruments and measures may directly have socioeconomic implications, the magnitude of these impacts may be influenced, in a positive and/or negative manner, by the history and socio-economic context of a given region/country. These multiple exogenous factors increase significantly the difficulty to assess the net-impact of the CAP on the social-economy of rural areas. Additionally, some CAP instruments and measures have a much more direct and observable impacts on this aspect than others. The robustness of findings is affected mainly by the availability of complete, detailed and updated data, describing the socio economic status of rural areas. There are several statistical definitions of rurality (notably rural areas and rural regions), not always answering evaluation needs requiring thus the development of specific analytical frameworks (see Chapter 5.1.7 Rural area definitions ). In addition, some variables are available for rural areas, others for rural regions. Furthermore, data (or most recent data) is sometimes only available at national level or at a low geographic resolution (such as NUTS1), which is not sufficient for analyses related to the territorial differentiation of effects with a high geographic resolution (NUTS3). Other limiting factors include the large array of interlinked socio-economic aspects and social inclusion of specific vulnerable groups and the broad range of policies under study, from the CAP, to European structural and investment funds (ESIF) and national/regional policies that, due to the heterogeneity of delivery mechanisms and multi-level governance systems involved, is difficult to investigate. Numerous mitigation techniques have been applied in the study, allowing to draw useful conclusions. For instance, second-best indicators (in case the thematic coverage is not ensured) were used and regional breakdown methods via proxy indicators (when the required geographic resolution is not available) were applied. This, however, can mask certain effects that could be more clearly singled out if more specialised datasets were available. The existence of a low number of regions, which receive no CAP funding and are similar enough to be matched with regions obtaining relevant funding, did not allow the contractor which carried out the support study, applying counterfactual regression methods based on comparisons with a control group. The correlation analysis and regression analysis shed light on statistical associations and provide insights into relationship not necessarily impacts and effects. The regression analysis identified only few significant relationships. The interpretation of the results is limited by the separate consideration of funding from CAP and European Social Fund (ESF) and European Regional Development Fund (ERDF) via two regressions and the fact that many impacts of CAP funding may only materialise in the future. Finally, the fact that the dependent and explanatory variables cover the same time-period may introduce endogeneity issues. To circumvent this drawback, the JRC developed specifically for this evaluation an analytical framework allowing for establishing causal links, distinguishing between the role of rural development support, direct payments and market expenditure. Some interviewees could not reply to questions related to the lack of effectiveness for Pillar I and II, due to their specialised ‘sectorial’ knowledge. 4.ANALYSIS The evaluation questions are structured following the five evaluation criteria: effectiveness, efficiency, relevance, coherence and EU added value. Chapters 5.1 to 5.5 focus on the impact of the CAP on balanced territorial development by looking at each of these criteria in turn. 5.1 Effectiveness

The evaluation criterion on effectiveness shows to what extent the set objectives were achieved, how they were linked to the specific intervention, and whether there were any unexpected or unintended effects. Questions related to the effectiveness of CAP instruments on balanced territorial development in rural areas, are presented in the following order: (i) farm income and distribution of support; (ii) productivity and competitiveness; (iii) jobs in agriculture and generational renewal; (iv) spill-over effects into the wider rural economy; (v) social inclusion; and (vi) building human capital. The last paragraph addresses the issue of the definition rural areas. 5.1.1 Farm income and distribution of support The average EU factor income per worker increased by 15% from 2013 to 2019 in real terms. The increase in income was mainly due to major gains in labour productivity, mostly driven by an outflow of labour from agriculture. Income by type of region (rural, intermediate and urban) also varied. Direct payments represent close to 30% of farmers’ income and case study respondents assessed them highly positive in supporting farm business maintenance and farm income notably in times of crisis (see Figure 10 ). The effectiveness of direct payments in stabilising farm income and thereby supporting farm competitiveness and economic viability was also highlighted in the consultation on the CAP and balanced territorial development. However, according to the Implementation Report of the Committee of the Regions (consultation of the regional hubs) direct payments are not enough to overcome market fluctuations and agricultural crises. In this context, this report as well as the case study analysis highlighted also the importance of CMO funding in terms of income stabilisation (e.g. during the crisis caused by the plant pathogen Xylella fastidiosa in Apulia - Italy). In crisis, the case study respondents deemed also Pillar II support important to farm incomes. Reducing the gap between the level of income support received by EU farmers The public consultation on the CAP and balanced territorial development highlighted that the uneven distribution of resources limits the effectiveness of CAP instruments and measures. The EU has introduced in its 2013 CAP reform a mechanism called external convergence with the aim of progressively adjusting income support per hectare in each Member State, upwards or downwards, to bring them closer to EU average for a more balanced income support distribution on the EU territory. The gap between direct payments per hectare is progressively decreasing as a result of external convergence. The change between 2015 and 2019 is in general inversely proportional to the level of direct payments per hectare. However, it should be noted that Member States may have transferred funds from direct payments to rural development or the contrary (as illustrated on the graph). The level of direct payments decreased mainly in the Netherlands, Greece and Belgium, while it increased mainly in Croatia, Malta, the Baltic States and Romania. In the case of Malta, the change is explained by the transfer from rural development to direct payments, which increased significantly between 2015 and 2019. In Croatia, the change between 2015 and 2019 is mainly explained by the phasing-in, i.e. the progressive increase of funding after accession (Croatia joined in 2013). Note: Direct payments (DP) per hectare of potentially eligible area (for the basic payment and small farmer scheme). The change in average direct payments per hectare determined is the result of external convergence, the transfers between pillars (from DP to Rural Development (RD) and vice-versa), as well as the implementation choices and trend in potentially eligible area. Source: DG Agriculture and Rural Development, based on CATS audit database The difference in the level of direct payments per hectare between farmers within Member States has reduced significantly between 2015 and 2019 as a result of internal convergence. 18 Member States apply the Basic payment scheme (BPS) and 10 Member States keep applying the Single area payment scheme (SAPS), thus have a national flat rate area payment since they joined the EU. Member States applying the BPS have three options: (1)a uniform unit value per hectare for all payment entitlements as from 2015 at national or regional level; (2)full convergence of the per hectare value by 2019 at national or regional level; or (3)partial convergence (‘tunnel model’): payment entitlements with a value lower than 90% (or between 90 and 100%) of the national/regional unit value in 2019 will have their value increased during the period 2015-2019 to close at least 1/3 of the gap between their initial unit value and the value in 2019. As a result of this internal convergence and also changes in Member States’ distribution of direct payments, the difference in the level of direct payments received by EU farmers reduced significantly: from EUR 1 680/ha in 2015 to EUR 1 240/ha in 2019 in the EU-28. The internal convergence led to the strongest decline in the difference between farmers in the Netherlands moving progressively to a national flat rate by 2019. The difference has remained high (up to EUR 2 000/ha in Spain and Portugal) in certain Member States still applying the historical model. In Member States applying SAPS the difference in level of direct payments per hectare is generally low, except in Bulgaria, due notably to the coupled payments distribution. Note: Based on 2018 figure for Slovakia Source: DG Agriculture and Rural Development, based on CATS audit database

In the 18 Member States applying the BPS, the 2013 reform has allowed moving away from historical references with a certain convergence of direct payments per hectare within Member States. As a result of both external and internal convergence, as well as other Member States implementation choices, accounting for total income support (direct payments and aid to areas facing natural or other specific constraints (ANC)), the differences between regional (Nuts3) per hectare levels reduced significantly between 2015 and 2019: ·increased by up to 5% in 272 NUTS 3 regions, ·increased by more than 5% in 327 NUTS 3 regions, ·decreased by up to 9.9% in 475 NUTS 3 regions, and ·decreased by 10% or more in 267 NUTS 3 regions. This led to a re-balancing of the level of support per hectare on the EU territory. However, some significant differences remain in Member States applying partial convergence (i.e. France, Italy, Spain, Portugal, see Figure 26 in Annex 4). In addition, it is also important to note that because of very different farm structures and income, a similar level of support per hectare does not translate on similar support per farm or worker and high income support per hectare does not necessarily mean a high share of support in income and vice versa. Source: DG Agriculture and Rural Development on the basis of the CATS database Redistribution of support to smaller farms Most direct payments are paid per hectare and the level of basic income support is converging towards closer levels, thus by definition larger farms receive more payments in absolute value. It explains why several interviewees during case studies pointed that the nature and structure of area-based payments (BPS/SAPS) favour large-scale farms and more competitive areas. The unfair distribution of support can also be considered to have implications on the feeling of being left behind, argument which was supported by public authorities, rural development experts, farmers, and producer organisation. By contrast, in the Netherlands (applying full convergence), case study respondents consider that direct payments reduced economic disparities between small and mid-sized and large-scale farms. This opinion is largely shared by respondents to the case studies (see Figure 10 ), which shows that there are more respondents pointing at the positive contribution of direct payments in reducing economic disparities than at the negative one. Redistribution of support towards smaller farms was one of the CAP’s objectives to address their higher income support needs. For this, Member States could choose to implement a redistributive payment to smaller farmers, as well as capping and degressivity of direct payments per farm. In 2016-2018, smaller farms in the EU (below 30 ha) received direct payments per hectare 25% higher than EU average. This contributes to address their higher need for income support, but only in part, as on EU average, farms below 30 ha had an income 40% below average over this period (see Figure 27 in Annex 4). Farms small in physical size often group together farms producing high value added products not always eligible to decoupled direct payments (i.e. farms specialised in horticulture and vineyards, intensive livestock farms, many small farms in Romania or part time farms). Comparing farms according to their economic size is more relevant in this context. In terms of economic class, the smallest class (below EUR 8 000 standard output) received EUR 244/ha in 2016-2018, which is below EU average of EUR 260/ha. This result is driven by the over representation of Romania in this class (57% of the represented farms). Nevertheless, as a result of the reform, the level of direct payments per hectare in this smallest economic class increased by 17% compared to 2011-2013. The increase was also very significant for farms between EUR 8 000 and EUR 50 000. While for farms with an economic size between EUR 100 000 and EUR 500 000 (concentrating close to 40% of direct payments) the per hectare payment declined by 5% with the reform (see Figure 6 ). However, income of smaller farms remains significantly lower than average and the share of direct payment support in income is significantly higher for the smallest economic farm size (48%) compared to the largest farms (18%). Income per worker (EUR) and share of direct payments (DP) in income (%) Direct payments per hectare (EUR/ha)



Note: Economic size classes: (1) EUR 2 000 – < 8 000; (2) EUR 8 000 – < 25 000; (3) EUR 25 000 – < 50 000; (4) EUR 50 000 – < 100 000; (5) EUR 100 000 – < 500 000; (6) > EUR 500 000. From 2018, the first economic size class includes only farms from EUR 4 000 to EUR 8 000. The income indicator used is the farm net value added per full time equivalent. Source: DG Agriculture and Rural Development, based on FADN data Ranking farmers according to income level (i.e. need for support), farmers with the highest level of income per worker received more direct payments per worker in 2016-2018 (see Figure 28 in Annex 4). However, due to the redistribution of support with the 2013 reform, the level of support for farmers with the highest income decreased to the benefit of farmers with lower income. Compared to the period 2011-2013, direct payments in 2016-2018 for the 10% farms with the lowest income increased by EUR 535 per worker and decreased for the farms with the highest income by EUR 2 577 per worker, rebalancing the support towards farmers most in need. Despite this redistribution of support, income of the 10% farms with the lowest income was negative in 2016-2018, highlighting the need for these farms to increase productivity as well as market revenues. Many of those farms are located in Romania, Poland and Greece and they are often specialist cereals, oilseeds and protein crops, mixed crops and livestock and specialist cattle farms. For the 10% farms with the highest income, direct payments represent less than 20% of their income. There is a high concentration of high-income farms in Denmark and the Netherlands. Redistribution of support to areas in need Direct payments and Pillar II support represent close to 50% of farmers income in mountain areas and CAP funding is deemed important in underpinning farm viability in the most marginal and remote rural areas. As concluded by The challenge of land abandonment after 2020 and options for mitigating measures of rural areas farms in remote areas are important for the provision of ecosystem services, thus the importance to maintain farms in many remote areas threatened by land abandonment. On EU average, farm income is lower in areas facing natural or other specific constraints (ANC) than in non-ANC. Pre-reform (2011-2013) direct payments per hectare were lowest in not-mountain areas facing other constraints and highest in areas facing no constraints (see Figure 32 in Annex 4). The reform led to a redistribution of support to areas facing constraints. With an increase of EUR 18/ha in mountain areas, the level of direct payments (around EUR 280/ha in 2016-2018) is now higher in mountain areas than in areas facing no constraints. In areas facing other constraints, the increase of EUR 8/ha was not enough to compensate for the gap in direct payment support. In these regions, the gap is closed thanks to the additional income support (ANC), bringing total income support to around EUR 270/ha as in plains. In mountain areas, adding ANC support, the level of income support reached close to EUR 380/ha in 2016-2018. Farmers in mountain areas receive also more other rural development subsidies (e.g. national top-ups, agri-environment-climate commitments). The high level of subsidies does not compensate fully for the income gap with plains though, but it explains in part why the income per worker in mountain areas is higher than in areas facing other constraints. In 2016-2018, the income per worker in mountain areas was 18% below income in areas facing no constraints, while in areas facing other constraints it was 25% below. Without this high level of operating subsidies, the income gap would be much larger. Note: ANC = support to farms in areas facing natural or other specific constraints; FNVA = farm net value added per full time equivalent = amount available to remunerate all factors of production (land, labour and capital, both external and own factors); other RD: rural development measures other than ANC (including national top-ups and agri-environment-climate commitments, but excluding investments supports). Source: DG Agriculture and Rural Development, based on FADN data Reducing the gap in income with the rest of the economy In 2019, agricultural income was still less than half the wage in the rest of the economy, although CAP support contributed to reducing significantly this income gap since the 1990s. In addition, the average income gap diminished further by approximately 2% (Figure 5) between 2010-2012 and 2017-2019. In three Member States only (Spain, Czechia and Slovakia), the average agricultural income was above the wage in the rest of the economy. Moreover, in 2019, the average income in predominantly rural regions reached 77% of the EU average income. It represents a 9 percentage points increase compared to 2013, meaning that the income gap with urban areas decreased significantly. Nevertheless, the case study analyses underlined that climate externalities, changing consumer preferences and price volatility continue to detrimentally affect farm viability and thus farm maintenance on the EU territory. Source: DG Agriculture and Rural Development on the basis of Eurostat data 5.1.2 Productivity and competitiveness

Lack of agricultural productivity and poor competitiveness of the agricultural sector were the issues most frequently cited by case study interviewees from the categories ‘public authorities and rural development experts’. Physical limitations (i.e. inhospitable climate, or suboptimal topography) are weakening agricultural competitiveness in rural regions (e.g. Spain). In other case study regions (e.g. Saxony-Anhalt), the relatively lower labour productivity and economic efficiency of the primary sector are important issues. These regions are generally characterised by strong migratory patterns and subsequent shortages of skilled labour across the economic sectors, not only in agriculture. Case study analyses highlighted the important contribution to farm-level productivity growth stemming from M04 – investments and M06 – farm and business development. In peripheral regions (cluster 2) and dynamic regions (cluster 3), the quantitative analysis demonstrated that M04 – investment funding enabled farm production capital and water conservation investments. Similarly, M01 – knowledge transfer, M02 – advisory services and M16 – cooperation are considered as beneficial to modernisation and farm-based productivity in several case studies . Case study analysis highlighted the importance of CMO funding for farms in terms of improved competitiveness of specific sectors such as wine (e.g. in Spain). The modernisation of the wine sector fosters the development of specialised companies and the creation of jobs that affect not only the producer and processing sector, but also related industries along value chains. In addition, the JRC counterfactual analysis of the effects of the CAP carried-out in the context of this evaluation, confirms that CAP support (market expenditure, direct payments and rural development support) contributed to improve labour productivity across time in agriculture, allowing the freed labour force to grasp labour opportunities in other sectors of the economy. Freed labour migrated in part to urban regions where there were more opportunities. This increase in labour productivity was accompanied by an increase in agricultural land productivity, as CAP support incentivized to farm modernisation (trough mechanisation e.g.), leading to economies of scale, better farm economic results and labour outflow from agriculture. Nevertheless, the analysis done by the JRC shows that without the CAP, that supported the maintenance of farms in most remote areas, this labour outflow would have been bigger towards urban areas. 5.1.3 Jobs in agriculture and generational renewal Overall labour input in EU agriculture at 9.1 million full-time equivalents in 2019 has been falling, although it now seems to be levelling off (from -3.9% per year in 2005-2011 to -1.25% per year in 2011-2019). Public authorities and rural development experts, surveyed in the case studies, highlighted that generational renewal in agriculture is hampered in part by land pressures. In some areas, the increase in farm size makes new entry into farming too costly for young and smaller farmers. In addition, the reduction in the availability of skilled workers (especially for seasonal production) is an issue. Respondents from the categories public authority, rural development expert, farmer, processor and producer organisation consider basic income support to provide positive impacts to generational renewal. The Implementation Report of the Committee of the Regions (consultation of the regional hubs), assessed that payments to young farmers (Pillar I) are an incentive to generational renewal but not sufficient. The evaluation of the CAP impact on generational renewal, showed that the support to young-farmers via direct payments and rural development imply the highest potential increase in the number of young farmers in less developed areas with many small farmers. The World Bank report also found a significant positive association between agricultural employment and decoupled Pillar I and Pillar II payments. However, wider socio-economic conditions greatly affect the relative attraction of farming for young people in many Member States. Moreover, the cluster analysis, carried-out for this evaluation, demonstrated that diversified regions (cluster 1) and dynamic regions (cluster 3), receiving high direct payments, CMO, M04 – investments and M06 – farm and business development funding, are positively associated with growth in the size of agricultural labour force between 2014 and 2017. Interviewees confirmed that Pillar I funding enables farms to retain labour force in agriculture. The counterfactual exercise of the JRC showed that all CAP support and in particular CMO and direct payments had a large causal impact on safeguarding employment in agriculture. In addition, the World Bank report highlights profitable and productive farming as a catalyst in many rural areas for driving people on to better jobs, higher wages and an improved quality of life. However, employment opportunities created in the agricultural sector are not necessarily conducive to long-term improvements in the standards of living. Case study respondents (Spain and Greece) highlighted seasonality and low payment as negative factors of agricultural work. The risk of exploitation and underpayment of seasonal workers, and the overrepresentation of women in precarious jobs are also highlighted by the European Economic and Social Committee in its Evaluation of CAP impact on territorial development of rural areas. As elaborated in the World Bank report, large differences in farm income among Member States result in seasonal migration of workers from low to high wage regions, and seasonal workers from outside EU provide labour force on a temporary basis. 5.1.4 Spill-over effects into the wider rural economy Employment in rural areas Primary agriculture still provides work for roughly 20 million people (both full time and part time). Furthermore, together with food processing, food retail and food services, agriculture makes up a sector providing around 40 million jobs in the EU. In addition, in 2019, the employment rate for the age group 15-64 reached 69% in rural areas in the EU-28, 6 pp higher then pre-CAP reform level in 2013, thus closing the gap with the employment rate over the whole territory. The expenditure of agricultural sector financed with Pillar I funding, such as the purchase of seed or fodder, fuel, chemical products or food processing, contributes to supporting employment in the respective industries. According to the input-output analysis, direct payments created or safeguarded 5.2 million jobs in the agricultural and related upstream sectors between 2015 and 2018, out of which 2.4 million jobs in the agricultural sector solely ( Figure 9 ). The number of safeguarded employment depends on the choice and mechanisms in the regional and national implementation of the CAP: most funding is targeted at farmers with only indirect targeting of the wider rural population. In addition, the JRC counterfactual analysis of the effects of the CAP carried-out in the context of this evaluation, shows that CAP support (market expenditure, direct payments and rural development support) contributed to a significant total employment growth in predominantly rural areas, with effects increasing over time and no significant differences in the role of the various instruments. The synthesis of the evaluation components of the enhanced Annual Implementation Report 2019, further demonstrates the effects of M01 - knowledge transfer, M04 - investments, M06 - farm and business development and M19 – LEADER in improving employment opportunities in rural areas (job maintenance and creation). France showed that ANC payments contributed to maintain grazing farms and associated jobs. Similar effects were reported in France for support to organic farming and agri-environment-climate actions. Rural development programmes support also the diversification of small enterprises in rural areas, especially through farm diversification (e.g. Austria) or the creation of new businesses in non-agricultural sectors (e.g. Estonia, Italy, Slovakia). However, the assessments also concluded that the rural development programmes’ contribution to raising employment in rural areas was not fully sufficient to compensate for the loss of jobs in the agricultural sector and rural areas (e.g. France, Luxemburg, Latvia). The European Economic and Social Committee, in its Evaluation on the CAP’s impact on territorial development of rural areas confirmed that CAP measures did not impact employment in rural areas as positively as most countries needed. Gross Value Added growth in the primary sector and related sectors According to the input-output analysis, approximately EUR 100 billion of the receipts of farmers coming from direct payments funding were spent on goods and services produced in domestic rural regions between 2015 and 2018 (see Figure 9 ). Out of this, EUR 45 billion were spent within the agricultural sector, while EUR 55 billion contributed to value-added creation outside agriculture in the upstream sectors. In total, EUR 36 billion were spent on manufactured products such as fodder and EUR 16.5 billion on wholesale trade. Domestic rural regions, i.e. the regions situated in the same Member State as where the funding was induced, are the main recipients of the re-invested money (domestic rural regions make up half of the expenditure in food, fodder and wholesale trade). Figure 9. Effects of direct payments in agricultural and upstream sectors (2015-2018) Number of created or safeguarded jobs Gross value added (EUR million)

Source: Evaluation support study In addition, the JRC counterfactual analysis of the effects of the CAP carried-out in the context of this evaluation, confirms that CAP support (market expenditure, direct payments and rural development support) contributed to the increase in gross value added in agriculture, with effects increasing over time. This translated into a growth of gross value added in rural regions and on the whole territory. This effect benefited the regions with relatively stronger rural development support, such as regions in central and eastern part of Europe and in Portugal. The cluster analysis showed that by improving economic opportunities and attractiveness in rural regions, M01 – knowledge transfer, M02 – advisory services and M16 - cooperation foster a more vibrant local economy with spill-overs. This is observed to a stronger degree (change in value added in primary sector and in wider economy) among the lesser developed peripheral and traditional regions (cluster 2 and 4). Enhanced quality of life in rural areas According to the Eurobarometer 504, the majority of Europeans consider that infrastructure and services are good in rural areas in their country, with proportions varying between 82% for the environment and landscape and 51% for access to high-speed internet connections; however, only a minority hold this view about job opportunities (37%). Compared with ten years ago, a majority says that things have improved in terms of access (55%) and transport infrastructure connecting to cities (37%) conversely, a majority thinks that things have got worse for job opportunities (42%) and health services (36%). Among the social aspects, respondents deem the role of Pillar II support (see Figure 10 ) as particularly positive in improving access to local infrastructure and services. Figure 10. Impact of the CAP on socio-economic aspects Direct payments Rural development measures Source: Evaluation support study; N=85 respondents from the categories public authority, rural development expert, farmer, processor and producer organisation According to the Implementation Report of the Committee of the Regions (consultation of the regional hubs), none of the measures of the European Direct Payment Regulation is considered to have a significant effect on the challenges posed by sub-optimal infrastructures and services. Over 50% of respondents to the public consultation of the long-term Vision for the EU’s rural areas also stated that infrastructure is the most pressing need for rural areas. Similarly, around 43% of respondents reported the lack of basic services in rural regions, with no major difference between stakeholder group. LAG managers and public authorities frequently cited M07 – basic services and M19 – LEADER, when discussing the effect of the CAP on the provision of social services in rural regions, however, effectiveness of CAP funding is often reported to be indirect. Some key sectors in terms of potential growth for rural areas include tourism (over 40% of accommodation (beds) in the EU (2019) are located in rural areas) and the renewable energy sector. A large number of rural development programmes contributed to the development of a broad variety of services and local infrastructures, notably for tourism, and thereby increasing the accessibility and mobility in rural areas (e.g. biking paths). Projects of basic services and village renewal played an important role in the development of local infrastructure, with a focus on energy efficiency and renewable energy (e.g. Spain). Overall, in traditional regions (cluster 4) the regression analysis indicates positive associations between M07 – basic services, M19 – LEADER, M04 – investment and M06 – farm and business development funding and change in doctors per 100 000 inhabitants. This is valid also for high related ESIF funding regions (predominantly regions in southern and central Europe). Improving access to healthcare and mental health services and services for migrant workers, is deemed important by public authorities and rural development experts from Bulgaria, Ireland and Estonia. Broadband is available to 98% of Europeans and 80% of European homes can access fast broadband (at least 30 Mbps) . However, in rural areas, less than 60% of households have access to fast broadband. In 2017, the Commission launched an action plan for rural broadband. This contained a coordinated set of actions with concrete deadlines to ensure that the specific difficulties in rolling out broadband in rural areas were addressed, thus helping to overcome the rural-urban digital gap. Broadband connectivity is supported by M07 – basic services (in particular M7.3 – broadband infrastructure). Member States (e.g. Greece and Spain) strategically decided to restrict the availability of this measure to certain territories that are particularly affected by remoteness and commuting challenges. The evaluation of the CAP on generational renewal highlighted that with EAFRD in Lithuania, next-generation-access broadband in rural areas increased from 15.6% to 28.7% between 2015 and 2019, while in Sweden it went up from 13.9% to 40.9%. These findings align with the improvement of 56.4% rural area connection pointed by a recent EC study. This is further complemented by the Annual Implementation Report 2019 , according to which, although the level of expenditure for the expansion of broadband and better use of information and communication technology in rural areas was overall low across the Member States, more significant progresses could be observed in Germany, Finland, France, Italy and Sweden. It is worth noticing that in some Member States, rural development support to broadband complements other national digital strategies (e.g. Austria, Italy, Spain), with the possibility to achieve potential synergies. The European Economic and Social Committee, in its Evaluation on the CAP’s impact on territorial development of rural areas, concluded that CAP measures helped people stay in the countryside and fight depopulation. Case study respondents deemed direct payments as having positive effects on many social aspects such as reducing depopulation and prevention of abandonment, although mostly addressing farmers. The quantitative analysis (see Annex 4) suggest that the small farmers’ scheme in the EU and M06 – farm and business development in dynamic regions (cluster 3) are not enough to prevent/reduce out-migration. However, not all Member States have implemented these schemes and without these instruments the effect on out-migration would have been even larger. In particular for dynamic regions, the pull-factor of neighbouring urban areas may outweigh the sustaining support for farm and business development. Concerning agri-environment-climate commitments and support to ANC, Estonian case study findings underlined the importance of these measures in retaining inhabitants in rural areas (primarily via sustained environmental quality). The Bulgarian case study also underlined the impact of these measures in allowing farms to diversify to organic production, which can contribute to valuable local employment opportunities and counteracting local poverty. Most respondents to the consultation on the long-term Vision for the EU’s rural areas (2 219, 95%) consider that the importance of ‘Landscape, countryside, biodiversity and wildlife habitat’ will increase in the next years (with no relevant difference in choices by stakeholder groups). However, as indicated in the study on ‘the challenge of land abandonment after 2020 and options for mitigating measures’ around 30% of agricultural areas in the EU are under at least moderate risk of land abandonment and effective agricultural land abandonment in the EU-27 might total 5 million ha by 2030. As demonstrated by the Scenar 2030 study, the CAP helps mitigating land abandonment. Without CAP, the decrease in agricultural production would not be significant, however, a pronounced reduction in land use would occur. This would affect territorial balance, with marginal areas being further marginalised or, at worst, abandoned, possibly leading to environmental degradation, with fewer jobs, and intensive agricultural areas being further concentrated. The impact of CAP policy tools on land use changes, production concentration and abandonment trends differ between farm types and production groups. Key policy tools to minimise these impacts of external drivers of land abandonment (climate change, globalisation, health crises) include improving farming conditions, supporting areas with natural constraints, forestry and agri-environmental measures and support to rural communities. New approaches to territorial development are on the rise that place a greater emphasis on social and environmental objectives and on the territorial anchorage of economies, including a concern on resilience. The ROBUST project identified five domains where innovative approaches have the potential to enhance rural-urban synergies: social services (focus on social welfare, services, accessibility); social and spatial proximity relations (reduction of physical and social distancing through e.g. short value chains; circularity (closing loops); green economy (rewarding beneficial ways to deliver ecosystem services) and culture and heritage.

5.1.5 Social inclusion This concept refers to the living and working conditions of people in situations of vulnerability (such as rural poor population living in remote rural areas, rural women, young, elderly, disabled, low skilled, ethnic groups, third country nationals). The share of rural population at risk of poverty and social exclusion, which varies from 15% in Austria to over 40% in Malta and some eastern Member States (e.g. Bulgaria), has reduced since 2008. These differences mostly stem from the diverse socioeconomic aspects in Member States, related to lower salaries, unemployment and higher living costs. However, in wealthier countries, rural areas tend to have lower shares than urban areas, whereas in eastern and southern Member States, rural areas have much higher rates of population at risk of poverty. Research has highlighted the potential positive role of CAP measures and instruments – particularly those in Pillar II – to address social and economic needs in rural areas (i.e. tackling social exclusion and promoting social capital and enhance quality of life). However, Pillar II funding directly targeted at social issues is relatively small. Less than 15% of EAFRD support is targeted at rural areas, while not being directly linked to agriculture and forestry, through LEADER and M07 – Basic services. In addition, for some elements key for farmers welfare (e.g. pension schemes, social transfers), EU policies have a limited influence, as responsibilities lie within the core competence of Member States. Half of CAP recipients receive less than EUR 1 250 per year, the distribution of CAP support is thus very inclusive. As indicated by respondents in the case studies, direct payments have positive impacts on farm poverty reduction. This is in line with the results of the World Bank report according to which the CAP reaches poorer regions within the EU Member States and decoupled Pillar I and Pillar II payments are associated with poverty reduction and decrease in inequality at regional (sub-national) levels. Although the number of people living below national poverty rate has decreased, various Member States stated that their rural development programme does not pursue a specific social policy agenda to reduce poverty in rural areas (e.g. Austria, Germany). According to case study respondents, Pillar I instruments mostly result in significant socio-economic benefits for the farmer/farming household, and to a lesser degree young people and rural populations in remote areas. Case study respondents deemed direct payments as having positive effects on social rights and systems, innovation, capacity building and cultural heritage (see Figure 10 ). However, people in situations of vulnerability, i.e. third country nationals, other EU nationals, ethnic groups, and disabled people are most poorly targeted by Pillar I instruments. Pillar II measures provide strong socio-economic benefits to farmers and farming household and also to multiple target groups: rural young people, low-skilled/unemployed people and population in remote places. Pillar II measures, are thus considered more effective in targeting people in situations of vulnerability (including the low skilled and unemployed, rural women and rural young people) than Pillar I instruments, however most CAP funding is disbursed via Pillar I, thereby limiting Pillar II effects. In its Evaluation on the CAP's impact on territorial development of rural areas, the European Economic and Social Committee confirmed that social inclusion of vulnerable groups into agricultural activities was not sufficiently ensured, even if farming has always been able to offer employment to vulnerable people who experience difficulties in finding work. Figure 11: Socio-economic benefits of CAP measures on target groups Impact of Pillar I (n=104) Source: Evaluation support study Case studies underlined the importance of M19 - LEADER and the Community-led Local Development (CLLD) approach in strengthening the social fabric in rural areas. The presence of NGOs working directly with ROMA communities and targeting information sessions for potential Roma beneficiaries helped LAGs to foster their social inclusion strategies targeted at ROMA populations. M16 - cooperation, when targeted, can enable socially disadvantaged groups to gain confidence, skills and technical advice to access investment measures (included via financial instruments). Moreover, M07 - basic services can also help a broader range of rural stakeholders, with other ESIF (e.g. ESF) playing a complementary role when combined in community-led Local Development. Case study respondents also attributed a high effectiveness of M04 – investments and M06 – farm and business development funding in improving farm-level productivity, diversification and in terms of social development. The Greek case study refers to ROMA populations in the context of their important role in the fruit-picking sector. The integration of non-EU immigrants is reported by several interviewees (farmer, processor, and producer organisation) as an issue in the examined Greek regions, where long-established immigrants (mostly from Asian countries) are reportedly still not well integrated. In turn, in Italy (Emilia-Romagna), where workers on dairy farms come mainly from India and Pakistan, no social inclusion issues have been reported, but rather, problems linked to administrative procedures (i.e. visas). The problem of limited employment opportunities for young people living in rural areas has been highlighted in multiple case studies (Austria, Spain, Bulgaria, Greece, France, Czechia). Besides employment, rural youth may also leave rural areas because of limited access to infrastructure (e.g. sports, recreation) and higher education possibilities outside rural areas. The Irish case study highlights social inclusion needs of the rural elderly, many of whom live with poverty, isolation, and poor housing conditions. Despite of the enormous progress that has been accomplished in the field of equal opportunities for women, the evidence points at the disadvantaged situation of women in farming and those living in rural areas. Recent studies showed that women manage only 30% of farms across the EU , and when they do, farms tend to be smaller, with lower incomes, and less access to financial support (loans). Furthermore, the EU Farm Economics overview analysis also found that on average, farms run by women had a lower income per annual work unit (38% lower than those run by men). The income gap by gender concerns all types of farming, with the biggest gap observed in dairy and field crop. This points at a gender imbalance in the sector, that is further confirmed in some case studies i.e. Tyrol, where women inclusion in the social fabric decrease with rurality and remoteness of the areas. It is also partly evidenced by women limited access to vocational training and certifications and by Italian case study regions, where women are particularly affected by long-term and hidden unemployment. This has to do with lack of equal opportunities, training and resources, women being forced to become caretakers of their families or communities (due to lack of adequate social support services and infrastructures), among other issues. Overall, results from the regression analysis suggest that funding for various Pillar II measures are associated with better general labour market inclusion of women in dynamic regions (cluster 3). Spain (Castilla La Mancha) has implemented a strategy to address the demographic challenge (Estrategia Nacional frente al Reto Demográfico 2017), through the implementation of the ITI (integrated territorial investment) delivery mechanism, where EAFRD, ERDF and ESF have been linked to territorial objectives and, more widely, also to the inclusion of certain areas or groups, such as youth and women. Respondents from the categories public authority, rural development expert, farmer, processor and producer organisation consider BPS/SAPS to provide some positive impacts to reducing gender disparities. 5.1.6 Building human capital Pillar II measures M01 – knowledge transfer and M02 – advisory services are territorially widespread across EU rural areas and play an important role in supporting farm-level investments in human capital. M16 - cooperation is similarly considered important to address farm innovation needs. In terms of enabling access to research and innovation, case study respondents also assessed young farmers’ payments as having moderate to positive impacts. Following the regression analysis, in diversified regions (cluster 1) high M07 – basic services and M19 – LEADER funding is positively associated with the change in the training rate as are regions with high funding in M01 – knowledge transfer, M02 – advisory services, and M16 - cooperation. The same trend is observed in relation to comparable ESIF expenditure. M10 – agri-environmental climate, M11 – organic farming, M12 – NATURA 2000, M13 – payments to ANC funding are positively associated with growth rates in the share of the population in training courses. However, this is not observed for high funding from related ESIF expenditure. Regression analysis shows that peripheral regions (cluster 2) with high Pillar I direct payment and Common Market Organisation funding are positively associated with the development of secondary educational attainment between 2014 and 2017. This is potentially a spill-over from improved farm viability: with the economic viability of the farm ensured, education may be more accessible for farm workers, managers and people employed in businesses along the value chain. In dynamic regions (cluster 3), high M01 – knowledge transfer, M02 – advisory services, and M16 – cooperation funding is positively associated with changes in the share of the population with tertiary education.

Building governance capacities and bottom-up participatory approaches are to some extent addressed through the delivery mechanism of LEADER/CLLD, via its specific characteristics of local embeddedness, encouraging participation of rural society in its own development. According to the consultation on the long-term Vision for the EU’s rural areas, a large majority of respondents (1 582, 68%) indicated that the most efficient way of involving rural people in the public debate is to organise events in rural areas. Many Member States reported increased participation of the rural population through various activities organised by the LAGs, both in design and implementation of local development strategies. In addition, M07 – basic services is also deemed to play an impactful role in strengthening social cohesion and fabric. Overall, the CAP contributes to balanced territorial development via poverty reduction and social inclusion in rural areas, as it narrows the economic disparities between less and more developed regions, with a focus on remote areas. The effects of CAP funding depend on the measure or instrument under consideration, and rural region characteristics, particularly the level of structural development. CAP impacts on social inclusion are larger in regions in which the agricultural sector is more important. By contrast, in more structurally developed regions, spill-overs into the wider rural population are generally lower. 5.1.7 Rural area definitions There is no single understanding of what ‘rurality’ means, as there are several statistical definitions. The Commission Communication on ‘A long term Vision for the EU’s Rural Areas’, investigated rurality at three geographical levels. The most detailed geographical level consists of 1 km² grid cells, followed by the local administrative unit (LAU) or municipality level and finally the NUTS-3 level regions. The classification of LAUs is called the degree of urbanisation and the classification of NUTS-3 level regions refers to the urban-rural regional typology. The amount of land classified as ‘rural’ will differ significantly between the three geographical scales. In Spain, the share of land covered by rural grid cells is 98%, by rural areas is 90% and 17% by predominantly rural regions. The impact on population is more limited, but still significant. It changes from 17% of the Spanish population in rural grid cells, to 27% in rural areas and 4% in predominantly rural regions. These statistical definitions do not always fit policy needs, given that there is also agriculture in urban areas. In addition, needs are higher in remote areas (far from cities) with lower population density and lower access to services and infrastructure. This issue of rural areas definition is approached by considering two different aspects: the implementation of rural development programmes at national (regional) level and the monitoring and evaluation purposes at EU level. Implementation of the CAP Member States have the flexibility to define the rural areas targeted by each Rural Development Programme (according to Article 50 of Regulation (EU) No 1305/2013). Quite a few Member States and regions differentiate this rural area demarcation even by measure of the EAFRD. The following table shows the various rural area definitions used in the case studies. Typology of definitions Corresponding case studies Definitions considering population data Bulgaria, Czechia, Germany, Estonia, Greece, Italy, Netherlands, Austria, Definitions considering socio-economic and territorial issues (e.g. population migration, unemployment rate and average monthly gross income) Estonia, Spain, France, Italy Definitions per EU typologies (urban-rural typology and degree of urbanisation) / OECD definition of rural areas Czechia, Greece, Austria Definitions ‘other than’, i.e. as opposed to urban areas Estonia, Ireland, Greece, France, Poland Definitions as per measure-specific delineations Bulgaria, Czechia, Germany, Greece, Spain, Poland Source: Evaluation support study According to the support study, definitions considering socio-economic and territorial issues may be considered as being the most comprehensive and the most tailored to the needs and specificities of the rural areas. Most of the rural development programmes reviewed in the support study include, besides a main definition of rural areas, several measures-specific definitions and exceptions that mostly lead to an increase of the scope of the territory defined as rural. The definition of rural areas has direct consequences on the targeting and allocation of Pillar II funding in certain rural areas, which also requires the coordination of public support, notably from other European structural and investment funds. Some Member States (e.g. Greece and Spain) strategically decide to restrict availability of some measures (e.g. M7.3 – broadband infrastructure)) to certain territories that are particularly affected. Member State-specific definitions which include demographic criteria suggest that CAP Pillar II measures are being targeted to areas facing demographic challenges. Continuity between programming periods is also important. In certain cases (Estonia and Italy), the definitions of rural areas applied in this current programming period are in line with and updated from the definitions applied in the 2007-2013 period. Definitions and monitoring and evaluation purposes The multiple definitions make EU policy making, monitoring and evaluation difficult. All definitions contain ‘grey zones’ such as intermediate or semi-dense areas. All are based solely on population / population density criterion failing to correctly identify EU rural territories characteristics and functionalities (e.g. distance to cities). There is a need to clarify the degree of rurality and to create a common ground with others EU policies (by using also population criteria), while in the meantime address the CAP and rurality analytical needs correctly. For example, the JRC evaluation exercise was based on a EU NUTS3 level description of the regional dimension of the CAP in the period 2011-2018. This required a characterisation of the rural regions, according to: (i) a multidimensional approach including several economic aspects; and (ii) the characteristics and contribution of the agri-sector in the rural economy. Investigating specific aspects of rurality might require sometimes the development of a dedicated analytical framework, as done by the JRC in the context of this evaluation. Nevertheless, for monitoring and evaluation purposes a single harmonised definition for identification of functional rural territories could be useful. In addition, a shared territorial definition of functional rural areas would be important to ensure a higher level of complementarity among all funds (CAP and European structural and investment funds). 5.2 Efficiency

The evaluation assesses the efficiency of the CAP measures and instruments’ contribution to achieving balanced territorial development, particularly focusing on the social and economic aspects, as well as on the administrative burden and costs incurred at the different levels of implementation in relation to the benefits achieved. A pure cost-benefit analysis of the measures and instruments has not been possible given the complexity and number of administrations involved, as well as the differences in management and implementation of the CAP measures. The assessment consists in a quantitative efficiency analysis of relevant CAP output indicators in 2015-2018 in comparison with the inputs, i.e. the funding to the relevant measures. Due to the absence of quantified information about several benefits of the measures, the efficiency assessment could be done only to a limited extent. Therefore, the case studies form the other main foundation in respect to the analysis, as they identify the obstacles to efficiency as experienced by managing authorities, beneficiary groups and stakeholder organisations. To complete the analysis available local data on administrative costs were compared with the estimated value of outputs/results or impacts, including programme expenditure. Instruments outreach per euro spent From the quantitative analysis of input/output ratio for funds, Pillar I instruments are judged relatively ‘efficient’ as, overall, across the EU territory, the funding is much smaller than the value-added of the funded sector (i.e. Pillar I spending is much lower than the gross value added from primary sector). In general, at NUTS3 level, areas with high agricultural activity are more ‘efficient’ in their use of Pillar I funds (see Map 2 in Annex 4). This is particularly true in Italy, Finland, Sweden, Hungary, and the Baltic countries, whereas France, Greece, Spain, Poland, Germany Austria and Bulgaria have more areas with CAP funding closer to the sector value added. The lowest efficiency scores are found in urban areas with minimum agricultural activity. Although data was not available for all rural development programmes for the number of training days, there is nonetheless significant variety in the ratio of CAP spend per amount of training delivered. Higher efficiency ratios (more than 600 days per million euro of spending) were found in territories with high proportions of farming population or activities (e.g. Greece, Spain, Ireland, Scotland, parts of Italy, as well as in Croatia, Latvia, Flanders and South Germany). More central Member States and Member States with more developed secondary sectors such as the Netherlands, Denmark and Austria, had lower ratios, suggesting that the types of training funded in these cases were more expensive, per training day delivered. The lowest scores (below 100 days of training per million euros) appear in Lombardy, Lazio, Denmark, some areas in Germany, the Netherlands, Czechia, Hungary, Cyprus and Estonia. However, it is difficult to draw strong conclusions from these variations because of the potentially wide variation in the types of training offered, in each case. Comparing the number of holdings participating in support schemes –, with the spending on M09 – setting-up of producer organisations, M16 – cooperation and M17 – risk management (see Map 3 in Annex 4), shows that the ratio of participants to funding input is relatively high (over 80 holdings per million euro of expenditure) in many Member States (including Portugal, Bulgaria, Cyprus, Romania, Poland, Latvia and some regions of Italy). The ratio is lower in Finland, Estonia, Austria and Hungary (between 20 and 80) and it appears to be very low (below 20) in most scarcely populated areas. This indicates that it is particularly costly to establish effective cooperation and joint working between farmers when the farms are not so closely co-located, which raises questions also about the efficiency of the funding in those situations. The European Innovation Partnership (EIP) intends to enhance human and social capital and promote innovation in agricultural practices, with direct or indirect economic benefits. Overall, the data on groups supported, actions initiated and actors involved show that by September 2021 funding for 2 085 completed operational groups has been provided under this measure, in the current programming period. The highest numbers of groups per million euros of spending are noted in Ireland, central Germany and some regions of Spain, suggesting good efficiency in using this measure, in these territories. Improved services and infrastructure is key in the pursuit of urban-rural territorial balance, because they make areas more attractive to younger people and families, and allow inhabitants of rural areas to improve their living conditions. The analysis of the population benefiting from improved services/infrastructures (IT or others) against expenditure on M07 – basic services (see Map 5 in Annex 4) shows that in all Member States which use the relevant CAP measure the whole population benefits from rural development investments, although the number per unit of spend varies significantly between programme areas. In some particularly remote areas with natural constraints or in Member States with an ageing rural population (e.g. Greece, Ireland, Scotland, Castilla y Leon) the measure reaches fewer people per million euros of expenditure (less than 500 people). The outreach per unit of spent is highest (above 12 000 people) in rural areas that benefit already from better infrastructure (e.g. in Galicia, Catalonia, Andalusia, Haute-Normandie, four regions in Germany, Finland and Flanders). The ratio is higher also in Member States that report younger rural populations and lower rural service provisions (e.g. Bulgaria, Poland). The calculations suggest that although needs for rural infrastructure and services depend also on cultural and local factors that go beyond the scope of CAP funding, such as health services and education, relatively small expenditure on M07 – basic services can benefit a large number of people in rural communities in terms of improved accessibility and opportunities. Considering the population covered by local action groups (LAG) ( Map 8 and Map 9 in Annex 4), France, Czechia, Slovakia and Hungary have the greatest reach per LEADER group (more than 80 000 people covered). The majority of the rural areas score between 20 000 and 80 000 persons per LAG, while Sweden, Estonia, Lithuania, East Germany, central Italy and central Spain (which include areas of low population density) score below 20 000. As for the number of LEADER projects funded, LAGs in Sweden, Denmark, Estonia, Latvia, Denmark, England, Czechia and Northwest Spain are funding many projects (more than 10 per LAG), while the majority of other areas fund between 2 and 10 projects. South Spain, Italy, Lithuania, central France and Wales had difficulties establishing LAG projects and they funded 0 or 1 project only. These indicators suggest that LAGs are succeeding in reaching rural people and funding projects throughout the EU territory with a few exceptions mainly in Italy, Spain and the Baltic countries. It is important to mention nevertheless that these indicators do not show the scale of LAG projects nor their ultimate impacts, so it is not possible to conclude that the territories with lower scores for these indicators will have lower LEADER impact, overall. Administrative burden The evidence presented in case studies highlight common issues concerning the efficiency of CAP measures and instruments in achieving social outcomes. A principal point concerns the accessibility of funding to all groups, which is affected by a range of issues including targeting, eligibility and selection criteria and the indirect effects of controls and administrative requirements on potential beneficiaries, and on other actors who support or facilitate their access to CAP funds. Case studies referred to e.g. lack of clarity regarding eligibility criteria (e.g. M11 – organic farming) and to inappropriate criteria (e.g. the requirement for plant cover in mountainous areas for some direct payments some heavy conditions linked to M06 – setting-up). Only two case study interviews (Ireland and Saxony-Anhalt) found that CAP funding under both pillars is accessible to most farmers. In most case studies, stakeholders shared the opinion that some types of CAP funding are complex to access. This means that farmers who lack confidence or financial or management capacity may decide not to apply for funds, or they may feel obliged to seek professional help to gain such access (Auvergne – both for Pillars; Italy, Poland, Czechia, Bulgaria for Pillar II and especially for LEADER in Austria). On Pillar I instruments, interviewees did not mention as many sources of administrative burden as for the rural development measures. However, they reported difficulties to implement in practice the greening schemes. Most importantly, they caused high administrative costs of demarcation and control due to some overlapping with cross-compliance and agri-environmental measures. Public authorities also signalled the lack of technical assistance fund under CMO policy instruments as a strong limitation for public authorities providing technical assistance to producer organisations’ programmes (Emilia-Romagna).Nevertheless, many case studies report that Pillar I aid is quite efficiently delivered, with relatively low administrative burden and swift application and payment processes. Online applications, as well as quasi-automatic systems managed by the paying agencies seem to improve efficiency in general, due to which beneficiaries do not have to spend much time to make their claims (Austria, Estonia). However, they can be relatively complex for smaller farmers or farmers without adequate computer knowledge or equipment to deal with them (Saxony-Anhalt). As regards cost-effectiveness, Pillar I aid is seen as not particularly targeted towards the social aspects of balanced territorial development and the needs of vulnerable or socially excluded rural population (supported by public administration, experts and NGO stakeholders). Most c