A report that is prepared annually by Member States and submitted to the European Commission to inform about the performance of the CAP Strategic Plans.

The Annual Performance Report (APR) as part of the CAP Performance, Monitoring and Evaluation Framework (PMEF) provides an annual overview of the implementation of a CAP Strategic Plan, including key qualitative and quantitative information by reference to financial data and to output and result indicators.

The APR helps to assess the progress made towards achieving targets and related milestones for relevant result indicators set in a CAP Strategic Plan. The APR is an important tool for assessing the effectiveness of a CAP Strategic Plan and ensuring that it is delivering the intended results.

Source: Regulation (EU) 2021/2115 of the European Parliament and of the Council of 2 December 2021 establishing rules on support for strategic plans to be drawn up by Member States under the common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulations (EU) No 1305/2013 and (EU) No 1307/2013

The requirements related to mandatory standards and requirements established in EU and national law, as well as conditionality (including good agricultural and environmental conditions (GAECs) and statutory management requirements (SMR)), as laid down in the CAP Strategic Plan. Support provided under the CAP that compensates for additional costs and income foregone can only compensate for those costs and income foregone resulting from commitments going beyond the baseline.

Source: Whereas Article 72 of the CAP Strategic Plan Regulation (EU) 2021/2115

Set of techniques which help scale up evaluation findings from the micro- to macro-level (e.g. from farm to sector, from plot to the CAP Strategic Plan/intervention area). For instance, these can be a GIS, satellite images and spatial analysis.

Source: European Evaluation Helpdesk for Rural Development (2018), TWG 5

Activities that seek to develop knowledge and skills of actors involved in the implementation, monitoring and evaluation of CAP Strategic Plans.

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

Causality refers to the relationship between causes and effects. It implies that a change in one variable (the cause or independent variable) directly changes another variable (the effect or dependent variable). Establishing causality is a central goal in many scientific and social science studies. 

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

The extent to which complementarity or synergy can be found within an intervention and in relation to other interventions. Coherence analysis may highlight areas where there are synergies that improve overall performance and are not possible if introduced at national level, or point to tensions e.g. objectives which are potentially contradictory, overlapping or approaches which are causing inefficiencies.

Source 1: DG AGRI (2017) Technical Handbook for the CMEF 2014-2020
Source 2: Better Regulation Toolbox, Tool #47 "Evaluation criteria and questions"

An indicator is a quantitative or qualitative factor or variable that provides a simple and reliable means to measure achievement, reflect changes connected to an intervention, or help assess the performance of a development actor. In the context of the CAP, the set of common indicators, binding for all Member States, serves to measure achievements and changes at both the CAP Strategic Plan and EU level.

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

Ensuring that there are no logical and factual contradictions including significant differences within or between different interventions, options and other parts of a programme, plan or assessment.

Source: Better Regulation Toolbox Tool #60 'Baselines'

External factors that have considerable capacity to generate unanticipated outcomes in terms of policy implementation. For example, confounding factors that stem from other programmes funded by European Structural and Investment (ESI) funds, national funding or other investment programmes, as well as the socio-economic consequences (caused by events such as COVID-19, the EU’s response to providing recovery efforts for rural development under the Next Generation EU, the war in Ukraine or the increase in energy costs) which can influence the CAP Strategic Plan interventions, targets and results.

Source: European Evaluation Helpdesk for Rural Development (2021), TWG 8

The quantification of the benefits that would be generated by one euro of costs imposed on society. While cost-effectiveness analysis (CEA) is closely related to cost-benefit analysis, it uses other measures instead of monetised benefits, such as increased life expectancy, educational attainment and abated emissions. In the evaluation context, the cost-effectiveness analysis can compare the evaluated intervention against best practices or similar interventions. It can also be used to assess effectiveness of the implementation process where different implementation approaches have been pursued. CEA is less easily applicable to interventions with more than one main objective. If the intervention aims to achieve a number of objectives (e.g. job creation and environmental protection) or have indirect impacts, the results of CEA may be misleading or irrelevant.

Source: Better Regulation Toolbox, Tool #57 ‘Methods to assess costs and benefits’

In the context of impact evaluation, a counterfactual refers to the hypothetical scenario of what would have happened to the same units (such as individuals or groups) had they not been exposed to the treatment or intervention being studied. It is a fundamental concept in establishing causality and especially relevant when assessing the effectiveness of a policy measure. 

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Covariates are variables included in statistical analyses to control for their effects on the outcome being studied. In impact evaluation models, they help isolate the effect of the primary independent variables on the dependent variable and are crucial for reducing confounding in econometrics models. For instance, farm size and farm type might be covariates when studying farm income.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Issues that horizontally affect all areas of the policy. Important cross-cutting issues for the CAP include driving simplification.

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

A deadweight effect is defined as the effects which would have arisen even if the intervention had not taken place. Changes observed in the situation of beneficiaries following the public intervention or reported by direct addressees as a consequence of the public intervention, that would have occurred, even without the intervention. For example: a farmer received assistance for the building of a self-catering cottage. However, an investigation into the profitability of the investment and the underlying motives suggest that he would have built the cottage, even without support. Thus, there is deadweight since the construction of the cottage cannot be imputed entirely to the intervention.

Source: DG AGRI (2017) Technical Handbook for the CMEF 2014-2020

In section 4.1 of the CAP Strategic Plans, Member States shall include definitions and minimum requirements which are common to several elements in the plans. These include:

The direction of the observed net effect of a programme or intervention, as measured by the corresponding impact indicator, in relation to the corresponding factors of success. The direction can be positive, negative, mixed or zero (no effect).

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Use of Factors of Success in Evaluation (2023)

The extent to which the intervention achieved, or is expected to achieve, its objectives, including any differential outcomes across groups. Effectiveness can provide insight into whether an intervention has attained its planned results, the process by which this was done, which factors were decisive in this process and whether there were any unintended effects. The evaluation should form an opinion on the progress made to date and the role of EU action in delivering observed changes.

Source 1: OECD (2021), Applying Evaluation Criteria Thoughtfully, OECD Publishing, Paris
Source 2: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

The extent to which the intervention achieved, or is expected to achieve, its objectives in an economic and timely way. ‘Economic’ is the conversion of inputs (funds, expertise, natural resources, time, etc.) into outputs, results and impacts, in the most cost-effective way possible, as compared to feasible alternatives in the context. ‘Timely’ delivery is within the intended timeframe, or a timeframe reasonably adjusted to the demands of the evolving context. This may include assessing operational efficiency (how well the intervention was managed). Efficiency analysis should explore the potential for simplification and burden reduction by measuring administrative and regulatory burdens and looking at aspects of simplification.

Source 1: OECD (2021), Applying Evaluation Criteria Thoughtfully, OECD Publishing, Paris
Source 2: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

Endogeneity occurs when an independent variable in a regression model is correlated with the error term, often due to omitted variables, measurement error or simultaneous bias. This correlation can lead to biased and inconsistent estimates of the model coefficients. For example, farm size and farm productivity will be endogenous in an impact assessment until omitted variables, such as farm type and location etc., are included and until a good strategy is adopted to control for the bi-directional causality.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Mobilising endogenous potential, valorising territorial assets and strengthening links between local community members/actors to achieve more with available resources and foster innovative, sustainable and integrated, community-driven projects that drive lasting impacts in the LAG area.

Enhanced results and impacts imply that the type and quality of projects implemented under LEADER are different compared to those which are or could be implemented under other programmes/interventions that do not apply the LEADER approach (typically top-down actions).

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Guidelines – Assessing the added value of LEADER (2024)

EU added value looks for changes that are due to an EU intervention, over and above what could reasonably have been expected from national actions by Member States.
In policy areas where the EU has non-exclusive competence, the analysis of EU added value should explore the actual application of the subsidiarity principle by assessing the added value of EU action compared to that of other actors.

Source: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

A comprehensive plan proposed by the European Commission in 2019 aimed at making the EU climate neutral by 2050. The plan outlines a set of policy initiatives designed to transition Europe to a sustainable, low-carbon economy while also promoting economic growth, job creation and social justice. The European Green Deal covers a wide range of areas, including climate change, energy, transport, agriculture, biodiversity, circular economy, pollution, and research and innovation.
It is also seen as a key initiative in addressing the global challenge of climate change and achieving the objectives of the Paris Agreement.

Launched by the European Commission in 2012, EIP-AGRI is the European Innovation Partnership focusing on the agricultural and forestry sectors. EIP-AGRI brings together innovation actors and creates synergies between existing policies. Its overarching aim is to foster competitiveness and sustainability in these sectors, thereby contributing to ensuring a steady supply of food, feed and biomaterials, and the sustainable management of the essential natural resources on which farming, and forestry depend by working in harmony with the environment. It adopts the interactive innovation model aimed at fostering bottom-up approaches and collaboration between various actors to make the best use of complementary types of knowledge (scientific, practical, organisational, etc.) to boost the co-creation and dissemination of solutions/opportunities that are ready to be implemented in practice.

Source 1: Communication from the Commission to the European Parliament and the Council on the European Innovation Partnership 'Agricultural Productivity and Sustainability' (2012)
Source 2: Evaluating the AKIS Strategic Approach in CAP Strategic Plans

Evaluation that takes place throughout the implementation of CAP Strategic Plans. It includes all evaluation activities carried out during the programming period. It does not include the ex ante evaluation, nor the ex post evaluation after the implementation period. Evaluations during the implementation period are to be included in the evaluation plan (Article 140 of Regulation (EU) 2022/2115).

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

Outcomes of the assessment of efficiency, effectiveness, impact and achievements of an intervention in comparison with policy objectives.

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

A precisely predefined critical factor, which is a prerequisite for, and has a direct impact on, and genuine link to, the effective and efficient achievement of a specific objective for an investment or EU priority. For the European Agricultural Fund for Rural Development (EAFRD), a set of priorities-linked conditionalities is listed in Annex V of Regulation (EU) 1305/2013 and another set of general conditionalities is listed in Part II of Annex XI of Regulation (EU) 1303/2013. Ex ante conditionalities aim to ensure the immediate start and efficient implementation of rural development programmes and their applicability is assessed by Member States in the framework of their preparation of the Rural Development Programmes 2014-2020 and, where appropriate, a partnership agreement. The European Commission assesses the consistency and adequacy of the information provided by the Member State. In cases where there is a failure to fulfil an applicable ex ante conditionality within the deadline laid down, the Commission has the power to suspend interim payments to the relevant priorities of the programme under precisely defined conditions.

Ex ante conditionalities do not apply in the 2023-2027 programming period.

The extent to which the various components of different interventions, affecting the same context, operate together to achieve their objectives. Where relevant, analysis of coherence may involve checking whether interventions are in line with the objectives of the European Green Deal, or whether the intervention is consistent with the overarching environmental goals (such as the European Climate Law) or other policies targeting the environment. At its widest, external coherence should also look at compliance with national policies or international agreements/declarations (for example EU labour market interventions might be looking into coherence with International Labour Organization conventions), in particular the UN Sustainable Development Goals or EU interventions in developing countries.

Source: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

Factors of success are criteria used to further develop and specify key evaluation elements and allow judging on the change brought about by the evaluated intervention(s). They form the basis for the establishment of the causal chain between outputs, results and impacts, and can be the core component around which evaluation findings are structured.

Source 1: Joint Evaluation Unit for the Directorates - General EuropeAid, Development and Foreign Affairs, Evaluation Methods For The European Union’s External Assistance
Source 2: Better Regulation Toolbox, Tool #46 ‘Designing the evaluation’

The Farm Sustainability Data Network (FSDN) is a statistical network converted from the FADN (Farm Accountancy Data Network) that will collect and process data on the economic, environmental and social sustainability of agricultural holdings (farms) in the EU. The FSDN is intended to provide a more comprehensive and holistic view of farm sustainability going beyond the traditional focus on farm income and agricultural productivity to include indicators related to climate change, biodiversity, soil health, water management and social issues, such as rural development and labour conditions. The FSDN is part of the post-2020 CAP and is expected to support policy decisions related to farm sustainability, as well as help evaluate the effectiveness of CAP measures in achieving sustainability objectives.

Source: Proposal for a Regulation of the European Parliament and of the Council amending Council Regulation (EC) No 1217/2009 as regards conversion of the Farm Accountancy Data Network into a Farm Sustainability Data Network

An initiative launched by the EU in May 2020 as part of the European Green Deal. The Farm to Fork strategy’s goal is to create a more sustainable food system by promoting a transition to a fair, healthy and environmentally friendly production and consumption.

The Farm to Fork strategy aims to accelerate the transition to a sustainable food system that should: have a neutral or positive environmental impact; mitigate climate change and adapt to its impacts; reverse the loss of biodiversity; ensure food security, nutrition and public health, making sure that everyone has access to sufficient, safe, nutritious, sustainable food; preserve affordability of food while generating fairer economic returns, fostering competitiveness of the EU supply sector and promoting fair trade.

The strategy sets out both regulatory and non-regulatory initiatives, with the common agricultural and fisheries policies as key tools to support a just transition.

Source: Communication rom the Commission to the European Parliament, the Council, the European Economic And Social Committee and the Committee of the Regions a Farm to Fork Strategy for a fair, healthy and environmentally-friendly food system COM/2020/381 final

Local and multi-level processes and mechanisms that ensure effective and transparent decision-making and relations between different actors involved in LEADER implementation.

Local governance in LEADER: Processes and mechanisms established, coordinated, and animated by the LAG to ensure participatory, transparent, and inclusive decision-making and strong community engagement in strategy development and implementation.

Multi-level governance in LEADER: Processes and mechanisms established collaboratively between Managing Authorities/Paying Agencies, regional authorities, and LAGs, based on EU-level standards, to empower LAGs, enhance their decision-making, management, and accountability capacities, and promote responsive, innovative and tailored local development strategies.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Guidelines – Assessing the added value of LEADER (2024)

Impact is an evaluation criterion that assesses the extent to which the intervention has generated or is expected to generate significant positive or negative, intended or unintended, higher-level effects. In EU evaluations, the impact is part of the evaluation criterion of effectiveness, analysing how the observed changes may be linked to the actions triggered by an EU intervention.

Source 1: OECD (2021), Applying Evaluation Criteria Thoughtfully, OECD Publishing, Paris
Source 2: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

Ex ante assessment of the prospective economic, environmental and social effects of a policy, often based on simulations.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Empirical evaluation that captures the higher-level effect (impacts) of a programme/intervention against a baseline situation (with or without a counterfactual approach).

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: CAP Evaluation Expert Insights – LEADER (2024)

The extent to which the various components of the same intervention operate together to achieve its objectives.

Source: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

‘Intervention’ means a support instrument with a set of eligibility conditions specified by a Member State in its CAP Strategic Plan based on a type of intervention provided for in the Strategic Plan Regulation (Article 3).

For each intervention specified in the CAP Strategic Plan, it shall be, among other things, specified: on which type of intervention it is based, the territorial scope, the specific design or requirements of the intervention, the eligibility conditions, the result indicators to which the intervention should contribute directly and significantly, the output indicator and the planned outputs, the planned unit amounts, and the annual financial allocation of the intervention (Article 111).

Source: DG AGRI (2017) Technical Handbook for the CMEF 2014-2020

The intervention strategy is developed for each Specific Objective of the CAP Strategic Plan and includes:

The key topics that must be addressed during the evaluation of a specific or cross-cutting objective. The key elements related to the assessment of effectiveness for each specific or cross-cutting objective are listed in Annex I of the Regulation (EU) 2022/1475. For other evaluation criteria (efficiency, relevance, coherence, Union added value) key elements have been proposed in the guidelines 'Use of factors of success in evaluation'.

The quantified level of the contribution of the CAP towards national or EU level targets. The magnitude of the effect is usually indicated as the percentage of the observed net effect of a programme or intervention, as measured by the corresponding impact indicator to the corresponding target set.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Use of Factors of Success in Evaluation (2023)

The National CAP Network is a network of stakeholders (e.g. organisations and administrations, advisors, researchers and other actors in the field of agriculture and rural development at national level) that supports the implementation of the CAP in each Member State.

The objectives and tasks of National CAP Networks are set by Article 126(3) and (4) of the Regulation (EU) 2021/2115. The network provides a platform for dialogue and cooperation between these groups and supports the implementation of the CAP through the exchange of information, best practices and experience.

The National CAP Network is a key tool to drive and steer policy at national level and to help ensure that policy measures are adapted to local conditions and needs, and implemented in a coordinated and effective manner. The network also provides a means for stakeholders to engage with the policymaking process and contribute to the development of new policy measures and initiatives.

Source: Regulation (EU) 2021/2115 of the European Parliament and of the Council of 2 December 2021 establishing rules on support for strategic plans to be drawn up by Member States under the common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulations (EU) No 1305/2013 and (EU) No 1307/2013

Groups of people (such as farmers, researchers, advisers, etc.) who work together on a practical innovation project with concrete objectives. Operational Groups are financed by the European Agricultural Fund for Rural Development.

Operational Groups are intended to bring together multiple actors such as farmers, researchers, advisers, businesses, environmental groups, consumer interest groups or other NGOs to advance innovation in the agricultural and forestry sectors.

Source: EIP - AGRI brochure on Innovation Support Services

Refers to the electronic information system for recording and keeping key information on the implementation of the CAP Strategic Plan needed for monitoring and evaluation, in particular for monitoring progress towards the objectives and targets set, including information on each beneficiary and operation.

Source: Regulation (EU) No 1303/2013 of the European Parliament and of the Council

This type of bias arises in statistical models when a relevant variable (i.e. that influences the dependent variable) is left out of the model. This omission can lead to incorrect estimates of the effects of other variables included in the model.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

A performance framework is established under the shared responsibility of Member States and the European Commission. The framework allows reporting, monitoring and evaluation of the performance of the CAP Strategic Plan during its implementation. It includes five elements:

1. a set of common output, result, impact and context indicators for monitoring, evaluation and annual performance monitoring;
2. targets and annual milestones established in relation to the relevant Specific Objective using the relevant result indicators;
3. data collection, storage and transmission;
4. regular reporting on performance, monitoring and evaluation activities;
5. the ex-ante, interim and ex post evaluations and all other evaluation activities linked to the CAP Strategic Plan.

Source: DG AGRI (2017) Technical Handbook for the CMEF 2014-2020

The PMEF consists of a set of elements as defined in Article 128 of the CAP Strategic Plan Regulation (EU) 2021/2115, including: common context, output, result and impact indicators; targets and milestones; data collection, storage and transmission; regular reporting on performance, monitoring and evaluation activities; and the ex-ante, interim, and ex post evaluations and all other evaluation activities linked to the CAP Strategic Plan. The performance framework will be established under the shared responsibility of Member States and the European Commission, which will allow reporting, monitoring and evaluation of the performance of the CAP Strategic Plan during its implementation. The list of common indicators related to output, result, impact and context as set out in Annex I of the 2021/2115 Regulation.

Source: Regulation (EU) 2021/2115 [A1] of the European Parliament and of the Council of 2 December 2021 establishing rules on support for strategic plans to be drawn up by Member States under the common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulations (EU) No 1305/2013 and (EU) No 1307/2013

Evaluation that assesses how a programme/intervention is implemented (e.g. governance, delivery system, communication, technical assistance, networks).

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: CAP Evaluation Expert Insights – LEADER (2024)

Relevance analyses the extent to which the objectives and design of interventions remain relevant to the current and future needs and problems in the EU, including wider EU policy goals and priorities. Relevance assessment involves looking at differences and trade-offs between different priorities or needs. It requires analysing any changes in the context to assess the extent to which the intervention can be (or has been) adapted to remain relevant.

Source 1: OECD (2021), Applying Evaluation Criteria Thoughtfully, OECD Publishing, Paris
Source 2: Better Regulation Toolbox, Tool #47 ‘Evaluation criteria and questions’

A sample is representative, if all the elements in a population have the same chance of being part of the sample. Hence, a representative sample has the same general characteristics as the target population and therefore accurate conclusions about a population can be drawn from the sample.

Source: European Evaluation Helpdesk for Rural Development (2021), TWG 8

Analytical work that supports evaluation without assessing the effect of the programme/intervention (e.g. context analysis, environmental monitoring study, study to develop evaluation methods and identification of data gaps).

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: CAP Evaluation Expert Insights – LEADER (2024)

Evaluation that captures achievements of results by beneficiaries in relation to targets planned but does not necessarily capture effects against a baseline situation.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: CAP Evaluation Expert Insights – LEADER (2024)

In the context of evaluations for the 2014-2020 Rural Development Programming (RDP) period, contributions of an operation to focus areas other than the focus area under which the operation has been primarily programmed. They are assessed in the context of the evaluation activities for the enhanced Annual Implementation Reports (AIRs) and the ex post evaluation e.g. when calculating the complementary result indicators. The evaluators should, if possible, calculate/assess the complementary result indicator of a specific focus area, taking into account both primarily programmed operations and the operations which have secondary contributions to that specific focus area. The quantification of secondary contributions provides a much more complete and better picture of the achievements of the specific focus areas under each RDP priority.

Source: European Evaluation Helpdesk for Rural Development (2017), TWG 8

This occurs when the sample used in a study or analysis is not representative of the population from which it was drawn. This can lead to skewed results and conclusions that do not accurately reflect the reality of the broader population.

Example: A group of farms receive a subsidy and the reasons behind granting the subsidy (e.g. farm size, years, operating, types of productions, output, etc.) need to be accounted for. Selection bias here can lead to an overestimation of the positive effects of CAP support on farm income because the sample of supported farms may be biased towards farms that benefit from more support than others.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Networks, mutual trust, shared mental models and beliefs that foster quality of collaboration and cooperation within and among LAG areas.

Source 1: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Guidelines – Assessing the added value of LEADER (2024)

Source 2: European Evaluation Helpdesk for Rural Development: Evaluation of LEADER/CLLD (2017)

Occurs when there is a mutual relationship between the independent variable (i.e. income) and the dependent variable (i.e. CAP support).

Example: The relationship between education and income. Education is often used as a predictor of income. However, this relationship can be endogenous because income can also predict education as high income persons can access education more easily.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Set of policy objectives that translate the General Objectives of the CAP into more concrete priorities taking into account relevant EU legislation, particularly with regard to climate, energy and environment.

The Specific Objectives of the CAP are defined at EU level and applied by Member States in their CAP Strategic Plans. There are nine Specific Objectives defined in Article 6 of the Regulation (EU) 2021/2115 and these objectives are complemented and interconnected with the Cross-Cutting Objective of modernising agriculture and rural areas by fostering and sharing of knowledge, innovation and digitalisation in agriculture and rural areas, and by encouraging their uptake by farmers, through improved access to research, innovation, knowledge exchange and training.

General and Specific Objectives are pursued through EU support financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) under the CAP.

Source: Recital 22, Article 6 of the Regulation (EU) No 2021/2115

This refers to the likelihood that a relationship observed in a data set is not due to random chance. Statistical significance is often determined using a 'p-value', with a lower p-value (typically less than 0.05) indicating a higher likelihood that the observed relationship is indeed significant and just a random occurrence.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

A target is a detailed performance requirement, arising from a policy objective, which needs to be met in order to achieve the stated objective. Targets are quantified whenever possible and typically time-bound.

Within the context of the CAP Strategic Plans and the Strategic Plan Regulation (EU) 2021/2115, ‘targets’ means pre-established values, set by Member States in the framework of their intervention strategies and to be achieved by the end of the CAP Strategic Plan period in relation to the result indicators (Article 3.7). The value of those targets shall be justified on the basis of the assessment of needs. All CAP Strategic Plans shall include quantified targets in relation to the Specific Objectives (whereas recital 101).

Furthermore, Article 3.6 establishes that 'milestones’ means intermediate pre-established values, set by Member States in the framework of their intervention strategies, and are to be achieved at a given point in time during the CAP Strategic Plan period to ensure timely progress in relation to the result indicators.

Source: European Evaluation Helpdesk for Rural Development (2015), TWG 1

The term refers to the collective use of an intervention as defined under a single article in the Strategic Plan Regulation (EU) 2021/2115. Types of interventions are defined in the form of direct payments, types of intervention in certain sectors and types of intervention for rural development.

Source: European Commission, Directorate-General for Agriculture and Rural Development, Chartier, O., Krüger, T., Folkeson Lillo, C. (2023). Mapping and analysis of CAP strategic plans : assessment of joint efforts for 2023-2027, (O.Chartier,editor,C.Folkeson Lillo,edito) Publications Office of the European Union.

This is a condition in causal inference where the treatment assignment (or exposure) is independent of the potential outcomes, given a set of covariates. When this condition holds, it is possible to obtain unbiased estimates of causal effects.

If the unconfoundedness assumption holds, the assignment (receiving or not receiving) of CAP subsidies is independent of the potential outcomes (farm income where the farm received the subsidy and farm income where the farm did not receive the subsidy), given the covariates. In other words, once controlling for farm size, type of crops and location, the assignment of CAP subsidies does not provide any additional information about potential farm income.

When estimating the effect of CAP subsidies (the treatment) on farm income (the outcome), suppose there is a dataset of farms with information on whether they received CAP subsidies, their income, and other covariates such as farm size, type of crops grown and location.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

The smallest part of an organised system which is being analysed. The unit of analysis can be defined at the micro and macro level of assessment. For instance, the unit of analysis at micro level could be parcels or farms whereas at the macro level it could be a catchment or NUTS 3, as well as an entire region or CAP Strategic Plan territory.

Source: European Evaluation Helpdesk for Rural Development (2018), TWG 5

This is the variable being tested and measured in an experiment or impact evaluation study. It is 'dependent' because its values depend on the influence/effects of the independent (fixed) variables. For example: farm income levels, farm productivity, etc.

Source: EU CAP Network supported by the European Evaluation Helpdesk for the CAP: Assessing the effectiveness and efficiency of CAP income support instruments (2024)

Also known as an independent variable, this refers to values controlled or predetermined by the researcher. It is hypothesised to cause or influence the dependent variable. For example: farm size, location, farm type, input prices, output prices, etc.