EUROPEAN COMMISSION Brussels, 9.12.2016 SWD(2016) 430 final COMMISSION STAFF WORKING DOCUMENT



IMPACT ASSESSMENT

Accompanying the document Strategy for Agricultural Statistics 2020 and beyond and subsequent potential legislative scenarios {COM(2016) 786 final}

{SWD(2016) 429 final}



Contents 1. THE PROBLEM 1.1. Context of European Union Agricultural Statistics 1.2. A changing world, unchanging agricultural statistics 1.3. The current EASS 1.4. Stakeholders of the EASS 1.5. Performance, evaluation and lessons learnt of current EASS 1.6. Problems of the current EASS 1.6.1. New and emerging data needs not adequately served 1.6.2. Data collections not sufficiently harmonised and coherent 1.6.3. Burden of providing data perceived as too high 1.6.4. Evolution of the problems 2. NEED FOR EU ACTION 3. OBJECTIVES 3.1. Meeting data needs 3.2. Coherence and integration 3.3. Burden reduction 4. OPTIONS 4.1. Baseline – No EU action on structural data of agriculture

4.2. Prolongation of the FSS Regulation (EC) No 1166/2008 4.3. Single new legal framework for the whole sector of agricultural statistics 4.4. Two-step integration of agricultural statistics 4.5. Early discarded options 4.6. Problem and solution tree 5. IMPACT ANALYSIS 5.1. Administrative burden impacts 5.2. Cost impacts 5.3. Impacts of Option 1 - Baseline – No EU action on structural data of agriculture 5.4. Impacts of Option 2 - Prolongation of the FSS Regulation (EC) No 1166/2008 5.5. Impacts of Option 3 – Single new legal framework for the whole sector of agricultural statistics 5.6. Impacts of Option 4 - Two-step integration of agricultural statistics 5.7. Impacts of early discarded options 6. COMPARISON OF OPTIONS 7. MONITORING AND EVALUATION ANNEXES Annex I: Procedural information Annex II: Stakeholder consultation Annex III: Who is affected by the initiative and how Annex IV: Impact analysis methodology

Annex V: Detailed list of data sets collected in the EASS Annex VI: Summary of present agricultural data collection and new needs in the EU Annex VII: List of abbreviations 1. THE PROBLEM 1.1. Context of European Union Agricultural Statistics The current European Agricultural Statistics System (EASS) has been developed since the early 1950s. Agricultural statistics are the oldest EU statistics still to be produced, and a large part of them are provided under legal obligations. The EASS covers more than 50 data sets that are transmitted to Eurostat by National Statistical Institutes (NSIs) or other national statistical authorities. It consists of seven statistical domains: structural data, agri-monetary statistics, crop production, organic farming, permanent crops, animal products and livestock, and agri-environmental indicators. In addition, the Directorate-General for Agriculture and Rural Development (DG AGRI) manages the Farm Accountancy Data Network (FADN), a survey that, while not officially part of EU statistics, is closely linked to the EASS. The main aim of the EASS is to support decision-making and policy design, implementation, monitoring and evaluation in areas related to agriculture, such as the Common Agricultural Policy (CAP) and climate change policies. Agriculture accounts for almost 40% of the EU budget, being the only policy almost entirely funded by the EU, where EU spending largely replaces national spending. For an annual budget of currently about 59 billion Euro, EU taxpayers must have the guarantee that this policy is based on hard facts and figures. Moreover, agriculture covers 47% of the EU territory, and the environmental impact of agricultural practices, but also the environmental services provided by agriculture are immense. Agriculture uses soil, water, air and biodiversity and affects these resources through land management practices and input, output, crop and livestock patterns. Agriculture also plays a special role in view of climate change: it is an important source of emissions (non-CO2 emissions from agriculture currently account for approximately 9% of total EU emissions), but can also sequester carbon (e.g. through reduced tillage practices) and protect carbon sinks related to agricultural land through good management practices. Without a thorough knowledge of what is produced where by whom and how through high-quality statistics, it would be very difficult to properly target agricultural, environmental and related policies. Lastly, agriculture produces close to 100% of the food we eat. The safety and security of food are non-negotiable. Detailed knowledge of production structures and supply chains is essential for rapid responses, particularly for crisis management purposes. In the global context, increasingly volatile food prices coupled with a still increasing world population present a challenge for all countries. Data on prices, yields and production structures are used in market analyses and market outlook models for policy development and management. They are also widely used by private operators to reduce asymmetries in market information. Economic dimension of agriculture Agriculture is an economic activity using natural resources such as solar energy, land, water, animals and plants, products from other industries and services such as fertilizers, pesticides, energy, know-how etc., and labour. Its outputs consist of food, feed, other animal and crop products, renewable biomass energy, and less tangible outputs such as ecosystem and socio-cultural services. These inputs and outputs are exchanged in markets regulated by price mechanisms. Key elements are e.g. the amount of production, productivity, prices of inputs and outputs, and farmers' incomes. Agricultural statistics need to measure all aspects of the economic dimension and deliver timely information on all interlinked economic aspects of agriculture. The fast evolution and rapid changes in the sector should be followed closely to provide appropriate warning signals, and flexible adjustments of data flows should be possible. Environmental dimension of agriculture Agriculture depends to a large extent on the environment, as it is part of primary production derived directly from biological processes. It consumes resources such as land, nutrients and water and provides resources such as biofuel and environmental services, thereby impacting the environment. These impacts are both detrimental (e.g. emissions) and beneficial (e.g. carbon sequestration) to the local, regional and global environment. Agricultural statistics need to depict these interlinkages correctly and give as realistic a picture of the magnitude of impacts as possible. In particular, collecting reliable statistical information on phenomena such as the two-way impact of agriculture on climate change is very important. The environmental dimension is thus likely to be one of the focus areas of agricultural statistics in the next ten years, backed up by a large number of emerging policy and data needs, such as measuring climate change and biodiversity.

Social dimension of agriculture The social dimension of agriculture is linked to the need to reduce risk and vulnerability (both environmental and economic, including food safety and food security), to living conditions of farming, and in a wider sense to the quality of life of the rural population and the viability of rural areas. Their vulnerability is a result of the mixture of environmental and economic risks. Extreme weather conditions which have become more common due to climate change and the increasing production of biofuels have increased changes in production levels and thus made the system more volatile. To reduce risks, forecasting the agricultural output is important, and thus for example early estimates of planted areas in combination with agro-meteorological data are a key issue. The social dimension also covers the living conditions of farmers and the rural population, and education and gender aspects. These facets have not been in the focus of traditional agricultural statistics, but are likely to gain in importance in the future. Agricultural statistics should thus open up towards capturing better the social dimension of agriculture. Thus, agricultural statistics cover important concepts not captured by other statistical domains. As comparable statistics from all EU Member States to address common issues in a common manner are necessary for the effective and efficient design, implementation, monitoring and evaluation of EU policies, a strong need arises for an EASS that should serve information needs linked to all aspects of agricultural activities and inform policies connected to and influencing many vitally important areas of EU and world society. The main EU policies depending on agricultural statistics are: 1.The Common Agricultural Policy (CAP), including direct payments, market measures, and Rural Development Programmes 2.The Water Framework Directive, including the Nitrates Directive and the Groundwater Directive 3.Air related Directives (National Emission Ceiling, Air Quality, and Integrated Pollution and Prevention Control) 4.Climate change policies (related to the UNFCCC Kyoto Protocol) 5.Nature conservation legislation, the Birds and Habitats Directives and several other biodiversity policy tools 6.Soil related policies, including the Soil Thematic Strategy and the Sewage Sludge Directive 7.Food safety, plant protection, animal health and animal welfare regulations 8.Regional cohesion policy In addition, the Joint Research Centre (JRC) relies heavily on agricultural statistics for a great number of research projects, models and tools for the benefit of the policies mentioned above. 1.2. A changing world, unchanging agricultural statistics The world is changing, while the EASS has so far remained rather static. Five main problem drivers have emerged: changes in world agriculture, climate change, changes in the CAP, changes in official statistics, and the unchanged EASS. Of these, the first three are largely out of Eurostat's control, changes in official statistics can only partly be influenced by Eurostat, and the EASS is under Eurostat's and the Member States' control.

Among the changes in world agriculture are changes to food safety and security, which are affected among other causes by crises such as Bovine spongiform encephalopathy (BSE); price volatility caused by different phenomena such as droughts; rapidly changing dietary habits such as Asia's growing appetite for dairy and meat; biofuels having an impact on supply chains; phosphorus shortages due to this essential, non-renewable fertiliser source running out and mostly only available in unstable regions; a still growing and increasingly less poor world population requiring more food (70% more for the world as a whole between 2005 and 2050, to then feed more than 9 billion people); rapidly increasing urbanisation, i.e. the removal of millions of people from traditional subsistence farming structures and their entry into formalised food supply chains (already in 2010, 57% of humans lived in urban areas; the Food and Agriculture Organization of the United Nations (FAO) expects this to rise to 67% until 2050), with great consequences for food consumption and food flows (e.g. more prepared meals, more food imports into supermarkets); and increasing agricultural concentration due to economic reasons (for example, between 2003 and 2013 more than 4 million, or over one in four, agricultural holdings disappeared in the EU while the total area used for agriculture remained stable) and many old farmers not finding successors (in the EU, almost a third of farms was managed by a person 65 or over, while a further quarter was managed by persons between 55 and 64, according to data from the Farm Structure Survey 2013). These phenomena are particularly important for the EU, as agricultural exports from the EU-28 amounted to 120 billion Euro in 2013 (in particular value-added products), with imports of just over 100 billion Euro (concentrated around animal feed and tropical products). Agricultural trade adds up to 6.9% of total exports and 6% of total imports of the EU, but amounts to 37% of its total trade balance, and the EU is currently negotiating several free trade agreements which will further increase trade in agri-food products. The increasing global interconnectedness of agricultural production structures, prices, yields and supply chains can thus lead to complex "butterfly effects" and calls for detailed data in this area to enable rapid crisis responses and generally more effective policy making. In the past, disregarding essential policy needs for agricultural statistics led to losses of vital information. For example, the discontinuation of most agricultural price and supply/demand balance sheet statistics in 2005 for cost-saving reasons led to a lack of data on the causes (supply/demand balance sheets) and effects (price developments) of the food price spike of 2007-2008, to the strong embarrassment of the EU. The agriculture ministers of the G20 subsequently focused on exactly these data when creating the Agricultural Market Information System (AMIS). Climate change and environmental effects will be felt more in the coming years. Food security will be impacted, with more production expected up to a certain point of warming and less afterwards. More frequent extreme weather events, such as droughts, floods and ensuing possible conflicts, are expected to lead to shortages and volatile prices. As stated above, agriculture has a strong environmental and climate change impact, and is itself strongly affected by climate change. Without a thorough knowledge of what is produced where by whom and how, it would be very difficult to target agricultural, environmental and related policy interventions (e.g. the ones identified in the 7th Environmental Action Programme) to where they are most needed. Therefore, good data on this aspect of agriculture is needed to enable environmentally sustainable action, such as a low-carbon transition in rural areas and investments in renewable energy sources, as planned in the European structural and investment funds for 2014-2020. Moreover, the links between agriculture, the environment and the climate are very complex and dynamic, and the impact of agricultural practices and products on human and animal health and welfare is strong, but not fully understood yet. Depicting all these interlinkages requires a lot from agricultural statistics. Within the EU, the CAP has recently been reformed and will continue to be reformed in response to changing national, European and global conditions and evolving policy. Some examples are the recent surge of organic food, the abolition of milk quotas, and the increasing diversity in EU agriculture. The Commission's recent experience in developing the CAP for 2014-2020 demonstrated the central role of statistics in designing, implementing, monitoring and evaluating this far-reaching policy. Reforms of the CAP should therefore also be reflected in agricultural statistics data collection. Official statistics are changing as well. New data sources such as administrative data, various registers (e.g. cattle, tax or business registers), results of research projects or Big Data have become more readily available. Information and communication technology and other new technologies enable modernised data collection. At the same time, national and EU budgets are ever more constrained, and calls to reduce the burden of data collection and production are becoming more frequent. These changes in the sources and ways of collecting and producing data require an adaptation of the framework for agricultural statistics for them to stay up to date and avoid becoming obsolete, inaccurate and too costly. This is in line with the European Statistical System's Vision 2020 to modernise official statistics, responding to similar challenges in other areas of statistics. All these developments put pressure on adapting the EASS to respond to the important growing and changing requirements and objectives. But despite many changes, streamlining, integration and modernisation efforts, the EASS has not changed enough: new and emerging data needs are not served adequately; concepts, definitions and legislation have not been fully harmonised, and cross-domain coherence and cooperation with other statistical domains is suboptimal; and the burden of data collection and production is perceived as high due to, inter alia, outdated data collection techniques, while comparable high-quality agricultural statistics from all Member States are more important than ever. 1.3. The current EASS The backbone of the current EASS is the decennial Agricultural Census and the related triennial Farm Structure Surveys (FSS), which provide reliable data on the structure of agricultural holdings in the EU, in order to assess the situation of agriculture across the EU and to monitor trends. The FSS is the only statistical source covering the widest range of farms, acting as a pivot reference for all agricultural statistics. Since 1966, the FSS has been used as a benchmark and basis (especially a sampling basis) for the other agricultural statistics, and the produced statistics are highly appreciated by policy makers (for example, FADN selection plans are based on FSS results). It is a key source for the design, implementation, monitoring and evaluation of the CAP and other EU policies such as those listed in chapter 1.1. FSS is a community-wide survey that uses the same list of characteristics and definitions in all countries. Information on individual farms is sent to Eurostat for processing and for the publication of aggregated statistics. Data are, inter alia, provided on general characteristics of the holding, a breakdown of the use of arable land by more than 40 different crops, livestock, the labour force, and other gainful activities on the farm. The implementation of the FSS is a resource-intensive operation: in 2013, more than 1.6 million holdings were interviewed throughout Europe; ranging from 1.488 (Malta) to 321.581 (Romania), by up to 3.000 field interviewers (Romania), depending on different national forms of survey organisation. The FSS is co-financed by the EU budget, amounting to over 58 million Euros for the period 2008-2013 and over 20 million Euros for the period 2014-2018. Statistics on agricultural production, including organic farming data, target those farms that make a significant contribution to total production, which can be very different across Member States. Use of administrative sources is promoted and well-developed in this domain, and modelling and forecasting are part of the statistical process. For example, crop production statistics determine the areas, production and yield of the most important crops. Animal production statistics deliver e.g. numbers of animals or the volume of milk. Agri-monetary statistics refer to market signals and therefore represent that part of production that is put on the market. Agricultural accounts cover the important agricultural industry. Coherence of the price and volume indices and of labour input is a core issue for producing accurate income indicators.

For agri-environmental indicators, a complete view is important for indicators like nutrient balance sheets. This is a relatively new area of agricultural statistics, where the methodology and data sources are mixed and often differ from those traditionally used in agricultural statistics. As the phenomena are very complex, research, scientific measurements and modelling are often the best tools to develop sound agri-environmental statistics. Eurostat's role is to receive the data, to process data and compile aggregates, to validate and assure quality (monitoring, analysing, investigating and improving data quality) and to disseminate the data on its website. Eurostat provides handbooks and guidelines, keeps methodologies and legal bases up to date, supports Member States, organises expert group meetings with all stakeholder for discussion of relevant issues, and monitors compliance with legal obligations. In addition to Member States' obligations to notify data to the Commission for market management and control purposes, there are also a number of legal reporting obligations for the Commission for which agricultural statistics serve as key input: The CAP lays down provisions for a monitoring and evaluation system in Article 110 of Regulation (EC) No 1306/2013 on the financing, management and monitoring of the common agricultural policy. This system is based on a comprehensive set of indicators which act as the starting point for a good monitoring and evaluation system. In order to obtain the data needed for these indicators, Article 110.4 specifies that "Member States shall provide the Commission with all the information necessary to permit the monitoring and evaluation of the measures concerned. As far as possible, such information shall be based on established sources of data, such as the Farm Accountancy Data Network and Eurostat." Likewise, Article 67 of Regulation (EC) No 1305/2013 on support for rural development by the European Agricultural Fund for Rural Development (EAFRD) requires the setting up of a monitoring and evaluation system based on a common set of indicators. Council Regulation (EC) No 1217/2009 of 30 November 2009 setting up a network for the collection of accountancy data on the incomes and business operation of agricultural holdings in the European Community relies heavily on data collected under the FSS for determining the field of survey and establishing the Community typology for agricultural holdings. And finally, in the context of the AMIS, the EU and those Member States that belong to the G20 are obliged to provide balance sheets (and monthly updates) for the four main crops included in the system (wheat, maize, rice and soybeans). Fulfilling its commitment to AMIS, DG AGRI submits monthly supply/demand balance sheets and publishes a Short Term Outlook report for arable crops, meats and dairy three times per year.

For a detailed list of all EASS data sets and their legal basis, see Annex IV. 1.4. Stakeholders of the EASS The main stakeholders of EU agricultural statistics are as follows: Producers of European Union agricultural statistics National Statistical Institutes (NSIs), other national authorities (ONAs), and Eurostat Survey respondents Farmers and businesses related to agriculture Users of European Union agricultural statistics Institutional users are all the EU Institutions and bodies involved at one stage or another in the design, implementation, monitoring and evaluation of agriculture related policies. More particularly; inside the Commission, DG AGRI relies very heavily on agricultural statistics notably in the context of designing, implementing, monitoring and evaluating the CAP, but also the Directorates-General (DGs) Climate Action (CLIMA), Environment (ENV), JRC, Regional and Urban Policy (REGIO), and Health and Food Safety (SANTE) use the EASS very intensively. The NSIs and international organisations such as FAO and the Organisation for Economic Co-Operation and Development (OECD) are also important institutional users. Non-institutional users include the following groups, according to their interest in agricultural statistics: 1.Users with a general interest: journalists and media; citizens

2.Users with a specific interest: national, regional and local decision makers; methodologists; marketing analysts; users interested in a particular domain/field related to agricultural statistics; farmers' associations and other non-governmental organisations; private businesses and farmers 3.Users with a research interest: scientific community – professors and researchers, universities and research institutions; consultants and researchers in governmental agencies and the private sector; experts in agricultural statistics The main quality aspects of statistics which are important for users are timeliness, relevance and comparability. As defined in the European statistics Code of Practice, timeliness is the length of time between the end of the event or phenomenon statistics describe and their availability (or time lag). Relevance means that European statistics meet the needs of users. And comparability means that European Statistics are consistent internally, over time and comparable between regions and countries and that it is possible to combine and make joint use of related data from different sources. 1.5. Performance, evaluation and lessons learnt of current EASS Eurostat carried out an ex-post evaluation of the current EASS. Its full outcome is presented in a separate staff working document. The main findings of this evaluation form the core of the agricultural statistics strategy 2020 and this impact assessment. They are sixfold: The current agricultural statistics legislation does not adequately serve new and emerging data needs because their provision is not included in the legislative acts, and the acts are not flexible and integrated enough to answer to new needs in a timely manner. The quality of the agricultural statistics is "fit for purpose" for most of the requirements of the users, thanks to the quality management approach put in place overall in the European Statistical System. The EASS is not flexible enough and is not reacting sufficiently quickly to the emerging needs, partly due to the inherent functioning of statistics, partly due to the way the regulations have been set up, but also because of a lack of budget and human resources. The data collections are not harmonised and coherent to a satisfactory degree because new data needs are emerging, legislation has been developed separately over many years, and there are partly different definitions, concepts and aims in different agricultural domains. The statistics could be produced more efficiently if the legislation is adapted so that various sources of information can be used and if Member States adopt more modern technology, but the burden and cost are appropriate considering the substantial budget of the CAP and its impact on the economic situation in agriculture, including on the individual farms as well as the need for data to monitor, evaluate and plan the CAP and the potential impact of agriculture on the environment. The burden of providing data is perceived as high because data needs are increasing, data collection is not harmonised, and resources continue to shrink at EU and national level. 1.6. Problems of the current EASS The current EASS faces three main problems. More details on the functioning of the EASS can be found in the ex-post evaluation Staff Working Document. 1.6.1. New and emerging data needs not adequately served The current EASS is not adapted to the new needs arising from changes at global level (e.g. developments in food safety and security as well as in climate change and environmental effects). At European level, policy changes of the CAP and other EU policies related to agriculture are not reflected well in the current EASS designed for previous versions of these policies, and the EASS is not flexible enough to accommodate future new data needs without a cumbersome and lengthy legislative procedure. This endangers the delivery of relevant and high-quality data. Changes in official statistics such as a greater use of administrative data, private and semi-public collections and new ways of collecting data (e.g. Big Data) are emerging and are of interest to the strategy's stakeholders due to their wish to reduce the burden of data collection, avoid overlaps, and make use of all possible sources to collect as much data as possible to satisfy their needs. As a legal constraint, the backbone of the EASS consists of data collected at farm level through the FSS, which are used in particular for monitoring structural changes in farms and farming practices. The existing legislation (Regulation (EC) No 1166/2008) only foresees surveys until 2016 and needs to be prolonged or replaced. It is crucial to provide legislation on the continued collection of farm survey statistics from 2020 (the next planned agricultural census) onwards, which would imply that the necessary legislation ought to be in place by the end of 2018 at the latest. These statistics are not only essential for the implementation of the current CAP until 2020, but also to build statistical evidence for any decision on a new CAP beyond 2020.

New data needs: The problem drivers detailed in the above paragraphs, the stakeholder consultations, the evaluation described in chapter 1.5. and different analyses over the years have resulted in several main new and emerging data needs for the EASS, mainly centred around environmental, climate change and economic data. These needs and the reasons for them are further detailed in Annex VI. Flexibility: NSIs wish to omit low-prevalence data from the collection process and be allowed to use as much as possible new data sources and burden-lowering systems to increase efficiency. This is currently not foreseen explicitly enough in the legislation and methodologies. Integration and interlinking: Stakeholders have expressed the view that there is a strong need to develop agricultural statistics in cooperation with other statistical domains. For example, at the DGAS Meeting in summer 2015, representatives stated that the integration and links of agricultural statistics with forestry, land use/cover and environmental statistics should be improved. Similarly, agricultural outputs should be better linked to the uses they are put to in order to get a better picture of the food chain. Countries also want to perform the agricultural census 2020, a global exercise, by using administrative registers and have asked for enhanced legal support in accessing individual administrative data. This would reduce the burden and costs of data collection, which is a prime concern. Similarly, the implementation of the data sharing obligations set in Article 17 of the Inspire Directive 2007/2/EC should enable Member State public authorities to access spatial data sets. Recently, grants have been awarded to investigate possibilities of using administrative data for agricultural statistics. Here, identifying discrepancies and differences e.g. in definitions and figures and harmonising them is important to increase integration and reduce overlaps between statistical and administrative data sources. Work continues in this area. A Eurostat survey of Member States on the use of administrative registers in agricultural statistics in 2014 revealed that of 19 countries replying, 88 different administrative sources are already used for agricultural statistics, e.g. to replace the FSS survey for some characteristics and/or to build or update the survey frame, pre-fill answers, impute non-responses, and validate the surveys. Reasons for not using administrative sources are incoherent concepts and definitions, different coverage, linking problems, problems of data quality, completeness, misclassification or timeliness, or risks of source instability. About a quarter of FSS 2013 data came from sources other than statistical questionnaires, highlighting the growing importance of non-traditional sources such as administrative data for statistics production. The need and potential for integration and interlinking is therefore high, and these potentials should be further investigated and deepened. A study on data needs for agri-environmental indicators (AEIs) showed that there is much to gain from streamlining data requirements for policy reporting, prioritising key AEIs, and harmonising data collection, processing and reporting chains. Respondents to the open public consultation agree that data needs could be better served by integration and harmonisation of European Union agricultural statistics, which would also improve consistency and coherence and help to reduce the burden of data collection. This was already noted in the United Nations Economic Commission for Europe (UNECE) Review of Agricultural Statistics 2008, which also found that FADN and the Integrated Administration and Control System (IACS) could be better linked to the FSS to allow for more complex analyses. Lastly, a mapping of agricultural statistics data flows with the policy DGs AGRI, CLIMA, ENV, SANTE and JRC in 2014 showed many overlaps between FSS, crop survey, livestock, FADN, permanent crops and Economic Accounts for Agriculture (EAA) data, also highlighting several integration possibilities. The surveys were chosen because they relate to farm level information, and they were compared on various characteristics such as reference periods, coverage, scope, precision, thresholds etc., and on the purpose and the main clients and users of the data collection. In all, there are 198 FSS characteristics; 35 crop survey characteristics overlap with it, 16 in livestock, 28 FADN categories partially overlap, and 8 permanent crop characteristics partially overlap. 1.6.2. Data collections not sufficiently harmonised and coherent This problem has been evidenced in the evaluation, in various stakeholder consultations and also arises out of the fact that the EASS has been developed since the early 1950s, with partly different definitions and concepts in different agricultural areas, continuously changing policy needs, a lengthy legislative process with many actors, and other constraints preventing a complete redesign and harmonised integration of the running system. New data needs also pose harmonisation problems. Inflexibility and incoherence The UNECE Review of Agricultural Statistics 2008 found that EU legislation on agricultural statistics possesses well-developed, but inflexible instruments, preventing active and fast integration of new developments in the data collection process. Similarly, the CPSA Seminar 2009 analysed that among others, land use statistics, crop and livestock data suffer from visible and critical data incoherence, and listed possible improvement actions. Lastly, the detailed results of the Eurostat User Satisfaction Survey 2014, a wide consultation open to the general public, showed that several users ask for a more coherent methodology and data basis between Member States. Users appreciate being able to compare data at EU level in one place instead of having to download data from 28 national statistical institutes, but said that more could be done to increase data harmonisation to increase the value. Harmonising concepts and definitions Harmonising concepts, definitions and terminology, while not easily quantifiable, is self-evidently a fundamental task to improve efficiency and achieve better integration and comparability of data collections. Harmonisation should for example be achieved between FSS, FADN and IACS (e.g. farmers, agricultural area, grazing land...). A common scope and shared technical and methodological documentation would also be helpful. In addition to collection from agricultural holdings, data can also be collected from up- and downstream enterprises, and from intermediate units, i.e. units producing certain services in agriculture. Common definitions would enable easier sharing and comparing of data. In general, agriculture needs to be defined better than before as it can be understood in many different, continuously evolving ways (e.g. laboratory-produced meat, insects for food etc.). Data providers and users expressed a wish to increase harmonisation and coherence in order to improve data comparability and usefulness and be able to do more with fewer resources at the CPSA meeting in November 2013. This need has been echoed by other users such as the research community for years. Among other recommendations, Eurostat's Internal Audit Capability (IAC) stated in its 2013 audit on statistical processes of agriculture statistics that voluntary data collections should be formalised and all variables should be applied consistently by Member States. And the Eurostat User Satisfaction Survey in 2014 revealed that only about half of respondents rated the comparability of European agriculture and fishery statistics as "good" or "very good", below the Eurostat average for each criterion, a finding repeated in 2015; key users, i.e. Commission services, other EU users, international organisations and political organisations rated the comparability even a bit worse. Detailed 2015 results revealed that users see missing, non-detailed and non-integrated data, a lack of timeliness, inconsistent time series due to methodological changes, and different thresholds not allowing comparing Eurostat data with national data as the most pressing problems. 1.6.3. Burden of providing data perceived as too high The burden of providing data for the EASS is perceived as high because while the number of variables is already very high, data needs are still increasing, data collection is not harmonised and coherent, and resources continue to shrink at EU and national level. Agricultural statistics are subject to budget cuts in Member States and are frequently not considered to have a high priority, possibly due to agricultural policy mostly being out of the hands of national governments and decided at EU level. Therefore, reducing the costs and burdens of the EASS and increasing its efficiency (see 1.5.) is important to safeguard its effective operation with high data quality. Member States have stated repeatedly, for example at the May 2014 ESSC meeting, that the burden and costs need to be taken into account when formulating new needs; any new variable's utility should be investigated and its precision and frequency clearly determined in order not to overburden data providers and data producers. This is especially important as the needs for relevant and reliable statistics are evolving fast and increasingly pressing. The Member States last reiterated the point that the burden and costs should be reduced or at least not increased at the 2015 DGAS meeting, the joint FSS/Crops Working Group Meetings in October 2015, and at the ESSC Meeting in November 2015. Thoroughly assessing the costs and benefits and actual needs and uses for new data against their administrative and operational burden was seen as extremely important by data producers. This is also evidenced by the evaluation described in chapter 1.5. However, data users consider agricultural statistics essential for policy development and management, so a good balance needs to be found. The current structures of the applied agricultural surveys and their data collection are complex and necessitate large operations in the Member States. Therefore, flexibility and coherence are needed to reduce the additional burden of collecting new data. A thorough evaluation of the burden of reporting FSS variables was conducted in 2011, finding that the burden ranged from moderate to very high depending on the country and the class of variables. While only a few countries saw the burden generally as high, certain characteristics such as on labour and other gainful activities of farm holders were seen as very burdensome by most Member States, indicating possibilities for improvement. In general, the burden of the FSS was seen as average, but not light by most countries. These findings deepened those of a burden-assessment exercise in 2010 based on a questionnaire sent to Member States to assess the production costs and response burden of EU basic legal acts in several statistical fields, among them statistics on agriculture. There, the FSS was seen as having a high production cost and response burden, whereas other agricultural statistics such as crop and livestock data had at most a medium cost and burden. Crop, livestock and meat, and milk and milk products data also served to cover national data needs in almost all Member States, FSS, pesticide, orchard and vineyard data in more than half of them, and EAA data in fewer than half. As the FSS is the keystone of the EASS, its burden should therefore be lowered to ensure its continuation and improvement. 1.6.4. Evolution of the problems

Agriculture will continue to change, and climate change and other environmental effects will persist, with the CAP and other EU policies changing in reaction to these developments and to political, economic and social priorities. This creates new data needs that the EASS must adapt to or risk not being continued. The latter would directly impact EU policies that depend on agricultural statistics. The direct and indirect consequences would be severe for the EU's and its Member States' priorities and goals, such as decreased food security, less effective mitigation of climate change, and a waste of CAP funds. Technical and organisational progress and societal changes such as increasing survey non-response will continue to influence official statistics, increasing its relative burden and decreasing the usefulness of unadapted statistical collections and collection methods. This could affect the EASS' continued funding, if it were seen not to deliver what it should, and its ability to respond to new and evolving data needs. The longer these problems remain unsolved, the more urgent and far-reaching their effects will become, with more and more severe consequences for the EU and its Member States' policy delivery, reputation and position in a highly dynamic global order. 2. NEED FOR EU ACTION Legal basis European Union statistics and the right for the European Commission to propose actions have their basis in Article 338 of the Treaty on the Functioning of the European Union (TFEU). EU-level action is further justified for reasons of efficiency, harmonisation and common output as mentioned in the current legal basis of European Union statistics, Regulation (EC) No 223/2009 on European Statistics. According to the statistical principles listed in the Regulation, figures provided must be of high quality, coherent, comparable over time and between data sets and countries, the production processes must be transparent, the response burden low and the costs reasonable. Added value of action at EU level Statistics provide an essential infrastructure for the sound and efficient functioning of democracy and a modern economy, so too for the European Union. Official statistics are a cornerstone of trust into EU institutions and procedures. Therefore, the information must be reliable, timely and independent of political influence, and provided in a convenient form for users. Furthermore, its preparation should not impose an excessive burden on data providers, and its collection must be undertaken in accordance with the principles of subsidiarity and proportionality. EU legislation facilitates the collection of data at the same level of detail in all Member States. It imposes the application of common standards, definitions and methodologies which, in addition to producing comparable results at the service of EU policies, improve efficiency, timeliness, reliability and harmonisation, or in short, increase data quality. Specific need for action at EU level in agricultural statistics As described in chapter 1, one of the major common European Union policies, the CAP, is inherently based on comparable, harmonised, high-quality data which can only be ensured by action at EU level. This consideration equally applies to the other policies listed in chapter 1 that depend on European agricultural statistics. Agricultural statistics also have a long tradition in Member States and in the EU, leading to valuable time series whose continuation would be advantageous to monitor and evaluate policies and track trends such as the evolution of the number of agricultural holdings. Lastly, the context of EU agricultural statistics as explained in chapter 1.1. and the changes in global agriculture as described in chapter 1.2. call for harmonisation and common solutions, as neither climate change nor global trade flows or food security issues stop at national borders. The Commission should therefore steer the EASS, within the larger framework of the European Statistical System (ESS), into a joint commitment to develop, produce and preserve the highest quality standards for European agricultural statistics. Subsidiarity and proportionality The scale of the actions included in the strategy justifies an EU initiative since the objective of the proposed action, namely the improvement of EU agricultural statistics, cannot be sufficiently achieved by the Member States and is therefore better achieved at EU level. Only the Commission can coordinate the necessary harmonisation of statistical information at EU level, while Member States will handle their national data collections in the way they see fit. Member States agree with this approach, as evidenced over the years, for example at the November 2013 CPSA meeting, when discussing the agricultural statistics work programme for 2015 and following years. Representatives of most Member States intervened, stating the importance of creating a more coherent and simplified legal framework and even calling for an extension of the legal framework to cover some high priority data that are currently collected only on a voluntary basis. The proposal also complies with the proportionality principle as the proposed strategy confines itself to the minimum required to achieve its objectives and does not go beyond what is necessary for this purpose. All of the above leads to the conclusion that action and legislation for a renewed agricultural statistics system at EU level is in the interest of both the European Union and the Member States. The added value of EU action is therefore that it allows for the best way of improvement of the statistical activities on EU policies related to agriculture. 3. OBJECTIVES The context of European Union agricultural statistics and the changes in world agriculture as explained in chapters 1.1. and 1.2., the current setup of the EASS, its stakeholders and their needs, and the evaluation of the system as outlined in chapters 1.3., 1.4., 1.5. and Annex II, and most of all the three main problems of the current EASS as described in chapter 1.6. have led Eurostat to formulate the strategy for agricultural statistics for 2020 and beyond, in order to develop a future European Agricultural Statistics System (EASS). Context of the future EASS The initiative aims at creating a more modern, flexible, coherent, efficient, cost-effective and lighter system for providing relevant and appropriate official EU agricultural statistical data of high quality that can interact with and be linked to other components of the ESS. In this policy context, Eurostat plays a central role. Eurostat has already included in the ESS Vision 2020 the development of statistical legislation covering broader areas, drawing upon multiple sources and providing for flexibility in order to address users' needs. The Commission envisages adapting agricultural statistics to the overall objective of modern statistics through the strategy for agricultural statistics. Quality statistics to support European policies are also the main driver of the European Statistical Programme 2013-2017. Environmental and agricultural statistics are one of the three pillars of statistical production under this programme. Among the relevant objectives of the programme is "the review and simplification of the agricultural data collection in line with the Common Agricultural Policy (CAP) review post-2013 and the redesign of the agricultural data collection processes, in particular with the objective of improving the quality and timeliness of the provided data". This initiative implements that objective.

The future EASS can also contribute to at least four of the ten priorities of the Juncker Commission, namely "1. A new boost for jobs, growth and investment", "3. A resilient energy union with a forward-looking climate change policy", 4. “A Deeper and Fairer Internal Market with a Strengthened Industrial Base” and "9. A stronger global actor", by providing better data for job, growth, investment, prevention and mitigation policies in agriculture, climate change, bio-energy and environmental actions, and a deeper understanding of global food flows, developments and risks, respectively. Agricultural statistics may also be useful to other EU or Member State priorities affecting or affected by agriculture and rural development. Finally, this initiative is also part of the Regulatory Fitness and Performance Programme (REFIT), aiming to fulfil its objectives of simplification, cost-efficiency and burden reduction by codifying amendments and voluntary agreements, reducing the number of basic legislative acts in the area of agricultural statistics, eliminating possibly no longer needed data sets, and providing more high-quality data while lowering the burden on respondents. General and specific objectives General objective:

Produce high-quality European agricultural statistics according to Article 338 TFEU. Specific objectives: Table 1: Specific objectives and problems addressed. Source: Eurostat Objective Addressing Problems Produce high-quality statistics that meet users' needs efficiently and effectively "New and emerging data needs not adequately served" "Burden of providing data perceived as too high" Increase the flexibility and reaction speed of the agricultural statistics system Improve the integration between agricultural, forestry, land use and environmental statistics Develop a responsive and responsible governance structure for agricultural statistics Improve the harmonisation and coherence of European agricultural statistics "New and emerging data needs not adequately served " "Data collections not sufficiently harmonised and coherent" "Burden of providing data perceived as too high" Produce more statistics while lowering the burden on respondents by exploring alternative data sources and possibilities of efficiency improvement "New and emerging data needs not adequately served " "Burden of providing data perceived as too high"



Stakeholder benefits The initiative aims to benefit the main EASS stakeholders in the following manner: Data users, such as the policy DGs of the European Commission, international organisations and others, by providing them with more and better, more flexible and integrated, and more harmonised and coherent agricultural statistics data to serve their policy making, monitoring, evaluation, research and other needs; as they have an interest in the policy, institutional users have a stake in the scope of agricultural statistics and in limiting the burden on businesses, whereas general, specific and research users have an interest in the scope and dissemination of agricultural statistics. Data producers such as National Statistical Institutes, Other National Authorities and Eurostat, as the administrative bodies in Member States and at EU level that carry out the statistical surveys and other data collection, production and dissemination tasks: more and better, more flexible and integrated, and more harmonised and coherent agricultural statistics produced in more efficient and alternative ways are planned to result in better data quality, better resource use, and leaner processes; as they will have to implement the policy, they have an interest in keeping agricultural statistics production costs at the same level or lowering them, in improving their production processes and outputs, and in receiving EU funding for data collection. Data respondents such as farmers and agricultural businesses: more and better, more flexible and integrated, and more harmonised and coherent agricultural statistics produced in more efficient and alternative ways are planned to improve data provision while simplifying data collection and reducing its burden; as they are affected by the policy, they have an interest in lowering response costs and burdens, and in maintaining their EU funding, which indirectly depends on high-quality statistics. 3.1. Meeting data needs Produce high-quality statistics that meet users' needs efficiently and effectively The EASS needs to deliver the statistical knowledge base needed for the design, implementation, monitoring and evaluation of the CAP, environmental policy and climate change policies, and other important EU and Member State policies. The effectiveness of the EASS is first and foremost measured against this requirement. The EASS has to be involved in the data needs identification and prioritizing process in order to safeguard the efficient functioning of these policies. For the CAP 2014-2020, a monitoring and evaluation framework has been developed with indicators which are largely based on statistical data. Where data gaps exist for these indicators, they need to be filled as a matter of priority. In particular, data needs related to soil quality, water, fertiliser and pesticide use should be fulfilled. Agri-environmental indicators are another example; they are currently under development to meet corresponding data needs. They are supposed to give information on the incorporation of environmental measures in agricultural policies and on the relation between agriculture and the environment. The aim is to use already available data from different sources, but there is potentially a need to start new surveys. At the moment, statistical legislation in this area only exists for pesticides while some other indicators are collected under administrative legislation.

The scope of agricultural statistics could be widened to include aspects of forestry, fisheries, land cover and use, and water use, as the related economic, social, and environmental issues faced by policy makers relate to all areas. Because of the fundamental relationship between agriculture and land, the geospatial aspect of land is an important element of the scope of agricultural statistics. Furthermore, the statistical data within the EASS must be produced and transmitted to Eurostat in an efficient manner allowing a reduction in the different steps of the process without reducing data quality. An important part of this is validation, i.e. the processes used to establish whether data conforms to specific criteria. The way agricultural statistics have developed during the years has not made it possible yet to streamline validation in the data transmission to Eurostat, but future common elements in agricultural statistics would reduce inconsistencies between domains and make it easier for users to understand the reasons for apparent discrepancies between data sets, while at the same time reducing the burden for NSIs, as the same terminology, definitions, scope etc. would be used. Increase the flexibility and reaction speed of the agricultural statistics system An increase of flexibility would allow an easier introduction of new needs, statistics and methodological approaches in order to better support the policy-making and decision processes. The EASS must be more agile and responsive to user needs, which evolve in line with policy changes. Key variables have been identified during the long history of the EASS, and the resulting time series need to be preserved. Journalists, NGOs, researchers in this complex field, all need to access the information they require in different ways. International cooperation is also important; the EASS must collaborate with and contribute to the developments of especially the statistical activities of FAO and OECD. The exact form of data collection will be left fully for Member State authorities to decide in a flexible manner so that there is ample room for modern electronic data collection, treatment, storage, transmission and dissemination systems. To facilitate this, the initiative is formulated in a technology-neutral way. EU statistical processes are already largely digitised; further on, even fundamental improvements of existing systems are possible and will be encouraged as long as the core legal obligations of data collection, processing, transmission, storage and dissemination remain fulfilled. Improve the integration between agricultural, forestry, land use, environmental and other statistics The EASS needs to interact with and be linked to several other statistical domains. Agriculture is a part of primary production together with forestry, fishing and hunting. The statistics on primary production would benefit from being considered as one statistical system. The primary production is based on land and water, so land use and cover statistics and primary production statistics should fit together seamlessly. These statistical components should be analysed together, and future statistical systems should clearly define their relations to each other. Agricultural practices have a major impact on the environment and climate change. The statistics on agricultural production, production methods and land use are crucial for several types of environmental statistics (e.g. water and air quality). The impact of crop and animal production (e.g. ruminants, leaking nutrients) on the carbon cycle is very important, but not fully understood yet. Agricultural products and by-products are also becoming increasingly important as a bio-energy source. The EASS therefore also needs to be connected to environmental statistics, indicators and accounts, and energy statistics. For example, rural development policy can be used to introduce buffer strips alongside water bodies and invest in water storage technologies. More integrated data would help to align different priorities better, e.g. to save water instead of just fulfilling lower-level goals of different policies, by increasing cooperation between agriculture ministries and water management authorities. Agricultural statistics should also open up towards cross-domain collaboration and compatibility with social statistics to improve data collection in the social dimension of agricultural statistics. At present, the FSS covers a wide scope of holdings, a substantial number of which produce mainly for their own consumption. This kind of information is important for describing both the social dimension of agricultural production and the reliance of many households on subsistence farming. Currently, the data needs in this area are not fully developed, as until now subsistence households have been a part of the FSS. The aim is to use, where possible and feasible, already available data from social statistics to avoid duplication of efforts, challenging the silo approach where appropriate, but without creating additional burdens and without losing vital policy-relevant information by "moving" small holdings from agricultural statistics to social statistics. Analogously, the need for detailed information on the workforce in farms could be fulfilled by seeking harmonisation of agricultural statistics with labour market statistics (provided that these cover a sufficiently high number of farmers and agricultural workers) and economic statistics. Agricultural prices including food price chains and other data (e.g. processing, transport and trade data) should also be analysed as to their potential for integration with agricultural statistics to get a broader picture of the economic dimension of agriculture and collect more food security information. These possible linkages between agricultural statistics and other statistical domains need to be carefully analysed to find the optimal way of structuring and producing European statistics. This will require adaptations of existing ESS statistical surveys to better take into account the overall data needs in order to reach a global reduction of the burden of statistics. The introduction of a unique identifier for agricultural holdings would make it possible to combine data from administrative registers and other sources and from various statistical surveys with each other, thus reducing the burden on respondents while increasing the available data. This would make it possible to introduce a building block approach in agricultural statistics, which would allow collecting data in the manner best suited for the purpose, and reusing it by combining it with other data sources. The identifier should be the same in all agricultural statistics, and should ideally also be used in administrative applications and be consistent with business statistics in order to allow for synergies. Develop a responsive and responsible governance structure for agricultural statistics Good governance is crucial for safeguarding an adequate knowledge base for sound agricultural policy making at national and EU level. A regular periodic performance assessment of the EASS is therefore important to guarantee its fitness for purpose. The governance system should be responsible for self-assessments, but cross-domain peer-reviews and external expertise are also useful. The EASS requires a pro-active, broad-minded and efficient governance structure, which represents, integrates and balances the interests of data users and data providers in the ESS context. Pro-activeness and reactiveness are important features, as agricultural policy is evolving and the system needs to be adapted in order to stay relevant. The governance needs to support the multi-dimensional and diverse reality of agriculture and agricultural statistics. The governance vision also has to be broad enough to enable the best possible balancing between various statistical domains to optimise the trade-offs, permeability and overall efficiency of the ESS. Lastly, the governance system should allow for capturing changing user needs and adapting legal aspects efficiently and quickly, include flexible modular solutions, and provide procedures and tools for assessment, monitoring and evaluation. 3.2. Coherence and integration Improve the harmonisation and coherence of European agricultural statistics In a period of increased demand for data for policy making and reduced resources, coherence and harmonisation are some of the best tools available to safeguard the continuity of high-quality statistical data at reasonable cost. Thus, the EASS needs a solid shared basis of common definitions and concepts for linking the existing statistical domains, especially as the present definition of an agricultural holding is linked to the production of agricultural products. Therefore, the range applied in agricultural statistics is very wide, from households producing some vegetables in their kitchen gardens to units with thousands of hectares.

Different thresholds are applied in the Member States , with some including virtually all rural households with bigger kitchen gardens, while others exclude the smallest holdings. This is accepted in the present legislation. It will be necessary to analyse what kind of statistical units should be covered by agricultural statistics, and whether the coverage should be different depending on the use. This approach should be described in a common framework, and then reflected in the statistical regulations. It is also important to share validation rules and practices, quality assurance, reporting and dissemination principles in line with the ESS Vision 2020. Currently, different definitions, overlaps and gaps create an unnecessary burden and problems for stakeholders. Another important action in this area is to re-use as much as possible existing administrative and other data. IACS, which is the most important system for the management and control of payments to farmers under the CAP, is an administrative register that many NSIs use as a source of data for surveys or for validation purposes. Eurostat and DG AGRI have cooperated in improving the use of IACS by organising a task force with representatives from several Member States in order to identify actions to simplify the use of this register. The Task Force concluded i.a. that statistical needs should be taken into account in the design phase of any national or European administrative database. In addition, IACS is part of several pilot studies to explore using administrative data for agricultural statistics. These pilots are run in the framework of ESS.VIP.BUS.ADMIN, a project on administrative data sources that implements one of the five key areas of the ESS Vision 2020, "New data sources". A separate Eurostat-DG AGRI task force on linkages between administrative data and statistics concluded in 2013 that there is scope for increasing the use of administrative data in agricultural statistics, provided that issues related to the harmonisation of units, definitions, classifications and timing can be resolved and that different objectives of data collections are taken into consideration (representativeness and completeness for statistics; legal compliance for administrative data related to the CAP). Slight differences in definitions or a lack of exchange across different players (statistical departments; paying agencies; ministries; regional/local authorities etc.) provide a barrier that needs to be overcome. Last but not least, IT systems should be adapted to link different data bases. The principle of "collect once, use many times" should apply to any statistical data collection, with the aim of not asking one farmer the same question more than once. In general, it seems that for some countries there could be a cost-saving, feasible option of providing data from registers instead of conducting a separate data collection, while this would be necessary for others. A part of the statistical surveys could thus be replaced by other data sources in an efficient manner if the related farms are well targeted. 3.3. Burden reduction Produce more statistics while lowering the burden on respondents by exploring alternative data sources and possibilities of efficiency improvement The variables, in particular those identified in previous burden assessment exercises as the most difficult (see chapters 1.5. and 1.6.3.), need to be looked at in order to simplify data collection, eliminate possibly no longer needed data sets in accordance with the REFIT objectives of simplification, cost-efficiency and burden reduction, and improve the reliability of the results. There is also a need to reduce the observed population, as surveying small farms is as expensive as large farms, while not all information is needed for both types of farms. The issue and definition of thresholds need to be discussed further (use of economic and/or physical criteria for defining thresholds, possibility of applying different approaches for different countries to address different agricultural realities in Member States etc.) Information and communication technology and other new technologies (e.g. Big Data) should also be integrated into the future EASS. There is potential for an increased use of information technology not only in data collection and processing, but also in dissemination. Technologies such as computer-assisted personal interviewing can lead to improvements in data quality and reduce the time lag between data collection and data analysis. A key requirement for this is that unique identifiers are introduced. Only then can data warehouses or similar databases be set up to ensure easy combination of data to enable greater efficiency, a higher flexibility for Member States to choose how data are collected, higher speed, and a lower burden on respondents. Integrated business processes comprising e.g. multi-source/cross-domain data integration, a common infrastructure and tools for data processing, exchange and dissemination, and standardised quality assessment should be promoted. Best practices should be applied across Member States. In addition, the effectiveness (fitness-for-purpose) and efficiency of data collection methods need to be assessed against the data needs and quality criteria. This means identifying whether the information needed can be provided by using already existing data in models, as bases for estimates, or if expert estimations can be used. In case data collection from farms is required, are there already existing surveys that can be easily adapted to take on board new needs, or are non-statistical sources available? Are the phenomena to be surveyed changing quickly or slowly? And are there possibilities to decrease the frequency or geographical level to save resources? These and other questions need to be answered so that data collection can be designed optimally. Some other ways to reduce the burden of data collection in agricultural statistics are, among others: different precision or frequency requirements and/or coverage for different survey modules, non-mandatory interlinking between modules, better integration following the principle "collect once, use many times", targeted sample surveys, and a system of core census surveys and modules with sample surveys of affected units, at a higher threshold and with less precision. 4. OPTIONS Taking everything described previously into account, Eurostat has developed four possible policy options to achieve the objectives detailed in chapter 3, with the main criteria of legal feasibility, technical feasibility, previous policy choices, coherence with other EU policy objectives, effectiveness and efficiency, proportionality, political feasibility, relevance, and strategic viewpoints: 1.Baseline – no EU action on structural data of agriculture 2.Prolongation of the FSS Regulation (EC) No 1166/2008 3.Single new legal framework for the whole sector of agricultural statistics 4.Two-step integration of agricultural statistics Statistical data are either produced in some way in collection, production and dissemination systems or not produced at all. Therefore, substantial "halfway" or intermediate options are not possible in this area, but slightly different implementations of the four options above are of course conceivable. They would however not be materially different in their aims and impacts from the four options above, so only those four have been analysed further.

4.1. Baseline – No EU action on structural data of agriculture If no EU action is taken, the result would be that the current Regulation (EC) No 1166/2008 will expire and the collection of structural data on agriculture will remain at the discretion of Member States. These data are considered to be a fundamentally important part of the EASS. The other agricultural statistics legislation (see Annex V) would remain in place as it is today, but with less assurance of quality as an agricultural census (based on Regulation (EC) No 1166/2008) is often used to update farm registers that are used for stratification in sample surveys. 4.2. Prolongation of the FSS Regulation (EC) No 1166/2008 This option is the renewal of the current FSS Regulation (EC) No 1166/2008 which expires by 2018. This would mean that the current system, in force since 1966, would continue without integrating changes. The other agricultural statistics legislation would remain in place, and the status quo would continue. 4.3. Single new legal framework for the whole sector of agricultural statistics This option would imply the creation of a completely new legal framework for all EU agricultural statistics. All legislation related to agricultural statistics would be integrated into one single framework regulation. The basic regulation would include common objectives and definitions (periodicity, scope, precision etc.) and would also specify, in general, the required statistical outputs. Implementing acts would define technical elements necessary for a harmonised implementation of the basic act, and delegated powers would be given to the European Commission to amend non-essential elements of the basic act in order to ensure the flexibility needed to respond to changing policy and data needs. Changes would be managed by acts subject to implementing measures defining methodologies with objective criteria to assess the change in burden entailed, in order to safeguard the burden reduction of the proposed new system, prevent the introduction of unexpected costs, and preserve subsidiarity. The framework regulation(s) foreseen for options 3 (and 4) would consist of a core set of variables fulfilling all requirements (essential structural variables, e.g. farm size and land use), which is asked every time that a survey is carried out, either as a census or as a sample survey, on farms above a minimum threshold; modules that are subsamples of the core and focus on certain thematic aspects from the current list of variables that are needed either at lower frequency, for smaller samples, or at different thresholds than the core, but which can be directly linked to the core survey results and shall always be conducted together with the core; and flexible ad-hoc satellites that focus on special topics that are not traditionally part of the EASS, i.e. surveys which aim to cover the variables that will be collected according to new and emerging data needs. Their exact contents would be determined prior to their implementation. These surveys are not planned to be carried out at a fixed frequency but may be repeated if needed. This system of core, module and satellite surveys was already the preferred outcome of a task force of interested stakeholders set up in 2011 to support Eurostat in identifying the best ways of creating an efficient system for the collection of structural, production and related data for agriculture at European level, and defining the best overall survey design in regard to organisation, frequency and sampling. An agricultural census is needed because it is the only way to get updates on the full agricultural population in the EU, so small, not market-oriented holdings should be included in the census and sample surveys, even if surveyed for less or different information. The census is the only data collection instrument that produces statistical information on farms at the lowest geographical level, and is therefore an essential source of information for governments and decision-makers. FAO also expects its member countries to follow the standards, concepts and definitions guidelines of its World Programme for the Census of Agriculture 2020 (WCA 2020) in order to achieve harmonised and internationally comparable results and allow countries to benchmark their performance against other countries, among other advantages. This and other international obligations are another reason for the need for an agricultural census. To link the farm information with other elements of agricultural statistics, Member States should be allowed and able to use data collected for production statistics, permanent crops statistics and organic farming statistics in the system of farm surveys. For this to work, definitions need to be identical, and farm identification numbers should be introduced. Such a unique farm identifier would also enable linking holdings covered by the FADN with holdings covered by the FSS. In Eurostat survey years, all structural information would thus have to be collected only once and could be shared with FADN data collectors at national level. This could also address the need to add additional variables to the FADN by transforming them into satellite surveys in the new EASS. Member States should also be encouraged to use administrative data sources and to establish farm registers, and efforts should be made to harmonise definitions and reference periods across data sources. Lastly, new thresholds, paired with special sample surveys on farm holdings below the thresholds in order to ensure sufficient coverage, and other actions are planned to be introduced to reduce the burden and cost of data collection mainly in countries with many small holdings (see 5.1. and 5.2.) 4.4. Two-step integration of agricultural statistics This option of a two-step integration of agricultural statistics would safeguard the continuation and modernisation of structural statistics on agriculture. Two new framework regulations would be introduced stepwise: an integrated farm statistics (IFS) regulation to be in place before the end of 2018 to ensure the agricultural census in 2020, and another framework regulation on statistics on agricultural input and output (SAIO) to be adopted and in place before 2022. This would allow achieving the benefits of option 3 while greatly reducing the timing challenge. Otherwise, this option would follow the structure of option 3. In order to safeguard the coherence between farm and aggregated data, a common scope would be integrated into both regulations, and shared technical and methodological documentation would be created. Together, both framework regulations would cover all aspects of the new statistical programme for agriculture. Step 1: Framework Regulation for Integrated Farm Statistics (IFS) The IFS would be based on the idea of having a limited core set of variables to be surveyed as a census in 2020 and as a sample survey in 2023 and 2026, several modules to be surveyed at different frequencies than the core variables and with lower quality requirements, and ad-hoc surveys that would be flexible and easier to change to adapt to changing needs, but also carried out at different frequencies and with lower quality requirements. This framework regulation would not only provide a legal basis for the structural data on farms, but also replace the Permanent crop statistics regulation (Regulation (EC) No 1337/2011; quinquennial orchards and vineyards surveys will be integrated as modules, as these surveys are in essence structural). In addition, parts of agri-environmental statistics presently not under legislation, where data need to be collected at farm level (such as irrigation, manure or nutrient use), would be integrated into this framework regulation. Thus, the current long list of compulsory variables in one single survey would be replaced with a new and flexible approach. All data are foreseen to be transmitted to Eurostat as micro-data. In order to make the use of administrative data easier, the inclusion of a compulsory register, fully coherent with business registers, and containing market oriented farms is also foreseen.

Step 2: Framework Regulation for Statistics on Agricultural Input/Output (SAIO) Another Framework Regulation for Statistics on Agricultural Input/Output (SAIO) is foreseen, consisting of aggregated crop and animal production statistics, agri-environmental statistics on fertilisers, nutrient balances and pesticides, and potentially agricultural price statistics. All these data are aggregated statistics with no micro data transmission to Eurostat, unlike the IFS. They deal with agricultural inputs (prices of seeds, pesticides, feed etc.) and outputs (crop and animal production and prices). The data can be collected from farms, administrative sources, intermediaries (dairies etc.), wholesale entities and market organisations, and often include a certain amount of expert estimations. The introduction of a coherent framework would notably allow for the development of an integrated legal architecture, as well as better planning of the surveys, and would allow combining databases into warehouses as well as achieving better coherence. As the Economic Accounts for Agriculture (EAA) are considered satellite accounts of the national accounts and macro-economic by nature, their integration into the new framework regulations is not being proposed, but to remain subject to independent legislation. 4.5. Early discarded options The CAP, one of the major common EU policies, is fully harmonised and therefore requires comparable data, which can only be established by statistical legislation at EU level (see chapter 2). Voluntary data collection is inherently less stable, enforceable, comparable and reliable than regulated, harmonised collection by national authorities and would constitute a major setback to legal, organisational, technical and financial systems that already exist for several decades within the EU. In addition, there would be a severe political, budget and security risk if the CAP, one of the EU's main policies, depended on data collected by unstable and unreliable means. In such a scenario, the evidence base of the CAP would be undermined, with negative consequences for policy development and implementation. That decision, if it were taken, should be a political one, and not one dictated by the scarcity of data. A scenario where the EU would discontinue its activities in agricultural statistics was therefore immediately discarded, and no options of actively abolishing EASS legislation have been considered beyond letting the FSS Regulation expire as in the baseline option 1. Eurostat considered the possibility of continuing the current legislative structure with separate legal acts per domain, but abandoned that option at an early stage, as the evaluation of the current EASS shows that the existing legislation is not fulfilling important data needs, lacks consistency and coherence and is perceived as too burdensome, all aspects of major importance. Various scenarios on different possibilities of grouping the statistical domains were discussed, but none of them would have given the necessary added value expected. Thus, improving the EASS by creating legislation that covers a larger area was seen as the soundest way to reach the objectives listed above and was further expanded on in the options analysed further. Considering the known structure of agricultural holdings in the EU, very few of which are large enterprises for a variety of reasons, an exemption for SMEs is not possible, as most data necessary for policy purposes would then be lost. The number of micro-enterprises in agriculture is very large, and for that reason appropriate information on these units is required. An adapted regime for very small units will be considered via legislative thresholds (see also 5.1. and 5.2.) 4.6. Problem and solution tree The problem drivers, the problems, the objectives and the options of the agricultural statistics strategy 2020 as well as the relations between these elements can now be visualised to enhance understanding. Figure 1: Problem drivers, problems, objectives and options of the agricultural statistics strategy 2020 and their relations. Source: Eurostat.

5. IMPACT ANALYSIS The decisions to produce European Union statistics are policy-driven. Their raison d'être is to support policy-making by providing EU institutions, Member State governments and other data users with relevant statistical information needed to design, implement, monitor and evaluate EU policies. EU statistics are important for evidence-based policy making for all Union policy areas and in particular for the ten priorities of the Juncker Commission. The "impact of statistics" is thus linked to the fact that they are an infrastructure serving many purposes in modern societies; but the social, economic and environmental impacts of this infrastructure are not directly measurable. However, as shown previously, a lack of high quality statistics can lead to serious indirect impacts such as wrong decisions, misallocations of money or even major political disruptions. Conversely, more and better data for evidence-based policy design, implementation and monitoring are indirectly highly significant and can have immense impacts in many areas of society, the economy and the polity, e.g. better CAP funds allocation increasing the effectiveness of European agriculture and thus EU food security. The main direct significant impacts of the production of European Union agricultural statistics are localised in cost and administrative burdens on NSIs and ONAs (who would for example benefit from more harmonised and coordinated data collection efforts), and cost and response burdens on agricultural holdings and organisations (e.g. small farms who would benefit from having to answer fewer surveys in a more flexible manner). Therefore, these impacts will be analysed in detail quantitatively and qualitatively in the following pages. 5.1. Administrative burden impacts Burden for data producers

In 2011, Eurostat concluded an exercise with the purpose of estimating the administrative burden of collecting FSS variables on data producers (NSIs and ONAs). The objective of this exercise was to estimate the overall burden related to a new proposed system of farm surveys composed of core, module and satellite surveys as compared to the current FSS system. This system was intended to collect core data from the main sample, module data from a sub-sample, and satellite data from a separate sample of farms. The overall burden was estimated using the results of the burden assessment exercise of FSS 2010 and SAPM 2010 (only those variables not covered by FSS core, module or satellite surveys) as a reference and starting point. In the exercise, each Member State estimated its own burden of each FSS and SAPM variable on a scale of 1-5, with 1 indicating a very low burden and 5 a very high burden. Based on the submitted results from the then 27 Member States, Eurostat calculated an indicator, i.e. a number indicating the average administrative burden score per variable. As the structure of this previously proposed system was largely identical to the structure of the currently proposed options 3 and 4, this methodology was adapted for this impact assessment to arrive at the conclusions detailed in the subchapters of the impacts of options 2, 3 and 4. However, the final structure of the future EASS is subject to negotiations and agreements in legislative and expert bodies, its implementation is dependent on inter alia technological and organisational feasibility, and the underlying numbers only represent averages of subjective national assessments of administrative burdens. Due to these and other factors, the results should be taken as orienting approximations rather than as exact predictions. Further details of the methodology, its underlying assumptions and estimations, and the full calculations are presented in Annex IV. The result of the calculations is that for a full "cycle" (one census and two sample surveys) of FSS surveys, options 3 and 4 are foreseen to lead to the following burden reduction for data producers as compared to a prolongation of the current status quo (option 2): Burden reduction in the short term despite adaptation costs, and a better performance (fulfilling new data needs, more system harmonisation and integration). Estimated total weighted burden score of 1007 instead of 1028 in the prolongation of the current status quo. Burden reduction in the long term due to no more adaptation costs, better flexibility and adaptability of the new system, and fewer farms to be surveyed. As to option 1, its burden impact is hard to assess due to very different systems in Member States, but it can be expected that less, and less regulated, data collection, will initially translate into some burden reduction as compared to option 2. In any case, the administrative burden must be seen in relation to the benefits created, in this case mainly serving important EU policies with a statistical evidence basis. Thus, a lower burden is not automatically better if it leads to inferior statistical products, and a higher burden is not automatically worse if it leads to better products. This balance should be kept in mind when assessing the burden of data collection. The burden of agricultural statistics other than the FSS could not be estimated due to a lack of data and very different Member State systems and practices precluding comparison. However, the structural survey remains the backbone of the EASS and is its central and biggest individual data collection; the results of this analysis should therefore in general be transferable to smaller collections. Burden for data respondents As described in chapter 1.6.3., in a burden-assessment exercise in 2010 based on a questionnaire sent to Member States to assess the production costs and response burden of EU basic legal acts in several statistical fields, among them statistics on agriculture, the FSS was seen as having a high production cost and response burden, whereas other agricultural statistics collections had at most a medium cost and burden while also serving to answer national data needs in most Member States. In this respect, one should however keep in mind that "the burden of statistics" is a perception of respondents which does not objectively reflect a measurable and genuine statistical impact, since it is sometimes confused with other opinion surveys, or combined with national addons. There is however a clear need to lower, to the extent feasible without compromising on quality, mainly the burden of the FSS data collection for data respondents (i.e. farmers, managers of agricultural holdings etc.) to ensure its continuation and improvement as the keystone of the EASS. This would also help to achieve a main goal of the Better Regulation initiative, namely reducing the burden for small and medium enterprises (SMEs), and also the REFIT objective of burden reduction. This goal could be achieved under options 3 and 4 mainly by a new threshold of 98% of total utilised agricultural area and livestock units expected to bring considerable savings mainly in countries with many very small holdings and reducing the number of surveyed farms overall by around 3.6 million to 8.4 million as compared to the almost 12 million farms surveyed for the FSS 2010 (i.e. a reduction of 30%). This change would constitute a significant easing of the survey burden for respondents across the EU and potentially benefit from more than one in two (Romania) to one in three (e.g. Bulgaria) and one in five (e.g. Poland) SME agricultural holdings (see 5.2. for further details and a country table on the effects of these changes). Further reductions of the burden for data respondents can be expected under options 3 and 4 through more efficient and moderately shorter questionnaires due to the core, module and satellite system, and under all options due to technological progress e.g. allowing completion of web-based surveys. As option 1 is expected to lead to fewer surveys in Member States, some burden reduction will also take place under this option. It is not easily possible to quantify all these different effects due to the sometimes vastly different statistical collection systems and economic conditions in EU Member States e.g. affecting rural Internet access and survey methods. To attempt an indicative quantification, the overall 30% reduction in the number of surveyed holdings can be applied fully, whereas integration and harmonisation actions on the side of data producers, shorter questionnaires as well as technological and other progress can be assumed to reduce the overall burden by 5%, resulting in an overall burden reduction by about one third for surviving farm holdings in the EU under options 3 and 4 as compared to option 2. To summarise: 100% burden reduction for most of the small farms below the new survey thresholds, benefiting from more than one in two (Romania) to one in five (e.g. Poland) SME farms. Burden reduction for the other farms due to more efficient and better integrated surveys, except for some farms having to fulfil new data needs by answering module or ad-hoc surveys in addition to the core surveys. 5.2. Cost impacts Qualitative analysis Need for EU funding of EU agricultural statistics As stated earlier, the collection of high-quality and comparable EU agricultural statistics cannot be sufficiently achieved by the Member States alone, but only at EU level on the basis of EU legal acts, because only the EU can ensure the necessary harmonisation of statistical information. In addition, the CAP is completely managed by the EU and Union funding replaces national spending, reducing the incentives for Member States to conduct costly surveys to collect a full set of agricultural statistics. Costs statements from earlier grant procedures show that especially the decennial agricultural censuses are very costly. Union support is therefore needed to ensure that countries with a large farming community do not have to carry too high a burden of the overall costs. Without EU support, many Member States may be tempted to reduce their agricultural statistics collections. Therefore, the EU contributes to the costs of agricultural statistics data collection via annual financing decisions with the budget being endorsed by the legislator. This contribution covers a share of the overall cost of carrying out agricultural statistics surveys and helps to offset the additional costs incurred by Member States in meeting the requirements of the Commission, concerning, in particular, the harmonisation of survey characteristics and the delivery of results in a common format and in time. Abolishing EU funding for statistics in agriculture would almost certainly lead to a loss of essential evidence for shaping policies at national and EU level and to a great risk of budget misallocation. For farmers, this could mean losing a significant part of their income. The impact assessment for the CAP 2014-2020 analysed the effects of a drastic reduction of the CAP budget and concluded that phasing out direct payments would lead to strong restructuring in the sector and much larger and more capital intensive farms. Production intensification in the most fertile regions and land abandonment in less advantageous areas would have negative environmental and social consequences. Focusing policy on rural development-type environmental measures would help to alleviate these problems, but would not contribute to enhancing the sustainability of agriculture. While agricultural statistics alone are not sufficient in guaranteeing the continuation of the CAP, they are a necessary ingredient for any future policy development. This holds for related policies such as rural development and climate change actions as well. Therefore, DG AGRI is committed to provide funding for the EASS for the foreseeable future.

EU agricultural statistics costs as an investment There are two possible alternatives for setting up agricultural statistics data collection. The first one is for the EU to organise it through procurement. Considering that coherence, consistency and long time series are needed, this would require substantial planning and expert know-how. There were almost 11 million farms in the European Union in 2013, all of which must be surveyed in an agricultural census. The costs involved in a procurement alternative are very difficult to estimate. Cooperation with Member States would in any case be necessary in order to create the sample. On the other hand, there exists a system of agricultural statistics in all Member States, with well-functioning processes and often with more than 100 years of experience in carrying out farm structure surveys. Quality is ensured through the use of a good sampling basis. The fact that Member States do not carry out these surveys only for EU policy needs, but also for their own national and regional policies, means that they are ready to invest their own funds, which can be seen from the fact that the total costs reported by the Member States for carrying out the agricultural census in 2010 amounted to about 320 million Euro, to which the EU contributed with 37.4 million Euro (11.7%). The total costs for the FSS 2013, which was a sample survey of about 1.7 million farms, amounted to about 47 million Euro, with a total EU contribution of 18.7 million Euro (39.9%). From this, the general conclusion can be drawn that the overall costs of not having EU agricultural statistics at all and/or only having disparate Member State collections (option 1) are much higher than collecting them either as in the status quo (option 2) or with a renewed legal, organisational and technical basis (options 3 and 4). This is because the costs of data collection, production and dissemination (e.g. 320 million Euro for the farm census in 2010 in the entire EU) are dwarfed by the costs of not having sufficient data to guide policies (e.g. 59 billion Euro per year for the CAP alone, let alone the costs of for example insufficient food security). European Union agricultural statistics and the EU contributions should therefore be seen as an investment rather than as pure costs. Furthermore, abandoning a working system in which great amounts of person-years, funds and other resources have been invested over the decades to try to achieve the same results in a more disorganised and disparate manner (option 1), or continuing the system unchanged despite mounting challenges, and thus exposing it to a risk of obsolescence and higher adaptation costs due to more parts to be changed and an even more urgent timeframe once its deficits become even greater (option 2), is certainly more costly in the short and long term even if only focusing on the direct objectives of serving data needs better, more coherently and lowering the burden, than updating the system (options 3 and 4). The following quantitative analysis of costs and benefits is therefore based on the assumption that European agricultural statistics are needed, and the identified options are analysed for their different approaches in achieving this goal. Quantitative analysis Costs of farm structure surveys for data producers According to the information provided to Eurostat by the Member States in the context of applying for financial support to carry out the farm structure surveys, the total costs for the agricultural census in 2010 amounted to almost 320 million Euro, while for the interim surveys in 2013 and 2016 the total reported costs have reached or will reach about 47 and 44 million Euro. As previously mentioned, the EU contributed 37.4 million Euro to the FSS 2010 (11.7%) and 18.7 million Euro to the FSS 2013 (39.9%). There are no reporting requirements on the costs of other agricultural statistics surveys, but as parts of quality reporting exercises, some countries have given rough estimates on the costs involved in crop production statistics. The costs in this domain range widely from 0.6 cent per ha of utilised agricultural area in Romania to 64 cent per ha in Poland, as costs are directly related to the use of other data sources than statistical surveys, for example administrative data. Therefore, no useful analysis was possible on the basis of this data. Possible cost savings in farm structure surveys for data producers Eurostat sent a questionnaire to Member State NSIs on FSS survey organisation and related costs in autumn 2015, based on their estimates of the FSS 2016, and if not available, on FSS 2013 data. The answers were used to calculate the potential reduction in the costs stated above, for options 3 and 4, and based on the two assumptions of 1) a new threshold of 98% of total utilised agricultural area and livestock units, and 2) allowing Member States with many small units to carry out a special sample survey on 5% of the smallest holdings in order to reach the 98% coverage requirement instead of including them in the regular sample. The current legal thresholds are too high to achieve sufficient coverage, so Member States now survey almost all holdings for coverage compliance. These two changes alone would reduce the number of surveyed farms by around 3.6 million to 8.4 million as compared to the almost 12 million farms surveyed for the FSS 2010 (and planned to continue to be surveyed in option 2), with a resultant reduction in census costs of about 56 million Euro compared to the status quo of almost 320 million Euro, i.e. about 18% (see table 2 below). The one-off implementation costs related to changes i