COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT Accompanying the document Strategy for Agricultural Statistics 2020 and beyond and subsequent potential legislative scenarios
Date: 2016-12-09
Institutions: European Commission, Eurostat
Subjects: EU statistics, agricultural statistics, agricultural structure, data collection, data protection, large holding, personal data, statistical method

EN 

   EN 

   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 ..................................................................................................................................... 4 

1.1. Context of European Union Agricultural Statistics ...................................................................... 4 

1.2. A changing world, unchanging agricultural statistics ................................................................... 6 

1.3. The current EASS .......................................................................................................................... 8 

1.4. Stakeholders of the EASS ............................................................................................................. 9 

1.5. Performance, evaluation and lessons learnt of current EASS ................................................... 10 

1.6. Problems of the current EASS .................................................................................................... 11 

1.6.1. New and emerging data needs not adequately served ...................................................... 11 

1.6.2. Data collections not sufficiently harmonised and coherent ............................................... 13 

1.6.3. Burden of providing data perceived as too high ................................................................. 14 

1.6.4. Evolution of the problems .................................................................................................. 15 

2. NEED FOR EU ACTION ....................................................................................................................... 15 

3. OBJECTIVES ....................................................................................................................................... 17 

3.1. Meeting data needs ................................................................................................................... 19 

3.2. Coherence and integration ........................................................................................................ 22 

3.3. Burden reduction ....................................................................................................................... 23 

4. OPTIONS ............................................................................................................................................ 24 

4.1. Baseline – No EU action on structural data of agriculture ......................................................... 24 

4.2. Prolongation of the FSS Regulation (EC) No 1166/2008 ............................................................ 24 

4.3. Single new legal framework for the whole sector of agricultural statistics ............................... 24 

4.4. Two-step integration of agricultural statistics ........................................................................... 26 

4.5. Early discarded options .............................................................................................................. 27 

4.6. Problem and solution tree ......................................................................................................... 27 

5. IMPACT ANALYSIS ............................................................................................................................. 28 

5.1. Administrative burden impacts .................................................................................................. 29 

5.2. Cost impacts ............................................................................................................................... 31 

5.3. Impacts of Option 1 - Baseline – No EU action on structural data of agriculture ...................... 35 

5.4. Impacts of Option 2 - Prolongation of the FSS Regulation (EC) No 1166/2008 ......................... 38 

5.5. Impacts of Option 3 – Single new legal framework for the whole sector of agricultural 
statistics ............................................................................................................................................ 39 

5.6. Impacts of Option 4 - Two-step integration of agricultural statistics ........................................ 42 

5.7. Impacts of early discarded options ............................................................................................ 43 

6. COMPARISON OF OPTIONS ............................................................................................................... 44 

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7. MONITORING AND EVALUATION ...................................................................................................... 45 

ANNEXES ............................................................................................................................................... 49 

Annex I: Procedural information ....................................................................................................... 49 

Annex II: Stakeholder consultation ................................................................................................... 52 

Annex III: Who is affected by the initiative and how ........................................................................ 59 

Annex IV: Impact analysis methodology ........................................................................................... 61 

Annex V: Detailed list of data sets collected in the EASS .................................................................. 66 

Annex VI: Summary of present agricultural data collection and new needs in the EU .................... 69 

Annex VII: List of abbreviations ........................................................................................................ 79 

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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.  

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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 

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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 regions1; 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)2  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).3 

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 

1 www.phosphorusplatform.eu  
2 Eurostat press release 206/2015 on EU farms, 26.11.2015  
3 Ibid. 

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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 
Programme4)  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  2014-2020.5  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 

4 Decision No 1386/2013/EU of the European Parliament and of the Council of 20 November 2013 
5 Communication from the Commission COM(2015) 639 final, 14.12.2015: Investing in jobs and growth – 
maximising the contribution of European Structural and Investment Funds  

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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 statistics6, 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. 

6 ESS Vision 2020 – Building the future of European statistics  

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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 

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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 Practice7, 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.  

7 European Statistics Code of Practice (DOI: 10.2785/18474) 

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  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. 

11 

 
 
 
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 20158, 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.9 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.10 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.11  

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 

8 Minutes of the DGAS Meeting 2015 
9 Minutes of the Joint FSS/Crops WG Meeting October 2015 
10 Document CPSA/719 for the CPSA Meeting April 2014 
11 Farm data needed for agri-environmental reporting (DOI: 10.2785/12758) 

12 

 
 
                                                            
Administration  and  Control  System  (IACS)  could  be  better  linked  to  the  FSS  to  allow  for 
more complex analyses.12 

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.13 14 

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.15  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.16 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.17 

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, 

12 UNECE Review of Agricultural Statistics 2008 
13 Document CPSA/718 for the CPSA Meeting April 2014 
14 Document CPSA/732 for the CPSA Meeting November 2014, Annex II 
15 Ibid. 
16 Document CPSA/584 for the CPSA Meeting May 2010 
17 Detailed Results of the Eurostat User Satisfaction Survey 2014 

13 

 
 
                                                            
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 2013.18 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 criterion19, 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.20 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.21 

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.22 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 meeting23, 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 meeting24, the joint FSS/Crops Working Group Meetings in 
October  201525,  and  at  the  ESSC  Meeting  in  November  201526.  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 

18 Minutes of the CPSA Meeting November 2013 
19 Report on the Eurostat User Satisfaction Survey 2014 
20 Report on the Eurostat User Satisfaction Survey 2015, 
    Complementary Report on the Eurostat 2015 Satisfaction Survey for key users 
21 Detailed results of the Eurostat User Satisfaction Survey 2015 
22 Minutes of the ESSC Meeting November 2015 
23 Minutes of the ESSC Meeting May 2014 
24 Minutes of the DGAS Meeting 2015 
25 Minutes of the Joint FSS/Crops WG October 2015 
26 Minutes of the ESSC Meeting November 2015 

14 

 
 
 
                                                            
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.27  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).28 
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) 

27 Document CPSA/613 for the CPSA Meeting May 2011 with Annexes 
28 OJ C 326/192 

15 

 
 
                                                            
No  223/200929  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.  

29 OJ L 87/164, amended by Regulation (EU) 2015/759, OJ L 123/90 

16 

 
 
                                                            
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  role30.  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.31  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  2013-201732.  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 
Commission33,  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 

30 Commission Decision on Eurostat of 17 September 2012 (2012/504/EU), OJ L 251/49 
31 The objective of the ESS Vision 2020 is to improve the efficiency of European statistics by reforming their 
production methods and modernising the ESS in order to meet the challenges that statistical producers are faced 
with, satisfy users and continue to be relevant in EU policymaking. The main idea is to move away from the 
traditional  way  of  producing  statistics  to  a  more  integrated  production  model  which  will  increase  efficiency, 
reduce the burden on respondents, cut the cost of compiling statistics and respond better to user needs. Using 
multiple  sources,  innovative  data  collection  methods,  and  cross-domain  concepts  is  emphasised.  (DOI: 
10.2785/059143)  
32 Regulation (EU) No 99/2013 on the European statistical programme 2013-17 
33 European Commission – 10 Priorities  

17 

 
 
                                                            
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" 

Increase the flexibility and reaction speed of 
the agricultural statistics system 

"Burden of providing data perceived as too 
high" 

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 " 

Produce more statistics while lowering the 
burden on respondents by exploring 
alternative data sources and possibilities of 
efficiency improvement 

"Data collections not sufficiently harmonised 
and coherent" 

"Burden of providing data perceived as too 
high" 

"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: 

18 

 
 
 
 
 
  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.34  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 

34 Commission Implementing Regulation (EU) No 834/2014 of 22 July 2014 laying down rules for the 
application of the common monitoring and evaluation framework of the common agricultural policy, OJ L 230/1 

19 

 
 
 
 
                                                            
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 

20 

 
 
 
 
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 

21 

 
 
 
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  States35,  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".36 

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 

35 Statistics Explained - Farm Structure Survey - Thresholds 
36 ESS.VIP.BUS.ADMIN (Administrative data sources)  

22 

 
 
 
 
 
                                                            
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. 

23 

 
 
 
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. 

24 

 
 
 
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.37 

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.38  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.) 

37 Document CPSA/631 for the CPSA Meeting November 2011 
38 FAO World Program of the Census of Agriculture 2020, Volume 1: Programme, concepts and definitions  

25 

 
 
 
 
 
                                                            
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 
the  Permanent  crop  statistics  regulation  (Regulation  (EC)  No  1337/2011; 
replace 
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, 
intermediaries  (dairies  etc.),  wholesale  entities  and  market 
administrative  sources, 
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. 

26 

 
 
 
 
 
 
As the Economic Accounts for Agriculture (EAA)39 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. 

39 Regulation (EC) No 138/2004 of the European Parliament and of the Council of 5 December 2003 on the 
economic accounts for agriculture in the Community, OJ L 33/1 

27 

 
 
                                                            
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. 

28 

 
 
 
 
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).40 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):41  

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. 

40 Document CPSA/SB/689 for the FSS WG Meeting September 2011 
41 With internal factors such as survey and system redesign and adaptation costs as well as fewer surveyed 
holdings, and external factors such as a continuing shrinkage of the number of agricultural holdings in the EU 
and technological progress already accounted for 

29 

 
 
                                                            
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 

30 

 
 
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. 

31 

 
 
 
 
 
 
 
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%). 

32 

 
 
 
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  in  legislation,  methodology  and  IT  systems  are 
estimated at around 26 million Euro.42 

Further savings, especially important for the costly FSS surveys, can be achieved by the core, 
module and ad-hoc survey system, more surveys being filled out online (shortening the time 
needed  for  data  collection  and  reducing  the  need  for  staff  conducting  personal  or  phone 
interviews  or  entering  data  from  postal  questionnaires), 
increased  coherence  and 
harmonisation between the different agricultural statistics domains (allowing Member States 
to  better  coordinate  their  data  collection  efforts,  reduce  the  collection  frequency  etc.),  and 
other  actions  at  European,  national  and  regional  levels  to  increase  efficiencies  and  reduce 
costs, such as better IT software and hardware setups, sharing of tools etc. However, as some 
of  these  actions  are  or  will  be  implemented  very  differently  between  and  even  within  the 
various  countries  due  to  different  institutional  set-ups,  technological  levels,  numbers  of 
farms,  types  of  surveys,  sample  sizes  and  other  methodological  issues  and  general  price 
levels in the countries etc., it is not possible for Eurostat to usefully quantify the potential cost 
reductions  due  to  these  actions  beyond  general  trends.  But  as  Member  States  are  only 
partially reimbursed for their expenses, it is in their own interest to keep the costs low, thus 
general cost-effectiveness can be assumed now and in the future. This assumption is backed 
by  the  fact  that  several  countries  report  estimated  costs  that  are  very  close  to  or  below  the 
threshold to receive the maximum EU contribution. 

42 Typically, survey design and data treatment together cost half as much as data collection – assuming a 25% 
rise of these costs for adaptation in line with historical experience, additional expenses will amount to around 
8% in the short term. 

33 

 
 
 
 
                                                            
Table  2:  Marginal  FSS  census  costs  and  reduction  under  options  3  and  4,  EU-27. 
Source: Eurostat 

A. 
Country 

B. 
Marginal costs per 
surveyed holding43 

C. 
Farms surveyed 
for FSS 201044 

AT 
BE 
BG 
CY 
CZ 
DE 
DK 
EE 
EL 
ES 
FI 
FR 
HU 
IRL 
IT 
LT 
LU 
LV 
MT 
NL 
PL 
PT 
RO 
SE 
SI 
SK 
UK 
Total 

in Euro 
24 
4 
30 
74 
15 
65 
15 
14 
27 
36 
8 
40 
18 
6 
53 
9 
24 
20 
20 
3 
11 
52 
4 
7 
10 
2 
8 
--- 

Number of farms 
150.200 
42.900 
370.200 
38.900 
22.900 
299.800 
42.100 
19.600 
674.200 
989.800 
63.900 
516.100 
576.800 
139.900 
1.620.900 
199.900 
2.200 
83.400 
12.500 
72.300 
1.506.600 
305.300 
3.859.000 
71.100 
74.600 
24.500 
188.700 
11.968.300 

D. 

Farms out under 
assumptions 1 and 245 
Number of farms 
13.700 
1.400 
121.600 
14.000 
0 
0 
700 
1.100 
188.800 
56.700 
300 
27.000 
249.200 
2.400 
458.300 
36.000 
100 
11.800 
6.600 
500 
249.700 
53.000 
1.991.900 
100 
14.500 
3.900 
2.400 
3.505.700 

E. 

Total FSS 
2010 costs46 

F. 
Saved costs:  
= B*D 

in Euro 
3.530.000 
960.000 
6.010.000 
5.540.000 
640.000 
15.650.000 
920.000 
810.000 
32.130.000 
24.680.000 
1.830.000 
25.770.000 
9.740.000 
1.870.000 
126.590.000 
3.340.000 
90.000 
1.000.000 
200.000 
2.450.000 
5.330.000 
16.900.000 
26.810.000 
690.000 
2.350.000 
370.000 
2.790.000 
318.990.000 

in Euro 
328.800 
5.600 
3.648.000 
1.036.000 
0 
0 
10.500 
15.400 
5.097.600 
2.041.200 
2.400 
1.080.000 
4.485.600 
14.400 
24.289.900 
324.000 
2.400 
236.000 
132.000 
1.500 
2.746.700 
2.756.000 
7.967.600 
700 
145.000 
7.800 
19.200 
56.394.300 

This quantification indicates that options 3 and 4, accounting for all possible cost savings and 
excluding adaptation costs that are hard to quantify due to the different systems in Member 
States (but expected to pay for themselves in the medium run), would lead to around a fifth 
less costs than the continuation of the status quo (option 2), assuming the number of holdings 
continues to shrink and that technology etc. progress under either option. To sum up: 

Cost  savings  for  data  producers  will  be  around  18%  or  56  million  Euro  Around  a  tenth  of 
these  savings  is  expected  to  accrue  to  Eurostat,  and  thus  the  EU  budget.  In  the  short  term, 
adaptation expenses of around 26 million Euro are estimated to occur. 

43  This  number  indicates  the  non-fixed  survey  costs  per  surveyed  holding  per  country  and  results  from 
calculations  based  on  the  country  responses  to  the  Eurostat  FSS  costs  questionnaire  referenced  above.  Where 
countries did not provide a response, the non-fixed survey costs were estimated based on total and staff costs 
countries reported for the FSS survey 2010. 
44 These numbers come from Eurofarm records. 
45 These numbers result from internal calculations conducted at Eurostat on the effect of different thresholds on 
the reduction of the census survey population. 
46  This  information  is  provided  by  Member  States  to  Eurostat  according  to  Articles  13  and  14  of  Regulation 
(EC) No 1166/2008. 

34 

 
 
 
 
                                                            
As  for  option  1,  Member  States  would  collect  some  agricultural  statistics  even  without  EU 
farm  structure  survey  obligations  due  to  international  obligations  (FAO  asks  to  carry  out 
agricultural censuses every decade) and national and regional policy desiderata, so the costs 
could only be partly reduced. However, Member States would be generally more flexible in 
deciding how to set up their agricultural statistics surveys and what to collect as long as they 
fulfil their other obligations, and the costs for the interim structure surveys would fall away. 
It is thus not possible for Eurostat to quantify the savings for the farm structure census under 
option  1,  but  as  mentioned  previously,  the  savings  from  completely  abolishing  the  interim 
sample  surveys  would  be  close  to  90  million  euros,  of  which  around  60%  would  accrue  to 
Member States. However, the costs to the users of the EASS would be quite high, as easily 
available, comparable and coherent datasets would no longer exist. But it is not possible for 
Eurostat to quantify these costs. 

Possible cost savings for data respondents 

The cost savings for data respondents should mirror those in the administrative burden impact 
section 5.1. (i.e. about a third less costs under options 3 and 4 as compared to the status quo 
option  2),  but  are  also  difficult  to  quantify  exactly  due  to  the  previously  stated  reasons. 
Holdings  exempted  from  future  surveys  due  to  the  new  thresholds  can  expect  moderate 
savings  in  person-hours  not  used  to  fill  out  questionnaires  anymore  under  options  3,  4  and 
potentially 1, while holdings still surveyed can expect small savings in person-hours due to 
more  efficient  surveys  deployed  in  more  convenient  and  technologically  advanced  ways 
under all options. However, this latter benefit could be neutralised under option 3 and 4 for 
some holdings by potentially longer surveys in some survey years due to having to fulfil new 
data needs via modules and satellites. In short: 

100% cost savings for many small farms below new thresholds as they will no longer have to 
respond to surveys. 

Overall, no major change in the total costs is expected for farms that continue to be surveyed. 
Some savings could arise due to more efficient survey techniques. However, this is likely to 
be offset by additional requirements related to new data needs and new ad-hoc surveys.  

5.3. Impacts of Option 1 - Baseline – No EU action on structural data of agriculture 

Effectiveness regarding objectives (fulfilling data needs, coherence and harmonisation, 
burden reduction) 

The data needs expressed above would only be fulfilled haphazardly and randomly, if at all. 
Without an EU-wide farm structure survey to anchor agricultural statistics, data would not be 
easily comparable, and drawing robust conclusions from them would be very difficult. In the 
long  term,  no  improvement  could  be  expected  due  to  a  lack  of  central  guidance  and 
coordination  in  a  common  forum  with  law-making  and  directive  power  such  as  the  EU 
provides.  The  impact  of  option  1  on  this  objective  would  therefore  be  very  negative  in  the 
short and long term. 

The  same  is  true  for  coherence  and  harmonisation:  without  a  unified  approach  in  the 
established EU fora, any harmonisation will happen only by chance. 

The burden on data producers and data respondents is likely to sink in the short term due to 
possible  national  reductions  of  the  farm  census  survey  and  the  abolition  of  the  interim 
surveys,  despite  continuing  obligations  to  international  organisations  such  as  FAO.  In  the 

35 

 
 
 
long  term,  the  data  collections  associated  with  a  less  effective  CAP  (due  to  a  lack  of  data) 
could get under pressure to realise savings in this large area of statistics. So the impact in the 
short  term  is  positive,  but  has  a  probability  of  turning  negative  or  at  least  reverting  to  the 
status quo in the long term. Therefore, the long-term burden impact is expected to be neutral. 

Efficiency regarding objectives (cost-effectiveness) 

As stated in 5.2., the absolute costs of data collections in this option are likely to sink in the 
short term, but the resources invested into the ESS and its improvement over the decades will 
be largely wasted due to abandoning the system of farm structure surveys, and the objectives 
will mostly not be achieved. Therefore, the overall impact is negative in this area, and likely 
to  turn  very  negative  in  the  long  term  due  to  a  progressively  worsening  capability  of  the 
system to achieve the increasingly demanding and urgent objectives. 

EU objectives (CAP and other EU policies, ESS) 

The EU would not have the necessary tools to carry out ex-ante and ex-post evaluations of 
the CAP because no harmonised farm-level data would be provided by Eurostat after 2016. If 
no policy actions were taken, CAP delivery would thus be severely handicapped due to a lack 
of data, with consequences for food security and climate change. In the long term, an absence 
of EU-level data on agriculture would severely impact the viability of the CAP and other EU 
policies. It is conceivable that they could be greatly reduced or even abolished if no robust 
evidence  were  available  to  ensure  their  effective  and  efficient  implementation,  with 
corresponding immense consequences for everyone affected by these policies. The costs for 
EU policy implementation, reputation and results would similarly be vast. Both the short- and 
long-term impacts would therefore be very negative. 

Efforts  made so far to  streamline the flows of agricultural statistics information  in  the  ESS 
would  be  wasted.  This  would  represent  a  loss  of  resources  (time,  finance,  technology, 
human). Other agricultural statistics would subsequently be negatively impacted by the lack 
of  harmonised  survey  data  expected.  Continuing  EU-wide  data  collection  on  a  voluntary 
basis  (gentlemen’s  agreements)  would  most  likely  compromise  the  quality  of  data,  make 
collection inherently unstable and would be a setback to legal, organisational, financial and 
personal  relations  systems  already  in  existence  for  several  decades.  This  option,  while 
seemingly reducing administrative burdens due to the expiration of the key FSS legislation, 
would therefore in fact greatly increase the complexity and burdens within the entire system 
of agricultural statistics and policy, as inadequate legislation-based data provision would have 
to  be  supplemented  by  a  multitude  of  complex,  uncoordinated  tools,  instruments  and 
procedures  of  questionable  quality  and  insecure  short-  and  long-term  sustainability.  ESS 
Code  of  Practice  principles  such  as  relevance,  accuracy  and  reliability,  timeliness  and 
punctuality,  coherence  and  comparability,  and  accessibility and  clarity  would  be  negatively 
affected, and short- and long-term impacts to the ESS in general would be very negative. 

Other impacts (Risks and indirect impacts) 

Option  1,  while  easy  to  implement  by  just  letting  the  FSS  regulation  expire,  presents  a 
significant  risk  to  the  continuity  of  agricultural  statistics  directly  and  to  EU  policy 
implementation, results and reputation indirectly. Everyone affected by policies dependent on 
the EASS would be affected, most likely in a negative way, and this would get worse as time 
progressed. The impacts would thus be very negative in both cases and both time horizons. 

36 

 
 
 
 
Impacts for stakeholders (users, producers and respondents) 

Data users would have less data of poorer quality to plan, evaluate and monitor EU, national, 
enterprise and other policies, with related indirect consequences for organisations and persons 
in any way affected by those policies. In the long term, data users would not only be affected 
by the lack of data, but also by the lack of the policies they are administering. They would 
have to produce or look for statistics themselves in an uncoordinated and inefficient way, and 
there  would  not  be  a  commonly  agreed  quality  assurance  of  EU  agricultural  statistics. 
Consultations  with  users  have  demonstrated  the  need  for  high  quality,  timely  and  EU-wide 
comparable  agricultural  statistics  produced  according  to  the  European  Statistics  Code  of 
Practice,  which  are  fit  for  purpose  in  underpinning  decision-making,  collected  in  a 
transparent  way,  and  free  from  political  influence.  Knowledge-sharing  and  increased 
efficiency  through  greater  use  of  technology  and  exploitation  of  data  collected  for  other 
purposes are other important user requirements which would not be ensured under Option 1. 
Lastly,  dependence  on  external  data  sources  may  have  a  potential  negative  impact  for  EU 
policy as this data may not be easily available or may become unavailable, may not be fit for 
purpose  or  politically  independent,  and  the  costs  of  external  data  may  be  higher  than 
anticipated. The impact on data users would therefore be very negative in the short and long 
term. 

Data producers would have freer hands to set up their own agricultural statistics systems and 
could  potentially  reduce  the  number  of  surveys  and  lower  the  quality  criteria  in  a  flexible 
manner,  leading  to  burden  reduction  and  cost  savings  (see  above).    However,  EU  Member 
States have commitments with international organizations such as FAO and OECD to provide 
structural data on agriculture, which means that they would have to conduct such surveys on 
their own with  a  high risk of losing the coordinated  and harmonised approach  the ESS has 
created over the years. They would have to produce data on Member State level without EU 
financial,  technical  or  organisational  support,  as  no  EU  budget  would  be  provided  without 
EU  legislation.  Given  the  resource  constraints  the  ESS  is  faced  with,  the  impact  of  no  EU 
budget  for  agricultural  statistics  production  would  be  considerable.  This  would  also  impact 
the  quality,  reliability  and  comparability  of  agricultural  statistics  and  thus  the  overall 
objective  of  European  Union  statistical  production:  to  support  the  design,  implementation, 
monitoring  and  evaluation  of  EU  policies.  This  overall  objective  cannot  be  fulfilled  by 
individual Member  States  on  their  own,  nor  by  Eurostat  without  data  provided  by  Member 
States.  However,  Eurostat  would  continue  its  efforts  to  convince  Member  States  that  farm 
structure data are important, trying to assure voluntary data transmission. It would also carry 
on  with  regular  Working  Group  meetings,  ensuring  information  exchange  and  discussions 
among countries, thus potentially achieving some central guidance and coordination.  

Still, reliable statistics produced according to the same high-quality standards in all Member 
States  are  necessary  in  order  to  be  able  to  compare  and  draw  conclusions  at  EU  level.  In 
addition, the European Statistics Code of Practice stipulates that adequate resource allocation 
is  a  necessary  precondition  for  the  proper  functioning  of  a  statistical  service.  Furthermore, 
only  very  little  modernisation,  coherence  and  integration  can  be  envisaged  if  there  is  no 
common effort. Despite the savings, the impact on data producers would thus be negative in 
the short and long term. 

Lastly, data respondents, while relieved of some of the burden of data collection in the short 
term, would receive fewer CAP funds in the long term due to the growing dysfunctionality of 
policies depending on the EASS, resulting from a lack of data. The impact would therefore be 
positive in the short, but negative in the long term. 

37 

 
 
Overall impact 

For  the  reasons  listed  above,  the  overall  impact  of  the  baseline  Option  1  would  be  very 
negative in the short and in the long term, as it basically constitutes a disorderly dismantling 
of the key element of the EASS, an essential service for agricultural and other EU policies. 

5.4. Impacts of Option 2 - Prolongation of the FSS Regulation (EC) No 1166/2008 

Effectiveness regarding objectives (fulfilling data needs, coherence and harmonisation, 
burden reduction) 

In  this  option,  the  farm  surveys  and  the  co-financing  of  the  national  surveys  would  be 
continued, ensuring the willingness of Member States to carry them out. The FSS Regulation 
could  be  changed  in  a  limited  way  to  respond  to  the  objectives  stated  above,  but  without 
further  integration  of  other  agricultural  statistics  or  altered  data  collection,  as  the  same 
approach  for  structural  statistics  as  applied  since  1966  would  be  continued  without  any 
significant updating. In practice, the rigid FSS Regulation excludes the possibility  to gather 
any new data that are greatly needed to  fulfil new requirements. Therefore, the  data  needs 
stated  previously  would  only  be  fulfilled  insufficiently,  and  this  problem  would  largely 
remain unsolved. The short-term impact would be negative. 

For  the  same  reasons,  the  incoherence  between  agricultural  and  rural  data  collected  in  the 
different  statistical  domains  (agriculture,  environment,  businesses  etc.)  would  remain  and 
provide  neither  consistency  across  domains  nor  an  integrated  approach  or  benefits  of 
expected synergies, except in a very limited way due to technological progress. Therefore, the 
impact on the objective of improving the coherence and harmonisation of the EASS would 
be negative as well. The same considerations apply to the objective of burden reduction. 

In  the  long  term,  the  effects  of  choosing  this  option  would  approach  those  of  option  1,  i.e. 
lead to a severe deterioration of the EASS. It would not be able to provide the data already 
urgently  needed  now  and  would  not  be  able  to  react  flexibly  to  future,  potentially 
economically,  socially  or  environmentally  disruptive  agricultural  developments,  e.g. 
affordable lab-grown meat. Coherence and harmonisation would not be able to be pursued in 
a meaningful way due to an unreformed legal, technical, methodological and organisational 
system, severely limiting the usefulness of different data collections, particularly in an ever 
more interconnected world. And the burden of data collection, while remaining nominally the 
same,  would  relatively  increase  as  resources  for  official  statistics  continue  to  be  cut  and 
problems  like  survey  nonresponse  continue  to  rise,  despite  expected  technological 
developments  leading  to  some  increase  in  efficiency.  The  long-term  impacts  of  this  option 
regarding the objectives would therefore be very negative. 

Efficiency regarding objectives (cost-effectiveness) 

The  immediate  costs  to  the  Member  States  would  remain  the  same  as  at  present,  i.e.  the 
impact is negative, as the current system is not very cost-effective in achieving its objectives. 
In  the  long  term,  not  reaping  financial  benefits  of  synergies  and  integration  and  the 
deterioration  of  the  EASS  as  described  in  the  previous  paragraph  would  create  a  very 
negative cost-effectiveness impact. 

EU objectives (CAP and other EU policies, ESS) 

The CAP and other EU policies depending on agricultural statistics already face difficulties 
due  to  the  current  EASS's  shortcomings.  If  this  were  to  continue  and  get  worse  due  to  an 

38 

 
 
unchanged EASS's more and more pronounced inability to adapt to a continuously changing 
world, the viability of these policies would be endangered, and the ESS's capability to deliver 
data  for  policymaking  could  be  called  into  question.  Not  changing  the  EASS  would  thus 
constitute a significant lost opportunity, disappoint important stakeholders’ expectations, lead 
to a high loss of credibility and reputation for the EU, and risk making European agricultural 
statistics irrelevant in the mid to long term, and by extension, much of the EU's policies as 
well. Therefore, the short-term impacts in this area would be negative both for EU policies 
and the ESS, and the long-term impacts would be very negative. 

Other impacts (Risks and indirect impacts) 

This  approach  would  require  little  preparatory  work  and  few  resource  investments  in  the 
short to mid-term, as the present arrangement would continue more or less unchanged. The 
timetable is also very realistic. Therefore, the short-term risks would be very small, and the 
impact  in  this  area  is  positive.  However,  in  the  long  term,  the  political,  legal  and 
organisational  opportunity  and  already  invested efforts  to  improve  the  EASS  would  be  lost 
and the window for change would close, to be reopened later, when the problems will have 
become even more urgent, only at greater cost. The long-term risk impact would therefore be 
negative, whereas the indirect impacts of worse EU policy delivery would be negative in the 
short term and very negative in the long term for the reasons stated previously. 

Impacts for stakeholders (users, producers and respondents) 

Data users in the European Commission and elsewhere would be very dissatisfied with this 
option, as  their  current  criticisms of  the EASS  would not  be answered, leading to a loss of 
usefulness of and trust in the system for them,  particularly in the long term as the situation 
deteriorates. The impacts would be negative in the short and very negative in the long term. 

Data  producers  would  continue  to  produce  EU  agricultural  statistics  as  they  do  now,  but 
suffer progressively more under the inefficiencies of the system. The complexity and burden 
within  the  entire  system  of  agricultural  statistics  and  policy  could  increase,  as  inadequate 
legislation-based data provision would have to be supplemented by a multitude of complex, 
uncoordinated tools, instruments and procedures of questionable quality and short- or long-
term sustainability in order to fulfil data users' requirements. While neutral in the short term, 
the impact on data producers would therefore be negative in the long term. 

Data respondents would not be significantly relieved of their burden of data collection either 
in the short or long term. The indirect impact of worse EU policy delivery could lead to fewer 
CAP  and  other  funds  and  increased  struggles  in  the  long  term,  resulting  in  a  neutral  short-
term and a negative long-term impact. 

Overall impact 

While  seemingly  only  mildly  negative  in  the  short  term,  the  highly  negative  drawbacks  of 
this  option  become  apparent  in  the  long  term,  as  it  deteriorates  due  to  a  continuously 
changing  world  not  being  answered  by  changing  agricultural  statistics.  Sticking  with  the 
status quo would therefore be very dangerous for the EASS and everything depending on it. 

5.5.  Impacts  of  Option  3  –  Single  new  legal  framework  for  the  whole  sector  of 
agricultural statistics 

Effectiveness regarding objectives (fulfilling data needs, coherence and harmonisation, 
burden reduction) 

39 

 
 
A framework regulation on the whole sector of agricultural statistics would include common 
objectives  and  definitions.  It  would  also  specify  the required  statistical  outputs  at a  general 
level, with delegated and implementing legislation specifying the exact content of each sub-
domain  of  agricultural  statistics.  It  would  enable  a  full  harmonisation  and  a  possibility  to 
update agricultural statistics, and increase responsiveness to user needs and their quality (due 
to higher coherence, clarity, reliability, accuracy and timeliness). The option would establish 
key  aspects  to  be  applied  to  all  agricultural  statistics  with  a  consistent  and  integrated 
approach  for  all  agricultural  statistics  domains.  It  would  also  meet  the  requirements  of  the 
ESS Vision 2020. Therefore, this option is expected to have a positive impact on data needs 
in  the  short  term,  and  a  very  positive  impact  on  coherence  and  harmonisation  (due  to  a 
single  framework  regulation  allowing  better  harmonisation  than  the  other  options  which 
entail  more  new  regulations,  unchanged  or  reduced  legislation).  In  the  long  term,  the 
flexibility and versatility of this option should allow fulfilling even currently unforeseen data 
needs quickly, and its adaptation costs should have paid for themselves, so that the impacts 
could then be seen as very positive. 

The calculations in  section 5.1. show that  the  burden of  this option is expected to initially 
become  slightly  lower  for  data  producers,  while  data  respondents  can  on  average  expect  a 
reduced burden due to fewer holdings having to be surveyed, leading to an overall positive 
impact. In the long term, the burden for data producers is expected to be lower than today's 
status quo after absorption of all adaptation costs and due to higher flexibility, leading to an 
overall very positive impact in combination with the savings for data respondents. 

Efficiency regarding objectives (cost-effectiveness) 

Option  3  requires  some  initial  adaptation  within  the  EASS,  but  should  be  able  to  realise 
significant cost savings in comparison with the current overall costs of the European Union 
agricultural statistics in the mid to longer term, both for data producers and data respondents 
(see 5.2.) As the option is expected to achieve the objectives, the cost-effectiveness impact is 
expected  to  be  positive  in  the  short  term  (better  results  at  slightly  reduced  cost)  and  very 
positive in the long term (better results at highly reduced cost). 

EU objectives (CAP and other EU policies, ESS) 

Option 3 would help to ensure that the CAP and other EU policies related to agriculture have 
better tools and data at their disposal. This would contribute to better planning, implementing, 
monitoring  and  evaluating  actions  and  imply  a  positive  impact  on  the  EU's  policies  and 
capabilities as well as its reputation in the short term, and a very positive impact in the long 
term as the new system settles in and new challenges will require new high-quality data fast, 
which the system will be able to provide. 

The ESS will also profit in several ways from this significant modernisation of an important 
one  of  its  parts:  increased  standing,  more  know-how  from  the  modernisation  process,  and 
improved integration overall. Therefore, both the short- and long-term impacts are expected 
to be very positive. 

Other impacts (Risks and indirect impacts) 

Due  to  the  challenge  of  embarking  on  a  wide-ranging,  sector-wide  reform  of  legislation 
within a short timeframe, this approach would increase the risk of having very complex, long 
and  difficult  negotiations  both  in  Eurostat  expert  groups  and  committees  and  in  the 
European Parliament and Council, and the resulting legislation would likely be unwieldy and 
in  danger  of  being  architecture-  instead  of  user-oriented.  Many  resources  would  also  be 

40 

 
 
needed during the entire process, raising the risk of a potential lack of human resources at one 
or several crucial points. As Regulation (EC) No 1166/2008 comes to an end with the FSS 
2016, this option could put at risk the continuation of the series of farm structure surveys and 
decennial  censuses  on  agriculture  that  form  the  backbone  of  EU  agricultural  statistics  if  no 
new  regulation  were  in  place  until  the  end  of  2018  at  the  latest  to  ensure  the  agricultural 
census 2020 and assure the continuity of the structural data supporting the CAP. If this hard 
deadline was not met, the consequences could be severe. However, Eurostat estimates that at 
least three to five years of analysis, negotiations and communication are needed to create an 
acceptable framework regulation for agricultural statistics. Therefore, the risk impact is very 
negative in the short term, but if these hurdles could be overcome (e.g. by ensuring that the 
proposals are clear on what will be potentially included in agricultural statistics in the future 
and what is not planned to be added, including robust mechanisms on controlling the burden, 
and  preparing  and  conducting  the  negotiations  well),  and  if  the  system  were  implemented 
despite  the  timing  constraints,  the  risks  would  greatly  shrink  as  the  system  would  be 
"futureproof". The impact would then be positive. Correspondingly, indirect impacts of better 
policy  delivery  due  to  better  data  are  expected  to  be  positive  in  the  short  term  and  very 
positive in the long term, as the new system settles in and is fully applied. 

A  project  like  this  can  also  have  an  impact  on  the  continuity  of  agricultural  statistics,  as 
both NSIs and Eurostat will have to carry out the normal production of statistics and prepare 
the  new  system  in  parallel.  This  can  cause continuity  impacts,  both  in data  availability  and 
time-series.  This  risk  is  not  easy  to  mitigate,  as  it  would  require  new  resources  which  are 
unlikely  to  be  available,  but  it  is  expected  that  the  results  of  the  project  will  benefit  both 
producers and users of agricultural statistics and pay for themselves in the mid to long term. 
Therefore, this particular risk does not change the overall risk assessment. 

Impacts for stakeholders (users, producers and respondents) 

Data  users  would  benefit  from  better,  more  flexible  and  integrated  data  to  apply  policies 
related to agriculture or use these data for research, implying a positive impact in the short 
and a very positive impact in the long term. 

Data producers would be able to benefit from reduced costs of data collection, a smoother 
and  not  more  burdensome  operation  of  the  EASS,  continued  guaranteed  financial  support, 
better statistical products, and more collaboration and knowledge-sharing at EU level, despite 
having  to  shoulder  some  adaptation work,  costs and  burdens  at  the  beginning  (see  5.1.  and 
5.2.). The expected impacts are therefore positive in the short and long term. 

Data respondents could benefit from reduced costs and burdens due to fewer holdings being 
surveyed,  continued  guaranteed  support  and  better  policy  delivery  due  to  better  data  under 
this  option.  In  particular,  the  new  EU  Member  States  and  the  Mediterranean  countries  are 
estimated  to  benefit  more  from  these  reductions  than  the  other  Member  States,  while  all 
Member  States  will  be  affected  by  the  required  adaptations  to  the  new  survey  system  (see 
Annex III for more details). The impacts are therefore expected to be positive in the short and 
long term. 

Overall impact 

Option 3 offers a good chance of achieving the objectives of the agricultural statistics strategy 
for 2020 and beyond while realising savings and reducing the burden. Particularly in the long 
term, this option would more than pay for itself. However, adopting and implementing it in a 
very short timeframe would present a significant risk.  

41 

 
 
 
5.6. Impacts of Option 4 - Two-step integration of agricultural statistics 

Effectiveness regarding objectives (fulfilling data needs, coherence and harmonisation, 
burden reduction) 

Data needs: The first regulation on farm level data with a limited core set of variables and 
several modules to be surveyed at different frequencies and with lower quality requirements 
would  likely  be  slightly  more  flexible  and  easier  to  adapt  than  the  single  framework 
regulation of option 3, while still fulfilling the requested data needs in conjunction with the 
second  framework  regulation.  The  second  regulation  would  deal  with  agricultural  inputs 
(prices,  fertilizers  and  pesticides)  and  outputs  (production  and  prices).  Both  regulations 
would remain open for new needs and help to improve cross-domain cooperation. Therefore, 
a positive impact is expected in the short term, and a very positive impact in the long term as 
the system settles in and is fully applied. 

Coherence  and  harmonisation:  The  introduction  of  a  coherent  framework  would  allow 
better  survey  planning,  combining  databases  into  data  warehouses  etc.,  though  not  in  as 
unified a manner as with the single framework regulation of option 3. The definitions would 
be the same in both regulations, and common code lists and terminologies would be created. 
Therefore, a positive impact in the short term and a very positive impact in the long term are 
expected. 

Burden reduction: Member States with a large number of subsistence households would be 
able  to  cut  down  the  size  of  the  surveys  significantly,  thus  making  considerable  burden 
savings added to those by technological progress and better use of IT tools. Additionally, the 
free choice of data sources in accordance with national laws and principles, together with the 
possibility of using available administrative and other recognised data sources should further 
reduce  the  financial  and  administrative  burden  on  respondents,  national,  regional  or  local 
authorities, and on citizens. The legal proposals will also aim to strike the right balance in the 
use of legal instruments, e.g. by restricting delegated acts to details and planning frameworks, 
or  by  giving  Member  States  the  option  to  control  the  costs  framework  via  an  objective 
methodology  applied  via  implementing  acts.  The  main  sources  of  costs  and  burdens  could 
also  already  be  fixed  at  the  level  of  the  basic  act  if  feasible,  e.g.  precision  requirements, 
sample  characteristics  or  periodicity.  As  under  option  3,  the  adaptation  costs  for  data 
producers make the total burden impact "only" positive in the short term, but very positive in 
the long term as the new system's synergies are implemented and its flexibility helps avoid 
costs of a new adaptation. 

Efficiency regarding objectives (cost-effectiveness) 

The  main  additional  costs  for  both  the  Commission  and  Member  States  will  come  from 
adapting  the  present  survey  legislation,  from  adapting  the  survey  methodology  and  from 
making changes to IT systems to improve the EASS as stated. These costs for Member States 
would eventually be paid back from savings in carrying out the surveys. Therefore, the cost-
effectiveness impact is expected to be positive in the short term and very positive in the long 
term (see also 5.2.) 

EU objectives (CAP and other EU policies, ESS) 

As under option 3, a better EASS would allow the EU to better achieve its objectives related 
to agriculture and represent progressive momentum for the European Commission, enhancing 
its reputation and also fulfilling the mandates of the ESS Vision 2020. The expected impacts 
in  the  short  and  long  term  are  therefore  the  same  ones  as  in  option  3:  positive  and  very 

42 

 
 
positive  for  the  CAP  and  other  EU  policies  and  objectives,  and  very  positive  and  very 
positive for the ESS. 

Other impacts (Risks and indirect impacts) 

Option  4  mitigates  the  main  timing  and  legislative  risks  of  option  3  due  to  its  two-step 
integration  approach,  tackling  the  most  urgent  work  on  structural  data  and  the  next 
agricultural census 2020 first and extending the system later to cover agricultural input and 
output  data,  and  it  allows  for  incremental  progress  and  legislative  flexibility  as  well  as  for 
integration  of  methodological  developments.  Nevertheless,  adopting  new  legislation  and 
implementing it carries certain risks of delays or failures during the process. Therefore, the 
expected risk impact is neutral in the short term, and positive in the long term. As in option 3, 
indirect  impacts  of  better  policy  delivery  are  expected  to  be  positive  in  the  short  term  and 
very positive in the long term, as the new system settles in and is fully applied. 

Impacts for stakeholders (users, producers and respondents) 

Data needs would be served well and possibly slightly more flexibly than in option 3 due to a 
more nimble legislative architecture; data collection would be harmonised and integrated; and 
the costs and burdens could be reduced through surveying fewer holdings, applying the new 
legislation,  harmonisation  and  use  of  technological  progress,  and  new  data  sources,  despite 
some  initial  adaptation work.  As  under  option  3,  this  would  benefit  users  applying  policies 
depending on agricultural statistics or using these statistics for research, data producers due to 
smoother and less burdensome operation, continued  guaranteed  financial support and better 
products,  and  data  respondents  due  to  reduced  costs  and  burdens  for  them  and  continued 
financial  support.  Therefore,  the impacts  on  stakeholders  are  expected  to  be  the  same  as  in 
the previous option. 

Overall impact 

This option offers the best cost-benefit advantages of achieving the objectives of the strategy 
while  mitigating  the  main  risk  of  option  3.  Initially,  the  changes  it  entails  still  need  to  be 
applied however, imposing some costs and burdens. Therefore, its overall impact is expected 
to be positive in the short term and very positive in the long term. 

5.7. Impacts of early discarded options 

As stated in  chapter  4.5., the  CAP requires comparable data, which can effectively only  be 
established  by  legislation  at  EU  level.  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 depended on data collected 
by unstable and unreliable means. Thus, improving or at the very least continuing the current 
legislation is the only way to reach the objectives named above. 

For these reasons, the effects of alternative approaches and instruments would resemble those 
of Option 1 and possibly be even worse. Therefore, their impact analysis has been subsumed 
under Option 1. 

43 

 
 
6. COMPARISON OF OPTIONS 

Taking  the  information  and  the  assessments  of  the  individual  impacts  from  the  previous 
chapter 5 into account, the following option comparison (table 3) can be constructed. 

Option  1  "Baseline"  offers  the  worst  outcomes  in  almost  all  dimensions,  particularly  in  the 
long  term  as  data  needs  and  resource  constraints  become  even  more  urgent.  Option  2 
"Prolongation"  offers  only  limited  benefit  in  the  short  term  and  severely  deteriorates  in  the 
long  term  as  the  current  EASS  becomes  more  outdated  and  cumbersome.  Options  3  "One 
framework regulation" and 4 "Two-step integration", while requiring some initial investments 
and new EU Regulations, offer the best chances to achieve the objectives formulated earlier 
in  a  cost-efficient  manner,  present  the  comparatively  lowest  risks,  have  the  most  positive 
indirect  impacts,  and  best  satisfy  stakeholders'  requirements.  They  also  fulfil  the  REFIT 
initiative's  goals  of  updating  EU  legislation  to  increase  its  cost-benefit  ratio  and  reduce  the 
burden on small and medium-sized enterprises (see chapters 5.1. and 5.2.) Option 4 also has 
the  added  benefits  of  presenting  less  timing  risk  in  the  legislative  process  (as  a  new 
agricultural census regulation needs to be adopted by the Council and the Parliament at the 
latest by the end of 2018) and being slightly more flexible due to a less unwieldy legislative 
architecture. Therefore, Eurostat prefers option 4 over option 3. 

The main stakeholders of the EASS, i.e. the Commission's policy DGs as data users, the NSIs 
and ONAs as data producers, and farmers as data respondents also prefer option 4 due to the 
reasons stated above and in Annex II, in particular with a view to the timing constraints and 
legislative process risks of option 3. If these constraints and risks were not present, a majority 
of stakeholders would prefer option 3, for a wholesale modernisation of the EASS. 

Table 3: Option comparison table. Source: Eurostat 

+ +  Very positive impact 
Positive impact 
+ 
Neutral impact 
0 
Negative impact 
- 
Very negative impact 
- - 
ST = short term; LT = long 
term 

Type of impact 
Time horizon 
Effectiveness re 
objectives 

Option 

Data needs 
Coherence 
Burden 

Efficiency re objectives 
EU objectives 

Other criteria 

CAP etc. 
ESS 
Risks 
Indirects 

1: Baseline 
- No EU 
action 
ST 
- - 
- - 
+ 
- 
- - 
- - 
- - 
- - 

LT 
- - 
- - 
0 
- - 
- - 
- - 
- - 
- - 

2: Prolong 
FSS 
Regulation 
LT 
ST 
- - 
- 
- - 
- 
- - 
- 
- - 
- 
- - 
- 
- - 
- 
- 
+ 
- - 
- 

3: Single 
framework 
regulation 
LT 
ST 
+ + 
+ 
+ + 
+ + 
+ + 
+ 
+ + 
+ 
+ + 
+ 
+ + 
+ + 
+ 
- - 
+ + 
+ 

4: Two-step 
integration 

ST 
+ 
+ 
+ 
+ 
+ 
+ + 
0 
+ 

LT 
+ + 
+ + 
+ + 
+ + 
+ + 
+ + 
+ 
+ + 

44 

 
 
 
 
Stakeholders 

- - 
Users 
Producers 
- 
Respondents  + 

- - 
- 
- 

- 
0 
0 

- - 
- 
- 

+ 
+ 
+ 

+ + 
+ 
+ 

+ 
+ 
+ 

+ + 
+ 
+ 

7. MONITORING AND EVALUATION 

Irrespective of  the  option  to  be  chosen,  it  will  be  important to  work  on the  monitoring  and 
evaluation  framework  to  reflect  the  changes  in  the  EASS,  to  improve  its  effectiveness  in 
measuring  performance,  and  to  align  with  similar  work  for  European  Statistics  in  general. 
Such work should build on the considerable experience and systems established to date. The 
following  actions  are  foreseen  to  monitor  and  evaluate  the  objectives  of  the  strategy  for 
agricultural statistics towards 2020 and beyond. 

Annual compliance monitoring about the statistics produced 

Eurostat conducts annual compliance assessments. An integral part of these assessments is a 
review of the situation with data producers and follow-up actions in case of non-compliance.  

In accordance with the requirements of EU legislation, countries are requested to provide the 
Commission with relevant figures on agricultural statistics. These figures are subject to strict 
transmission deadlines which must be respected for the good management, dissemination and 
usefulness  of  EU  statistics,  as  missing  or  incomplete  data  lead  to  shortcomings  in  the 
availability  of  information  (i.e.  it  is  not  possible  to  calculate  EU  aggregates  and  to  publish 
data according to planned time schedules).  

Regulation (EC) No 223/2009 which is the basic legal framework for the functioning of the 
European  Statistical  System  and  for  all  sectoral  legislation  for  the  production  of  European 
statistics has been amended and adopted on 29 April 2015. The amended Regulation's Article 
12 (Quality), paragraphs 3 and 3a, defines Eurostat's approach to reporting on the accuracy of 
national data and quality aspects: 

"Member States shall provide the Commission (Eurostat) with reports on the quality of data 
transmitted,  including  any  concerns  they  have  regarding  the  accuracy  of  the  data.  The 
Commission  (Eurostat)  shall  assess  the  quality  of  the  data  transmitted,  on  the  basis  of 
appropriate  analysis,  and  shall  prepare  and  publish  reports  and  communications  on  the 
quality of European statistics. 

In  the  interest  of  transparency,  the  Commission  (Eurostat)  shall,  where  appropriate,  make 
public its assessment of the quality of national contributions to European statistics." 

While  timeliness,  punctuality  and  completeness  are  already  important  factors  in  the  annual 
compliance  assessments  to  ensure  a  timely  dissemination  of  agriculture  statistics,  more 
attention will be paid to these and other quality dimensions in order to ensure confidence in 
the statistics produced by the ESS. 

45 

 
 
 
 
 
 
 
 
 
 
 
Continuous improvement of  the  EASS: identification of new data  needs  and  new data 
sources, improvement of coherence, reduction of burden 

At  present,  Eurostat  conducts  annual  hearings  with  policy  DGs  of  the  Commission.  An 
important  point  for  these  hearings  is  the  exchange  of  information  on  the  respective  work 
programmes. They provide a formal platform for stating upcoming needs for new statistics, 
and to review the usefulness of the available statistics. 

Further  collaboration  with  the  policy  DGs,  NSIs  and  ONAs  will  take  place  at  different 
hierarchical  levels  in  regular  Working  Group  meetings  and  seminars,  Directors'  Group 
meetings, ESSC meetings, and through frequent bilateral exchanges. Particular attention will 
be  focused  on  the  identification  of  administrative  data  and  other  information  sources 
maintained under EU legislation, and the assessment of their suitability for the production of 
statistics  in  order  to  establish  agreements  for  their  stability,  accessibility  and  eventual 
adaptation  to  better  fit  statistical  requirements.  Furthermore,  periodic  surveys  and  analyses 
such as those referenced in the previous chapters will be conducted to identify potential for 
improvement  of  European  agricultural  statistics  and  for  reductions  of  its  burden,  e.g.  by 
abolishing  variables  with  a  low  cost-benefit  ratio,  made  possible  by  a  more  flexible  legal 
framework. Finally, quality reports by Member States, in which they are obliged to report on 
the costs and burdens of data collection and production, will be crucial in evaluating the cost-
effectiveness of the EASS. 

These actions are expected to monitor and evaluate the specific strategy objectives "Produce 
high-quality  statistics  that  meet  users'  needs  efficiently  and  effectively",  "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",  and  "Produce  more  statistics  while 
lowering  the  burden  on  respondents  by  exploring  alternative  data  sources  and  efficiency 
improvement techniques". 

Triennial monitoring reports 

In order to monitor the functioning of the renewed EASS and to ensure its fulfilment of the 
REFIT goals of simplification and burden reduction, a regular reporting on the functioning of 
the  overall  system  will  be  carried  out  every  three  years.  These  reports  will  include  the  key 
performance indicators listed below: 

46 

 
 
 
 
 
 
Table 4: Key performance indicators and targets. Source: Eurostat 

Key performance indicators 

Targets 

KPI1  Percentage of users that rate as "Very 
good" or "Good" the overall quality of 
the European agricultural statistics 
provided by Eurostat. 

KPI2  Percentage of users that rate as "Very 
good" or "Good" the timeliness of 
European agricultural statistics for their 
purposes. 

 

60% 

 

60% 

KPI3  Percentage of users that rate as "Very 

 

60% 

good" or "Good" the comparability of 
European agricultural statistics among 
regions and countries.  

Source: Annual user satisfaction survey 
(USS) carried out by Eurostat 

KPI4  Number of data extractions (in millions) 

made by external users from Eurostat 
public databases of agricultural 
statistics via the Eurostat website.  

Source: Monitoring reports on Eurostat 
electronic dissemination 

KPI5  Punctuality of European agricultural 

statistics:  average number of days of 
advance (positive) or delay (negative), 
in comparison to the legal target.  
Source: Monitoring of the data transmission 
and dissemination by Eurostat 

  Decrease as compared to 
previous year does not 
exceed 5% 

  No delays  
  Advance in comparison to 
legal target is maintained 
from year to year 

KPI6  Inventory of new data needs and when 

  A draft reply to new data 

they have been answered 

KPI7  Inventory of legal acts 

needs received in year N is 
discussed with the expert 
group Directors of 
Agricultural Statistics in N+1 

  Number of basic legal acts 
for agricultural statistics is 
reduced to 3 by 2022. 

KPI8  Number of meetings 

  Annual hearing with policy 

Specific objectives 

Operational 
objectives 

Serve new and emerging data needs flexibly by 
Produce high-quality 
statistics that meet 
users' needs efficiently 
and effectively 

Statistics fulfil the 
quality requirements 
for European 
statistics 

Increase the flexibility 
and reaction speed of 
the agricultural statistics 
system 

Quick adaptation of 
data collections in 
case of emerging 
needs 

Improve the integration 
between agricultural, 
forestry, land use and 
environmental statistics 

Develop a responsive 
and responsible 
governance structure 
for agricultural statistics 

By 2022, all 
agricultural statistics, 
except on Economic 
accounts for 
agriculture, are 
produced und the 
framework created 
under this strategy. 
Expert groups: annual 
meetings and regular 
information and 
consultation 

Policy DGs: Annual 
hearings and regular 
information and 
consultation 

KPI9  Number of consultations of expert 
groups on legal proposals 

Make agricultural statistics data collections harmonised and coherent by 
Use of standard 
Improve the 
concepts, definitions 
harmonisation and 
and code lists. 
coherence of European 
agricultural statistics 

lists 

KPI10Inventory of concepts, definitions, code 

DGs 

  Annual meeting of expert 
groups (Directors of 
Agricultural Statistics, and 
established Working Groups) 
For each legal proposal, at 
least two consultations of 
expert groups 

 

  By 2022, all data collections 
use standard concepts, 
definitions and code lists. 

47 

 
 
 
 
 
Ensure that burden is 
lowered 

Address the burden of providing data by 
Produce more statistics 
while lowering the 
burden on respondents 
by exploring alternative 
data sources and 
efficiency improvement 
techniques 

KPI11 Number of operators (farms, dairies, 
slaughterhouses, …) replying to 
questionnaires for agricultural statistics, 
annually 

 

KPI12 Percentage of data elements extracted 

 

from administrative sources 

KPI13 Percentage of data elements reused 

 

from existing statistical surveys or 
registers 

For the EU as a whole, the 
total number of contacts with 
respondents as compared to 
2017 benchmark is: 90% in 
2022, 80% in 2027. 
For the EU as a whole, 
percentage of data elements 
extracted from administrative 
sources as compared to 
2017 benchmark increased 
by 10% in 2022, 20% in 
2027. 
For the EU as a whole, 
percentage of data elements 
reused from statistical 
surveys or registers as 
compared to 2017 
benchmark increased by 5% 
in 2022, 10% in 2027. 

Evaluation 

The second triennial monitoring report will be replaced by a retrospective evaluation of the 
renewed  EASS,  conducted  according  to  the  European  Commission's  evaluation  guidelines. 
This  could  also  constitute  a  basis  in  case  further  revisions  of  the  legislation  would  be 
envisaged. 

48 

 
 
 
 
 
ANNEXES 

Annex I: Procedural information 

Basic information 

Name of the initiative: A strategy for agricultural statistics towards 2020 and beyond 

Lead DG: Eurostat 

Agenda Planning number: 2015/ESTAT/035 

Organisation and timing 

An  Interservice  Impact  Assessment  Steering  Group  (IASG)  was  set  up,  to  which  the 
following Directorates-General were invited: the Secretariat-General (SG), the Legal Service 
(SJ),  Agriculture  and  Rural  Development  (AGRI),  Budget  (BUDG),  Climate  Action 
(CLIMA), Environment (ENV), Joint Research Centre (JRC), Regional Policy (REGIO), and 
Health and Food Safety (SANTE). The IASG met three times: 

  On 18/06/15 with Eurostat, SG, DG AGRI, DG BUDG, DG CLIMA, DG ENV, JRC 
and  DG  SANTE  participating,  to  discuss  the  strategy  and  the  open  public 
consultation. 

  On  07/12/2015  with  Eurostat,  SG,  DG  AGRI,  DG  ENV  and  DG  SANTE 
participating, to  discuss the draft impact  assessment report and  the draft evaluations 
staff working document, with documents sent on 27/11/15. 

  On  21/01/2016  with  Eurostat,  SG,  DG  AGRI,  DG  ENV  and  JRC  participating,  to 
discuss  the  final  draft  impact  assessment  report  and  the  final  draft  evaluations  staff 
working document, with documents sent on 13/01/16. 

In  the  interim,  written  communication  was  conducted  on  documents  for  the  open  public 
consultation  (launched  on  18/08/15),  a  note  on  evidence  and  evaluations  for  agricultural 
statistics data needs (02/09/15; the note is now part of the impact assessment report and the 
evaluations  staff  working  document),  and  the  inception  impact  assessment  for  the  strategy 
(16/10/15,  consultation  on  revised  version  following  IASG,  SG  and  College  feedback 
is  now  published  since  16/12/15  on  http://ec.europa.eu/smart-
01/12/15; 
regulation/roadmaps/index_en.htm).  Following  the  third  meeting  of  the  IASG,  the  Impact 
Assessment Report was submitted to the Regulatory Scrutiny Board on 03/02/16. 

the  IIA 

Regulatory Scrutiny Board (RSB) 

The RSB examined the Impact Assessment Report for the strategy for agricultural statistics 
towards 2020 and beyond on 02/03/16 and gave a positive opinion, with a recommendation to 
further improve the report in the following key aspects:  

1)  Strengthen  the  links  with  the  REFIT  evaluation  conclusions  and  stress  (and  quantify 
wherever possible) the simplification/burden reduction potential of the proposed solution;  

2)  Deepen the analysis as regards impacts on particular Member States in view of the potential 
simplification/cost savings on the one hand and on the other the necessary financial outlays 
to adapt the national statistical systems to the new framework;  

3)  To allow for a future evaluation of the initiative, include benchmarks against which the key 

performance indicators will be assessed.  

49 

 
 
The  report  has  been  adapted  according  to  these  recommendations  and  further  technical 
comments. 

Evidence and sources 

The  specific  evidence  sources  used  are  referenced  throughout  the  document  whenever  they 
are  used.  In  particular,  the  main  problems  of  the  EASS  of  unfulfilled  data  needs,  a  lack  of 
coherence and harmonisation and a too high perceived burden are evidenced by substantial, 
regular, in-depth stakeholder consultations and events since at least 2008 (see also Annex II), 
and  by  certain  outside  studies.  The main  quantitative  analysis  of  administrative  burden  and 
cost  impacts  is  based  both  on  stakeholder  information  (targeted  questionnaires,  financial 
statements,  legal  reporting  obligations  etc.)  and  internal  Eurostat  database  simulations  and 
calculations as described in the relevant passages. 

The  stakeholders'  issues  with  the  EASS  are  considered  to  be  represented  and  evidenced 
faithfully  and  completely  in  the  stakeholder  consultations  and  events.  In  fact,  these  regular 
seminars  and  meetings  mainly  exist  to  create  an  exchange  between  Eurostat  and  the  main 
data users, data producers and partly also data respondents of European agricultural statistics, 
and it is in Eurostat's evident own interest to produce relevant and high-quality data. 

For the same reasons, the quantitative stakeholder information is considered to be robust and 
as  complete  as  sometimes  very  different,  varied  and  complex  statistical  data  collection  and 
production  systems  permit;  stakeholders  are  also  in  many  cases  legally  obliged  to  provide 
exact  numbers.  The  Eurostat  simulations  have  also  been  conducted  to  the  high  standard 
required  by  the  ESS  Code  of  Practice.  However,  uncertainties  inherent  in  the  EASS  (e.g. 
different  technical  or  business  standards  on  different  farms  even  in  the  same  country, 
particularly long validation processes etc.) may preclude estimating burden and cost savings 
exactly beyond a certain resolution. Nevertheless, savings are expected to be in the estimated 
magnitudes and relations.  

External expertise 

This impact assessment has been conducted internally within Eurostat. Other sources such as 
previous  internal,  Commission  or  NSI  surveys,  expert  advice  and  estimates,  and  external 
studies of relevance to the impact assessment are referenced where appropriate.  

However, considering the role of statistics in society, it is mainly the users and producers of 
statistical  data  that  have  sufficient  in-depth  knowledge  to  give  a  solid  view  on  the  state  of 
play in the domain. These stakeholders have been working closely with Eurostat in the last 
years in a series of activities aiming at further developing agricultural statistics. With this in 
mind, the reliability of the findings can be seen as quite high.  

Limitations 

  Despite  considerable  input  from  users  about  their  data  needs,  more  detailed 
information  about  the  ways  the  data  are  used  would  be  needed  for  a  better 
understanding of how requests can be fulfilled in the most efficient manner; 

  Eurostat  is  aware  that  data  are  not  always  coherent  and  of  sufficiently  high  quality. 
However, there are no studies on how much this issue impacts the use of agricultural 
statistics,  on  how  users  take  decisions  on  how  to  utilise  the  statistics  and  which 
actions they take to improve the analyses made; 

50 

 
 
  The  burden  of  statistical  surveys  on  farmers  as  respondents  is  often  mentioned  as  a 
negative  aspect  of  statistics.  However,  there  are  no  studies  that  would  provide  full 
quantification  of  the  total  costs  of  producing  agriculture  statistics,  and  more  work 
would  be  required  to  fully  assess  the  cost/benefit  ratio  between  the  potential  added 
support and the actual burden of statistical surveys. 

51 

 
 
 
 
 
Annex II: Stakeholder consultation 

Summary of stakeholder consultations 

The  development,  production  and  dissemination  of  European  agricultural  statistics  is 
achieved  by  Eurostat  through  close,  coordinated  and  regular  cooperation  in  the  European 
Statistical System, building upon a long partnership between Eurostat and the NSIs as well as 
all other relevant authorities. 

The main categories of stakeholders of European agricultural statistics are producers (NSIs 
and  other  national  authorities  as  well  as  Eurostat),  respondents  (farmers,  farmers' 
organisations  and  businesses)  and  users  (public  and  private  decision  makers,  in  particular 
European  Commission  DGs;  researchers  and  journalists).  They  have  been  consulted 
extensively on problems and desired changes in the status quo, their data needs and priorities, 
possible  policy  options  to  solve  the  problems,  impacts  of  suggested  actions,  and  the 
formulation of the strategy specifically, as the following overview table shows. The main fora 
for these consultations have been the Standing Committee for Agricultural Statistics (CPSA) 
meetings  and  seminars  and  its  successor's,  the  Directors'  Group  for  Agricultural  Statistics 
(DGAS)  meetings  and  seminars  (for  NSI  directors  of  agricultural  statistics,  international 
organisations, farmers' organisations, data respondents, data users and others), the European 
Statistical  System  Committee  (ESSC)  meetings  (for  NSI  directors-general),  and  regularly 
scheduled consultations and hearings (for Commission DGs). 

Table  AII.1:  Overview  of  stakeholder  consultations  on  the  agricultural  statistics 
strategy 2020 

Consultation on 
problems and 
changes 
ESSC Meeting May 
2014 

Consultation on 
needs and priorities 

Consultation on 
options and impacts 

CPSA Meetings and 
Seminars since 2009 

DGAS Meeting July 
2015, ESSC Meeting 
November 2015 

Open public 
consultation August-
November 2015 

Producers 

Respondents  

CPSA Seminars since 2009 

Users 

Open public consultation August-November 2015 
Written consultations and Hearings since 2014 

to 

from 

18/08/15 

22/11/15 

conducted 

In addition to the consultations in the main fora, an open public consultation on the strategy 
was 
via 
http://ec.europa.eu/eurostat/about/opportunities/consultations/eass.  The  link  was  distributed 
widely  to  all  agricultural  statistics  working  group  contacts,  stakeholder  DGs,  trade 
organisations,  scientists  etc.,  and  responding  to  the  questionnaire  was  highly  encouraged. 
Contributions  were  explicitly  sought  from  users  of  European  agricultural  statistics,  survey 
respondents  and  citizens,  as  well  as  from  producers  of  European  statistics  and  other 
statisticians. Anyone with an interest in the topic was thus invited to express their views on 
the identified questions, as  well as  to present their  opinions as  to  what additional measures 
could  be  appropriate.  Furthermore,  an  Inception  Impact  Assessment  for  the  strategy  was 
developed within Eurostat and with support from the IASG and opened for feedback from the 
public, of which none has been received for this document. 

52 

 
 
 
 
Therefore, Eurostat considers to have reached all relevant agricultural statistics stakeholders 
by one or more of the means described. The minimum standards for consultation of interested 
parties by the Commission47 are considered to be met for the following reasons. 

Table  AII.2:  Reasons  the  agricultural  statistics  strategy  2020  consultations  meet  the 
Commission minimum standards 

Minimum standard  Reasons it was met 
Clear content 

Target groups met 

Publication 

Time limit 

Acknowledgement 
and feedback 

Eurostat  provided  extensive  information  on  the  context,  objectives, 
options and issues of the agricultural statistics strategy as well as clear 
contact details, deadlines and procedural information to all partners in 
consultations,  communications,  meetings,  seminars  and  hearings,  as 
the related documents and minutes show. 
Eurostat reached out to those affected by the strategy, those involved 
in  implementing  the  strategy,  those  interested  in  the  strategy,  and 
others  potentially  affected  by  the  strategy  in  the  ways  described 
above. 
Eurostat  reached  agricultural  statistics  stakeholders  either  in  more 
formal fora to which stakeholders were invited or by the open public 
consultation  published  on  "Your  Voice  in  Europe",  as  described 
above. 
Eurostat  clearly  communicated  relevant  deadlines  for  different  steps 
of  the  strategy  development  process  to  stakeholders,  as  the  related 
documents and minutes show. The open public consultation ran from 
18/08/14 to 22/11/15, i.e. for more than the recommended 12 weeks. 
Eurostat  took  stakeholder  comments  and  opinions  extensively  into 
account during the development of the strategy and provided further 
feedback  directly  at  the  relevant  meetings  or  afterwards  in  written 
communication,  as  the  related  documents  and  minutes  show.  The 
summary  results  of  the  open  public  consultation  (see  below) 
influenced further refining of the strategy. 

Details of stakeholder consultations 

Chronologically,  the  main  stakeholder  consultation  events  leading  to  the  inception, 
development  and  refining  of  the  agricultural  statistics  strategy  towards  2020  and  beyond 
were: 

1.  United Nations Global Strategy on Agricultural Statistics 2008 

One  of  the  outcomes  of  the  2007  International  Statistical  Institute  Conference  on 
Agricultural Statistics was a consensus regarding the challenges of applying statistics 
to several issues in agricultural development, such as food security, the use of food for 
biofuels,  and  environmental  impacts  of  agriculture.  At  the  same  time,  a  general 
decline  in  the  overall  quality  and  availability  of  agricultural  statistics was  observed. 
These  concerns  were  discussed  during  the  2008  meeting  of  the  United  Nations 
Statistical Commission (UNSC), leading to the formation of a working group assigned 

47 COM(2002) 704 final 

53 

 
 
 
 
                                                            
to  draft a strategic plan to improve world agricultural statistics. The working group, 
under  the  guidance  of  the  United  Nations  Statistics  Division  (UNSD),  included  the 
World Bank, the United Nations Food and Agriculture Organization (FAO), Eurostat, 
the United States Department of Agriculture (USDA), and the International Statistical 
Institute (ISI). Using input from the working group and other stakeholders, the World 
Bank  with  the  help  of  heads  and  representatives  of  national  statistical  offices  and 
ministries of agriculture from 27 countries, the FAO, the International Monetary Fund 
(IMF), Eurostat, OECD, and the USDA prepared a paper to be discussed at the 2009 
meeting of the UNSC, which concluded that a global strategy was needed to improve 
agricultural  statistics.  The  technical  content  and  strategic  directions  of  the  Global 
Strategy were endorsed by the 41st session of the UNSC. The final strategy document 
contains  a  minimum  list  of  agricultural  statistics  which  also  has  validity  for  EU 
member states.  

2.  Study on agri-environmental indicators 2009 

Eurostat commissioned a study on “Direct and indirect data needs linked to the farms 
for agri-environmental indicators”, carried out by Wageningen University, to set up a 
sustainable system for collecting data from farmers and other sources that would serve 
European  and  national  statisticians  to  create  agri-environmental  indicators.  These 
would  in  turn  serve  policy  makers,  agricultural  and  environmental  researchers,  and 
observers of climate change and other environmental issues linked to agriculture. The 
different data needs were to be analysed and the best way to collect them identified. 
The aim was to receive suggestions on a future data collection setup that met as many 
of the identified information needs as possible and that was optimally adapted to user 
needs, available resources and respondent burden. 
During the work, all Commission policies relating to the subject were identified and 
analysed. Several task forces were formed with experts from Member States and user 
stakeholders,  questionnaires  were  sent  to  the  competent  authorities  in  the  countries, 
and  at  the  end  a  seminar  was  organised,  with  more  than  60  participants  from  the 
research community, policy makers and statisticians from Member States and several 
Commission DGs represented. The result of the project is a list of all data needed to 
make policy related to agri-environmental issues, set up in such a way that data can be 
reused  wherever possible  and with potential  data sources identified,  with the aim of 
avoiding double collection.48 The results of the project have been confirmed by both 
users and producers of agricultural statistics and are also used by FAO and OECD. 

3.  CPSA/DGAS Seminars 2009-Present 

Eurostat  has  organised  a  series  of  seminars  connected  to  its  regular  CPSA/DGAS 
meetings  since  2009,  in  order  to  understand  where  further  developments  of 
agricultural  statistics  are  needed.  These  seminars  have  been  open  to  interested 
stakeholders  besides  the  normal  CPSA/DGAS  meeting  participants,  including 
farmers' unions, research institutions and private companies. The titles of the seminars 
have  ranged  from  "New  needs,  challenges  and  the  changing  role  of  statisticians" 
(2009,  54  participants  from  NSIs  and  other  Member  State  organisations,  as  well  as 
DG AGRI, JRC and FAO) to "Agriculture and environment  – best practices in farm 

48 Farm data needed for agri-environmental reporting (DOI: 10.2785/12758) 

54 

 
 
 
 
 
 
                                                            
surveys" (2012, 41 participants from Member States and DG AGRI, DG CLIMA, DG 
ENV  and  JRC)  and  "Appropriate  statistics  for  farming  in  the  EU"  (2014,  52 
participants from Member States, DG AGRI and FAO). 

4.  Commission consultation 2014 

Eurostat  asked  the  main  Commission  users  of  agricultural  statistics  for  their  most 
important  data  needs.  A  similar  request  was  sent  to  the  European  Environment 
Agency  (EEA)  in  2015.  Most  of  the  statistical  data  presently  collected  by  Eurostat 
have  been  confirmed  as  still  being  needed,  with  some  very  limited  exceptions.  In 
addition, several new needs were specified. 

5.  Strategy development and endorsement 2014-2015 

Based  on  the  problems  and  needs  expressed  by  the  stakeholders  over  the  years, 
Eurostat  initiated  the  planning  process  for  a  future  system  of  European  agricultural 
statistics  in  early  2014,  starting  with  internal  meetings,  discussions  and  draft 
documents.  The  CPSA/DGAS  endorsed  Eurostat's  approach  of  preparing  a  strategy 
for agricultural statistics towards 2020 and beyond at its meeting in April 2014.49 The 
ESSC  approved  the  approach  at  its  meeting  in  May  2014.  The  performance  of  the 
current EASS, lessons learnt and main data needs were analysed on the basis of expert 
advice, research projects and by contacting the main stakeholders in the Commission, 
while  national needs, according  to  the subsidiarity principle, were  handled by NSIs. 
Following  that,  a  paper  on  the  strategy  was  developed  by  Eurostat  and  further 
elaborated  and  refined  by  an  extended  CPSA  partnership  group  consisting  of  three 
subgroups on 1) the "what" of data needs, 2) the "how" of data collection modes, and 
3)  implementation  specific  issues,  and  by  the  CPSA  itself  at  its  November  2014 
meeting. Further, continuous stakeholder consultations helped Eurostat to finalise the 
strategy,  and  it  was  endorsed  by  the  DGAS  in  June  201550  and  by  the  ESSC  in 
November 2015.51 

6.  Open public consultation 2015 

The open public consultation, conducted as detailed above between 18 August and 22 
November  2015  on  the  "Your  Voice  in  Europe"  platform  and  distributed  widely, 
received  53  responses,  mainly  from  NGOs  and  interest  groups  (20),  Member  State 
public  authorities  (12),  researchers  (8),  businesses  (8)  and  others.  This  is  not  a  high 
number, but a wide range of opinions was represented, in many cases by stakeholders 
who are not reached by Eurostat's main channels of stakeholder consultation such as 
DGAS  Seminars.  Most  main  stakeholders  have  other  venues  to  express  their  needs 
where  they  have  done  so,  which  was  fully  taken  into  account.  Therefore,  the  inputs 
were useful and were considered proportionately. However, they were not split further 
by respondent group due to the groups' non-representative sizes. 

Respondents  said  that  they  use  almost  all  parts  of  the  EASS  for  purposes  such  as 
communication, policymaking and research. They see the EASS as meeting their data 

49 Document CPSA/718 for the CPSA Meeting April 2014 
50 Document DGAS/2 for the DGAS Meeting 2015 
51 Minutes for the ESSC Meeting November 2015 

55 

 
 
 
 
 
 
 
 
 
                                                            
needs moderately well and with an acceptable burden, but see the system as inflexible 
and  partly  incoherent.  Comments  focused  on  data  needs  for  land  use  and  cover, 
fertiliser use, production, environmental and climate change data; serving data needs 
better  by  integration,  harmonisation  and  a  new  legal  basis  for  European  agricultural 
statistics, which would also improve consistency and coherence; burden reduction by 
data integration, information and communication technology; and improving response 
rates  by  reminding  farmers  that  CAP  funding  requires  data.  Other  problems  of  the 
EASS  were  seen  in  a  lack  of  timeliness  and  in  missing  data.  These  concerns  and 
possible  solutions,  insofar  as  they  were  not  already  part  of  the  strategy,  were  taken 
account of. Respondents saw option 1 as very negative, option 2 as neutral-negative, 
option  3  as  positive  with  a  higher  burden  than  in  the  status  quo,  and  option  4  as 
positive with a slightly higher burden than in the status quo. Option 4 was preferred 
by far. 

7.  Strategy implementation 2015-Present 

Intensive consultations with stakeholders on the implementation of the strategy have 
already taken part in the FSS and Crop Statistics Working Group meetings in October 
2015 and are planned in early spring 2016 for the Animal Production Statistics, FSS 
and Crop Statistics WG Meetings. Additional written consultations and exchanges of 
views  are  being  organised  as  necessary.  The  DGAS  (meeting  scheduled  for  June 
2016) will be consulted before the ESSC consultation (foreseen for autumn 2016). It 
is planned for the Commission to submit a Regulation implementing the 1st step of the 
strategy to the European Council and the European Parliament by the end of 2016. 

Results 

The  main  results  of  the  above  consultations,  forming  the  core  of  the  agricultural  statistics 
strategy 2020 and subsequently of this impact assessment, are threefold: 

  The  current  European  Union  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.  Moreover,  the  FSS  Regulation  which  is  a 
central piece in the current overall European Union agricultural statistics system will 
cease to provide any statistical information as of 2018. 

These  new  data  needs  mainly  stem  from  new  developments  in  agriculture,  revised 
legislation  and  changing  policy  priorities,  in  particular  the  recently  reformed  CAP 
which  is  applied  by  DG  AGRI  for  actions  such  as  “greening”  and  climate  change 
objectives  and  also  influences  actions  in  DG  ENV,  DG  CLIMA,  DG  REGIO  etc., 
such as environmental accounts or biodiversity policies.52 These policies require high-
quality data to enable evidence-based policy design, implementation and evaluation. 
Key stakeholders expressed this need at multiple specific occasions in the last years: 

a.  DG  AGRI  evaluated  its  use  of  FSS  data  to  identify  priority  characteristics, 
desired frequencies and other required features in 2011. It was found that the 
FSS  is  a  unique  source  of  information  for  a  wide  range  of  farm  structural 

52 Minutes of the ESSC Meeting May 2014  

56 

 
 
 
 
 
 
                                                            
elements in the EU, and its data are used in a number of publications and for 
evaluations  of  different  policies,  sectors  and  impacts.  However,  many  more 
data  were  needed  on  environmental  aspects,  especially  with  increasing 
“greening” requirements in the then-upcoming CAP reform. 

b.  Member  State  representatives  at  the  CPSA  meeting  in  November  2013 
confirmed and supported specific new data needs identified for the 2016 and 
future  FSS  following  the  CAP  reform.53  Moreover,  representatives  discussed 
and welcomed specific requirements for new FSS legislation at this meeting.54 

c.  The Director-General of DG AGRI stressed at a presentation for the ESSC in 
May  2014  that  relevant,  timely  and  comprehensive  agricultural  statistics  are 
needed for designing, monitoring and evaluating the CAP and its expenditure 
and that the need  for high-quality  agricultural statistics is  stronger than  ever, 
enumerating several specific data needs for different policies and actions. 

d.  Several  data  users’  specific  needs  were  queried  and  then  presented  and 
confirmed  at  the  CPSA  meeting  in  November  2014,  including  main 
Commission  data  users'  and  Member  States'.55  56  Since  then,  other  users, 
among them the EEA, have communicated their data needs to Eurostat. 

Furthermore,  stakeholders  underlined  that  new,  changing  and  emerging  as  well  as 
existing, stable data needs must be answered in a more flexible and integrated way to 
react faster to new developments, provide data in a timelier manner and account for 
different data collection modes and situations in Member States  with  a fast process. 
Examples  of  agricultural  data  that  have  recently  increased  in  importance  are  agri-
environmental indicators. 

  The data collections are not harmonised and coherent because new data needs are 
emerging,  legislation  has  been  developed  separately  over  many  years,  and  there  are 
partly different definitions and concepts  in  different agricultural  areas. The need  for 
harmonisation and coherence was expressed several times recently: 

a.  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  2013.57 
This need has been echoed by other users such as the research community for 
years. 

b.  Eurostat's  Internal  Audit  Service  (IAS)  recommended  in  its  2013  audit  on 
statistical  processes  of  agriculture  statistics  that  voluntary  data  collections 
should be formalised, all variables should be applied consistently by Member 
States,  Member  State  compliance  with  quality  requirements  should  be 
documented and monitored systematically, completeness of disseminated data 
should be increased, and using administrative and other data sources should be 
considered in view of the identified issues. 

53 Minutes of the CPSA Meeting November 2013 
54 Document CPSA/706 for the CPSA Meeting November 2013 
55 Document CPSA/732 for the CPSA Meeting November 2014 
56 Document CPSA/732 for the CPSA Meeting November 2014, Annex I 
57 Minutes of the CPSA Meeting November 2013 

57 

 
 
 
 
 
                                                            
c.  The Eurostat User Satisfaction Survey in 2014, a wide consultation open to the 
general  public,  revealed  that  only  about  half  of  respondents  rated  the 
completeness and comparability of European agriculture and fishery statistics 
as  "good"  or  "very  good",  below  the  Eurostat  average  for  each  criterion.58 

  The  burden  of  providing  data  is  perceived  as  too  high  because  data  needs  are 
increasing, data collection is not harmonised, and resources continue to shrink at EU 
and national level. This burden was confirmed as jeopardising data collection and data 
quality.  In  several  recent  exchanges  with  data  providers,  ways  of  reducing  it  and 
increasing the cost-benefit ratio have been discussed: 

a.  The  topic  was  discussed  in  depth  at  the  CPSA  November  2013  meeting. 
Several ways to reduce the burden such as improving the use of administrative 
data  registers,  reusing  data  collected  once  multiple  times,  and  harmonising 
concepts  and  definitions  across  legislation,  domains  and  databases  were 
proposed.59 

b.  Eurostat  mapped  common  characteristics  and  data  flows  in  agricultural 
statistics for the CPSA November 2014 meeting, in order to find opportunities 
to reduce the burden.60 

58 Report on the Eurostat User Satisfaction Survey 2014 
59 Minutes of the CPSA Meeting November 2013 
60 Document CPSA/732 for the CPSA Meeting November 2014, Annex II 

58 

 
 
 
 
 
 
 
                                                            
Annex III: Who is affected by the initiative and how 

As  stated  in  the  impact  analysis  for  options  3  and  4,  the  practical  implications  of 
implementing the agricultural statistics strategy for 2020 and beyond for data producers, i.e. 
NSIs, ONAs and Eurostat, and for data respondents, i.e. farmers and agricultural businesses, 
would be as follows: 

  Data  producers  would  have  to  adapt  their  data  collection,  production  and 
dissemination systems to new or different variables in surveys and to more integrated 
data  collection  e.g.  by  linking  administrative  and  statistical  databases,  which  would 
create some initial burden and costs. In the midterm, they would benefit from reduced 
costs of data collection, a more smoothly integrated operation of the EASS, continued 
financial support, and better statistical products (see chapters 5.1 and 5.2.) 

  Data respondents would in many cases benefit from not being surveyed anymore or 
surveyed  much  less  frequently  and  exhaustively  due  to  the  changed  systems  e.g. 
allowing  to  pre-fill  questionnaires  with  administrative  data  or  to  reduce  survey 
frequencies. Those holdings still being surveyed would not experience much change 
in their operations apart from having to respond to partly different questionnaires than 
now,  which  could  oblige  them  to  perform  additional  tasks  to  collect  the  necessary 
data. But this is expected to be balanced out by questionnaires that are shortened and 
relieved  of  the  most  burdensome  variables  (see  chapters  5.1  and  5.2.)  All  eligible 
respondents  would  benefit  from  continued  guaranteed  financial  CAP  support  and 
better policy delivery due to better data. 

As  to  the  effects  on  EU  Member  States,  especially  in  the  short  term  when  the  biggest 
financial outlays will be needed to implement the proposal, the  new Member States and the 
Mediterranean countries are estimated to be more affected than the others. There are going to 
be two main impacts of the new legislation: 

1)  The  number  of  farms  that  are  included  in  the  agricultural  census  will  be  reduced  by 
potentially 30%, which corresponds in absolute terms to more than 3.5 million from a total of 
almost  12  million  in  2010.  Current  analyses  show  that  Romania,  Italy,  Hungary,  Poland, 
Greece,  and  Bulgaria  would  be  most  impacted  and  thus  stand  to  gain  most  in  budgetary 
savings (their total savings could be up to 48 million euro according to Eurostat estimations) 
as can be seen from table 2. 

Some  of  these  Member  States  will  need  to  carry  out  an  additional  sample  survey  on  small 
farms  below  the  cut-off  threshold  in  order  to  allow  estimating  their  impact  on  agricultural 
production and rural society. Using the information from table 2 and adding the fixed costs 
for  setting  up  a  survey  provided  by  the  countries,  the  costs  for  the  six  Member  States 
mentioned  above  would  amount  to  only  about  8  million  euros,  thus  clearly  indicating  the 
huge costs savings involved in the reduction. 

2) The possibility of collecting data using sub-samples will be greatly increased. This means 
that it will be possible to target only specific farms in the surveys. Setting up these surveys 
will be greatly improved by the introduction of a unique farm identifier or a farm register, in 
close  collaboration  with  keepers  of  administrative  registers.  Such  a  system  will  be  fully 
voluntary  for  the  Member  States,  but  will  require  initial  investments,  both  in  National 
Statistical Authorities and in the authorities owning the administrative registers. 

59 

 
 
However, all Member States will be affected by the required adaptations to the new survey 
system in the short and medium term. Eurostat has no evidence that any Member State would 
be more strongly impacted than others in this regard. 

60 

 
 
 
 
 
Annex IV: Impact analysis methodology 

Analysis of the potential impacts of the different policy options for the future EASS has been 
based on the methodology proposed in the Better Regulation Guidelines of the Commission. 
As a first step, potential impacts were identified in relation to the different options. This was 
followed by a primarily qualitative analysis in order to identify the more important impacts of 
the  various  options.  This  analysis  was  complemented  with  an  analysis  of  information 
linked  to  the 
available  from  a  number  of  monitoring  and  evaluation  documents 
implementation  of  the  current  EASS  as  well  as  from  a  series  of  consultations  with 
stakeholders  of  EU  agricultural  statistics,  the  results  of  the  open  public  consultation,  and 
several  other  documents  and  quantitative  calculations  outlined  above.  When  analysing  the 
impacts  of  the  different  options,  the  following  main  aspects  were  taken  into  account: 
effectiveness  in  relation  to  the  objectives  (fulfilling  data  needs;  coherence  and  integration; 
reducing  the  burden);  efficiency  in  achieving  the  objectives  (cost-effectiveness);  coherence 
with  overarching  EU  objectives  (CAP  and  other  EU  policies  depending  on  agricultural 
statistics  and  general  EU  objectives;  ESS  policies);  other  important  criteria  (risks;  indirect 
impacts  e.g.  on  climate  change);  and  impacts  on  stakeholders  (users,  producers  and 
respondents). Administrative burden and cost impact calculations are outlined further before 
being applied to the individual options. 

In  line  with  the  Better  Regulation  guidelines,  the  impact  assessment  should  also  provide 
details  for  all  options  on  the  information  obligations  for  businesses,  citizens  and 
national/regional/local  administrations  which  are  likely  to  be  added  or  eliminated  if  the 
option  were  implemented.  In  those  cases  in  which  the  change  in  administrative  burden  is 
likely to be significant, the effects should be quantified using the EU Standard Cost Model. 
However, this approach is difficult to apply while analysing the impact in terms of costs and 
burden  of  a  multi-annual  agricultural  statistics  programme.  Firstly,  due  to  the  difficulty  of 
performing  an  information  obligations  mapping  exercise  in  the  long  term  because  of  the 
multitude  of  providers  of  EU  statistics.  Secondly,  because  of  the  national  specificities  in 
terms of organisation of the statistical production systems, which makes it difficult to apply 
the EU Standard Cost Model for quantification. While analysing the impact in terms of costs 
and  burden  of  the  different  policy  options,  Eurostat  therefore  relied,  inter  alia,  on  the 
experience  gathered  from  previous  agricultural  surveys  and  combined  it  with  evidence 
gathered  from  previous  and  ongoing  quantitative  and  qualitative  assessments  of  costs  and 
burden related to the statistical production in the field, in order to assess the expected costs 
and burdens of data collection for respondents such as farms and agricultural businesses. 

Burden impact analysis methodology 

Step 1: Estimation of burden per variable 

To estimate the burden of each variable in the new system the following methods were used:  

(i) The assumption for variables included in the FSS or SAPM 2010 was that the burden has 
not changed, so the value (1-5) from the burden assessment exercise 2010 was used. Based 
on the values  submitted by the Member  States, a rounded average value was calculated for 
each variable.  

(ii) For some new variables, which are similar but not exactly the same as variables in FSS or 
SAPM 2010, the assumption was that the burden would be the same as for similar variables 
in the burden assessment exercise 2010, and so these values were used. For instance,  cattle 
housing was not collected for different types of cattle in FSS 2010, but it was included as a 

61 

 
 
new  variable  in  the  proposal,  and  continues  to  be  a  new  data  need.  The  value  for  cattle 
housing was 3 in the assessment of SAPM 2010, and therefore it has been assumed that the 
burden of each variable for cattle housing in the new system is also 3. 

(iii) For new variables for which no similar variable exists previously the highest value of a 
burden  (5)  has  been  assigned  to  calculate  the  maximum  possible  burden,  as  this  will  allow 
showing  the  worst  possible  case.  Eurostat  assumes  that  the  actual  situation  will  be  less 
drastic.  

Step 2: Estimation of burden per survey year  

For each core, module and satellite survey a total burden was estimated by aggregating the 
burden of the variables included, as shown in rows 1-10 of table AIV.1. A total burden was 
estimated in row 11. It takes into account differences in the amount of variables per survey 
year and the level of burden of the variables included. 

The  combined  total  estimated  burden  for  FSS  and  SAPM  2010  was  613  (a  census  year), 
while for FSS 2013 and FSS 2016 it is 467 (sample survey years). The total burden for IFS 
2023  is  estimated  at  672  (a  sample  survey  year),  which  is  higher  than  that  of  FSS  2010  or 
FSS 2013, as new variables are being added. The total burden for IFS 2020 (a census year) 
and for IFS 2026 (a sample survey year) is estimated at 574, which is lower than that of FSS 
2010, as some variables have been moved from FSS 2010 to a module which is not requested 
in these years, but it is higher than that for FSS 2013, as a satellite has been added.  

Table AIV.1: Estimation of total burden FSS/IFS 2010-2026. Source: Eurostat 
FSS 
2016 
467 
0 
0 
0 
0 
0 
0 
0 
0 
0 
467 

1.    Total burden core 
2.    Total burden module I 
3.    Total burden module II 
4.    Total burden module III 
5.    Total burden module IV 
6.    Total burden module V 
7.    Total burden module VI 
8.    Total burden satellite A 
9.    Total burden satellite B 
10.  Total burden SAPM 
11.  Total burden  

FSS/SAPM 
2010 
430 
0 
0 
0 
0 
25 
65 
69 
6 
18 
613 

FSS 
2013 
467 
0 
0 
0 
0 
0 
0 
0 
0 
0 
467 

IFS 
2020 
290 
0 
56 
30 
24 
0 
0 
0 
174 
0 
574 

IFS 
2023 
290 
41 
0 
0 
24 
25 
70 
222 
0 
0 
672 

IFS 
2026 
290 
0 
56 
30 
24 
0 
0 
0 
174 
0 
574 

Step 3: Estimation of burden per survey year weighted for size of survey 

The  total  burden  estimated  in  step  2  does  not  take  into  account  differences  in  the  burden 
related to different sample sizes. In Table AIV.2 the weighting factors for the core carried out 
as a census, the core carried out as a sample survey, and the modules and satellite surveys are 
presented. For  the purpose  of this analysis an initial  value was assumed based on proposed 
precision requirements. 

Table AIV.2: Weighting factors. Source: Eurostat 

Census 
Sample core 
Sample module 
Sample satellite 

Fixed part 
0.5 
0.5 
0.5 
0.5 

Variable part 
0.5 
0.3 
0.2 
0.2 

Total factor 
1 
0.8 
0.7 
0.7 

62 

 
 
  
 
 
 
The census was taken as the benchmark and therefore equals 1. It is assumed that the actual 
burden  of  the  core,  module  and  satellite  consists  of  a  fixed  part  (a  minimum  burden 
regardless of sample size, e.g. minimum amount of staff, databases etc. needed to carry out 
surveys) and a  variable part  (which increases with  the size of the survey, e.g. person-hours 
dedicated  to  data  collection,  validation  etc.)  Therefore,  the  relation  between  the  expected 
sample size and the weighting factor is not proportional, but is an addition of a fixed part and 
a variable part. The fixed part is assumed to be 50% of the total burden estimated in step 2, 
which  is  in  line  with  historical  experience  from  comparable  data  collections.  The  variable 
part is assumed to be 50% of the total burden estimated in step 2 when the survey is carried 
out as a census, 30% when the core is carried out as a sample survey, and 20% for modules 
and satellites. 

The total weighted burden for FSS/SAPM 2010 is thus 558, and for FSS 2013 and FSS 2016 
it is 374 (see Table AIV.3). In 2023 and 2026 the weighted burden is expected to be higher 
than in 2013 and 2016, however the weighted burden of IFS 2020 is estimated to be lower 
than that of FSS/SAPM 2010 (although new variables have been added, many variables have 
been moved to modules). 

Table AIV.3: Estimation of total burden and total weighted burden FSS/IFS 2010-2026. Source: Eurostat 
IFS 
2023 
672 
499 

1.  Total burden (step 2) 
2.  Total weighted burden  

FSS/SAPM 
2010 
613 
558 

FSS 
2016 
467 
374 

IFS 
2020 
574 
489 

FSS 
2013 
467 
374 

IFS 
2026 
574 
431 

Step 4: Estimation of weighted burden per survey year accounting for internal actions 

Adding to the burden of the variables included in the IFS and the sample size, a burden on the 
Member  States  in  2020  and  2023  related  to  redesigning  systems  to  adapt  to  the  new 
regulation(s) is expected. It was assumed that this burden is 25% of the total burden estimated 
in step 3 in 2020 and 10% in 2023, to calculate the upper range of the burden. These factors 
reflect  the  additional  costs  for  the  statistical  institutes  related  to  redesigning  their  systems 
only.  After  2023,  it  is  expected  that  Member  States  will  have  adapted  their  systems  to  the 
new regulation, and therefore these costs are no longer expected. These assumed proportions 
are at the high end of historical experience when considering that a large part of the costs of 
agricultural  census  data  collections  comes  from  having  to  survey  a  large  number  of  farms, 
which is little affected by system redesign (because a shorter questionnaire still needs to  be 
used in all farm holdings), but were nevertheless kept to estimate the upper range of redesign 
costs. 

Among the  actions foreseen for options 3 and 4, a new threshold of 98% of total utilised 
agricultural area and livestock units (and allowing Member States with many small holdings 
to  conduct  a  special  survey  on  5%  of  the  smallest  holdings  in  order  to  reach  the  threshold 
instead of including them in the regular sample) is expected to bring considerable reductions 
in  the  administrative  burden  for  data  producers,  mainly  in  countries  with  many  small 
holdings.  The  current  legal  thresholds  are  too  high  to  achieve  sufficient  coverage,  so  some 
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).  Assuming  conservatively  that  half  of  this  reduction  by  30% 
translates  into  a  burden  reduction  (due  to  fixed  costs  of  data  collection  regardless  of  the 
number  of  surveyed  holdings,  see  step  3),  this  would  result  in  a  factor  for  fewer  surveyed 

63 

 
 
  
 
holdings  of  0.85  from  2020  on.  Similarly,  better  coherence,  harmonisation,  integration  and 
flexibility  of  agricultural  statistics  data  collection  can  be  expected  to  result  in  at  least  5% 
burden reduction. 

The  total  weighting  factor  to  estimate  the  burden  reduction  from  internal  actions  (resulting 
from multiplying the individual factors with each other and rounded to 5 percent to account 
for uncertainties) can be seen in table AIV.4. 

Table AIV.4: Estimation of burden factors for internal actions. Source: Eurostat 

Factor for redesigning systems 
Factor for fewer surveyed holdings 
Factor for better coherence etc. 
Total factor for internal actions 

2020 
1.25 
0.85 
0.95 
1 

2023 
1.1 
0.85 
0.95 
0.90 

2026 
1 
0.85 
0.95 
0.80 

Step 5: Estimation of weighted burden per survey year accounting for external factors  

A further reduction in administrative burden can be expected due to external factors, foremost 
the continuing shrinkage of the number of agricultural holdings in the EU caused by the 
problem  drivers  detailed  earlier.  The  number  of  farms  in  the  EU  has  already  shrunk  from 
almost  15 million holdings  to 11 million between  2003 and 2013 and is expected to  shrink 
further. This effect applies equally to all options, but is important to be included to get a full 
picture  of  the  evolution  of  the  burden  of  European  agricultural  statistics  data  collection. 
Unfortunately,  there  are  no  exhaustive  studies  available  on  this  subject,  and  the  rate  of 
shrinkage depends on many factors, several of which are hard to predict, so only a range of 
the number of EU farm holdings between 2020 and 2026 could be estimated: 1) unchanged to 
the status quo, i.e. 11 million, 2) based on a linear projection of the current annual shrinkage 
rate of 3.7%, i.e. around 8.2 million holdings in 2020, 7.3 million in 2023, and 6.5 million in 
2026, and 3) based on an accelerated annual shrinkage rate of 5%, i.e. 7.5 million holdings in 
2020,  6.4  million  in  2023,  and  5.5  million  in  2026.  If  half  of  these  reductions  can  be 
translated  into  burden  reductions  (again  accounting  conservatively  for  fixed  costs  of  data 
collection), this results in the burden reduction factors outlined in table AIV.5. 

Lastly, technological, methodological, organisational and other progress can be expected 
to  reduce  the  burden  of  data  collection  irrespective  of  the  chosen  option.  2%  improvement 
per  year  would  result  in  8%  less  burden  by  2020,  15%  by  2023,  and  22%  by  2026.  Again 
assuming  conservatively  that  only  half  of  these  potential  gains  can  be  translated  into  real 
burden reductions, the resulting factors, multiplied with the estimations for the shrinkage of 
holdings, can be seen in table AIV.5. 

Table AIV.5: Estimation of burden factors for external factors. Source: Eurostat 

Shrinkage of holdings scenario 1 (unchanged) / incl.technological etc. progress 
Shrinkage of holdings scenario 2 (-3.7%/year) / incl.technological etc. progress 
Shrinkage of holdings scenario 3 (-5.0%/year) / incl.technological etc. progress 

2023 
1 / 0.93 

2020 
1 / 0.96 
0.88 / 0.85  0.83 / 0.77  0.80 / 0.71 
0.84 / 0.81  0.79 / 0.73  0.75 / 0.67 

2026 
1 / 0.89 

Step 6: Total weighted burden per survey year 

Table AIV.6 presents the total burden including the additional or reduced burdens for internal 
actions and external factors in the Member States. 

64 

 
 
 
  
  
 
  
  
 
 
Table AIV.6: Estimation of total weighted burden FSS/IFS 2010-2026. Source: Eurostat 

1. Total burden (step 2) 
2. Total weighted burden (step 3) 
3. Total weighted burden with internal actions only, from 
2020 (step 4) 
4. Total weighted burden with external factors only, from 
2020 (step 5) 
Shrinkage of holdings scenario 1 
Shrinkage of holdings scenario 2 
Shrinkage of holdings scenario 3 
5. Total weighted burden with internal actions and 
external factors, from 2020 
Shrinkage of holdings scenario 1 
Shrinkage of holdings scenario 2 
Shrinkage of holdings scenario 3 

FSS/SAPM 
2010 
613 
558 

FSS 
2013 
467 
374 

FSS 
2016 
467 
374 

IFS 
2020 
574 
489 

IFS 
2023 
672 
499 

IFS 
2026 
574 
431 

558 

374 

374 

489 

449 

345 

558 
558 
558 

558 
558 
558 

374 
374 
374 

374 
374 
374 

374 
374 
374 

374 
374 
374 

469 
416 
396 

469 
416 
396 

464 
384 
364 

418 
346 
328 

384 
306 
289 

307 
245 
231 

The  meaning  of  these  calculations  can  be  clearly  seen  from  table  AIV.7,  in  which  a  full 
"cycle"  (one  census  and  two  sample  surveys)  of  FSS  surveys  is  summed  up,  the  middle 
scenario  2  for  the  shrinkage  of  the  number  of  holdings  is  taken  as  a  benchmark,  and  the 
options are compared as far as possible. 

Table AIV.7: Estimation of administrative burden change for a full FSS/IFS cycle. Source: Eurostat 

Option 1 
Option 2 
No changes at all 
Only external factors 
Options 3 and 4 
Only survey redesign 
Survey redesign + internal actions 
Survey redesign + external factors 
All actions and factors 

Current cycle (2010-2016)  Next cycle (2020-2026)  Future cycles (2030+) 
1306 

n/a 

n/a 

1306 
1306 

1306 
1306 
1306 
1306 

1306 
1028 

1419 
1283 
1106 
1007 

1306 
Further reduction 

1419 
1135 
Further reduction 
Further reduction 

It can be seen that under options 3 and 4, the total weighted burden for a full "cycle" of FSS 
surveys,  when  including  internal  actions  intended  to  reduce  the  burden  of  agricultural 
statistics data collection, but excluding externally imposed changes, would be slightly lower 
than  in  the  current  status  quo  (which  equals  option  2),  despite  shouldering  high  adaptation 
costs  (1283 versus  1306).  For  the  next  and  further  "cycles",  this  burden  would  shrink  even 
further  to  1135  versus  1306  because  there  would  be  no  new  large  system  adaptation 
necessary  for  the  time  being.  Similar  relations  hold  or  would  hold  when  also  including 
external changes thought to affect each option equally. 

Thus, it can be concluded that the administrative burden for data producers of options 3 and 4 
would  be  slightly  lower  than  the  burden  of  the  status  quo  option  2,  even  though  the  new 
system  would  absorb  high  adaptation  costs,  fulfil  new  data  needs,  and  perform  in  a  more 
harmonised  and  integrated  manner.  In  the  future,  the  comparison  would  be  even  more 
favourable, as no more adaptation costs would be incurred and the new system would be able 
to adapt much easier to changing and emerging requirements. 

65 

 
 
  
 
 
  
 
 
 
 
 
 
 
 
 
Annex V: Detailed list of data sets collected in the EASS 

Table AV.1: Current European agricultural statistics data sets, frequency and legal 
basis 
* = non-statistical legislation 

Domain 
Structural 
data 

Data set 
Agricultural census 

Farm structure surveys 

Frequency 
Every 10 
years 
Every 3 years 

Agri-
monetary 
data 

Economic accounts for agriculture 
Agricultural labour input statistics 

Annually 

Legal basis 
Regulation (EC) No 
1166/2008 
Implementing 
Regulation (EC) No 
1200/2009 
Regulation (EC) No 
138/2004 on the 
economic accounts for 
agriculture in the 
Community 

Unit value statistics for agricultural 
products 
Selling prices of agricultural 
products 
Price indices of agricultural 
products 
Agricultural prices - land (including 
rent) 
Crops from arable land - area and 
yield 
Permanent crops from arable land 
Vegetables, melons, strawberries 
Agricultural land use 
Supply balance sheets – wine 

Crop 
production 
data 

Crops products: supply balances 
sheets 

Annually 

Regulation (EC) No 
543/2009 concerning 
crop statistics 

Regulation EC laying 
down detailed rules for 
the application of 
Council Regulation 
(EC) No 479/2008 as 
regards the vineyard 
register, compulsory 
declarations and the 
gathering of 
information to monitor 
the wine market, the 
documents 
accompanying 
consignments of wine 
products and the wine 
sector registers to be 
kept 

66 

 
 
 
 
Early estimates for Crop production 

Annually 

Early estimates for Fruit and 
Vegetables 
Certified registered organic 
operators 
Certified organic crop area and 
production 
Certified organic livestock, animal 
products and aquaculture 
Manufacturing of organic products 
Structure of orchards and vineyards  Every 5 years  Regulation (EU) No 

Regulation (EC) No 
834/2007 on organic 
production and 
labelling of organic 
products 

Annually 

1337/2011 concerning 
European statistics on 
permanent crops 
Regulation (EC) No 
1165/2008 concerning 
livestock and meat 
statistics 

Organic 
farming data 

Permanent 
crop statistics 

Animal 
products and 
livestock data 

Livestock survey - cattle - 
May/June 
Livestock survey - cattle - 
November/December 
Livestock survey - cattle – regional 
Livestock survey - pigs - May/June 
Livestock survey - pigs - 
November/December 
Livestock survey - pigs – regional 
Livestock survey - sheep & goats - 
November/December 
Livestock survey - sheep & goats – 
Regional 
Slaughterings other than in 
slaughterhouses 
Slaughterings other than in 
slaughterhouses 
Slaughterings in slaughterhouses 
Gross indigenous production – 
cattle 
Gross indigenous production – pigs 
Gross indigenous production - 
sheep & goats 
Activity of hatcheries* 
Trade of chicks* 
Structure of hatcheries* 

Monthly 

Sub-annually 

Monthly 

Annually 

Milk collection - Table A 
Milk production - Table B 

Monthly 
Annually 

Regulation (EC) No 
617/2008 laying down 
detailed rules for 
implementing 
Regulation (EC) No 
1234/2007 as regards 
marketing standards for 
eggs for hatching and 
farmyard poultry 
chicks 
Council Directive 
96/16/EC on statistical 

67 

 
 
Milk questionnaire 
Milk on farms - Table C 
Milk protein contents - Table H 
Milk regional collection - Table I 
Structure of Dairies - Collection 
Centres by volume of annual milk 
collection 
Use of pesticides 
Sales of pesticides 

Fertiliser statistics 
National level gross nitrogen 
balances 
National level gross phosphorus 
balances 

Agri-
environmenta
l data 

surveys of milk and 
milk products 

Every 3 years 

Every 5 years  Regulation (EC) No 
Annually 

1185/2009 concerning 
statistics on pesticides 

Furthermore, there are derived agricultural statistics: 

  Supply balance sheets for main crop products 
  Rural development indicators  
  GIP forecast (quarterly/semi-annual) 

European agricultural statistics currently under development are: 

  LUCAS/ land use statistics 
  More agri-environmental indicators 
  Statistics on production of eggs for human consumption and of honey. 

68 

 
 
 
 
 
 
Annex VI: Summary of present agricultural data collection and new needs in the EU 

Table AVI.1: Summary of present EU agricultural data collection and new data needs. 
Source: Eurostat. 

* = New data need 

Item 

Location  

Type of unit 

Legal status 

Main purpose of the 
production of the holding 
Utilised agricultural area 

Land use types 

Constraints on agricultural 
activity 

Other areas on farms 

Structure of production 
factors 

Total area of the holdings 

Total area 

Description  

Survey/ source 
(suggested for new 
needs) 
Basic information 

Level 

Frequency 

FSS census 

Holding 

Every 10 years 

Accurate geo-reference 
of the holding 
Rounded geo-reference 
of the holding 
Parcel geo-reference* 
Household, holding 

Natural person/ juridical 
person/ common land 
Producing for market or 
for own consumption* 
Total area 

FSS interim surveys 

Holding 

FSS 
FSS 

FSS 

FSS  

Crop statistics 
FSS 

FSS 

Parcel 
Holding 

Holding 

Holding  

Region 
Holding 

Holding 

Crop statistics 

Region 

Holding 

Holding 

Region 

Holding 

Arable crops, 
temporary grasses,  
permanent crops, 
permanent grassland, 
wooded area, etc. 
LFA, mountain area 
Ecological focus area 
Non-agricultural land on 
the holding 

Structure of holdings, 
crops, grassland, 
number of livestock, 
etc. 
Structure of plantations 
(fruit, olive, grapes) 
,and density and age 
Structure of rearing 

FSS 

FSS 

FSS 

Crop statistics 
Production assessment and forecast 

2-3 year 
intervals 

2-3 year 
intervals 
2-3 year 
intervals 

2-3 year 
intervals 
Annual 
2-3 year 
intervals 
2-3 year 
intervals 
Annual 

2-3 year 
intervals 

2-3 year 
intervals 
Annual 

2-3 year 
intervals 

2-3 year 
intervals 
annual 

Permanent crop 
statistics 

Region 

Every 5 years 

FSS 

Holding 

Structure of hatcheries 
Structure of dairies 

Animal statistics 

National 
National  Every 3rd year 

69 

 
 
 
 
Item 

Description  

Survey/ source 
(suggested for new 
needs) 

Level 

Frequency 

Nutrient surplus 

Gross Nutrient Balance  Agri-environmental 

statistics 

Production at various stages  Area sown/planted, 

Crop statistics 

National  Annual 
Region* 
Region 

? 
Annual 

Crop statistics 
Crop statistics 

Animal statistics 
Animal statistics 
Animal statistics 

? 
Animal statistics 
Animal statistics 
Animal statistics 
Animal statistics 
Animal statistics 
Agri-monetary 

harvested, area under 
grass, grazed 
Detailed livestock 
Laying hens* 
Placing of chicks 
Cows‘ milk collection + 
products obtained 
Yields 
Annual and permanent 
crops 
Grassland* 
Main slaughter 
Other slaughter 
Cows’ milk 
All milks 
Eggs*  
Production index 
(volume) 
Other production, e.g. 
mushrooms 
Early estimates 
GIP meat 
Processed products 
(dairy products, wines) 
For main annual crops, 
wine 
External trade of chicks  Animal statistics 
Animal statistics 
Availabilities and use of 
milk 
Absolute price 

Crop statistics 
Animal statistics 

Crop statistics 

FSS 

Agricultural price 
statistics 
Agricultural price 
statistics 
Agri-environmental 

Semi-annual 
Region 
Country 
Annual 
Country  Monthly 

Region 
Region 

Annual 
Annual 

Annual? 
Region 
Monthly 
Region 
National  Annual 
Region 
Annual 
National  Annual 
Country 
Annual 
Regional  Annual 

Holding 

2-3 year 
intervals 
Monthly 

Region 
National  Once or twice 

a year 

Country 

Annual 

Monthly 
Annual 

Country  Quarterly 

Country  Quarterly 

Country 

5 year intervals 

FSS 

Holding 

Crop statistics 

Region 

2-3 year 
intervals 
Annual 

Farm management 

70 

Production achieved 

Production forecast 

Supply balance sheets 

Selling prices of production 

Price index 

N and P content of products*  Crop products, animal 

Energy crops 

products, grassland 
production, clover and 
mixture 
Area 

 
 
Item 

Description  

Farm income 

Indicators A and B 

Farm work 

Structure of farm labour 
force 
Family labour force 

Farm management 

Diversification 

Viability 
Water management 

Soil management 

Manure management 

Animal management 

Pesticides 

Work for agricultural 
production 
Labour input 
By gender, age, 
working time class 
By gender, age, 
working time class 
Family link 

Other Gainful Activities 

The holder, the 
manager 
Education level 
Support for rural 
development 
Other activities directly 
related to the holding 
Land tenure 
Irrigable, irrigated area 

Per main crops 

Irrigated areas per 
crop* 
Irrigation methods 
Source of irrigation 
water 
Tillage methods 
Soil coverage 
Crop rotation 
Application techniques 
Import/ export 
Manure storage system 
for cattle, pigs, poultry 
Housing systems for 
cattle, pigs, poultry 
Grazing system for 
each grazing livestock 
Sales 
Use by agriculture by 
crop 

FSS 

FSS 

FSS 

FSS 

FSS 

Survey/ source 
(suggested for new 
needs) 
Agri-monetary 
statistics 
FSS 

Agri-Monetary 
FSS 

Level 

Frequency 

Country 

Annual 

Holding 

Country 
Holding 

2-3 year 
intervals 
Annual 
2-3 year 
intervals 

FSS 

FSS 

Holding 

Holding 

Crop statistics 

Region 

Holding 

2-3 year 
intervals 
10 year 
intervals 
Annual* 

2-3 year 
intervals 

Holding 

2-3 year 
intervals 

Holding 

2-3 year 
intervals 

Holding 

Holding 

2-3 year 
intervals 
5 year intervals 

Pesticide 

Country 

Annual 
Every 5th year 

71 

 
 
Item 

Description  

Fertilizers 

Other N input* 

Feed* 

Production days for living 
animals* 

Rice cultivation system* 

Histosols* 

Soil management* 

Price of input 

Structure  

Survey/ source 
(suggested for new 
needs) 
Agri-environmental 
statistics 

Level 

Frequency 

Regional  Annual 

Agri-environmental 

National 

? 

? 

? 

? 

? 

? 

Regional  Annual 

Every 10 years 

Every 3rd year 

Regional  Annual 

Agri-monetary 

Country  Quarterly 

Use of  N, P, K 
fertlizers 
Use per detailed type of 
N-fertilizers* 
Application rate of 
mineral fertilizers (kg N 
/ ha)* 
Application rate of 
organic fertilizers 
(manure) (kg N/ha)* 
Application rate of 
sludge and slurry (kg 
N/ha)* 
Atmospheric N 
deposition* 
Share of dry matter of 
crops, grass, 
concentrates or 
compound feed, feed 
additives, feed by 
animal type* 
Production days for 
living animals (or 
number of cycles)* 
Rice cultivation 
systems according to 
IPCC* 
Area of cultivated 
histosols' 
Share of crop residues 
returned to the soil' 
Crop residues 
management' 
Share of legumes in 
grassland' 
N-fixing crops in 
rotation' 
Grasslands 
management' 
Changes in price of 
input 

Organic farming 
FSS 

Structure, area and 
livestock 

Holding 

2-3 year 
intervals 

72 

 
 
 
 
 
 
 
 
 
Item 

Description  

Production factors 

Production 

Processing 
Operators 

Area under organic 
farming: total, 
converted, under 
conversion 
Crops, livestock  

Fish species* 
Area of clover and 
mixture 
Potential: Unutilised 
agricultural area 
Per crop, animal 
product, fish 
Volume 
Number 

Survey/ source 
(suggested for new 
needs) 
Organic Statistics 

Level 

Frequency 

National  Annual 

? 
FSS 

Region 
Holding 

Annual 
2-3 year 
intervals 

Organic Statistics 

National  Annual 

Table  AVI.2:  Details  of  new  data  needs  by  problem  driver  and  stakeholder  groups. 
Source: Eurostat. 

Data need 

Reasons 

Climate change challenges, 
e.g. land data on exchange of 
greenhouse gases between 
atmosphere, soils and 
vegetation; land management 
data e.g. on grazing of 
livestock, tillage, manure, 
urea application; water 
availability, extreme climatic 
events etc. 

Other important data needs, 
such as data for development 
policies, e.g. on food 
production structures and 
yields, price volatility; 

  The  carbon  footprint  of 

the  agricultural  sector 

is 
influenced  by  soil  carbon  contents  and  management 
practices.  Emissions  and  removals  should  be  accounted 
for better to improve future policy design. In addition, the 
adaptive capacity of agriculture to climate change needs to 
be better assessed. 

  Land  management  and  agricultural  activity  data  are  a 
necessary  basis  to  estimate  greenhouse  gas  emissions 
according to IPCC methodology enshrined in international 
law.  Agriculture  emits  about  10%  of  total  greenhouse 
gases in the EU and is the second largest greenhouse gas 
source  in  the  EU  after  energy.  It  is  thus  relevant  for 
emissions  reduction  after  2020  and  beyond,  and  also  for 
political  climate  and  energy  frameworks  and  emissions 
targets. 

  Farm  data  to  be  collected  for  emissions  accounting  and 
reduction can only be collected by sampling at farm scale 
and  relate  especially  to  animal  feeding,  animal  housing, 
manure storage and manure application. 

  EU  agriculture  affects  developing  countries  through  the 
availability of stocks for aid and through impacts on food 
prices. 

  The  contribution  of  agriculture  to  the  production  of 

73 

 
 
 
renewable energy data e.g. on 
biofuels; animal welfare data 
e.g. on livestock management 
practices and stocking 
densities 

FSS data improvements, e.g. 
more details, better 
timeliness, fewer data gaps 

Main CAP needs: what is 
produced (information on 
crops, livestock, production, 
yields etc.), by whom 
(information on farms, farm 
holders and managers, family 
members, non-family labour, 
total labour input, by sex and 
age, training status, working 
time etc.), and how 
(information on production 
methods, organic farming, 
input use, farming intensity, 
stocking densities, tillage 
methods, manure 
management, irrigation etc.) 

Also needed: information on 
where production is located 
(regional distribution, areas 
facing constraints etc.) and 
how agriculture interacts with 
the environment (land use, 
landscape, crop diversity, 

renewable energy needs to be better assessed. 

  More information for animal welfare policies is required. 

  FSS  data  are  used  by  DG  AGRI  and  other  users  as  the 
backbone  for  almost  all  analyses  of  farms  and  farming-
related  activities  in  the  EU;  they  are  the  standard  source 
for  data  related  to  farm  numbers,  types,  sizes,  land  use, 
farm  holder  characteristics  and the farm  labour  force  and 
provide essential time series.61 They are also a key source 
of  information  to  build  sampling  frames  for  surveys  and 
for  data  on  small  areas  and  rare  products.  Together  with 
crop  and  animal  production  statistics,  FSS  data  provide 
essential 
for  meaningful  policies  on 
agriculture,  rural  development,  territorial  cohesion  and 
many aspects of enviromental and economic development, 
on  the  efficiency  and  competitiveness  of  the  sector,  and 
the  nature  and  development  of  rural  areas;  they  enable 
analysing  and  highlighting 
trends,  monitoring  and 
evaluating  policy  impacts,  and  identifying  problem  areas 
and designing new policies. 

information 

  Agricultural 

central 

statistics 

for  designing, 
are 
negotiating, implementing,  monitoring  and  evaluating  the 
CAP, the most complex and harmonised EU-level policy. 
It covers agricultural production and production methods, 
agricultural  markets,  provision  of  public  goods  and 
services  by  agriculture,  development  of  rural  areas  and 
farmers'  income.  These  elements  cannot  be  seen  in 
isolation  or  with  different  priorities,  and  all  need  a  solid 
knowledge  base.  Statistics  are  used  at  each  stage  of  the 
policy cycle, from problem analysis to policy conception, 
impact assessment, monitoring and evaluation, in order to 
target policy interventions efficiently and effectively. The 
informed,  rapid  and 
data  are  also  needed  for  an 
appropriate reaction in crises and towards market signals. 
It  would  therefore  be  best  to  focus  on  the  needed  survey 
systems to make them flexible for new and emerging data 
needs.  

  The reformed CAP also puts more emphasis on protecting 
the  environment  and  the  climate,  sustainable  farming 
practices,  animal  welfare  and  rural  development,  for 
which more data are needed. 

  Eurostat  completed  a  project  to  identify  the  data  needs 
related  to  agri-environmental  indicators  (AEIs),  which 

61 Document CPSA/631 for the CPSA Meeting November 2011, Annex I 

74 

 
 
 
                                                            
biodiversity, soil, air and 
water quality, emissions from 
agriculture, environmental 
focus areas, environmentally 
sensitive grassland etc.). Also 
data on prices, yields and 
production structures for 
market analyses and market 
outlook models, information 
on the food supply chain, and 
information on income from 
agricultural activities. 

For Rural Development 
Policy, information on the 
economic situation of rural 
areas, other income-
generating activities, rural 
infrastructure, demography, 
employment and the 
environment is needed. 

Data for CAP "greening", i.e. 
a land-based policy with 
strong environmental 
requirements; for this, 
reliable data about land uses, 
land conditions and 
management practices is 
required, e.g. on crop 
diversity, permanent 
grasslands, and ecological 
focus areas 

28 agri-environmental 
indicators to monitor the 
integration of environmental 
concerns into the CAP at EU, 
national and regional levels, 
e.g. data on pesticides, soil 
quality and waste 

Organic farming data 

Further DG AGRI data needs 
for the monitoring and 
evaluation system of the 

that  a 

requirements,  giving  an  opportunity 

give  information  on  the  incorporation  of  environmental 
measures  in  agricultural  policies  and  on  the  relation 
between  agriculture  and  the  environment.  The  study 
confirmed 
large  amount  of  farm  data  and 
information  are  needed,  and  that  a  number  of  key  AEIs 
have  data  requirements  in  common  with  key  policy 
reporting 
to 
harmonise  data  collection  and  reporting.  The  data 
requirements  for  calculating  the  AEIs  consist  of  97 
different  types  of  data.  20  can  be  obtained  from  the  FSS 
and  12  from  the  SAPM,  which  could  benefit  AEI 
collection if it were more regular instead of a one-off. 43 
other data sources were identified. There may be a need to 
start  new  surveys  and  install  new  statistical  legislation 
(which  so  far  exists  only  for  pesticides)  to  collect  the 
remaining  data.  The  28  AEIs  are  of  extreme  importance 
for EU agri-environmental policy reporting. These results 
have  been  confirmed  by  in-depth  discussions  with  users 
and  producers  of  agricultural  statistics  and  are  also  used 
by  FAO  and  OECD.62  This  is  also  relevant  to  IPCC 
guidelines for the evaluation of agricultural statistics with 
regard  to  climate  policy  questions.  Similarly,  a  study  on 
grassland  statistics63  found  different  data  needs  and  was 
used as input for the strategy. 
In  addition,  the  International  Statistical  Institute's  World 
Statistics  Congress  2015,  a  biennial  meeting  of  official 
statisticians with over 1600 participants, stressed that agri-
environmental  indicators  can  be  useful  for  work  on 
climate-smart  agriculture,  which  aims  to  increase  food 
production,  lower  emissions  and  increase  resilience;  but 
data  must  be  updatable  and  comparable  over  time  and 
across countries, for which more work is needed. 

 

  Organic farming is a main way for farmers to benefit from 
"greening" direct payments and can account for up to 30% 
of the CAP; statistics in this area are of bad quality due to 
coverage  and  timeliness  problems.  More  maturation  and 
new legislation are needed to improve the data quality.64 
  DG  AGRI  is  interested  in  data  for  questions  such  as 
whether land  prices  are  influencing  land  use  patterns  and 
to  understand  "land  grabbing"  better;  only  partial  land 
prices until 2009 exist. In addition, the reference for CAP 
support is shifting from farmers to land. 

  As  for  supply  balance  sheets  (SBS),  it  was  decided  to 
reduce these statistics around 2004. There were about 100 

62 Farm data needed for agri-environmental reporting, ISBN 978-92-79-19648-5  
63 Draft final report Grassland Project 
64 Document DGAS/12 for DGAS Meeting 2015 

75 

 
 
                                                            
CAP, e.g. agricultural 
productivity, emissions, food 
supply chain data, land prices 
and rents, supply balance 
sheets, fertiliser use, and soil 
quality 

SBS based on gentlemen's agreements then. The last SBS 
for  cereals  was  produced  in  2013,  and  there  is  no 
alternative  source.  SBS  suffered  from  a  lack  of  data,  an 
unharmonised  methodology  and  some  suspicious  figures, 
but their discontinuation led to the consequences described 
above, and there are international reporting obligations for 
AMIS  and  the  G-20.  Therefore,  DG  AGRI  would  like  to 
see SBS on wheat, maize, barley, rice, rapeseed, soybean 
and  sunflowers  reintroduced,  based  on  a  clear  and 
harmonised  methodology  and  better  quality  data  within  a 
sustainable  legal  framework.  These  data  should  come 
from  statistics  because  there  is  an  established  code  of 
practice,  i.e.  guaranteed  quality;  models  can  suffer  from 
"garbage in, garbage out". 

DG ENV data needs: Data is 
needed to monitor the effects 
of implementation of current 
environmental policies and 
legislation and for the 
development of new policies. 

For the Biodiversity Strategy, 
data on land management 
(e.g. reparcelling), on 
biodiversity features (e.g. 
presence of landscape 
features), farming practices 
(e.g. High Nature Value 
Farmland), and land use (e.g. 
semi-natural grasslands). 

For the Water Framework 
Directive/Nitrates Directive, 
data on land management 
(e.g. irrigated area), farming 
practices (e.g. Nutrient 
Balance), and equipment (e.g. 
water saving permitted by 
irrigation systems, manure 
storage). 

For the Clean Air 
package/Industrial Emission 
Directive: data on grazing of 
livestock, fertilizer 
application, manure storage, 
animal housing. 

For the Soil Thematic 
Strategy: data on land use 
(e.g. green cover), farming 

  Agricultural statistics are crucial to monitor the causes of 
the  existing  gaps  for  achieving 
the  objectives  of 
environmental  policies.  According  to  the  EEA's  2015 
report  on  the  State  of  the  Environment,  agriculture  lists 
first  in  its  list  of  socio-economic  sectors  which  are 
degrading the natural capital of Europe. European farming 
involves the use of soil, water, biodiversity and landscape. 
So  it  establishes  a  more  complex  relation  with  the 
environment  in  comparison  to  closed  industrial  systems, 
and  therefore  it  is  challenging  to  avoid  environmental 
damage. Farmland covers nearly half of the territory of the 
European  Union,  so  if  certain  farming  practices  cause 
environmental  problems,  these  problems  tend  to  be 
widespread  and  tend  to  have  significant  impacts  on  the 
ecology.  That  said,  some  European  farming  systems  are 
also  actively  beneficial  for  the  environment.  In  particular 
High Nature Value  farming systems, which can be found 
in many of the Natura 2000 areas protected under the EU 
Habitats and Birds Directives,  as well as in other regions 
where  traditional,  extensive  farming  systems  remain  are 
positive,  but  their  presence  is  under  threat  by  land 
abandonment, agricultural intensification and land take. 
  Some  indicators  on  the  state  of  the  environment  are 
already  directly  collected  by  environmental  legislation, 
such  as  status  of  conservation  of  habitats  (Natura  2000), 
state  of  water  bodies  (Water  framework  directive), 
national emissions (National Emission Ceiling Directives) 
and  Nitrates  content  in  water  (Nitrates  Directives),  but 
there  are  legislation  gaps  for  example  on  soil  and 
biodiversity  outside  Natura  2000,  which 
requires 
indicators. The planned Commission initiative on land as a 
resource  will  also  require  a  solid  knowledge  base,  from 
impact 
problem  analysis 
assessment.  

to  policy  conception  and 

  To  make  the  link  with  the  data  on  state  of  the 

76 

 
 
environment,  other  agricultural  statistics  data  are  needed. 
Data  on land  management,  agricultural  activity,  land  use, 
biodiversity  features,  farm  equipment  and  machinery, 
farming  practices  etc.  are  necessary  to  identify  the 
remaining  actions  needed  at  EU  level  in  order  to  fill  the 
gaps  for  achieving  the  environmental  objectives.  These 
actions  can  be  both  the  adaptation  and  reinforcement  of 
the  greening  of  the  CAP,  and  the  strengthening  of 
implementation  of  environmental  legislation.  This  is  why 
especially  the  survey  on  agricultural  production  methods 
and  agri-environmental  indicators  are  essential  for  DG 
ENV.  This  is  especially  relevant  in  relation  to  the 
following current agenda of the EU Environmental Policy: 
the  Mid  Term  review  of  the  Biodiversity  Strategy65,  the 
the  Circular 
recently  adopted  EU  action  plan  for 
Economy66,  the  3rd  Implementation  Report  on  the  Water 
Framework  Directive  -  River  Basin  Management  Plans, 
the  new  Clean  Air  Policy  Package67,  and  the  future 
initiative  on  land  as  a  resource,  as  indicated  in  the  2011 
Road Map for Resource-Efficient Europe68. 

  DG  JRC  needs  data  to  perform  quality  assurance  in  the 
area  of  annual  greenhouse  gas  inventories  and  for 
research. It also needs data for its bioeconomy observatory 
in  order  to  assess  the  progress  and  impact  of  the 
bioeconomy,  i.e.  those  parts  of  the  economy  that  use 
renewable biological resources.  griculture naturally plays 
a big role in the bioeconomy.69 

  DG  SANTE  needs  data  to  counter  diseases  and  health 
risks that are increasing in scope, size and reach (also due 
to climate change) and influence food safety; in addition, 
the agri-food chain is becoming more globally integrated, 
with  increasing  health  repercussions  on  markets  and 
consumers. 

  The  outcomes  of  the  CPSA/DGAS  Seminars  confirmed 
that  most  of  the  agricultural  statistics  presently  collected 
by  Eurostat  are  still  needed,  and  there  are  several  new 
specific  needs.  The  continued  collection  of  base  data  is 
needed  to  establish  time  series,  long-term  trends  etc.  for 
informed  policy  development  and  establishing  targeted 
and effective policies. 

  Food  supply  chain  data  are  politically  important  for 
relations  and  price 

bargaining  power,  contractual 

practices (e.g. type  of 
tillage), and management 
practices (e.g. use of organic 
fertilizers). 

For the Resource Efficiency 
scoreboard: land use (e.g. 
area under organic farming) 
and land management (e.g. 
Nutrient balances, Water 
exploitation index). 

Needs of other important 
stakeholders: DG JRC, DG 
SANTE 

Key needs stated at 
CPSA/DGAS Seminars: 
Number and structure of 
farms and core variables of 
agricultural production; 
production, area harvested 
and planted, yields; producer 
prices (both output and input, 
including land prices and 

65 COM(2015) 478 final 
66 COM(2015) 614/2 
67 COM/2013/0918 final 
68 COM/2011/0571 Final 
69 COM(2012) 60 

77 

 
 
                                                            
transmission  along  the  chain.  Data  needed  are  e.g.: 
numbers  of  operators  at  different  stages  (producers, 
processors,  retailers,  consumers),  concentration  ratios, 
prices  at  different  stages  etc.  As  production  chains  are 
increasingly split up in shorter phases with more and more 
players involved, these data are becoming more important, 
in  order  to  allow  for  an  informed,  rapid  and  appropriate 
reaction  in  crises,  and  allow  economic  operators  to 
understand and react to market signals. 

  Land  cover  and  use  data  are  needed  for  environmental, 
renewable  energy  and  climate  change  policies  because 
land use heavily influences them; a lack of good land use 
data led to this area not being fully taken on board during 
the Kyoto climate change negotiations.70 
Irrigation  data  are  important  as  agriculture  is  one  of  the 
heaviest water users; as the climate changes, this can lead 
to more droughts and water shortages. 

 

  Geo-referenced  information  is  required  to  combine  in  an 
efficient way agricultural information with environmental 
information. 

  Detailed local data are requested as environmental impacts 
of biodiversity, soil and water are geographically specific. 

rents); exports and imports; 
stocks of core crops; number, 
production and producer 
prices of core livestock; land 
cover and use; organic 
farming; areas irrigated and 
quantity of water withdrawn 
for agricultural irrigation; 
fertilisers in quantity and 
value; pesticides in quantity 
and value; feed in quantity 
and value; age and sex of 
farmers, family and 
workforce; working time and 
other gainful activities of 
farmers and their family 
members; indicators and data 
on new greening elements 
(crop diversity; permanent 
grassland including 
environmentally sensitive 
grassland; ecological focus 
areas); geo-referenced 
information; data on food 
supply chains; continued 
collection of base data; 
detailed local data; erosion, 
pollution, landscapes; 
machinery 

70 Document CPSA/686 for CPSA Meeting May 2013 

78 

 
 
 
 
 
 
 
 
 
 
 
 
                                                            
Annex VII: List of abbreviations 

AEI 

AMIS   

BSE 

CAP 

CPSA   

DG AGRI 

DG BUDG 

Agri-Environmental Indicators 

Agricultural Market Information System 

Bovine spongiform encephalopathy 

Common Agricultural Policy 

Comité Permanent de la Statistique Agricole 

Directorate-General for Agriculture and Rural Development 

Directorate-General for Budget 

DG CLIMA 

Directorate-General for Climate Action 

DG ENV 

DG REGIO 

DG SANTE 

DGAS  

EAA 

EAFRD 

EASS   

EEA 

ESS 

ESSC   

Directorate-General Environment 

Directorate-General for Regional and Urban Policy 

Directorate-General for Health and Food Safety 

Directors' Group for Agricultural Statistics 

Economic Accounts for Agriculture 

European Agricultural Fund for Rural Development 

European Agricultural Statistics System 

European Environment Agency 

European Statistical System 

European Statistical System Committee 

ESS.VIP.BUS.ADMIN 

Vision Implementation Project Administrative Data Sources 

FADN  

FAO 

FSS 

IACS   

IAS 

IFS 

IMF 

Farm Accountancy Data Network 

Food and Agriculture Organization of the United Nations 

Farm Structure Survey 

Integrated Administration and Control System 

Internal Audit Service 

Integrated Farm Statistics 

International Monetary Fund 

79 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ISI 

JRC 

NGO 

NSI 

OECD  

ONA 

REFIT  

SAIO   

SAPM  

SBS 

SG 

SJ 

TFEU   

UNECE 

UNFCCC 

UNSC  

UNSD  

USDA  

International Statistical Institute 

Joint Research Centre 

Non-Governmental Organization 

National Statistical Institute 

Organization for Economic Cooperation and Development 

Other National Authority 

Regulatory Fitness and Performance 

Statistics on Agricultural Input and Output 

Survey on Agricultural Production Methods 

Supply Balance Sheet 

Secretariat-General 

Legal Service 

Treaty on the Functioning of the European Union 

United Nations Economic Commission for Europe 

United Nations Framework Convention on Climate Change 

United Nations Statistical Commission 

United Nations Statistics Division 

US Department of Agriculture 

WCA 2020 

World Programme for the Census of Agriculture 

80