1.1. Contact organisation
Natural Resources Institute Finland (Luke)
1.2. Contact organisation unit
Statistical services unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Luke, Latokartanonkaari 9, PO Box 2, FI-00790 Helsinki
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
31 October 2025
2.2. Metadata last posted
5 November 2025
2.3. Metadata last update
31 October 2025
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
3.2. Classification system
Data are arranged in tables using many classifications. Please find below information on most classifications.
The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2021/2286.
The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard gross margin (SGM) (until 2007) or standard output (SO) (from 2010 onward) which is calculated for each crop and animal. The farm type is determined by the relative contribution of the different productions to the total standard gross margin or the standard output of the holding.
The territorial classification uses the NUTS classification to break down the regional data. The regional data is available at NUTS level 2.
3.3. Coverage - sector
The statistics cover agricultural holdings undertaking agricultural activities as listed in item 3.5 below and meeting the minimum coverage requirements (thresholds) as listed in item 3.6 below.
3.4. Statistical concepts and definitions
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
3.5. Statistical unit
See sub-category below.
3.5.1. Definition of agricultural holding
The agricultural holding is a single unit, both technically and economically, that has a single management and that undertakes economic activities in agriculture in accordance with Regulation (EC) No 1893/2006 belonging to groups:
- A.01.1: Growing of non-perennial crops
- A.01.2: Growing of perennial crops
- A.01.3: Plant propagation
- A.01.4: Animal production
- A.01.5: Mixed farming or
- The “maintenance of agricultural land in good agricultural and environmental condition” of group A.01.6 within the economic territory of the Union, either as its primary or secondary activity.
Regarding activities of class A.01.49, only the activities “Raising and breeding of semi-domesticated or other live animals” (with the exception of raising of insects) and “Bee-keeping and production of honey and beeswax” are included.
3.6. Statistical population
See sub-categories below.
3.6.1. Population covered by the core data sent to Eurostat (main frame and if applicable frame extension)
The thresholds of agricultural holdings are available in the annex.
Annexes:
3.6.1 Thresholds of agricultural holdings
3.6.1.1. Raised thresholds compared to Regulation (EU) 2018/1091
No3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
No3.6.2. Population covered by the data sent to Eurostat for the modules “Labour force and other gainful activities”, “Rural development” and “Machinery and equipment”
The same population of agricultural holdings defined in item 3.6.1.
3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”
Restricted from publication
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
The subset of agricultural holdings defined in item 3.6.2 with irrigable area.
3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
The same population of agricultural holdings defined in item 3.6.1.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
Not applicable for our country, according to Article 7(5) of Regulation (EU) 2018/1091.
3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Restricted from publication
3.7. Reference area
See sub-categories below.
3.7.1. Geographical area covered
The entire territory of the country.
3.7.2. Inclusion of special territories
Åland Islands
3.7.3. Criteria used to establish the geographical location of the holding
The location where all agricultural activities are situated3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Farm structure statistics in our country cover the period from 1995 onwards. Older time series are described in the previous quality reports (national methodological reports).
3.9. Base period
The 2023 data are processed (by Eurostat) with 2020 standard output coefficients (calculated as a 5-year average of the period 2018-2022). For more information, you can consult the definition of the standard output.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land refers to the reference year 2023. For land variables, the 12-month reference period ending on 31 December 2023. In the case of successive crops from the same piece of land, the land use refers to a crop that is harvested during the reference year, regardless of when the crop in question is sown.
5.2. Reference period for variables on irrigation and soil management practices
Reference period for variables on irrigation is 12-month period ending on 31 December 2023.
Reference period for variables on soil management practices is 12-month period starting on 1 July 2022 and ending on 30 June 2023.
5.3. Reference day for variables on livestock and animal housing
For the livestock variables, the reference day is 1 April 2023.
The animal housing variables are not applicable for 2023.
5.4. Reference period for variables on manure management
The manure management variables are not applicable for 2023.
5.5. Reference period for variables on labour force
The 12-month period ending on 31 December 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2023.
5.7. Reference day for all other variables
For the module 'Machinery and equipment', the 12-month period ending on 31 December 2023.
6.1. Institutional Mandate - legal acts and other agreements
See sub-categories below.
6.1.1. National legal acts and other agreements
Legal act6.1.2. Name of national legal acts and other agreements
Statistics Act (280/2004)
Act on Food and Natural Resources Statistics (562/2014)
6.1.3. Link to national legal acts and other agreements
Statistics Act (280/2004) - in English
Statistics Act (280/2004) - in Finnish
Act on Food and Natural Resources Statistics (562/2014) - in Finnish
6.1.4. Year of entry into force of national legal acts and other agreements
Statistics Act (280/2004): 2004
Act on Food and Natural Resources Statistics (562/2014): 2014
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
The Act on Food and Natural Resources Statistics gives Luke rights to access data available in governmental registers and datasets. In addition, there are written agreements with data providing and receiving agencies. For example, Luke has an agreement with Statistics Finland covering all the datasets that we exchange between agencies without invoicing. This agreement is not publicly available.
7.1. Confidentiality - policy
Confidentiality is a fundamental principle of statistics and assures the confidential processing of data provided by informants, and the Natural Resources Institute Finland has undertaken to follow this principle. Clear provisions for statistical confidentiality and data protection are stated in the Statistics Act (280/2004), guaranteeing statistical confidentiality and data protection. The statistical confidentiality and data protection of Official Statistics of Finland are guided by the recommendations of the Advisory Board of Official Statistics of Finland. The written instructions, guidelines and training in order to preserve and ensure statistical confidentiality and data protection are available for the staff. Luke has data protection and privacy policy and practices. Luke’s data protection officer assists in general questions related to data protection.
Those working on the statistics have signed a confidentiality agreement, as well as external parties who undertake work on behalf of the Luke’s statistical services unit. According to the Statistics Act (280/2004, section 24), a person who violates the provisions on secrecy, non-disclosure and prohibition of use referred to in section 13 shall be sentenced to a fine for violation of statistical confidentiality.
Privacy policy of statistics is publicly available. It sets out principles and commitments focused on statistical confidentiality that reinforce the trust of respondents, the public and other stakeholders. We inform data providers of our practices at the beginning of each statistical survey. Provisions are in place to ensure that prior to the release of statistical information (aggregate data and microdata), statistical disclosure control methods are applied in order to secure statistical confidentiality. Microdata is released for research purposes only.
7.2. Confidentiality - data treatment
See sub-categories below.
7.2.1. Aggregated data
See sub-categories below.
7.2.1.1. Rules used to identify confidential cells
Threshold rule (The number of contributors is less than a pre-specified threshold)Secondary confidentiality rules
7.2.1.2. Methods to protect data in confidential cells
Cell suppression (Completely suppress the value of some cells)7.2.1.3. Description of rules and methods
The individual values of sums, averages or other data are not presented if calculated from figures of less than three farms. All results and data are published as weighted averages. The number of responses is not disclosed. Use of the secondary confidentiality rules has been limited and done manually. It is mainly applied to regional aggregated data tables.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
No7.2.2.2. Methods of perturbation
Removal of variablesReduction of information
7.2.2.3. Description of methodology
Microdata is not disseminated. However, researchers can get microdata for scientific research. This requires written application for the data addressed to Luke's Information Services (tietopalvelu@luke.fi). The researchers are not allowed to publish microdata.
Information for the IFS is collected for statistical use only. Microdata is made available to external users for research purposes only after ensuring that all identification information on the holder and the holding has been removed. These are for example farm ID number, address, name of the farmer and coordinates of location of the farm.
Farm-specific information is not surrendered to the authorities. Information can be provided to research institutions for research use, but only if the recipients and users adhere to the same confidentiality requirements as Luke.
Clear conditions for granting statistical authorities and researchers access to microdata for statistical and scientific purposes are stated in the Statistics Act (280/2004) and Act on Food and Natural Resources Statistics (562/2014). Luke has a policy to share published statistical data as open data for the users. According to the Statistics Act, Luke can share data with other statistical authorities taking into account confidentiality and data protection requirements. In practice, Luke and Statistics Finland share some data including identifiers.
For scientific use, Luke can give individual data without identifiers. The microdata files are delivered to the users by secure channels. In a written decision the rules for using data in a secure way are defined. Luke gives access to microdata for a certain period and after this period, the user has to delete the microdata and inform Luke when the data is deleted.
The terms of use of statistics are described at Luke's webpage. See more information on release of data and data sharing.
8.1. Release calendar
There is a common release calendar for all of Luke's statistics. The release calendar is published at the end of the year prior to its effective period. This includes final releases for IFS.
8.2. Release calendar access
8.3. Release policy - user access
All the releases are in the release calendar. Data is available to all users at 9 a.m. on the date of release. Data users can subscribe to email notifications to be alerted when statistics are published. If there is a press release linked to statistics, it will also be released earliest at 9 a.m. on the same day.
8.3.1. Use of quality rating system
No8.3.1.1. Description of the quality rating system
Not applicable.
The data are disseminated at national level every 3-4 years.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
News release related to labour force in agriculture (in Finnish and Swedish)
News release related to farmland management and irrigation (in Finnish and Swedish)
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
No10.2.2. Production of on-line publications
No10.2.3. Title, publisher, year and link
Not applicable.
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
The number of consultations of data tables is not available.
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
Online database, select 'AGRICULTURAL STATISTICS'
There are four statistics releases related to IFS 2023 data:
- Labour force: Agricultural and horticultural labour force 2023
- Farmland management and irrigation: Farmland Management and Irrigation
- Other entrepreneurship in agriculture and horticulture: Other Entrepreneurship in agriculture and horticulture
- Machinery and equipment: published under Structure of agricultural and horticultural enterprises: Machinery and equipment of agricultural and horticultural enterprises in 2023
Choose 'Statistics database' from the right side of the statistics releases page to access online datasets.
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
Yes10.5. Dissemination format - other
Not available.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
See sub-categories below.
10.6.1. Metadata completeness - rate
Not requested.
10.6.2. Availability of national reference metadata
No10.6.3. Title, publisher, year and link to national reference metadata
Not applicable.
10.6.4. Availability of national handbook on methodology
No10.6.5. Title, publisher, year and link to handbook
Not applicable.
10.6.6. Availability of national methodological papers
No10.6.7. Title, publisher, year and link to methodological papers
Not applicable.
10.7. Quality management - documentation
Not available.
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Training coursesUse of best practices
Quality guidelines
11.1.3. Description of the quality management system and procedures
The quality management framework follows the European Statistics Code of Practice (CoP). The producers of Official Statistics of Finland have approved a common quality assurance in which they commit to common quality criteria and quality assurance measures. The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice.
We follow the Generic Statistical Business Process Model (GSBPM) for the statistical production. We monitor the quality of the material at different stages of the process. With regard to the data collected, the key point for ensuring data quality is the data collection application, which includes a wide range of checks. We check the quality of the register data on a farm-by-farm basis, for example by checking for changes from the previous year. Data verification is carried out in collaboration with subject matter experts, statisticians, and other specialists.
An example of training courses is the online course ‘Code of Practices’ produced by Statistics Finland. Good practices are presented, for example, in Statistics Finland's Quality Guidelines for Official Statistics handbook.
The Advisory Board of Official Statistics of Finland has published the quality criteria that we fulfil in Luke.
11.1.4. Improvements in quality procedures
Systematic validation improvements with SAS-procedures.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
The users are all the stakeholders in the Common Agricultural Policy (CAP) and other policy areas such as environment, regional development, climate change and health:
- policy makers: European Commission's Directorate-General for Agriculture and Rural Development (DG AGRI), National Ministries of Agriculture, European Parliament, etc.;
- reviewers, assessors, analysts;
- professional groups (unions, press, farmers);
- researchers;
- educational institutions.
12.1.1. Main groups of variables collected only for national purposes
Following data was collected for national statistical purposes:
- Number of foreign labour force
- Energy consumption of agriculture and horticulture
- Information on other gainful activity: The most important line of business
- Usage of farrowing crates for sows (related to pig housing)
- Soil management methods: type of drainage (subsurface drainage area, controlled subsurface drainage area, surface drainage area, no drainage area), methods of tillage (autumn ploughing, spring ploughing, deep reduced tillage, shallow reduced tillage, sowing in untilled soil)
12.1.2. Unmet user needs
We ask stakeholders about their data needs and include them in the questionnaire if the data needs fit within the areas covered by the survey.
12.1.3. Plans for satisfying unmet user needs
We do not have plans on how to satisfy all user needs.
12.2. Relevance - User Satisfaction
No satisfaction survey is carried out.
12.2.1. User satisfaction survey
No12.2.2. Year of user satisfaction survey
Not applicable.
12.2.3. Satisfaction level
Not applicable12.3. Completeness
Information on not collected, not-significant and not-existent variables is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
12.3.1. Data completeness - rate
Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.
13.1. Accuracy - overall
See categories below.
13.2. Sampling error
See sub-categories below.
13.2.1. Sampling error - indicators
Please find the relative standard errors on Eurostat’s website, at the link: CircaBC website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
All the land and animal variables are from the administrative registers. There are some variables which do not meet RSE thresholds stated in Regulation (EU) 2018/1091. Reason for this is that there are quite few pig and poultry farms in Finland and there are big variations between them.
There is a significant variance in the variable ARA (arable land) in the FI1D region (Eastern and Northern Finland). This NUTS 2 region is geographically very long in the north-south direction, which leads to substantial differences in farms across the area. In the future, we will calibrate the statistical weights to improve the estimates for arable land, pigs and poultry.
13.2.3. Reference on method of estimation
The results were estimated with SAS software. Variances of the characteristics collected on the sample survey were estimated using the CLAN software developed by Statistics Sweden.
13.2.4. Impact of sampling error on data quality
Low13.3. Non-sampling error
See sub-categories below.
13.3.1. Coverage error
See sub-categories below.
13.3.1.1. Over-coverage - rate
The over-coverage rate is available on Eurostat’s website, at the link: CircaBC.
The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.1.1.1. Types of holdings included in the frame but not belonging to the population of the core (main frame and if applicable frame extension)
Temporarily out of production during the reference period13.3.1.1.2. Actions to minimize the over-coverage error
None13.3.1.1.3. Additional information over-coverage error
Agricultural and horticultural register is updated every year using administrative registers.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under-coverage error
See sub-categories below.
13.3.1.3.1. Under-coverage rate
There was no under-coverage. Statistical farm register includes only holding with Standard Output (SO) greater or equal to 2000 SO.
13.3.1.3.2. Types of holdings belonging to the population of the core but not included in the frame (main frame and if applicable frame extension)
None13.3.1.3.3. Actions to minimise the under-coverage error
Not applicable.
13.3.1.3.4. Additional information under-coverage error
We update the statistical agricultural and horticultural register every year. The frame was updated for the year 2023 before farm structure survey started, and thus prevented under-coverage.
13.3.1.4. Misclassification error
No13.3.1.4.1. Actions to minimise the misclassification error
Not applicable.
13.3.1.5. Contact error
No13.3.1.5.1. Actions to minimise the contact error
Not applicable.
13.3.1.6. Impact of coverage error on data quality
None13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
The most important administrative source of data for farm structure statistics is Integrated Administration and Control System (IACS), where the date from farm subsidy applications is recorded. Farmers almost invariably fill in their subsidy applications meticulously, as they may otherwise face sanctions. Errors in land areas and livestock figures are usually minor and result from misunderstandings, lack of time, or inaccurate data entry. Information from other animal registers (bovine, pig, sheep and goat) is used as a source of animal number data. Farmers must inform the record keeper of any changes in their farm’s animal numbers by the due date. These registers are therefore largely comprehensive.
Farmers found questions concerning their labour force and the farm’s other business activities quite difficult. Calculating working hours retrospectively was a problem, as most farms do not keep an account of working hours. In these cases, calculating the annual number of hours spent on farm work was sometimes challenging. In Finland, agricultural workers – and livestock farmers in particular – work more than 1 800 hours per year, that is, more than one person-year. In previous surveys, forestry work may have been partially included in farm work. From 2005 onwards until 2016, the number of hours spent on forestry work has been a separate item in the questionnaire. This time there was no separate category for forestry work. However, there was instruction that working hours are not including forestry work. Even now, the classification of certain tasks is open to various interpretations. In some cases, it is not always clear at what point farm or horticultural production becomes further processing, that is, other business activity.
Other questions for which farmers’ responses may contain measurement errors include irrigation, arable farming, horticulture, and livestock production. As this information may not be directly obtainable from registers, farmers may find it difficult to provide completely accurate information. This does not, however, have a significant effect on the final results.
13.3.2.2. Causes of measurement errors
Complexity of variablesRespondents’ inability to provide accurate answers
13.3.2.3. Actions to minimise the measurement error
Pre-testing questionnaireExplanatory notes or handbooks for enumerators or respondents
On-line FAQ or Hot-line support for enumerators or respondents
Training of enumerators
13.3.2.4. Impact of measurement error on data quality
Low13.3.2.5. Additional information measurement error
Not available.
13.3.3. Non response error
See sub-categories below.
13.3.3.1. Unit non-response - rate
See item 13.3.1.1.
The unit non-response rate is unweighted.
The unit non-response rate is calculated as the share of eligible non-respondent holdings to the eligible holdings. The eligible holdings include those holdings with unknown eligibility status which are imputed or re-weighted for (therefore considered eligible).
The unit non-response rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.3.1.1. Reasons for unit non-response
Failure to make contact with the unitRefusal to participate
13.3.3.1.2. Actions to minimise or address unit non-response
None13.3.3.1.3. Unit non-response analysis
We did not carry out non-response analysis. There is only partial non-response because most of the core variables are from the administrative registers.
13.3.3.2. Item non-response - rate
We do not calculate item non-response rate because it is impossible to know whether farmer should have answered some special questions or not (e.g. OGA questions).
13.3.3.2.1. Variables with the highest item non-response rate
Not applicable.
13.3.3.2.2. Reasons for item non-response
Not applicable13.3.3.2.3. Actions to minimise or address item non-response
Imputation13.3.3.3. Impact of non-response error on data quality
Low13.3.3.4. Additional information non-response error
Not available.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
Data entryData processing
13.3.4.2. Imputation methods
None13.3.4.3. Actions to correct or minimise processing errors
Cross check of results to compare with earlier figures. Number of animals and UAA have been published earlier as official statistics and figures have been processed.
13.3.4.4. Tools and staff authorised to make corrections
Statistical department uses SAS software and only staff in the Statistical department are allowed to make corrections.
13.3.4.5. Impact of processing error on data quality
Low13.3.4.6. Additional information processing error
Not available.
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
Not applicable, because only final results are published.
14.1.2. Time lag - final result
14 months.
14.2. Punctuality
See sub-categories below.
14.2.1. Punctuality - delivery and publication
See sub-categories below.
14.2.1.1. Punctuality - delivery
Not requested.
14.2.1.2. Punctuality - publication
National statistics were published as scheduled in February, April, May and June 2025.
15.1. Comparability - geographical
See sub-categories below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable, because there are no mirror flows in Integrated Farm Statistics.
15.1.2. Definition of agricultural holding
See sub-categories below.
15.1.2.1. Deviations from Regulation (EU) 2018/1091
The definition of the agricultural holding is the same as in Regulation (EU) 2018/1091.
15.1.2.2. Reasons for deviations
Not applicable.
15.1.3. Thresholds of agricultural holdings
See sub-categories below.
15.1.3.1. Proofs that the EU coverage requirements are met
We requested prior approval from Eurostat before the data collection and provided Eurostat the numeric proofs mentioned in Article 3(3) of Regulation (EU) 2018/1091. Eurostat issued the prior approval.
However, in practice, according to Eurostat's analysis, the used economic threshold (2 000 euros) is not raised and meets the thresholds set in Annex II of Regulation (EU) 2018/1091.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
There are no differences between the national thresholds and the thresholds used for the data sent to Eurostat.
15.1.3.3. Reasons for differences
Not applicable.
15.1.4. Definitions and classifications of variables
See sub-categories below.
15.1.4.1. Deviations from Regulation (EU) 2018/1091 and EU handbook
The variable SHR_ARA_ROT (Share of arable land with crop rotation) is calculated by crops being cultivated three consecutive years in the same plot, as the Handbook suggests five consecutive years. There are no other differences in the definition of variables.
15.1.4.1.1. The number of working hours and days in a year corresponding to a full-time job
The information is available on Eurostat’s website, at the link: CircaBC.
The number of working hours and days in a year for a full-time job correspond to one annual working unit (AWU) in the country. One annual work unit corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis. Annual working units are used to calculate the farm work on the agricultural holdings.
15.1.4.1.2. Point chosen in the Annual work unit (AWU) percentage band to calculate the AWU of holders, managers, family and non-family regular workers
See item 15.1.4.1.1.
15.1.4.1.3. AWU for workers of certain age groups
See item 15.1.4.1.1.
15.1.4.1.4. Livestock coefficients
Finland uses LSU coefficients which are set in Regulation (EU) 2018/1091.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
There are no "Other livestock" in any farm.
15.1.4.2. Reasons for deviations
The share of arable land with crop rotation was calculated by mistake using three consecutive years instead of five.
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
There are no deviations from Regulation (EU) 2018/1091.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land does not exist15.1.6.1. Collection of common land data
Not applicable15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Not applicable15.1.6.4. Source of collected data on common land
Not applicable15.1.6.5. Description of methods to record data on common land
Not applicable.
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
Not applicable.
15.1.7. National standards and rules for certification of organic products
See sub-categories below.
15.1.7.1. Deviations from Council Regulation (EC) No 834/2007
There are no deviations.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
There are no differences in methods used across regions within the country.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
Since 2013.
15.2.2. Definition of agricultural holding
See sub-categories below.
15.2.2.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.2.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
15.2.3. Thresholds of agricultural holdings
See sub-categories below.
15.2.3.1. Changes in the thresholds of holdings for which core data are sent to Eurostat since the last data transmission
There have been no changes15.2.3.2. Description of changes
Not applicable.
15.2.4. Geographical coverage
See sub-categories below.
15.2.4.1. Change in the geographical coverage since the last data transmission to Eurostat
There have been no changes15.2.4.2. Description of changes
Not applicable.
15.2.5. Definitions and classifications of variables
See sub-categories below.
15.2.5.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.5.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
15.2.6. Reference periods/days
See sub-categories below.
15.2.6.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.6.2. Description of changes
Not applicable.
15.2.7. Common land
See sub-categories below.
15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no changes15.2.7.2. Description of changes
Not applicable.
15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat
In 2023, the total number of holdings in Finland declined by approximately 7%. The figures reflect the long-term declining trend in the number of family farms and group holdings, whereas the proportion of legal person farms is increasing.
Since Finland did not provide core data for all farms but only for the sample farms, even a small change in crops with relatively little cultivation area - when combined with a large weighting factor - can have a significant impact on the overall results and reported cultivation areas.
- C1110T - Common wheat and spelt - outdoor. The area under wheat cultivation has shown a yearly increase since 2018.
- C1200T - Rye and winter cereal mixtures (maslin) - outdoor. As with common wheat, the area under rye cultivation has increased annually since 2020.
- P1000T - Field peas, beans and sweet lupins - outdoor. The observed change is explained by the increased cultivation area of field peas.
- I1110T - Rape and turnip rape seeds - outdoor. The change is due to an increase in the cultivation area of turnip rape.
- I1120T - Sunflower seed - outdoor. The cultivated area of sunflower seed has increased.
- I2200T - Hemp - outdoor. The cultivated area is small and there is a large variation between years.
- I5000T - Aromatic, medicinal and culinary plants - outdoor. The area is small and there is a large variation between years. The observed decrease can be explained mostly by a reduction in the cultivation area of caraway.
- V0000_S0000TO - Fresh vegetables (including melons) and strawberries grown in rotation with non-horticultural crops - outdoor - open field. The time series evolution can be explained by a decrease in the cultivation area of garden peas.
- J1000T - Permanent pastures and meadow (excluding rough grazing) - outdoor and J2000T - Permanent rough grazing - outdoor. The area of permanent pastures, meadows and rough grazing has a long-term declining trend.
- F3000T - Berries (excluding strawberries) - outdoor. The cultivation area of several berry crops (excluding strawberries) has increased.
- I6000T + I9000T Energy crops n.e.c. - outdoor, Other industrial crops n.e.c. - outdoor. Some oilseeds and fibre crops were misclassified to I9000T in IFS 2020.
- A3120 - Breeding sows, live weight 50 kg or over. The number of animals has declined because of development of pork market.
- A4220 - Other goats. In 2020, it seems that some animals were missing from this group.
- LSU: The share of holdings without livestock has increased in 2023 and the share of holdings having LSU20-49 (from 20 to 49.9 LSU) has decreased.
- Labour force: The proportion of non-family labour of the total AWUs in agriculture has increased. Non-family labour has a higher proportion of women compared to holders and other family labour. This has contributed to the increase in the proportion of F_AWU.
15.2.9. Maintain of statistical identifiers over time
No15.3. Coherence - cross domain
See sub-categories below.
15.3.1. Coherence - sub annual and annual statistics
Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.
15.3.2. Coherence - National Accounts
Not applicable, because Integrated Farm Statistics have no relevance for national accounts.
15.3.3. Coherence at micro level with data collections in other domains in agriculture
See sub-categories below.
15.3.3.1. Analysis of coherence at micro level
No15.3.3.2. Results of analysis at micro level
In Finland, we get a lot of data from registers. All the animals and crop areas are from agricultural registers. We use same data in the animal and crop statistics than in the IFS.
15.3.4. Coherence at macro level with data collections in other domains in agriculture
See sub-categories below.
15.3.4.1. Analysis of coherence at macro level
Yes15.3.4.2. Results of analysis at macro level
Coherence cross-domain: IFS vs CROP PRODUCTION
With regards to the discrepancies on:
- C0000T - Cereals for the production of grain (including seed) - outdoor, and
- G0000T - Plants harvested green from arable land - outdoor.
In IFS data, the values for the variables C0000T and G0000T are from IACS. In crop statistics, the area of grain harvested C0000T is smaller because a part of the crop is harvested as fresh crop. This area is recorded under G0000T in crop statistics.
Coherence cross-domain: IFS vs ORGANIC CROP PRODUCTION
PECRT_ORG - Permanent crops (including young and temporarily abandoned plantations, excluding areas producing for own consumption only) - outdoor - organic
The IFS variable PECRT_ORG is not comparable with PECR, as this is not an organic area.
Coherence cross-domain: IFS vs ANIMAL PRODUCTION
A3110 - Piglets, live weight under 20 kg
The Eurobase value is the number of pigs on 1 December 2023, whereas the IFS value is the number of pigs on 1 April 2023. There is also a difference in the classification for this variable.
Coherence cross-domain: IFS vs ORGANIC ANIMAL PRODUCTION
A2300F_ORG - Dairy cows - organic. The number of organic cows has decreased.
A4100_ORG - Sheep - organic. The number of organic sheep has decreased. The number of animals for IFS is taken from IACS, while the number of animals in Eurobase is based on the organic farming register. The weights overestimate the number of sheep in IFS data.
A4200_ORG - Goats - organic. The number of organic goats has increased. The number of animals for IFS is taken from IACS, while the number of animals in Eurobase is based on the organic farming register. The weights overestimate the number of goats in IFS data.
15.4. Coherence - internal
The data are internally consistent. This is ensured by the application of a wide range of validation rules.
See sub-categories below.
16.1. Coordination of data collections in agricultural statistics
The schedules of the IFS 2023 survey were synchronised to avoid the situation where farmers must answer to several surveys simultaneously from Luke. There is also coordination that one question is asked only once.
Luke follows the data collection principle laid down in the Finnish Statistics Act (280/2004): existing register data should be utilised where possible, and no information included in registers should be inquired upon again for statistical purposes. The majority of the data for the IFS 2023 were taken directly from statistical registers.
For IFS 2023, we got farmers' education from education register and work done by farm worker from Farmers' Social Insurance Institution (Mela). The Incomes Register was used to define how much regularly hired employees worked.
16.2. Efficiency gains since the last data transmission to Eurostat
Further automationIncreased use of administrative data
16.2.1. Additional information efficiency gains
Same data structure as in 2020 helped us to use the same database and mapping tables.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
We did not record the duration of collecting core variables from farms. A big part of core variables were taken from the registers. Collecting of the rest of the core variables and data for all the modules took 26 minutes per farm on average.
16.3.2. Module ‘Labour force and other gainful activities‘
Not available.
16.3.3. Module ‘Rural development’
Not relevant, because the data was taken from administrative sources.
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Not available.
16.3.6. Module ‘Soil management practices’
Not available.
16.3.7. Module ‘Machinery and equipment’
Not available.
16.3.8. Module ‘Orchard’
Not applicable (exemption from data collection).
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
Revision policy follows release guidelines of the Advisory Board of Official Statistics of Finland. These guidelines are set up according to European requirements and are publicly available (only in Finnish). According to these guidelines, errors discovered in published data are corrected as soon as they are discovered and information on major errors and revisions will be published earliest possible.
If statistical data needs to be corrected, this must be mentioned on the release page with a link provided to a separate page explaining which figures have been corrected. For example, the agricultural and horticultural labour force statistics were corrected twice (in March 2022 and February 2025), and the corrections were explained on the correction page.
17.2. Data revision - practice
The data collected for IFS was delivered to Eurostat as a single file. The information was validated by Eurostat, which gives feedback as list of errors and items to be checked. Luke then carried out the necessary changes and corrections. If any errors are later detected or specified, a revised file will be sent to Eurostat.
Part of the data were published nationally. Once the data have passed Eurostat’s validation process, a final version will be published. Any corrections to published national data will be made according to the recommendations of the Advisory Board of Official Statistics of Finland.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
See sub-categories below.
18.1.1. Sampling design & Procedure frame
See sub-categories below.
18.1.1.1. Type of frame
List frame18.1.1.2. Name of frame
Statistical register of agricultural and horticultural enterprises.
18.1.1.3. Update frequency
Annual18.1.2. Core data collection on the main frame
See sub-categories below.
18.1.2.1. Coverage of agricultural holdings
Sample18.1.2.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.2.2.1. Name of sampling design
Stratified one-stage random sampling18.1.2.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.2.2.3. Use of systematic sampling
No18.1.2.2.4. Full coverage strata
There were no full coverage strata.
18.1.2.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.2.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.3. Core data collection on the frame extension
See sub-categories below.
18.1.3.1. Coverage of agricultural holdings
Not applicable18.1.3.2. Sampling design
Not applicable.
18.1.3.2.1. Name of sampling design
Not applicable18.1.3.2.2. Stratification criteria
Not applicable18.1.3.2.3. Use of systematic sampling
Not applicable18.1.3.2.4. Full coverage strata
Not applicable.
18.1.3.2.5. Method of determination of the overall sample size
Not applicable.
18.1.3.2.6. Method of allocation of the overall sample size
Not applicable18.1.4. Module “Labour force and other gainful activities”
See sub-categories below.
18.1.4.1. Coverage of agricultural holdings
Sample18.1.4.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.4.2.1. Name of sampling design
Stratified one-stage random sampling18.1.4.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
There were no full coverage strata.
18.1.4.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.4.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable18.1.5. Module “Rural development”
See sub-categories below.
18.1.5.1. Coverage of agricultural holdings
Sample18.1.5.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.5.2.1. Name of sampling design
Stratified one-stage random sampling18.1.5.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.5.2.3. Use of systematic sampling
No18.1.5.2.4. Full coverage strata
There were no full coverage strata.
18.1.5.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.5.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.6. Module “Animal housing and manure management module”
Restricted from publication
18.1.6.1. Coverage of agricultural holdings
Restricted from publication
18.1.6.2. Sampling design
Restricted from publication
18.1.6.2.1. Name of sampling design
Restricted from publication
18.1.6.2.2. Stratification criteria
Restricted from publication
18.1.6.2.3. Use of systematic sampling
Restricted from publication
18.1.6.2.4. Full coverage strata
Restricted from publication
18.1.6.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.6.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.7. Module ‘Irrigation’
See sub-categories below.
18.1.7.1. Coverage of agricultural holdings
Sample18.1.7.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.7.2.1. Name of sampling design
Stratified one-stage random sampling18.1.7.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
There were no full coverage strata.
18.1.7.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.7.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.7.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.8. Module ‘Soil management practices’
See sub-categories below.
18.1.8.1. Coverage of agricultural holdings
Sample18.1.8.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.8.2.1. Name of sampling design
Stratified one-stage random sampling18.1.8.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
There were no full coverage strata.
18.1.8.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.8.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.8.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.9. Module ‘Machinery and equipment’
See sub-categories below.
18.1.9.1. Coverage of agricultural holdings
Sample18.1.9.2. Sampling design
The sample was stratified by unit location, unit size and unit specialisation.
- Unit location: NUTS 3
- Unit size classes (SO in euros):
-
- 2 000 – 25 000
- 25 000 – 50 000
- 50 000 – 100 000
- 100 000 – 250 000
- Greater than 250 000
- Unit specialisation:
-
- Cereals production and other plant production
- Greenhouse production
- Outdoor production
- Milk production
- Beef production
- Other cattle husbandry
- Pig husbandry
- Poultry husbandry
- Other grazing livestock
- Mixed production
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
There were no full coverage strata.
18.1.9.2.5. Method of determination of the overall sample size
We used optimal sample size method.
18.1.9.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.9.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.10. Module ‘Orchard’
See sub-categories below.
18.1.10.1. Coverage of agricultural holdings
Not applicable18.1.10.2. Sampling design
Not applicable.
18.1.10.2.1. Name of sampling design
Not applicable18.1.10.2.2. Stratification criteria
Not applicable18.1.10.2.3. Use of systematic sampling
Not applicable18.1.10.2.4. Full coverage strata
Not applicable.
18.1.10.2.5. Method of determination of the overall sample size
Not applicable.
18.1.10.2.6. Method of allocation of the overall sample size
Not applicable18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.11. Module ‘Vineyard’
Restricted from publication
18.1.11.1. Coverage of agricultural holdings
Restricted from publication
18.1.11.2. Sampling design
Restricted from publication
18.1.11.2.1. Name of sampling design
Restricted from publication
18.1.11.2.2. Stratification criteria
Restricted from publication
18.1.11.2.3. Use of systematic sampling
Restricted from publication
18.1.11.2.4. Full coverage strata
Restricted from publication
18.1.11.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.11.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.12. Software tool used for sample selection
SAS
18.1.13. Administrative sources
See sub-categories below.
18.1.13.1. Administrative sources used and the purposes of using them
The information is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
18.1.13.2. Description and quality of the administrative sources
See the Excel file in the annex.
Annexes:
18.1.13.2. Description and quality of administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
None18.1.14. Innovative approaches
The information on the innovative approaches and the quality methods applied is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
18.2. Frequency of data collection
The data collection is carried out every 3 to 4 years.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Telephone, electronic versionUse of Internet
18.3.2. Data entry method, if paper questionnaires
Not applicable18.3.3. Questionnaire
Please find the questionnaires in Finnish and English in annexes. There were no paper questionnaires, the data was collected via web form.
Annexes:
18.3.3 Questionnaire in English
18.3.3 Questionnaire in Finnish
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Completeness checksRange checks
Comparisons with previous rounds of the data collection
Other
18.4.2. Staff involved in data validation
Staff from central department18.4.3. Tools used for data validation
SAS and Eurostat's validation checks through eDAMIS.
18.5. Data compilation
We used Neyman's optimal allocation.
18.5.1. Imputation - rate
Not applicable.
18.5.2. Methods used to derive the extrapolation factor
Design weight18.6. Adjustment
Covered under Data compilation.
18.6.1. Seasonal adjustment
Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.
See sub-categories below.
19.1. List of abbreviations
AWU – Annual Working Unit
CAP – Common Agricultural Policy
CoP – Code of Practice
DG – Directorate-General
DG AGRI – Directorate-General for Agriculture and Rural Development
EU – European Union
GSBPM – Generic Statistical Business Process Model
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LSU – Livestock unit
NUTS – Nomenclature of territorial units for statistics
OGA – Other gainful activities
RSE – Relative standard error
SGM – Standard Gross Margin
SO – Standard output
UAA – Utilised agricultural area
19.2. Additional comments
No additional comments.
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
31 October 2025
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
See sub-category below.
See sub-categories below.
See sub-categories below.
See sub-categories below.
See categories below.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
We used Neyman's optimal allocation.
See sub-categories below.
The data are disseminated at national level every 3-4 years.
See sub-categories below.
See sub-categories below.
See sub-categories below.
