1.1. Contact organisation
Statistics Portugal
1.2. Contact organisation unit
Economic Statistics Department / Agriculture and Environment Statistics Unit
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Av. António José de Almeida
1000-043 LISBOA
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
3 March 2025
2.2. Metadata last posted
6 March 2025
2.3. Metadata last update
3 March 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 2019/2020 (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 list of variables and their description are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2021/2286:
- Annex I - Description of the variables listed in Annex III to Regulation (EU) 2018/1091 to be used for the core structural data;
- Annex II - List of variables per module;
- Annex III - Description of the variables listed in Annex II to this Regulation to be used for the module data;
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;
- for the module “Orchards”: apples, pears, peaches, nectarines, olives, oranges, small citrus fruits, lemons and grapes for table use, each one by age of plantation and density of trees.
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
Yes3.6.2. 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 subset of agricultural holdings defined in item 3.6.2 with arable land and with other utilised agricultural area subject to drainage.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
The subset of agricultural holdings defined in item 3.6.2, with any of the individual orchard variables that meet the threshold specified in 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
Azores and Madeira
3.7.3. Criteria used to establish the geographical location of the holding
The main building for productionThe majority of the area of the holding
The most important parcel by physical size
The most important parcel by economic size
The residence of the farmer (manager) not further than 5 km straight from the farm
3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Farm structure statistics in PT covers the period from 1989 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 12-month period ending on October 31, within the reference year 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
The 12-month period ending on October 31, within the reference year 2023.
5.3. Reference day for variables on livestock and animal housing
The reference day for livestock variables was September 1, within the reference year 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 October 31, within the reference year 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on December 31, 2023.
5.7. Reference day for all other variables
The reference day was October 1, within the reference year 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
Law nº 22/2008 (Official Journal (OJ) no 92 1st Series, of 13th May 2008) - Law of the National Statistical System: It defines the general basis of the National Statistical System.
6.1.3. Link to national legal acts and other agreements
Law nº 22/2008 (Official Journal (OJ) no 92 1st Series, of 13th May 2008)
6.1.4. Year of entry into force of national legal acts and other agreements
2008
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
Not applicable.
7.1. Confidentiality - policy
The national legislation provides for the confidentiality of data collected both as regards data on enterprises and on individuals. The principle of statistical confidentiality is thus applied, i.e. individual statistical data cannot be disclosed (Article 6 of Law No 22/2008 of 13 May). The violation of statistical confidentiality considered as a breach of the obligation of professional secrecy is punishable (Article 32 of Law No 22/2008 of 13 May).
All those involved in the IFS were bound by contracts or protocols listing their responsibilities with regard to the IFS. These responsibilities were notably technical, or within the scope of statistical confidentiality and professional secrecy, in accordance with the law (Articles 6 and 32 of Law No 22/2008 of 13 May).
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)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 IFS promotes the most extensive possible use of information, while ensuring compliance with the NSS Law.
Output dissemination until municipality
The analysis made to the variables collected in IFS and their mostly physical nature prevents the respective agricultural holders from being in any way identified. Moreover, there are variables such as crop area (in the case of temporary crops, as the name indicates, they vary every year depending on market and weather conditions during the crop year, and, in the case of permanent crops, they vary depending on the options taken by farmers at a given moment, with new planting or grubbing-up, etc.), which, due to its variability, do not allow for the identification of any holder. Information on livestock is under the same conditions: due to seasonality throughout the crop year, arising either from the productive cycle or from demand peaks on feast days (Christmas, Easter, etc.), it reveals significant changes in total livestock over the year. Also, agricultural labour is not subject to secrecy, given that it is collected and made available in groups, according to the legislation in force (Article 6 (4) (b) of the NSS Law).
Therefore, and also given the vast geographical area covered, no situations are envisaged in which the information released leads to direct or indirect identification of a certain agricultural holder, therefore there will be no statistical confidentiality treatment.
Dissemination of economic data, by type
Any issues related to the typology of holdings and economic data associated with physical data that are measurable in euro may be released, provided that they are based on aggregates. This information is currently already released as such, therefore this situation is also covered by the legislation in force.
For dissemination at parish level and for some variables, cells are suppressed if the number of holdings is less than 3.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
Yes7.2.2.2. Methods of perturbation
Recoding of variablesRemoval of variables
Reduction of information
Merging categories
Rounding
Micro-aggregation
7.2.2.3. Description of methodology
The academic community has special requirements as regards statistical data, especially in terms of the development of research and preparation of Masters and PhD theses.
Against this background, Statistics Portugal established a Protocol with the Ministry of Science, Technology and Higher Education, with a view to facilitating access by researchers to the statistical data required for their activity (Protocol).
For this purpose, the interested researchers must be approved by the Office of Planning, Strategy, Assessment and International Relations, where they may obtain all the necessary information.
8.1. Release calendar
In Statistics Portugal there is a release calendar in our web portal.
8.2. Release calendar access
Please find information at INE website (calendarios).
8.3. Release policy - user access
Statistical data are a key asset in today society, and an essential tool in supporting the most relevant decision-making processes, both at the public and private level, and in carrying out analyses and research.
Statistical data are therefore of great interest to public and private decision-makers, politicians, economic agents, analysts and researchers, paving the way for all individuals to gain more awareness of their citizenship.
Data dissemination, which is a key stage of statistical activity, is instrumental in implementing and highlighting strict compliance with the mission of statistical authorities.
The dissemination policy of Statistics Portugal lays down the fundamental principles governing the dissemination of official statistics, directly or indirectly produced under its responsibility. It should have as main reference the applicable principles of the National Statistical System: technical independence, statistical confidentiality, quality and accessibility.
In accordance with provision 15, Chapter B of the dissemination policy, prior access, under embargo, to official statistical data is granted (at around 9 am of the release day) to the Directors of Madeira and Azores Regional Statistics Offices, when data allow for NUTS 2 breakdown.
There were no deviations of this policy in IFS.
8.3.1. Use of quality rating system
Yes, the EU quality rating system8.3.1.1. Description of the quality rating system
The methodology is described in the EU handbook.
Every 10 years for census but every 3-4 years to all IFS/FSS.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
Please find information at this INE website.
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
Not available.
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
Statistics Portugal - Web Portal
Access through two types of navigation (list and tree navigation). For both, select "Agriculture, forestry and fishing"/"Agricultural census".
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
Yes10.6.3. Title, publisher, year and link to national reference metadata
Title - Methodological Document (DMet) - INTEGRATED FARM STATISTICS 2023 (IFS 2023)
Publisher - Statistics Portugal (INE-PT) / Department of Economic Statistics / Agriculture and Environment Statistics Office
Statistical operation*_ name: Integrated Farm Statistics.
Acronym: IFS.
Statistical operation_ code: 9.
Accountability code / CGA: 647 - Farm statistics Survey.
DMET version: 4.0
DMET version_ into force date: October 2023.
DMet last update: October 2023.
Responsible entity: Statistics Portugal (INE-PT) / Department of Economic Statistics / Agriculture and Fishery Statistics Office
Please see the annex with Methodological Document (DMet) - INTEGRATED FARM STATISTICS 2023 (IFS 2023).
This document is included in Statistics Portugal Metadata System at: SMI website - Documentacao Metodologica.
Annexes:
10.6.3 Title, publisher, year and link to national reference metadata
10.6.4. Availability of national handbook on methodology
Yes10.6.5. Title, publisher, year and link to handbook
Title - Manual de Instruções
Publisher - Statistics Portugal
Year - 2023
Please see the annexes.
Annexes:
10.6.5 Title, publisher, year and link to handbook - Mainland
10.6.5 Title, publisher, year and link to handbook - Azores
10.6.5 Title, publisher, year and link to handbook - Madeira
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
Within the statistical production process of Statistics Portugal, any statistical operation should be certified through a methodological dossier validated by the whole organisational structure of Statistics Portugal ensuring compliance with the European Statistics Code of Practice (see the document attached).
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Use of best practicesQuality guidelines
Benchmarking
Designated quality manager, quality unit and/or senior level committee
Compliance monitoring
Peer review
External review or audit
Certification
11.1.3. Description of the quality management system and procedures
Statistics Portugal has a quality management system in place following, whenever convenient, the principles of the ISO 9001:2015 Standard, and having adopted a systematic and process-oriented approach in accordance with the Plan-Do-Check-Act cycle. This system comprises a wide range of instruments, methods, and activities covering process documentation, performance assessment, and user relations.
SP is part of the European Statistical System (ESS) and has adopted the European Statistics Code of Practice, since its first edition (2005), as firm guidance for the success of its mission. Since its last revision (November 2017), the Code comprises the Quality Declaration of the European Statistical System, 16 Principles and 84 indicators of best practices and standards for each of the Principles, defining the European benchmarks for the statistical activity, covering the institutional environment, statistical processes, and statistical outputs.
For further details on quality assurance at Statistics Portugal, please see the following website: INE website.
11.1.4. Improvements in quality procedures
Here are some examples of recent or ongoing quality assurance activities:
- Information Security Management System: the information managed by Statistics Portugal, including the procedures that support it, as well as the systems, applications and networks are valuable assets of society. By guaranteeing the confidentiality, integrity and/or availability of the information, Statistics Portugal ensures the credibility of the services it provides. Therefore, Statistics Portugal has assumed the objective of systematizing its Information Security Management System (ISMS) in alignment with the best international practices, namely ISO / IEC 27001: 2013 Standard. The ISMS is comprised of a set of policies and procedures that are available to Statistics Portugal staff and users.
- Statistical Production Process Handbook: The Statistical Production Process Handbook (3rd edition – V.2.0 – updated in 2020) describes the statistical production process systematically, following the principles and organization of version 5.1 of the Generic Statistical Business Process Model (GSBPM) (2019, UNECE), at the phase and sub-process levels. It also includes a higher level of detail through the identification of the main tasks and responsibilities associated with each of the sub-processes.
- Records Management System: Statistics Portugal is working on the development and implementation of a records management and process reengineering IT solution, which will render management and statistical production processes more efficient.
- ISO 9001:2015 Standard certification: Statistics Portugal is currently organizing information and studying the possibility of certifying Statistics Portugal Quality Management System in alignment with the ISO 9001:2015 Standard.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
Agriculture Ministry, Environmental Ministry, Farm Associations, public administration in general. the main purposes are related to draw/redraw policies (namely agricultural, regional, territorial cohesion, rural development, environmental) with sound, relevant and timeliness data.
12.1.1. Main groups of variables collected only for national purposes
The IFS was structured to make it possible to provide information on the characteristics defined for the farm structure survey (general characteristics, crop areas, livestock, agricultural buildings and structures, agricultural population and labour force, other non-agricultural activities and measures to support rural development).
Other characteristics (variables), or greater detail in mandatory characteristics pursuant to Community legislation, were also surveyed, namely irrigation and machinery and equipment.
The determination of the final version of the national characteristics to be included and the formulation of mandatory questions pursuant to Community legislation resulted from contacts with a number of entities, which contributed to defining the variables that would provide relevant statistical data with no excessive statistical burden on respondents.
12.1.2. Unmet user needs
All users' needs are met.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
Not applicable.
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 website: 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 Europa website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
For the calculation of the sample size, Annex V of Regulation (EU) 2018/1091 was taken into account. However, some variables presented greater variability a posteriori than was anticipated during the sizing.
13.2.3. Reference on method of estimation
See annex.
The tool used to calculate the RSEs was the SAS software.
Annexes:
13.2.3 Methodology used to calculate relative standard errors
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 Europa website.
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)
Below thresholds during the reference periodCeased activities
Merged to another unit
Duplicate units
13.3.1.1.2. Actions to minimize the over-coverage error
Removal of ineligible units from the records, leaving unchanged the weights for the other units13.3.1.1.3. Additional information over-coverage error
Not available.
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
Not available.
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)
New birthsNew units derived from split
Units with outdated information in the frame (variables below thresholds in the frame but above thresholds in the reference period)
13.3.1.3.3. Actions to minimise the under-coverage error
Follow up the interviews status
13.3.1.3.4. Additional information under-coverage error
Not available.
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
Yes13.3.1.5.1. Actions to minimise the contact error
Cross-check with administrative registers
13.3.1.6. Impact of coverage error on data quality
Unknown13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
Statistics Portugal considers that variables are not affected by measurement errors.
13.3.2.2. Causes of measurement errors
Not applicable13.3.2.3. Actions to minimise the measurement error
Other13.3.2.4. Impact of measurement error on data quality
None13.3.2.5. Additional information measurement error
The methodology used to avoid/minimise incorrect and/or incomplete data included:
• Interview techniques (interpretation of the questions) – questions would be posed to the interview in a way to avoid personal interpretations;
• Outline of the agricultural holding – on the occasion of the interview, the interviewer would always prepare an outline of the agricultural holding characterising it correctly, to be used as an auxiliary tool in subsequent analyses. The outline would be duly identified and attached to the questionnaire;
• Entry of “Observations” – the “Observations” field of the questionnaire should include all information deemed relevant by the interviewer, which would help to validate and analyse collected data after the interview. This prevented questionnaires from being returned and/or avoided subsequent contacts with the interviewee to confirm/justify the information.
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 identify the unitFailure to make contact with the unit
Refusal to participate
Inability to participate (e.g. illness, absence)
13.3.3.1.2. Actions to minimise or address unit non-response
RemindersLegal actions
Weighting
13.3.3.1.3. Unit non-response analysis
Statistics Portugal does not carry out a non-response analysis.
13.3.3.2. Item non-response - rate
Statistics Portugal does not carry out any analysis.
13.3.3.2.1. Variables with the highest item non-response rate
Not available.
13.3.3.2.2. Reasons for item non-response
RefusalFarmers do not know the answer
13.3.3.2.3. Actions to minimise or address item non-response
Follow-up interviews13.3.3.3. 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 entryCoding
13.3.4.2. Imputation methods
None13.3.4.3. Actions to correct or minimise processing errors
Validation rules, actions by central office of monitoring assessment, analysis from supervisors of field chain.
13.3.4.4. Tools and staff authorised to make corrections
Our IT system allows corrections at a regional or central level.
Software tools: The computer application in force (SAGR) was developed for WEB environment in the JAVA language, Web Server Apache and with the ORACLE DBMS.
Departments authorized to access and correct data: Data Collection and Management Department (DRGD) and Agriculture and Environmental Statistics Unit Department (DEE/AA)
Profiles: National and regional coordinators and supervisors
13.3.4.5. Impact of processing error on data quality
Unknown13.3.4.6. 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
Statistics Portugal does not disseminate preliminary results.
14.1.2. Time lag - final result
11.5 months (news release and online database)
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
The results were released in advance on 10 December 2024 (scheduled initially for 16 December 2024)
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
No deviations.
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
| Total | Covered by the thresholds | Attained coverage | Minimum requested coverage | |
| 1 | 2 | 3=2*100/1 | 4 | |
| UAA excluding kitchen gardens | 3 880 000 | 3 805 929 | 98.1% | 98% |
| LSU | 2 210 000 | 2 166 768 | 98.0% | 98% |
Statistics Portugal confirms that the national thresholds respect the IFS thresholds from 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
No differences.
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
No deviations.
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 Europa website.
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
No deviations.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
No deviations. For Statistics Portugal this variable is flagged L (non-significant variable).
15.1.4.2. Reasons for deviations
Not applicable.
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
No deviations.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land exists15.1.6.1. Collection of common land data
Yes15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Common land is included in the land of entities meeting the definition of agricultural holdings, having own managers.15.1.6.4. Source of collected data on common land
Surveys15.1.6.5. Description of methods to record data on common land
As any other holding.
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
No deviations.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
No differences.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
No time series break since 1989.
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
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
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
The evolution over time of the number of holdings by legal status of the holding marks a general decline in the number of holdings, with different speeds by legal personality.
- the shares of FARM_HLD and especially FARM_NFAM declined in 2023 in comparison with 2020, and that instead FARM_FAM and PER_LEG_EG+PER_LEG_NEG increased their shares.
- the number of holdings in PT decreased from 2020 to 2023 but this reduction was uneven; the holdings that ceased their activity were predominantly those with low UAA and/or SO EURO.
Here are listed some findings gathered from the tie series comparison between 2020 and 2023:
- Products like N0000S and U1000 resulted to have sharp variations between years. these variables resulted to have a high RSE.
- Holdings having benefitted of rural development measures increased remarkably in 2023.
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
Yes15.3.3.2. Results of analysis at micro level
Several data sources were used, namely Crop Statistics, Animal Statistics, IACS, Animal register, Organic farm register and Beekeepers register. The deviations observed are within the limits of the confidence intervals.
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 (main area in 1000 ha) in relative terms
They were spotted discrepancies for W1000T vs W1000 - PT so far confirms the IFS figures and will consult the PT Wine Agency for further analysis.
Coherence cross-domain: IFS vs ORGANIC CROP PRODUCTION (hectares) in relative terms
Sharp discrepancies were identified for ARA vs ARA_ORG, PECR vs PECR_ORG and UAAXL0000 vs UAAXK0000_ORG.
Although all the efforts to avoid these discrepancies, namely during the sample design and data collection, the organic figures are lower than the ones on administrative sources.
Coherence cross-domain: IFS vs ANIMAL PRODUCTION (1000 heads) in relative terms
A2010 (Bovine animals less than 1 year old), discrepancies may be due to the reference date: VALUE_IFS_2023 = 01 September 2023 and VALUE_EUROBASE = 01 December 2023. Other factors that can be pointed out to explain these discrepancies:
- Livestock variables are the least “structural” items, meaning they may vary over time and according to the reference period quicker than most variables, which makes their validation more difficult.
- There are methodological differences between the operations under analysis (eg: IFS = sample survey; Animal production for cattle = exhaustive).
- Errors in the categories classification during collection of data.
A4120 (Other sheep), VALUE_IFS_2023 = 01 September 2023 and VALUE_EUROBASE = 01 December 2023. Higher value of “Other sheep” due to the presence of lambs in the holding in December, from the concentrated birth season of September/October of the same year..
A3100 (Live swine), VALUE_IFS_2023 = 01 September 2023 and VALUE_EUROBASE = 01 December 2023. Other factors that can be pointed out to explain these discrepancies:
- Livestock variables are the least “structural” items, meaning they may vary over time and according to the reference period quicker than most variables, which makes their validation more difficult.
- For the most “structural” variable collected for pig livestock ( A3120- Breeding sows >= 50 Kg) the regional differences are not so significant.
Coherence cross-domain: IFS vs ORGANIC ANIMAL PRODUCTION (heads) in relative terms
A2000_ORG (Organic farming stock of bovine animals) - VALUE_IFS_2023 (01 September 2023) includes both animals under conversion and fully converted while VALUE_EUROBASE includes only fully converted animals;
A2300F_ORG (Organic farming stock of dairy cows) - The difference is not significant;
A4100_ORG (Organic farming stock of sheep (all ages)) - VALUE_IFS_2023 (01 September 2023) includes both animals under conversion and fully converted while VALUE_EUROBASE includes only fully converted animals;
A4200_ORG (Organic farming stock of goats (all ages)) - VALUE_IFS_2023 (01 September 2023) includes both animals under conversion and fully converted while VALUE_EUROBASE includes only fully converted animals;
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 co-ordination is made by the field chain (interviewers) since field work is distributed previously taking into account the location of the farm. Since the majority of the holdings have holders which are natural persons, there are few cases where the respondents have to answer multiple questionnaires with the same kind of questions.
16.2. Efficiency gains since the last data transmission to Eurostat
Further automationFurther training
16.2.1. Additional information efficiency gains
Not available.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Not available.
16.3.2. Module ‘Labour force and other gainful activities‘
Not available.
16.3.3. Module ‘Rural development’
Not available.
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 available.
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
As a rule, data in IFS are not subject to revisions.
17.2. Data revision - practice
Not relevant.
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
Farm register and the agricultural sample base
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
See sub-categories below.
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
Other
Annexes:
18.1.2.2.2 Stratification criteria
18.1.2.2.3. Use of systematic sampling
No18.1.2.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.2.2.2. Stratification criteria
18.1.2.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.2.2.5 Method of determination of the overall sample size
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
Sample18.1.3.2. Sampling design
Concatenation of the NUTS II region (2013) with NUTS II (2024) and Agrarian region.
18.1.3.2.1. Name of sampling design
Stratified one-stage random sampling18.1.3.2.2. Stratification criteria
Unit location18.1.3.2.3. Use of systematic sampling
No18.1.3.2.4. Full coverage strata
No full coverage strata.
18.1.3.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.3.2.5 Method of determination of the overall sample size
18.1.3.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.3.2.6 Method of allocation of the overall sample size
18.1.4. 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
See sub-categories below.
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
Other
Annexes:
18.1.4.2.2 Stratification criteria
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.4.2.2. Stratification criteria
18.1.4.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.4.2.5 Method of determination of the overall sample size
18.1.4.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.4.2.6 Method of allocation of the overall sample size
18.1.4.2.7. 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
Concatenation of the NUTS II region (2013) with NUTS II (2024) and Agrarian region.
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
Other
Annexes:
18.1.5.2.2 Stratification criteria
18.1.5.2.3. Use of systematic sampling
No18.1.5.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.5.2.2. Stratification criteria
18.1.5.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.5.2.5 Method of determination of the overall sample size
18.1.5.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.5.2.6 Method of allocation of the overall sample size
18.1.5.2.7. 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
See sub-categories below.
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
Other
Annexes:
18.1.7.2.2 Stratification criteria
18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.7.2.2. Stratification criteria
18.1.7.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.7.2.5 Method of determination of the overall sample size
18.1.7.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.7.2.6 Method of allocation of the overall sample size
18.1.7.2.7. 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
See sub-categories below.
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
Other
Annexes:
18.1.8.2.2 Stratification criteria
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.8.2.2. Stratification criteria
18.1.8.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.8.2.5 Method of determination of the overall sample size
18.1.8.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.8.2.6 Method of allocation of the overall sample size
18.1.8.2.7. 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
See sub-categories below.
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
Other
Annexes:
18.1.9.2.2 Stratification criteria
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.9.2.2. Stratification criteria
18.1.9.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.9.2.5 Method of determination of the overall sample size
18.1.9.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.9.2.6 Method of allocation of the overall sample size
18.1.9.2.7. 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
Sample18.1.10.2. Sampling design
See sub-categories below.
18.1.10.2.1. Name of sampling design
Stratified one-stage random sampling18.1.10.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
Other
Annexes:
18.1.10.2.2 Stratification criteria
18.1.10.2.3. Use of systematic sampling
No18.1.10.2.4. Full coverage strata
To increase homogeneity in the size 5 group, that contains large holdings, an additional group is defined: size 6, which we considered exhaustive. See annex 18.1.10.2.2. Stratification criteria
18.1.10.2.5. Method of determination of the overall sample size
See annex
Annexes:
18.1.10.2.5 Method of determination of the overall sample size
18.1.10.2.6. Method of allocation of the overall sample size
Neymann allocationAnnexes:
18.1.10.2.6 Method of allocation of the overall sample size
18.1.10.2.7. 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
For the study and selection of the sample the package SAS was used, with programs made for the occasion.
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
Problems related to data quality of the sourceRisk concerning the stability of the source to political changes
Other
18.1.14. 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 agricultural census is conducted every 10 years. The decennial agricultural census is complemented by sample or census-based data collections organised every 3-4 years in-between.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Face-to-face, non-electronic versionTelephone, non-electronic version
18.3.2. Data entry method, if paper questionnaires
Manual18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3 Questionnaire in English - Mainland
18.3.3 Questionnaire in English - Azores
18.3.3 Questionnaire in English - Madeira
18.3.3 Questionnaire in Portuguese - Mainland
18.3.3 Questionnaire in Portuguese - Azores
18.3.3 Questionnaire in Portuguese - Madeira
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Data format checksCompleteness checks
Routing checks
Range checks
Relational checks
Data flagging
Comparisons with previous rounds of the data collection
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
InterviewersSupervisors
Staff from local departments
Staff from central department
18.4.3. Tools used for data validation
IT tools
18.5. Data compilation
See annex
Annexes:
18.5 Data compilation
18.5.1. Imputation - rate
Not applicable.
18.5.2. Methods used to derive the extrapolation factor
Design weightNon-response adjustment
18.6. 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
CGA – Accountability code
DEE/AA – Agriculture and Environmental Statistics Unit Department
DMet – Methodological Document
DRGD – Data Collection and Management Department
ESS – European Statistical System
EU – European Union
FSS – Farm Structure Survey
GSBPM – Generic Statistical Business Process Model
IACS – Integrated Administration and Control System
IEC – International Electrotechnical Commission
IFS – Integrated Farm Statistics
INE – Instituto Nacional de Estatística / National Institute of Statistics
ISMS – Information Security Management System
ISO – International Organization for Standardization
LSU – Livestock unit
NSS – National Statistical System
NUTS – Nomenclature of territorial units for statistics
OJ – Official Journal
PhD – Doctor of Philosophy
RSE – Relative Standard Error
SGM – Standard Gross Margin
SO – Standard output
SP – Statistics Portugal
UAA – Utilised agricultural area
UNECE – United Nations Economic Commission for Europe
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 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
3 March 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;
- for the module “Orchards”: apples, pears, peaches, nectarines, olives, oranges, small citrus fruits, lemons and grapes for table use, each one by age of plantation and density of trees.
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.
See annex
Annexes:
18.5 Data compilation
See sub-categories below.
Every 10 years for census but every 3-4 years to all IFS/FSS.
See sub-categories below.
See sub-categories below.
See sub-categories below.
