1.1. Contact organisation
Swedish Board of Agriculture
1.2. Contact organisation unit
Statistics Division
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Jordbruksverket
SE-551 82, JÖNKÖPING
Sweden
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
28 February 2025
2.2. Metadata last posted
6 March 2025
2.3. Metadata last update
28 February 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 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, drainage on the agricultural holdings;
- 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 area 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.
In Sweden, energy forest is considered as an agricultural activity.
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 hodlings
3.6.1.1. Raised thresholds compared to Regulation (EU) 2018/1091
Yes3.6.1.2. 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 3.6.1 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”
The subset of agricultural holdings defined in item 3.6.1, 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
Not applicable.
3.7.3. Criteria used to establish the geographical location of the holding
The main building for productionThe location where all agricultural activities are situated
The majority of the area of the holding
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
The records of agricultural statistics in Sweden date back to the beginning of the nineteenth century. In the first half of the twentieth century, established statistical methods were introduced for production of statistics on agricultural holdings, crop areas, crop production, livestock, etc. In 1968, in order to improve the coordination of the statistics within the agricultural sector, Sweden established a farm register which was updated annually. The register covered:
- all agricultural holdings with more than 2 hectares of arable land,
- holdings with a large number of livestock but with less than 2 hectares of arable land, and
- holdings with horticultural production.
Since its establishment the farm register has been used as a sample frame for both farm structure surveys and other agricultural statistical surveys.
During the 1990s, the farm structure surveys were subject to few methodological and technical changes. The substitution of some censuses with sample surveys, together with the processing of statistics in PC-environment, led to a reduction of the costs for producing agricultural statistics. However, the substitution of some censuses with sample surveys inevitably led to lack of agricultural statistics on municipality level for the years the substitution occurred.
The Swedish accession to the European Union in 1995 created the need for adapting national agricultural statistics to the EU legislation. Until 2001, Sweden conducted farm structure surveys annually, switching every year between the EU and the national legislation. The main difference between these two surveys, consisted on the number of the characteristics surveyed. The national farm structure surveys met primarily national requirements and therefore were far less extensive than the ones based on the EU legislation. In 2001, national farm structure surveys were abandoned, thus embracing the surveys based on EU legislation as the sole farm structure survey.
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, yes/no on the presence of machinery and equipment) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land shall refer to the reference year 2023. The specific 12-month reference period ends on 31 October 2023. In the case of successive crops from the same piece of land, the land use shall refer 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 1 November 2022 - 31 October 2023 for both the "Irrigation" and "Soil management practices" modules.
For the variable irrigable area included into the core module, the reference period is the 12-month period starting on 1 June 2022 and ending on 31 May 2023.
5.3. Reference day for variables on livestock and animal housing
The reference day is 1 June 2023 for livestock variables. 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 starting on 1 June 2022 and ending on 31 May 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2023. In practice the years 2021 and 2022 as the Regulation (EU) No 1305/2013 no longer applies for 2023.
5.7. Reference day for all other variables
Machinery and equipment module: the reference day is 1 June 2023.
Reference day for all other variables: the 12-month period starting on 1 June 2022 and ending on 31 May 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
1) Act (2001:99) on Official Statistics
2) Regulation (2001:100) on Official Statistics
3) The Swedish Board of Agriculture's Regulations on Statistical Surveys of the Structure of Agriculture (SJVFS 2023:1)
6.1.3. Link to national legal acts and other agreements
- Riksdagen website - Lag-200199-om-den-officiella-statistiken_sfs-2001-99.
- Riksdagen website - Forordning-2001100-om-den-officiella_sfs-2001-100.
6.1.4. Year of entry into force of national legal acts and other agreements
1) 2001
2) 2001
3) 2023
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
The Regulation (2001:100) on Official Statistics regulates how data can be shared between institutions. Article 13 of the Regulation states that all data, free of charge, shall be shared with Statistics Sweden and other institutions. Institutions can either obtain data from each other or from the Statistics Sweden.
7.1. Confidentiality - policy
The confidentiality of the data was kept in accordance with Act 24, 8 § of the Swedish confidentiality law on statistics (2009:400). According to this Act, the data provided by the holdings must be used for only statistical at an aggregated level and for research purposes. In both these cases, information that could identify the holder and the holding itself should be hidden.
The questionnaires sent in by the farmers were disclosed only for the staff of the Statistics Division, and could not be shown to anyone outside of the division. All the personnel working within the Statistical Division of the Swedish Board of Agriculture (including the ones employed to work with the IFS 2023) had to sign a statistical confidentiality form which guaranteed the use and the storage of the data in accordance with the confidentiality law.
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 Swedish confidentiality law on statistics (2009:400) applies during the dissemination of the results. To ensure non-identification of individual holdings in the dissemination, the number of holdings within a region or municipality is not disclosed if the region or the municipality in question has less than x agricultural holdings (where x indicates a confidential number). In such cases the symbol [..] is given in the table cell.
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
None7.2.2.3. Description of methodology
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. The user must make an official request, stating information about the purpose, etc., of accessing microdata. Based on this, a disclosure review is made with respect to confidentiality.
For statistical purposes, authorities within the Swedish statistical system can share information between authorities. Statistics Sweden provides a web form for ordering microdata. See the SCB website - Bestalla mikrodata.
8.1. Release calendar
There is a release calendar for all official statistics. This is decided in December the year prior to the release year of the publications. In this release calendar the results based on IFS are included.
| Name of the report | Reference | Publication date |
|---|---|---|
| Livestock in June 2023, preliminary results | JO0103 | 12 December 2023 |
| Livestock in June 2023, final results | JO0103 | 31 January 2024 |
| Use of agricultural land 2023, final results | JO0104 | 07 February 2024 |
| Type of farming 2023. Swedish typology | JO0105 | 07 Mars 2024 |
| Holdings and holders 2023 | JO0106 | 21 Mars 2024 |
| Farm labour force 2023 | JO0401 | 13 June 2024 |
| Other gainful activities on agricultural holdings 2023 | JO0108 | 11 June 2024 |
| Full-time farming in Sweden 2023 | JO0109 | 18 June 2024 |
| Horticultural fruit trees 2023 | JO0119 | 07 November 2024 |
| Irrigation and drainage of agricultural land 2023 | JO0112 | 20 November 2024 |
There will also be a release of data on machinery and equipment during 2025. Date is not set at this moment.
8.2. Release calendar access
The release calendar is published on the website of the Swedish Board of Agriculture in December, every year.
Link to the release calendar at the Swedish Board of Agriculture (in Swedish).
8.3. Release policy - user access
All statistics are published on the website of the Swedish Board of Agriculture and are described in our statistic reports. The statistics are released at 8:00 A.M. on the publication date stated on the release calendar.
Release of data is made available to all users at the same time. No users can access the data before it has been released at 8:00 A.M. on the predefined release date.
8.3.1. Use of quality rating system
Yes, another quality rating system8.3.1.1. Description of the quality rating system
The quality rating system that we use is based on the values of coefficients of variation. If the coefficients of variation are 35% or more, the data is seen as too unreliable and will therefore not be published.
Some of the statistics are collected and disseminated on the years the farm structure surveys are conducted, while others are collected and disseminated on yearly bases.
Statistics disseminated every IFS-year:
- Type of farming. Swedish typology;
- Holdings and holders;
- Other gainful activities on agricultural holdings;
- Farm labour force;
- Full-time farming in Sweden.
Statistics disseminated on yearly bases:
- Livestock in June, preliminary results;
- Livestock in June, final results;
- Use of agricultural land, final results.
Regarding 2023, there will also be a publication on irrigation and drainage of agricultural land.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
Livestock in June 2023, preliminary results
Link: Antalet lantbruksdjur minskar.
Livestock in June 2023, final results
Link: Färre djur på svenska gårdar
Type of farming 2023. Swedish typology
Link: Färre jordbruksföretag - störst minskning på växtodlingssidan
Holdings and holders 2023
Link: Antal kvinnor med jordbruk i enskild firma ökar
Other gainful activities on agricultural holdings 2023
Link: Kombinationsverksamheter viktiga för jordbruket
Farm labour force 2023
Link: Antal sysselsatta i jordbruket fortsätter att minska
Irrigation and drainage of agricultural land 2023
Link: Bevattning och dränering av jordbruksmark 2023
For publications "Use of agricultural land 2023, final results", "Full-time farming in Sweden 2023" and "Horticultural fruit trees 2023", there were no press releases.
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
Yes, in English also10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
Livestock in June 2023, preliminary results (JO0103), Anders Grönvall, 2023
Link: Lantbrukets djur i juni 2023. Preliminär statistik
Livestock in June 2023, final results (JO0103), Anders Grönvall, 2024
Link: Lantbrukets djur i juni 2023 Slutlig statistik
Use of agricultural land 2023, final results (JO0104), Ylva Olsson, 2024
Link: Jordbruksmarkens användning 2023. Slutlig statistik
Type of farming 2023. Swedish typology (JO0105), Anders Grönvall, 2024
Link: Jordbruksföretagens driftsinriktning 2023. Svensk typologi
Holdings and holders 2023 (JO0106), Elin Lund, 2024
Link: Jordbruksföretag och företagare 2023
Other gainful activities on agricultural holdings 2023 (JO0108), Johan Holmer, 2024
Link: Jordbruksföretagens kombinationsverksamheter 2023
Farm labour force 2023 (JO0401), Jesper Fransson, Elin Lund, 2024
Link: Sysselsättning i jordbruket 2023
Full-time farming in Sweden 2023 (JO0109), Ylva Olsson, 2024
Link: Heltidsjordbruket i Sverige 2023
Horticultural fruit trees 2023 (JO0119), Jörgen Persson, 2024
Link: Trädgårdsodlingens fruktträd 2023
Irrigation and drainage of agricultural land 2023 (JO0112), Anders Grönvall, 2024
Link: Bevattning och dränering av jordbruksmark 2023
There will be a publication on machinery and equipment during 2025. Date is not set at this moment.
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
During 2023, we had the following number of consultations in each area:
- Livestock: 7 104
- Agricultural holdings and holders: 3 961
- Use of agricultural land: 9 998
- Labour force: 692
During the period January to October 2024, we had the following number of consultations in each area:
- Livestock: 7 255
- Agricultural holdings and holders: 4 338
- Use of agricultural land: 8 212
- Labour force: 820
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
Results from the Farm Structural Survey/Integrated Farm Statistics can be found under the fields:
- Arealer (information on areas of arable land, agricultural land, irrigation and drainage);
- Företag och företagare (information on holdings and holders, other gainful activities and typology);
- Lantbrukets djur (information on animals);
- Sysselsättning (information on labour force and education on holder);
- Trädgårdsodling (information on horticulture).
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
Yes10.5. Dissemination format - other
The results from farm statistics are also published together with other agricultural statistics in the Agricultural Statistics compilation (previously Agricultural Statistics Yearbook).
Agricultural Statistics compilation 2024: Jordbruksstatistisk sammanställning 2024.
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
Yes10.6.5. Title, publisher, year and link to handbook
The quality policy handbook is based on the principles for European statistics and can be found at this website.
We also have a production process handbook based on the principles laid down on the Code of Practice, which can be found at this website.
10.6.6. Availability of national methodological papers
Yes10.6.7. Title, publisher, year and link to methodological papers
All published statistical reports have a methodological paper called "Statistical production" and a "Quality Declaration" attached.
Livestock in June 2023, preliminary results (JO0103), Anders Grönvall, 2023
Link to the methodological paper
Link to the quality declaration
Livestock in June 2023, final results (JO0103), Anders Grönvall, 2024
Link to the methodological paper
Link to the quality declaration
Use of agricultural land 2023. Final results (JO0104), Ylva Olsson, 2024
Link to the methodological paper
Link to the quality declaration
Type of farming 2023. Swedish typology (JO0105), Anders Grönvall, 2024
Link to the methodological paper
Link to the quality declaration
Holdings and holders 2023 (JO0106), Elin Lund, 2024
Link to the methodological paper
Link to the quality declaration
Other gainful activities on agricultural holdings 2023 (JO0108), Johan Holmer, 2024
Link to the methodological paper
Link to the quality declaration
Farm labour force 2023 (JO0401), Jesper Fransson, Elin Lund, 2024
Link to the methodological paper
Link to the quality declaration
Full-time farming in Sweden 2023 (JO0109), Ylva Olsson, 2024
Link to the methodological paper
Link to the quality declaration
Irrigation and drainage of agricultural land 2023 (JO0112), Anders Grönvall, 2024
Link to the methodological paper
Link to the quality declaration
Horticultural fruit trees 2023 (JO0119), Jörgen Persson, 2024
Link to the methodological paper
Link to the quality declaration
10.7. Quality management - documentation
We work in accordance with the principles laid down on the Code of Practice.
For each publication made, we have an advanced documentation, describing in-depth all the steps required from initiating a survey until the final publication of data.
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
11.1.3. Description of the quality management system and procedures
We follow the Generic Statistical Business Process Model (GSBPM) for the statistical production. Our quality management group consists of professionals within different statistical areas (statistical methods, statistical production and data dissemination). During the stage of statistical production, we also use checklists derived from the principles laid down on the Code Of Practice (COP).
11.1.4. Improvements in quality procedures
The GSBPM production process requires analysis and evaluation of the statistics after each delivery.
For example, there is a constant ongoing work in farm structural statistics in using and linking administrative data in order to ensure good quality of data, to lower response burden and to make better use of existing administrative sources.
There has also been work (on variable levels) on differences in data quality depending on ways of collecting data. Differences between data collected from paper questionnaire and from web-questionnaire. This to ensure that both the paper and the web questionnaire are developed in the best possible way.
11.2. Quality management - assessment
We produce our statistics in accordance with the Quality Declaration of the European Statistical System (QDESS).
Our principles of quality are based on: relevance, accuracy, timeliness and punctuality, accessibility and clarity, as well as comparability and coherence. In accordance with the QDESS, our statistics are developed, produced and disseminated based on sound methodologies, the best international standards and appropriate procedures that are transparent and well documented.
In our work we strive to minimise the burden on our respondents and establish a good cooperation with data providers and data users.
We work systematically with identifying our strengths and weaknesses but also with modernising and innovating the statistical production in order to improve our statistics and the statistical quality framework.
12.1. Relevance - User Needs
Internationally, the biggest users are the European Union, FAO and the OECD.
Nationally, the biggest users are state institutions/policy makers, county administrative boards, the Federation of Swedish farmers, municipalities, media and the Swedish University of Agricultural Sciences.
In 2012, the Swedish Board of Agriculture (SBA) conducted a user survey. According to the survey, the county administrative boards were great users of the agricultural statistics produced by the SBA. They used our statistics on agricultural land, livestock and statistics on holding and holders. According to the survey, 18 county administrative boards needed statistics in municipality level. The Federation of Swedish Farmers also needed more statistics in municipality levels, mainly statistics on livestock and statistics on agricultural holdings.
The Ministry of Trade and Industry and other departments at the Swedish Board of Agriculture are also big users of our statistics. These users require data on regional level.
The user survey can be found at this website.
The request on more regional statistics was met by keeping FSS/IFS as a census even in years when only a sample survey normally have been conducted.
User councils for agricultural statistics are also held regularly, where the largest users are represented and have the opportunity to provide feedback.
12.1.1. Main groups of variables collected only for national purposes
The IFS 2023 was carried out as a combination of variables collected for national purposes. The agricultural census 2023 included the following variables for national purpose:
a) Information about the holding: holder’s name, address, personal or organisational number, telephone number, e-mail address, client number in the administrative register for single farm payment, client number in the register of organic farming (at the control body), and production location number for bovine animals. The purpose of this collection is to receive updated information on holdings to be able to link data from different registers and to make a better version of Farm Register.
b) More detailed information about areas and different types of crops.
c) Number of livestock of different kinds, was collected in accordance with the requirements laid down on the Regulation (EC) No 1166/2008. For horses, the number was reported.
d) In the farm labour force module, the gender was applied even for non family labour employed.
e) In the soil management practices module, a few more questions on drainage were included to be able to have comparable figures with previous national surveys on drainage.
f) In the irrigation practices module, the sources of irrigation were reported as a percentage of volume used.
g) In the orchard module, all variables on apples were divided into different varieties.
The statistical characteristics b)-g) were collected in order to produce the customary annual national statistics of farm structure as well as to fulfil the EU requirements on agricultural statistics.
12.1.2. Unmet user needs
User needs are met by conducting IFS as a census every time.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
We do not measure user satisfaction. However, we have annual user meetings with the aim of highlighting the needs for statistics within the agricultural sector.
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 website: Circabc.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
For the module on machinery and equipment, the precision requirements for some of the variables on pigs and poultry on NUTS 1 and NUTS 2 levels were not met. The reason was that there were a little bit higher non-responses on this part of the survey than anticipated. In combination with a small population of holdings with pigs (especially breeding pigs) this increased the relative standard error.
For future surveys, we must be more consistent in minimising non-response, but in cases where specific average error targets exist, we can also estimate at an early stage whether they will not be met based on a given response rate.
13.2.3. Reference on method of estimation
The extrapolation factor was calculated using Horvitz-Thompson estimation in each stratum. The extrapolation factor was N/n in each stratum, where N is the total number of observations and n is the number of observations in the sample.
The RSE is calculated using formula (∑Nh(Nh-nh)sh2/nh )/x, where s is the standard deviation, x is the observed variable and h is the strata. The variance estimation is based on the final weights adjusted for non-response.
13.2.4. Impact of sampling error on data quality
None13.3. 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 website: 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)
Below thresholds during the reference periodCeased activities
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
Over-coverage - holdings which are not part of the 2023 target population (mainly holdings which have recently closed down) have been identified and removed from the register and have not been included in the processing. The over-coverage in the survey is therefore negligible. These are not included in the calculation of weights.
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
Core, labour force, rural development, and soil management practices
Newly created holdings, belonging to the 2023 target population, and, which did not apply for subsidies in 2023 (and thus were not included in IACS), or were not found in the poultry-, sheep- or pig registers, but were above the threshold values for inclusion in the target population, were not included in the survey. The number of such holdings is estimated to be very small. It is considered to be rare in Sweden to have newly established holdings that do not appear in any of the mentioned registers.
The farm register was updated when respondents reported changes on holdings according to the instructions in the questionnaires. When the reported data were inadequate, further investigations were necessary. In general, the remaining degree of under-coverage was considered to be so small that no correction for this was needed.
Irrigation, machinery and equipment
The modules on irrigation and machinery and equipment were conducted in the end of the collection face for the core census and the samples were based on those who at that point had answered the survey on core variables. At this point there were holdings that did not respond to the core survey and some cases where the information was not consistent. Those cases were not included in the sample frame. However, they were handled by adjusting the weighting factors.
Orchard
In the orchard module, there was no known under-coverage.
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 units derived from split13.3.1.3.3. Actions to minimise the under-coverage error
See the information under 13.3.1.3.1
13.3.1.3.4. Additional information under-coverage error
Not available.
13.3.1.4. Misclassification error
Yes13.3.1.4.1. Actions to minimise the misclassification error
Sweden uses extractions from constantly updated registers (IACS and different animal administrative registers). If a holding is misclassified in the frame it will be reclassified with the new data. The holding will not change its stratum though. We also have low standard errors.
13.3.1.5. Contact error
Yes13.3.1.5.1. Actions to minimise the contact error
In very few cases we identified that some of the addresses to the holders were incorrect. The correct addresses were found manually in most of these cases. In few cases, addresses were not found, so these holdings were treated as non-response and imputed.
13.3.1.6. Impact of coverage error on data quality
Low13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
The 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
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
None13.3.2.5. 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
Other
13.3.3.1.2. Actions to minimise or address unit non-response
Follow-up interviewsReminders
Imputation
Weighting
13.3.3.1.3. Unit non-response analysis
Some of non-responding holdings have probably been closed down, while others have been impossible to reach despite efforts with reminders by post and telephone calls. Only a few, 91 respondents, refused to fill in the questionnaire or give information when contacted. For part of these non-respondents, information about crops and bovines was found in IACS or the Bovine register, which confirmed that these holdings still existed. The holdings where no information was found in administrative registers were treated as over-coverage due to the risk of double counting, e.g. of crop areas.
Due to the low non-response we did not do any further analysis in the bias from the non-respondents.
The weights were recalculated for the unit non-response on the sample characteristics.
13.3.3.2. Item non-response - rate
In the farm labour force section, about 40% of the respondents had values that were imputed. However, only about 13% had missing values for all characteristics in the labour force section.
In the section other gainful activities, there was a non-response on 17% of the respondents.
In the machinery and equipment module, there was a non-response rate between 2% and 28%.
In the module on irrigation practices, there was a non-response rate between 5% and 24%.
In the orchard module, there was a very high unit non-response rate on approximately 65%.
13.3.3.2.1. Variables with the highest item non-response rate
Item non-response was most frequent in the farm labour force and other gainful activity sections. Then, variables with most non-response were:
- MOGA_FAM_RH - Family members working on the holding and having other gainful activities (related to the agricultural holding) as their main activity,
- SOGA_FAM_RH - Family members working on the holding and having other gainful activities (related to the agricultural holding) as their secondary activity,
- MOGA_NFAM_RH - Non-family labour force regularly working on the holding and having other gainful activities (related to the agricultural holding) as their main activity,
- SOGA_NFAM_RH - Non-family labour force regularly working on the holding and having other gainful activities (related to the agricultural holding) as their secondary activity,
- MOGA_FAM_NRH - Family members of holder-manager of the sole holder holding, who are working on the agricultural holding and have other gainful activities (not related to the agricultural holding) as their main activity, and
- SOGA_FAM_NRH - Family members of holder-manager of the sole holder holding, who are working on the agricultural holding and have other gainful activities (not related to the agricultural holding) as their secondary activity.
13.3.3.2.2. Reasons for item non-response
Skip of due questionFarmers do not know the answer
13.3.3.2.3. Actions to minimise or address item non-response
Follow-up interviewsImputation
13.3.3.3. Impact of non-response error on data quality
Low13.3.3.4. Additional information non-response error
The item non-response has been considered to be the most serious type of non-sampling errors.
To avoid bias from partial non-response, much work has been done to create new imputation methods minimising the risk for bias from imputation.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
Data entryImputation methods
13.3.4.2. Imputation methods
Deductive imputationRatio imputation
Cold-deck imputation
Random hot deck imputation
Previous data for the same unit
13.3.4.3. Actions to correct or minimise processing errors
In order to minimise processing errors, much work has been done to create new imputation methods, thus minimising the risk for bias from imputation.
In addition, we regularly do different checks to detect processing errors from the scanning procedure.
13.3.4.4. Tools and staff authorised to make corrections
The corrections were primarily made using SAS, by the staff of the Statistics division at the Swedish Board of Agriculture.
In some cases, Statistics division staff made corrections directly in the data collection system. The system allows these corrections to be traced.
13.3.4.5. Impact of processing error on data quality
Low13.3.4.6. Additional information processing error
Overall, the errors from data processing are estimated of non-significant magnitude, even though some errors can still exist on individual holdings.
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
The first results were released before 31 December 2023.
14.1.2. Time lag - final result
Time lag, final results: 16 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
One publication was delayed.
- Farm labour force 2023 (JO0401) was published with a delay of 9 days.
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
In Sweden, energy forest is considered as an agricultural activity.
15.1.2.2. Reasons for deviations
In Sweden, it is permitted to grow short-rotation Scots forest (energy forest) on arable land while maintaining farm support if it is poplar, hybrid aspen or willow. There are crop codes for this and the cultivation is thus equated with other agricultural crops even if it does not involve food production.
15.1.3. Thresholds of agricultural holdings
See sub-categories below.
15.1.3.1. Proofs that the EU coverage requirements are met
Please see the attached file.
Annexes:
15.1.3.1 Proofs that the EU coverage requirements are met
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
Sweden has higher national thresholds when compared to the Regulation (EU) 2018/1091. However, the same thresholds are used both for the data collected and published at national level and the data sent to Eurostat. Thus, there is a small difference between the interpretation of the national thresholds and the thresholds used for Eurostat. This due to that UAAT in Swedish national thresholds include the energy forest and the areas with nursery plants which make some differences in the number of holdings included. There is a small number of holdings that is included nationally but not in the EU definition, however data for all holdings are sent to Eurostat.
Sweden applies higher national thresholds when compared to those set in Annex II of Regulation (EU) 2018/1091. These national thresholds are used both for the data collected and published at national level and for the data sent to Eurostat. Therefore, the same number of holdings are included nationally and in the data sent to Eurostat. There is a small difference between the interpretation of the national thresholds and those set in Annex II of Regulation (EU) 2018/1091. In the Swedish national thresholds, UAAT (utilised agricultural area-outdoor) includes energy forest and areas with nursery plants. Thus, energy forest and nursery plants are included in the thresholds for data sent to Eurostat. Another difference is that for a few holdings (6 for 2023) they used to have a pig population but at the reference day there are no pigs on the holding. In the national thresholds these holdings are included.
15.1.3.3. Reasons for differences
In the national statistics in Sweden we include the areas with energy forest and nursery plants in the utilised agricultural area (UAAT). As UAAT is a factor in the threshold this makes the population a little bit higher in Sweden.
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 differences.
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 website: 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
We used the same livestock coefficients as the ones set in the Regulation (EU) 2018/1091.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
Equidae are included in "Other livestock n.e.c."
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
There are no deviations. Data is collected, published and sent to Eurostat in compliance with the reference periods/days set in 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 from Council Regulation (EC) No 834/2007.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
There are no differences.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
The length of comparable time series is between 2010 and 2023, which means 14 years for some variables collected annually, such as areas and animals. For FSS/IFS-variables, in general, there are comparable time series for the years 2010, 2013, 2016, 2020 and 2023 on those variables included in the surveys.
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 some changes but not enough to warrant the designation of a break in series15.2.6.2. Description of changes
The reference date for livestock is the first Thursday in June every year. While this means the relative date (the first Thursday) remains consistent, the actual calendar date can vary. For example, the reference date was 4 June in 2020 and 1 June in 2023.
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 we assist to a further concentration in agriculture, which can be seen by the holdings breakdown by SO euro and UAA, where, an increase of average of SO_EURO (and UAA), it corresponds a decrease of the median.
Evolution over time (2023 vs 2020) of Crops
C1400T – The area with oats varies between different years and decreased over time.
I1110T – Winter rape is the largest crop that are included in this variable and it has been increasing over time.
I1120T – This is small areas that has been increasing over time.
I1140T – The areas of linseed vary between years and has increased.
I1190T – This is small areas and it has decreased.
I2200T – This is small areas and it has been increasing the last year.
I6000T + I9000T – There have been some changes in where lawn is included. This includes lawn (in I9000T) from 2023. In 2020 lawn was included in ARA99T.
V0000_S0000TO and V0000_S0000TK – There have been some changes in how the country defines the different crops included. They are adjusted which crop that should be included in each variable. Changes were made to make it comparable to the variables in the irrigation module.
G3000T – Green maize areas are increasing.
ARA99T – It does not include lawn anymore (see I6000T+I9000T).
Q0000T – It was smaller areas in 2023.
L0000T –SE adjusts which crop that are included in each variable and crops that was included in L0000T year 2020 are now included in N0000T instead. N0000T was in 2020 included in the NSNE-file.
SRCAA – The area is decreasing.
FA9 – These data is not comparable. SE has changed the way they handle these data. By the new “definition” the FA9 should be much higher in 2020.
I6000T – This is small areas and it has decreased.
Evolution over time of Animals
A5000X5100 – 2023 data are correct, figures for 2020 may be reassessed.
Evolution over time of other gainful activities
SOGA_FAM_NRH – 2023 data are correct, figures for 2020 may be reassessed as they seem overestimated.
15.2.9. Maintain of statistical identifiers over time
Yes15.3. 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
We use administrative registers for data on agricultural area and cattle. For these variables, there is no difference between our national and the IFS results.
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
ARA99T – the sharp difference between the 2 datasets (on a relatively low absolute figure) seems due to the result that there is a number of small crops included in the crop production data that is not included in the IFS data.
C0000T in SE21 – In 2023, the weather was hot and dry at the beginning of the summer and then it rained a lot. In total it was almost 10 % of cereals area that was harvested as green fodder or not harvested at all. Usually it is about 5 %. In SE21 there was about 25 % harvested as green fodder (”normal year” it is about 15 %).
Coherence cross-domain: IFS vs ANIMAL PRODUCTION (1000 heads) in relative terms
The difference between IFS and Animal production statistics for cattle is due to the different reference date (June vs December).
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
We do coordinate the Integrated Farm Statistics with the survey on livestock.
16.2. Efficiency gains since the last data transmission to Eurostat
Further automationIncreased use of administrative data
Other
16.2.1. Additional information efficiency gains
The questionnaires include only variables that cannot be obtained from administrative registers. Further, Sweden has adjusted the questionnaires to the different types of the holdings surveyed. We have three different questionnaires. The small questionnaire (L) is sent to 41 000 agricultural holdings. It includes pre-printed general information on the holding, and questions on agricultural area and livestock that cannot be obtained from registers. The bigger questionnaires (SJ) and (SF) are sent to the rest of the population and include questions on labour force and other gainful activities. The SJ questionnaire is sent to 3 400 legal agricultural holdings and SF to 19 600 private agricultural holdings.
Further, Sweden has developed a statistical model for calculating most of the variables within the module 'Soil management practices'. It was made for three detailed topics: tillage methods, soil cover on arable land and crop rotation on arable land. No questions for these three parts were sent to agricultural holdings during the IFS 2023. The statistical model was developed based on register data from different organisations in Sweden, where most information is from Swedish Board of Agriculture and IACS. For crop rotation, the modelling was made in a similar way as in 2016.
Sweden has further developed the IT-system used for statistical surveys making it easier for holdings to answer the questionnaires electronically on the website of the Swedish Board of Agriculture.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
We estimate it takes about 7 minutes for the farmers to fill in the questionnaire with all the core variables, including the time for them to send the questionnaire to the Swedish Board of Agriculture.
16.3.2. Module ‘Labour force and other gainful activities‘
We estimate it takes about 9 minutes for the farmers to answer all the questions in the questionnaire on the module 'Labour force and other gainful activities'.
16.3.3. Module ‘Rural development’
This information is obtained from a register at the Swedish Board of Agriculture. The farmers do not answer this module on their questionnaire. Thus, answering time is 0.
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
We estimate it takes about 5 minutes for the farmers to fill in the questionnaire with all the irrigation variables, including the time for them to send the questionnaire to the Swedish Board of Agriculture.
16.3.6. Module ‘Soil management practices’
The only question that was put to the farm was about drainage where it takes in general less than 1 minute for the farmer to answer. The rest of the variables in this module was created by a model approach where information from different registers was used.
16.3.7. Module ‘Machinery and equipment’
We estimate it takes about 7 minutes for the farmers to fill in the questionnaire with all the variables on machinery and equipment, including the time for them to send the questionnaire to the Swedish Board of Agriculture.
16.3.8. Module ‘Orchard’
We estimate it takes about 25 minutes for the farmers to fill in the questionnaire with all the orchard variables, including the time for them to send the questionnaire to the Swedish Board of Agriculture. In the questionnaire there was division of variables for national purposes and most of time spent with questionnaire was due to those variables. For the variables sent to Eurostat we estimate the time spent to 15 minutes.
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
We have a work program that is updated every year, where major revisions are reflected. There are routines for how preliminary and final statistics are published and comparisons are made to monitor quality.
If there are errors in data already published, then the errors have to be documented and the data has to be updated. Updated data together with a comment will be published.
17.2. Data revision - practice
Some data concerning 2023 are published as “preliminary results” clearly informing that these can deviate from the final statistics to be published later in accordance with the publication schedule set for national official statistics.
For the publications on "Farm labour force 2023", "Full-time farming in Sweden 2023" and "Irrigation and drainage of agricultural land 2023", there have been minor revisions.
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
The statistical farm register, which has been in use since 1968 as a frame for different agricultural surveys, was the frame for the IFS 2023.
The IFS 2023 frame population consisted of holdings from the IFS 2020 updated with information from holdings in the livestock survey for the years 2021 and 2022, and holdings applying for subsidies in 2021, 2022 and 2023 (IACS). The frame was also updated with information from the poultry-, sheep- and pig registers. The last update of the frame was conducted in April 2023.
We combine IACS with the cattle register, and the last known value for other animal and horticulture production.
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
Census18.1.2.2. Sampling design
Not applicable.
18.1.2.2.1. Name of sampling design
Not applicable18.1.2.2.2. Stratification criteria
Not applicable18.1.2.2.3. Use of systematic sampling
Not applicable18.1.2.2.4. Full coverage strata
Not applicable.
18.1.2.2.5. Method of determination of the overall sample size
Not applicable.
18.1.2.2.6. Method of allocation of the overall sample size
Not applicable18.1.3. 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
Stratified random sampling is used. One of the stratification variables was the location at NUTS 3 level.
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
Unit legal status
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
There was a number of full coverage strata, mostly based on hectares and on the number of different types of animals. These criteria were met for full coverage strata:
- More than 100 hectares of cereals; or
- more than 100 sheep; or
- more than 200 cattle; or
- more than 800 pigs; or
- more than 10 AWU in last survey; or
- more than 100 hectares of irrigation area in 2020; or
- more than 5 hectares of fruits; or
- more than 1000 poultry; or
- more than 100 turkeys; or
- more than 100 sows; or
- more than 10 boars; or
- new holdings with more than 10 hectares of pasture and no animals in register; or
- included in 2022 survey on manure; or
- high number of slaughtering according to slaughtering register; or
- more than 2 production places for pigs and poultry; or
- more than 20 hectares of sugar beets or oilseeds; or
- high number of animals according to production place register but low number according to last known information.
18.1.4.2.5. Method of determination of the overall sample size
The sample size for the labour force module was determined by doing 11 different Neymann allocations based on 11 different variables (cereals, oilseeds, forage plants, pasture, dairy cows, non-dairy cows, other cattle, sows, piglets, sheep and poultry). In each stratum the highest sample size based on the 11 allocations was chosen. The total number (n) was iterated to a level where all RSEs according to Annex V of Regulation (EU) 2018/1091 were met and also so that we nationally could produce figures on NUTS 3 level.
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
Census18.1.5.2. Sampling design
Not applicable.
18.1.5.2.1. Name of sampling design
Not applicable18.1.5.2.2. Stratification criteria
Not applicable18.1.5.2.3. Use of systematic sampling
Not applicable18.1.5.2.4. Full coverage strata
Not applicable.
18.1.5.2.5. Method of determination of the overall sample size
Not applicable.
18.1.5.2.6. Method of allocation of the overall sample size
Not applicable18.1.5.2.7. 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 design is a stratified random sample based on the population that in October hade answered the core data collection and that had irrigable agricultural land.
18.1.7.2.1. Name of sampling design
Stratified one-stage random sampling18.1.7.2.2. Stratification criteria
Unit size18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
There was a full coverage strata for those holdings that according to the core part did have at least 5 hectares of irrigable area and were not included in the sample for the module on "Machinery and equipment".
However, there was an under-coverage in the frame due to non-response on the core census in June. See also in section 13.3.1.3.1.
18.1.7.2.5. Method of determination of the overall sample size
The sample size was determined by the possibilities to have good national quality data on NUTS 2 level.
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 for the module on soil management practices was the same as for the module on labour force and other gainful activities. See 18.1.4 and its sub-items.
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
Unit legal status
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
See 18.1.4.2.4
18.1.8.2.5. Method of determination of the overall sample size
See 18.1.4.2.5
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 design is a stratified random sample based on the population that in October had answered the core data collection.
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit specialization
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
Holdings with at least one of following characteristics are in full coverage strata:
- more than 200 hectares of pasture
- more than 3 hectares of fruits and berries
- more than 10 hectares of vegetables on open field
- more than 5 000 m2 of greenhouse area
- more than 150 dairy cows
- more than 100 non dairy cows
- more than 300 other cattle (except cows)
- more than 100 sows
- more than 1 000 piglets
- more than 300 sheep
- more than 25 000 poultry
- more than 750 hectares of cereals and green fodder
However, there was an under-coverage in the frame due to non-response on the core census in June. See also in section 13.3.1.3.1.
18.1.9.2.5. Method of determination of the overall sample size
The sample size was determined by doing 11 different Neymann allocations based on 11 different variables (cereals, oilseeds, forage plants, pasture, dairy cows, non-dairy cows, other cattle, sows, piglets, sheep and poultry). In each stratum the highest sample size based on the 11 allocations was chosen. The total number (n) was iterated to a level where all RSEs according to Annex V of Regulation (EU) 2018/1091 were met.
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
Census18.1.10.2. 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
Problems related to data quality of the source18.1.14. 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
Paper auto-questionnairePostal, electronic version (email)
Telephone, electronic version
Use of Internet
18.3.2. Data entry method, if paper questionnaires
Optic18.3.3. Questionnaire
Please find the questionnaire in annex in Swedish and English.
Annexes:
18.3.3 Questionnaire on core variables in Swedish
18.3.3 Questionnaire on core variables and labour force module (private holdings) in Swedish
18.3.3 Questionnaire on core variables and labour force module (legal holdings) in Swedish
18.3.3 Questionnaire on irrigation module in Swedish
18.3.3 Questionnaire on machinery and equipment module in Swedish
18.3.3 Questionnaire on orchard module in Swedish
18.3.3 Questionnaire on core variables in English
18.3.3 Questionnaire on core variables and labour force module (private holdings) in English
18.3.3 Questionnaire on core variables and labour force module (legal holdings) in English
18.3.3 Questionnaire on irrigation module in English
18.3.3 Questionnaire on machinery and equipment module in English
18.3.3 Questionnaire on orchard module in English
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
Other
18.4.2. Staff involved in data validation
InterviewersStaff from central department
18.4.3. Tools used for data validation
The software used for data validation were SAS and Excel.
18.5. Data compilation
Methodology for determination of weights (extrapolation factors)
1. Design weights
The extrapolation factor was calculated using Horvitz-Thompson estimation in each stratum. The extrapolation factor was N/n in each stratum, where N is the total number of observations and n is the number of observations in the sample.
2. Adjustment of weights for non-response
The weighing scheme was produced on the units that responded. Weights are only used for those variables included in the sample survey.
3. Adjustment of weights to external data sources
No adjustments of weights to external data sources have been done.
4. Any other applied adjustment of weights
No other adjustments of weights.
18.5.1. Imputation - rate
In the land characteristics, the unweighted imputation rate was between 0% and 16% depending on the variables collected.
In the livestock characteristics, there was no imputation on cattle (A2010, A2020, A2120, A2220, A2130, A2230_2300, A2230, A2300, A2300F, A2300G) as this data was taken from the cattle register. For other animals (A4100, A4110K, A4120, A4200, A4210K, A4220, A3110, A3120, A3130, A5140, A5110O, A5000X5100), there was an unweighted imputation rate in general between 0% and 5%.
In the farm labour force section, about 40% of the respondents had at least one missing value. However, only about 6 % had missing values for all characteristics.
In the module on other gainful activities, there was an unweighted imputation rate of 17%.
In the module on support for rural development, all characteristics were collected from administrative data and therefore no data was imputed.
In the module of irrigation methods, there was an unweighted imputation rate between 1% and 12%.
In the module of machinery and equipment, there were 38% of the holdings that were imputed by some variables. The unweighted imputation rate on variables was between 2% and 28%.
In the module of orchard, there was an unweighted imputation rate of up to 85%.
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
COP – Code of Practice
EU – European Union
FAO – Food and Agriculture Organization of the United Nations
FSS – Farm Structure Survey
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
OECD – Organisation for Economic Co-operation and Development
QDESS – Quality Declaration of the European Statistical System
RSE – Relative standard error
SBA – Swedish Board of Agriculture
SFR – Statistical Farm Register
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 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
28 February 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, drainage on the agricultural holdings;
- 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 area 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, yes/no on the presence of machinery and equipment) and
- the number of agricultural holdings having these characteristics.
Methodology for determination of weights (extrapolation factors)
1. Design weights
The extrapolation factor was calculated using Horvitz-Thompson estimation in each stratum. The extrapolation factor was N/n in each stratum, where N is the total number of observations and n is the number of observations in the sample.
2. Adjustment of weights for non-response
The weighing scheme was produced on the units that responded. Weights are only used for those variables included in the sample survey.
3. Adjustment of weights to external data sources
No adjustments of weights to external data sources have been done.
4. Any other applied adjustment of weights
No other adjustments of weights.
See sub-categories below.
Some of the statistics are collected and disseminated on the years the farm structure surveys are conducted, while others are collected and disseminated on yearly bases.
Statistics disseminated every IFS-year:
- Type of farming. Swedish typology;
- Holdings and holders;
- Other gainful activities on agricultural holdings;
- Farm labour force;
- Full-time farming in Sweden.
Statistics disseminated on yearly bases:
- Livestock in June, preliminary results;
- Livestock in June, final results;
- Use of agricultural land, final results.
Regarding 2023, there will also be a publication on irrigation and drainage of agricultural land.
See sub-categories below.
See sub-categories below.
See sub-categories below.
