Farm structure (ef)

1.1. Contact organisation

Statistics Netherlands

1.2. Contact organisation unit

Environmental, energy and spatial statistics, team Agriculture and Nature

1.3. Contact name

Confidential because of GDPR

1.4. Contact person function

Confidential because of GDPR

1.5. Contact mail address

Postbus 24500
2490 HA Den Haag

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

16 May 2025

2.2. Metadata last posted

6 June 2025

2.3. Metadata last update

16 May 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;
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, pears area, 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

3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091

3.6.2. 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/or with some elements of ecological focus areas (terraces, field margins, agroforestry, etc.) and/or with UAA 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

The special territories Aruba, Curaçao, Sint Maarten, Bonaire, Sint Eustatius and Saba are excluded from the data collection.

3.7.3. Criteria used to establish the geographical location of the holding

Other

3.7.4. Additional information reference area

The geographical location of the holding corresponds to the headquarters of the holding in the business register (BR), which is usually located close to the agricultural activities.

The coordinates of the headquarters are used to determine the geographical location; in a few cases where coordinates are missing the postal code or the location of the largest parcel or stable is used.

3.8. Coverage - Time

Farm structure statistics in our country cover the period from 1980 onwards.

Note: this concerns the information published online; older farm structure information is available, partly as far back as 1851, but only in paper publications.

Time series related to EU regulations for Integrated Farm Statistics (IFS), previously Farm Structure Survey (FSS), are described in previous quality reports.

3.9. Base period

The 2023 data are processed (by Eurostat) with 2020 standard output coefficients (calculated as a 5-year average of the period 2018-2022). For more information, you can consult the definition of the standard output.

Two kinds of units are generally used:

the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
the number of agricultural holdings having these characteristics.

See sub-categories below.

5.1. Reference period for land variables

The use of land refers to the reference year 2023. 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.

The 12-month period ending on 15 May within the reference year 2023.

5.2. Reference period for variables on irrigation and soil management practices

The 12-month period for variables on irrigation and soil management practices is ending on 31 December 2022.

5.3. Reference day for variables on livestock and animal housing

The reference day 1 April 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 ending on 1 April within the reference year 2023.

5.6. Reference period for variables on rural development measures

The three-year period ending on 31 December 2023.

5.7. Reference day for all other variables

The reference day 1 April 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 act

6.1.2. Name of national legal acts and other agreements

Statistics Netherlands Act (Wet op het Centraal bureau voor de statistiek).

6.1.3. Link to national legal acts and other agreements

Wet op het Centraal bureau voor de statistiek.

6.1.4. Year of entry into force of national legal acts and other agreements

2003

6.1.5. Legal obligations for respondents

Yes

6.2. Institutional Mandate - data sharing

Statistics Netherlands Act gives Statistics Netherlands (CBS) rights to access data available in governmental registers and datasets. It also describes the conditions for data sharing. Furthermore, there are written agreements with data providing and receiving agencies.

7.1. Confidentiality - policy

The census data are protected by the Act on Registration of personal data and the Statistics Netherlands Act. These Acts protect data on individual private or legal persons against illegal use, such as being published, sold, used or exchanged without permission of the persons involved. All personnel with access to the data have to comply with these Acts. Furthermore, it is not allowed to use the data for any other purpose than for which the data was collected or for producing statistics and is not allowed to publish data in such a way that individuals or data on individuals may be traced.

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)
Other primary confidentiality rules
Secondary confidentiality rules

7.2.1.2. Methods to protect data in confidential cells

Table redesign (Collapsing rows and/or columns)
Cell suppression (Completely suppress the value of some cells)
Rounding: controlled, deterministic or random (Round each cell value to a pre-specified rounding base)

7.2.1.3. Description of rules and methods

A solution to ensure statistical confidentiality and prevent unauthorised disclosure could be to apply the rule of dominance, that is to hide the contents of table cells where the data are from few holdings. This is a very complicated operation. Very often a hidden cell value can be recalculated by difference from data in other tables. However, once you start to adapt tables by making changes in some cells, you have to continue this in other tables and the hiding operation spreads throughout the table set like an oil spill.
Therefore, we have chosen an easier and pragmatic approach by redesigning the tables and collapsing rows and/or columns: tables with a danger of disclosing individual data are published only at country or province level, or the level of detail is lowered at regional level. Usually tables with sensitive characteristics, e.g. economic size, sometimes in combination with a second dimension e.g. farm type, are not published at lower regional levels. Sensitive characteristics for which there are only very few holdings will not be published.

Primary and secondary confidentiality are addressed by cell suppression and rounding. Small count cells are suppressed from the publication, e.g. the cell value is replaced by some special characters like ‘/’. Protecting the unsafe cells this way is called primary suppression, and to ensure these cannot be derived by subtractions from published marginal totals, additional cells are selected for secondary suppression. The threshold for small count cells is 5 contributors. For some tables we use the method of conventional rounding (each cell is rounded to the nearest multiple of the base. The marginal totals and table totals are rounded independently from the internal cells).

Besides regular publications via the Statline database, the website or press releases, requests for information can be addressed at our Infoservice. In the case custom-made tables are prepared confidentiality rules are applied whenever needed.
For custom-made tables a distinction is made in information on 'sensitive' and 'non-sensitive' characteristics. Sensitive characteristics are characteristics that could lead to disclosure of individual personal data (age of the farmer, education level, etc.) or of economic data on the individual farm (SO). For this type of tables, the confidentiality regime is very strict and provisions are made that each cell contains enough cases so that no individual farms or farmers can be identified, otherwise the cell will be kept confidential (and special attention is given to secondary disclosure).

In all cases privacy protection has the highest priority, therefore all requests for custom-tables are scrutinised.

7.2.2. Microdata

See sub-categories below.

7.2.2.1. Use of EU methodology for microdata dissemination

7.2.2.2. Methods of perturbation

Recoding of variables
Reduction of information

7.2.2.3. Description of methodology

All micro-datasets remain on the dedicated server at Statistics Netherlands. Before statistical results are released, all data is checked for the risk of disclosure.

Statistics Netherlands has several micro-data services for research.

Services are:

Additional statistical research, conducted by Statistics Netherlands.

Statistics Netherlands can carry out research based on the research questions of the applicant. If necessary they can add and link researchers own datasets to statistical data sources available at Statistics Netherlands (including the agricultural census). The results of the study are published on the website of Statistics Netherlands and are thus accessible to everyone. Moreover, most publications appear in print as a research report. This work is carried out for a fixed rate per hour.

Own research using data from Statistics Netherlands.

Under certain conditions, Statistics Netherlands makes available micro-data for statistical research. To be authorised to use this data the researcher must work at an organisation authorised by the Central Commission for Statistics (CCS). Research can be conducted on site at our offices in The Hague and Heerlen, or from the researchers' own workplace using a secure internet connection (remote access).

Statistics Netherlands requires that all statistical results be published and made available to other interested persons and organisations. Statistics Netherlands publishes an overview of publications based on research based on micro-data from Statistics Netherlands.

For the methods of perturbation, we use recoding of variables and reduction of information. For recoding of variables, this concerns variables that are directly traceable to individual holdings (e.g. farm identification number, business register number, unique identification number for livestock farming). For reduction of information, this concerns variables that can be aggregated to a less detailed level (e.g. crops, animals).

8.1. Release calendar

There is no release calendar specifically for IFS. All regular information concerning statistical release dates from the annual agricultural census (including crops, livestock and labour force) is published online on the Statline database. Statistics Netherlands is in the process of creating new dissemination products, with increased integration of IFS data in the future. Statistics Netherlands will examine the possibilities within the organisation to make a release calendar for IFS available in the future.

8.2. Release calendar access

Not applicable.

8.3. Release policy - user access

In general, information is released through tables on the Statline database, and articles on Statistics Netherlands website. Each Friday, CBS publishes the publication planning for its upcoming news releases. All information is made available to all users at the same time. Prior to publication of a news release, CBS reserves the right to grant pre-release access under embargo to relevant government departments, institutions and news organisations. Information on the release policy and the pre-release access policy can be found here: Publication policy.

8.3.1. Use of quality rating system

8.3.1.1. Description of the quality rating system

Not applicable.

The data for the annual agricultural census are disseminated according to a pre-determined release policy, with regular updates within the year.

10.1. Dissemination format - News release

See sub-categories below.

10.1.1. Publication of news releases

Yes

10.1.2. Link to news releases

Besides tables on the CBS Statline database, there have (so far) been several news releases on subjects in the agricultural census.

Publications in English include:

An overview of all publications in English on agriculture can be found here: Agriculture.

Beside these, there have been several publications that are only available in Dutch, an overview can be found here: Landbouw.

10.2. Dissemination format - Publications

See sub-categories below.

10.2.1. Production of paper publications

10.2.2. Production of on-line publications

Yes, in English also

10.2.3. Title, publisher, year and link

The Netherlands in numbers, 2023 edition (published by Statistics Netherlands)
Nederland in cijfers, editie 2023 (The Netherlands in numbers, 2023 edition) (published by Statistics Netherlands)
Staat van Landbouw, Natuur en Voedsel - editie 2023 (State of Agriculture, Nature and Food - 2023 edition) (published by Berkhout, P., H. van der Meulen, P. Ramaekers)
Staat van Landbouw, Visserij, Voedsel en Natuur 2024 (State of Agriculture, Fisheries, Food and Nature 2024) (published by Berkhout, P., H. van der Meulen, P. Ramaekers)

10.3. Dissemination format - online database

See sub-categories below.

10.3.1. Data tables - consultations

See Statline - Datasets via thema (Dutch) and Statline - Datasets by themes (English)

Note: the indicative number of hits is based on the year 2023 (total).

Dutch tables (under 'Landbouwtelling' and 'Biologische landbouw'):

Landbouw; gewassen, dieren, grondgebruik en arbeid op nationaal niveau (crops, livestock and land use at national level): approx. 30 000 hits;
Landbouw; gewassen, dieren en grondgebruik naar regio (crops, livestock and land use by region): approx. 47 000 hits;
Landbouw; gewassen, dieren en grondgebruik naar gemeente (crops, livestock and land use, by municipality): approx. 58 000 hits;
Landbouw; gewassen, dieren en grondgebruik naar bedrijfstype, nationaal (crops, livestock and land use by farm type at national level): approx. 14 500 hits;
Landbouw; gewassen, dieren en grondgebruik naar hoofdbedrijfstype, regio (crops, livestock and land use, by general farm type and region): approx. 21 500 hits;
Landbouw; arbeidskrachten naar regio (labour force by region): approx. 11,000 hits;
Landbouw; gewassen, dieren en grondgebruik naar omvangsklasse en regio (crops, livestock and land use, by size classes and region): approx. 10 000 hits;
Landbouw; economische omvang naar omvangsklasse, bedrijfstype (information by economic size classes and farm type): approx. 12 000 hits;
Landbouw; economische omvang naar omvangsklasse, hoofdbedrijfstype, regio (information by economic size classes, general farm type and region): approx. 6 500 hits;
Landbouw; bedrijven met verbredingsactiviteiten, hoofdbedrijfstype, regio (other gainful activities by main farm type and region): approx. 11 000 hits;
Landbouw; gewassen, dieren en grondgebruik, bedrijfstak (SBI 2008) (crops, livestock and land use by NACE): approx. 9 800 hits;
Biologische landbouw; gewassen, dieren, grondgebruik en arbeid (organic farming; crops, livestock, land use and labour force): approx. 13 000 hits.

English tables (under 'Agricultural census'):

Agriculture; crops, livestock and land use by general farm type, region: approx. 24 000 hits;
Agriculture; labour force by region: approx. 8 500 hits.

10.3.2. Accessibility of online database

Yes

10.3.3. Link to online database

See CBS website (Dutch) and CBS website (English)

Notes:

tables in Dutch can be found under Thema's/Landbouw;
tables in English can be found under Themes/Agriculture/Agricultural census. These include information on crops, livestock and land use by general farm type and region, and on labour force. The Dutch site contains additional tables, with more detailed information such as on regional breakdown, size classes and other gainful activities.

10.4. Dissemination format - microdata access

See sub-category below.

10.4.1. Accessibility of microdata

Yes

10.5. 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

Yes

10.6.3. Title, publisher, year and link to national reference metadata

The table explanation page (attached to the online datasets mentioned in section 10.3.1) serves as national reference metadata, which includes methodological information (e.g. general information, definitions, sources and methods) and a link to the survey description.

Website to the survey description: CBS website - Agricultural census.

10.6.4. Availability of national handbook on methodology

10.6.5. Title, publisher, year and link to handbook

Not applicable.

10.6.6. Availability of national methodological papers

Yes

10.6.7. Title, publisher, year and link to methodological papers

Statistics Netherlands publishes an outline of statistical methods used by CBS on its website, see Statistical methods.

10.7. Quality management - documentation

The present methodological report for IFS.

11.1. Quality assurance

See sub-categories below.

11.1.1. Quality management system

Yes

11.1.2. Quality assurance and assessment procedures

Training courses
Use of best practices
Quality guidelines
Benchmarking
Compliance monitoring
Self-assessment
Peer review
External review or audit
Certification

11.1.3. Description of the quality management system and procedures

Statistics Netherlands is certified according to ISO 9001:2015 standard; a peer review was conducted in 2022.

There exists a quality management system to assure and assess quality through different procedures: training courses, use of best practices, quality guidelines, benchmarking, compliance monitoring, self-assessment, peer review, external review or audit, and certification. The quality management system is described in section 4.2. from the 'CBS Jaarplan 2023' (CBS Annual Plan 2023) (Dutch only): 4. Kaders voor een adequate statistische voorziening (4. Frameworks for adequate statistical provision).

11.1.4. Improvements in quality procedures

From 4 to 8 July 2022, Statistics Netherlands (CBS) was the subject of a peer review under supervision of the European Statistical System (ESS).
Based on interviews, the international peer review team, led by the former Director General of the Croatian statistical institute, investigated the Netherlands’ compliance with the quality principles and indicators of the European Statistics Code of Practice.

Fourteen recommendations have been formulated to help the Netherlands do its work better. They focus on, for example, publication policy, confidentiality and privacy, availability of private data sources and the CBS Academy.
The full report and recommendations are publicly available at this website.

11.2. Quality management - assessment

See 11.1.4 and the attached Quality declaration.

12.1. Relevance - User Needs

The main groups of users are policy makers, researchers and the general public. Information from the combined data collection is used also for subsidy payments, enforcement of manure law and emission calculations.

Each user will have its own set of variables of interest. This cannot be specified for every user group, but in a general sense:

• for subsidy payments: land (arable crops, horticultural crops, grasslands, rough grazings, fallow land, natural territory);
• for emission calculations: livestock (cattle, pigs, poultry, horses, rabbits, fur animals);
• for researchers, policy makers: special topics (e.g. succession, land treatment, etc.), labour force, etc.;
• for enforcement of manure law: land, livestock.

12.1.1. Main groups of variables collected only for national purposes

The variables are collected using a combined data collection, according to the principle 'collect once use multiple times'.
This means that there are virtually no characteristics that are collected ONLY for national purposes; most characteristics are (also) collected for EU and other international regulations.
Occasionally, characteristics solely for national policy needs are integrated in the combined data collection, but in IFS years this is usually avoided in order to keep the administrative burden as low as possible.

The list of characteristics for the annual agricultural census is determined by a group of experts on agriculture. Because the data collected is used for multiple purposes the level of detail is much higher than for IFS.
Characteristics that are 'extended' for (a.o.) national information needs are:

• livestock, mainly for enforcement of the manure law and emission calculations;
• arable crops, mainly for enforcement of the manure law and subsidies;
• horticultural crops, because of the specific economic importance of this agricultural sector in the Netherlands.

12.1.2. Unmet user needs

The user needs are discussed in the WG for the national census. All stakeholders specify their information needs, which have to be accompanied by a legal basis for data collection. Only if there is a legal basis, and data is not available through other sources, integration in the combined data collection is considered. If user needs cannot be taken on-board the coming census year they may be moved to the next year (provided there is a legal basis, otherwise they are not taken on-board).

12.1.3. Plans for satisfying unmet user needs

User needs that are 'need to know' but can not (yet) be integrated in the current census, will be looked upon in the next census.

12.2. Relevance - User Satisfaction

There is no specific procedure to measure user satisfaction for the census, however information comes from WG members and data users, also the Netherlands Enterprise Agency (RVO) carries out a user satisfaction survey for the combined data collection.

12.2.1. User satisfaction survey

12.2.2. Year of user satisfaction survey

Not applicable.

12.2.3. Satisfaction level

Not applicable

12.3. Completeness

Information on not collected, not-significant and not-existent variables is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).

12.3.1. Data completeness - rate

Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.

13.1. Accuracy - overall

See categories below.

13.2. Sampling error

See sub-categories below.

13.2.1. Sampling error - indicators

Please find the relative standard errors on Eurostat’s website, at the link: CircaBC website.

13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091

There are no cases where RSEs are above thresholds.

13.2.3. Reference on method of estimation

Core and modules are carried out as a census. We did not use a methodology to calculate relative standard errors and we consider that the relative standard errors are equal to zero (or "missing" where the totals of variables are equal to zero).

13.2.4. Impact of sampling error on data quality

None

13.3. 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 period
Temporarily out of production during the reference period
Ceased activities
Merged to another unit
Other

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 units

13.3.1.1.3. Additional information over-coverage error

Because of the combined data collection, the initial sampling frame (the administrative farm register) contains units that are relevant for other stakeholders, but do not belong to the population of the agricultural census (e.g. below the threshold or non-agricultural NACE). These units are removed during processing.

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

Under-coverage is very low (estimated to be less than 1 or 2%).

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)

Units with outdated information in the frame (variables below thresholds in the frame but above thresholds in the reference period)
Other

13.3.1.3.3. Actions to minimise the under-coverage error

The agricultural census is part of a combined data collection. Data from the combined data collection is also used for enforcement of manure law and compliance with emission obligations, therefore there are regular checks on correct registration and on information supplied, with fines if necessary.

13.3.1.3.4. Additional information under-coverage error

Because of the compulsory registration in the business register, the obligation to fill in the census questionnaire, the dependency of subsidies on registration, and the possibility of fines, the under-coverage is estimated to be very low. Furthermore, there are regular checks on completeness of the frame.

Other types of holdings belonging to the core population but not included in the main frame are holdings which could not be selected from the business register because they are registered with an incorrect (non-agricultural) NACE (e.g. the NACE that the holding received when registering in the register no longer matches the activities of the holding).

13.3.1.4. Misclassification error

Yes

13.3.1.4.1. Actions to minimise the misclassification error

Misclassification errors cannot totally be ruled out but are estimated to be minimal.

Initially holdings are selected from the administrative farm register (AFR) which is constantly updated with the BR and contains (a.o.) information on the NACE activity. This information can be wrong or incomplete.
Given the extensive checks and the use for legal purposes, misclassification in the AFR is expected to be very small. Also during processing additional checks are made to ensure that misclassification errors are minimised.

13.3.1.5. Contact error

Yes

13.3.1.5.1. Actions to minimise the contact error

Contact information is constantly updated. Information comes a.o. from the BR, I&R registers, IACS or direct information from respondents in the census questionnaire.

13.3.1.6. Impact of coverage error on data quality

Low

13.3.2. Measurement error

See sub-categories below.

13.3.2.1. List of variables mostly affected by measurement errors

Measurement errors cannot totally be ruled out, but are expected to be minimal. There are no specific variables that are mostly affected, but it is clear that the possibility of measurement errors is closely related to the clarity and complexity of the questions. Also new/unfamiliar questions can lead to measurement errors. Many questions are recurring annually and will be improved if unclear, but for new questions this may take some time.

13.3.2.2. Causes of measurement errors

Complexity of variables
Unclear questions
Respondents’ inability to provide accurate answers

13.3.2.3. Actions to minimise the measurement error

Pre-testing questionnaire
Pre-filled questions
Explanatory notes or handbooks for enumerators or respondents
On-line FAQ or Hot-line support for enumerators or respondents
Other

13.3.2.4. Impact of measurement error on data quality

Low

13.3.2.5. Additional information measurement error

The internet application eliminates interviewer caused errors, and largely reduces erroneous answers by the respondents, because many checks are already implemented in the application. Measurement errors due to difficult or unclear questions or definitions are minimal because a census is held every year, and the questions are kept constant as much as possible and improved if necessary. Also the questionnaire is designed, reviewed and validated by a group of experts. Survey instrument errors are likely to be minimal, because the internet application in use is already operational for several years. Remaining errors are mostly detected at early stage, either by automated control programs, or from plausibility checks during the analysis phase.

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

Refusal to participate
Inability to participate (e.g. illness, absence)

13.3.3.1.2. Actions to minimise or address unit non-response

Reminders
Legal actions
Imputation
Other

13.3.3.1.3. Unit non-response analysis

Analyses have been carried out on the groups of non-respondent holdings. This showed that these were mainly holdings that ceased activities but failed to report this, and also (despite the possible fines) some refusals.
Since the combined data collection is also used to apply for subsidies, holdings that do not qualify for (CAP) subsidies such as greenhouses seem to be more likely not to respond.

13.3.3.2. Item non-response - rate

We did not calculate item non-response rate. Item non-response in an online questionnaire is hard to detect. If a question is not answered it is not clear whether the subject is not present or whether the question has not been completed.

The only way to prevent item non-response is to make answering mandatory, which may not be desirable because of administrative burden (and even in that case it does not guarantee that the correct answer will be given).

Item non-response cannot be assessed for some variables in imputed non-respondent holdings. Imputation for unit non-response uses information from the previous census year, however not all variables are also available in the previous year. The number of variables that cannot be imputed is low (main variables are asked annually) and it is not certain that 'model information' on the variable in question (e.g. by next neighbour imputation) is accurate or even present for the current holding. The variables that are not present in the previous year are therefore not filled in. Because the imputation rate is very low (approx. 1%) item non-response errors resulting from this are very low.

13.3.3.2.1. Variables with the highest item non-response rate

Variables with item non-response, which cannot be assessed in imputed non-respondent holdings, mainly concern machinery and equipment, soil management practices, and irrigation.

13.3.3.2.2. Reasons for item non-response

Refusal
Skip of due question
Farmers do not know the answer

13.3.3.2.3. Actions to minimise or address item non-response

Other

13.3.3.3. Impact of non-response error on data quality

Low

13.3.3.4. Additional information non-response error

Unit non-response is handled by imputation of information from the previous census. Analyses have shown that this information is still highly accurate (since a census is held every year). Comparison with I&R registers e.g. showed that the overall difference between the imputed values and the numbers from the registers is only a few percent. Furthermore, the non-response rate is very low and several actions (including fines) are in place to minimise non-response. Other actions to minimise unit non-response and item non-response is to keep the burden as low as possible by using registrations whenever possible.

Other actions to minimise item non-response is by built-in routing and checks in the online questionnaire (e.g. the respondent has to answer certain (blocks of) questions).
For some questions, item non-response is eliminated by making them compulsory based on other information available (e.g. when there are animals registered in I&R, information on that animal type must be supplied). For some types of questions, item non-response is minimised by making compulsory to check at least one item in a drop-down list.

13.3.4. Processing error

See sub-categories below.

13.3.4.1. Sources of processing errors

Data processing

13.3.4.2. Imputation methods

Previous data for the same unit

13.3.4.3. Actions to correct or minimise processing errors

To minimise processing errors the information system is extensively tested and manual actions are minimised as much as possible. All corrections are made using scripts (no manual adjustments) and before data is released extensive checks and analyses are performed.

13.3.4.4. Tools and staff authorised to make corrections

Standard software tools installed at Statistics Netherlands are used (SPSS, R, Excel, etc.). Only staff involved in the processing of the agricultural census is authorised to make corrections.

Note: pre-processing is done at RVO; final processing, including additional corrections is done at Statistics Netherlands.

13.3.4.5. Impact of processing error on data quality

Low

13.3.4.6. Additional information processing error

Due to the validation that is already part of the internet application, the pre-processing done at RVO and the extensive testing, there are only very few additional corrections necessary.

13.3.5. Model assumption error

In specific cases a model is used to derive the livestock numbers for cattle, sheep, goats and poultry from the corresponding I&R registers.

For cattle, sheep and goats, the I&R register contains the livestock numbers per housing location. Each housing location consists of one or more stables and each stable has its own 'production purpose' ('for milk', 'for meat' and 'mixed').

For stables with production purpose 'for milk' and 'for meat', the needed variables are completely derived from the register using algorithms.
For stables with production purpose 'mixed', the respondent has to subdivide the number of animals registered in I&R into the requested subcategories, whereby the total number of animals, sex and age cannot be altered.

For poultry, the I&R register is built up from the compulsory transport notifications of poultry to and from the holding. The poultry categories are completely derived from the I&R register using algorithms.

The algorithms were established in a project financed by the Ministry. They were extensively tested and finally validated and reviewed by a group of experts.
The use of algorithms has drastically reduced administrative burden, while the numbers derived from the algorithms have shown to closely approximate the numbers obtained through a questionnaire.

The livestock numbers are derived from the corresponding I&R registers, using established algorithms.

14.1. Timeliness

See sub-categories below.

14.1.1. Time lag - first result

The day of the release of first results was before 31 December 2023.

The first provisional results on main crops at country level were published by the end of August 2023. The first provisional results of all the regular census subjects at country level, were published by the end of October 2023, and the first complete set of preliminary results (all regular census subjects at country and regional level) were published in November 2023.

14.1.2. Time lag - final result

Final results of the 2023 census were published 29 March 2024, 3 months after the last day of the reference year.

Note: this relates to the items in the annual agricultural census. For IFS, these are the subjects from the core and the modules on labour force and OGA. The results from the modules on irrigation, soil management practices, machinery and equipment, orchard and rural development are not published nationally (besides possibly some dedicated articles later on).

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 actual publication date was in accordance with the target date for publication.
See also item 14.1.2

15.1. Comparability - geographical

See sub-categories below.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable, because there are no mirror flows in Integrated Farm Statistics.

15.1.2. Definition of agricultural holding

See sub-categories below.

15.1.2.1. Deviations from Regulation (EU) 2018/1091

The definition of agricultural holdings is in accordance with Regulation (EU) 2018/1091. Some data of agricultural holdings is included in the national statistics that is not included in EU statistics. This concerns holdings with bulb forcing, Belgian endive cultivation and special mushroom cultivation (like oyster mushrooms, shiitake) with a different definition (see 15.1.2.2.). Holdings with only these activities are ineligible for IFS and are not included in the records sent to Eurostat.

15.1.2.2. Reasons for deviations

Regarding bulb forcing, in the combined survey/national agricultural census farmers are asked to report the number and/or kilograms of bulbs forced in the previous season. If these farmers did not have bulb forcing in the reference year 2023 (and did not have other agricultural activities), they are non-eligible for IFS, but the holdings are included in the national statistics because Statistics Netherlands reports the number/kg of bulbs forced in the previous season. This concerns a negligible number of holdings, because most of the holdings that report number and/or kilograms of bulbs forced in the previous season also have hectares of bulb forcing in the reference year 2023. Farmers with bulb forcing in the reference year 2023 report the hectares of bulb forcing and are included in IFS.

Regarding special mushroom cultivation (oyster mushrooms and shiitake), farmers must report the substrate used in 2022 (in tonnes) in the combined survey/national agricultural census. If these farmers did not cultivate special mushrooms in the reference year 2023 (and did not have other agricultural activities) they are non-eligible for IFS, but the holdings are included in the national statistics because Statistics Netherlands reports the substrate used in 2022. This concerns a negligible number of holdings, because most of the holdings that report substrate used in 2022 also have hectares of special mushroom cultivation in the reference year 2023. Farmers who cultivated special mushrooms in the reference year 2023 report the hectares cultivated and are included in IFS.

Regarding Belgian endive cultivation, farmers need to report in the combined survey/national agricultural census the area of Belgian endive grown in 2022 which is harvested in the 2022/2023 season. If these farmers did not have Belgian endive cultivation in the reference year 2023 (and did not have other agricultural activities) they are non-eligible for IFS. This concerns a negligible number of holdings, because most of the holdings that report area of Belgian endive grown in 2022 also have hectares of Belgian endive cultivation in the reference year 2023. The area of Belgian endive cultivation in the reference year 2023 is included in IFS.

15.1.3. Thresholds of agricultural holdings

See sub-categories below.

15.1.3.1. Proofs that the EU coverage requirements are met

The threshold in the national agricultural census is 3 000 euro SO-NL.
This SO-NL calculation is based on more detailed SO coefficients then the ones sent to Eurostat (which are weighted averages of the national coefficients).

The national agricultural census contains much more detail than the variables sent to Eurostat, especially for crops. For all crops and livestock variables in the national agricultural census SO coefficients are calculated, and SO-NL is based on these coefficients.

The threshold of 3 000 euro SO-NL is also used for the population sent to Eurostat. Because SO-EU coefficients are weighted averages of the SO-NL coefficients, the SO-EU is in most cases different from SO-NL.

The proof that the use of the SO-NL threshold is compliant with the requirements set by Regulation (EU) 2018/1091 was provided to and approved by Eurostat at the end of 2022.

15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat

There are no differences in the national thresholds and the thresholds for the data sent to Eurostat. Only the ineligible holdings (SO-EU = 0) are excluded from the data sent to Eurostat.

15.1.3.3. Reasons for differences

Not applicable.

15.1.4. Definitions and classifications of variables

See sub-categories below.

15.1.4.1. Deviations from Regulation (EU) 2018/1091 and EU handbook

There are generally no different definitions or classifications compared to the regulations and the handbook, except for the following:

Other gainful related activities directly related to the holdings

Especially when the other gainful activities of the holdings become more important, there is a tendency to place the activities in a separate legal unit, often with its own manager. This generates a decrease in the share of holdings with other gainful activities directly related to the holdings.

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

No use of different LSU coefficients.

15.1.4.1.5. Livestock included in “Other livestock n.e.c.”

Other livestock n.e.c. also includes breeding of rodents (e.g. guinea pigs, gerbils, hamsters).

15.1.4.2. Reasons for deviations

See 15.1.4.1.

15.1.5. Reference periods/days

See sub-categories below.

15.1.5.1. Deviations from Regulation (EU) 2018/1091

The reference period for the irrigation module and the soil management practices is the calendar year 2022.

15.1.5.2. Reasons for deviations

The reason for the deviation for the irrigation module is that for the IFS 2023 the farmers have to fill in the form before between 1 March and 15 May of that year. This makes it impossible to provide us with information on irrigation for the year 2023. Therefore we asked the farmers to fill in information for the year 2022, the same applies for the soil management practices.

15.1.6. Common land

The concept of common land does not exist

15.1.6.1. Collection of common land data

Not applicable

15.1.6.2. Reasons if common land exists and data are not collected

Not applicable.

15.1.6.3. Methods to record data on common land

Not applicable

15.1.6.4. Source of collected data on common land

Not applicable

15.1.6.5. 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

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

23 years for the data published by CBS and 8 years for the data published by Eurostat.

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 changes

15.2.2.2. 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 changes

15.2.3.2. 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 changes

15.2.4.2. 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 changes

15.2.5.2. 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 changes

15.2.6.2. Description of changes

Not applicable.

15.2.7. Common land

See sub-categories below.

15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat

There have been no changes

15.2.7.2. Description of changes

Not applicable.

15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat

In the 2023 vs 2020 comparison it can be noticed that:

The number of farms run by legal entities and by non-family managers increased. The number of agricultural holdings in the Netherlands is decreasing. Smaller holdings in particular are closing down and other holdings are growing. Larger holdings are increasingly opting for legal entities in connection with liability, taxes and financing options.
There has been a remarkable increase of share of holdings having SO_EURO falling in the upper class > 500 000€). The number of agricultural holdings is decreasing more rapidly for years now than the number of hectares and animals. Partly because there is no successor, holdings are being merged. Cultivation is more efficient and intensive. This has increased the size of the companies and related to this the SO_EURO.
Due to the introduction of the new CAP in 2023 and the eco-schemes, there have been remarkable changes in the cultivation of crops. Especially the cultivation of protein crops such as lupins, field beans and soya has increased (which explains the increase in P1000T and I1130T). Also, fallow land (Q0000T) increased because of an increase in green manure to meet greening requirements.
More and more dairy farmers, arable farmers and fruit growers are opting for nut cultivation (F4000T). The reason is that the consumption of nuts is increasing in The Netherlands. Nut cultivation is sustainable and contribute to the protein transition from animal to vegetable proteins.
I1190T is decreasing mainly because of the decrease in the cultivation of poppy (Papaver somniferum L.). A threat to the cultivation of poppy are residues of plant protection products. The crop is very sensitive to plant production products and can absorb residues of products from previous cultivation, which causes exceedances of the MRL (Maximum Residue Limit) which makes the cultivation less attractive.
Due to the weather conditions, less grain maize and corn-cob-mix could be sown in 2023, hence the decrease in C1500T compared to IFS 2020.
The decrease in A5140 is the result of both the switch to concepts with lower occupancy and the fact that the existing barn surface area in the Netherlands remains the same because hardly any new barns are being built. In 2023, Dutch supermarkets have switched to BLK 1 star poultry meat, a Dutch quality mark on food packaging by which consumers can quickly see which standards are used to grow animals. This includes certain husbandry requirements that require broiler farmers to breed broilers of a slow-growing breed with lower barn occupancy.
The reason for the declining number of rabbits, breeding females (A6111) is the declining number of farms. Due to ageing of the holder and the lack of a successor, the number of rabbit farms is decreasing. The number of farms with other gainful activities is increasing, which results in an increase of non-family members regularly working on the holding and having other gainful activities.

15.2.9. Maintain of statistical identifiers over time

15.3. 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

Yes

15.3.3.2. Results of analysis at micro level

Results are coherent at micro level for Annual Crop Statistics and Animal Production Statistics.

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

Yes

15.3.4.2. Results of analysis at macro level

Coherence cross-domain: IFS vs ORGANIC CROP PRODUCTION (hectares) in relative terms

The area of organic permanent crops has increased from 2022 to 2023.

Coherence cross-domain: IFS vs ANIMAL PRODUCTION (1000 heads) in relative terms

The difference in IFS vs Animal Production is caused mainly by different reference day/reference period. In addition, for some animal types (e.g. poultry) there may be a period between production cycles in which the housing is empty (e.g. regular sanitary cleaning of animal houses) and a lower number or no livestock are on the holding. Because IFS is a structural survey, the livestock of these holdings correspond to the number of animals just before the sanitary cleaning.

Coherence cross-domain: IFS vs ORGANIC ANIMAL PRODUCTION (heads) in relative terms

The number of organic bovine animals has increased from 2022 to 2023.

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

Questionnaires for crop yield predictions and other agricultural statistics are tuned to the census in order to prevent asking the same question to farmers twice. For the same reason, the census questionnaire is combined with the application for the single payment scheme in the context of the CAP.

16.2. Efficiency gains since the last data transmission to Eurostat

Further automation
Increased use of administrative data
Other

16.2.1. Additional information efficiency gains

Further efficiency gains were reached by pre-filling the questionnaire as much as possible from the previous census, or from administrative registers, and (in specific cases) by the use of algorithms to derive the requested animal categories directly from the I&R registers. Also the plausibility checks in the electronic questionnaire itself have been further developed.

16.3. Average duration of farm interview (in minutes)

See sub-categories below.