Statistics Netherlands

Environmental, energy and spatial statistics, team Agriculture and Nature

Postbus 24500
2490 HA Den Haag

See sub-categories below.

The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force.  They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.

The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.

The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.

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) 2018/1874.

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.

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.

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 2020 are set in Commission Implementing Regulation (EU) 2018/1874.

The following groups of variables are collected in 2020:

• 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 "Animal housing and rural development module":  animal housing, nutrient use and manure on the farm, manure application techniques, facilities for manure.

See sub-category below.

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.

See sub-categories below.

The thresholds of agricultural holdings are available in the annex.

The same population of agricultural holdings defined in item 3.6.1

The above answer holds for the modules ‘Labour force and other gainful activities’ and ‘Rural development’. The module ‘Machinery and equipment’ is not collected in 2020.

The same population of agricultural holdings defined in item 3.6.2 (not only agricultural holdings with at least one of the following: bovine animals, pigs, sheep, goats, poultry).

See sub-categories below.

The entire territory of the country.

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

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 few cases where coordinates are missing the postal code or the location of the largest parcel or stable is used.

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.

Older (EU) time series are described in the previous quality reports (national methodological reports).

The 2020 data are processed (by Eurostat) with 2017 standard output coefficients (calculated as a 5-year average of the period 2015-2019). 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.

The use of land refers to the reference year 2020. 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.

Not applicable for 2020.

The reference day 1 April within the reference year 2020.

The 12-month period ending on 1 April 2020. This period includes the reference day used for livestock and animal housing.

The 12-month period ending on 1 April within the reference year 2020.

The three-year period ending on 31 December 2020.

The reference day 1 April within the reference year 2020.

See sub-categories below.

See sub-categories below.

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

wetten.nl - Regeling - Wet op het Centraal bureau voor de statistiek - BWBR0015926 (overheid.nl)

20-11-2003

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.

See sub-categories below.

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.

See sub-categories below.

See sub-categories below.

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, pragmatic approach: 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 the lower regional levels. Sensitive characteristics for which there are only very few holdings will not be published. 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, ..) 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).

For non-sensitive characteristics (e.g. number of animals or crop areas) a less strict regime is used (often these characteristics can be easily observed, or are directly available from farmers own website). In these cases it is accepted that information on individual farms may be derived. In all cases privacy protection has the highest priority, therefore all requests for custom-tables are scrutinised.  

See sub-categories below.

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, see: 
https://www.cbs.nl/en-gb/our-services/customised-services-microdata

Services are:

• Customized research, conducted by Statistics Netherlands
https://www.cbs.nl/en-gb/our-services/customised-services-microdata/customised-research

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
https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research

Under certain conditions, Statistics Netherlands makes available micro-data for statistical research. To be authorized to use this data the researcher must work at an organisation authorized 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.

See sub-categories below.

There is no release calendar specifically for IFS. All regular information from the annual agricultural census (including crops, livestock and labour force) is published on-line on the StatLine database, according to a pre-determined release policy.
For all StatLine tables the table explanation contains the release policy for the respective table.

An overview of new and revised StatLine tables can be found here: https://www.cbs.nl/en-gb/cijfers/statline/new-and-revised-statline-tables (EN) and https://www.cbs.nl/nl-nl/cijfers/statline/recente-cijfers (NL) 

Information on Ad hoc and incidental subjects, including IFS, is released through articles on the Statistics Netherlands website.

The release calendar for the annual agricultural census can be accessed through the tables on the online Statline database (StatLine (cbs.nl))

Note: 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. 

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. In special cases the press may be granted access to publications under embargo. Information on the release policy can be found here: Publication policy (cbs.nl)

Not applicable

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

See sub-categories below.

See sub-categories below.

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

Publications in English include:

Dairy goat herd has increased again (cbs.nl)
Less protein crop farming in the Netherlands (cbs.nl)
Decline in pig farming (cbs.nl)
Slight decline in arable crop area (cbs.nl)
Nearly 30 thousand contract workers in agriculture (cbs.nl)

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

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

See sub-categories below.

All dissemination is via Statline: StatLine - Datasets via thema (cbs.nl) (Dutch) and StatLine - Datasets by themes (cbs.nl) (English)

and the Statline Netherlands website (CBS - Statistics Netherlands).

See also 10.1.2.

See sub-categories below.

See StatLine - Datasets via thema (cbs.nl) (Dutch) and StatLine - Datasets by themes (cbs.nl) (English)

Note: the indicative number of hits is based on Q4 2020.

Dutch tables (under 'Landbouwtelling en biologische landbouw'):
- Landbouw; nationaal (crops, livestock and land use at national level), approx. 2500 hits
- Landbouw; regio (crops, livestock and land use by region), approx. 2000 hits
- Landbouw; gemeente (crops, livestock and land use, by municipality), approx. 2000 hits
- Landbouw; bedrijfstype, nationaal (crops, livestock and land use by farmtype at national level), approx. 500 hits
- Landbouw; hoofdbedrijfstype, regio (crops, livestock and land use, by general farm type and region), approx. 1000 hits
- Landbouw; arbeidskrachten, regio (labour force by region), approx. 250 hits
- Landbouw; klassenindeling,regio (crops, livestock and land use, by size classes and region), approx. 500 hits
- Landbouw; economische omvang (information by economic size classes and farm type), approx. 500 hits
- Landbouw; economische omvang, regio (information by economic size classes, general farm type and region), approx. 250 hits
- Landbouw; verbreding (other gainful activities by main farm type and region), approx. 250 hits
- Activiteiten van biologische landbouwbedrijven, regio (organic farming by stage of conversion and region), approx. 250 hits

English tables (under agricultural census):
- Agriculture; crops, livestock and land use by general farm type, region, approx. 500 hits
- Agriculture; labour force by region, approx. 150 hits 

See https://statline.cbs.nl.

See sub-category below.

Not available

Not requested.

See sub-categories below.

Not requested.

Not applicable

Not applicable

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

 The present methodological report for IFS.

See sub-categories below.

See sub-categories below.

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

The 2015 peer review identified the following areas of concern: the budget available for the programme in general and for investment in the ICT infrastructure in particular; the departure of experienced personnel due to retirement; and the re-positioning of CBS's Autonomous Administrative Authorities. Other areas for focus included improving quality management and the availability of background information, including metadata, in English. 

A recommendation from the ISO audit was to constantly carry out and improve the PDCA cycle (Plan, Do, Check, Act).  

The follow up of the findings and recommendations of the peer review and the ISO 9001 audit is constantly monitored.

See 11.1.4 and the attached Quality declaration.

See also: https://www.cbs.nl/en-gb/over-ons/organisation/quality.

See sub-categories below.

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, ..) labour force, ....;
• for enforcement of manure law: land, livestock.

The variables are collected using a combined data collection, according to the principle 'collect once use many 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.

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). 

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. 

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

Not applicable

Information on low- and zero prevalence variables is available on Eurostat's website.

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

See sub-categories below.

See categories below.

See sub-categories below.

Please find the relative standard errors for the main variables in the annex.

There are no cases where RSEs are above thresholds.

Not applicable. Core and modules are carried out as a census. 

See sub-categories below.

See sub-categories below.

The over-coverage rate is available in the annex. 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. 

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. 

Not requested.

See sub-categories below.

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

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.

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.

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.

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.

See sub-categories below.

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.

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.

See sub-categories below.

The unit non-response rate is in the annex of 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.

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.

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 is minimised 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.

Item non-response cannot be assessed for some variables in imputed non-respondent holdings. Imputation for unit-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.

Not applicable

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 minimize non-response.

See sub-categories below.

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.

Standard software tools installed at Statistics Netherlands are used (SPSS, R, Excel, ...). 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.

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.

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.

See sub-categories below.

See sub-categories below.

Data collection closed 15 October 2020; from 15 May 2020 onwards there were cutbacks in place for subsidy applications; by then already well over 90% of respondents had answered.
The first provisional results on main crops at country level were published by the end of June 2020. The first provisional results of all the regular census subjects at country level, were published by the end of September 2020, and the first complete set of preliminary results (all regular census subjects at country and regional level) were published in November 2020. The final results from the 2020 census were published in March 2021.

Final results of the 2020 census were published 19 March 2021, 2.5 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. After this the IFS modules on animal housing and manure management and rural development were prepared.
The dataset was sent for validation to Eurostat in August 2021. The results from the modules on animal housing and manure management and rural development are not published nationally (besides possibly some dedicated articles later on). 

See sub-categories below.

See sub-categories below.

Not requested.

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

See sub-categories below.

See sub-categories below.

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

See sub-categories below.

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

Not applicable

See sub-categories below.

The threshold in the national agricultural census is 3000 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 3000 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 regulation is given in the annex.

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

Not applicable

See sub-categories below.

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.

The information is available in the annex. 
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.

The information is available in the annex of item 15.1.4.1.1. 

The information is available in the annex of item 15.1.4.1.1. 

No use of different LSU coefficients.

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

See 15.1.4.1.

See sub-categories below.

No deviations.

Not applicable

Not applicable

Not applicable

Not applicable

See sub-categories below.

No deviations.

Not applicable

Not applicable

See sub-categories below.

20 years

See sub-categories below.

Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. 

See sub-categories below.

Not applicable

See sub-categories below.

Not applicable

See sub-categories below.

Legal personality of the agricultural holding

In IFS, there is a new class (“shared ownership”) for the legal personality of the holding compared to FSS 2016, which trigger fluctuations of holdings in the classes of sole holder holdings and group holdings.

Other livestock n.e.c.

In FSS 2016, deer were included in this class, but in IFS they are classified separately.
Also in FSS 2016, there was a class for the collection of equidae. That has been dropped and equidae are included in IFS in "other livestock n.e.c."

Livestock units

In FSS 2016, turkeys, ducks, geese, ostriches and other poultry were considered each one in a separate class with a coefficient of 0.03 for all the classes except for ostriches (coefficient 0.035). In IFS 2020, the coefficients were adjusted accordingly, with turkeys remaining at 0.03, ostriches remaining at 0.35, ducks adjusted to 0.01, geese adjusted to 0.02 and other poultry fowls n.e.c. adjusted to 0.001.

Organic animals

While in FSS only fully compliant (certified converted) animals were included, in IFS both animals under conversion and fully converted are to be included.

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.

See sub-categories below.

Not applicable

See sub-categories below.

Not applicable

Not for all variables an unambiguous explanation for their evolution can be given. The trends are confirmed by the annual agricultural census.
For some variables, there are clear policy measurements, for others it will mainly be adjustment to market conditions.

Regarding A2220 (Heifers, 1 to less than 2 years old) and A4210K (Goats, breeding females):
The reduction of the cattle population is the result of the phosphate reduction plan. This mainly had consequences for young cattle in dairy farming.
The dairy goat sector is a sector that has been growing in the Netherlands for years. There are fewer 'rules' in the goat sector than in other sectors and the milk price of goat milk continues to rise. Businesses are expanding as a result and some cattle farmers will have switched to goats.

The trends for G2000T (Leguminous plants harvested green – outdoor), I1130T (Soya – outdoor), P1000T (Field peas, beans and sweet lupins – outdoor) and I1190T (Other oil seed crops n.e.c. – outdoor) are linked to the protein transition and sustainability programs. For soy, it also applies that three Northern provinces provided subsidies in 2017 to stimulate the cultivation of soy in the Netherlands; later other provinces also started subsidy programs.

The development of J2000T (Permanent rough grazings – outdoor) has to do with the CAP measure concerning the conservation of permanent grassland. The share of permanent grassland is monitored at the national level. If the share of permanent grassland decreases nationally, action is taken towards individual farmers. This may result in a sales ban and an obligation to repair.

See sub-categories below.

Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.

Not applicable, because Integrated Farm Statistics have no relevance for national accounts.

See sub-categories below.

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

See sub-categories below.

They have been identified few discrepancies between crops and animal statistics with the correspondent figures in IFS.

For Crops: the reason for the discrepancies concerning I0000 and I9000 is that in IFS Chicory is assigned to industrial crops (I0000 and I9000 respectively), while in crops statistics this was assigned to fresh vegetables outdoor(V0000_S0000T, in particular to Chicory For Consumption).

For Animals: the difference in IFS vs animal population is caused mainly by different reference day/reference period (1 April for IFS and December for animal population). Also in IFS corrections for temporary vacancy of stables are made.

The data are internally consistent. This is ensured by the application of a wide range of validation rules.

See sub-categories below.

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.

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.

See sub-categories below.

Not available

Not available

Not relevant

Not available

See sub-categories below.

In the revision policy, a distinction is made between provisional and final data. As long as data are provisional, changes can be made available as 'update'. Updates usually take place whenever additional or better information is available. An update does, besides the reason for the update, not require any further information for the user. As soon as data are final, changes can only be made available as ‘correction’ or ‘revision’. Corrections require additional information for the user (reason for the correction, impact, etc.).
Revisions take place when there are major changes in data and methodology, mostly with severe impact on time-series. Revisions also require additional information for the user. Mostly recalculations for previous data are made to re-establish comparable time-series.

After publication of the complete table set for the annual agricultural census, they are kept provisional for three months. During this period there are usually no further updates. When data are final, corrections are only made if they have severe impact on the published data.
Normally there are only minor differences between provisional and final data; corrections after data are final are rare.
Revision has taken place following the transition from SGM to SO and the new typology in 2010. Recalculations (based on SO 2004) have then been made for the agricultural census back to 2000.

Not requested.

See the timetable of the statistical process in the annex.

See sub-categories below.

See sub-categories below.

Administrative Farm Register (AFR), built up from and  updated by the Business Register (BR) and other administrative sources

See sub-categories below.

Not applicable.

Not applicable.

Not applicable.

See sub-categories below.

Not applicable.

Not applicable

Not applicable

See sub-categories below.

Not applicable

Not applicable

Not applicable

See sub-categories below.

Not applicable

Not applicable

Not applicable

See sub-categories below.

Not applicable

Not applicable

Not applicable

Not applicable

See sub-categories below.

The information is available on Eurostat's website.

See the attached Excel file in the Annex.

The information on innovative approaches and the quality methods applied is available on Eurostat's website.

A national agricultural census is conducted every year. In the years an IFS is held the IFS questions are integrated in the national agricultural census.

See sub-categories below.

Please find the questionnaire in annex.

See sub-categories below.

Data validation is, as far as possible, already implemented in the internet application. After data collection several software tools are used during processing and validation (SPSS, R, Excel).

After data collection and pre-processing by RVO data is transferred to Statistics Netherlands for final data compilation, which includes checks and analyses at different levels (micro, meso, macro).

The overall imputation rate is approx. 1%. Imputation is done for unit non-response, and includes all corresponding variables from the previous data collection.

Covered under Data compilation.

Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.

See sub-categories below.

AFR – Administrative Farm Register

BR – Business Register

CAP – Common Agricultural Policy

CAPI –  Computer Assisted Personal Interview

CATI – Computer Assisted Telephone Interview

CAWI – Computer Assisted Web Interview

CBS – Statistics Netherlands

FSS – Farm Structure Survey

IACS – Integrated Administration and Control System

IFS – Integrated Farm Statistics

I&R - Identification and Registration of Livestock

LSU – Livestock units

NACE – Nomenclature of Economic Activities

NUTS – Nomenclature of territorial units for statistics

OGA – Other gainful activities

PAPI – Paper and Pencil Interview

RVO – Rijksdienst voor Ondernemend Nederland / Netherlands Enterprise Agency

SGM – Standard Gross Margin

SO – Standard output
SO-EU – Standard Output according to EU-coefficients
SO-NL – Standard Output according to national, more detailed, coefficients

UAA – Utilised agricultural area

WG – Working Group

No additional comments.