Farm structure (ef)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: Statistics Netherlands


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Statistics Netherlands

1.2. Contact organisation unit

Environmental, energy and spatial statistics, team Agriculture and Nature

1.5. Contact mail address

Postbus 24500
2490 HA Den Haag


2. Metadata update Top
2.1. Metadata last certified 24/08/2021
2.2. Metadata last posted 24/08/2021
2.3. Metadata last update 24/08/2021


3. Statistical presentation Top
3.1. Data description

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

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

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

3.2. Classification system

Data are arranged in tables using many classifications. Please find below information on most classifications.

The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 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.

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 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.
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
No
3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
No
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

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.

3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”

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).

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 in 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 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.

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

3.9. Base period

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.


4. Unit of measure Top

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.


5. Reference Period Top

See sub-categories below.

5.1. Reference period for land variables

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.

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

Not applicable for 2020.

5.3. Reference day for variables on livestock and animal housing

The reference day 1 April within the reference year 2020.

5.4. Reference period for variables on manure management

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

5.5. Reference period for variables on labour force

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

5.6. Reference period for variables on rural development measures

The three-year period ending on 31 December 2020.

5.7. Reference day for all other variables

The reference day 1 April within the reference year 2020.


6. Institutional Mandate Top
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

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

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

20-11-2003

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. Confidentiality Top
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, 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.  

7.2.2. Microdata

See sub-categories below.

7.2.2.1. Use of EU methodology for microdata dissemination
No
7.2.2.2. Methods of perturbation
Other
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, 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.


8. Release policy Top
8.1. Release calendar

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.

8.2. Release calendar access

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. 

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. 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)

8.3.1. Use of quality rating system
No
8.3.1.1. Description of the quality rating system

Not applicable


9. Frequency of dissemination Top

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


10. Accessibility and clarity Top
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 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).

10.2. Dissemination format - Publications

See sub-categories below.

10.2.1. Production of paper publications
No
10.2.2. Production of on-line publications
Yes, in English also
10.2.3. Title, publisher, year and link

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.

10.3. Dissemination format - online database

See sub-categories below.

10.3.1. Data tables - consultations

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 

10.3.2. Accessibility of online database
Yes
10.3.3. Link to online database

See https://statline.cbs.nl.

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
No
10.6.3. Title, publisher, year and link to national reference metadata

Not applicable

10.6.4. Availability of national handbook on methodology
No
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 (cbs.nl)

10.7. Quality management - documentation

 The present methodological report for IFS.


11. Quality management Top
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; a peer review was conducted in 2015.

11.1.4. Improvements in quality procedures

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 (PlanDoCheckAct).  

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

11.2. Quality management - assessment

See 11.1.4 and the attached Quality declaration.

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



Annexes:
11.2. Quality declaration


12. Relevance Top
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, ..) labour force, ....;
• 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 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.

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 RVO carries out a user satisfaction survey for the combined data collection.

12.2.1. User satisfaction survey
No
12.2.2. Year of user satisfaction survey

Not applicable

12.2.3. Satisfaction level
Not applicable
12.3. Completeness

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

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. Accuracy Top
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 for the main variables in the annex.



Annexes:
13.2.1. Relative standard errors
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. Methodology used to calculate relative standard errors

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

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 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. 



Annexes:
13.3.1.1. Over-coverage rate and Unit non-response rate
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.

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
No
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

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.

13.3.3.1.1. Reasons for unit non-response
Refusal to participate
Other
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

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.

13.3.3.2.1. Variables with the highest item non-response rate

Not applicable

13.3.3.2.2. Reasons for item non-response
Skip of due question
Other
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 minimize non-response.

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, ...). 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. Timeliness and punctuality Top
14.1. Timeliness

See sub-categories below.

14.1.1. Time lag - first result

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.

14.1.2. Time lag - final result

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). 

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. Coherence and comparability Top
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 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.

15.1.2.2. Reasons for deviations

Not applicable

15.1.3. Thresholds of agricultural holdings

See sub-categories below.

15.1.3.1. Proofs that the EU coverage requirements are met

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.



Annexes:
15.1.3.1. Compliance assessment
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 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.

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 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.



Annexes:
15.1.4.1.1. AWU
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

The information is available in the annex of item 15.1.4.1.1. 

15.1.4.1.3. AWU for workers of certain age groups

The information is available in the annex of 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

No deviations.

15.1.5.2. Reasons for deviations

Not applicable

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

Not applicable

15.2. Comparability - over time

See sub-categories below.

15.2.1. Length of comparable time series

20 years

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 some changes but not enough to warrant the designation of a break in series
15.2.2.2. Description of changes

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

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 some changes but not enough to warrant the designation of a break in series
15.2.5.2. Description of changes

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.

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

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.

15.2.9. Maintain of statistical identifiers over time
Yes
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

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.

15.4. Coherence - internal

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


16. Cost and Burden Top

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.

16.3. Average duration of farm interview (in minutes)

See sub-categories below.

16.3.1. Core

Not available

16.3.2. Module ‘Labour force and other gainful activities‘

Not available

16.3.3. Module ‘Rural development’

Not relevant

16.3.4. Module ‘Animal housing and manure management’

Not available


17. Data revision Top
17.1. Data revision - policy

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.

17.2. Data revision - practice

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.

17.2.1. Data revision - average size

Not requested.


18. Statistical processing Top


Annexes:
18.Timetable_statistical_process
18.1. Source data

See sub-categories below.

18.1.1. Population frame

See sub-categories below.

18.1.1.1. Type of frame
List frame
18.1.1.2. Name of frame

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

18.1.1.3. Update frequency
Continuous
18.1.2. Core data collection on the main frame

See sub-categories below.

18.1.2.1. Coverage of agricultural holdings
Census
18.1.2.2. Sampling design

Not applicable.

18.1.2.2.1. Name of sampling design
Not applicable
18.1.2.2.2. Stratification criteria
Not applicable
18.1.2.2.3. Use of systematic sampling
Not applicable
18.1.2.2.4. Full coverage strata

Not applicable.

18.1.2.2.5. Method of determination of the overall sample size

Not applicable.

18.1.2.2.6. Method of allocation of the overall sample size
Not applicable
18.1.3. Core data collection on the frame extension

See sub-categories below.

18.1.3.1. Coverage of agricultural holdings
Not applicable
18.1.3.2. Sampling design

Not applicable.

18.1.3.2.1. Name of sampling design
Not applicable
18.1.3.2.2. Stratification criteria
Not applicable
18.1.3.2.3. Use of systematic sampling
Not applicable
18.1.3.2.4. Full coverage strata

Not applicable

18.1.3.2.5. Method of determination of the overall sample size

Not applicable

18.1.3.2.6. Method of allocation of the overall sample size
Not applicable
18.1.4. Module “Labour force and other gainful activities”

See sub-categories below.

18.1.4.1. Coverage of agricultural holdings
Census
18.1.4.2. Sampling design

Not applicable

18.1.4.2.1. Name of sampling design
Not applicable
18.1.4.2.2. Stratification criteria
Not applicable
18.1.4.2.3. Use of systematic sampling
Not applicable
18.1.4.2.4. Full coverage strata

Not applicable

18.1.4.2.5. Method of determination of the overall sample size

Not applicable

18.1.4.2.6. Method of allocation of the overall sample size
Not applicable
18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable
18.1.5. Module “Rural development”

See sub-categories below.

18.1.5.1. Coverage of agricultural holdings
Census
18.1.5.2. Sampling design

Not applicable

18.1.5.2.1. Name of sampling design
Not applicable
18.1.5.2.2. Stratification criteria
Not applicable
18.1.5.2.3. Use of systematic sampling
Not applicable
18.1.5.2.4. Full coverage strata

Not applicable

18.1.5.2.5. Method of determination of the overall sample size

Not applicable

18.1.5.2.6. Method of allocation of the overall sample size
Not applicable
18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable
18.1.6. Module “Animal housing and manure management module”

See sub-categories below.

18.1.6.1. Coverage of agricultural holdings
Census
18.1.6.2. Sampling design

Not applicable

18.1.6.2.1. Name of sampling design
Not applicable
18.1.6.2.2. Stratification criteria
Not applicable
18.1.6.2.3. Use of systematic sampling
Not applicable
18.1.6.2.4. Full coverage strata

Not applicable

18.1.6.2.5. Method of determination of the overall sample size

Not applicable

18.1.6.2.6. Method of allocation of the overall sample size
Not applicable
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable
18.1.12. Software tool used for sample selection

Not applicable

18.1.13. Administrative sources

See sub-categories below.

18.1.13.1. Administrative sources used and the purposes of using them

The information is available on Eurostat's website.

18.1.13.2. Description and quality of the administrative sources

See the attached Excel file in the Annex.



Annexes:
18.1.13.2. Quality of the administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
None
18.1.14. Innovative approaches

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

18.2. Frequency of data collection

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.

18.3. Data collection

See sub-categories below.

18.3.1. Methods of data collection
Use of Internet
18.3.2. Data entry method, if paper questionnaires
Not applicable
18.3.3. Questionnaire

Please find the questionnaire in annex.



Annexes:
18.3.3. Questionnaire
18.4. Data validation

See sub-categories below.

18.4.1. Type of validation checks
Data format checks
Completeness checks
Routing checks
Range checks
Relational checks
Data flagging
Comparisons with previous rounds of the data collection
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
Supervisors
Staff from central department
Other
18.4.3. Tools used for data validation

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).

18.5. Data compilation

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).

18.5.1. Imputation - rate

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

18.5.2. Methods used to derive the extrapolation factor
Not applicable
18.6. Adjustment

Covered under Data compilation.

18.6.1. Seasonal adjustment

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


19. Comment Top

See sub-categories below.

19.1. List of abbreviations

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

19.2. Additional comments

No additional comments.


Related metadata Top


Annexes Top