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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | Statistics Netherlands |
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1.2. Contact organisation unit | Environmental, energy and spatial statistics, team Agriculture and Nature |
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1.5. Contact mail address | Postbus 24500 |
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2.1. Metadata last certified | 24/08/2021 | ||
2.2. Metadata last posted | 24/08/2021 | ||
2.3. Metadata last update | 24/08/2021 |
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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. |
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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. |
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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. |
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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:
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3.5. Statistical unit | |||
See sub-category below. |
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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. |
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3.6. Statistical population | |||
See sub-categories below. |
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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 |
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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. |
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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). |
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3.7. Reference area | |||
See sub-categories below. |
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3.7.1. Geographical area covered | |||
The entire territory of the country. |
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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. |
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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. |
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3.8. Coverage - Time | |||
Farm structure statistics in our country cover the period from 1980 onwards Older (EU) time series are described in the previous quality reports (national methodological reports). |
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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. |
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Two kinds of units are generally used:
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See sub-categories below. |
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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. |
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5.2. Reference period for variables on irrigation and soil management practices | |||
Not applicable for 2020. |
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5.3. Reference day for variables on livestock and animal housing | |||
The reference day 1 April within the reference year 2020. |
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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. |
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5.5. Reference period for variables on labour force | |||
The 12-month period ending on 1 April within the reference year 2020. |
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5.6. Reference period for variables on rural development measures | |||
The three-year period ending on 31 December 2020. |
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5.7. Reference day for all other variables | |||
The reference day 1 April within the reference year 2020. |
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6.1. Institutional Mandate - legal acts and other agreements | |||
See sub-categories below. |
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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). |
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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) |
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6.1.4. Year of entry into force of national legal acts and other agreements | |||
20-11-2003 |
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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. |
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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. |
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7.2. Confidentiality - data treatment | |||
See sub-categories below. |
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7.2.1. Aggregated data | |||
See sub-categories below. |
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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 |
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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) |
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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. 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 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. |
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7.2.2. Microdata | |||
See sub-categories below. |
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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.
Services are: • Customized research, conducted by Statistics Netherlands Statistics Netherlands can carry out research based on the research questions of the applicant. If necessary they can add and link researchers own datasets to statistical data sources available at Statistics Netherlands (including the agricultural census). The results of the study are published on the website of Statistics Netherlands and are thus accessible to everyone. Moreover, most publications appear in print as a research report. This work is carried out for a fixed rate per hour. • Own research using data from Statistics Netherlands Under certain conditions, Statistics Netherlands makes available micro-data for statistical research. To be 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. |
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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. 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. |
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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. |
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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) |
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8.3.1. Use of quality rating system | |||
No | |||
8.3.1.1. Description of the quality rating system | |||
Not applicable |
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The data for the annual agricultural census are disseminated according to a pre-determined release policy, with regular updates within the year. |
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10.1. Dissemination format - News release | |||
See sub-categories below. |
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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) 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). |
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10.2. Dissemination format - Publications | |||
See sub-categories below. |
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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. |
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10.3. Dissemination format - online database | |||
See sub-categories below. |
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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'): English tables (under agricultural census): |
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10.3.2. Accessibility of online database | |||
Yes | |||
10.3.3. Link to online database | |||
10.4. Dissemination format - microdata access | |||
See sub-category below. |
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10.4.1. Accessibility of microdata | |||
Yes | |||
10.5. Dissemination format - other | |||
Not available |
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10.5.1. Metadata - consultations | |||
Not requested. |
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10.6. Documentation on methodology | |||
See sub-categories below. |
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10.6.1. Metadata completeness - rate | |||
Not requested. |
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10.6.2. Availability of national reference metadata | |||
No | |||
10.6.3. Title, publisher, year and link to national reference metadata | |||
Not applicable |
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10.6.4. Availability of national handbook on methodology | |||
No | |||
10.6.5. Title, publisher, year and link to handbook | |||
Not applicable |
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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). |
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10.7. Quality management - documentation | |||
The present methodological report for IFS. |
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11.1. Quality assurance | |||
See sub-categories below. |
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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 |
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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. |
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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 (Plan, Do, Check, Act). The follow up of the findings and recommendations of the peer review and the ISO 9001 audit is constantly monitored. |
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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 |
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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); |
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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'. 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. • livestock, mainly for enforcement of the manure law and emission calculations; |
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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). |
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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. |
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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. |
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12.2.1. User satisfaction survey | |||
No | |||
12.2.2. Year of user satisfaction survey | |||
Not applicable |
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12.2.3. Satisfaction level | |||
Not applicable | |||
12.3. Completeness | |||
Information on low- and zero prevalence variables is available on Eurostat's website. |
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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. |
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13.1. Accuracy - overall | |||
See categories below. |
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13.2. Sampling error | |||
See sub-categories below. |
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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 |
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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. |
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13.2.3. Methodology used to calculate relative standard errors | |||
Not applicable. Core and modules are carried out as a census. |
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13.2.4. Impact of sampling error on data quality | |||
None | |||
13.3. Non-sampling error | |||
See sub-categories below. |
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13.3.1. Coverage error | |||
See sub-categories below. |
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13.3.1.1. Over-coverage - rate | |||
The over-coverage rate is available in the annex. The over-coverage rate is unweighted. Annexes: 13.3.1.1. Over-coverage rate and Unit non-response rate |
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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 |
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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. |
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13.3.1.2. Common units - proportion | |||
Not requested. |
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13.3.1.3. Under-coverage error | |||
See sub-categories below. |
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13.3.1.3.1. Under-coverage rate | |||
Under-coverage is very low (estimated to be less than 1 or 2%). |
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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 |
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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. |
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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. |
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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. |
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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. |
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13.3.1.6. Impact of coverage error on data quality | |||
Low | |||
13.3.2. Measurement error | |||
See sub-categories below. |
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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. |
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13.3.2.2. Causes of measurement errors | |||
Complexity of variables Unclear questions Respondents’ inability to provide accurate answers |
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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 |
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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. |
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13.3.3. Non response error | |||
See sub-categories below. |
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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. |
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13.3.3.1.1. Reasons for unit non-response | |||
Refusal to participate Other |
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13.3.3.1.2. Actions to minimise or address unit non-response | |||
Reminders Legal actions Imputation Other |
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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. |
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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. 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. |
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13.3.3.2.1. Variables with the highest item non-response rate | |||
Not applicable |
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13.3.3.2.2. Reasons for item non-response | |||
Skip of due question Other |
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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. |
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13.3.4. Processing error | |||
See sub-categories below. |
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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. |
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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. |
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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. |
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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 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 livestock numbers are derived from the corresponding I&R registers, using established algorithms. |
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14.1. Timeliness | |||
See sub-categories below. |
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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. |
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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. |
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14.2. Punctuality | |||
See sub-categories below. |
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14.2.1. Punctuality - delivery and publication | |||
See sub-categories below. |
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14.2.1.1. Punctuality - delivery | |||
Not requested. |
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14.2.1.2. Punctuality - publication | |||
The actual publication date was in accordance with the target date for publication. |
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15.1. Comparability - geographical | |||
See sub-categories below. |
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15.1.1. Asymmetry for mirror flow statistics - coefficient | |||
Not applicable, because there are no mirror flows in Integrated Farm Statistics. |
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15.1.2. Definition of agricultural holding | |||
See sub-categories below. |
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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. |
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15.1.2.2. Reasons for deviations | |||
Not applicable |
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15.1.3. Thresholds of agricultural holdings | |||
See sub-categories below. |
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15.1.3.1. Proofs that the EU coverage requirements are met | |||
The threshold in the national agricultural census is 3000 euro SO-NL. 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 |
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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. |
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15.1.3.3. Reasons for differences | |||
Not applicable |
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15.1.4. Definitions and classifications of variables | |||
See sub-categories below. |
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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. |
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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. Annexes: 15.1.4.1.1. AWU |
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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. |
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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. |
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15.1.4.1.4. Livestock coefficients | |||
No use of different LSU coefficients. |
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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). |
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15.1.4.2. Reasons for deviations | |||
See 15.1.4.1. |
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15.1.5. Reference periods/days | |||
See sub-categories below. |
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15.1.5.1. Deviations from Regulation (EU) 2018/1091 | |||
No deviations. |
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15.1.5.2. Reasons for deviations | |||
Not applicable |
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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 |
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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 |
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15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections | |||
Not applicable |
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15.1.7. National standards and rules for certification of organic products | |||
See sub-categories below. |
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15.1.7.1. Deviations from Council Regulation (EC) No 834/2007 | |||
No deviations. |
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15.1.7.2. Reasons for deviations | |||
Not applicable |
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15.1.8. Differences in methods across regions within the country | |||
Not applicable |
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15.2. Comparability - over time | |||
See sub-categories below. |
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15.2.1. Length of comparable time series | |||
20 years |
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15.2.2. Definition of agricultural holding | |||
See sub-categories below. |
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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. |
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15.2.3. Thresholds of agricultural holdings | |||
See sub-categories below. |
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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 |
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15.2.4. Geographical coverage | |||
See sub-categories below. |
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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 |
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15.2.5. Definitions and classifications of variables | |||
See sub-categories below. |
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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. 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. |
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15.2.6. Reference periods/days | |||
See sub-categories below. |
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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 |
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15.2.7. Common land | |||
See sub-categories below. |
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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 |
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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. Regarding A2220 (Heifers, 1 to less than 2 years old) and A4210K (Goats, breeding females): 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. |
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15.2.9. Maintain of statistical identifiers over time | |||
Yes | |||
15.3. Coherence - cross domain | |||
See sub-categories below. |
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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. |
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15.3.2. Coherence - National Accounts | |||
Not applicable, because Integrated Farm Statistics have no relevance for national accounts. |
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15.3.3. Coherence at micro level with data collections in other domains in agriculture | |||
See sub-categories below. |
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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. |
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15.3.4. Coherence at macro level with data collections in other domains in agriculture | |||
See sub-categories below. |
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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. |
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15.4. Coherence - internal | |||
The data are internally consistent. This is ensured by the application of a wide range of validation rules. |
|
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See sub-categories below. |
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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. |
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16.2. Efficiency gains since the last data transmission to Eurostat | |||
Further automation Increased use of administrative data Other |
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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. |
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16.3. Average duration of farm interview (in minutes) | |||
See sub-categories below. |
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16.3.1. Core | |||
Not available |
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16.3.2. Module ‘Labour force and other gainful activities‘ | |||
Not available |
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16.3.3. Module ‘Rural development’ | |||
Not relevant |
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16.3.4. Module ‘Animal housing and manure management’ | |||
Not available |
|
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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.). |
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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. |
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17.2.1. Data revision - average size | |||
Not requested. |
|
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Annexes: 18.Timetable_statistical_process |
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18.1. Source data | |||
See sub-categories below. |
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18.1.1. Population frame | |||
See sub-categories below. |
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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 |
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18.1.1.3. Update frequency | |||
Continuous | |||
18.1.2. Core data collection on the main frame | |||
See sub-categories below. |
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18.1.2.1. Coverage of agricultural holdings | |||
Census | |||
18.1.2.2. Sampling design | |||
Not applicable. |
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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. |
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18.1.2.2.5. Method of determination of the overall sample size | |||
Not applicable. |
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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. |
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18.1.3.1. Coverage of agricultural holdings | |||
Not applicable | |||
18.1.3.2. Sampling design | |||
Not applicable. |
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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. |
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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 |
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18.1.13. Administrative sources | |||
See sub-categories below. |
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18.1.13.1. Administrative sources used and the purposes of using them | |||
The information is available on Eurostat's website. |
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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 |
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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. |
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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. |
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18.3. Data collection | |||
See sub-categories below. |
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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 |
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18.4. Data validation | |||
See sub-categories below. |
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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 |
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18.4.2. Staff involved in data validation | |||
Supervisors Staff from central department Other |
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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). |
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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). |
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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. |
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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. |
|
|||
See sub-categories below. |
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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 UAA – Utilised agricultural area WG – Working Group |
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19.2. Additional comments | |||
No additional comments. |
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