1.1. Contact organisation
Central Statistics Office
1.2. Contact organisation unit
Agriculture Surveys Section
1.3. Contact name
Restricted from publication1.4. Contact person function
Restricted from publication1.5. Contact mail address
Central Statistics Office, Skehard Road, Cork, Ireland
1.6. Contact email address
Restricted from publication1.7. Contact phone number
Restricted from publication1.8. Contact fax number
Restricted from publication2.1. Metadata last certified
3 June 20242.2. Metadata last posted
3 June 20242.3. Metadata last update
3 June 20243.1. 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
No3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
No3.6.2. Population covered by the data sent to Eurostat for the modules “Labour force and other gainful activities”, “Rural development” and “Machinery and equipment”
The same population of agricultural holdings defined in item 3.6.1 i.e. above at least one of the thresholds set in Regulation (EU) 2018/1091.
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 subset of the population of agricultural holdings defined in item 3.6.2 with at least one of the following: bovine animals, pigs, sheep, goats, poultry.
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
Restricted from publication3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
Restricted from publication3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
Restricted from publication3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Restricted from publication3.7. Reference area
See sub-categories below.
3.7.1. Geographical area covered
The entire territory of the country.
3.7.2. Inclusion of special territories
Not applicable.
3.7.3. Criteria used to establish the geographical location of the holding
The most important parcel by physical size3.7.4. Additional information reference area
Not applicable.
3.8. Coverage - Time
A Farm Structure Survey (FSS) is carried out between Censuses to measure changes in Farm Structure. The first Census of Agriculture (COA) in Ireland was carried out in 1847, and annually thereafter until 1953. Between 1960 and 1980 Censuses were carried out at 5 yearly intervals. From 1980 Censuses were carried out at 10 yearly intervals.
There is an available time series from the 1850s to the present day for the number of holdings, livestock totals and utilised agricultural area.
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.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land refers to the reference year 2020, as land variables are obtained from the IACS system, the 12-month reference period is January 1 2020 to December 31 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
The 12-month reference for total irrigable area is January 1 2020 to December 31 2020.
5.3. Reference day for variables on livestock and animal housing
The reference day of 1 June within the reference year 2020.
5.4. Reference period for variables on manure management
The 12-month period ending on 31 December 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 31 December 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 of 1 June within the reference year 2020.
6.1. Institutional Mandate - legal acts and other agreements
See sub-categories below.
6.1.1. National legal acts and other agreements
Legal act6.1.2. Name of national legal acts and other agreements
The statistical activities for the CSO are governed by the Statistics Act, 1993. This act provides the legislative framework for the CSO. It sets put the right of the Office to conduct statistical inquiries (See Part III – Collection of Information of the Act).
Part III (Section 25) of the Statistics Act specifies that a ministerial order can be put in place to prescribe persons and undertakings to provide information under the Act. Such an order was deemed necessary for the Census of Agriculture and was published before data collection commenced. The Order is named the Statistics (Census of Agriculture) Order 2020.
Part II (Section 20, 21 and 22) of the Statistics Act specifies the responsibilities of the CSO staff. It should be noted that as the COA is a Paper Data Collection and Computer Assisted Web Interviewing (CAWI) Census, enumerators do not directly visit farms/respondents.
6.1.3. Link to national legal acts and other agreements
https://www.irishstatutebook.ie/eli/1993/act/21/enacted/en/html
https://www.irishstatutebook.ie/eli/2020/si/281/made/en/print
6.1.4. Year of entry into force of national legal acts and other agreements
The Statistics Act entered into force in 1993 and the Statistics (Census of Agriculture) Order entered into force in 2020.
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
Part IV of the Statistics Act, 1993, mentioned above grants the CSO right of access to records of public authorities for statistical purposes (with a number of exceptions). Specifically under the Act, the CSO may request any public authority to provide data that they hold as a source of statistical information and, where appropriate and practical, developing its recording methods and systems for statistical purposes. This underpins co-operation with the Department of Agriculture, Food and the Marine (DAFM) on the subject of its farm registers. (See Part IV – Use of Records of Public Authorities for Statistical Purposes of the Act above.)
DAFM and the CSO have strengthened their relationship over the previous number of years and a Memorandum of Understanding underpins the data sharing agreements.
7.1. Confidentiality - policy
All information returned on COA questionnaires is treated as strictly confidential and is used for statistical purposes only. This is guaranteed by both Irish and EU law.
Section 33 of the Statistics Act 1993 states:
33.(1) No information obtained in any way under this Act or the repealed enactments which can be related to an identifiable person or undertaking shall, except with the written consent of that person or undertaking or the personal representative or next-of-kin of a deceased person, be disseminated, shown or communicated to any person or body except as follows:
( a ) for the purposes of a prosecution for an offence under this Act;
( b ) to officers of statistics in the course of their duties under this Act;
( c ) for the purposes of recording such information solely for the use of the Office in such form and manner as is provided for by a contract in writing made by the Director General which protects its confidentiality to his satisfaction.
The Act guarantees the confidentiality of all data provided, expressly prohibiting the disclosure of information which can be related to any identifiable person or enterprise. (See Part V - Protection of Information of the Act above). It specifies the offences and penalties occurred for breaching this confidentiality. (See Part VI - Offences, Penalties and Evidence of the Act above).
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)Dominance rule (The n largest contributions make up for more than k% of the cell total)
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)
7.2.1.3. Description of rules and methods
In the national release, a category is primary confidential if any one of the following conditions applies:
- there are five or less units,
- one unit accounts for more than 80% of the total (dominance rule 1),
- two units account for more than 90% of the total (dominance rule 2).
A category is secondary confidential if publishing that category indirectly reveals information about a confidential category.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
Not applicable7.2.2.2. Methods of perturbation
None7.2.2.3. Description of methodology
Not applicable.
8.1. Release calendar
The release calendar for all statistical publications in the CSO is agreed at the beginning of each year. In 2021, the agriculture team agreed to release preliminary results from the Census in December 2021, and in 2022, the team agreed to release final results in May 2022.
8.2. Release calendar access
The release calendar can be publicly accessed on the CSO website using the following link.
8.3. Release policy - user access
The CSO’s standard practice is that statistics are released to all users at the same time unless they have pre-release access. Pre-release access is limited, controlled, and publicised. The CSO standard is the release of results at 11:00am, with no pre-release access. A policy on pre-release access is in place which gives effect to the principle of Objectivity and Impartiality as set out in the European Statistics Code of Practice (ESCOP).
For the IFS preliminary and final releases, the CSO standard release of results at 11:00am on the date entered into the release calendar was followed. Named individuals also had the opportunity to be granted pre-release access to advance notification of the release at 10:00am by following the procedure outlined in the pre-release access policy.
8.3.1. Use of quality rating system
No8.3.1.1. Description of the quality rating system
Not applicable.
Statistics on the structure of farming in Ireland are generally published every 3/4 years depending on the Farm Structure Survey (FSS) or IFS planned schedule. The FSS was most recently carried out in 2016 and IFS surveys will take place in 2023 and 2026.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
Yes10.1.2. Link to news releases
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
No10.2.2. Production of on-line publications
Yes, in English also10.2.3. Title, publisher, year and link
Census of Agriculture 2020 - Preliminary Results
CSO statistical publication, 09 December 2021, 11am
On-line ISSN: 2009-5716
https://www.cso.ie/en/releasesandpublications/ep/p-coa/censusofagriculture2020-preliminaryresults/
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
Not available.
10.3.2. Accessibility of online database
Yes10.3.3. Link to online database
Census of Agriculture statistics for 2020 can be viewed using the CSOs online database (PXSTAT) the relevant tables are AVA24 through to AVA40 at the link below.
https://data.cso.ie/product/CAPR
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
No10.5. 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
No10.6.3. Title, publisher, year and link to national reference metadata
Not applicable - private documentation.
10.6.4. Availability of national handbook on methodology
No10.6.5. Title, publisher, year and link to handbook
Not applicable - private documentation.
10.6.6. Availability of national methodological papers
No10.6.7. Title, publisher, year and link to methodological papers
Not applicable - private documentation.
10.7. Quality management - documentation
Not available.
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Training coursesUse of best practices
Quality guidelines
Self-assessment
11.1.3. Description of the quality management system and procedures
Training courses – the CSO has a dedicated Statistical Training Unit in place to ensure that statisticians are supported when performing their work. Each particular statistician role has an essential statistical requirements and an office skills register per statistician is used to determine a statisticians training needs. Training needs are determined with a gap analysis and training is supplied early in the term of the statistician.
Use of best practices – the CSO has a dedicated Methodology team who assist with the design of procedures to be implemented throughout Official Statistics.
Quality guidelines – the CSO began implementation of a Quality Management Framework in 2016 and a new quality strategy 2020-2023 has recently been published. Statistical procedures within the office are required to adhere to the guidelines with the Framework and policy.
Self-assessment – there is an annual requirement in the CSO to complete a self-assessment quality questionnaire on all statistical products that statisticians are responsible for.
11.1.4. Improvements in quality procedures
The CSO Quality Strategy 2020-2023 has led to a number of improvements in quality procedures. A new metadata management application (Colectica) is being utilised across the office which has modernised and standardised the processes around questionnaire design, variable specifications, and metadata management. This will be very valuable over the remainder of the decade for IFS data collections.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
The main users of the data are individuals from the DAFM, the Irish FADN liaison agency, environmental agencies, agricultural press (print and online), farming organisations and the public.
These groups were consulted during planning and a small number of additional variables (not in Regulation (EU) No. 2018/1091) were collected for national purposes. The need for these variables was identified through a consultation process with the main stakeholders prior to the survey design stage. Specifically these variables related to:
Sheep: A more detailed breakdown of sheep required to continue time series from past data collections.
Poultry: Further sub-division of IFS characteristics to continue past time series.
Equidae: Equidae in Ireland are generally part of the horse racing industry but are kept on in-scope IFS farms.
Farm Succession: Information on farm succession planned for Ireland was requested, as Ireland has an aging farming population, this information will feed into agricultural policy beyond CAP.
Manure Management: There was interest from the users for manure application methods on tillage farms when manure was being spread was also an important user need.
Information was also collected and collated for out-of-scope IFS farms, these farms make little contribution to the total Utilised Agricultural Area and total Livestock Units but receive farm supports under CAP and cover approximately 3% of holdings.
12.1.1. Main groups of variables collected only for national purposes
Sheep: Rams, ewes (under and over 2 years) and other sheep (under and over 1 year).
Poultry: Sub-division of both broilers and turkeys into breeding birds and table birds.
Equidae: Sub-division of Equidae into thoroughbred, other horses and mules, jennets and asses.
Farm Succession: Farm holders were asked if a succession plan was in place and if the person to succeed was a family member or not and their gender.
Manure Management: Application methods were split into grassland and tillage methods and a Spring, Summer and Autumn breakdown was determined.
12.1.2. Unmet user needs
Some users requested Labour and Manure Management statistics as a more detailed geographical level than NUTS3. This is not possible as this information was collected via sample surveys and designed to meet the precision requirements as set out in Annex V of Regulation No. 2018/1091.
12.1.3. Plans for satisfying unmet user needs
It may be possible to meet some of the regional need for the Agriculture Labour Force by matching across non-agricultural administrative sources. This will be explored in the lead up to and during processing of IFS 2023.
12.2. Relevance - User Satisfaction
It may be possible to meet some of the regional need for the Agriculture Labour Force by matching across non-agricultural administrative sources. This will be explored in the lead up to and during processing of IFS 2023.
12.2.1. User satisfaction survey
No12.2.2. Year of user satisfaction survey
Not applicable.
12.2.3. Satisfaction level
Not applicable12.3. Completeness
Information on 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.
13.1. 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
Of the 65 eligible cases, five were non-compliant (7.69%).
Some land variables in the LAFO module had large RSEs, two eligible cases, “Cereals” and “Plants harvested green from arable land” in IE06 had RSEs over 5%. The "cereals / IE06" pair has an RSE of 6.33% and the "plants harvested green / IE06" pair has an RSE of 5.07% so a larger sample size in future data collections for the LAFO module should lower these RSEs.
In the IE06 region for the LAFO module, there were two RSEs for two eligible cases the “Dairy Cows” LSU and “Sheep and Goats” LSU variables. These RSEs were 5.20% and 5.68%, dairy farming and sheep farming are not predominant in this region and a larger sample size for these modules in future data collections should be adequate to lower the RSEs.
In the IE06 region for the AHMM module, these was one non-compliant RSE (8.7%), for the "Sheep and Goats" eligible case. As stated above sheep farming is not predominant in this region and a larger sample size will be required for repeat AHMM modules in future IFS data collections.
Finally, the IE06 region has the fewest farms of Irelands NUTS2 regions but is also a predominant region for arable land and most of the common Irish livestock classifications will be eligible cases in this region. Future sampling designs will incorporate this information and ensure that IE06 eligible cases are compliant.
13.2.3. Methodology used to calculate relative standard errors
see annex
Annexes:
13.2.3 RSE Method IE
13.2.4. Impact of sampling error on data quality
None13.3. Non-sampling error
See sub-categories below.
13.3.1. Coverage error
See sub-categories below.
13.3.1.1. Over-coverage - rate
The over-coverage rate is available 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 periodCeased activities
Merged to another unit
13.3.1.1.2. Actions to minimize the over-coverage error
Other13.3.1.1.3. Additional information over-coverage error
Over Coverage described in 13.3.1.1 is based on the dataset of farm holdings that are above threshold as per ANNEX II of Regulation (EU) No. 2018/1091. There are approximately 5,000 active below threshold farm holdings in Ireland that are included in the national publication of results. Remaining over coverage farm holdings are ones that have ceased activity or have merged with other units.
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 errors are likely to be very low for Irish farm holdings. The Department of Agriculture manages a number of administrative databases and data sharing agreements ensure that the CSO can obtain and use these databases to ensure minimal under-coverage. For Irish farm holders to receive CAP payments, they must have a registered herd number with the Department.
13.3.1.3.2. Types of holdings belonging to the population of the core but not included in the frame (main frame and if applicable frame extension)
New births13.3.1.3.3. Actions to minimise the under-coverage error
All necessary steps are taken to ensure full coverage of the population. The Agricultural Register, finalised after FSS 2016, was updated further annually and in April 2020 (prior to the Census) to add 4 687 new births which had been identified as newly-active holdings on the Department of Agriculture’s administrative databases. Administrative databases include, IACS, Bovine, Ovine, Poultry and Organic farming Registers. The only holdings that could have been excluded were those farming but not registered on the databases referenced. The likelihood of a new farm not falling into these databases was considered low.
13.3.1.3.4. Additional information under-coverage error
Not available
13.3.1.4. Misclassification error
No13.3.1.4.1. Actions to minimise the misclassification error
Modular samples were taken towards the end of 2020 from the main frame of eligible holdings. For this reason, classifications used to form strata were close to final. Allocation of holdings to strata did not change after data collection of the LAFO and AHMM modular data for the vast majority of holdings.
13.3.1.5. Contact error
No13.3.1.5.1. Actions to minimise the contact error
The contact data was provided by the Agriculture Register. In some cases, the holder could not be reached at that address and the questionnaire was returned unopened. This occurred in 1,328 cases, many of these cases were followed up by telephone and it was found that some of the holdings had merged with another of that the holding was inactive.
13.3.1.6. Impact of coverage error on data quality
None13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
Temporary (G1000T) and Permanent Grasslands (J1000T & J2000T).
Areas declared for the above characteristics on IACS differed substantially from the returns on the Census instrument. The breakdown of grasslands obtained from respondents on the instrument was assumed valid, particularly given the geographical location of the Rough grazing returns.
13.3.2.2. Causes of measurement errors
Other13.3.2.3. Actions to minimise the measurement error
Explanatory notes or handbooks for enumerators or respondents13.3.2.4. Impact of measurement error on data quality
None13.3.2.5. Additional information measurement error
The measurement errors in grassland, were found in the IACS declarations and were corrected for the Census and are considered correct in the dataset sent to Eurostat.
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
Failure to make contact with the unit13.3.3.1.2. Actions to minimise or address unit non-response
RemindersImputation
Weighting
Other
13.3.3.1.3. Unit non-response analysis
Administrative data within the reference year of 2020 was available for close to 100% of the unit non-responders. The nature of the core data collected using the Census instrument and the available auxiliary information meant that accurate deductive imputation could be performed. Unit deductive imputation was performed for the demographic characteristics of the holder and manager of the holding, the legal personality of the holding, the location of the holding, presence of and heads of livestock (sheep, goats and poultry).
13.3.3.2. Item non-response - rate
Item non-response rate on the paper survey instrument could be detected for certain characteristics that should be on most if not all holdings – characteristics of the holder or manager, grassland. It was more difficult to determine if there was item non-response for livestock characteristics but administrative data could be used to deduce if responding units were active sheep or poultry holdings. If item non-response was found, it was controlled for and corrected with edits and imputation.
13.3.3.2.1. Variables with the highest item non-response rate
There was more item non-response on the paper questionnaire than the electronic questionnaire. Variables such as the year the manager started (Y_FARM_MAN) and the level of training of the manager (TNG_MAN) were the characteristics with the highest item non-response. Processing staff could edit these during processing by contacting the holder or by using previous returns if available.
13.3.3.2.2. Reasons for item non-response
Skip of due question13.3.3.2.3. Actions to minimise or address item non-response
RemindersImputation
Other
13.3.3.3. Impact of non-response error on data quality
None13.3.3.4. Additional information non-response error
Adjusting non-response was handled at two stages during the process, staff would edit returned questionnaires if it was possible to determine with follow-up or previous information. The second stage to handle non-response was with imputation - for many characteristics it was possible to use administrative data as a source for deductive imputation. If it was not possible to deduce a value, donor imputation (both hot deck and cold deck) was implemented.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
Imputation methodsData processing
13.3.4.2. Imputation methods
Deductive imputationCold-deck imputation
Random hot deck imputation
13.3.4.3. Actions to correct or minimise processing errors
Due to the sheer number of paper questionnaires to be processed, it can be assumed that some errors took place during processing. To minimise these errors, different team members worked on the same questionnaires at each stage of the process i.e no team member assess the same form at different stages of processing.
The deductive imputation methods implemented were considered to be an excellent solution to missing data and were always the first method (before probabilistic methods) to be implemented where appropriate.
13.3.4.4. Tools and staff authorised to make corrections
Processing staff used optical scanning to capture each return electronically, this software was configured to flag errors or erroneous data at scanning. Staff then used the CSOs Data Management System (DMS) software to correct data. Ineligible digits and data are highlighted and corrected on screen by referring to previous returns or by deduction. The data then enters the edit phase where data is passed through a range of pre-programmed edit checks. Here, arithmetic checks, range checks and consistency checks (with previous returns) are carried out and the data is examined. These edits are processed through the DMS before more edits are carried out in SAS.
The majority of the imputation was performed in SAS with imputation of the a small proportion of INSPIRE grid cell codes performed using SAS in parallel with R-Studio.
13.3.4.5. Impact of processing error on data quality
None13.3.4.6. Additional information processing error
Not available.
13.3.5. Model assumption error
Not applicable
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
Preliminary COA results were published in December 2021, this was 11 months after the end of the reference year.
14.1.2. Time lag - final result
Final publication of the results is planned for May 2021 which will be a lag of 17 months after the end of the reference year.
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 preliminary publication of results was delivered on schedule, there was no difference between the actual and planned dates.
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
There was no deviation in the definition of an agricultural holding as defined in Regulation (EU) 2018/1091.
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 data sent to Eurostat is for units with at least one characteristic above the thresholds stated in Annex II of Regulation (EU) 2018/1091, data is also available for 4,845 under threshold active farms. The table below summarises the UAA and LSU breakdown for the above threshold farm holdings.
|
|
Total |
Covered by thresholds |
Attained coverage |
Minimum requested coverage |
| 1 |
2 |
3 = 2*100/1 |
4 |
|
| UAA (exc KG) |
4,931,862 |
4,920,270 |
99.8 |
98.00 |
| LSU |
6,321,090 |
6,319,365 |
99.9 |
98.00 |
There is close to 100% coverage provided by the farm holdings sent to Eurostat for UAA and LSUs on Irish farm holdings.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
Approximately 3.6% of Irish farm holdings are below the Regulatory thresholds. Outside of the thresholds, any farm holding registered with a herd number in receipt of farm payments is included in national publications. Livestock and Utilised Agriculture Area on these smaller farm holdings is also included in regular data transmissions to Eurostat throughout the year.
15.1.3.3. Reasons for differences
Data collection in Ireland is primarily carried out using agricultural administrative data so it is possible to capture information on the above and below threshold farmers. Information on these small farms is important, they may not contribute a large number of LSUs or farm a large portion of land but these farm holdings are in receipt of farm payments and national users are interested.
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
Definitions and classifications of the characteristics in the IFS 2020 data sent to Eurostat match those in Regulation (EU) 2018/1091, Commission Implementing Regulation (EU) 2018/1874 and the IFS 2020 manual.
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
The Livestock unit coefficient definition matches the regulatory definition for Ireland and the definition contained in Regulation (EU) 2018/1091.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
Equidae
15.1.4.2. Reasons for deviations
Not applicable
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
The reference period/days match those set in Regulation (EU) 2018/1091.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land exists15.1.6.1. Collection of common land data
Yes15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Common land is included in separate records representing virtual entities without managers.15.1.6.4. Source of collected data on common land
Administrative sources15.1.6.5. Description of methods to record data on common land
Irish common land is collected at the county (local government areas) geographical level and recorded per county in the data sent to Eurostat. Land use administrative data from the Department of Agriculture is transmitted separately with and without common land thus alleviating the risk of double counts. All survey instruments sent to holdings also specify that common land should not be included.
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
We do not experience problems to collect data on common land.
15.1.7. National standards and rules for certification of organic products
See sub-categories below.
15.1.7.1. Deviations from Council Regulation (EC) No 834/2007
There are no deviations in the national standards and rules for certification of organic products from Council Regulation (EC) No 834/2007.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
There are no differences in the methods used across regions within the country.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
There is a comparable farm structural time series available nationally for the previous 40 years in Ireland with comparable livestock, land use and holding number time series back to the 1850s.
The current data sent to Eurostat differs slightly in format from the 2016 FSS data as thresholds were not applied to the 2016 data. This only results in a slight difference in farm numbers (as discussed in section 15.1.3.1) as the 4,785 farm holdings below threshold farms are now not included. Farm structure based on the above threshold farm holdings only is not considered as a considerable break in the time series as land utilisation, livestock and farm labour are comparable between 2016 and 2020.
15.2.2. Definition of agricultural holding
See sub-categories below.
15.2.2.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.2.2. Description of changes
Regulation (EU) 2018/1091 newly considers agricultural holdings with only fur animals. However our country does not raise 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 some changes but not enough to warrant the designation of a break in series15.2.3.2. Description of changes
The only change that applying the thresholds is to remove the smaller farm holdings from the Eurostat data, this has impacted the number of Irish farm holdings but has had no impact on the LSUs, UAA and farm labour statistics. The farms below threshold account for 0.24% of national UAA and 0.03% of national LSUs. Therefore, we do not consider the application of thresholds to cause a break in time series.
15.2.4. Geographical coverage
See sub-categories below.
15.2.4.1. Change in the geographical coverage since the last data transmission to Eurostat
There have been no changes15.2.4.2. Description of changes
Not applicable.
15.2.5. Definitions and classifications of variables
See sub-categories below.
15.2.5.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series15.2.5.2. 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.
15.2.6. Reference periods/days
See sub-categories below.
15.2.6.1. Changes since the last data transmission to Eurostat
There have been some changes but not enough to warrant the designation of a break in series15.2.6.2. Description of changes
The 12-month reference period for land variables and labour force variables has changed since the 2016 FSS. The land variable reference has changed as planned to January 2020 to December 2020 given the reliance on IACS administrative sources.
LAFO reference period was adapted due to the pandemic – data was collected in December 2020, so it was logical to determine from farm holders labour in the previous year - a reference period of January 2020 to December 2020.
15.2.7. Common land
See sub-categories below.
15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no changes15.2.7.2. Description of changes
Not applicable.
15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat
The information is available here: (Eurostat to insert the link after the validation of the data file).
15.2.9. Maintain of statistical identifiers over time
No15.3. Coherence - cross domain
See sub-categories below.
15.3.1. Coherence - sub annual and annual statistics
Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.
15.3.2. Coherence - National Accounts
Not applicable, because Integrated Farm Statistics have no relevance for national accounts.
15.3.3. Coherence at micro level with data collections in other domains in agriculture
See sub-categories below.
15.3.3.1. Analysis of coherence at micro level
Yes15.3.3.2. Results of analysis at micro level
In an IFS year, the annual programme for statistics in Ireland is built around the IFS data collection so micro level analysis is built into the process for both preparing the IFS data and creating “Annual Crop Statistics” and “Animal Production Statistics” aggregates for Eurostat.
The Irish statistics are based on a combination of administrative data and survey/census data and our analysis has shown that there are some classification errors (see 13.3.2.1) for the temporary and permanent grasslands breakdown from the administrative data.
The “Animal Production Statistics” sheep data that is transmitted to Eurostat is for a reference date in December whereas the IFS sheep data is for a reference date in June so there is no directly comparable source for sheep data. Nationally, there is an annual release of sheep data and the IFS sheep are coherent with this data.
15.3.4. Coherence at macro level with data collections in other domains in agriculture
See sub-categories below.
15.3.4.1. Analysis of coherence at macro level
Yes15.3.4.2. Results of analysis at macro level
15.4. Coherence - internal
The data are internally consistent. This is ensured by the application of a wide range of validation rules.
See sub-categories below.
16.1. Coordination of data collections in agricultural statistics
While the IFS data is not collected in another CSO survey, the annual June agriculture survey is replaced by the IFS in IFS years.
The utilisation of administrative data – Bovine Register, IACS, Organic Register and Rural Development Measures eliminates the need for farmers to provide this data. The combination of this data and the fact that the Labour data was collected as a sample survey meant that the survey instrument for Core IFS data collection was halved in size.
The CSO is focused on continuously reducing the response burden on farmers. The final section of the IFS questionnaires, and indeed every agricultural survey, asks the respondent to indicate, in minutes, how long it took to complete the form. This allows CSO to measure the change in response burden from year to year.
16.2. Efficiency gains since the last data transmission to Eurostat
On-line surveysIncreased use of administrative data
16.2.1. Additional information efficiency gains
Not applicable.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Mean time in minutes to complete the Core questionnaire (online & paper together) was 16.70 minutes and the median was 15 minutes.
16.3.2. Module ‘Labour force and other gainful activities‘
Mean time in minutes to complete the Labour Force questionnaire (paper only) was 16.02 minutes and the median was 10 minutes.
16.3.3. Module ‘Rural development’
Not relevant.
16.3.4. Module ‘Animal housing and manure management’
Mean time in minutes to complete the AHMM questionnaire (paper only) was 20.48 minutes and the median was 15 minutes.
16.3.5. Module ‘Irrigation’
Restricted from publication16.3.6. Module ‘Soil management practices’
Restricted from publication16.3.7. Module ‘Machinery and equipment’
Restricted from publication16.3.8. Module ‘Orchard’
Restricted from publication16.3.9. Module ‘Vineyard’
Restricted from publication17.1. Data revision - policy
The revision policy for the CSO can be found in the following link.
The policy relates to revisions on both online publications and the PxStat (CSOs online database).
The policy considers a scheduled revision of the form preliminary to final as a “Planned Routine revision”. When the revisions are made the new data will be labelled with a code of “2” indicating a routine revision.
The policy considers an unplanned revision to correct a mistake as an “Unplanned revision”. When this type of revision is made, the new data will be labelled with a code of “4” indicating an unplanned revision. An explanatory note stating the reason for the revision and the date the revision took place must also accompany the data.
The policy considers conceptual or methodological changes that cause changes in data values requiring revision of historical data, or a break in series as a “Planned Major revision”. When this type of revision is made, the new data will be labelled with a code of “3” indicating a major revision. An explanatory note stating the reason for the revision and the date the revision took place must also accompany the data.
Data prior to and post revision must be stored in a secure location so that it can be easily found, referenced, and analysed as appropriate.
17.2. Data revision - practice
There are no planned revisions for the 2020 IFS data in Ireland. If any unplanned revisions arise, the policy mentioned in 17.1 will be followed.
17.2.1. Data revision - average size
Not requested.
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 frame18.1.1.2. Name of frame
The frame is housed in the CSOs Data Management System and is named the “Agriculture Register”.
18.1.1.3. Update frequency
Annual18.1.2. Core data collection on the main frame
See sub-categories below.
18.1.2.1. Coverage of agricultural holdings
Census18.1.2.2. Sampling design
Not applicable for 2020.
18.1.2.2.1. Name of sampling design
Not applicable18.1.2.2.2. Stratification criteria
Not applicable18.1.2.2.3. Use of systematic sampling
Not applicable18.1.2.2.4. Full coverage strata
Not applicable for 2020.
18.1.2.2.5. Method of determination of the overall sample size
Not applicable for 2020.
18.1.2.2.6. Method of allocation of the overall sample size
Not applicable18.1.3. Core data collection on the frame extension
See sub-categories below.
18.1.3.1. Coverage of agricultural holdings
Not applicable18.1.3.2. Sampling design
Not applicable.
18.1.3.2.1. Name of sampling design
Not applicable18.1.3.2.2. Stratification criteria
Not applicable18.1.3.2.3. Use of systematic sampling
Not applicable18.1.3.2.4. Full coverage strata
Not applicable
18.1.3.2.5. Method of determination of the overall sample size
Not applicable.
18.1.3.2.6. Method of allocation of the overall sample size
None18.1.4. Module “Labour force and other gainful activities”
See sub-categories below.
18.1.4.1. Coverage of agricultural holdings
Sample18.1.4.2. Sampling design
A one-stage stratified sampling design was implemented for the “Labour and other gainful activities” module. Irish NUTS 3 regions were incorporated into the sampling design as well as the strata mentioned below in 18.1.4.2.2.
18.1.4.2.1. Name of sampling design
Stratified one-stage random sampling18.1.4.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
There were no full coverage strata included in the sampling design for the Labour force and other gainful activities module.
18.1.4.2.5. Method of determination of the overall sample size
The sample size was designed and calculated at NUTS 2 to meet the precision requirements set out in Annex V of Regulation (EU) 2018/1091, that is:
The RSE was required to be < 5% for variables in the precision table where 7.5% or more of the UAA in the region or 7.5% or more of the livestock units in the region and 5% or more of the variable in the country.
18.1.4.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable18.1.5. Module “Rural development”
See sub-categories below.
18.1.5.1. Coverage of agricultural holdings
Census18.1.5.2. Sampling design
Not applicable.
18.1.5.2.1. Name of sampling design
Not applicable18.1.5.2.2. Stratification criteria
Not applicable18.1.5.2.3. Use of systematic sampling
Not applicable18.1.5.2.4. Full coverage strata
Not applicable.
18.1.5.2.5. Method of determination of the overall sample size
Not applicable.
18.1.5.2.6. Method of allocation of the overall sample size
Not applicable18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.6. Module “Animal housing and manure management module”
See sub-categories below.
18.1.6.1. Coverage of agricultural holdings
Sample18.1.6.2. Sampling design
A one-stage stratified sampling design was implemented for the “Animal Housing and Manure Management” module. Irish NUTS 3 regions were incorporated into the sampling design as well as the strata mentioned below in 18.1.6.2.2.
18.1.6.2.1. Name of sampling design
Stratified one-stage random sampling18.1.6.2.2. Stratification criteria
Unit sizeUnit location
Unit specialization
18.1.6.2.3. Use of systematic sampling
No18.1.6.2.4. Full coverage strata
Intensive pig and poultry enterprises were selected as full coverage strata.
18.1.6.2.5. Method of determination of the overall sample size
The sample size was designed and calculated at NUTS 2 to meet the precision requirements set out in Annex V of Regulation (EU) 2018/1091, that is:
The RSE was required to be < 5% for variables in the precision table where 7.5% or more of the UAA in the region or 7.5% or more of the livestock units in the region and 5% or more of the variable in the country.
18.1.6.2.6. Method of allocation of the overall sample size
Proportional allocation18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.7. Module ‘Irrigation’
Restricted from publication18.1.7.1. Coverage of agricultural holdings
Restricted from publication18.1.7.2. Sampling design
Restricted from publication18.1.7.2.1. Name of sampling design
Restricted from publication18.1.7.2.2. Stratification criteria
Restricted from publication18.1.7.2.3. Use of systematic sampling
Restricted from publication18.1.7.2.4. Full coverage strata
Restricted from publication18.1.7.2.5. Method of determination of the overall sample size
Restricted from publication18.1.7.2.6. Method of allocation of the overall sample size
Restricted from publication18.1.7.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication18.1.8. Module ‘Soil management practices’
Restricted from publication18.1.8.1. Coverage of agricultural holdings
Restricted from publication18.1.8.2. Sampling design
Restricted from publication18.1.8.2.1. Name of sampling design
Restricted from publication18.1.8.2.2. Stratification criteria
Restricted from publication18.1.8.2.3. Use of systematic sampling
Restricted from publication18.1.8.2.4. Full coverage strata
Restricted from publication18.1.8.2.5. Method of determination of the overall sample size
Restricted from publication18.1.8.2.6. Method of allocation of the overall sample size
Restricted from publication18.1.8.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication18.1.9. Module ‘Machinery and equipment’
Restricted from publication18.1.9.1. Coverage of agricultural holdings
Restricted from publication18.1.9.2. Sampling design
Restricted from publication18.1.9.2.1. Name of sampling design
Restricted from publication18.1.9.2.2. Stratification criteria
Restricted from publication18.1.9.2.3. Use of systematic sampling
Restricted from publication18.1.9.2.4. Full coverage strata
Restricted from publication18.1.9.2.5. Method of determination of the overall sample size
Restricted from publication18.1.9.2.6. Method of allocation of the overall sample size
Restricted from publication18.1.9.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication18.1.10. Module ‘Orchard’
Restricted from publication18.1.10.1. Coverage of agricultural holdings
Restricted from publication18.1.10.2. Sampling design
Restricted from publication18.1.10.2.1. Name of sampling design
Restricted from publication18.1.10.2.2. Stratification criteria
Restricted from publication18.1.10.2.3. Use of systematic sampling
Restricted from publication18.1.10.2.4. Full coverage strata
Restricted from publication18.1.10.2.5. Method of determination of the overall sample size
Restricted from publication18.1.10.2.6. Method of allocation of the overall sample size
Restricted from publication18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication18.1.11. Module ‘Vineyard’
Restricted from publication18.1.11.1. Coverage of agricultural holdings
Restricted from publication18.1.11.2. Sampling design
Restricted from publication18.1.11.2.1. Name of sampling design
Restricted from publication18.1.11.2.2. Stratification criteria
Restricted from publication18.1.11.2.3. Use of systematic sampling
Restricted from publication18.1.11.2.4. Full coverage strata
Restricted from publication18.1.11.2.5. Method of determination of the overall sample size
Restricted from publication18.1.11.2.6. Method of allocation of the overall sample size
Restricted from publication18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication18.1.12. Software tool used for sample selection
The software used for sample selection was SAS EG version 7.15.
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 Description_quality_administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
Other18.1.14. Innovative approaches
The information on innovative approaches and the quality methods applied is available on Eurostat's website.
18.2. Frequency of data collection
The agricultural census is conducted every 10 years. The decennial agricultural census is complemented by sample or census-based data collections organised every 3-4 years in-between.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Postal, non-electronic versionTelephone, electronic version
Use of Internet
18.3.2. Data entry method, if paper questionnaires
Optic18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3 Core Questionnaire
18.3.3 Labour Questionnaire
18.3.3 AHMM Questionnaire
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Completeness checksRange checks
Comparisons with previous rounds of the data collection
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
Staff from local departments18.4.3. Tools used for data validation
The CSO Data Management System was utilised for verification and edits of each questionnaire that was returned.
Further data validation took place using SAS and R-Studio.
18.5. Data compilation
Design weights were obtained by taking the inverse of the inclusion probabilities. Weights were then adjusted based on non-response within the sampling strata.
18.5.1. Imputation - rate
Administrative data within the reference year of 2020 was available for close to 100% of the unit non-responders. This also meant that it could be determined if there was true item non-response when data was missing. The nature of the core data collected using the Census instrument and the available auxiliary information meant that accurate deductive imputation could be performed
There was more item non-response on the paper questionnaire than the electronic questionnaire. Variables such as the year the manager started (Y_FARM_MAN) and the level of training of the manager (TNG_MAN) were the characteristics with the highest item non-response. Processing staff could edit these during processing by contacting the holder or by using previous returns if available.
18.5.2. Methods used to derive the extrapolation factor
Design weightNon-response adjustment
18.6. Adjustment
Covered under Data compilation.
18.6.1. Seasonal adjustment
Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.
See sub-categories below.
19.1. List of abbreviations
CAP – Common Agricultural Policy
CAPI – Computer Assisted Personal Interview
CATI – Computer Assisted Telephone Interview
CAWI – Computer Assisted Web Interview
DAFM – Department of Agriculture, Food and the Marine
DMS – Data Management System
EPA – Environmental Protection Agency
FSS – Farm Structure Survey
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LSU – Livestock units
NACE – Nomenclature of Economic Activities
NUTS – Nomenclature of territorial units for statistics
PAPI – Paper and Pencil Interview
SO – Standard output
UAA – Utilised agricultural area
19.2. Additional comments
No additional comments.
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2020 are set in Commission Implementing Regulation (EU) 2018/1874.
The following groups of variables are collected in 2020:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module "Animal housing and rural development module": animal housing, nutrient use and manure on the farm, manure application techniques, facilities for manure.
See sub-category below.
See sub-categories below.
See sub-categories below.
See sub-categories below.
See categories below.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
Design weights were obtained by taking the inverse of the inclusion probabilities. Weights were then adjusted based on non-response within the sampling strata.
See sub-categories below.
Statistics on the structure of farming in Ireland are generally published every 3/4 years depending on the Farm Structure Survey (FSS) or IFS planned schedule. The FSS was most recently carried out in 2016 and IFS surveys will take place in 2023 and 2026.
See sub-categories below.
See sub-categories below.
See sub-categories below.