1.1. Contact organisation
Central Statistics Office
1.2. Contact organisation unit
Agriculture Surveys Section
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Central Statistics Office, Skehard Road, Cork, Ireland
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
21 October 2025
2.2. Metadata last posted
5 November 2025
2.3. Metadata last update
21 October 2025
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.
The statistical unit is the agricultural holding (farm). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
3.2. Classification system
Data are arranged in tables using many classifications. Please find below information on most classifications.
The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2021/2286.
The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard gross margin (SGM) (until 2007) or standard output (SO) (from 2010 onward) which is calculated for each crop and animal. The farm type is determined by the relative contribution of the different productions to the total standard gross margin or the standard output of the holding.
The territorial classification uses the NUTS classification to break down the regional data. The regional data is available at NUTS level 2.
3.3. Coverage - sector
The statistics cover agricultural holdings undertaking agricultural activities as listed in item 3.5 below and meeting the minimum coverage requirements (thresholds) as listed in item 3.6 below.
3.4. Statistical concepts and definitions
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
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.
3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”
Restricted from publication
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
Not applicable for our country, according to Article 7(7) of Regulation (EU) 2018/1091.
3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
The same population of agricultural holdings defined in item 3.6.1
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
Not applicable for our country, according to Article 7(5) of Regulation (EU) 2018/1091.
3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Restricted from publication
3.7. Reference area
See sub-categories below.
3.7.1. Geographical area covered
The entire territory of the country.
3.7.2. Inclusion of special territories
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 available.
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 2023 data are processed (by Eurostat) with 2020 standard output coefficients (calculated as a 5-year average of the period 2018-2022). For more information, you can consult the definition of the standard output.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land refers to the reference year 2023, as land variables are obtained from the IACS system, the 12-month reference period is 1 January 2023 to 31 December 2023. In the case of successive crops from the same piece of land, the land use refers to a crop that is harvested during the reference year, regardless of when the crop in question is sown.
5.2. Reference period for variables on irrigation and soil management practices
The variables on irrigation are not applicable for Ireland. For the soil management practices variables, the 12-month period ending on 31 December within the reference year 2023.
5.3. Reference day for variables on livestock and animal housing
The reference day for livestock variables is 1 June within the reference year 2023. The animal housing variables are not applicable for 2023.
5.4. Reference period for variables on manure management
The manure management variables are not applicable for 2023.
5.5. Reference period for variables on labour force
The 12-month period ending on 31 December within the reference year 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2023.
5.7. Reference day for all other variables
The reference day of 1 June within the reference year 2023.
6.1. Institutional Mandate - legal acts and other agreements
See sub-categories below.
6.1.1. National legal acts and other agreements
Legal 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.
6.1.3. Link to national legal acts and other agreements
6.1.4. Year of entry into force of national legal acts and other agreements
The Statistics Act entered into force in 1993.
6.1.5. Legal obligations for respondents
No6.2. Institutional Mandate - data sharing
The Central Statistics Office (CSO) has a Memorandum of Understanding (MoU) with the Department of Agriculture, Food and the Marine (DAFM). The MoU was updated in 2024, this was signed by the current Director General of the CSO and the Director General of the DAFM. This MoU ensures transmission of administrative agriculture data from the DAFM to the CSO.
7.1. Confidentiality - policy
All information returned on IFS 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. A table cell is suppressed if its inclusion would allow the calculation of another cell that has been suppressed by a previous rule. A cell is flagged using the ".." notation, which is the standard across all CSO online publications.
Some tables were redesigned to combine regions IE061 and IE062 in the national release due to low cell counts in those table cells.
Secondary confidentiality was applied manually to each table in isolation.
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. Results from the Integrated Farm Statistics survey 2023 were published in December 2024 on the Central Statistics Office website.
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 11am, 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 publications, the CSO standard release of results at 11am 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 10am 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 IFS was most recently carried out in 2023 and will take place again in 2026 and 2030. Dissemination typically is scheduled for 18-24 months after the reference date. Frequency of dissemination is typically every 3 years, 4 if there are 4 years between references dates; e.g. 2016 to 2020.
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
CSO statistical publication, 17 December 2024, 11am
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 2023 can be viewed using the CSOs online database (PxStat); the relevant tables are IFS01 through to IFS75 (with a few exceptions) and are available at the link below. After accessing the link below, please select "Business sectors", then filter by "Agriculture" and then by "Farm Structure Survey".
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 requirement and an office skills register per statistician is used to determine 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.
Quality reports and documentation – All statistical products are required to have an up-to-date quality report published on the CSO website. This is monitored by the quality team.
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 DAFM, the Irish FADN liaison agency, environmental agencies, the agricultural press (print and online), farming organisations, and the public. The main needs include detailed and robust statistics on demographic profiles of farmers, farm labour, and organic farming. Up-to-date data on farmer demographics have been useful for our users in researching the aging profile of farmers in Ireland, as well as farm succession planning. In IFS years, IE produces data for farm type and size, which is used by the Irish FADN liaison agency (Teagasc) to select recipients for the national farm survey on an annual basis. The agriculture surveys section frequently liaises with researchers from all Irish universities and agricultural research bodies on a wide range of queries. Many ad-hoc queries can be answered by running bespoke tabulations on IFS data.
12.1.1. Main groups of variables collected only for national purposes
The users, mentioned in item 12.1, were consulted during planning and a small number of additional variables (not in Regulation (EU) 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: Rams, ewes (under and over 2 years) and other sheep (under and over 1 year).
Equidae: Sub-division of Equidae into thoroughbred, other horses and mules, jennets and asses.
Pigs: A more detailed breakdown of pigs are required to continue time series from past data collections.
Poultry: Further sub-division of IFS characteristics to continue past time series.
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. 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.
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.
Renewable energy on farms: More details were collected on renewable energy on farms to fulfil national needs.
12.1.2. Unmet user needs
Some users requested labour and manure management statistics as a more detailed geographical level than NUTS 3. 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 (EU) 2018/1091.
12.1.3. Plans for satisfying unmet user needs
There are no plans for satisfying unmet user needs.
12.2. Relevance - User Satisfaction
The CSO monitor views and downloads of publications and data tables to determine interest level in the results. Media resulting from the IFS 2023 results was monitored. An annual meeting between the CSO, the Agriculture Ministry and other semi-state agriculture related institutes. In 2025, the IFS 2023 results will be a topic for discussion. These bodies are primary users of the IFS data, the meeting is a good opportunity to assess user satisfaction.
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 not collected, not-significant and not-existent variables is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
12.3.1. Data completeness - rate
Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.
13.1. Accuracy - overall
See categories below.
13.2. Sampling error
See sub-categories below.
13.2.1. Sampling error - indicators
Please find the relative standard errors on Eurostat’s website, at the link: CircaBC website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
Of the 76 eligible cases, 5 were non-compliant (6.58%).
In the IE04 and IE06 regions, the RSEs for A2300F_LSU (Dairy cows) were 10.49% and 9.34% respectively. In the IE06 region, the RSE for C0000T (Cereals for the production of grain (including seed) - outdoor) was 8.43%. In IE06, A2300G_LSU (Non-dairy cows) and A4000_LSU (Sheep and goats) were non-compliant with RSEs of 6.06% and 7.13% respectively. To address these high RSEs, LAFO will be issued with a larger sample size in 2026. Low response to the LAFO survey for tillage and dairy farms caused this non-compliance.
13.2.3. Reference on method of estimation
The relative standard errors were calculated in R.
Below is an example of code in R used to calculate RSE values.
calculate_rse <- function(x) {
mean_val <- mean(x, na.rm = TRUE)
se_val <- sd(x, na.rm = TRUE) / sqrt(length(x))
rse <- (se_val / mean_val) * 100
return(rse)}
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 on Eurostat’s website, at the link: CircaBC.
The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.1.1.1. Types of holdings included in the frame but not belonging to the population of the core (main frame and if applicable frame extension)
Below thresholds during the reference periodCeased activities
Merged to another unit
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 unitsOther
13.3.1.1.3. Additional information over-coverage error
Over-coverage described in 13.3.1.1 is based on the dataset of farm holdings that are below all thresholds presented in Annex II of Regulation (EU) 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 Agriculture Register, was updated 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. This register was revised before selecting the sample for IFS 2023 surveys. This was achieved by examining changes across the following administrative databases; 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 is 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 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 modular data for the vast majority of holdings.
13.3.1.5. Contact error
Yes13.3.1.5.1. Actions to minimise the contact error
The Agriculture Register was updated with up-to-date administrative sources from the Department of Agriculture before data collection began. Updating the register helped to minimise the contact error.
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. Cause of measurement errors is believed to be the difficulty of completing grassland information for payments. Typically, payments are the same for different types of grassland, not incentivising correct reporting of grassland from year to year.
13.3.3. Non response error
See sub-categories below.
13.3.3.1. Unit non-response - rate
See item 13.3.1.1.
The unit non-response rate is unweighted.
The unit non-response rate is calculated as the share of eligible non-respondent holdings to the eligible holdings. The eligible holdings include those holdings with unknown eligibility status which are imputed or re-weighted for (therefore considered eligible).
The unit non-response rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.3.1.1. Reasons for unit non-response
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 2023 was available for close to 100% of the unit non-responders. The nature of the core data collected 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 CSO 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 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
Not applicable, because first results were not published.
14.1.2. Time lag - final result
Farm statistics results were published in December 2024, 11 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 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 5 092 under threshold active farms. These farms are not sent in the microdata transmission to Eurostat but are included in the national publication.
There is close to 100% coverage provided by the farm holdings sent to Eurostat for UAA and LSU on Irish farm holdings.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
Approximately 3.8% 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 data on these smaller farm holdings is also included in regular data transmissions to Eurostat throughout the year to fulfil the SAIO requirements.
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 2023 data sent to Eurostat match those in Regulation (EU) 2018/1091, Commission Implementing Regulation (EU) 2021/2286 and the IFS 2023 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 on Eurostat’s website, at the link: CircaBC.
The number of working hours and days in a year for a full-time job correspond to one annual working unit (AWU) in the country. One annual work unit corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis. Annual working units are used to calculate the farm work on the agricultural holdings.
15.1.4.1.2. Point chosen in the Annual work unit (AWU) percentage band to calculate the AWU of holders, managers, family and non-family regular workers
See item 15.1.4.1.1.
15.1.4.1.3. AWU for workers of certain age groups
See item 15.1.4.1.1.
15.1.4.1.4. Livestock coefficients
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 periods/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 item 15.1.3.1) as the 5 092 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, 2020 and 2023. Data sent for 2020 had the threshold applied so is comparable to the 2023 data.
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
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
15.2.3. Thresholds of agricultural holdings
See sub-categories below.
15.2.3.1. Changes in the thresholds of holdings for which core data are sent to Eurostat since the last data transmission
There have been no changes15.2.3.2. Description of changes
Not applicable.
15.2.4. Geographical coverage
See sub-categories below.
15.2.4.1. Change in the geographical coverage since the last data transmission to Eurostat
There have been no 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 no changes15.2.5.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
15.2.6. Reference periods/days
See sub-categories below.
15.2.6.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.6.2. Description of changes
Not applicable.
15.2.7. Common land
See sub-categories below.
15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no 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
In 2023, the number of holdings in Ireland was relatively in line with the 2020 figures. Major fluctuations occurred in the legal status of the holding, with a remarkable increase in the share of PER_LEG_EG + PER_LEG_NEG (legal person) and a reduction of FARM_SPOU (farm managed by spouse of holder) and FARM_NFAM (farm not managed by any family member of holder).
With regards to the over time evolution of the variables, there was an increase in I1110T (rape and turnip rape seeds - outdoor), increase in oilseeds due to an increase in demand. I1120T (sunflower seed - outdoor), I1140T (linseed (oilflax) - outdoor), I5000T (aromatic, medicinal and culinary plants - outdoor), and I6000T + I9000T (energy crops n.e.c. - outdoor and other industrial crops n.e.c. - outdoor) also increased. There were relatively small areas in 2020, so fluctuations appear relatively larger.
V0000_S0000TO (Fresh vegetables (including melons) and strawberries grown in rotation with non-horticultural crops - outdoor - open field) had a remarkable increase. It should be noted that relatively small areas in 2020 and/or in 2023 make fluctuations look relatively larger.
The drop in A4210K (goats, breeding females), A3130 (other pigs), and the fluctuations in forage plants were rechecked and appear to be genuine changes as they were obtained directly from registers.
The increase in FLF_D_RFAMXHLD_F (members of sole holders' family, excluding the holder, directly employed by the farm - female) appears to be a genuine increase as data was collected via the labour force survey for which collection and processing remained consistent from 2020 to 2023.
In 2023, the share of holdings having benefitted from rural development measures sharply increased compared to the 2020 figures.
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
Coherence cross-domain: IFS vs CROP PRODUCTION
IFS and crop data are compiled in different ways in order to produce microdata. IFS data aligns with the results of the census of agriculture. Crop data is based solely on administrative sources; consequently, it does not fully cover land area in Ireland. IFS produces better land coverage through surveying.
Coherence cross-domain: IFS vs ORGANIC CROP PRODUCTION
Organic crop production figures are supplied by the Department of Agriculture based on estimates from organic certification boards. These figures do not fully align with who is receiving organic payments. IFS data is based on who is receiving organic payment data since IFS has to be produced at a microdata level. Not all farmers operating as organic receive payments, but Ireland cannot capture and include these in microdata because the organic certification boards produce only aggregates. Differences may arise if organic payment data does not align with other land use administrative sources.
Coherence cross-domain: IFS vs ORGANIC ANIMAL PRODUCTION
Organic animal figures are supplied by the Department of Agriculture based on estimates from organic certification boards. These figures do not fully align with who is receiving organic payments. IFS data is based on who is receiving organic payment data since IFS has to be produced at a microdata level. Not all farmers operating as organic receive payments, but Ireland cannot capture and include these in microdata because the organic certification boards produce only aggregates. Differences may arise if organic payment data does not align with other animal registers or survey results.
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 available.
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 (data were collected from the administrative sources).
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Not applicable for Ireland (data were not collected in 2023).
16.3.6. Module ‘Soil management practices’
Mean time in minutes to complete the core questionnaire (online & paper together) was 16.70 minutes and the median was 15 minutes.
16.3.7. Module ‘Machinery and equipment’
Mean time in minutes to complete the core questionnaire (online & paper together) was 16.70 minutes and the median was 15 minutes.
16.3.8. Module ‘Orchard’
Not applicable for Ireland (data were not collected in 2023).
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. 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 (CSO's 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 2023 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.
18.1. Source data
See sub-categories below.
18.1.1. Sampling design & Procedure 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 CSO 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.
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.
18.1.2.2.5. Method of determination of the overall sample size
Not applicable.
18.1.2.2.6. Method of allocation of the overall sample size
Not 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
Not applicable18.1.4. 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 force 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”
Restricted from publication
18.1.6.1. Coverage of agricultural holdings
Restricted from publication
18.1.6.2. Sampling design
Restricted from publication
18.1.6.2.1. Name of sampling design
Restricted from publication
18.1.6.2.2. Stratification criteria
Restricted from publication
18.1.6.2.3. Use of systematic sampling
Restricted from publication
18.1.6.2.4. Full coverage strata
Restricted from publication
18.1.6.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.6.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.7. Module ‘Irrigation’
See sub-categories below.
18.1.7.1. Coverage of agricultural holdings
Not applicable18.1.7.2. Sampling design
Not applicable.
18.1.7.2.1. Name of sampling design
Not applicable18.1.7.2.2. Stratification criteria
Not applicable18.1.7.2.3. Use of systematic sampling
Not applicable18.1.7.2.4. Full coverage strata
Not applicable.
18.1.7.2.5. Method of determination of the overall sample size
Not applicable.
18.1.7.2.6. Method of allocation of the overall sample size
Not applicable18.1.7.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.8. Module ‘Soil management practices’
See sub-categories below.
18.1.8.1. Coverage of agricultural holdings
Sample18.1.8.2. Sampling design
Stratified random sampling. Stratified by farm size and NUTS 3 regions resulting in 48 strata.
18.1.8.2.1. Name of sampling design
Stratified one-stage random sampling18.1.8.2.2. Stratification criteria
Unit sizeUnit location
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
No full coverage strata.
18.1.8.2.5. Method of determination of the overall sample size
Sample size based off advice from NSI IE methodology department. Results of previous farm structure and agriculture census surveys were analysed. Sample size was deemed sufficient and so a similar sample size was chosen for 2023.
18.1.8.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.8.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.9. Module ‘Machinery and equipment’
See sub-categories below.
18.1.9.1. Coverage of agricultural holdings
Sample18.1.9.2. Sampling design
Sample was allocated using simple random sampling. Strata were based on farm size and NUTS 3 resulting in 48 strata.
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit location
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
No full coverage strata.
18.1.9.2.5. Method of determination of the overall sample size
Sample size based off advice from NSI IE methodology department. Results of previous farm structure and agriculture census surveys were analysed. Sample size was deemed sufficient and so a similar sample size was chosen for 2023.
18.1.9.2.6. Method of allocation of the overall sample size
Neymann allocation18.1.9.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.10. Module ‘Orchard’
See sub-categories below.
18.1.10.1. Coverage of agricultural holdings
Not applicable18.1.10.2. Sampling design
Not applicable.
18.1.10.2.1. Name of sampling design
Not applicable18.1.10.2.2. Stratification criteria
Not applicable18.1.10.2.3. Use of systematic sampling
Not applicable18.1.10.2.4. Full coverage strata
Not applicable.
18.1.10.2.5. Method of determination of the overall sample size
Not applicable.
18.1.10.2.6. Method of allocation of the overall sample size
Not applicable18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.11. Module ‘Vineyard’
Restricted from publication
18.1.11.1. Coverage of agricultural holdings
Restricted from publication
18.1.11.2. Sampling design
Restricted from publication
18.1.11.2.1. Name of sampling design
Restricted from publication
18.1.11.2.2. Stratification criteria
Restricted from publication
18.1.11.2.3. Use of systematic sampling
Restricted from publication
18.1.11.2.4. Full coverage strata
Restricted from publication
18.1.11.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.11.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.12. Software tool used for sample selection
The software used for sample selection was SAS Enterprise Guide 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, at the link: Additional data - Eurostat (europa.eu).
18.1.13.2. Description and quality of the administrative sources
See the Excel file in the annex.
Annexes:
18.1.13.2. Description and quality of administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
Other18.1.14. Innovative approaches
The information on the innovative approaches and the quality methods applied is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
18.2. Frequency of data collection
The IFS conducted every 3-4 years, they take place in years ending in 0, 3 and 6. Years ending in 0 are carried out as a census whereas years ending in 3 and 6 are carried out as a sample survey.
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
Two questionnaires were issued to collect IFS 2023 variables. They are attached below.
Annexes:
18.3.3 Questionnaire (agricultural labour force survey) in English
18.3.3 Questionnaire (farm structure survey) in English
18.3.3 Questionnaire (agricultural labour force survey) in Irish
18.3.3 Questionnaire (farm structure survey) in Irish
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 in 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
Not available.
18.5.2. Methods used to derive the extrapolation factor
Design weightNon-response adjustment
Calibration
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
AWU – Annual Working Unit
CAP – Common Agricultural Policy
COA – Census of Agriculture
CSO – Central Statistics Office
DAFM – Department of Agriculture, Food and the Marine
DMS – Data Management System
ESCOP – European Statistics Code of Practice
EU – European Union
FADN – Farm Accountancy Data Network
FSS – Farm Structure Survey
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LAFO – Labour force and other gainful activities
LSU – Livestock unit
MoU – Memorandum of Understanding
NSI – National Statistical Institute
NUTS – Nomenclature of territorial units for statistics
RSE – Relative standard error
SAIO – Statistics on agricultural input and output
SGM – Standard gross margin
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 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
21 October 2025
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
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 IFS was most recently carried out in 2023 and will take place again in 2026 and 2030. Dissemination typically is scheduled for 18-24 months after the reference date. Frequency of dissemination is typically every 3 years, 4 if there are 4 years between references dates; e.g. 2016 to 2020.
See sub-categories below.
See sub-categories below.
See sub-categories below.
