1.1. Contact organisation
Central Statistics Office (CSO), Ireland
1.2. Contact organisation unit
Survey on Income and Living Conditions, Release and Publications Unit, Income Consumption and Wealth Division
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Income, Consumption and Wealth division
Central Statistics Office
Skehard Road
Cork
T12 X00E
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
28 March 2025
2.2. Metadata last posted
28 March 2025
2.3. Metadata last update
28 March 2025
3.1. Data description
The European Union Statistics on Income and Living Conditions (EU-SILC) is a survey-based instrument aiming at collecting timely and comparable cross-sectional and longitudinal multidimensional microdata on income, poverty, social exclusion and living conditions. In addition, it collects module variables every three years, six years or ad-hoc new policy needs modules.
The EU-SILC instrument provides two types of data:
- Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions
- Longitudinal data pertaining to individual-level changes over time, observed periodically over four‐or more year rotation scheme (Annex III (2) of 2019/1700). Social exclusion and housing condition information is collected mainly at household level while labour, education and health information is obtained for persons aged 16 and over. The core of the instrument is income information at very detailed component level and mainly collected at personal level.
3.2. Classification system
- International Standard Classification of Education (ISCED'2011);
- International Standard Classification of Occupations (ISCO-08);
- Classification of Economic Activities (NACE Rev.2-2008);
- Common classification of territorial units for statistics (NUTS 2);
- SCL Geo Code- Geographical code list;
- The recommendations made by the United Nations in the Canberra Group Handbook on Household Income Statistics should also be taken into account.
For more details on the classification used please, see EU Vocabularies, Eurostat's metadata server or CIRCABC
3.3. Coverage - sector
Data refer to all private households and individuals living in the private households in the national territory at the time of data collection.
The EU-SILC survey is a key instrument for the European Semester and the European Pillar of Social Rights, providing information on income distribution, poverty and social exclusion, as well as various related living conditions and poverty EU policies, such as on child poverty, access to health care and other services, housing, over indebtedness and quality of life. It is also the main source of data for microsimulation purposes and flash estimates of income distribution and poverty rates.
3.4. Statistical concepts and definitions
Statistical concepts and definitions for EU-SILC are specified in Regulation (EU) 2019/1700, Commission Implementing Regulation (EU) 2019/2181, and Commission Implementing Regulation (EU) 2019/2242. Additional information is available in the EU statistics on income and living conditions (EU-SILC) methodology and in the methodological guidelines and description of EU-SILC target variables (see CIRCABC).
Further details are provided in items 5, 15.1.1.1, 15.2.2 and 18.3.
3.5. Statistical unit
Statistical units are private households and all persons living in these households who have usual residence in the Member State. Annex II of the Commission implementing regulation (EU) 2019/2242 defines specific statistical units per variable and specifies the, content of the quality reports on the organisation of a sample survey in the income and living conditions domain pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council.
3.6. Statistical population
The target population is private households and all persons composing these households having their usual residence in the Member State. Private household means a person living alone or a group of persons who live together, providing oneself or themselves with the essentials of living.
3.6.1. Reference population
Definitions of reference population, household and household membership
| Reference population |
Private household definition |
Household membership |
|---|---|---|
| It is a voluntary (for selected households) survey of private households. The survey population is all private households and their current members residing in the state at the time of the data collection. |
A sample of dwellings is taken from the population and data is then collected on everyone within a household. The sample therefore excludes individuals living in public institutions (e.g. prisons, hospitals, nursing homes, etc.), communal accommodation and persons of no fixed abode. |
All current members of a selected private household. Up until 2019 in defining a ‘household’, the national IE SILC usedan 'address' concept (i.e. all persons living at the same address treated as a single household). From 2020 the national IE SILC definition of a household uses a shared income and expenditure concept. Flatmates or housemates that don’t share expenditure will now be considered as separate households, and students living away from home and substantially supported by their parents will be considered members of the parent household. |
3.6.2. Population not covered by the data collection
The sub-populations that are not covered by the data collection includes: those who moved out of the country’s territory; or those with no usual residence; or those living in institutions or who have moved to an institution compared to the previous year.
3.7. Reference area
The survey population is all private households and their current members residing in the state at the time of the data collection along with inhabitants of the following off-shore islands:
Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia.
All other offshore islands are excluded from the sample frame as they account for less than 2% of the total population.
3.8. Coverage - Time
The SILC statistics are compiled on an annual basis. The SILC was implemented in Ireland from 2003, begininning with a pilot in the first year.
For 2003 - 2019 the income reference period was the 12 months prior to date of interview, while data collection ran for 12 months (Jan-Dec).Thus the income reference period for Irish data up until 2019 covered Jan of year T-1 to Dec of year T.
The Irish SILC had a full break in time series in 2020. From 2020, the income reference period for SILC year T is the previous calendar year, T-1. The interview period is the first six months of year T.
3.9. Base period
Not applicable.
The data involves several units of measure depending upon the variables. Income variables are transmitted to Eurostat in national currency. For more information, see methodological guidelines and description of EU-SILC target variables available on CIRCABC
Description of reference period used for incomes
| Period for taxes on income and social insurance contributions |
Income reference periods used |
Reference period for taxes on wealth |
Lag between the income ref period and current variables |
|---|---|---|---|
| Income reference period. |
Up until 2019 the IE SILC income reference period was the 12-month period immediately preceding the sample household's interview date. This resulted in a 24-month income reference period for each annual SILC survey. Commencing with the 2020 IE SILC,the SILC income reference period will be the T-1 calendar year. |
Income reference period. |
Data collection is the first six months of the year. The income reference period is the T-1 calendar year. Thus the lag beween income reference period and the current variables can be up to six months. |
6.1. Institutional Mandate - legal acts and other agreements
Regulation (EU) 2019/1700 was published in OJ on 10 October 2019, establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples (IESS). The Annex to the Commission implementing regulation (EU) 2019/2180 of 16 December 2019 specifies the detailed arrangements and content for the quality reports pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council and Regulation (EU) 2019/2242.
6.2. Institutional Mandate - data sharing
Confidential microdata are not disclosed by Eurostat. Access to confidential microdata for scientific purposes may be granted on the basis of Commission Regulation 557/2013 and Regulation 223/2009 of the European Parliament and the Council on European statistics.
7.1. Confidentiality - policy
All information supplied to the CSO is treated as strictly confidential. The Statistics Act 1993 sets stringent confidentiality standards: Information collected may be used only for statistical purposes, and no details that might be related to an identifiable person or business undertaking may be divulged to any other government department or body.
These national statistical confidentiality provisions are reinforced by the following EU legislation:
- Council Regulation (EC) No 223/2009 on European statistics for data collected for EU statistical purposes.
CSO's Code of Practice on Statistical Confidentiality
This Code of Practice relates to the protection of the confidentiality of the individual information relating to persons and undertakings collected by the CSO.
- This Code of Practice applies to all information collected by the CSO whether directly in compulsory (statutory) and voluntary statistical inquiries or indirectly from the administrative records of other public authorities.
- The information collected by the CSO is used only for statistical purposes.
- The confidentiality of information relating to identifiable persons and undertakings is protected at all stages of statistical operations: collection, storage, processing, and dissemination.
- The computer files that contain the results of surveys do not, in general, contain the names or addresses of respondents. Limited exceptions are made, however, when there are strong statistical reasons for doing so.
- In the case of external trade statistics the CSO will, on the request of any importer or exporter, suppress the publication of information that reveals details of its business (the passive confidentiality approach).
- Stringent precautions are actively taken in disseminating all other statistical results to ensure that particulars relating to identifiable persons or undertakings are neither directly nor inadvertently disclosed, and that any disclosure of individual information is made only with the written permission of the data provider concerned (the active confidentiality approach). For example, in the case of business statistics, published information is based on a minimum number of three respondents and then only when one or two enterprises do not have too dominant a share of the total.
- Office and field staff appointed to the CSO sign a Declaration of Secrecy specified in the Statistics Act, 1993 and are fully instructed on their obligations to protect the confidentiality of any identifiable information to which they have access.
- High security is maintained on the CSO computer network. Authorised access within the Office to computer files containing confidential data is strictly limited and controlled by a system of personal/section passwords that are regularly updated.
- Information relating to identifiable persons or undertakings may only be provided to a non-CSO person or body in the limited cases specified in the Statistics Act 1993.
- Confidential information is transferred in anonymous form to the Statistical Office of the EU (Eurostat) for the compilation of aggregate Community statistics under the protective provisions of Regulation (EC) No 223/2009 as amended by Regulation (EU) No 2015/759. Under further European and Irish legislation, non-anonymised Balance of Payments related statistical microdata may be transmitted by the CSO to the European Central Bank.
- The EuroGroups Register (EGR) aims to improve the quality of multinational enterprise group information by allowing compilers of statistics to produce statistics on the basis of Europe-wide shared and coordinated information. The legal basis for the EGR is provided by Regulations (EC) No 177/2008 and (EC) No 223/2009. Confidential non-anonymised data on multinational enterprise groups and their constituent units that are contained in the EuroGroups Register is transferred from the CSO to Eurostat, and from Eurostat to the national statistical authorities in each Member State. Under further European and Irish legislation, this data may be transmitted by Eurostat to the European Central Bank, to the central banks of Member States. This data is transmitted under the conditions that it is used exclusively for statistical purposes, and that it is treated as confidential in accordance with Community provisions.
- The Director General requires Heads of Division to confirm annually the steps taken within their Divisions to ensure ongoing compliance with this Code of Practice.
7.2. Confidentiality - data treatment
National SILC publication
SILC results are published as aggregated statistics on the CSO website. These aggregate statistical outputs are freely available to everyone. Publishing data in aggregate form means no individual or household is identifiable. No third party has access to any individual’s data provided to the CSO. Furthermore, percentage results from SILC are published to one decimal place. Monetary results are rounded to the nearest euro and results based on a cell size of fewer than 30 unweighted observations are not published due to low reliability.
SILC Research Microdata Files (RMFs)
Access is granted via Virtual Desktop Infrastructure (VDI) only. SILC microdata cannot be matched to other datasets by researchers without prior agreement. A review of the SILC RMF was conducted by the Methodology department in the CSO. As a result any variables deemed potentially disclosive (e.g. county) were removed. Researchers are issued guidelines with regards to the use of the SILC RMF.
The CSO emphasises that Officers of Statistics are legally obliged to ensure the confidentiality of RMF data. As part of this, persons applying for access to RMFs are required to demonstrate their knowledge of statistical disclosure control and to apply these methods to all tables intended for dissemination. Any discussions of the data by the researcher (e.g. discussions of tables or analysis which could potentially disclose details of individual records) must be restricted to other Officers of Statistics appointed to the same statistical research project. The CSO also has the right to perform any appropriate statistical disclosure control, either before the RMF is issued to the researcher, or to any subsequent output generated from the RMF. This does not lessen the aforementioned obligations on the researcher appointed as an Officer of Statistics to perform all necessary statistical disclosure control. Failure to do so will result in CSO sanctions.
SILC Anonymised Microdata File (AMFs)
Anonymised Microdata Files are issued to the Irish Social Science Data Archive (ISSDA) and the Luxembourg Income Study Database (LIS). The data is then disseminated by these organisations and as such the files have tighter Statistical Disclosure Control (SDC) rules in place. Generally speaking, any monetary values are rounded to the nearest €10, and categorical variables are re-categorised according to recommendations to the statistical disclosure control review carried out by the Methodology department.
EU-SILC RMF Statistical Disclosure Control
Each year Eurostat will contact the SILC statistician with regards to any changes to the anonymization rules used for the Irish EU-SILC RMF disseminated by Eurostat.
8.1. Release calendar
National results for SILC Year T are published within the first quarter of the Year T + 1. The date of dissemination of all statistics released by CSO can be found in the Release Calendar. This calendar is regularly updated.
8.2. Release calendar access
Please refer to the Release calendar - Eurostat (europa.eu) publicly available on the Eurostat’s website.
8.3. Release policy - user access
In line with the Community legal framework and the European Statistics Code of Practice, Eurostat disseminates European statistics on Eurostat's website (see section 10 - 'Accessibility and clarity'), respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users. Additional information about microdata access is available in Statistics on Income and Living Conditions - Access to microdata - Eurostat (europa.eu).
Annual
10.1. Dissemination format - News release
Not applicable.
10.2. Dissemination format - Publications
The national results for SILC 2024 were released on the following dates:
10.3. Dissemination format - online database
National SILC data is published in tabular format via the CSO’s dissemination database PxStat.
List of SILC databases:
- Core SILC data 2004-2019
- Core SILC data 2020-present
- SILC Report on Household Amenities and Access to Services
- Poverty Insights - Income Reference Periods 2018 to 2020
- SILC Module on the Intergenerational Transmission of Disadvantages
- SILC Module on the Impact of Childhood Poverty Experiences on Adult Life
- SILC Module on Well-being
Note that SILC data as published on the CSO website is based on national defintions of income, equivalence scale, etc. & tends not to be directly comparable with estimates on the Eurostat database. See the background notes of the SILC publications on the CSO website for further information.
10.3.1. Data tables - consultations
See Annex attached.
Annexes:
CSO SILC table analytics 2024
10.4. Dissemination format - microdata access
SILC RMF
The cross-sectional SILC RMF (Researcher Microdata File) is available through the CSO. This is the most detailed SILC datafile available to researchers and access is tightly controlled - see link. Access to the RMF is available to national users only, whereby the organistaion a researcher represents must be approved, and each researcher attends training and agrees to the terms of becoming an "Officers of Statistics" before being granted access to data. Data is made available to approved researchers via a VDI (Virtual Desktop Infrastructure) and users are required to have all outputs (e.g. tabulations) approved by a CSO statistician.
ISSDA AMF
An AMF (Anonymised Microdata File) of cross-sectional SILC data is available via the Irish Social Science Data Archive (ISSDA), at University College Dublin. These files have a high degree of statistical disclosure control applied and are primarily aimed at students. Data is disseminated as csv files. Access is granted via ISSDA.
LIS AMF
An AMF (Anonymised Microdata File) of cross-sectional SILC data is available via the Luxembourg Income Study Database (LIS). These files have a high degree of statistical disclosure control applied. Access is granted via the LIS.
10.5. Dissemination format - other
The SWITCH model, Ireland’s tax-benefit microsimulation model created and maintained by the Economic & Social Research Institute (ESRI) is based on SILC data.
10.5.1. Metadata - consultations
Not applicable.
10.6. Documentation on methodology
SILC Survey information, methodological documents, background notes and national quality reports are all publicly available on the CSO website and updated when necessary.
10.6.1. Metadata completeness - rate
All required concepts are provided.
10.7. Quality management - documentation
Links to National Quality Reports and Background Notes.
11.1. Quality assurance
To ensure the quality of our SILC statistical processes and products, the Central Statistics Office adheres to international best practice. While each statistical area is responsible for managing the quality of their statistical processes and outputs, they are supported by staff from the CSO’s Quality Management, Support and Assurance (QMSA) division who are responsible for the development and implementation of the CSO’s Quality Management Framework (QMF). The QMF is an extensive and long-term programme of activities, which will ensure that the statistical production standards applied in the CSO continue to meet the highest standards as regards quality and efficiency. The overall goal of the QMF is meeting the required standard as set out in the European Statistical System Code of Practice (ESCOP) and the QMF foundations are based on establishing the UNECE’s Generic Statistical Business Process Model (GSBPM) as the operating statistical production model in the CSO.
All Statisticians working on SILC are trained in best practice and their work is quality reviewed by more senior team members from the area. Data checks are performed using administrative data from other departments such as the Department of Social Protection, Revenue, and other Govenment bodies to ensure coherence and comparability. An annual self-assessment is undertaken each year following the national SILC publication where any improvements and recommendations are implemented the following year. For SILC 2024 both survey data processing code and publication processing code were fully reviewed and updated/re-written where needed.
11.2. Quality management - assessment
Relevance
The relevance of SILC data has suffered somewhat from issues of timeliness. Overcoming these timeliness failings is one of the main driving forces behind Eurostat’s revision of the EU-SILC legal basis. Under Regulation No 1177/2003 the SILC cross sectional data transmission deadline from the Member States to the Commission (Eurostat) for a data collection year T was November 30 of year T+1. From 2022, under Regulation 2019/1700 there has been improved timeliness, with shorter deadlines for SILC data submission, the new transmission deadline being December 31 of year T (the current survey year). To meet the new transmission deadline, the CSO changed the data collection period from continuously throughout the year to the first 6 months of the year.
Accuracy and Reliability
Along with publishing national estimates from the SILC, measures of the accuracy of these estimates are also calculated and reported in the National Quality Report. These measures include precision estimates such as Confidence Intervals, Variances, Standard Errors, and Design Effects. Furthermore, the Statistical Significance of Year-on-Year Change and Coefficient of Variation are also calculated.
The availability of administrative data from the Revenue and the Department of Social Protection has greatly improved the reliability of SILC data. Measurement errors in the overall income levels of individual respondents have greatly reduced and the reliability of the overall social welfare income for each individual on the dataset has also greatly improved. The variable that allows all of this data to be linked is the Personal Public Service Number (PPSN). Anomalies may still arise in these data sources and these are identified and resolved using SILC Data Collection Unit's comprehensive micro-editing system.
Timeliness and Punctuality
The timeliness and punctuality of SILC has been improving over the last few years, primarily thanks to the implementation of Regulation 2019/1700. For SILC 2024 the time lag (in months) between the end of the survey reference period and the publication date was 14 months for the results in Survey on Income and Living Conditions (SILC) 2024.
Coherence
Much of the income micro-data comes directly from administrative sources such as Department of Social Protection and Revenue. Coherence checks of employee and self-employed income data are performed and published in the National Quality Report.
Comparability
Eurostat disseminate their own statistics using EU-SILC data. The definitions adopted by Eurostat differ slightly from national definitions and concepts. Therefore, when making international comparisons to ensure consistency Eurostat SILC statistics should be used.
12.1. Relevance - User Needs
The main users of EU-SILC statistical data are policy makers, research institutes, media, and students.
SILC provides a wealth of information in the areas of income, poverty, inequality, well-being and social exclusion. A wide range of individuals and organisations in society and politics use the data in the form of statistics and micro-data. The relevance of the information is greatly enhanced by the CSO’s impartiality and independence as an organisation. The CSO's publication of SILC data caters specifically to national user needs by employing national income and poverty indicator definitions that differ to those employed by Eurostat. Additional publications focusing on module data are also produced as resources allow.
The main users of EU-SILC are:
- Institutional users like other European Commission services, other European institutions (such as the ECB), national administrations (mainly those in charge of monitoring social protection and social inclusion), or other international organisations;
- Statistical users in Eurostat or in Member States' National Statistical Institutes to feed sectoral or transversal publications such as the Annual Progress Report on the Lisbon Strategy (structural indicators), the Sustainable Development Strategy monitoring report, the Eurostat yearbook and various pocketbooks, among other reports;
- Researchers having access to microdata for their purposes in assessing and aiding evidence-based policy discussions;
- End users - including the media - interested in the living conditions and social cohesion of countries in the EU.
List of annual national SILC publications available on the Ireland Statistical website.
12.2. Relevance - User Satisfaction
Eurostat carried out an online general User Satisfaction Survey (USS) in the period between April and July 2019 to obtain better knowledge about users, considering their needs and satisfaction with the services provided by Eurostat. The survey has shown that EU-SILC is of very high relevance for users. For the majority, both aggregates and micro-data were important or essential in their work irrespective of the purpose of their use. The use of the ad-hoc modules was less widespread than the use of the nucleus variables. Nevertheless, there was an interest in repeating these modules to allow for the possibility of comparing data over time. Users emphasised a need for more detailed micro-data, which is currently not possible. Under the new legal framework implemented from 2021, the NUTS 2 division will be available for the main indicators. Finally, users were satisfied with overall quality of the service delivered by Eurostat, which encompasses data quality and the supporting service provided to them.
For more information, please consult the User Satisfaction Survey.
The Central Statistics Office does not compile information on EU SILC user satisfaction directly.
There is an Irish Civil Service wide user satisfaction survey which would also relate to the Central Statistics Office given that it is under the remit of the Department of the Taoiseach. See 2019 Survey of Civil Service Customer Satisfaction Survey Results. This survey found that in 2019:
- Overall satisfaction levels for service delivery and outcome are the highest recorded to date
- 85% of customers were satisfied with both the service received (up from 83% in 2017 and 76% in 2015)
- 85% of customers were satisfied with the outcome of their most recent contact with the civil service (up from 82% in 2017 and 76% in 2015)
- 89% indicated that service levels are mostly meeting or exceeding expectations (up from 87% in 2017 and 83% in 2015)
- Dissatisfaction is at its lowest level since 2009. Dropping from 39% in 2009 to 20% in 2019
- Confidence that any personal data supplied to the civil service would be securely managed has improved (up 9 points to 68% since the 2017 survey)
12.3. Completeness
There was only one core variable not collected in SILC 2024:
- HY170 - Value of goods produced for own consumption. Ireland stopped collecting this variable since SILC 2020 as it is not relevant in the Irish context.
Two core varirables may not be fully comparable with other EU countries due to restrictions with collecting the data in Ireland:
- PY021 - Income from private use of company car. Not always possible to separate from PY020.
- PY050 - Cash profits or losses from self-employment. Administrative self-employment for year T-1 is not available in time for the transmission deadline.
The following optional variables were not collected in SILC 2024 in order to reduce reponse burden:
- HY030G: Imputed rent
- RL080: Remote education
- HI130G: Interest expenses [not including interest expenses for purchasing the main dwelling]
- HI140G: Household debts
12.3.1. Data completeness - rate
There was only one core variable not collected in SILC 2024:
- HY170 - Value of goods produced for own consumption. Ireland stoppped collecting this variable since SILC 2020 as it is not relevant in the Irish context.
13.1. Accuracy - overall
According to Reg. (EU) 2019/1700 Annex II, precision requirements for all data sets are expressed in standard errors and are defined as continuous functions of the actual estimates and of the size of the statistical population in a country or in a NUTS 2 region. For the income and living conditions domain, the estimated standard errors of the following indicators are examined according to certain parameters set:
- · Ratio at‐risk‐of‐poverty or social exclusion to population;
- · Ratio of at‐persistent‐risk‐of‐poverty over four years to population;
- · Ratio at‐risk‐of‐poverty or social exclusion to population in each NUTS 2 region.
Further information is provided in section 13.2 Sampling error.
13.2. Sampling error
EU-SILC is a complex survey involving different sampling designs in different countries. In order to harmonise and make sampling errors comparable among countries, Eurostat (with the substantial methodological support of Net-SILC2) has chosen to apply the "linearisation" technique coupled with the “ultimate cluster” approach for variance estimation.
Linearisation is a technique based on the use of linear approximation to reduce non-linear statistics to a linear form, justified by asymptotic properties of the estimator. This technique can encompass a wide variety of indicators, including EU-SILC indicators. The "ultimate cluster" approach is a simplification consisting of calculating the variance taking into account only variation among Primary Sampling Unit (PSU) totals. This method requires first stage sampling fractions to be small which is nearly always the case. This method allows a great flexibility and simplifies the calculations of variances. It can also be generalized to calculate variance of the differences of one year to another.
The main hypothesis on which the calculations are based is that the "at risk of poverty" threshold is fixed. According to the characteristics and availability of data for different countries, we have used different variables to specify strata and cluster information.
In particular, countries have been split into 3 groups:
- BE, BG, CZ, IE, EL, ES, FR, HR, IT, LV, HU, PL, PT, RO, SI, UK and AL, whose sampling design could be assimilated to a two-stage stratified type we used DB050 (primary strata) for strata specification and DB060 (Primary Sampling Unit) for cluster specification;
- DK, DE, EE, CY, LT, LU, NL, AT, SK, FI, CH whose sampling design could be assimilated to a one stage stratified type we used DB050 for strata specification and DB030 (household ID) for cluster specification;
- MT, SE, IS, NO, whose sampling design could be assimilated to a simple random sampling, we used DB030 for cluster specification and no strata.
For Ireland, the standard errors are calculated in SAS using the PROC SURVEYMEANS statement, specifyng the following:
- Weight = DB090 (Householf cross-sectional weight)
- Cluster = DB060 (Primary sampling units)
- Strata = DB050 (Stratu)
Add Annex 3 Sampling Errors.
Please note that Annex 3 needs to be updated for longitudinal data once longtudinal weights (DB095) are calculated later this year.
Annexes:
Annex 3 - Sampling Errors
13.2.1. Sampling error - indicators
The concept of accuracy refers to the precision of estimates computed from a sample rather than from the entire population. Accuracy depends on sample size, sampling design effects and structure of the population under study. In addition to that, sampling errors and non-sampling errors need to be taken into account. Sampling error refers to the variability that occurs at random because of the use of a sample rather than a census and non-sampling errors are errors that occur in all phases of the data collection and production process.
13.3. Non-sampling error
Non-sampling errors are basically of 4 types:
- Coverage errors: errors due to divergences existing between the target population and the sampling frame.
- Measurement errors: errors that occur at the time of data collection. There are a number of sources for these errors such as the survey instrument, the information system, the interviewer and the mode of collection.
- Processing errors: errors in post-data-collection processes such as data entry, keying, editing and weighting.
- Non-response errors: errors due to an unsuccessful attempt to obtain the desired information from an eligible unit. Two main types of non-response errors are considered:
- Unit non-response: refers to absence of information of the whole units (households and/or persons) selected into the sample.
- Item non-response: refers to the situation where a sample unit has been successfully enumerated, but not all required information has been obtained.
13.3.1. Coverage error
Coverage errors include over-coverage, under-coverage and misclassification:
- Over-coverage: relates either to wrongly classified units that are in fact out of scope, or to units that do not exist in practice.
- Under-coverage: refers to units not included in the sampling frame.
- Misclassification: refers to incorrect classification of units that belong to the target population
13.3.1.1. Over-coverage - rate
Coverage error
| Main problems |
Population (sub-population) |
Size of error |
Comments |
|---|---|---|---|
| Over-coverage |
223 |
2.45% |
The Sampling frame can contain properties that are vacant. |
| Under-coverage |
N/A |
N/A |
Unable to calculate. |
| Misclassification |
N/a |
N/A |
Unable to calculate. |
13.3.1.2. Common units - proportion
N/A
13.3.2. Measurement error
Measurement error for cross-sectional data
| Cross-sectional data |
|||
|---|---|---|---|
| Source of measurement errors |
Building process of questionnaire |
Interview training |
Quality control |
| No formal evaluation of sources of error is available, although measures are in place to minimise error. |
The SILC questionnaire was fully reviewed for SILC 2024, taking on board feedback from field staff, the questionnaire design unit, and testing within the CSO. Field staff can also relate back any issues experienced with the questionnaire or the wording of questions. |
The quality of the data collected is improved using regular field staff training (including the use of video recording of training interviews) and de-briefings – for example, suggestions are invited from field staff regarding the wording of certain questions. Comprehension errors: most of the terms used by the survey are readily understood, although some issues occasionally arise |
Quality control is provided and ensured by CSO statisticians. |
13.3.3. Non response error
Non-response errors are errors due to an unsuccessful attempt to obtain the desired information from an eligible unit. Two main types of non-response errors are considered:
- Unit non-response which refers to the absence of information of the whole units (households and/or persons) selected into the sample. According to Annex VI of the Reg.(EU) 2019/2242
- Household non-response rates (NRh) is computed as follows:
NRh=(1-(Ra * Rh)) * 100
Where Ra is the address contact rate defined as:
Ra= Number of address/selected person (including phone, mail if applicable) successfully contacted/Number of valid addresses/selected person (including phone, mail if applicable) selected
and Rh is the proportion of complete household interviews accepted for the database
Rh=Number of household interviews completed and accepted for database/Number of eligible households at contacted addresses (including phone, mail if applicable)
-
- Individual non-response rates (NRp) is computed as follows:
NRp=(1-(Rp)) * 100
Where Rp is the proportion of complete personal interviews within the households accepted for the database
Rp= Number of personal interview completed/Number of eligible individuals in the households whose interviews were completed and accepted for the database
-
- Overall individual non-response rates (*NRp) is computed as follows:
*NRp=(1-(Ra * Rh * Rp)) * 100
For those Members States where a sample of persons rather than a sample of households (addresses, phones, mails etc.) was selected, the individual non-response rates will be calculated for ‘the selected respondent.
- Item non-response which refers to the situation where a sample unit has been successfully enumerated, but not all the required information has been obtained.
13.3.3.1. Unit non-response - rate
Unit non-response rate for cross-sectional
| Address (including phone, mail if applicable) contact rate |
Complete household interviews |
Complete personal interviews |
Household Non-response rate |
Individual non-response rate |
Overall individual non-response rate |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (Ra) |
(Rh) |
(Rp) |
(NRh) |
(NRp) |
(NRp)* |
||||||||||||
| A |
B |
C |
A |
B |
C |
A |
B |
C |
A |
B |
C |
A |
B |
C |
A |
B |
C |
| 99.37% |
98.78% |
100% |
61.93% |
40.87% |
85.50% |
100% |
100% |
100% |
38.46% |
59.63% |
14.50% |
0 |
0 |
0 |
38.46% |
59.63% |
14.50% |
where
A=total (cross-sectional) sample,
B =New sub-sample (new rotational group) introduced for first time in the survey this year,
C= Sub-sample (rotational group) surveyed for last time in the survey this year.
Unit non-response rate for longitudinal data
Response rate for households by wave
| Response rate for household | Wave 2 | Wave 3 | Wave 4 | Wave 5* | Wave 6* |
|---|---|---|---|---|---|
| Wave response rate | 72.16 | 83.19 | 84.67 | 85.99 | 85.50 |
| L follow-up rate | 72.16 | 83.19 | 84.67 | 85.99 | 85.50 |
| Follow-up ratio | 0.63 | 0.79 | 0.80 | 0.81 | 0.81 |
| Achieved sample size ratio | 0.24 | 0.67 | 0.72 | 0.75 | 0.76 |
Response rate for persons by wave
| Response rate for persons | Sample persons / co-residents | Wave 2 | Wave 3 | Wave 4 | Wave 5* | Wave 6* |
|---|---|---|---|---|---|---|
| Wave response rate | Sample persons | 60.45 | 101.62 | 102.37 | 100.73 | 103.03 |
| co-residents | 68.67 | 68.80 | 34.86 | 29.16 | 18.55 | |
| L follow-up rate | Sample persons | 100 | 100 | 100 | 100 | 100 |
| Achieved sample size ratio (persons aged 16 and over) | All persons | 0.6 | 1.0 | 1.0 | 1.0 | 1.0 |
| Sample persons | 0.6 | 1.0 | 1.0 | 1.0 | 1.0 | |
| co-residents | n/a | n/a | n/a | n/a | n/a | |
| Response rate for non-sample persons | co-residents | 1 | 1 | 1 | 1 | 1 |
Sample and response rate by wave
| Year of the survey | Sample of households | Sample of individuals 16+ | Response rate of the households | Response rate of individuals 16+ |
|---|---|---|---|---|
| Wave 1 | 4712 | 3036 | 31.69 | 100 |
| Wave 2 | 1720 | 2139 | 62.85 | 100 |
| Wave 3 | 1091 | 1738 | 79.38 | 100 |
| Wave 4 | 941 | 1477 | 79.81 | 100 |
| Wave 5* | 500 | 758 | 81.00 | 100 |
| Wave 6* | 356 | 525 | 18.82 | 100 |
Annexes:
Annex A
13.3.3.2. Item non-response - rate
The computation of item non-response is essential to fulfil the precision requirements. Item non-response rate is provided for the main income variables both at household and personal level.
Item non-response which refers to the situation where a sample unit has been successfully enumerated, but not all the required information has been obtained.
13.3.3.2.1. Item non-response rate by indicator
See Annex 2 attached.
Annexes:
Annex 2 - Item Non-Response
13.3.4. Processing error
Description of data entry, coding controls and the editing system
| Data entry and coding (if any used) |
Editing controls |
|---|---|
| Data entry controls are set within the questionnaire. Most questions are set so that only certain values can be entered as a response. Some coding is done within the questionnaire e.g. country coding for country of birth, country of citizenship, country of birth of mother/father, Only valid country codes can be chosen for entry. Education level is also coded within the questionnaire. |
There aren't really any edit rules for income. CSO takes the administrative data and uses the survey data if it's not available, we assume the administrative data is correct when it is available as it tends to be a clean data source. When using the survey data we check for very large values which really only occur when people use the estimate bands and check the wrong box. For people who give a very high income estimate band we check the occupation to see if it's plausible. If it isn't plausible, we treat it as a missing value. The main check with income is checking that everyone who said they had a particular type of income has either an administrative value, a survey value or gets an estimated value if the first two are not available. The area where the largest number of errors are found and corrected is the relationship matrix. This would include missing and incorrect entries. Checking that children have a father/mother/both assigned, checking that spouse is assigned if marital status is married, etc. Households do have to be individually examined if the edit checks fail. The correct codes must be manually assigned then often based on logic and what makes most sense. |
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
The national results for SILC 2024 were released on the CSO website on the following date:
- On 11th March 2025, results from SILC were published as the first stage focusing on Deprivation for the Survey on Income and Living Conditions (SILC) 2024: Enforced Deprivation.
- On 20th March 2025, results from SILC were published as the final release focusing on Income and Poverty for the Survey on Income and Living Conditions (SILC) 2024.
Data collection period for SILC 2024: 01 January - 30 June 2024
Date of the first fully validated delivery of data: 22 December 2024
Number of days between the end of fieldwork and the first fully validated delivery of data to Eurostat: 175 days
Income reference year: 01 January -31 December 2023
Number of days between end of reference year and to the day of publication of the first results: 436 days
14.1.1. Time lag - first result
On 11th March 2025, results from SILC were published as the first stage focusing on Deprivation for the Survey on Income and Living Conditions (SILC) 2024: Enforced Deprivation.
Number of days between end of reference year and to the day of publication of the first results: 436 days
14.1.2. Time lag - final result
On 20th March 2025, results from SILC were published as the final release focusing on Income and Poverty for the Survey on Income and Living Conditions (SILC) 2024.
Number of days between end of reference year and to the day of publication of the final results: 445days
14.2. Punctuality
SILC 2024 data for Ireland was transmitted to Eurostat on 22 December 2024.
The agreed deadline was 31 December 2024.
14.2.1. Punctuality - delivery and publication
The national results for SILC 2024 were released on the CSO website on the following dates:
- 20th March 2025, after income data was fully processed, the results from SILC were published as the final release for the Survey on Income and Living Conditions (SILC) 2024.
Number of months between end of data collection (30 June 2024) to final release (20th March 2025) of national results: 9 months
Number of months between end of income reference period (31 Decmber 2023) to final release (20th March 2025) of national results: 15 months
15.1. Comparability - geographical
Not applicable - IE data for each NUTS2 region come from the same sources.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
See Annex 8 (Breaks in Series) attached.
Annexes:
Annex 8 - Break in Time Series
15.2.1. Length of comparable time series
4 years since last break in series. IE SILC had a full break in series in 2020.
15.2.2. Comparability and deviation from definition for each income variable
Comparability and deviation from definition for each income variable
| Income |
Identifier |
Comparability |
Deviation from definition (if any) |
|---|---|---|---|
| Total hh gross income |
(HY010) |
F |
|
| Total disposable hh income |
(HY020) |
F |
|
| Total disposable hh income before social transfers other than old-age and survivors' benefits |
(HY022) |
F |
|
| Total disposable hh income before all social transfers |
(HY023) |
F |
|
| Income from rental of property or land |
(HY040) |
F |
|
| Family/ Children related allowances |
(HY050) |
F |
|
| Social exclusion payments not elsewhere classified |
(HY060) |
F |
|
| Housing allowances |
(HY070) |
F |
|
| Regular inter-hh cash transfers received |
(HY080) |
F |
|
| Alimonies received |
(HY081) |
F |
|
| Interest, dividends, profit from capital investments in incorporated businesses |
(HY090) |
F |
|
| Interest paid on mortgage |
(HY100) |
F |
|
| Income received by people aged under 16 |
(HY110) |
F |
|
| Regular taxes on wealth |
(HY120) |
F |
|
| Taxes paid on ownership of household main dwelling |
(HY121) |
F |
|
| Regular inter-hh transfers paid |
(HY130) |
F |
|
| Alimonies paid |
(HY131) |
F |
|
| Tax on income and social contributions |
(HY140) |
F |
|
| Repayments/receipts for tax adjustment |
(HY145) |
F |
|
| Value of goods produced for own consumption |
(HY170) |
NC |
No longer collected from 2020. Not relevant in the Irish context. |
| Cash or near-cash employee income |
(PY010) |
F |
|
| Other non-cash employee income |
(PY020) |
F |
|
| Income from private use of company car |
(PY021) |
P |
Not always possible to separate from PY020. |
| Employers social insurance contributions |
(PY030) |
F |
|
| Contributions to individual private pension plans |
(PY035) |
F |
|
| Cash profits or losses from self-employment |
(PY050) |
L |
Administrative self-employment for year T-1 is not available in time for the transmission deadline. |
| Pension from individual private plans |
(PY080) |
F |
|
| Unemployment benefits |
(PY090) |
F |
|
| Old-age benefits |
(PY100) |
F |
|
| Survivors benefits |
(PY110) |
F |
|
| Sickness benefits |
(PY120) |
F |
|
| Disability benefits |
(PY130) |
F |
|
| Education-related allowances |
(PY140) |
F |
|
F= Fully comparable; L= Largely comparable; P= Partly comparable and NC= Not collected.
15.3. Coherence - cross domain
The coherence of two or more statistical outputs refers to the degree to which the statistical processes, by which they were generated, used the same concepts and harmonised methods. A comparison with external sources for all income target variables and the number of persons who receive income from each ‘income component’ will be provided, where the Member States concerned consider such external data to be sufficiently reliable.
15.3.1. Coherence - sub annual and annual statistics
Not applicable.
15.3.2. Coherence - National Accounts
Coherence with National Accounts for income variables
| EU-SILC variables |
National Accounts item (S14) |
Coverage rate (calculated as EUSILC and NA ratio) |
EUSILC growth rate (nominal, year to year) |
National accounts growth rate (nominal, year to year) |
|---|---|---|---|---|
| Employee income: |
D11/rec Wages and salaries |
0.95 |
10.5% |
11.6% |
| Income from self-employment: PY050G Cash benefits or losses from self-employment |
B3g Mixed income, gross |
0.91 |
16.8% |
(-4.7%) |
| Social benefits other than social transfers in kind: +PY120G Sickness benefits |
D62/rec: Social benefits, other than social transfers in kind |
0.71 |
4.0% |
4.1% |
| Social contributions and taxes on income paid: |
D61/use: net social contributions |
0.48 |
13.5% |
6.5% |
| Total disposable household income HY020 |
B6 Gross disposable income |
0.34 |
8.1% |
9.0% |
Comparison of household income: European Union Statistics on Income and Living Conditions and National Accounts
Annexes:
Annex 7 - Coherence
15.4. Coherence - internal
Not applicable.
Mean (average) interview duration per household = 13.3 minutes.
Mean (average) interview duration per person = 12.3 minutes.
Mean (average) interview duration for selected respondents (if applicable) = N/A.
17.1. Data revision - policy
See link for CSO revisions policy: CSO General Revisions Policy - Central Statistics Office
17.2. Data revision - practice
No planned revisions.
Unplanned historical revisions
Revisions to the national publication of SILC data are typically accompanied by an information notice highlighting the changes.
- SILC 2020 (first published December 17th 2021) was revised on May 6th 2022. Survey weights for 2020 SILC results were adjusted to reflect the estimated household distribution within the rental sector. See Revision to SILC 2020
- SILC 2012-2016 data was revised on December 17th 2018. Data was reweighted to account for the new NUTS3 groupings and new population estimates. See Revisions to SILC 2012-2016
- SILC 2012-2014 was revised on February 1st 2017 due to processing error which resulted in disposable income being underestimated over the period (2012-2014). See Revisions SILC 2017.
- SILC 2010 was revised on February 13th 2013 due to a processing error which affeted income estimates. More information can be found on Press Release Survey on Income and Living Conditions (SILC) 2011.
- SILC 2003 was revised on December 12th 2005. The results were revised following the application of improved re-weighting and calibration methods in line with EU recommendations. See EU-SILC 2004 (with revised 2003 estimates).
- SILC 2020 - 2022 were revised on the [to be added] as a result of revised weights following the receipt of results from Census 2022. Please see Information Note: Census Revisions - SILC 2020 to 2022 - Central Statistics Office
- SILC 2023 was revised on February 29th 2024 as a result of revised weights following the reciept of results from Census 2022.
17.2.1. Data revision - average size
No planned revisions.
Detailed information concerning sampling frame, sampling design, sampling units, sampling size, weightings and mode of data collection can be found in this section (please see below). Such information is mainly used for the computation of the accuracy measures.
18.1. Source data
The annual SILC survey is the main data source for SILC. Information is collected from the head of household and all household members,aged 16 and over, on tablet computers by trained interviewers, using Computer-Assisted Personal Interview (CAPI) or Computer-Assisted Telephone Interview (CATI) software.
In addition, the CSO has access to two primary micro-data sources. These are the Department of Social Protection (DSP) social welfare data and the Revenue Commissioners’ employee income data. The Administrative Data Centre (ADC) division within the CSO securely manage the ownership of these data sources and SILC’s Data Collection Unit has only limited access to the data. The CSO works with the DSP and Revenue, on a continuing basis, to ensure good quality data is available on a timely basis.
DSP data is used in the popoulation of PY090, PY100, PY110, PY120, PY130, PY140, HY050, HY060, HY070.
Revenue data is used in the population of PY010, PY020, PY030, PY050, PY080, PY100, HY110.
Other sources of administrative data include:
- Direct payments paid to farmers e.g. Common Agriculture Policy (CAP) entitlements provided by the Department of Agriculture, Food and the Marine (DAFM) thus enabling the CSO to capture these payments as part of the SILC income calculation for PY050.
- Student Universal Support Ireland (SUSI) provides Ireland’s single national awarding authority for all higher and further education grants. Used in PY140.
- Local Property Tax (LPT) data which is liable on all residential properties in Ireland. Used in HY120, HY121.
- Residential Tenancies Board (RTB) provides private residential rental income data. Used in HY040.
- Housing Assistance Payment (HAP) provides social housing support provided by all local authorities. Used in HY070, HH060.
The CSO is continuously expanding the use of administrative data for SILC.
18.1.1. Sampling Design
In 2022 a new sampling methodology (which was further refined in 2023) was introduced to ensure SILC will be able to meet the precision requirements specified in the IESS regulation. Waves 1, 2 and 3 of the SILC 2024 sample were selected using this methodology. In SILC 2024 Wave 4 , 5 and 6 comes from the 2018 sampling frame.
The following is a brief overview of the revised SILC sample methodology, from which Waves 1 of SILC 2024 was selected:
- The SILC sample is a Stratified Simple Random Sample (SSRS).
- The sample is stratified by county and 10 equivalised income bands.
- Households were selected using probability proportional to size (PPS) of each strata.
- The sampling frame is the 2022 Census, excluding households previously sampled for other social surveys.
The Wave 1 sample methodology for SILC in 2022 was the same as the method used in 2023 and 2024 with the following exception. In 2023 and 2024, wave 1 households were selected using probability proportional to size (PPS) of each strata. In 2022 wave 1 households were selected using Neyman allocation. This involved allocating the sample across the strata according to the variability of income, where strata with large variance were allocated more of the sample.
The following is a brief overview of the 2014 SILC sample methodology, from which Waves 4-6 of SILC 2024 were selected:
- The SILC sample is a multi-stage cluster sample resulting in all households in Ireland having an equal probability of selection.
- The sample is stratified by NUTS4 and quintiles derived from the Pobal HP (Haase and Pratschke) Deprivation Index.
- In the 2018 sample the clusters are based on Census Enumeration Areas, rather than the Household Survey Collection Unit Small Areas used in the 2014 sample.
- A sample of 1,200 blocks (i.e. Census Enumeration Areas, Census 2016) from the total population of blocks is selected.
- Blocks are selected using probability proportional to size (PPS), where the size of the block is determined by the number of occupied households on Census night 2016. 100 households from each block are selected at random to be retained for selection within each block.
- All occupied households on Census night 2016 within each block are eligible for selection in the SILC sample.
- Households within blocks are selected using simple random sampling without replacement (SRS) for inclusion in the survey sample.
2024 Sample Size
Number of sampling units selected in sample: 9,121
Achieved sample size (i.e. accepted interviews)
- Achieved households: 4,885
- Persons aged 16+ who completed a personal interview (including by proxy): 9673
- Total number of persons (all ages) in achieved sample: 12,066
18.1.2. Sampling unit
The initial sample is a sample of private dwellings, taken from the population of private dwellings. A dwelling may contain multiple ‘households’, and only households available for interview are requested to participate. However, data is collected on everyone within the household. The sample excludes individuals living in institutions or communal accommodation and persons of no fixed abode.
The basic units of observation are individuals normally resident in Ireland and Irish households. Until 2019 in defining a ‘household’, the national SILC used an 'address' concept (i.e. all persons living at the same address treated as a single household). From 2020 the national SILC definition of a household has used a shared income and expenditure concept. Flatmates or housemates that do not share expenditure will now be considered as separate households, and students living away from home and substantially supported by their parents will be considered members of the parent household.
18.1.3. Sampling frame
The sampling frame (for the 2024 IE SILC) was the register of all private dwellings occupied on the night of the 2022 Census of Population for wave 1s and 2016 Census of Population for waves 2 to 6.
The final sampling frame used for sample selection excludes all the Island communities, and individuals living in public institution (e.g.prisons, hospitals, nursing homes, etc.), communal accommodation and persons of no fixed abode.
18.2. Frequency of data collection
The data collection period spans the six months of the year from January to June. The sample allocation is distributed evenly throughout the six months with household interviews being conducted on a weekly basis.
18.3. Data collection
Mode of data collection
|
|
1-PAPI |
2-CAPI |
3-CATI |
4-CAWI |
5-PAPI proxy |
6-CAPI-proxy |
7-CATI-proxy |
8-CAWI proxy |
9-other |
|---|---|---|---|---|---|---|---|---|---|
| % of total |
0 |
100% |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
Description of collecting income variables
| The source or procedure used for the collection of income variables |
The form (gross, net) in which income variables at component level have been obtained |
The method used for obtaining target variables in the required form |
|---|---|---|
|
The annual SILC survey is the main data source for SILC. Information is collected from the head of household and all household members, aged 16 and over, on tablet computers by trained interviewers, using Computer-Assisted Personal Interview (CAPI) software. Respondents are asked in interview to supply their Personal Public Service Number (PPSN). The PPSNs are used to link the respondents survey record with any income that may be available for them on the social welfare (SW) or revenue administrative data files. |
Gross/net conversion is required for self-employment income (collected net). |
Gross/net conversion is applied where required, as per flags. |
The annual SILC survey is the main data source for SILC. Information is collected from all household members on tablet computers by trained interviewers, using primarily Computer-Assisted Personal Interview (CAPI) software. The questionnaire is completed using the Blaise application and data is transferred to the CSO’s head office in Cork via a ‘secure tunnel’. To ensure security and confidentiality encrypted data is synchronised on a daily basis using the REACH interface.
Tracing of moved households/persons was implemented for SILC 2024.
Administrative Data Sources
Plausibility and coherence checks are applied to administrative data sources used in the processing of SILC data. SILC staff are members of an internal CSO administrative data user group where any issues with regards to administrative data sources are highlighted and addressed.
Cost-of-Living Measures
In 2022, the Irish Government announced a series of cost-of-living measures aimed at helping households meet higher costs. These cost-of-living measures included direct payments to individuals and households through social transfer and indirect measures in the form of electricity credits. Direct payments are included in their appropriate social transfer variables. Indirect measures (electricity credits) are not included in household income (HY070) not housing costs (HH070)
Between March and May 2022, the following cost-of-living measures, aimed at helping households pay higher energy bills were introduced:
- a €125 lump sum Fuel Allowance paid in March 2022 to all households that were in receipt of the Fuel Allowance;
- a €100 lump sum Fuel Allowance paid in May 2022 to all households that were in receipt of the Fuel Allowance.
In July 2022, the rates of payments for the Back-to-School Clothing and Footwear Allowance scheme were increased by €100 for each eligible child.
Budget 2023 contained additional cost-of-living measures that were paid to individuals and households during 2023. Budget cost-of-living measures that were paid/implemented in 2023 included:
- Two universal €200 energy credits applied to domestic electricity customer accounts in January 2023 and in March 2023.
Additional cost-of-living supports were announced in February 2023 which included:
- €200 lump sum payment to be paid in April to people in receipt of long-term social welfare payments;
- €200 payment for Working Family Payment recipients who have not received the lump sum on their primary payment, to be paid in April;
- €100 Child Benefit additional lump sum payment per child;
- €100 one-off increase in the Back-to-School Clothing and Footwear Allowance.
Budget 2024 contained additional cost-of-living measures that were paid to individuals and households during the latter part of 2023 [insert link]. Budget cost-of-living measures that were paid/implemented in 2023 included:
- a double monthly payment for Child Benefit for each child on 5 December 2023;
- a €300 lump sum Fuel Allowance payment to all households that were in receipt of the Fuel Allowance;
- a €200 cost-of-living lump sum payment for pensioners and people in receipt of the Living Alone Increase;
- a €400 cost-of-living lump sum payment to recipients of the Working Family Payment;
- a €400 cost-of-living lump sum payment for people getting the Carer's Support Grant;
- a €400 cost-of-living lump sum for people in receipt of Disability Allowance, Invalidity Pension or Blind Pension;
- a €100 cost-of-living lump sum payment for people with a qualified child;
- a universal €150 energy credit applied to domestic electricity customer accounts in December 2023.
The income reference period of SILC in year T is the calendar year T-1, therefore 2024 poverty rates were calculated by using January to December 2023 income. The electricity credits that households received in 2023 are treated as income in the SILC survey.
Annexes:
Annex 4 - Data Collection
18.4. Data validation
The annual SILC survey is the main data source for SILC. Information is collected from all household members on tablet computers by trained interviewers, using Computer-Assisted Personal Interview (CAPI) software. The data is captured using Blaise software. The Blaise dataset is available as an ASCII file and this is converted into a SAS dataset before being further processed. Certain variables are transferred into the CSO’s Data Management System (DMS) where extensive editing and data cleaning is conducted. Many questions only allow answers to be entered to a limited set of predefined categories and therefore the number of edits required is limited. Questionnaire routing is used to ensure questions are only asked to relevant respondents. In addition, invalid responses are prevented at the point of capture where appropriate and this ensures that implausible data is prevented from being captured.
In addition, the CSO has access to two primary micro data sources. These are the Department of Social Protection (DSP) social welfare data and Revenue Commissioners’ employee income data. The Administrative Data Centre (ADC) division within the CSO owns these data sources and SILC’s DCU has limited access to them. The CSO works with the DSP and Revenue, on a continuing basis, to ensure good quality data is available on a timely basis. Revenue Real Time data and payments data from the DSP are entered into the CSO’s DMSsystem. Much of the income micro-data comes directly from administrative sources such as revenue and the department of social protection. The availability of such good quality micro-data considerably reduces the possibility of measurement error in the measurement of direct incomeand social transfers. This also reduces the burden on the SILC DCU section in micro-editing these complex variables.
SILC DCU staff work on editing the SILC data throughout the year. Editing of the SILC data begins at the earliest opportunity. Full instructions are sent out to the field interviewers on how to clear the edits. The section manual outlines how these queries on the edits are to be dealt with. The next stage of editing takes place when the data is entered in the DMS. Detailed instructions are in the section manual outlining how these edits are to be resolved. Once the data is cleaned using the above edits more detailed checking of incomes is conducted using SAS. At this stage, outliers in the micro-data are reviewed and inconsistencies in the longitudinal data are further investigated. The cleaned data is then forwarded to the SILC Reporting and Analysis section where extensive macro-editing is completed to benchmark SILC results against Revenue and Department of Social Protection aggregated data thus ensuring coherency with these known figures. At this final stage, any discovered anomalies in the data (or process) are reviewed and resolved where possible.
18.5. Data compilation
See 18.5.1 - 18.5.3.
18.5.1. Imputation - rate
The imputation rate was around 2%.
18.5.2. Calculation of weighting factors and weight adjustments
See Annex 5 attached.
Annexes:
Annex 5 - Weighting
18.5.3. Estimation and imputation
See Annex 6 attached.
Annexes:
Annex 6 - Estimation & Imputation
18.6. Adjustment
Not applicable.
18.6.1. Seasonal adjustment
Not applicable.
See Annex 9 attached.
Annexes:
Annex 9 - Rolling Module
The European Union Statistics on Income and Living Conditions (EU-SILC) is a survey-based instrument aiming at collecting timely and comparable cross-sectional and longitudinal multidimensional microdata on income, poverty, social exclusion and living conditions. In addition, it collects module variables every three years, six years or ad-hoc new policy needs modules.
The EU-SILC instrument provides two types of data:
- Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions
- Longitudinal data pertaining to individual-level changes over time, observed periodically over four‐or more year rotation scheme (Annex III (2) of 2019/1700). Social exclusion and housing condition information is collected mainly at household level while labour, education and health information is obtained for persons aged 16 and over. The core of the instrument is income information at very detailed component level and mainly collected at personal level.
28 March 2025
Statistical concepts and definitions for EU-SILC are specified in Regulation (EU) 2019/1700, Commission Implementing Regulation (EU) 2019/2181, and Commission Implementing Regulation (EU) 2019/2242. Additional information is available in the EU statistics on income and living conditions (EU-SILC) methodology and in the methodological guidelines and description of EU-SILC target variables (see CIRCABC).
Further details are provided in items 5, 15.1.1.1, 15.2.2 and 18.3.
Statistical units are private households and all persons living in these households who have usual residence in the Member State. Annex II of the Commission implementing regulation (EU) 2019/2242 defines specific statistical units per variable and specifies the, content of the quality reports on the organisation of a sample survey in the income and living conditions domain pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council.
The target population is private households and all persons composing these households having their usual residence in the Member State. Private household means a person living alone or a group of persons who live together, providing oneself or themselves with the essentials of living.
The survey population is all private households and their current members residing in the state at the time of the data collection along with inhabitants of the following off-shore islands:
Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia.
All other offshore islands are excluded from the sample frame as they account for less than 2% of the total population.
Description of reference period used for incomes
| Period for taxes on income and social insurance contributions |
Income reference periods used |
Reference period for taxes on wealth |
Lag between the income ref period and current variables |
|---|---|---|---|
| Income reference period. |
Up until 2019 the IE SILC income reference period was the 12-month period immediately preceding the sample household's interview date. This resulted in a 24-month income reference period for each annual SILC survey. Commencing with the 2020 IE SILC,the SILC income reference period will be the T-1 calendar year. |
Income reference period. |
Data collection is the first six months of the year. The income reference period is the T-1 calendar year. Thus the lag beween income reference period and the current variables can be up to six months. |
According to Reg. (EU) 2019/1700 Annex II, precision requirements for all data sets are expressed in standard errors and are defined as continuous functions of the actual estimates and of the size of the statistical population in a country or in a NUTS 2 region. For the income and living conditions domain, the estimated standard errors of the following indicators are examined according to certain parameters set:
- · Ratio at‐risk‐of‐poverty or social exclusion to population;
- · Ratio of at‐persistent‐risk‐of‐poverty over four years to population;
- · Ratio at‐risk‐of‐poverty or social exclusion to population in each NUTS 2 region.
Further information is provided in section 13.2 Sampling error.
The data involves several units of measure depending upon the variables. Income variables are transmitted to Eurostat in national currency. For more information, see methodological guidelines and description of EU-SILC target variables available on CIRCABC
See 18.5.1 - 18.5.3.
The annual SILC survey is the main data source for SILC. Information is collected from the head of household and all household members,aged 16 and over, on tablet computers by trained interviewers, using Computer-Assisted Personal Interview (CAPI) or Computer-Assisted Telephone Interview (CATI) software.
In addition, the CSO has access to two primary micro-data sources. These are the Department of Social Protection (DSP) social welfare data and the Revenue Commissioners’ employee income data. The Administrative Data Centre (ADC) division within the CSO securely manage the ownership of these data sources and SILC’s Data Collection Unit has only limited access to the data. The CSO works with the DSP and Revenue, on a continuing basis, to ensure good quality data is available on a timely basis.
DSP data is used in the popoulation of PY090, PY100, PY110, PY120, PY130, PY140, HY050, HY060, HY070.
Revenue data is used in the population of PY010, PY020, PY030, PY050, PY080, PY100, HY110.
Other sources of administrative data include:
- Direct payments paid to farmers e.g. Common Agriculture Policy (CAP) entitlements provided by the Department of Agriculture, Food and the Marine (DAFM) thus enabling the CSO to capture these payments as part of the SILC income calculation for PY050.
- Student Universal Support Ireland (SUSI) provides Ireland’s single national awarding authority for all higher and further education grants. Used in PY140.
- Local Property Tax (LPT) data which is liable on all residential properties in Ireland. Used in HY120, HY121.
- Residential Tenancies Board (RTB) provides private residential rental income data. Used in HY040.
- Housing Assistance Payment (HAP) provides social housing support provided by all local authorities. Used in HY070, HH060.
The CSO is continuously expanding the use of administrative data for SILC.
Annual
The national results for SILC 2024 were released on the CSO website on the following date:
- On 11th March 2025, results from SILC were published as the first stage focusing on Deprivation for the Survey on Income and Living Conditions (SILC) 2024: Enforced Deprivation.
- On 20th March 2025, results from SILC were published as the final release focusing on Income and Poverty for the Survey on Income and Living Conditions (SILC) 2024.
Data collection period for SILC 2024: 01 January - 30 June 2024
Date of the first fully validated delivery of data: 22 December 2024
Number of days between the end of fieldwork and the first fully validated delivery of data to Eurostat: 175 days
Income reference year: 01 January -31 December 2023
Number of days between end of reference year and to the day of publication of the first results: 436 days
Not applicable - IE data for each NUTS2 region come from the same sources.
See Annex 8 (Breaks in Series) attached.
Annexes:
Annex 8 - Break in Time Series
