Statistics Austria

Directorate: Social Statistics
Unit: Social and Living Conditions

Guglgasse 13, 1110, Vienna, Austria

28 May 2025

18 November 2025

24 October 2025

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:

1. Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions;
2. Longitudinal data pertaining to individual-level changes over time, observed periodically over four‐or more year rotation scheme (Annex III (2) of 2019/1700). EU-SILC Austria provides longitudinal data pertaining to a four year rotation scheme. 

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.

• 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 - 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.

Note that due to a very small number of respondents in Austria with ISCED level 0, i.e., less than primary education (primary education is compulsory in Austria),  these respondents are lumped together with the ISCED level 1 category, i.e. primary education. 

Data refer to all private households and individuals living in the private households in the national territory (Austria) 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.

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, 15.2.2 and 18.3.

Statistical units are private households and all persons living in these households who have usual residence in Austria.

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 organization 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 Austria. 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 sub-populations that are not covered by the data collection include:

1. those who have moved out of Austria's territory; or
2. those who have no usual place of residence; or
3. those living in institutions; or
4. those who have moved into an institution compared to the previous year.

EU-SILC in Austria covers all of Austria, i.e., the whole geographical area.

Annual data, reference year 2024. The income reference period is the calendar year 2023.

EU-SILC in Austria has been carried out annually since 2004 based on a rotational panel design . The income reference period is always the year preceding the survey year.

Please also refer to the descriptions of reference periods in section 5.

Not applicable.

The data involves several units of measure depending upon the variables. Income variables are transmitted to Eurostat in national currency (EUR).

For more information, see methodological guidelines and description of EU-SILC target variables available on CIRCABC.

EU Regulation (EU) 2019/1700 was published in the OJ on October 10, 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 December 16, 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.

At national level, the Ordinance of the Federal Minister of Labour, Social Affairs and Consumer Protection on Statistics on Income and Living Conditions (Income and Living Conditions Statistics Ordinance - ELStV; Federal Law Gazette II No. 277/2010) was issued on 31 August 2010, which regulates the collection and linking of administrative data records. This ordinance was amended in 2013 (Federal Law Gazette II, No. 230/2013), in 2018 (Federal Law Gazette II, No. 313/2018), in 2019 (Federal Law Gazette II No. 319/2019), in 2021 (Federal Law Gazette II No. 38/2021) and most recently in 2024 (Federal Law Gazette II No. 80/2024). The currently valid version can be found at the Legal Information System of the Republic of Austria (in German).

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.

At national level, Statistics Austria provides selected anonymised microdata standardised data sets (SDS) and as task-specific data sets (ADS) for use in scientific research and education. In the sense of statistical secrecy and as a measure of data protection, the data are anonymised so that a direct or indirect identification of a concrete individual case is de facto impossible. 

SDS can be downloaded after registration and activation. By registering, users agree to the terms of use. For more information, see part 8. Additional information about microdata access is available at Center for science and especially part 10.4. 

Data published or made available as micro-data are fully anonymized. No confidential data are involved.

Linking to other data sources (register data) is done according to the national regulation using a fully anonymized key.

User data are fully anonymized, regional variables below NUTS2 and some other variables (e.g. day and month of birth) are excluded, and several variables (e.g. age above 80 years, country of birth, size of dwelling etc.) are recoded to prevent from identification.

For tables and indicators small cells are masked (based on sample size or standard error).

Austrian EU-SILC data are published annually, in April the following year. The data for EU-SILC 2024 were published on 29^th of April 2024.

The main tables are available on the Statistics Austria' EU-SILC Website (poverty and household income).

Please refer to the Release calendar - Eurostat (europa.eu) publicly available on the Eurostat’s website as well as to Statistics Austria's release calendar.

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. 

At national level, Statistics Austria provides selected anonymised microdata standardised data sets (SDS) and as task-specific data sets (ADS) for use in scientific research and education. In the sense of statistical secrecy and as a measure of data protection, the data are anonymised so that a direct or indirect identification of a concrete individual case is de facto impossible. 

SDS can be downloaded after registration and activation (for more information on how to gain access see part 10.4). 

Annual.

The main results for 2023 are available Statistics Austria' EU-SILC Website (poverty and household income). 

The press release from 25 April 2024 can be found on the following links:

• Press release in Englsh
• Press release in German

An overview of publications can be found on the Website on Poverty and on Household income (content can vary on German and English site):

1. Statistics Austria webpage on poverty and 
2. Statistics Austria webpage on household income

Besides these EU SILC-specific publications, there are also other publications containing results from EU-SILC in other thematic publications of Statistics Austria (e.g. housing, migration and immigration, education, SDGs etc.).

Data as pre-published tables and indicators can be accesses on the Statistics Austria' EU-SILC Website (poverty and household income). 

Micro-data for national users (for scientific research and education purposes) is available after registration, by providing information about the purpose of use, as well as identifying the persons that will gain access. By registering, users agree to the terms of use. Additional information about microdata access is available at the Center for science (see 10.4).

Tables or Micro-data for international comparisons can be applied for at Eurostat. Contact point: estat-microdataaccess@ec.europa.eu. For more details, see access to microdata and Publications on the basis of European microdata CROS (europa.eu).

Not available.

The EU-SILC micro-data for national users (for scientific research and education purposes) is available after registration, by providing information about the purpose of use, as well as identifying the persons that will gain access and agreeing to the terms of use (in German).

The use of Austrian data from EU-SILC can be requested from Statistics Austria (Contact: +43 (1) 71128 8285, richard.heuberger@statistik.gv.at)

The cross-sectional data sets have been available since the start of the survey (2003). The anonymised datasets contain the non-monetary questionnaire variables as well as the aggregated and imputed income components according to the EUROSTAT target variable logic (EUROSTAT). The data are made available free of charge for scientific purposes. Compliance with the terms of use by the project staff must be ensured by the respective project management.

For the use of the data in courses, compliance with the terms of use of the data must be ensured by the course instructor through appropriate measures (e.g. signature list). This includes in particular that the data is not used beyond the purpose of the course.

The data from EU-SILC is also used for academic theses.  In this case the professor who supervises the thesis must be named as the project leader and must therefore comply with the the data usage conditions. The data usage agreement must also be signed by the supervisor. 

By registering, users agree to the terms of use. Additional information about microdata access is available at the Center for science (more EU-SILC relevant information is available on the German version of the website). 

Tables or Micro-data for international comparisons can be applied for at Eurostat. Contact point: estat-microdataaccess@ec.europa.eu. For more details, see access to microdata and Publications on the basis of European microdata CROS (europa.eu).

See also parts 6.2, 8, and 9.3, and 10.3.

The EU SILC results are of great interest to the policy makers in Austria (for e.g. the Federal Ministry for Social Affairs, Health, Care and Consumer Protection), researhers, as well as the media. Thus, next to the data published in the publications described in parts 10.1 to 10.4, EU-SILC results can be also found in

• other thematic publication formats of Statistics Austria (e.g. housing, migration and immigration, education, SDGs etc.)
• Publication of articles in policy and scientific papers (for example the Social report 2024 (German only))
• Scientific user conferences organized by Statistics Austria every few years
• lectures, talks, and TV-debates (for e.g. TV debate Childhood poverty, or the presentation of the social report 2024, both German only)
• Statistics Austria social media channels,
• news articles, etc.

Not available.

Tha national quality report in German can be found on the on the Statistics Austria' EU-SILC Website (poverty and household income). A short English version is also available on the same website (under Documentation > Standard Documentation).  

For more information on the metadata on the income benefits, please refer to Annex 10: Metadata on benefits.

100%

Product quality is at the centre of Statistics Austria's quality work. In order to be able to achieve a sufficient quality for statistical products, it is necessary to comply with specified standards in the respective process steps. In order to ensure this, Statistics Austria has created guidelines that relate to all topics that are relevant to the statistical production process. The aim of the quality guidelines is, on the one hand, to give the employees of Statistics Austria a reference for all relevant process steps and, on the other hand, to convey to users that compliance with certain standards is mandatory for the products of Statistics Austria.

Statistics Austria's Quality Guidelines can be downloaded from Statistics Austria's Website information on standards. See also parts 11.1 and 11.2.

The quality managment for the EU SILC survey is described in the national quality reports (in German) that can be found at Statistics Austria' EU-SILC Website (poverty and household income)

The quality management unit as shown in the organizational structure of Statistics Austria is a centralized unit reporting directly to the Director General for Statistics. The competences and tasks of the quality management unit comprise all components of the quality policy of Statistics Austria.

Product quality is a central part of the Quality Commitment Statement. Quality reports are available for all statistical products (part of the Standard-Documentations) for monitoring product quality, as well as Statistics Austria’s quality guidelines, Since 2004 Statistics Austria performs a series of so called "Feedback-Talks" on Quality based on the Standard Documentations (including quality reports). All major statistical products are covered by the set of Standard-Documentations. The feedback talks are conducted in close cooperation with the Quality Subcommittee of the Statistics Council.

In 2010 Statistics Austria elaborated quality guidelines covering all stages of the statistical production process. The full version of quality guidelines is available on the website of Statistics Austria:

1. German version 
2. Summary in English 

Statistics Austria participated in the latest round of European Peer Reviews from April 4th to 8th, 2022. All information about the peer review, including previous rounds and links to the report can be found on Statistics Austria’s web site.

The main users of EU-SILC statistical data are policy makers, research institutes, media, and students.

On average, the EU-SILC team at Statistics Austria processes about 60 data requests per year. Users are mainly universities, research institutes and scientific departments of public institutions. EU-SILC data are mainly used for scientific research and academic degrees. Statistics Austria provides user with the income target variables, the national questionnaire variables for non-income variables and some calculated indicator variables.

Eurostat carried out an online general User Satisfaction Survey (USS) in 2024 to obtain a 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, since the topic “Population and social conditions” was the one in which the users were most interested in (page 17). For the majority, both aggregates and micro-data were important or essential in their work irrespective of the purpose of their use. 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 User Satisfaction Survey 2024 (and previous years).

The following variables have not been collected for EU-SILC in Austria. The reason for not collecting is explained below.

PY020G/PY020N:

From 2014 onwards Statistics Austria decided to exclude all questions on non-cash employee incomes, since modelling was starting to get problematic and since incomes from these sources are not that important in Austria. Additionally, these incomes are not included in the computation of household incomes.

PY021G/PY021N 

is fully included in PY010G/PY010N.

HY120G/HY120N:

There are no taxes on wealth in Austria.

HY121G/HY121N:

There are no taxes on wealth in Austria.

HY145N:

HY145N is not delivered because this variable is filled only for countries that record net income at the component level only.

HY170G/HY170N:

From EU-SILC 2011 onwards HY170G is no longer collected because of it is not regarded as a relevant component of the household income (amounts are too small).

Optional variables:

RL080:

Not collected in order to reduce respondent burden.

HI130G:

Not collected in order to reduce respondent burden.

HI140G:

Not collected in order to reduce respondent burden.

Not requested by Reg. 2019/2180.

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.

EU-SILC is a complex survey involving different sampling designs in different countries. In order to harmonize and make sampling errors comparable among countries, Eurostat (with the substantial methodological support of Net-SILC2) has chosen to apply the "linearization" technique coupled with the “ultimate cluster” approach for variance estimation.

Linearization 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 in 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:

1. 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;
2. 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;
3. 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 more information, please refer to Annex 3 on sampling errors.

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.

Statistics Austria uses a calibrated bootstrap procedure for standard error estimation of indicators in EU-SILC. Recalibration of bootstrap weights is carried out by considering geographic, sociodemographic as well as income and activity status characteristics that are also marginal distribution for the calibration of household weights. The R Package “surveysd” developed by the Methods Department of Statistics Austria is applied for this work. In EU-SILC 2024 this recalibration procedure of the bootstrap replicates weights was extended to the longitudinal weight RB064 in order to take into account the effect of the calibration of longitudinal weights on the standard error of the persistent at-risk-of-poverty-rate (the calibration procedure for longitudinal weights is described in Annex 5). 

The standard errors, and the confidence intervals of the main indicators at country level (AT) and NUTS2 levels are presented in Annex A. Annex A also included the standard errors and confidence intervals of the persistent-risk-of-poverty ratio over four years.

For more information on sampling errors, please also refer to Annex 3.

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

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

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

Frequency of timing between the sampling frame and the target population:

In 2024 there was anywhere between four months (start of data collection) and ten months (end of data collection) discrepancy between the drawing of the sample and the target population. The sample frame was drawn from the central residence register with cut-off date 30 September 2023. People who moved in or out of a private household in Austria between this date and the period of data collection (February to July 2024; for more see parts 3.3, 5, 14.1, and 18) are under, i.e., overrepresented in the sample, respectively.  

This discrepancy may lead to both over- and under-coverage (see 13.3.1.1). 

Not requested by Reg. 2019/2180.

1) CAPI = Computer Assisted Personal Interviewing; CATI = Computer Assisted Telephone Interviewing; CAWI = Computer Assisted Web Interviewing

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:

1) 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.

2) 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.

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 which refers to the absence of information of the whole units (households and/or persons) selected into the sample. According to the Commission implementing regulation (EU) 2019/2180 specifying content of the quality reports on the organization 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.

For the longitudinal unit-non-response data and the response rate please refer to Annex A.

Note. In 2024, 75 Households were excluded for quality reasons even though they did initially participate in the survey (or at least some of the adult household members participated). Despite participation they returned incomplete interviews and thus were excluded from the net sample. These interviews are coded with db135 = 2, interview rejected and in this variable are indistinguishable from those that refused to participate completely. 

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.

Please refer to Annex 2 on item non-response.

For re-interview rates by wave, sex and age of the respondents please refer to Annex A.

There are no models used in treatment of specific sources of error.

Pursuing annex V of the IESS regulation, Member States shall submit for the Income and Living Conditions domain pre-checked microdata without direct identifiers, according to the following deadlines (IESS Regulation (EU) 2019/1700 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples):

• By the end of year N, submission of cross-sectional and longitudinal variables for the data collection of year N, including cross-sectional weights.
• In exceptional cases, microdata concerning income variables may be submitted as provisional data.
• By 28 February of year N+1, receipt of revised, final income data is expected.
• By the end of October of year N+1, at the latest, longitudinal weights are to be submitted to complete the data files.

Number of days between the end of fieldwork and the first fully validated delivery of data to the Commission (Eurostat):

• End of field-work: 30 July 2024
• First data delivery: 20 December 2024
• Days between the end of fieldwork and the first fully validated delivery: 213 days.

Date of the first full delivery of data to the Commission (Eurostat). 28 February 2025.

Months between end of reference year N (2024) and the first fully validated delivery: 0

Months between end of reference year N (2024) and the final fully validated delivery: 2

Date of the dissemination of national results: 29 Aprtil 2025

On the following link you can find Statistics Austria's press release calendar.

The number of days (or weeks or months) from the last day of the reference period to the day of publication of first results.

National publication date: 29 April 2025 – 5 months after the end of the reference period (first results = final results)

The press release from 29 April 2025 can be found on the following links:

• Press release in English
• Press release in German

On the following link you can find Statistics Austria's press release calendar.

The number of days (or weeks or months) from the last day of the reference period to the day of publication of first results.

National publication date: 29 April 2025 – 5 months after the end of the reference period (first results = final results)

The press release from 29 April 2025 can be found on the following links:

• Press release in English
• Press release in German

On the following link you can find Statistics Austria's press release calendar.

Time lag between the actual delivery of the data and the target date when it should have been delivered.

First delivery (due date 31 December 2024, delivery 20 December 2024): -11 days

Final delivery (due date 28 February 2025, delivery 28 February 2025): 0 days

The number of months between the delivery/release date of (national) data and the target date on which they were scheduled for delivery/release. 

National publication (due date 29 April 2025, publication 29 April 2025): 0 days

The number of months after end of reference year N (2024), data were published at national level: 5 months.

The percentage of data release delivered on time: 100%

There are no conceptual differences between results on national level and NUTS2 level except for the size of the confidence intervals. The standard errors are larger for the NUTS region, since the regions and the resulting sample sizes are smaller. To adjust for this discrepancy, the national publication strategy is to publish 3-year averages for NUTS2-results. This strategy aims to smooth yearly differences due to small sample sizes.

Not applicable.

Please refer to Annex 8 - Breaks in Series.

There are no significant breaks because of data collection methodology since 2008 (when data collection via data registers was introduced)

A break in series for the main (AROPE) indicator from 2021 onwards, due to the new definition and implementation of the new regulation. Nationally however, the new AROPE indicator is back calculated and published from 2018 onwards.

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.

Detailed Income information in the Austrian HBS is imputed from EU-SILC based on a statistical matching procedure. Therefore, comparison of EU-SILC and HBS in terms of income variables is not meaningful for Austria.

For more information, please refer to Annex 7 on coherence.

Not applicable.

1. estimated value, as for disposable income only one estimate is produced for NPOs and private households
2. estimated on the basis of the population prognosis
3. estimate for 1.3% of the total consumption expenditures based on the Household budget survey (HBS) 2019/20 
4. National accounts 2023

For additional comparison and growth rate information for the income variables please refer to Annex 7 - Coherence.

There are no known inconsistencies within the data sets of EU-SILC 2024.

Mean (average) interview duration per household = 41.9 minutes.

Mean (average) interview duration per person = 15.7 minutes.

No foreseen data revision for EU-SILC 2024 as of May 2025.

Potential new data deliveries, if necessary, are unlikely to affect the central indicators (e.g. if some changes to hy022 or hy023 are necessary). When results remain unchanged this is no revision. Since micro-data have not yet been disseminated to users (other than Eurostat), these potential changes are not relevant for users.

If under any circumstances the need for a data revision occurs this will be communicated with full transparency (e.g. by adding an “Erratum”- Section in the Book of Tables and by providing the date and type of change, the variables and/or indicators that were affected etc.).

No revisions planned.

For the general revision policy see 17.1

No revisions planned.

For the general revision policy see 17.1

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.

The sampling frame for the first wave (for more see 18.1.1) households of EU-SILC 2024 was based on the central residence register (Zentrales Melderegister - ZMR). The ZMR is a continuously updated population register based on the registration of the main residence. It contains basic demographic information about the person (for e.g. date and place of birth, citizenship, etc.) as well as the address(es) of a person. The ZMR is administrated by the Federal Ministry of the Interior (BMI). Data of the ZMR are delivered quarterly to Statistics Austria.

In order to facilitate more complex sampling and estimation procedures, the ZMR information For EU SILC is supplemented by socioeconomic and demographic variables from administrative registers. Linkage for the merging of the ZMR information with administrative register data was carried out by a pseudonymized ID key (bereichsspezifisches Personenkennzeichen - bPK).

The ZMR was filled in for the first time after the census in 2001 by merging the municipal population registers and is since continuously updated on the basis of the municipalities' residence notifications. It contains the respective address data of the registered main and secondary residences for all persons registered in Austria. When merging the address data of different persons of a household, different spellings of the address may lead to unrecognized residential connections. As a rule, there is exactly one household at a given address. In rare cases, however, there may be several households, understood as economic units, at one address. Whether an address contains several households can only be clearly determined in the course of the data collection. Furthermore, it must be taken into account that the ZMR information does not always correspond to the reality, i.e. sometimes the actual household composition collected during the interview differs from that in the ZMR.

In 2024, 4,479 addresses were selected at the beginning of the fieldwork to constitute the rotational group 1 (and 1,492 addresses were drawn as a reserve). The reference date for the sampling frame of EU-SILC 2024 was the 30th of September 2023. Addresses sampled in the previous waves of EU-SILC 2021-2023 as well as addresses selected for other household surveys where the fieldwork overlapped by up to plus or minus 3 months with the EU-SILC fieldwork were excluded from the sampling frame. This was carried out by using socio-demographic variables in combination with the available income information. This so-called "rich frame" was used to train a machine learning model for estimating the AROPE for the whole frame before the field work. This predicted AROPE was used as a sub-stratification criterion within each NUTS2 province variable.

As in the previous years, for EU-SILC 2024, the data was not only collected via household interviews. Essential components of the household income were calculated from administrative data sources. About 87% of the volume of the total income of a household is calculated from administrative data. The rest (e.g. income from self-employment) is surveyed during the interviews.

The table below describes the income data that is collected from administrative registers data and is used for the measurement of the income components for EU-SILC. 

Sampling design

EU-SILC in Austria uses an integrated rotational design meaning that each year about one fourth of the sample is replaced by a new rotational group.  EU-SILC 2023 was the 20th year of EU-SILC in Austria as a panel. Each rotational group of the sample 2023 entered the survey in a different year:  2020 (R4), 2021 (R1), 2022 (R2) and 2023 (R3).

Stratification and sub stratification criteria 

The first wave sample of EU-SILC 2024 is a one-stage stratified probability sample. The sample of the first wave was stratified according to 18 strata that where comprised of the 9 Austrian provinces (NUTS 2 units) subdivided into 2 groups that were defined by an estimation of the main indicator "at risk of poverty or social exclusion" (AROPE). To accomplish this, a machine learning model (random forest) for estimating AROPE for the entire rich frame was applied and thus made it possible to use this estimated dichotomous variable as a sub-stratification criterion. The aim of the sub-stratification with characteristics that are highly correlated with the main income-based indicators of EU-SILC was to achieve a more efficient sample and a smaller standard error for the AROPE indicator. 

Sample size and allocation criteria

The first wave sampling process was carried out according to a stratified one-stage probability sample with systematic sample selection without replacement and disproportional allocation. 4 479 addresses for the first wave rotational group of 2024 (R4/24) were planned for selection. The number of selected households was determined as approximately 0.1% of all eligible addresses. The sample design for the initial EU-SILC 2024 survey was adapted with regard to the allocation per province compared to the previous year. Since 2021, the allocation criterion has been the precision of the risk of poverty or exclusion (AROPE) indicator in the cross-section (based on the latest available results from EU-SILC). The aim of this sample design is to obtain the most precise sample possible (in terms of the standard error of AROPE). Therefore, the allocation of the sample for SILC 2024 per province was adjusted with respect to Eurostat's precision specifications. The precision of the sample defined by Eurostat in terms of the standard error (SE) of AROPE per province was taken into account. For each province, it was calculated how much larger the sample would have to be to meet the precision requirements. The resulting distribution of addresses to be drawn was then scaled to the required gross sample. 

In the end, the gross sample consisted of 9783 households, i.e., 4901 households for the first rotational year (2024) and 4822 households for the follow-up years (of which 2029 were in the second year, 1464 in the third year, and 1329 in the forth year). The 4901 households included 419 extra addresses added from the reserve adresses (see 18.1) in order to achieve the required sample size, as well as three additional households in the first wave, which were identified as shared flats.

The follow-up addresses are the addresses that were successfully interviewed in 2023, i.e., part of the EU SILC 2023 database.

Note that 20 sample households in wave 2+ that couldn’t be accessed due to temporary conditions during the field work in previous years (2022 or 2023) were not followed in 2024, although they should have been followed according to Doc 65 (p. 625 f). This processing error will be fixed from 2025 onwards.

The achieved sample size was 6193 households, i.e., 2071 households who took part in EU SILC for the first time in 2024, and 4122 household who were already part in the previous waves of EU SILC (1625, 1283, and 1214 for the second, third and fourth year respectively). 12672 people were registered in these 6193 households, 10625 of which as 16 or older and thus potentially eligible for a personal interview. From them 12556 interviews were accepted in the EU SILC 2024 database, 12514 of which for household members 16 or older. 37 of these 12514 interviews were fully imputed. 

Sampling units are dwelling units registered in the central residence register (ZMR). The sampling frame consisted of all accommodations with at least one person aged 16 years or older who has their main registered residence (Hauptwohnsitzmeldung) in these accommodations. Institutional housing facilities, dwelling units where no person with a main residence in the dwelling is 16 years or older were excluded from the sample. Units that have been selected for the prior samples of EU-SILC were excluded as well.

The sampling frame of the first wave households of EU-SILC 2024 was based on the the central residence register (Zentrales Melderegister -ZMR). The ZMR is a continuously updated population register based on the registration of the main residence. It contains information on the person (date and place of birth,etc.) and on the address(es) of a person. The ZMR is administrated by the Federal Ministry of the Interior (BMI). Data of the ZMR are delivered quarterly to Statistics Austria. In order to facilitate more complex sampling and estimation procedures of the ZMR information needed for sampling was enriched by socioeconomic and -demographic variables from administrative registers. Linkage was carried out by a pseudonymized key (bereichsspezifisches Personenkennzeichen - bPK).

 For the national questionnaires (German and English), please refer to Annex 1 – National questionnaires. For the mode of data collection per rotation, please refer to Annex 4 - Data collection.

Checks to detect processing errors have been implemented in the electronic questionnaire. Validation applied during post-data-collection-processing includes formal data checks as well as checks for plausibility and consistency which use longitudinal or external information. Detected errors or inconsistencies are fed back for validation to the interviewer concerned, they are either corrected or approved and can also lead to an adjustment of questions or interviewer guidelines in the next year’s survey.

For further information, please refer to the Annexes of this section.

Please see Parts 13.3.4, 18.5 and the information provided in the Annex 6 on imputation (Part 18.5.3.).

Please see the information provided in the Annex 5 on the weighting procedure.

Please see the information provided in the Annex 6 on imputation and estimation.

Not applicable.

Not applicable.

Information on the quality of the rolling module can be found in the questionnaire attached to this section.