Poverty and social exclusion (tipspo)

Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Eurostat, the statistical office of the European Union


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes
Footnotes



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Eurostat, the statistical office of the European Union

1.2. Contact organisation unit

Eurostat, C1, National accounts methodology. Indicators

1.5. Contact mail address

Office address:
Joseph Bech building
5, Rue Alphonse Weicker
2721 Luxembourg

Functional mail box: ESTAT-MIP@ec.europa.eu


2. Metadata update Top
2.1. Metadata last certified 26/03/2024
2.2. Metadata last posted 20/11/2023
2.3. Metadata last update 20/11/2023


3. Statistical presentation Top
3.1. Data description

The main source for the compilation of statistics on income, social inclusion and living conditions is the EU-Statistics on Income and Living Conditions (EU-SILC). EU-SILC collects timely and comparable multidimensional microdata on income, poverty, social exclusion and living conditions.

The EU-SILC collection is a key instrument for providing information required by the European Semester and the European Pillar of Social Rights, and the main source of data for microsimulation purposes and flash estimates of income distribution and poverty rates. For more information, please consult EU social indicators.

The indicator People at risk of poverty or social exclusion and its sub-populations (People at risk of poverty after social transfers, Severely materially and socially deprived people and People living in households with very low work intensity) are part of the set of MIP auxiliary indicators.

3.2. Classification system

The EU-SILC results are produced in accordance with the relevant international classification systems. The classifications used in EU-SILC are described in the methodological guidelines and description of target variables 2021 in CIRCABC.

The classifications used in the EU-SILC are based on international systems:

-        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);

-        The recommendations made by the United Nations in the Canberra Group Handbook on Household Income Statistics should also be taken into account.

3.3. Coverage - sector

Not applicable.

3.4. Statistical concepts and definitions

The definitions of the MIP relevant indicators are the following:

  • People at risk of poverty or social exclusion (% of total population) - Persons who are at risk of poverty, or severely materially deprived, or living in households with very low work intensity. Persons are only counted once even when they are present in more than one of the three sub-indicators.
  • People at risk of poverty after social transfers (% total population) - Persons with an equalised disposable income below the risk-of-poverty threshold, which is set at 60 % of the national median equalised disposable income (after social transfers) as a % of total population.
  • Severely materially and socially deprived people (% total population) - Persons having living conditions which are severely constrained by a lack of resources, such that they experience an enforced lack of at least 7 out of the following 13 deprivation items: i) capacity to face unexpected expenses, ii) capacity to afford paying for one week annual holiday away from home, iii) capacity to being confronted with payment arrears (on mortgage or rental payments, utility bills, hire purchase instalments or other loan payments), iv) capacity to afford a meal with meat, chicken, fish or vegetarian equivalent every second day,  v) ability to keep home adequately, vi) have access to a car/van for personal use, vii) replacing worn-out furniture, viii) having internet connection, ix) replacing worn-out clothes by some new ones, x) having two pairs of properly fitting shoes (including a pair of all-weather shoes), xi) spending a small amount of money each week on him/herself, xii) having regular leisure activities, or  xiii) getting together with friends/family for a drink/meal at least once a month. 
  • People living in households with very low work intensity (% of population aged 0-64) - Persons aged 0-64, living in households where the adults (aged 18-64) worked less or equal to 20% of their total work potential during the past year. Students aged 18-24, people who are retired or who receive any pension (except survivor’s pension), people in the aged 60-64 who are inactive and living in a household where the main income is pensions, are excluded. 

 

Income

The total disposable income of a household is calculated by adding together the personal income received by all household members plus income received at household level. Missing income information is imputed.

Disposable household income includes:

- all income from work (employee wages and self-employment earnings);

- private income from investment and property;

- transfers between households;

- all social transfers received in cash including old-age pensions.

Note: Some of the income components are mandatory only from 2007: Imputed rent, Interest paid on mortgage, Employer's social insurance contributions. From the 2007 year on, all countries have to supply gross income information.  

The current definition of total household disposable income used for the calculation of EU-SILC based indicators excludes:

- imputed rent - i.e. money that one saves on full (market) rent by living in one's own accommodation or in accommodation rented at a price that is lower than the market rent,

- non monetary income components, in particular value of goods produced for own consumption, social transfers in kind and non-cash employee income except company cars.

 

Household definition

A 'private household' means "a person living alone or a group of people who live together in the same private dwelling and share expenditures, including the joint provision of the essentials of living". EU-SILC implementing Regulation No 1983/2003 on updated definitions, defines households in terms of sharing household expenses and (for non-permanent members) in terms of duration of stay and (for temporarily absent members) in terms of duration of absence.

Household type:

A common classification was developed by Eurostat for use in data collection surveys including ECHP, LFS, HBS and EU-SILC as well as the subsequent presentation of indicators relating to income, housing, education, healthcare, etc. Rather than focusing on "couples" and/or "families", the classification is constructed by reference to the numbers of adult members, their age and gender, and the numbers of dependent children living with them.

 

For further information see the respective metadata file on Income and living conditions (ilc).

3.5. Statistical unit

Households and household members.

3.6. Statistical population

The EU-SILC target population in each country consists of all persons living in private households. Persons living in collective households and in institutions are generally excluded from the target population.

3.7. Reference area

The data published under the MIP domain present data for each EU Member State, as well as euro area (EA) and the European Union as a whole. 

3.8. Coverage - Time

Details on data availability are available under the links: tipslc10, tipslc20, tipslc30 and tipslc40.

3.9. Base period

Not applicable.


4. Unit of measure Top

Percentage of population and 3 year change in percentage points. 


5. Reference Period Top

The various statistics are generally presented on an annual basis (the survey year, whatever the underlying income reference period)

The income reference period in EU-SILC is a fixed 12-month period (such as the previous calendar or tax year) for all countries except IE for which the survey is continuous and income is collected for the last twelve months. Other data is typically collected on the date of the survey.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

The EU-SILC project was launched in 2003, on the basis of a 'gentlemen's agreement' in six MS (Belgium, Denmark, Greece, Ireland, Luxembourg, and Austria) as well as in Norway.

EU-SILC currently operates under the Regulation of the European Parliament and the Council (Regulation (EU) No 2019/1700) and a series of Commission implementing Regulations. For further information see Legislation - Income and living conditions - Eurostat (europa.eu)

 

The indicators are part of the MIP Scoreboard Auxiliary indicators set up under Regulation (EU) No 1176/2011 of the European Parliament and of the Council. The framework Regulations for the MIP indicators are :

Further details are published on Eurostat dedicated web section.

6.2. Institutional Mandate - data sharing

Not applicable.


7. Confidentiality Top
7.1. Confidentiality - policy

Regulation 2015/759 of 29 April 2015 amending Regulation (EC) No 223/2009 on European statistics of 11 March 2009 [recital 24 and Article 20(4)], stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those data.

7.2. Confidentiality - data treatment

Not applicable.


8. Release policy Top
8.1. Release calendar

There is no special release calendar. Indicators based on national SILC data are published soon after its delivery and acceptance. In general it takes place in the course of year N+1 (where N = year of data collection) in case of indicators based on cross-sectional data and starting from the second half of year N+1 in case of indicators based on longitudinal data.

8.2. Release calendar access

Not applicable.

8.3. Release policy - user access

The MIP Regulation stipulates that “the Commission shall make the set of indicators and the thresholds in the scoreboard public” (Art. 4, para. 6, Regulation (EU) No 1176/2011 of 16 November 2011 on the prevention and correction of macroeconomic imbalances) and that “the Commission shall update the values for the indicators on the scoreboard at least on an annual basis” (Art. 4, para. 8). In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see § 10 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. Detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.


9. Frequency of dissemination Top

Annual.


10. Accessibility and clarity Top
10.1. Dissemination format - News release

News releases on-line.

10.2. Dissemination format - Publications

The indicators are part of the MIP auxiliary indicators used to identify emerging or persistent macroeconomic imbalances in EU countries. The MIP indicators are part of an annual exercise, where the first step is the compilation of an Alert Mechanism Report (AMR) and its Statistical Annex.

10.3. Dissemination format - online database

See data availability for the table: tipslc10, tipslc20, tipslc30 and tipslc40.     

10.4. Dissemination format - microdata access

Not applicable.

10.5. Dissemination format - other

Not applicable.

10.6. Documentation on methodology

Detailed guidelines of EU-SILC can be found in the following documents:

10.7. Quality management - documentation
  • Regulation CE 28/2004 on the content of intermediate and final quality reports published in the OJ on 5 January 2004
  • Comparative EU Quality Reports are available on Eurostat website: EU Quality Reports
  • National Quality Reports are available on Eurostat website: National Quality Reports


11. Quality management Top
11.1. Quality assurance

EU-SILC is based on a framework Regulation No 1177/2003 that defines the scope, definitions, time reference, characteristics of the data, data required, sampling, sample sizes, transmission of data, publication, access for scientific purposes, financing, reports and studies. In addition, Eurostat and Member States have developed the technical aspects of the instrument, in particular the Regulation on 'Quality Reports' No 28/2004. Further on, Eurostat and Member States have carried out several methodological studies on different areas.

11.2. Quality management - assessment

Output standardisation is achieved by defining the format (list and content of target variables, data format) and the timetable of data transmission. This is complemented by Eurostat consistency and integrity checks so that minimum output quality standard is reached. In addition, countries should report to Eurostat on any deviation from the standard.

Data are accompanied with quality reports analysing the accuracy, coherence and comparability of the data. Detailed information on quality documentation is presented under § 10.7.


12. Relevance Top
12.1. Relevance - User Needs

The indicators are part of the MIP auxiliary indicators and together with the MIP Scoreboard indicators they are part of the Statistical Annex of the Alert Mechanism Reports. The MIP Scoreboard is used as an early warning system in the context of macroeconomic surveillance of the EU Member States. The aim of the scoreboard is to trigger in-depth studies, which will do analyses to determine whether potential imbalances identified in the early-warning system are benign or problematic.

12.2. Relevance - User Satisfaction

A satisfaction survey of users of EU-SILC was conducted in 2010. 68 users of EU-SILC responded to the user survey. For the majority, available aggregated data were important or essential in their work irrespective of the purpose of their use. Moreover, the frequency of use of the statistics was high. The survey has shown that EU-SILC is of very high relevance for users.

The use of the ad-hoc modules was less widespread than the use of the primary variables. Nevertheless there was high interest to repeat these modules in order to have the possibility of comparing data over time. The EU-SILC's legal basis specifies that the variables covered by the modules are to be collected every four years or less frequently. As stated above the modules of 2011 and 2012 will cover topics very similar to those of 2005 and 2007 respectively.

The overall quality of EU-SILC data was rated as adequate to good. Among the various dimensions, coherence was rated highest for both micro-data and aggregated statistics. Accuracy was the most important aspect for users and scored highly in the quality assessment.

Comparability across countries for aggregated data was the least appreciated factor, being rated 'Adequate', but it was very important for users. The users also considered the metadata provided about differences between national practices and methods as insufficient. Timeliness also needed improvement according to the users but this should not be achieved at the expense of accuracy.

Poverty, well being, material deprivation and child poverty, the particular topics that Eurostat indicated as potential areas of expansion of EU-SILC, attracted the attention of many users, showing Eurostat's good understanding of their needs. Most of them considered additional breakdowns of the disseminated poverty indicators as most important. Additionally, needs expressed spontaneously by users referred most to data on income and benefits but also to household characteristics, health, social and living conditions, education and labour status characteristics.

Finally, users were satisfied with overall quality of the service delivered by Eurostat, which encompasses data quality and the supporting service provided to them.

12.3. Completeness

EU-SILC covers only people living in private households (all persons aged 16 and over within the household are eligible for the operation), i.e. persons living in collective households and in institutions are generally excluded from the target population.

EU-SILC may exclude small parts of the national territory amounting to no more than 2% of the national population and the national territories. National territories that may be excluded include the French Overseas Departments and territories, the Dutch West Frisian Islands, with the exception of Texel, the all Irish offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia.

The coverage over time for each indicator is illustrated under §3.8 .


13. Accuracy Top
13.1. Accuracy - overall

Regulation 1177/2003 defines the minimum effective sample sizes to be achieved, i.e. the actual sample sizes will have to be larger to the extent that the design effect exceeds 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. The allocation of the effective sample size is done according to the size of the country and ensuring minimum precision criteria for the key indicator at national level (absolute precision of the at-risk-of-poverty rate of 1%).

13.2. Sampling error

Standard errors of key indicators are commonly used as a measure of the reliability of data collected through sample survey. EU-SILC was designed to provide measure of at-risk-of-poverty rate with an absolute precision of about one point. The sample sizes were defined taking into account this accuracy requirement. Member States compute variance estimates for the main indicators; Linearisation, Jacknife and Bootstrap techniques are programmed.

For further information please consult the national and EU quality reports: EU and National Quality reports

13.3. Non-sampling error

The term 'non-sampling error' is a generic one that encompasses any errors other than sampling errors. The non-sampling errors discussed in this section are: coverage errors, measurement and processing errors, and non-response errors.

Coverage errors

Coverage errors are caused by the imperfections of a sampling frame for the target population of the survey.

In EU-SILC two main groups can be defined in terms of the sampling source used:

  • Some countries have relied on household information from population registers. In order to make the best coverage of the target population, registers have to be updated frequently. It means any modification in the population (both people moving in and people moving out) must be reported as quickly as possible.
  • Other countries have used Census databases in order to select addresses. The databases also have to be updated to represent the units that have come into being after the Census and thus ensure the cross-sectional representativeness of the sample.

A systematic source of coverage problems is the time lag between the reference date for the selection of the sample and the fieldwork period, which should be made the shortest. 

In addition, some countries carried out EU-SILC as a sub-sample of the units (addresses) that successfully cooperated to other existing surveys. Assuming selective non-response in these surveys, this may entail selection bias (under-coverage).

Measurement and processing errors

Generally, measurement errors arise from the questionnaire, the interviewer, the interviewee and the data collection method used.

It is vital in a survey like EU-SILC, which collects a multitude of complex income components, that the questionnaire is constructed so that the interviewee can provide as quickly as possible all the correct information. It appears that most of the countries took care in designing the questionnaire. In particular, experiences from pilot surveys and/or former EU-SILC waves were used in order to optimize the data collection process. The questionnaires were also tested in order to identify potential sources of problems. 

Due to the complexity and the sensitivity of the survey, the interviewees could not or did not want to give information about all their incomes. For instance, capital of self-employment income may have been under-reported. Besides, EU-SILC collects non-monetary income components (imputed rent, income from private use of company car) that could have an unfamiliar terminology to some people. The risk of confusion on the information to report is then higher than with more conventional monetary income components.

Non-response errors

All surveys have to deal with non-response, i.e. information missing for some of the sample units. Unit non-response happens when no interview can be obtained, while item non-response does when only some of the items are missing. EU-SILC suffers from these two types of non-response:

  • Unit non-response: when a household refuses to cooperate or is away during the fieldwork period. Other reasons can explain unit non-response: the questionnaire is lost; the household is unable to respond because of incapacity or illness. It may also happen that a person in a household refuses to cooperate although the household interview has been accepted ('individual' non-response).
  • Item non-response: typically happens to questions the interviewee does not answer because he considers them personal or not easily understandable.

Non-response is a potential source of bias particularly if the non-responding units have specific survey patterns ('non-ignorable' non-response). For instance, one might expect persons with high incomes to be more reluctant to give income information to an interviewer, thus making the upper income class under-represented in the sample and the estimates downwardly biased. 

Commission Regulation 28/2004 has defined indicators aiming at measuring unit non-response in EU-SILC: Address contact rate (Ra), Household response rate (Rh), Individual response rate (Rp). 

At this step, elaborate models controlling many external control variables are desirable in order to correct non-response. Most countries did apply either a standard post-stratification based on homogeneous response groups or a more sophisticated logistic regression model. 

Individual non-response rate appears to be marginal. Most countries have actually imputed missing individual questionnaires. 

Item non-response is high for some income components. It has been dealt with by imputation. The technique aims at 'filling the holes' in a distribution, so only unit non-response can be assumed. However, it has to be kept in mind that imputed values are not exact values and underlain on a model that could not be the perfect fit of the reality. 

Imputation can have a significant effect on the overall accuracy: it generally skews a sample distribution so estimates will be biased. Furthermore, variance estimates assuming that imputed values are the exact ones, will be generally biased. The impact of imputation on the EU-SILC data is difficult to assess as yet. 

Total non-response of selected household/individuals is required to be below 40%.

Item non-response for non income variable is limited to 5%. When non-response in income components affects a subcomponent collected through interview, statistical imputation or modelling is required. This aspect is controlled in the datasets through imputation flags which represent the proportion of collected over recorded amounts.


14. Timeliness and punctuality Top
14.1. Timeliness

Indicators based on national SILC data are published on Eurostat website soon after its delivery and acceptance. In general it takes place in the course of year N+1 (where N = year of data collection) in case of indicators based on cross-sectional data and starting from the second half of year N+1 in case of indicators based on longitudinal data.

14.2. Punctuality

For information on punctuality of the national SILC data please consult the EU quality reports: EU Quality Reports


15. Coherence and comparability Top
15.1. Comparability - geographical

The indicators are associated with a high level of comparability.

EU-SILC aims at ensuring standardisation of the concepts, implementation and process. It is based on a common framework defined by harmonised lists of primary and secondary variables, common concepts, a recommended design, common requirements (for imputation procedures, weighting, sampling errors calculation) and classifications aiming at maximising comparability of the information produced.

For further information see the respective metadata file on Income and living conditions (ilc).

15.2. Comparability - over time

Comparability over time is ensured by a common data source (EU-SILC) since 2005.

15.3. Coherence - cross domain

EU-SILC follows international standards: ISCO, NACE, ISCED, degree of urbanisation, Canberra recommendations for income data.

The sets of weights available in EU-SILC datasets have been obtained using calibration techniques which ensure basic coherence of estimates obtained from EU-SILC micro datasets and demographic counts.

Further coherence analysis with other surveys like Labour Force Survey or Household Budget Survey or other statistics as National Accounts and Social Protection Accounts can be found in the national quality reports: National Quality Reports.

15.4. Coherence - internal

Not applicable.


16. Cost and Burden Top

Not applicable.


17. Data revision Top
17.1. Data revision - policy

Errors, whether arising from input data or calculation methodology, are corrected as soon as possible following their identification, and replacement figures are published.

Data collection:

With effect from 2004, EU-SILC data collection is governed by a framework regulation of the Council and the Parliament and implementation regulations of the Commission. Changes in methodology are developed in collaboration with NSIs and are announced in the Official Journal of the European Communities.

Indicators:

The development of indicators under the Open Method of Coordination is a transparent, collaborative process with Member States. The work of the Indicators Sub Group of the Social Protection Committee is ongoing to refine and develop the portfolio of indicators. Once agreement is reached on a revision to previous methodology, or an expansion to the list, this is implemented as rapidly as possible and the results on Eurobase and associated explanatory notes are updated.

17.2. Data revision - practice

Revisions of previously released EU-SILC data may happen in case major errors are identified in the data delivered or in their processing.


18. Statistical processing Top
18.1. Source data

ECHP:

From 1994 to 2001, the major data source in this domain was the European Community Household Panel (ECHP). Between 2001 and 2005 there was a transitional period, during which national data were harmonised to compute the indicators in this domain.

EU-SILC:

In most cases participant countries launch EU-SILC from scratch with integrated cross-sectional and longitudinal elements (this is the Eurostat recommendation). Other countries use a combination of registers and interviews. Others seek to adapt existing national sources.

Precision requirements are set via the prescription of minimum effective sample sizes that are specified in the EU-SILC framework regulation 1177/2003. They should be carefully designed to ensure representativity - and are to be increased by participant countries to the extent that their national sample is not determined on a simple random basis, or to reflect likely levels of non-response, or to reflect any specific national requirements. Separate values are specified for the cross-sectional and longitudinal elements.

The minimum effective sample size for the cross-sectional element covers some 273,000 individuals living in 130,000 private households (LU: 3250, DE: 8250).

18.2. Frequency of data collection

Annual.

18.3. Data collection

With effect from 2004, EU-SILC data collection is governed by a framework regulation of the Council and the Parliament and implementation regulations of the Commission. As for the year 2003, seven countries delivered EU-SILC data on voluntary basis.

Information can be collected either from registers or from interviews. For the interview, there are four different ways to collect the data: Paper-Assisted Personal Interview (PAPI), Computer-Assisted Personal Interview (CAPI) which is the most used, Computer-Assisted Telephone Interview (CATI) mainly used in countries where income data are extracted from registers, Self-administrated questionnaire. All collected data are confidential. Eurostat receives the data only from National Statistical Institutes. 

18.4. Data validation

There is a comprehensive validation procedure applied prior to finalisation of the EU-SILC database. Source data is initially reviewed at national level. It is subsequently submitted to Eurostat for multilateral validation together with detailed quality report, following which bilateral contacts are pursued as necessary.

18.5. Data compilation

Estimates at aggregate level are calculated as the population-weighted arithmetic average of individual national figures.

18.6. Adjustment

Missing survey data is imputed using procedures specified in EU-SILC implementation Regulation N° 1981/2003. This includes income data, household composition data and other elements.


19. Comment Top

See Related metadata on Income and living conditions (ilc) here below.


Related metadata Top
ilc_sieusilc - Income and living conditions


Annexes Top


Footnotes Top