1.1. Contact organisation
[TR1] Turkish Statistical Institute (TURKSTAT)
1.2. Contact organisation unit
Income and Living Conditions Statistics Group
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Necatibey Street Number: 114 06420 Çankaya /ANKARA /TÜRKİYE
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
6 November 2025
2.2. Metadata last posted
6 November 2025
2.3. Metadata last update
24 November 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 - 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 the list of classification on the Eurostat webpage, Metadata and Statistics explained on classification.
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 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.
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 |
|---|---|---|
| The entire members of the households that live within the borders of the Republic of Türkiye were included within the scope. However, the institutional population in the dormitories, guesthouses, child care centers, orphanages, nursing homes, private hospitals, prisons, military barracks was excluded out of the scope. |
The community which is comprised by one or more than one members living together in the same housing or part of the housing unit, either with blood relationship or not, meeting the basic needs together, participating the services and management of the household. |
Members whose permanent residence is address of the sample household are accepted as household member even though they are not temporarily in the household at the time of the interview. Additionally, those living in institutional units (soldiers and ranks doing compulsory military service, persons in prison, elderly people in nursing homes, students in dormitories, etc.) are not regarded as the household members. |
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 entire territory of the Republic of Türkiye was included in the scope of the survey, covering all settlements within national borders.
3.8. Coverage - Time
2006-2024
SILC has been implemented in Türkiye every year, since 2006.
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 |
|---|---|---|---|
| Same definition as standard EU-SILC. |
The field work of the survey was carried out between March-July 2024.
|
Same definition as standard EU-SILC |
The initial results of the survey on Survey on Income and Living Conditions has been announced to the public as a press release in 12th month of the year that is the field application applied. |
6.1. Institutional Mandate - legal acts and other agreements
Regulation (EU) 2019/1700 was publish 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
EU regulation 2019/2180: Information on ownership of data, indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interests of the source or other relevant parties.
Confidentiality policy: description of any provisions in addition to European legislation that are relevant to the statistical confidentiality applied to the data collection, transmission to Eurostat or publication.
7.2. Confidentiality - data treatment
EU regulation 2019/2180: Information on ownership of data, indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interests of the source or other relevant parties.
Confidentiality – data treatment: a general description of the rules applied to treating microdata and macro data (including tabular data) with regard to statistical confidentiality. Please describe the conditions for data protection and anonymization at the national level.
8.1. Release calendar
Annexes:
Official Statistics
8.2. Release calendar access
Please refer to the Release calendar - Eurostat (europa.eu) publicly available on the Eurostat’s website. In addition please refer to the national calendar of publication.
Annexes:
National calendar of publication
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 EU-SILC microdata.
Annual
10.1. Dissemination format - News release
The results of the Income and Living Conditions Survey are announced to the public as a press release in both Turkish and English simultaneously to all interested parties through the TURKSTAT website respectively:
Annexes:
Income Distribution Statistics 2024
Poverty and Living Conditions Statistics 2024
10.2. Dissemination format - Publications
In TURKSTAT, EU-SILC results are not published as a publication. Survey results are published as a press release and micro data only.
10.3. Dissemination format - online database
TURKSTAT provides access and usage facility for the micro data of survey and researches in accordance with the legal legislation based on the national and international researchers demand.
Micro data files comprise individual data for one given statistic, which have been filtered appropriately to achieve anonymous information so as to ensure confidentiality (Regulation of Procedure and Principles of Data Confidentiality and Confident Data Security in Official Statistics).
When using micro data files, any published information including data obtained thereby must quote the TURKSTAT as the primary data source. Furthermore, the level of accuracy or reliability of the information derived by the authors is exclusively their responsibility (Turkish Statistical Institute, Instructions for the Access and Use of Micro Data).
Turkish Statistical Institute, Instructions for the Access and Use of Micro Data came into effect on September 1, 2012 and revised on September 3, 2020, regulating the procedures for micro data access and usage. According to Part 2 Item 5 of Turkish Statistical Institute, Instructions for the Access and Use of Micro Data, the researchers of the following institutions and organizations can access to micro data produced and/or published by the TURKSTAT upon approval of the Presidency on condition that they are used in researches for scientific purpose:
Institutions and organizations covered under the Official Statistics Programme
Other official institutions and organizations in Türkiye
Universities and other higher educational institutions
Research based establishments and institutions
International organizations at which Türkiye is a member
Micro data sets are established from the records in order to reinforce the scientific researches by the Institute. These data sets brought into use upon approval of the Presidency are classified into Group A and B depending on access procedures.
Micro data relating to EU-SILC are published on official website of TURKSTAT without micro data sets. Researchers who meet the criteria defined in the Directive on Access to and Use of Microdata may submit their applications.
Annexes:
Applications of EU-SILC micro data set
EU-SILC Micro Data on official website of TURKSTAT (without micro data sets)
10.3.1. Data tables - consultations
No information available
10.4. Dissemination format - microdata access
Income and Living Conditions Survey Micro Data Sets (Cross-Sectional and Longitudinal), 2024.
Income and living conditions survey has been conducted within the scope of the studies compliance with European Union (EU) since 2006. The aim of the survey is to supply comparable annual data on income distribution, relative poverty, living conditions and social exclusion. The survey is applied every year regularly and used panel survey method and the sample persons are traced during four years. It is aimed to get two kinds of data set cross-sectional and panel every year.
Related data sets including cross-sectional and 2-year, 3-year and 4-year panel results of Income and Living Conditions Survey contains micro data in the form of CSV format, data guidance, basic indicators and methodological information.
10.5. Dissemination format - other
Not available
10.5.1. Metadata - consultations
Not applicable
10.6. Documentation on methodology
Methodological documentations are available here:
Income Distribution Statistics
Poverty and Living Conditions Statistics
See Annex 11-Metadata on benefits (from 2018 onwards)
Annexes:
Methodological documentations relating to Income Distribution Statistics
Methodological documantations relating to Poverty and Living Conditions Statistics
10.6.1. Metadata completeness - rate
Not applicable
10.7. Quality management - documentation
Institutional quality report in national level is available on the TURKSTAT official web site.
2024 Institutional quality report
Annexes:
Institutional quality report (2024)
11.1. Quality assurance
Not applicable.
11.2. Quality management - assessment
Data are accompanied with quality reports analysing the accuracy, coherence and comparability of the data.
The quality of the TR-SILC survey can be assumed to be high. Its concepts and methodology have been developed according toEuropean and international standards and using best practices from all EU Member States. TR-SILC indicators are considered tobe sufficiently accurate for all practical purposes they are put into. The indicators are disseminated following a predetermined Release calendar.
Further work is ongoing to improve the quality and in particular the comparability of the indicators. Key priorities are greater harmonisation of methods for quality adjustment and sampling.
12.1. Relevance - User Needs
The main users of EU-SILC statistical data are: Eurostat/EU related institutions, policy makers, research institutes, media, students, Eurostat/EU related institutions, other international organizations (IMF, World Bank, OECD, etc.), public institutions/organizations (ministries, other public institutions), local authorities, universities and research institutes, media organizations, individual users.
User needs of statistics are:
- RIP (Official Statistical Program) Working Group Meeting
- Statistical Council meeting
- Joint meetings with other institutions
- Meetings/workshops organized by user organizations
- Examination of information requests
- Publication review (OECD, UN, Eurostat etc.)
- Working groups or direct communication with in-house users
- Examination of international requests (EU acquis, OECD, UN etc.)
12.2. Relevance - User Satisfaction
Eurostat carried out a general User Satisfaction Survey (USS) to obtain a better understanding of users’ needs and their satisfaction with the services provided by Eurostat. The survey results indicated that EU-SILC data are of very high relevance to users. For the majority of respondents, both aggregated data and microdata were considered important or essential for their work, regardless of the purpose of use. The use of ad-hoc modules was less widespread compared to the use of annual variables. Users also highlighted a strong need for more detailed microdata.
For further information, please consult the Eurostat User Satisfaction Survey.
For further national information, please consult the TurkStat User Satisfaction Survey.
12.3. Completeness
All target and additional module’s variable in TR-SILC are fully in line with the methodological guidelines (Doc-065 2023 operation year) and the Commission (Eurostat) requirements. Although all target variables for the survey were collected, no field study was conducted on the optional variables in TR application.
These variables are not collected:
DB050, DB060, DB062, DB070, DB080, DB095, DB100, HY145N, RB065, RB066, PB070
12.3.1. Data completeness - rate
100% of requested variables were transmitted
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
TURKSTAT is using the Eurostat method.
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 |
|
2.4 % |
DB120=23 Address/phone non-contacted: non-existent/non-residential or non-private/ unoccupied /not principal residence |
| Under-coverage |
NA |
NA |
|
| Misclassification |
NA |
NA |
|
13.3.1.2. Common units - proportion
not applicable
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 |
| The main source of measurement errors is: |
The TURKSTAT questionnaire of TR SILC is developed according to EU-SILC regulations and EUROSTAT guidelines. Translation controlled by at least two persons to decreased the measurement errors. |
Interviewers are firstly trained and provided with training tools (e.g. instruction manuals, or presentations) by TURKSTAT. Also there is an e-mail group to discuss the methodological issues during the fieldwork. |
HARZEMLİ is the program developed by TURKSTAT in Java and chosen to produce the CAPI application in SILC. Data entry process is completed / finished in the field by using laptops. Controls of data are made in field during data entering by warnings (red or green). After sending data interviewer check the data by using SAS codes from the first day of field work. In regional offices, interviewers are responsible for data entering, supervisors are responsible for data control and analysis of data and group leaders are responsible for editing and aggregating data. After obtaining some corrections, data are sent to Central Office. In Central Office, after completing of data analyze by regional basis, data are analysis by using SAS codes. |
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:
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.
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 |
| 99.94 |
99.79 |
100.0 |
98.69 |
96.84 |
99.41 |
99.85 |
99.85 |
99.86 |
1.37 |
3.37 |
0.59 |
0.15 |
0.15 |
0.14 |
1.52 |
3.51 |
0.72 |
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.
| Response rate for household |
Wave 2 |
Wave 3 |
Wave 4 |
|---|---|---|---|
| Wave response rate |
95.53 |
94.2 |
97.67 |
| L follow-up rate |
99.44 |
98.86 |
99.34 |
| Follow-up ratio |
98.72 |
93.05 |
101.7 |
| Achieved sample size ratio |
98.72 |
93.05 |
101.7 |
| Response rate for persons |
Sample persons/ co-residents |
Wave 2 |
Wave 3 |
Wave 4 |
|---|---|---|---|---|
|
Wave response rate |
Sample persons |
99.78 |
99.78 |
99.86 |
| Co-residents |
99.75 |
99.57 |
99.67 |
|
|
L follow-up rate |
Sample persons |
99.87 |
99.77 |
99.87 |
|
Achieved sample size ratio
|
All persons |
98.02 |
93.62 |
101.3 |
| Sample persons |
95.84 |
91.64 |
99.52 |
|
| Co-residents |
. |
165.9 |
135.8 |
|
| Response rate for non-sample persons |
Co-residents |
99.75 |
99.57 |
99.67 |
| Year of the survey | Sample of households | Sample of individuals 16+ | Response rate of the households | Response rate of individuals 16+ |
|---|---|---|---|---|
| Wave 1 | 25925 | 60462 | 88.6 | 99.7 |
| Wave 2 | 18339 | 41968 | 95.5 | 99.8 |
| Wave 3 | 11934 | 26738 | 94.2 | 99.8 |
| Wave 4 | 5790 | 12855 | 97.7 | 99.8 |
| Wave 5* | ||||
| Wave 6* |
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
Please see TR_2024_Annex 2-Item_non_response_13.3.3.2.1
13.3.4. Processing error
Description of data entry, coding controls and the editing system
| Data entry and coding (if any used) |
Editing controls |
|---|---|
| The information is collected via the CAPI questionnaire using the Harzemli data entry program implemented by TURKSTAT. After the questions, data rules, and logical inconsistencies between responses (red and green alerts) are updated, the data entry program is tested by both Regional and Central Office staff. The software is installed on each interviewer’s computer before the fieldwork begins. |
The main errors identified during the subsequent data collection process were: Missing or unnecessary values; Values outside the acceptable range Inconsistent values when compared with other information within the same record; Inconsistent answers compared to those given in previous survey rounds |
| Re-interview rates |
Wave-2
|
Wave-3 |
Wave-4 |
|---|---|---|---|
| (a) individuals in interviewed households % |
95.6 |
88.3 |
90.2 |
| (b) individuals out of scope % |
3.1 |
1.7 |
2.1 |
| (c) individuals not interviewed for reasons other than their being out of scope % |
1.3 |
9.9 |
7.7 |
| Re-interview rates for people leaving their original household total |
1.9 |
1.6 |
1.1 |
| Re-interview rates for people leaving their original household males |
1.8 |
1.5 |
1.1 |
| Re-interview rates for people leaving their original household females |
1.9 |
1.6 |
1.1 |
| Re-interview rates for young people (16-35) total |
4.1 |
3.4 |
2.4 |
| Re-interview rates for young people (16-35) male |
3.9 |
3.1 |
2.1 |
| Re-interview rates for young people (16-35) female |
4.3 |
3.7 |
2.6 |
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
The initial results of the TR EU-SILC was announced to the public as a press release same year with the field application applied.
14.1.1. Time lag - first result
In TURKSTAT, for the EU-SILC first results is equal to final results.
First results for the year of 2024:
- End of reference period: 26 July 2024
- National publication date: 27 December 2024
The initial results of the TR EU-SILC was announced to the public as a press release same year with the field application applied.
14.1.2. Time lag - final result
In TURKSTAT, for the EU-SILC first results is equal to final results.
Final results for the year of 2024:
- End of reference period: 26July 2024.
- National publication date: 27 December 2024.
TR- SILC R24 data sets were transmitted to EUROSTAT in March 2025 first time. The validation completed in April 2025.
14.2. Punctuality
Time lag between the actual delivery of the data and the target date when it should have been delivered: 0 month
14.2.1. Punctuality - delivery and publication
Number of months between the delivery/release date of (national) data and the target date on which they were scheduled for delivery/release: 0 month
Percentage of data release delivered on time: 100%
15.1. Comparability - geographical
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 harmonized 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.
See the TR_2024_Annex 7-Coherence_15.3-15.3.2
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
15.2. Comparability - over time
In 2024, there were no breaks in the series that affected the comparability of TR SILC.
See TR_2024_Annex 8-Breaks in series_15.2
15.2.1. Length of comparable time series
The number of reference periods in time series from last break.
Length of comparable time series = 2024 - 2014 + 1 = 11 years
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) |
F |
|
| Cash or near-cash employee income |
(PY010) |
F |
|
| Other non-cash employee income |
(PY020) |
F |
|
| Income from private use of company car |
(PY021) |
F |
|
| Employers social insurance contributions |
(PY030) |
F |
|
| Contributions to individual private pension plans |
(PY035) |
F |
|
| Cash profits or losses from self-employment |
(PY050) |
F |
|
| 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
Please see “See the TR_2024_Annex 7-Coherence_15.3-15.3.2”.
15.4. Coherence - internal
In 2024, no major coherence issues were identified in the EU-SILC dataset for Turkey. The statistical outputs were produced based on harmonized concepts and methodologies aligned with EU guidelines. Minor discrepancies between EU-SILC results and other administrative sources may stem from differences in data collection periods, reference definitions, or coverage.
Mean (average) interview duration per household = 32.7 minutes.
Mean (average) interview duration per person = 9 minutes.
Mean (average) interview duration for selected respondents (if applicable) = minutes.
17.1. Data revision - policy
There are no scheduled revisions. Therefore, not applicable.
17.2. Data revision - practice
Not applicable.
17.2.1. Data revision - average size
Not applicable.
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 sampling frame of the first wave households of SILC 2024 was composed by the registers of Address Based Population Register (ABPR) and National Address database.
18.1.1. Sampling Design
The sample design of SILC was created by the valuable contributions of Prof. Vijay Verma, University of Sienna. Weighting procedures and the standard error calculations were carried out under the valuable consultation of Prof. Gianni Betti, University of Siena. In the subject of the accuracy, the recommendations of European Union EU SILC guideline were taken into account.
Type of sampling (stratified, multi stage, clustered) design:
The Survey on Income and Living Conditions is an annual survey with a rotational-group design. The sample comprises four independent sub-samples, each of which is a four-year panel. Each subsample is selected as to represent the whole country. Each year, the sample is rotated with one of the panels. The 75% of the sampling size is foreseen to leave in the frame of the panel from one year to another. The aim of this follow-up rule is to reflect the changes in the target population and to analyze longitudinally the conditions and income variables of the individuals over time.
The TR SILC 2023 survey follows a stratified multi-stage cluster sampling, which is also the case of the beginning year (2006) of the survey.
Stratification and sub-stratification criteria:
The 2023 survey is designed to produce estimations on NUTS-2 level.
In order to get homogenous groups in the sample selection, urban-rural information was used in the implicit stratification. In the study, the significant change in the administrative division in 2014 was reflected to the sample allocation of 2023 design. The sample size of 2023 in each NUTS-2 was allocated by taking into account both old and new administrative division so that the control was ensured in the settlements moving from rural to urban. In the allocation, the sample sizes got proportionally to population sizes were weighted by 1.5 in the urban-urban part, by 1.5 in the urban-rural part and by 1 in the rural-rural part. Then the rural-rural cells with 0 size were increased to 1 so that at least 1 cluster was ensured in the rural-rural part. Consequently, even if the urban rural estimations are not planned to produce, this breakdown provided representative homogenous groups for the selection of sample in the design.
As said, the beginning year of TR SILC was 2006. Each year the survey has 4 subsamples, which have the same representative structure. The structure of year 2007 had no difference from the year 2006. The figure below shows the subsample numbers of the years 2006 and 2007.
|
|
2006 |
2007 |
|---|---|---|
| Subsample No |
2 |
|
| 3 |
3 |
|
| 4 |
4 |
|
| 1 |
1 |
|
|
|
2 |
18.1.2. Sampling unit
In the beginning year of TR SILC (2006) the sampling frame of the survey was obtained from Enumeration Listings based on 2000 General Population Census. The blocks (PSU’s), only including the household addresses, were determined from this listing.
By 2007, the sampling frame of the survey is based on Address Based Population Register and National Address Database. The sampling frame of blocks (PSU’s), including the household addresses, was determined from this register. The households are defined in this frame so that in each household belonging to the "National Address Database", at least 1 person is registered in the "Address Based Register System".
Each block constitutes approximately 100 (between 80 and 120) household addresses. “Probability Proportional to Size” (PPS) selection was used for selecting the blocks. The number of household addresses in each block has been defined as the measure of size in the PPS selection.
At the second stage, households (SSU’s) were selected by “systematic selection” from the sampled blocks.
18.1.3. Sampling frame
The sampling frame is based on the Address Based Population Register System and National Address Database which was established in 2009. From this linked system, clusters (blocks) involving approximately 100 dwelling addresses (between 80 and 120) are constructed and this blocked list is defined as the sampling frame of the EU-SILC survey. The register system is updated twice in the year. Addresses of the institutional population are not included in the sampling frame.
18.2. Frequency of data collection
| Total duration of the data collection of the sample in 2021-2024 |
|||||
|---|---|---|---|---|---|
| Year |
Start_day |
Start_month |
End_day |
End_month |
Total working day of field work |
| 2024 |
26 |
2 |
14 |
6 |
110 |
| 2023 |
27 |
3 |
4 |
8 |
131 |
| 2022 |
28 |
2 |
1 |
7 |
124 |
| 2021 |
15 |
3 |
22 |
8 |
113 |
18.3. Data collection
The income and Living Conditions Survey is carried out regularly each year. Field application is performed between March-July.
Data are collected with CAPI (Computer Assisted Personal Interview Method) system through personal interview with households included in the sample as well as all household members aged 16 and over in the field applications. In order to use the advantages of making computer surveys, interviews are conducted face-to-face with tablet computers.
The field application is carried out by TURKSTAT regional offices by using HARZEMLİ data entry program developed by TURKSTAT by using observation methods and administrative records used together in the data collection of SILC.
Staffs who are called as the interviewer, controller implement the survey. During the field application, field organization units work coordinately with the central organization units. Compilation of data collection and data analysis phases are performed successfully by these units.
Letters and brochures giving information about the survey and its purpose and how and when the application will be done are sent to households before survey implementation.
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 |
|
90.8 |
9.2 |
|
|
|
|
|
|
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 |
|---|---|---|
|
|
|
|
18.4. Data validation
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 next year’s survey.
In the process data-entry is a logical control of extreme values, filled-in information on all issues, data comparability checks, links between individual questionnaires and registers is carried out. After processing the primary data and receiving the target changes, a verification with the SAS program provided by Eurostat for verification and validation of the data is performed. Additional compatibility checks are performed before publishing the information.
The format of the data is verified and validated through the check programs provided by Eurostat.
Many external administrative sources of data (unemployment benefits, old-age benefits, survivor's benefits, sickness benefits, disability benefits) are used for checking and validating the data obtained by the respondents. The estimates stemming from national accounts are benchmark's values used to validate SILC estimates.
18.5. Data compilation
The "Eurostat Doc-065" document was examined for the “2024 Income and Living Conditions Survey”, the changes and additions in the document were reflected to questionnaire and handbook. After the regional officers were trained, all preparations for the 2024 SILC were completed and the field application was started in February 2024. Currently, SILC 2024 field application and concurrent processing of SAS analyzes are finished.
The survey follows the instructions of the related year EU SILC Operation. Weighting consists of four stages: design weights, non-response adjustment, calibration and trimming. Also, both cross sectional and panel weights are calculated.
Outliers and missing values of interest income are imputed by using SPSS modeler program at the stage of statistical analysis of incomes.
18.5.1. Imputation - rate
In TURKSTAT, the imputation study for EU-SILC is implemented only for bank interest income by using “IBM SPSS Modeler program”. Accordingly;
Variable Name: Bank interest income
Total Number of Units: 8.159
Number of Imputed Units: 7.520
Rate (%): 92.17
18.5.2. Calculation of weighting factors and weight adjustments
The survey follows the instructions of the related year EU SILC Operation. Weighting consists of four stages: design weights, non-response adjustment, calibration and trimming. Also, both cross sectional and panel weights are calculated.
18.5.3. Estimation and imputation
Outliers and missing values of interest income are imputed by using SPSS modeler program at the stage of statistical analysis of incomes.
18.6. Adjustment
Not applicable.
18.6.1. Seasonal adjustment
Not applicable.
See Annex 9 - Rolling module
TR-2024-Annex 2_Item-non-response-13.3.3.2.1
TR-2024-Annex 3_Sampling-errors-13.2
TR-2024-Annex 4_Data-collection-18.3
TR-2024-Annex 7_Coherence_15.3-15.3.2
TR-2024-Annex 8_Breaks-in-series-15.2
TR-2024-Annex 9_Rolling_module
TR-2024-Annex_A_EU-SILC-content-tables
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.
24 November 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 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 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 entire territory of the Republic of Türkiye was included in the scope of the survey, covering all settlements within national borders.
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 |
|---|---|---|---|
| Same definition as standard EU-SILC. |
The field work of the survey was carried out between March-July 2024.
|
Same definition as standard EU-SILC |
The initial results of the survey on Survey on Income and Living Conditions has been announced to the public as a press release in 12th month of the year that is the field application applied. |
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
The "Eurostat Doc-065" document was examined for the “2024 Income and Living Conditions Survey”, the changes and additions in the document were reflected to questionnaire and handbook. After the regional officers were trained, all preparations for the 2024 SILC were completed and the field application was started in February 2024. Currently, SILC 2024 field application and concurrent processing of SAS analyzes are finished.
The survey follows the instructions of the related year EU SILC Operation. Weighting consists of four stages: design weights, non-response adjustment, calibration and trimming. Also, both cross sectional and panel weights are calculated.
Outliers and missing values of interest income are imputed by using SPSS modeler program at the stage of statistical analysis of incomes.
The sampling frame of the first wave households of SILC 2024 was composed by the registers of Address Based Population Register (ABPR) and National Address database.
Annual
The initial results of the TR EU-SILC was announced to the public as a press release same year with the field application applied.
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 harmonized 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.
See the TR_2024_Annex 7-Coherence_15.3-15.3.2
In 2024, there were no breaks in the series that affected the comparability of TR SILC.
See TR_2024_Annex 8-Breaks in series_15.2
