European Union, Survey of Income and Living Conditions 2017 – Public Use File
Lithuania, 2017
Get MicrodataIdentification
LTU_2017_EU-SILC_v01_M_v01_A_PUF
European Union, Survey of Income and Living Conditions 2017 – Public Use File
| Name | Country code |
|---|---|
| Lithuania | LTU |
Other Household Survey [hh/oth]
The Survey of Income and Living Conditions (EU-SILC) is the European Union reference source for comparative statistics on income distribution and social exclusion at the European level, particularly in the context of the 'Programme of Community action to encourage cooperation between member states to combat social exclusion' and for producing key policy indicators on social cohesion for the follow up of the EU2020 main target on poverty and social inclusion and flagship initiatives in related domains, e.g. in the context of the European Semester. It provides two types of annual 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, and
- Longitudinal data pertaining to individual-level changes over time, observed periodically over a four-year period.
The first priority is to be given to the delivery of comparable, timely and high quality data. The cross-sectional data is collected in two stages: An early subset of variables collected by register or interview to assess as early as possible poverty trends. A full set of variables provided along with the longitudinal data to produce main key policy indicators on social cohesion.
The 2017 Survey of Income and Living Conditions (EU-SILC) provides Statistics on income, social inclusion and living conditions cover objective and subjective aspects of these themes in both monetary and non-monetary terms for both households and individuals. They are used to monitor the Europe 2020 strategy, in particular through its poverty reduction headline target.
The main source for the compilation of statistics on income, social inclusion and living conditions is the EUStatistics
on Income and Living Conditions (EU-SILC) instrument. It collects comparable multidimensional micro-data on:
(a) income
(b) poverty
(c) social exclusion
(d) housing
(e) labour
(f) education
(g) health
Sample survey data [ssd]
Version
Version 01
Scope
The scope of the study includes:
- Household composition;
- Dwelling and living conditions;
- Household expenditures;
- Basic needs for all household children;
- Social transfers and family benefits;
- Agricultural activity;
- Economic activity, employment and unemployment;
- Income;
- Health status.
Coverage
National
Cities and settlements
The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Statistics Lithuania | Government of Lithuania |
| Name |
|---|
| European Commission |
Sampling
European Union, Survey of Income and Living Conditions 2017 survey was designed using a stratified simple random sample. Concerning the sampling unit, households are drawn from the Lithuanian Resident Registry, which is updated regularly. All members of the household aged 16 and over at the end of the income reference period are eligible for inclusion in the sample. For more detailed information please refer to the Methodology - Sampling documents, found under the 'Documentation' tab.
The minimum effective sample sizes for Lithuania are as follows:
- Cross sectional survey
- Households: 4,000
- Individuals: 9,000
- Longitudinal survey
- Households: 3,000
- Individuals: 6,750
Data collection
| Start | End |
|---|---|
| 2017 | 2017 |
Data appraisal
Given the high policy relevance of EU-SILC there is increasing demand from the stakeholders for accuracy measures of the published indicators and for measures of the significance of net change of indicators over time for correct monitoring of the evolution of social exclusion phenomena. As seen, EU-SILC is a complex survey involving different sampling design in different countries. For this reason, "to the book" standard methods for calculating accuracy measures are not directly applicable. Eurostat with the substantial contribution of Net-SILC2 has put in place a simple method for standard error estimation based on linearization and coupled with the ultimate cluster approach. 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.
For further details on this method for standard error estimation, please consult the working paper Standard error estimation for the EU-SILC indicators (https://ec.europa.eu/eurostat/en/web/products-statistical-working-papers/-/KS-RA-13-024).
Access policy
Statistics Lithuania
Public use files URL: https://osp.stat.gov.lt/viesos-duomenu-rinkmenos
Cost: None
Data Access
The use of the datasets must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated online)
Example:
Statistics Lithuania. European Union, Survey of Income and Living Conditions 2017 – Public Use File (EU-SILC) 2017, Ref. LTU_2017_EU-SILC_v01_M_PUF. Dataset downloaded from [URL] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
| Name | Affiliation | |
|---|---|---|
| Statistics Lithuania | Government of Lithuania | info@stat.gov.lt |
Metadata production
DDI_LTU_2017_EU-SILC_v01_M_v01_A_PUF_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank | Documentation of the study |
2020-12-06
Metadata version
Version 01 (January 2021)