Base de données
Presentation of the EU-SILC database:
The European Union Statistics of Income and Living Conditions (EU-SILC) is a unique data source, due to its’ country coverage, the large set of socio-economic variables it provides and the possibility to merge household members.
The EU-SILC is a harmonized survey, provided by Eurostat. EU-SILC was created in 2003 to replace the European Community Household Panel (ECHP) and now includes 32 European countries. Since then, Eurostat has released a new wave every year. The survey gathers harmonized and comparable data at the individual and at the household level on income and living conditions, as well as on many individuals’ demographic and socio-economic characteristics (sex, age, education, labor market position, parenthood etc.).
The main purpose of EU-SILC is to EU-SILC provide data on income, poverty, social exclusion and living conditions in the European Union. Social exclusion and housing-condition information is collected at household level. Income data is collected at personal level, with some components included in the 'Household' section. Labour, education and health observations only apply to persons aged 16 or older.EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.
Therewith, the EU-SILC is mainly used for economic analysis, while researchers use demographic information (such as the number of children present in the household) as controls. However, SILC is also used more and more for demographic analysis, and in particular for fertility research, as the large international sample allows both marginal effects to be modeled and institutional determinants to be taken into account.Household members can be merged to each other, which allows observing not only individual but also partner characteristics as well as those of children living in the parental household.
EU-SILC is composed of two datasets – one cross-sectional and one longitudinal. The annual cross-sectional data are produced from the longitudinal panel (integrated design, see figure below). The longitudinal dataset of EU-SILC is a rotational panel of four years, which means that for the majority of countries, individuals are observed for a maximum period of four years. The integrated design allows for a large number of observations for the cross-sectional database. In the cross-sectional database, ¼ of individuals are observed for the first time, ¼ for the second time, ¼ for the third time, and ¼ for the fourth time (as shown for ‘Time = T’ in the Figure). This integrated design reduces measurement bias due to cumulated respondent burden and sample attrition.
Some countries provide a follow-up for longer than four years (France, Norway and Luxembourg). In contrast, there is no longitudinal database for Germany. The majority of countries joined the survey in 2004 and 2005, while several Eastern European and Mediterranean countries joined in later (Malta, Croatia, Romania, etc.).
The survey contains information on both individuals and households. It is possible to identify adult women, their partner – if they have one – and the children who live in the same household. EU-SILC has not been designed to directly measured fertility indicators, as the survey does not report information on the number of children directly. However, children are observed with a proper identification number when living in their parents’ households. This allows to compile fertility indicators indirectly by using the ‘own children method’: This method consists in calculating fertility rates by age for a certain year by considering children who are living in the observed household at the time of the survey and who are born in the particular year of interest.
For individuals aged 15+, EU-SILC provides both a register-file and a personal-file. The register-file contains basic demographic information (age, sex, residential status…). The personal-file contains information about education, labour market participation and income. For children aged 0 to 14, SILC provides only a register-file. Besides an individual registration number, the register-files contain a household-id as well as a father-, mother- and spouse/partner-id, which enables users to merge household members. However, no distinction is made between biological parents, adoptive parents, foster parents and step-parents.
Households are generally followed when moving as a whole. Individuals who leave their original household are, however, hard to follow, and this leads to problems of attrition.
EU-SILC provides detailed measures of individuals’ labor market status (reported on a monthly basis; distinction between full-time and part-time employment and employment and self-employment, type of contract, hierarchy and sector etc.). This information is rarely available in other, more ‘demographic’ surveys. One exception is the Gender and Generations Surveys, but this survey has more limited country and time coverage (just three waves, and only the first wave is nationally representative). Besides, in the GGS, information on socio-economic characteristics of the partner is not available, and employment measures are less detailed than in the EU-SILC. Other surveys such as the European Labour Force survey contain information on labor supply, but not on income. Some surveys exist that contain both demographic and economic variables, with individuals being tracked for more than only four years. But the limitation of these datasets is their national focus, since these long-run surveys are generally run in only one given country (the German Socioeconomic Panel or the American Panel Study of Income Dynamics for example).
Besides research on fertility, the EU-SILC can be used for research on life expectancy and population aging, and also –albeit to a lesser extent- for research on migration (as SILC only allows distinguishing between natives, individuals born in Europe and individuals born outside Europe).
The follow-up of individuals and households allows distinguishing between determinants and consequences of demographic behavior, as individual and household characteristics can be observed before and after certain events. For example, it allows observing income and labour market status during a certain period before the potential conception of a child when the purpose is to investigate socio-economic determinants of childbirth.
More information on the EU-SILC database including a list of variables and the codebooks can be found here:
http://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions