The European Union Statistics on Income and Living Conditions (EU-SILC) set of surveys are an important source of comparative statistical data. EU-SILC provides data on income, living conditions, poverty and social exclusion, material deprivation: topics of growing interest to scholars in Europe and elsewhere. EU-SILC surveys are fielded in 29 European countries and coordinated by Eurostat. Although the survey is harmonised, the individual level microdata consists of many dissimilarities across participating countries because of different national conditions, methods of data collection and/or data processing. The aim of this article is to discuss the opportunities and limitations of EU-SILC datasets. In addition to discussing the development, methodology and basic pitfalls of EU-SILC, this article focuses on (a) income variables, (b) differences in income among countries and (c) impact of income differentials on data comparability. The main problems of income data may be summarised as follows. 1) Some countries use registers to report income variables while others obtain this information from interviews, and this difference lowers their comparability. 2) The incidence of negative or zero values makes the construction of poverty and inequality measures difficult. 3) There are national differences in the net-to-gross income conversion procedure. This study shows using a four country analysis that the net-to-gross conversion procedure overestimates gross wages in two countries and underestimates it in two others. Notwithstanding these methodological issues, EU-SILC is an important resource for the comparative study of income., Martina Mysíková., and Obsahuje bibliografii a bibliografické odkazy
The European Union Statistics on Income and Living Conditions (EU-SILC) set of surveys are an important source of comparative statistical data. EU-SILC provides data on income, living conditions, poverty and social exclusion, material deprivation: topics of growing interest to scholars in Europe and elsewhere. EU-SILC surveys are fielded in 29 European countries and coordinated by Eurostat. Although the survey is harmonised, the individual level microdata consists of many dissimilarities across participating countries because of different national conditions, methods of data collection and/or data processing. The aim of this article is to discuss the opportunities and limitations of EU-SILC datasets. In addition to discussing the development, methodology and basic pitfalls of EU-SILC, this article focuses on (a) income variables, (b) differences in income among countries and (c) impact of income differentials on data comparability. The main problems of income data may be summarised as follows. 1) Some countries use registers to report income variables while others obtain this information from interviews, and this difference lowers their comparability. 2) The incidence of negative or zero values makes the construction of poverty and inequality measures difficult. 3) There are national differences in the net-to-gross income conversion procedure. This study shows using a four country analysis that the net-to-gross conversion procedure overestimates gross wages in two countries and underestimates it in two others. Notwithstanding these methodological issues, EU-SILC is an important resource for the comparative study of income.
The article presents estimates of the reliability of measurement in the Czech surveys carried out in the EU-SILC international longitudinal research project. The reliability estimates were obtained using the Quasi Simplex Model (QSM), which has never before been used in Czech research. An analysis was carried out on all the items in the EU-SILC questionnaire that fulfilled the criteria for the QSM analysis: PH010, the item that asks respondents about their subjective health, HS120, the item that asks about the household’s financial situation, and HS130, which asks what the minimum sufficient income of a household is. The analysis drew on all available data from Czech EU-SILC surveys, that is, data from five rotating panel surveys carried out between 2005 and 2012. The QSM analysis showed that for the selected items EU-SILC data are highly reliable; the estimated reliability of each item was around 0.8, for HS130 it was even above 0.9. The steadiness of the results was confirmed by the high consistency of the reliability estimates across all the panels. A small difference was observed between the reliability of data collected using the PAPI mode and data collected using CAPI. Given the attributes of the QSM model, however, it was impossible to test statistically whether the reliability of PAPI and CAPI data differ significantly.
Providing adequate housing at affordable prices remains a challenge for all welfare states. As part of a pilot project for developing a common methodology for reference budgets in the European Union, reference rents and other housing costs (energy, taxes, maintenance) corresponding to adequate dwellings for four hypothetical households living in nine capital regions of the EU were estimated. In this paper, we discuss the approach that we have taken. Quality criteria for adequate housing were derived from EU indicators of housing deprivation, and the recent UK Housing Standards Review. We used data from the Study of Income and Living Conditions (EU-SILC) of 2012. Unsurprisingly, the estimates of reference rents vary strongly across capitals, reflecting cross-national differences in the level of the average rent. By contrast, other housing costs, which mainly reflect energy costs, vary much less.
This article provides a critique of the use of Esping-Andersen and Kemeny’s typologies of welfare and housing regimes, both of which are often used as starting points for country selections in comparative housing research. We find that it is conceivable that housing systems may reflect the wider welfare system or diverge from it, so it is not possible to “read across” a housing system from Esping-Andersen’s welfare regimes. Moreover, both are dated and require revisiting to establish whether they still reflect reality. Of the two frameworks, Esping-Andersen’s use of the state-market-family triangle is more geographically mobile. Ultimately, housing systems are likely to be judged on the “housing outcomes” that they produce. However, it is suggested that current use of variables within EU-SILC in order to establish “housing outcomes” may be misleading since they do not reflect acceptable standards between countries with greatly differing general living standards and cultural norms.
This paper discusses the strengths and weaknesses of pan-European datasets, in particular ECHP and EU-SILC, for research in housing. Although ‘housing’ is a complex topic when studied from a European comparative perspective, I argue that there is no inherent reason why housing should be less amenable to cross-national research than other equally complex topics in comparative social science research, such as research into family change and stability, or the impact of educational systems on social stratification. Given appropriate theory, conceptualisation and contextualisation, along with strong methodologies, meaningful and informative research in housing with ECHP and EU-SILC are possible. There are however a number of limitations, which are mainly related to the fact that both datasets are geared towards the ‘production’ of a ‘system of social indicators’ informing European and national governments. Because of these limitations, ECHP and in particular EU-SILC are less attractive and less useful for academic research then they could potentially be.