Micro- and macro-drivers of child deprivation in 31 European countries — 2020 edition

This paper analyses child deprivation in 31 European countries, using the scale officially adopted in March 2018 to measure child-specific deprivation at EU level. It combines single level and multilevel models to get a full picture of child deprivation drivers in EU countries. With regard to within-country differences, our results confirm the combined impact of variables related to the “longer-term command over resources” and variables indicating “household needs”. However, our results also show that the relationship of these variables with child deprivation differs between countries. In the richest countries, the explanatory power of the variables related to household needs is the largest, whereas in the most deprived countries, the explanatory power of resource variables is generally greater. With regard to between-country differences, the specification of the model needs careful consideration. We argue that multilevel models should include household income at the micro level, if the aim is to fully gauge the impact of households’ “longer-term command over resources” at the micro level. The multilevel model then assesses how much country-level features that are not reflected in household income and other individual characteristics at the micro level contribute to explaining differences across countries in deprivation. We find that public spending on in-kind social benefits is significant in this respect. Public spending on cash transfers plays only a limited role, when household incomes at the micro level are included; they play a significant role when household income is excluded. This does not diminish the importance of cash transfers in fighting child deprivation, but it qualifies the conclusions of papers which have analysed the relationship of social transfers on deprivation, using multilevel models but without controlling for individual household income. Finally, we find a significant relationship of GDP per capita, even when individual household incomes are included. This is not self-evident: it shows that GDP per capita is a proxy for important contextual variables which are not reflected in individual incomes and other individual characteristics. [+]

The comparability of the EU-SILC income variables: review and recommendations — 2020 edition

EU-SILC is the most important microdata source for studying income and living conditions across the European Union. In this paper, we study variations between countries with respect to how individual income components are aggregated into the EU-SILC target variables. In particular, we look at compliance with Eurostat guidelines, misclassifications and omitted income sources, all potentially undermining cross-national comparability. On the basis of a survey among national statistical institutes, we compiled a database which maps the exact classification of income components onto the EU-SILC target variables. The focus of the database is on EU-SILC 2015, covering 26 EU-SILC countries. The database contains information on the composition of variables on total income before and after transfers; income from benefits, work and capital; social contributions and taxes. As a result of this exercise, we outline some general conclusions with regard to (1) cross-national deviations with regard to the calculation of the EU-SILC total income variables; (2) the classification of national income components (e.g. particular benefits) that can be considered “borderline cases” which are currently classified inconsistently across countries; (3) possibilities for improving the definition of target variables; (4) the (unjustified) omission of some income components from EU-SILC target variables; (5) recommendations that may be helpful to improve the comparability of EU-SILC in the future. [+]