Measuring Child Poverty and Its Uncertainty: A Case Study of 33 European Countries

Abstract

Over the last few years, there has been increased interest in compiling poverty indicators for children, as well as in providing uncertainty measures that are associated with point estimates. In this paper, we provide point, variance, and interval confidence estimates of the at-risk-of-poverty rate indicator for 33 European countries. Using the 2018 EU-SILC survey, we analysed the spatial distribution of poverty by providing graphical representations at the national level. Our results reveal rates of child poverty that are higher than in the national estimates for most of the countries. By considering the computation of standard errors, we used the bootstrap method thanks to its convenient properties. It is worth noting that, for some countries, such as Finland, Belgium, and Ireland, the confidence intervals do not overlap. These results suggest differences among countries not only in terms of child poverty, but also in terms of social protection and the welfare state.

Public Policies of Welfare State and Child Poverty in the European Union

“…However, the relationship between child poverty and the different categories of social expenditures is not similar. In all the estimated models, and in accordance with previous studies [12,20,22], we find a negative relationship between child poverty and government spending on education and health, whereas a positive correlation is found with government social protection spending. Likewise, our findings lead us to confirm our hypothesis that the correlation between child poverty and government social spending differs depending on the tax structure of the Member States.…”

“…Nevertheless, the relationship between child poverty and the different categories of social spending is not clearly established. Considering the items of government spending in education and health, related literature has found that a higher spending in both helps to reduce child poverty rates [12,20,22]. However, the association between spending on social protection and child poverty is not well defined.…”

“…Within the social expenditure, we consider specifically the government spending in education, health and social protection. Likewise, and taking into account that child poverty and the effectiveness of social spending policies may differ not only at country level but also depending on the social protections systems and the characteristics of welfare states [22,29], we distinguish between two groups of Member States. The first group is made up of the Member States that throughout the 2008-2018 period had a tax system (ratio of direct taxes over indirect taxes) that is more progressive than that of the EU-28 as a whole, and the rest of the Member States would make up the second group.…”

Measuring teachers’ readiness to use ICT before the COVID-19 pandemic in Italy

“…In this context, a nonparametric bootstrapping approach that makes no assumptions about the nature of the underlying population is more appropriate (Chernick 1999 ). Indeed, bootstrapping is a popular method of producing confidence intervals because of its generality (see, among others, Benedetti et al 2020 ; D’Agostino et al 2022 ; Rousselet et al 2021 ). Accordingly, for comparing two groups, we create the distribution of bootstrap differences in the means (i.e., we generate M bootstrap samples from each group and compute the statistic of interest ( ) for each bootstrap sample), and then we use the 25th value and the 975th value of the ranked differences as boundaries of the 95% confidence interval.…”

Estimating fuzzy measures of deprivation at local level in Tuscany

“…The second dimension shows high factor loadings for items regarding expenditure for children needs and education. Therefore, we interpret it as an indicator of “Children specific deprivation” (see Carraro and Ferrone 2020 ; Benedetti et al 2020 for related studies on this topic).…”