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

Ilaria Benedetti, Gianni Betti and Federico Crescenzi
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Ilaria Benedetti: Department of Economics, Engineering, Society and Business, University of Tuscia, 01100 Viterbo, Italy
Federico Crescenzi: Department of Statistics, Computer Science, Applications “G. Parenti”, University of Florence, 50134 Florence, Italy

Sustainability, 2020, vol. 12, issue 19, 1-12

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.

Keywords: child poverty; at-risk-of-poverty rate; uncertainty; bootstrap replication method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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