Standard error estimation for the EU-SILC indicators of poverty and social exclusion

Abstract

Since EU-SILC was launched, much attention has been paid to sampling errors. However, the computation of standard errors for estimates based on EU-SILC is confronted with several challenges. In this article, we propose a simple approach for standard error estimation based upon basic statistical techniques. The proposed estimator is simple and flexible, yet theoretically justified. It can accommodate nearly all the sampling designs and the target indicators used in EU-SILC, no matter their complexity. The proposed approach can be easily implemented with standard statistical software (SAS, SPSS, Stata, R…) and requires minimal computing power. We illustrate the proposed approach by showing preliminary standard error estimates for key EU-SILC indicators of poverty and social exclusion: the new “Europe-2020” indicator of poverty or social exclusion (AROPE indicator) and the persistent at-risk-of-poverty rate, which is the core EU-SILC longitudinal indicator. The change in the AROPE between two years is also considered. It is necessary to estimate the standard error of changes to judge whether the observed differences are statistically significant.

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ORCID for Yves G. Berger: orcid.org/0000-0002-9128-5384

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