Standard error estimation for the EU-SILC indicators of poverty and social exclusion : 2013 edition

The computation of standard errors for estimates based on EU-SILC is confronted with several challenges. This working Paper proposes a simple and flexible approach for standard error estimation, yet methodologically justified. It can accommodate nearly all sampling designs and indicators based on EU-SILC, no matter their complexity. The proposed approach can be easily implemented with standard statistical software and requires minimal computing power. It is illustrated by showing preliminary standard error estimates for key EU-SILC indicators: the "Europe-2020" indicator of poverty or social exclusion (AROPE) 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 as it is necessary to estimate its standard error to judge whether the observed evolutions are statistically significant.