For example, 4 out of the 21 Italian regions have poverty headcounts overlapping the national value, so that the statistical difference of the estimates for these regions and the national values cannot be confirmed at a 5% confidence level. Data providers can also usefully ‘flag’ estimates with high sampling error, using simple criteria such as the number of sampled household in the respective cell or defining reliability thresholds based on the coefficient of variation. Standard errors or other quality assessments are however not routinely published for regional data. Such information cannot be easily produced by researchers from micro-data files as the computation of sampling error need to take into account variations in the sampling design. Unfortunately, detailed information on the sampling structure is rarely available in the public-use files of household surveys such as the EU-SILC.