There is an urgent need for regional indicators, especially on poverty and social exclusion, by policy makers in the EU. Surveys which were designed to estimate these indicators on national level, such as EU-SILC, usually do not provide the required precision for reliable estimates on regional levels like NUTS2 and below.

With the R-Package ‚surveysd‘, available on CRAN, we present a package for estimating standard errors for yearly surveys with and without rotating panel design. Using surveys with complex survey designs e.g. multistage sampling design is supported and can be freely defined. The implemented method for standard error estimation uses bootstrapping techniques in combination with multiple consecutive waves of the survey. This leads to a reduction in the standard error, especially for estimates done on a subgroup of the survey data. The package enables the user to estimate point estimates as well as their standard error on arbitrary subgroups of his/her data. Also the applied point estimate can freely be chosen, although some predefined point estimates are already implemented. Finally the results can be visualized in two different ways to gain quick insight in the quality of the estimated results.