Small area estimation with state-space common factor models for rotating panels

Macroeconomic indicators about the labour force, published by national statistical institutes, are predominantly based on rotating panels. Sample sizes of most labour force surveys in combination with the design-based or model-assisted mode of inference obstruct the publication of such indicators on a monthly frequency. Previous research proposed a multivariate structural time series model to obtain more precise model-based estimates by taking advantage of sample information observed in previous periods. In the paper this model is extended to use sample information from other domains or strongly correlated auxiliary series. A relatively parsimonious version of these models is currently used by Statistics Netherlands to produce official monthly figures about the labour force.