Small area estimation with spatiotemporal mixed model

A spatiotemporal model with nested random effects is proposed for small area estimation where sample data are generated from a rotating panel survey. Two methods of estimation are introduced, integrating the backfitting algorithm and bootstrap procedure in two different approaches. Simulation study shows superior predictive ability of the fitted model. The small area estimation methods also produced efficient estimates of parameters in a wide class of population scenarios. The model-based small area estimation procedure is also better over the design-based approach in estimating unemployment rate from the Philippine Labor Force Survey.