Bootstrap confidence intervals for total value in small area statistics

In small area statistics, many problems deal with the estimation of unknown parameters. This paper will consider interval estimation. Three bootstrap confidence intervals of the total value for the small area are proposed. They are obtained by the percentile method, the t-bootstrap method, and the two-stage t-bootstrap method in the case of application of the count post-stratification estimator for total value. The proposed procedures are illustrated with simulation examples in which the investigated variable has the normal or Poisson distribution in population strata. We do not have to know the population or small area distribution for determining the bootstrap confidence intervals for small area parameters. This is the great advantage of bootstrap methods.