Small area estimation under an inverse Gaussian model

In this paper, we consider analysis of variance methodology for inverse Gaussian distribution and adapt it for estimation of small area parameters in finite populations. It is demonstrated, through a Monte Carlo study, that these estimators offer a competitive choice for positively skewed survey data such as income or yield of a particular sector.