Robust Small Area Estimation Using a Mixture Model

Julie B. Gershunskaya


Different methods have been proposed in the small area estimation literature to deal with outliers in individual observations and in the area-level random effects. In this paper, we propose a new method based on a scale mixture of two normal distributions. Using a simulation study, we compare the performance of a few recently proposed robust small area estimators and our proposed estimator based on a mixture distribution. We then compare the proposed method with the existing methods to estimate monthly employment changes in the metropolitan statistical areas using data from the Current Employment Statistics Survey conducted by the U.S. Bureau of Labor Statistics (BLS).