Abstract

Spatial version of multivariate Fay–Herriot model is introduced and small area predictor under this model is proposed. The residual maximum likelihood is employed for estimating the parameters of the proposed model. Analytical and bootstrap approaches for estimating the mean squared error (MSE) of the proposed predictor are also developed. The performance of the proposed predictor and the MSE estimators are evaluated through various simulation studies. The results evidently show that the proposed predictor outperforms the existing predictors. An application of the proposed methodology has also been made using the 2011–12 Consumer Expenditure Survey data of India.