Empirical best linear unbiased predictors in multivariate nested-error regression models

Tsubasa Ito and Tatsuya Kubokawa

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 10, 2224-2249

Abstract: For analyzing unit-level multivariate data in small area estimation, we consider the multivariate nested error regression model (MNER) and provide the empirical best linear unbiased predictor (EBLUP) of a small area characteristic based on second-order unbiased and consistent estimators of the ‘within’ and ‘between’ multivariate components of variance. The second-order approximation of the mean squared error (MSE) matrix of the EBLUP and its unbiased estimator are derived in closed forms. The confidence interval with second-order accuracy is also provided analytically.

Date: 2021
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DOI: 10.1080/03610926.2019.1662048

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