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The paper reviews empirical best linear prediction (EBLUP) and the associated jackknife MSE estimator of EBLUP. The bias of jackknife MSE estimator is of order o(m −1), where m is the number of small areas. The jackknife works well both for normal and nonnormal Fay-Herriot models. The proposed methodology is illustrated using a real life example from the(More)
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