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Outlier Robust Small-Area Estimation Under Spatial Correlation, Timo Schmid, Nikos Tzavidis, Ralf Munnich, Raymond L. Chambers

Faculty of Engineering and Information Sciences - Papers: Part A

Modern systems of official statistics require the estimation and publication of business statistics for disaggregated domains, for example, industry domains and geographical regions. Outlier robust methods have proven to be useful for small-area estimation. Recently proposed outlier robust model-based small-area methods assume, however, uncorrelated random effects. Spatial dependencies, resulting from similar industry domains or geographic regions, often occur. In this paper, we propose an outlier robust small-area methodology that allows for the presence of spatial correlation in the data. In particular, we present a robust predictive methodology that incorporates the potential spatial impact from other areas (domains) on the small …