Efficient small-domain estimation by combining information from multiple surveys through regression / Takis Merkouris.: CS11-619/2006-7E-PDF

"In this paper, we explore the possibility of enhancing the precision of domain estimators by combining comparable information collected in multiple surveys of the same population. To this end, we propose a regression method of estimation that is essentially an extended calibration procedure whereby comparable domain estimates from the various surveys are calibrated to each other. We show through analytic results and an empirical study that this method may greatly improve the precision of domain estimators for the variables that are common to these surveys, as these estimators make effective use of increased sample size for the common survey items. The proposed design-based direct estimators involve only domain-specific data on the variables of interest. This is in contrast to small-domain (mostly, small-area) indirect estimators, based on a single survey, which incorporate through modeling data that are external to the targeted small domains. The proposed approach is also highly effective in handling the closely related problem of estimation for rare population characteristics"--Abstract.

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