National statistical institutes (NSIs) fulfil an important role as providers of objective and undisputed statistical information on many different aspects of society. To this end NSIs try to construct data sets that are rich in information content and that can be used to estimate a large variety of population figures. At the same time NSIs aim to construct these rich data sets as efficiently and cost effectively as possible. This can be achieved by utilizing already available administrative data as much as possible, and supplementing these administrative data with survey data collected by the NSI. In this paper we focus on one of the challenges when using a mix of administrative data sets and surveys, namely obtaining numerically consistent population estimates. We will sketch general approaches based on weighting, imputation and macro-integration for solving this problem, and discuss their advantages and drawbacks.
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