The literature of Small Area Estimation (SAE) is dominated by sample‐survey‐based applications, where administrative register data are used as covariates in the models. This chapter characterizes the settings of SAE which involve administrative data according to whether there are relevant additional sample survey data present and, if so, how the target measure is related to the available data in the two sources. Register‐based statistics, however, are becoming more and more common, and integration of survey and administrative data can raise many distinct issues. The chapter talks about the time lag that exists in many registers, including sampling error, measurement error arising from progressive administrative data, coverage error, relevance error and probability linkage error. Coverage errors in the context of population size estimation are discussed. The two settings considered in detail include register‐based SAE without any survey data, and SAE based on integration of sample survey and register data.


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    Title :

    Small Area Methods and Administrative Data Integration


    Contributors:


    Publication date :

    2016-02-29


    Size :

    21 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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