Estimation within the new integrated system of household surveys in Germany

Saeideh Kamgar (), Florian Meinfelder (), Ralf Münnich () and Hamidreza Navvabpour ()
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Saeideh Kamgar: Allameh Tabataba’i University
Florian Meinfelder: Universität Bamberg
Ralf Münnich: Universität Trier, FB IV, VWL
Hamidreza Navvabpour: Allameh Tabataba’i University

Statistical Papers, 2020, vol. 61, issue 5, No 14, 2117 pages

Abstract: Abstract In 2015, the European Commission has drafted a framework regulation for integrated European social statistics. This integration covers the Labour Force Survey, the Statistics on Income and Living conditions, and others. In order to avoid an inappropriate response burden, administrative and other sources shall be considered to achieve accurate survey estimates. Combining information from different data sources has become a field of growing research interest among statistical offices and other institutions. In the statistical literature this problem is known as data fusion or statistical matching, and is widely considered as a particular missing-data pattern. Assuming that budgets are limited, and that only some additional information can be obtained to improve the quality of the data fusion, we investigate different scenarios of using these limited resources within an integrated system of household surveys. Our main objective is to develop a framework that fosters on the one hand the estimation of statistical models using several surveys, and on the other hand classical totals for different sub-classes and areas which are of special interest for official statistics.

Keywords: Missing-by-design patterns; Split questionnaire designs; Multiple imputation; Small area estimation (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s00362-018-1023-z

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