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Methods for estimating the quality of multisource statistics
van Delden,A. Scholtus,S. de Waal,T. Csorba,Irene
van Delden,A.
Scholtus,S.
de Waal,T.
Csorba,Irene
Abstract
With the increasing availability of data, official business statistics are more often based on multiple data sources. Evaluating accuracy, i.e. bias and variance, of output based on multiple sources has therefore become an important topic. Estimating the accuracy is important to inform users about data quality, and it can be a trigger to adjust processing steps when accuracy drops below an acceptable level. An inventory of methods to estimate output accuracy of multisource statistics has been made in the European project KOMUSO. The bias and variance of multisource statistics are affected by errors on the representation side (units and populations) and by errors on the measurement side. Additionally, when combining sources at microlevel, unit-level linkage errors may occur. We will introduce recently developed methods to estimate bias and variance of outputs as affected by representation error, linkage error, and measurement error, illustrated by examples for business statistics.
Description
Date
2023
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John Wiley & Sons Inc.
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Keywords
linkage error, measurement error, output accuracy, quality assessment, representation error
Citation
van Delden, A, Scholtus, S, de Waal, T & Csorba, I 2023, Methods for estimating the quality of multisource statistics. in Advances in business statistics, methods and data collection . John Wiley & Sons Inc., pp. 781-804. https://doi.org/10.1002/9781119672333.ch34