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Abstract
Journal of Official Statistics, Vol.27, No.3, 2011. pp. 467490

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Algorithms for Correcting Sign Errors and Rounding Errors in Business Survey Data

Abstract:
Selective editing is often used for the data of structural business surveys. Records containing potentially influential errors are edited manually, whereas the other, noncritical records can be edited automatically. At Statistics Netherlands, the automatic editing is performed by an advanced software package called SLICE. Prior to this several types of obvious inconsistencies are detected and corrected deductively. This article describes two additional types of frequently occurring obvious inconsistencies, sign errors and rounding errors. Simple algorithms are given that detect and correct these errors. Correction of these errors in a separate step will increase the efficiency of the subsequent editing process, because more records will be eligible (and suitable) for automatic editing. By way of illustration, the algorithms are applied to real data from the Dutch structural business survey.

Keywords:
Structural business statistics, automatic editing, deductive correction, sign errors, rounding errors

Copyright Statistics Sweden 1996-2018.  Open Access
ISSN 0282-423X
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