Automated and Manual Data Editing: A View on Process Design and Methodology

Pannekoek Jeroen (), Scholtus Sander () and Mark Van der Loo ()
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Pannekoek Jeroen: Statistics Netherlands, P.O. Box 24500, 2490 HA The Hague, The Netherlands
Scholtus Sander: Statistics Netherlands, P.O. Box 24500, 2490 HA The Hague, The Netherlands
Mark Van der Loo: Statistics Netherlands, P.O. Box 24500, 2490 HA The Hague, The Netherlands

Journal of Official Statistics, 2013, vol. 29, issue 4, 511-537

Abstract: Data editing is arguably one of the most resource-intensive processes at NSIs. Forced by everincreasing budget pressure, NSIs keep searching for more efficient forms of data editing. Efficiency gains can be obtained by selective editing, that is, limiting the manual editing to influential errors, and by automating the editing process as much as possible. In our view, an optimal mix of these two strategies should be aimed for. In this article we present a decomposition of the overall editing process into a number of different tasks and give an upto- date overview of all the possibilities of automatic editing in terms of these tasks. During the design of an editing process, this decomposition may be helpful in deciding which tasks can be done automatically and for which tasks (additional) manual editing is required. Such decisions can be made a priori, based on the specific nature of the task, or by empirical evaluation, which is illustrated by examples. The decomposition in tasks, or statistical functions, also naturally leads to reuseable components, resulting in efficiency gains in process design.

Keywords: Automatic editing; selective editing; edit rules; process design; process evaluation (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:29:y:2013:i:4:p:511-537:n:3

DOI: 10.2478/jos-2013-0038

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