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Explore the challenges in statistical data editing processes, highlighting the dichotomy between "Us" and "Them" in decision-making. Learn how to align methods for stable time series and economy overviews while addressing the need for coherence in related subprocesses.
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Post-editing: a source of inconsistencies We are not alone! Ton de Waal,UN/ECE Work Session on Statistical Data Editing,Bonn, September 2006
Results of sociological and psychological research • Over 40 years of research has shown that basically two kinds of persons exist: • Us • Them • Main characteristic of us: • Always right, unless misinformed by them • Main characteristic of them: • Always wrong, unless they listen to advice given by us
Example of one of us • One of us could be responsible for monthly business statistics for certain branch of industry • focuses on specific domains for that branch • uses population frame available at that moment • uses background information available at that moment • aims for stable time series without much fluctuations over time • reducing fluctuations (variation) is more important than bias • many outliers are identified
Example of one of them • One of them could be responsible for National Accounts • may focus on other domains as us • uses updated population frame • uses updated and more background information • aims for overview of entire economy • reducing bias is more important than reducing variance • less outliers need to be identified
Problem of NSI’s • NSI’s need to produce information on related topics, but on different moments and from different points of view • Short term business statistics • Annual business statistics • Price indexes • National Accounts • Who are “us” and who are “them”?
Conclusion • Need to aim for coherence and consistency across chain of related subprocesses • Agreements need to be made between various subprocesses • Methods of various subprocesses need to be geared one another • We are not alone!
