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Does the model matter for GREG estimation?: a business survey example
Stockholm University, Faculty of Social Sciences, Department of Statistics. (Department of Statistics)
Office for National Statistics, U.K..
University of Southampton.
2001 (English)In: Journal of Official Statistics, ISSN 0282-423X, E-ISSN 2001-7367, Vol. 17, no 4, 527-544 p.Article in journal (Refereed) Published
Abstract [en]

Although asymptotically design-unbiased, GREG estimators may produce bad estimates. The paper examines the behaviour of GREG estimators when the underlying models are misspecified. It shows how an efficient GREG estimator was found for a business survey that posed some problems. The work involved data exploration in several steps, combined with analyses of g-weights, residuals and standard regression diagnostics. We discuss two diagnostics for whether a GREG estimate is reasonable or not. A common justification for the use of GREG estimators is that, being asymptotically design unbiased, they are relatively robust to model choice. However, we show that the property of being asymptotically design unbiased is not a substitute for a careful model specification search, especially when dealing with the highly variable and outlier prone populations that are the focus of many business surveys.

Place, publisher, year, edition, pages
Stockholm: Statistics Sweden , 2001. Vol. 17, no 4, 527-544 p.
Keyword [en]
Generalised regression estimator; g-weight function; outliers; model misspecificatio.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:su:diva-85773OAI: oai:DiVA.org:su-85773DiVA: diva2:584783
Available from: 2013-01-09 Created: 2013-01-09 Last updated: 2017-12-06Bibliographically approved

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