Cost-effective Estimation of the Population Mean Using Prediction Estimators

dc.creatorFujii, Tomoki
dc.creatorvan der Weide, Roy
dc.date2013-09-26T17:15:15Z
dc.date2013-09-26T17:15:15Z
dc.date2013-06
dc.date.accessioned2026-07-01T01:01:24Z
dc.descriptionThis paper considers the prediction estimator as an efficient estimator for the population mean. The study may be viewed as an earlier study that proved that the prediction estimator based on the iteratively weighted least squares estimator outperforms the sample mean. The analysis finds that a certain moment condition must hold in general for the prediction estimator based on a Generalized-Method-of-Moment estimator to be at least as efficient as the sample mean. In an application to cost-effective double sampling, the authors show how prediction estimators may be adopted to maximize statistical precision (minimize financial costs) under a budget constraint (statistical precision constraint). This approach is particularly useful when the outcome variable of interest is expensive to observe relative to observing its covariates.
dc.formatapplication/pdf
dc.formattext/plain
dc.identifierhttp://documents.worldbank.org/curated/en/2013/06/17928599/cost-effective-estimation-population-mean-using-prediction-estimators
dc.identifierhttps://hdl.handle.net/10986/15868
dc.identifierhttps://doi.org/10.1596/1813-9450-6509
dc.identifier.urihttp://hdl.handle.net/123456789/414333
dc.languageEnglish
dc.languageen_US
dc.publisherWorld Bank, Washington, DC
dc.relationPolicy Research Working Paper;No. 6509
dc.rightsCC BY 3.0 IGO
dc.rightshttp://creativecommons.org/licenses/by/3.0/igo/
dc.rightsWorld Bank
dc.subjectprediction
dc.subjectdouble sampling
dc.subjectmaximum likelihood
dc.subjectgeneralized method of moment
dc.subjectregression estimator
dc.titleCost-effective Estimation of the Population Mean Using Prediction Estimators

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