Cost-effective Estimation of the Population Mean Using Prediction Estimators

This 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 outperf...

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Bibliographic Details
Main Authors: Fujii, Tomoki, van der Weide, Roy
Format: Publications & Research
Language:English
en_US
Published: World Bank, Washington, DC 2013
Subjects:
Online Access:http://documents.worldbank.org/curated/en/2013/06/17928599/cost-effective-estimation-population-mean-using-prediction-estimators
http://hdl.handle.net/10986/15868
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Summary:This 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.