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 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.
Prediction, Double Sampling, Maximum Likelihood, Generalized Method Of Moment, Regression Estimator
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Fujii, Tomoki and van der Weide, Roy.
Cost-effective estimation of the population mean using prediction estimators. (2013). 1-36. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1523
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