Cost-effective Estimation of the Population Mean Using Prediction Estimators
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World Bank, Washington, DC
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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.
Palabras clave
prediction, double sampling, maximum likelihood, generalized method of moment, regression estimator