Publication Type

Working Paper

Version

publishedVersion

Publication Date

6-2013

Abstract

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.

Keywords

Prediction, Double Sampling, Maximum Likelihood, Generalized Method Of Moment, Regression Estimator

Discipline

Econometrics | Macroeconomics

Research Areas

Applied Microeconomics

Issue

6509

First Page

1

Last Page

36

Identifier

10.1596/1813-9450-6509

Publisher

World Bank Policy Research Working Paper 6509

City or Country

Washington, DC

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

Additional URL

https://doi.org/10.1596/1813-9450-6509

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