Cost-effective estimation of the population mean using prediction estimators
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by The World Bank in its series Policy Research Working Paper Series with number 6509.
Date of creation: 01 Jun 2013
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-07-05 (All new papers)
- NEP-ECM-2013-07-05 (Econometrics)
- NEP-FOR-2013-07-05 (Forecasting)
You can help add them by filling out this form.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Roula I. Yazigi).
If references are entirely missing, you can add them using this form.