EconPapers    
Economics at your fingertips  
 

Benchmarked Estimators for a Small Area Mean Under a Onefold Nested Regression Model

Marius Stefan and Michael Hidiroglou

International Statistical Review, 2021, vol. 89, issue 1, 108-131

Abstract: In this paper, we modify small area estimators, based on the unit‐level model, so that they add up to reliable higher‐level estimates of population totals. These modifications result in benchmarked small area estimators. We consider two benchmarking procedures. One is based on augmenting the unit‐level model with a suitable variable. The other one uses the calibrated weights of the direct estimators that are reliable at the higher levels. These weights are used in estimators that are based on the aggregation of the unit‐level model for each small area. The mean squared error estimators of the proposed benchmarked estimators are obtained by suitably modifying those associated with the corresponding non benchmarked estimators. The properties of the estimators are evaluated via simulation.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/insr.12380

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:89:y:2021:i:1:p:108-131

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0306-7734

Access Statistics for this article

International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg

More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-19
Handle: RePEc:bla:istatr:v:89:y:2021:i:1:p:108-131