Canadian Journal of Statistics

Benchmarked small area prediction

Early View

Abstract

Small area estimation often involves constructing predictions with an estimated model followed by a benchmarking step. In the benchmarking operation, the predictions are modified so that weighted sums satisfy constraints. The most common constraint is the constraint that a weighted sum of predictions is equal to the same weighted sum of the original observations. Two benchmarking procedures for nonlinear models are proposed: a linear additive adjustment and a method based on an augmented model for the expectation function. Variance estimators for benchmarked predictors are presented and vetted through simulation studies. The benchmarking procedures are applied to county estimates of the proportion of area in cropland using data from the National Resources Inventory.

Related Topics

Related Publications

Related Content

Site Footer

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.