Regression modelSurvey estimation

Small Area Estimation (Fay-Herriot Model)

Small Area Estimation (SAE) refers to statistical techniques that produce reliable estimates for subpopulations — geographical regions, demographic groups, or administrative units — where direct survey samples are too sparse to yield acceptable precision. The Fay-Herriot model, introduced by Robert Fay and Roger Herriot in 1979, is the canonical area-level SAE model. It supplements weak direct survey estimates with auxiliary covariate information through an empirical Bayes or BLUP framework, substantially reducing mean squared error for small domains.

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Sources

  1. Fay, R. E., & Herriot, R. A. (1979). Estimates of income for small places: An application of James-Stein procedures to census data. Journal of the American Statistical Association, 74(366), 269–277. DOI: 10.1080/01621459.1979.10482505

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Referenced by

ScholarGateSmall Area Estimation (Small Area Estimation (Fay-Herriot Model)). Retrieved 2026-06-04 from https://scholargate.app/en/survey-methodology/small-area-estimation