Small area estimation is any of several statistical techniques involving the estimation of parameters for small sub-populations, generally used when the sub-population of interest is included in a larger survey.

The term "small area" in this context generally refers to a small geographical area such as a county. It may also refer to a "small domain", i.e. a particular demographic within an area. If a survey has been carried out for the population as a whole (for example, a nation or statewide survey), the sample size within any particular small area may be too small to generate accurate estimates from the data. To deal with this problem, it may be possible to use additional data (such as census records) that exists for these small areas in order to obtain estimates.

One of the more common small area models represents the county-level effect of any area characteristics unaccounted for.

The Fay-Herriot model, a random effects model, has been used to make estimates for small domains when the sample from each domain is too small for fixed effects.

Further reading

• G. E Battese, R. M Harter & W. A Fuller. "An error component model for prediction of county crop areas using survey and satellite data", Journal of the American Statistical Association, 83, 28–36. https://www.jstor.org/stable/2288915

• M. Ghosh, J. N. K. Rao. "Small area estimation: An appraisal", Statistical Science, vol 9, no.1 (1994), 55–76. http://projecteuclid.org/euclid.ss/1177010647

• Jiang, J., and Lahiri, P. "Mixed model prediction and small area estimation", Editor's invited discussion paper, "Test," Vol. 15, 1, (2006), 1-96.

• Danny Pfefferman. "Small area estimation – New developments and directions", International Statistical Review (2002), 70, 1, 125–143.

• J. N. K. Rao (2003), Small area estimation, Wiley, .