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Inferential Issues in Model-Based Small Area Estimation: Some New Developments

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  • Rao J. N. K.

    (Carleton University, Ottawa, Canada)

Abstract

Small area estimation (SAE) has seen a rapid growth over the past 10 years or so. Earlier work is covered in the author’s book (Rao 2003). The main purpose of this paper is to highlight some new developments in model-based SAE since the publication of the author’s book. A large part of the new theory addressed practical issues associated with the model-based approach, and we present some of those methods for area level and unit level models. We also briefly mention some new work on synthetic estimation of area means or totals based on implicit models.

Suggested Citation

  • Rao J. N. K., 2015. "Inferential Issues in Model-Based Small Area Estimation: Some New Developments," Statistics in Transition New Series, Polish Statistical Association, vol. 16(4), pages 491-510, December.
  • Handle: RePEc:vrs:stintr:v:16:y:2015:i:4:p:491-510:n:2
    DOI: 10.21307/stattrans-2015-029
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    References listed on IDEAS

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    1. Berg, Emily & Chandra, Hukum, 2014. "Small area prediction for a unit-level lognormal model," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 159-175.
    2. Gauri Datta & Tatsuya Kubokawa & Isabel Molina & J. Rao, 2011. "Estimation of mean squared error of model-based small area estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 367-388, August.
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