A Comparison of Small Area Estimation Methods for Poverty Mapping

• Autorzy: María Guadarrama , Isabel Molina , J. N. K. Rao
• Języki publikacji: EN

Abstrakty

EN

We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes proposal of Molina, Nandram and Rao (2014). We put ourselves in the point of view of a practitioner and discuss, as objectively as possible, the benefits and drawbacks of each method, illustrating some of them through simulation studies. (original abstract)

Słowa kluczowe

EN

Small area estimates; Poverty indicators; Estimators

PL

Statystyka małych obszarów; Wskaźniki ubóstwa; Estymatory

• Czasopismo: Statistics in Transition
• Rocznik: 2016
• Tom: 17
• Numer: nr 1
• Strony: 41--66

Twórcy

autor

María Guadarrama

• Universidad Carlos III de Madrid

autor

Isabel Molina

• Universidad Carlos III de Madrid

autor

J. N. K. Rao

• Carleton University, Canada

Bibliografia

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