Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain
Domingo Morales (),
María del Mar Rueda () and
Dolores Esteban ()
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Domingo Morales: Miguel Hernández University of Elche
María del Mar Rueda: University of Granada
Dolores Esteban: Miguel Hernández University of Elche
Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2018, vol. 138, issue 3, 873-900
Abstract This paper introduces small area estimators of poverty indexes, with special attention to the poverty rate (or Head Count Index), and studies the sampling design consistency and the asymptotic normality of these estimators. The estimators are assisted by nested error regression models and are model-assisted counterparts of model-based empirical best predictors. Simulation studies show that these estimators present a good balance between sampling bias and mean squared error. Data from the 2013 Spanish living conditions survey with respect to the region of Valencia are used to determine the performance of this new method for estimating the poverty rate.
Keywords: Small area estimation; Poverty index; Model-assisted estimation; Nested error regression model; Empirical best predictor (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:soinre:v:138:y:2018:i:3:d:10.1007_s11205-017-1678-1
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