Small area estimation of average compositions under multivariate nested error regression models

E. López vizcaíno, D. Morales, M. J. Lombardía Cortiña, A. Pérez Martín, M. D. Esteban Lefler

This communication investigates the small area estimation of population averages of unit-level compositional data. The new methodology transforms the compositions into vectors of Rm and assumes that the vectors follow a multivariate nested error regression model. Empirical best predictors of domain indicators are derived from the fitted model and their mean squared errors are estimated by parametric bootstrap. An application
to real data from the Spanish household budget survey, in 2016, is given. The target is to
estimate the average of proportions of annual household expenditures on food, housing and others, by Spanish provinces.

Keywords: small area estimation, nested error regression models, compositional data, household budget surveys

Scheduled

Statistical Models I
June 10, 2022  10:10 AM
A11

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