A compositional approach to predict small area proportions
D. Morales, M. D. Esteban Lefler, M. J. Lombardía Cortiña, M. E. López Vizcaíno, A. Pérez Martín
This talk introduces an area-level compositional mixed model by applying an additive logistic transformation to a multivariate Fay-Herriot model. Small area estimators of the proportions of a categorical variable are derived from the new model and the corresponding mean squared errors are estimated by parametric bootstrap. Several simulation experiments designed to analyze the behaviour of the introduced estimators are carried out. An application to real data from the Spanish Labour Force Survey of Galicia (north-west of Spain), in the first quarter of 2017, is given. The target is the estimation of domain proportions of people in the four categories of the variable labour status: under 16 years, employed, unemployed and inactive.
Palabras clave / Keywords: labour force survey, small area estimation, area-level models, compositional data, bootstrap, labour status
Programado
Sesión bilateral SEIO-DStatG: Small Area Estimation (Organizadores: Ralf Münnich y Domingo Morales)
1 de junio de 2018 12:30
Sala Cristal
Otros trabajos en la misma sesión
N. Rojas-Perilla
J. P. Burgard, M. D. Esteban Lefler, D. Morales, R. Münnich, A. Perez Martin
M. J. Lombardía Cortiña, E. López Vizcaíno, C. Rueda Sabater
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