Small area estimation of proportions under area-level compositional mixed models

15.03.2019 11:15 – 12:15

RESEARCH CENTER FOR STATISTICS SEMINAR / ABSTRACT

This paper introduces area-level compositional mixed models by applying transformations to a multivariate Fay-Herriot model. Small area estimators of the proportions of the categories of a classification 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.

Lieu

Bâtiment: Uni Mail

Bd du Pont-d'Arve 40
1205 Geneva

Room: M 5220, 5th floor

Organisé par

Faculté d'économie et de management
Research Center for Statistics

Intervenants

Domingo MORALES, Professor at Centro de Investigación Operativa, Universidad Miguel Hernández de Elche, Spain

entrée libre

Classement

Catégorie: Séminaire

Mots clés: Linear mixed models, Small area estimation, Time correlation, Poverty proportions

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www.unige.ch/gsem/en/research/seminars/rcs/

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