Small area estimation of the proportion of single-person households : Application to the Spanish Household Budget Survey
Bugallo, María (Universidad Miguel Hernández de Elche)
Morales, Domingo (Universidad Miguel Hernández de Elche)
Esteban, María Dolores (Universidad Miguel Hernández de Elche)

Data:	2024
Resum:	Household composition reveals vital aspects of the socioeconomic situation and major changes in developed countries for decision-making and mapping the distribution of single-person households is highly relevant and useful. Driven by the Spanish Household Budget Survey data, we propose a new statistical methodology for small area estimation of proportions and total counts of single-person households. Estimation domains are defined as crosses of province, sex and age group of the main breadwinner of the household. Predictors are based on area-level zero-inflated Poisson mixed models. Model parameters are estimated by maximum likelihood and mean squared errors by parametric bootstrap. Several simulation experiments are carried out to empirically investigate the properties of these estimators and predictors. Finally, the paper concludes with an application to real data from 2016.
Ajuts:	Ministerio de Ciencia, Innovación y Universidades PGC2018-096840-B-I00
Nota:	Altres ajuts: Govern Valencià, projecte PROMETEO-2021-063
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Small area estimation ; Zero-inflated poisson mixed model ; Area-level data ; Household budget survey ; Single-person household
Publicat a:	SORT : statistics and operations research transactions, Vol. 48 Núm. 1 (2024) , p. 125-152, ISSN 2013-8830

Adreça original: https://raco.cat/index.php/SORT/article/view/428636
DOI: 10.57645/20.8080.02.16

28 p, 4.0 MB

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