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Mapping the Poverty Proportion in Small Areas under Random Regression Coefficient Poisson Models
dc.contributor.author | Diz-Rosales, Naomi | |
dc.contributor.author | Lombardía, María José | |
dc.contributor.author | Morales, Domingo | |
dc.date.accessioned | 2023-11-15T14:56:02Z | |
dc.date.available | 2023-11-15T14:56:02Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/2183/34236 | |
dc.description | Cursos e Congresos, C-155 | es_ES |
dc.description.abstract | [Abstract] In a complex socio-economic context, policy makers need highly disaggregated poverty indicators. In this work, we develop a methodology in small area estimation to derive predictors of poverty proportions under a random regression coefficient Poisson model, introducing bootstrap estimators of mean squared errors. Maximum likelihood estimators of model parameters and random effects mode predictors are calculated using a Laplace approximation algorithm. Simulation experiments are conducted to investigate the behaviour of the fitting algorithm, the predictors and the mean squared error estimator. The new statistical methodology is applied to data from the Spanish survey of living conditions to map poverty proportions by province and sex, developing a tool to support policy decision making | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2020/14 | es_ES |
dc.description.sponsorship | This research is part of the grant PID2020-113578RB-I00, funded by MCIN/AEI/10.13039/501100011033/. It has also been supported by the Spanish grant PID2022-136878NB-I00, the Valencian grant Prometeo/2021/063, by the Xunta de Galicia (Competitive Reference ED431C-2020/14) and by CITIC that is supported by Xunta de Galicia, collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Sistema Universitario de Galicia (CIGUS). The first author was also sponsoredby the Spanish Grant for Predoctoral Research Trainees RD 103/2019 being this work part of grant PRE2021-100857, funded by MCIN/AEI/10.13039/501100011033/ and ESF+ | |
dc.language.iso | eng | es_ES |
dc.publisher | Universidade da Coruña, Servizo de Publicacións | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/MÉTODOS ESTADÍSTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORÍA Y APLICACIONES | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-136878NB-I00/ES/ESTIMACION EN AREAS PEQUEÑAS Y MODELOS MULTIVARIANTES MIXTOS | es_ES |
dc.relation.uri | https://doi.org/10.17979/spudc.000024.18 | |
dc.rights | Attribution 4.0 International (CC BY 4.0) | es_ES |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/deed.es | * |
dc.subject | Algoritmos de aproximación | es_ES |
dc.subject | Simulación | es_ES |
dc.subject | Pobreza | es_ES |
dc.title | Mapping the Poverty Proportion in Small Areas under Random Regression Coefficient Poisson Models | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.startPage | 109 | es_ES |
UDC.endPage | 115 | es_ES |
UDC.conferenceTitle | VI Congreso Xove TIC: impulsando el talento científico. Octubre, 2023, A Coruña | es_ES |