Poisson mixed models for studying the poverty in small areas

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• 作者：Miguel Boubeta^a ; Marí ; a José ; Lombardí ; a^a ; ^{maria.jose.lombardia@udc.es} ; Domingo Morales^b
• 关键词：Bootstrap ; Empirical best predictor ; Mean squared error ; Moment-based method ; Poisson mixed models ; Poverty proportion ; Time dependency
• 刊名：Computational Statistics & Data Analysis
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：107
• 期：Complete
• 页码：32-47
• 全文大小：857 K
• 卷排序：107

文摘

Empirical best predictors are studied under area-level Poisson mixed models with time effects. Four cases are considered. The first two cases use independent time random effects. In the second two cases, the time effects follow an autoregressive process of order one. The four models are fitted by the moment-based method and the corresponding empirical best predictors are derived and compared with plug-in predictors. Several simulation experiments investigate the performance of both predictors. A parametric bootstrap procedure is considered for estimating the mean squared error. The developed methodology is applied to estimate the proportion of people under the poverty line by counties and sex in Galicia (a region in north-west of Spain).