Multinomial-based small area estimation of labour force indicators*

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Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models (2017, unknown): “Under multinomial logit mixed models, the papers of López-Vizcaíno et al. (2013, 2015) on the estimation of small area proportions are remarkable.”
Small area estimation of labour force indicators under a multinomial model with correlated time and area effects (2015, methodology): “We emphasize that the approach introduced for estimating labour force indicators and also the indicators by Molina et al. (2007) and López-Vizcaı́no et al. (2013) are not adapted to the particularities of a complex sampling design.”
Empirical best prediction under area-level Poisson mixed models (2016, methodology): “…linear mixed model (GLMM) with logit link function, and with combination of Penalized Quasi-Likelihood (PQL) and REML for estimation of unknown parameters have been considered by Saei and Chambers (2003), Johnson et al. (2010), López-Vizcáıno et al. (2013) and López-Vizcáıno et al. (2015).”