Hierarchical Bayes multivariate estimation of poverty rates based on increasing thresholds for small domains

Fabrizi, Enrico; Ferrante, Maria Rosaria; Pacei, Silvia; Trivisano, Carlo

doi:10.1016/j.csda.2010.11.001

Cited by 20 publications

(15 citation statements)

References 12 publications

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“…However, these sampling covariances are sometimes modelled and given structure (e.g. Fay, 1987;Huang & Bell, 2004;González-Manteiga et al, 2008;Fabrizi et al, 2011).…”

Section: Motivating Datamentioning

confidence: 99%

Multivariate spatial hierarchical Bayesian empirical likelihood methods for small area estimation

Porter

Holan

Wikle

2015

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Recent advances in small area estimation incorporating both explicit spatial autocorrelation and empirical likelihood techniques have produced estimates with greater precision. Furthermore, the multivariate Fay–Herriot models take advantage of within‐location correlation between multiple outcomes for a set of small areas. We extend the Fay–Herriot model by utilizing empirical likelihood techniques to the spatially explicit multivariate setting. We then model the five‐year period estimates from the American Community Survey (2006–10) of percent of unemployed individuals and percent of families in poverty for the counties of Missouri. We demonstrate bivariate reduction in leave‐one‐out median absolute deviation over an approximately equivalently specified parametric model. Copyright © 2015 John Wiley & Sons, Ltd.

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“…However, these sampling covariances are sometimes modelled and given structure (e.g. Fay, 1987;Huang & Bell, 2004;González-Manteiga et al, 2008;Fabrizi et al, 2011).…”

Section: Motivating Datamentioning

confidence: 99%

Multivariate spatial hierarchical Bayesian empirical likelihood methods for small area estimation

Porter

Holan

Wikle

2015

Stat

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“…The algorithm was tested by means of simulation exercises and found to provide estimates close to those obtained using the linearization method for simpler parameters (i.e., averages) for which this latter method may be applied. It has also been applied to the same data by Fabrizi et al (2011a).…”

Section: Mean Square Error Estimationmentioning

confidence: 99%

Mapping average equivalized income using robust small area methods

Fabrizi

Giusti

Salvati

et al. 2014

Papers in Regional Science

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Measures of economic well‐being are often needed for geographically small areas, as economic indicators may be distributed unevenly among the subsets of relatively small regions. We consider small area estimation of average equivalized income. Disposable household income data are usually available only for a sample of households, typically too small to provide reliable estimates for small regions. We consider a small area estimation technique that is robust to outliers, produces results consistent with design weighted estimates obtained for larger areas and yield maps with approximately no shrinkage. The proposed methodology is applied to the Local Labour Systems in Tuscany (Italy).

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“…A multivariate logistic–normal model was adopted by Fabrizi et al . () with the aim of estimating poverty rates based on various thresholds.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

“…Ferrante and Trivisano (2010) proposed a multivariate SAE approach for count data based on the multivariate Poisson-log-normal distribution. A multivariate logistic-normal model was adopted by Fabrizi et al (2011) with the aim of estimating poverty rates based on various thresholds. This paper is organized as follows.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Small Domain Estimation of Business Statistics by Using Multivariate Skew Normal Models

Ferrante

Pacei

2017

Journal of the Royal Statistical Society Series A: Statistics in Society

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Summary Small domain business statistics are becoming important for better planning business policies. We focus on the estimation of the averages of value added and labour cost in small domains. To take into account the positive skewness in the distribution of outcomes and the correlation between them, we propose a bivariate skew normal small area model. Estimates are obtained from real survey data. The performance of the estimator proposed is evaluated on the basis of both survey data and a synthetic firm population. Results show that the model proposed increases the estimates’ reliability and that the estimates obtained make it possible to perform detailed regional economic studies.

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Hierarchical Bayes multivariate estimation of poverty rates based on increasing thresholds for small domains

Cited by 20 publications

References 12 publications

Multivariate spatial hierarchical Bayesian empirical likelihood methods for small area estimation

Multivariate spatial hierarchical Bayesian empirical likelihood methods for small area estimation

Mapping average equivalized income using robust small area methods

Small Domain Estimation of Business Statistics by Using Multivariate Skew Normal Models

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