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Author
Azevedo Neves André Felipe (National School of Statistical Sciences, Brazil), do Nascimento Silva Denise Britz (National School of Statistical Sciences, Brazil), da Silva Moura Fernando Antonio (Federal University of Rio de Janeiro, Brazil)
Title
Skew Normal Small Area Time Models for the Brazilian Annual Service Sector Survey
Source
Statistics in Transition, 2020, vol. 21, nr 4 Special Issue, s. 84-102, rys., tab., dodatek, bibliogr. s. 98-99
Keyword
Statystyka małych obszarów, Modele bayesowskie, Sektor usług
Small area estimates, Bayesian models, Services sector
Note
summ.
Country
Brazylia
Brazil
Abstract
Small domain estimation covers a set of statistical methods for estimating quantities in domains not previously considered by the sample design. In such cases, the use of a model-based approach that relates sample estimates to auxiliary variables is indicated. In this paper, we propose and evaluate skew normal small area time models for the Brazilian Annual Service Sector Survey (BASSS), carried out by the Brazilian Institute of Geography and Statistics (IBGE). The BASSS sampling plan cannot produce estimates with acceptable precision for service activities in the North, Northeast and Midwest regions of the country. Therefore, the use of small area estimation models may provide acceptable precise estimates, especially if they take into account temporal dynamics and sector similarity. Besides, skew normal models can handle business data with asymmetric distribution and the presence of outliers. We propose models with domain and time random effects on the intercept and slope. The results, based on 10-year survey data (2007-2016), show substantial improvement in the precision of the estimates, albeit with presence of some bias. (original abstract)
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The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
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ISSN
1234-7655
Language
eng
URI / DOI
http://dx.doi.org/10.21307/stattrans-2020-032
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