Estimation of Small Area Characteristics Using Multivariate Rao-Yu Model

• Autorzy: Alina Jędrzejczak , Jan Kubacki
• Języki publikacji: EN

Abstrakty

EN

The growing demand for high-quality statistical data for small areas coming from both the public and private sector makes it necessary to develop appropriate estimation methods. The techniques based on small area models that combine time series and cross-sectional data allow for efficient "borrowing strength" from the entire population and they can also take into account changes over time. In this context, the EBLUP estimation based on multivariate Rao-Yu model, involving both autocorrelated random effects between areas and sampling errors, can be useful. The efficiency of this approach involves the degree of correlation between dependent variables considered in the model. In the paper we take up the subject of the estimation of incomes and expenditure in Poland by means of the multivariate Rao-Yu model based on the sample data coming from the Polish Household Budget Survey and administrative registers. In particular, the advantages and limitations of bivariate models have been discussed. The calculations were performed using the sae and sae2 packages for R-project environment. Direct estimates were performed using the WesVAR software, and the precision of the direct estimates was determined using a balanced repeated replication (BRR) method. (original abstract)

Słowa kluczowe

EN

Small area estimates; Estimators; Multi-dimensional analysis

PL

Statystyka małych obszarów; Estymatory; Analiza wielowymiarowa

• Czasopismo: Statistics in Transition
• Rocznik: 2017
• Tom: 18
• Numer: nr 4
• Strony: 725--742

Twórcy

autor

Alina Jędrzejczak

• University of Lodz, Poland; Statistical Office in Lodz, Poland

autor

Jan Kubacki

• Statistical Office in Lodz, Poland

Bibliografia

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Identyfikatory

DOI

10.21307/stattrans-2017-009