Estimation of multi-way tables subject to coherence constraints

Fedele Greco ()
Additional contact information
Fedele Greco: Alma Mater Studiorum - Università di Bologna; Dipartimento di Scienze statistiche - Italy

Statistica, 2016, vol. 76, issue 2, 115-125

Abstract: Nowadays, traditional population censuses based on total enumeration of the population are being accompanied by sample surveys. Sampling within censuses allows to reduce costs and workload of authorities involved in censuses operations, along with the statistical burden for the people involved in the enumeration. In this paper, we deal with estimation of multi-way contingency tables involving variables measured both via census and sampling. In this framework, two main issues need to be addressed: first of all, sample size for estimating some of the entries of the contingency tables may be too small, delivering estimates prone to huge sampling variability. On the other hand, since estimates of the joint distribution need to be coherent with the marginal distribution of the variable collected via a census, estimation methods need to be coherent with the constraint imposed by marginal distribution of variables measured via census. The problem is tackled via a model-based approach that allows to comply with all coherence constraints following a fairly simple procedure. The merit of the proposed methodology is illustrated by means of a simulation study.

Keywords: Population Census; Multi-way tables; Generalised Raking; Bayesian hierarchical models (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bot:rivsta:v:76:y:2016:i:2:p:115-125

Access Statistics for this article

Statistica is currently edited by Department of Statistics, University of Bologna

More articles in Statistica from Department of Statistics, University of Bologna Contact information at EDIRC.
Bibliographic data for series maintained by Giovanna Galatà ().