Recent Advances in Estimation of Poverty Indicators for Domains and Small Areas

Risto Lehtonen, Ari Veijanen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In the paper, we consider the estimation of indicators on poverty and socialexclusion for population subgroups or domains and small areas. For at-risk-of poverty rate, we discuss indirect estimators including model-assisted logistic generalized regression estimators and new model calibration estimators. Logistic mixed models areused in these methods. For quintile share ratio, indirect model-based synthetic estimators and new calibration-based predictor-type methods using linear mixed models are considered. Unit-level auxiliary data are incorporated in the estimation procedures. Design-based direct estimators that do not use auxiliary data and models are used for comparison. Design bias and accuracy of estimators are examined with simulation experiments using register data maintained by Statistics Finland and semi-synthetic data generated from the EU-SILC survey.
Original languageEnglish
Title of host publicationPROCEEDINGS OF THE 46TH SCIENTIFIC MEETING OF THE ITALIAN STATISTICAL SOCIETY
Publication date21 Jun 2012
Publication statusPublished - 21 Jun 2012
MoE publication typeA4 Article in conference proceedings
Event46th Scientific Meeting of the Italian Statistical Society - Rooma, Italy
Duration: 20 Jun 201222 Jun 2012

Fields of Science

  • 112 Statistics and probability

Cite this

Lehtonen, R., & Veijanen, A. (2012). Recent Advances in Estimation of Poverty Indicators for Domains and Small Areas. In PROCEEDINGS OF THE 46TH SCIENTIFIC MEETING OF THE ITALIAN STATISTICAL SOCIETY