Estimation of poverty rate and quintile share ratio for domains and small areas

Risto Lehtonen, Ari Veijanen

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

Abstract
In the paper, we consider the estimation of indicators on poverty and social exclusion for population subgroups or domains and small areas. For at-risk-of poverty rate, we discuss indirect design-based estimators including model-assisted logistic generalized regression estimators and various model calibration estimators. Logistic mixed models are used in these methods. For quintile share ratio, indirect model-based synthetic estimators and calibration-based predictor-type methods using linear mixed models are considered. Unit-level auxiliary data are incorporated in the estimation procedures for these methods. We present a method called frequency-calibration or n-calibration to be used for quintile share ratio estimation in cases where aggregate level auxiliary data only are available. Design-based direct estimators that do not use auxiliary data and models are used as baseline methods. Design bias and accuracy of estimators are evaluated with design-based simulation experiments using real register data maintained by Statistics Finland and semi-synthetic data generated from the EU-SILC survey.
Original languageEnglish
Title of host publicationStudies in Theoretical and Applied Statistics
EditorsGiorgio Alleva, Andrea Giommi
Place of PublicationCham
PublisherSpringer International Publishing AG
Publication date2016
ISBN (Print)978-3-319-27272-6
ISBN (Electronic)978-3-319-27274-0
DOIs
Publication statusPublished - 2016
MoE publication typeA3 Book chapter

Publication series

NameStudies in Theoretical and Applied Statistics
ISSN (Print)2194-7767

Fields of Science

  • 112 Statistics and probability

Cite this

Lehtonen, R., & Veijanen, A. (2016). Estimation of poverty rate and quintile share ratio for domains and small areas. In G. Alleva, & A. Giommi (Eds.), Studies in Theoretical and Applied Statistics (Studies in Theoretical and Applied Statistics ). Cham: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-27274-0