Estimation of poverty indicators for domains with unit-level auxiliary information

Risto Lehtonen, Ari Veijanen

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskaplig


The paper presents current developments on the estimation of poverty
indicators for domains and small areas in the context of the EU FP7 project
AMELI (Advanced Methodology for European Laeken Indicators). The indicators
considered are the Gini coeffi cient, relative median at-risk-of poverty gap
(poverty gap for short) and quintile share ratio (S20/S80 ratio). The corresponding
estimators to be compared are of direct, synthetic or composite type. It appears
that a direct (default) estimator can be quite ineffi cient, and a more effi cient
indirect synthetic estimator is often seriously biased. Composite estimators
are constructed as a linear combination of the direct and indirect estimators.
Underlying the indirect estimators, we use mixed models with domain-specifi c
random intercepts. Unit-level auxiliary data are incorporated into the estimation
procedure. In our case, these data are based on statistical registers maintained
by Statistics Finland. To cover realistic sampling designs, both equal and unequal
probability sampling designs are covered. By using selected indicators on bias and
accuracy, the relative performance of the estimators is assessed with Monte Carlo
simulation experiments based on real data.
Titel på gästpublikationProceedings of the Q2010 Conference : European Conference on Quality in Official Statistics
Antal sidor1
StatusPublicerad - 2010
MoE-publikationstypB3 Ej refererad artikel i konferenshandlingar


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Lehtonen, R., & Veijanen, A. (2010). Estimation of poverty indicators for domains with unit-level auxiliary information. I Proceedings of the Q2010 Conference: European Conference on Quality in Official Statistics (s. 164). Tilastokeskus.