Poverty measures are typically estimated from sample observations and, therefore, they should not be used only as descriptive statistics, but rather as tools for statistical inference. Statistical analysis with explicit tests and confidence intervals is important to ensure that changes in measured poverty levels within or across countries correspond to real changes. The aim of the paper is to provide a comprehensive review of the main developments on the inferential aspects of the unidimensional poverty indices.

Measuring unidimensional poverty: a review of the inference literature

Chiara Gigliarano
Primo
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In corso di stampa

Abstract

Poverty measures are typically estimated from sample observations and, therefore, they should not be used only as descriptive statistics, but rather as tools for statistical inference. Statistical analysis with explicit tests and confidence intervals is important to ensure that changes in measured poverty levels within or across countries correspond to real changes. The aim of the paper is to provide a comprehensive review of the main developments on the inferential aspects of the unidimensional poverty indices.
In corso di stampa
Edward Elgar Publishing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2123466
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