Measuring unidimensional poverty: a review of the inference literature

Chiara Gigliarano and Pietro Muliere

Chapter 10 in Research Handbook on Measuring Poverty and Deprivation, 2023, pp 106-117 from Edward Elgar Publishing

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.

Keywords: Development Studies; Economics and Finance; Geography; Research Methods; Sociology and Social Policy (search for similar items in EconPapers)
Date: 2023
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