Non-parametric estimation and weak convergence of poverty measures
type: Dataset
contact point: Organization
  fn: CCSD
keyword: indice-general-de-pauvrete
keyword: estimateurs-a-noyau
keyword: estimateurs-de-type-plug-in
keyword: statthstatistics-statstatistics-theory-statth
keyword: intervalles-de-confiance
keyword: processus-empirique-indexe-par-des-fonctions
keyword: mathmath-stmathematics-mathstatistics-mathst
keyword: convergence-faible
keyword: theses
keyword: infoeu-reposemanticsdoctoralthesis
landing page: https://theses.hal.science/tel-00825389
description: This dissertation first presents a general representation of poverty measures that concerns all uni-dimensional poverty measures based on the income distribution. We then, deals with two types of estimators of this general poverty index : a kernel one and a plug-in one, and analyze their asymptotic properties. Our methodology, essentially based on the modern theory of empirical processes indexed by functions, offers a general and rigorous framework, which allows to study in the same approach, the asymptotic behaviour of all the income-based poverty measures that are still available yet in the literature. We obtain the strong and uniform consistency of a very broad class of poverty measures including almost all the poverty indices proposed by economists, both decomposable and non-decomposable. This result applies for building simultaneous and accurate asymptotic confidence bands for the theoritical poverty index . A uniform functional central limit theorem is also established for this wide class of poverty measures. As a consequence, robust statistical inference procedures, based upon the covariance structure, are developped using a Wald test, in order to compare in a non-ambiguous manner two different populations in terms of poverty
identifier: NNT: 2011PA066053
issued: 2026-05-11T01:06:40.761074
language: fr
modified: 2026-05-11T01:06:40.761079

test_moissonnage_selune
type: Agent

Non-parametric estimation and weak convergence of poverty measures
type: Distribution
access URL: https://theses.hal.science/tel-00825389
format: HTML
issued: 2026-05-11T01:06:40.776727
modified: 2026-05-11T01:06:40.743489