Robust weighting schemes of multidimensional poverty attributes

Mehmet Pinar, T. Stengos, N. Topaloglou

Research output: Contribution to conferenceLecture

Abstract

This paper describes how to obtain a robust weighting scheme of well-being indicators to arrive at the least (highest) possible multidimensional poverty for a given population when we have a given set of pre-determined normative weights as a benchmark. In particular, we test whether the allocation of weights to each well-being dimension for assessing the poverty level of a given population are robust or whether different weighting schemes would have offered a highest (lowest) possible multidimensional poverty to that population. Identification of poor through the choice of dimension specific poverty lines and setting weights to different dimensions may lead to different poverty levels and a reversal of poverty assignments across populations. We offer a robust weighting scheme to the attributes of well-being which can equally well be applied to union, intersection or intermediate identification approaches when dealing with multidimensional indicators of poverty. We derive a robust weighting scheme for which multidimensional poverty is highest (lowest) for a given deprivation level. Moreover, different set of dimension specific poverty lines can be chosen where multidimensional poverty is driven by only a set of dimensions where poverty lines above these levels can no longer be considered in the multidimensional poverty comparisons. We illustrate our methodology through multidimensional poverty analysis in different population groups in Kenya and Canada.
Original languageEnglish
Publication statusPublished - 2014
EventEconometrics Seminar - Center for Operations Research and Econometrics, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Duration: 27 Oct 2014 → …

Other

OtherEconometrics Seminar
CountryBelgium
CityLouvain-la-Neuve
Period27/10/14 → …

Fingerprint

Weighting
Multidimensional poverty
Poverty
Well-being
Poverty line
Deprivation
Benchmark
Kenya
Canada
Methodology
Reversal
Assignment

Cite this

Pinar, M., Stengos, T., & Topaloglou, N. (2014). Robust weighting schemes of multidimensional poverty attributes. Econometrics Seminar, Louvain-la-Neuve, Belgium.
Pinar, Mehmet ; Stengos, T. ; Topaloglou, N. / Robust weighting schemes of multidimensional poverty attributes. Econometrics Seminar, Louvain-la-Neuve, Belgium.
@conference{63375692e1bd44f3bd7e832834d302f5,
title = "Robust weighting schemes of multidimensional poverty attributes",
abstract = "This paper describes how to obtain a robust weighting scheme of well-being indicators to arrive at the least (highest) possible multidimensional poverty for a given population when we have a given set of pre-determined normative weights as a benchmark. In particular, we test whether the allocation of weights to each well-being dimension for assessing the poverty level of a given population are robust or whether different weighting schemes would have offered a highest (lowest) possible multidimensional poverty to that population. Identification of poor through the choice of dimension specific poverty lines and setting weights to different dimensions may lead to different poverty levels and a reversal of poverty assignments across populations. We offer a robust weighting scheme to the attributes of well-being which can equally well be applied to union, intersection or intermediate identification approaches when dealing with multidimensional indicators of poverty. We derive a robust weighting scheme for which multidimensional poverty is highest (lowest) for a given deprivation level. Moreover, different set of dimension specific poverty lines can be chosen where multidimensional poverty is driven by only a set of dimensions where poverty lines above these levels can no longer be considered in the multidimensional poverty comparisons. We illustrate our methodology through multidimensional poverty analysis in different population groups in Kenya and Canada.",
author = "Mehmet Pinar and T. Stengos and N. Topaloglou",
year = "2014",
language = "English",
note = "Econometrics Seminar ; Conference date: 27-10-2014",

}

Pinar, M, Stengos, T & Topaloglou, N 2014, 'Robust weighting schemes of multidimensional poverty attributes' Econometrics Seminar, Louvain-la-Neuve, Belgium, 27/10/14, .

Robust weighting schemes of multidimensional poverty attributes. / Pinar, Mehmet; Stengos, T.; Topaloglou, N.

2014. Econometrics Seminar, Louvain-la-Neuve, Belgium.

Research output: Contribution to conferenceLecture

TY - CONF

T1 - Robust weighting schemes of multidimensional poverty attributes

AU - Pinar, Mehmet

AU - Stengos, T.

AU - Topaloglou, N.

PY - 2014

Y1 - 2014

N2 - This paper describes how to obtain a robust weighting scheme of well-being indicators to arrive at the least (highest) possible multidimensional poverty for a given population when we have a given set of pre-determined normative weights as a benchmark. In particular, we test whether the allocation of weights to each well-being dimension for assessing the poverty level of a given population are robust or whether different weighting schemes would have offered a highest (lowest) possible multidimensional poverty to that population. Identification of poor through the choice of dimension specific poverty lines and setting weights to different dimensions may lead to different poverty levels and a reversal of poverty assignments across populations. We offer a robust weighting scheme to the attributes of well-being which can equally well be applied to union, intersection or intermediate identification approaches when dealing with multidimensional indicators of poverty. We derive a robust weighting scheme for which multidimensional poverty is highest (lowest) for a given deprivation level. Moreover, different set of dimension specific poverty lines can be chosen where multidimensional poverty is driven by only a set of dimensions where poverty lines above these levels can no longer be considered in the multidimensional poverty comparisons. We illustrate our methodology through multidimensional poverty analysis in different population groups in Kenya and Canada.

AB - This paper describes how to obtain a robust weighting scheme of well-being indicators to arrive at the least (highest) possible multidimensional poverty for a given population when we have a given set of pre-determined normative weights as a benchmark. In particular, we test whether the allocation of weights to each well-being dimension for assessing the poverty level of a given population are robust or whether different weighting schemes would have offered a highest (lowest) possible multidimensional poverty to that population. Identification of poor through the choice of dimension specific poverty lines and setting weights to different dimensions may lead to different poverty levels and a reversal of poverty assignments across populations. We offer a robust weighting scheme to the attributes of well-being which can equally well be applied to union, intersection or intermediate identification approaches when dealing with multidimensional indicators of poverty. We derive a robust weighting scheme for which multidimensional poverty is highest (lowest) for a given deprivation level. Moreover, different set of dimension specific poverty lines can be chosen where multidimensional poverty is driven by only a set of dimensions where poverty lines above these levels can no longer be considered in the multidimensional poverty comparisons. We illustrate our methodology through multidimensional poverty analysis in different population groups in Kenya and Canada.

UR - http://www.uclouvain.be/en-43677.html

M3 - Lecture

ER -

Pinar M, Stengos T, Topaloglou N. Robust weighting schemes of multidimensional poverty attributes. 2014. Econometrics Seminar, Louvain-la-Neuve, Belgium.