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Journal of Poverty and Social Justice • vol 31 • no 1 • 101–127 • © Policy Press 2023
Print ISSN 1759-8273 • Online ISSN 1759-8281 • https://doi.org/10.1332/175982721X16644668262304
Accepted for publication 29 September 2022 • First published online 18 November 2022
research article
The use of the consensual approach for the
improvement of existing multidimensional poverty
data in Latin America: an illustration based on data
from the City of Buenos Aires
Luis Beccaria, labeccari@gmail.com
Ana Laura Fernández, analaurafer@gmail.com
Universidad Nacional de General Sarmiento, Argentina
Héctor Nájera, hecatalan@hotmail.com
Universidad Nacional Autónoma de México, México
This article aims at contributing to the current literature on poverty data limitations and
measurement by discussing the process for producing the frst multidimensional poverty measure
based on the consensual approach for the City of Buenos Aires. The results show a remarkable level
of consensus about the necessities of life in the twenty-frst century, underline the importance
of generating more suitable indicators of deprivation and show that unmet basic needs-type
variables are no longer adequate for measuring poverty in countries like Argentina. According
to the valid and reliable poverty index, 20.3% of the city’s population live in households in
multidimensionally poor households, this being the social dimension that shows the highest
deprivation rate.
Key words multidimensional poverty • poverty measures • consensual approach
To cite this article: Beccaria, L., Fernández, A.L., and Nájera, H. (2023) The use of the consensual
approach for the improvement of existing multidimensional poverty data in Latin America: an
illustration based on data from the City of Buenos Aires, Journal of Poverty and Social Justice,
31(1): 101–127, DOI: 10.1332/175982721X16644668262304
Introduction
Multidimensional poverty (MDP) measurement research has a long track record
in Latin America (LA) (Boltvinik, 2013). During the 1980s, the unmet basic needs
(UBN) approach has underpinned most indices in the region. Using census data,
estimations were produced based on indicators that proxied lacking a limited group
of basic needs (particularly access to water, sanitation and conditions of the dwelling
and, in some cases, access to primary education).
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