Measuring Multidimensional Poverty in a Complex Environment; Identifying the Sensitive Links

The central hypothesis of this study is that a holistic, systems-based approach employing multiple analytical tools is useful for identifying the most sensitive links within complex communities to down-scale global development priorities such as the United Nations Sustainable Development Goals. Resu...

Full description

Saved in:
Bibliographic Details
Published in:Procedia engineering 2015, Vol.107, p.172-180
Main Authors: Voth-Gaeddert, L.E., Oerther, D.B.
Format: Article
Language:English
Subjects:
canonical correlation analysis
complex systems
latent factor regression
multidimensional poverty
structural equation modeling
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The central hypothesis of this study is that a holistic, systems-based approach employing multiple analytical tools is useful for identifying the most sensitive links within complex communities to down-scale global development priorities such as the United Nations Sustainable Development Goals. Results of latent factor regression, canonical correlation analysis, and structural equation modeling were compared for multiple, publically-available data sets for two rural regions in Brazil and Guatemala. The results of this study confirm previously reported findings, and collectively support the central hypothesis demonstrating a pathway for linking global priorities with the complex realities of ‘on-the-ground’ development conditions in specific communities.
ISSN:1877-7058
1877-7058
DOI:10.1016/j.proeng.2015.06.071