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Measuring Multidimensional Poverty in a Complex Environment; Identifying the Sensitive Links
Procedia Engineering
  • L. E. Voth-Gaeddert
  • Daniel B. Oerther, Missouri University of Science and Technology

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.

Meeting Name
Humanitarian Technology: Science, Systems and Global Impact, HumTech 2015 (2015: May 12-14, Boston, MA)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
  • Correlation methods,
  • Factor analysis,
  • Large scale systems,
  • Analytical tool,
  • Canonical correlation analysis,
  • Complex environments,
  • Complex reality,
  • Global development,
  • Latent factor,
  • multidimensional poverty,
  • Structural equation modeling,
  • Sustainable development,
  • complex systems,
  • latent factor regression
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
© 2015 Elsevier Ltd, All rights reserved.
Publication Date
Citation Information
L. E. Voth-Gaeddert and Daniel B. Oerther. "Measuring Multidimensional Poverty in a Complex Environment; Identifying the Sensitive Links" Procedia Engineering Vol. 107 (2015) p. 172 - 180 ISSN: 1877-7058
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