Rating the Rich: An Ordinal Classification to Determine Which Rich Countries are Helping Poorer Ones the Most

• Published in: Social indicators research Vol. 116; no. 1; pp. 47 - 65
• Main Authors: Sianes, Antonio, Dorado-Moreno, Manuel, Hervás-Martínez, César
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer 01.03.2014; Springer Netherlands; Springer Nature B.V
• Subjects: Algorithms; Antipoverty Programs; Artificial Intelligence; Artificial neural networks; Civil Society; Classification; Cooperation; Countries; Developing Countries; Development sociology; Development Strategies; Energy; Environmental security; Experiments; Foreign aid; GDP; Gross Domestic Product; History, theory and methodology; Human Geography; International development; LDCs; Low Income Groups; Machine learning; Machinery; Methodology; Microeconomics; Modeling; Networks; Neural networks; Neurons; Peer Influence; Poverty; Public Health; Public policy; Quality of Life Research; Ratings & rankings; Research Design; Social research; Social Sciences; Sociologists; Sociology; Sociology of economy and development; Statistical Analysis; Studies; Policy coherence for development; Fight against poverty; Ordinal classification; Commitment to development index; Artificial neural networks; Congruence; Poverty; Development aid; Classification; Developing Countries; Fight; Commitment; Advanced Countries; Development policy

When talking about poverty, a lot of energy is expended by academics and sociologists in the identification and classification of the poor. Less attention is paid to classifying the rich. The Center for Global Development created the Commitment to Development Index in 2003, which ranks countries acc...