A new set of cluster driven composite development indicators

A new set of cluster driven composite development indicators

Abstract Composite development indicators used in policy making often subjectively aggregate a restricted set of indicators. We show, using dimensionality reduction techniques, including Principal Component Analysis (PCA) and for the first time information filtering and hierarchical clustering, that...

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Bibliographic Details
Main Authors: Anshul Verma, Orazio Angelini, Tiziana Di Matteo
Format: Article
Language:English
Published: SpringerOpen 2020-04-01
Series:EPJ Data Science
Subjects:
Development economics
Composite indicators
Information filtering
Clustering
World Development Indicators
Online Access:http://link.springer.com/article/10.1140/epjds/s13688-020-00225-y

Internet

http://link.springer.com/article/10.1140/epjds/s13688-020-00225-y

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