FEEM working papers "Note di lavoro" series
2019 .008

On the Use of Spectral Value Decomposition for the Construction of Composite Indices


Authors: Luca Farnia
Series: Economics for Sustainability
Editor: Sergio Vergalli
Keywords: Composite Index, Weighting, Correlation Matrix, Principal Component, Factor Analysis
JEL n.: C38, C43, C15

Abstract

High dimensional composite index makes experts’ preferences in setting weights a hard task. In the literature, one of the approaches to derive weights from a data set is Principal Component or Factor Analysis that, although conceptually different, they are similar in results when FA is based on Spectral Value Decomposition and rotation is not performed. This work motivates theoretical reasons to derive the weights of the elementary indicators in a composite index when multiple components are retained in the analysis. By Monte Carlo simula-tion it offers, moreover, the best strategy to identify the number of components to retain.

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Suggested citation: Farnia, L. (2019), 'On the Use of Spectral Value Decomposition for the Construction of Composite Indices', Nota di Lavoro 8.2019, Milano, Italy: Fondazione Eni Enrico Mattei

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