Review of some statistical methods for constructing composite indicators

Abstract

The methodology for the construction process of composite indicators is reviewed in a step-by-step approach ranging from the ex-ante definition of the latent variable that is intended to be measured through the aggregation process. We focus on comparing four statistical aggregations methods in terms of their weighting and aggregation approaches: Distance P2, Principal Component Analysis, Data Envelopment Analysis and Mazziotta-Pareto Index. An empirical comparison among them is provided and the composite indicators divergences are discussed.