On a Generalized Non-compensatory Composite Index for Measuring Socio-economic Phenomena

Matteo Mazziotta () and Adriano Pareto ()
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Matteo Mazziotta: Italian National Institute of Statistics
Adriano Pareto: Italian National Institute of Statistics

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2016, vol. 127, issue 3, No 3, 983-1003

Abstract: Abstract Composite indices for measuring multidimensional phenomena have become very popular in a variety of economic, social and policy domains. The literature offers a wide range of aggregation methods, all with their pros and cons. The most used are additive methods, but they imply requirements and properties which are often not desirable or difficult to meet. For example, they assume a full substitutability among the components of the index: a deficit in one dimension can be compensated by a surplus in another. In this paper, we consider a non-compensatory composite index for spatial comparisons and its variant for spatio-temporal comparisons. A study of the aggregation function is, for the first time, presented and its main properties are formally defined. As an example of application, a set of individual indicators of well-being for OECD countries is considered and a comparison between the two approaches is provided, in order to show what they offer and how they work.

Keywords: Data aggregation; Ranking; Non-substitutability; Penalty; Coefficient of variation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (27)

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DOI: 10.1007/s11205-015-0998-2

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