Noncompensatory/nonlinear composite indicators for ranking countries: a defensible setting

By Giuseppe Munda, Michela Nardo. 2009

302 citations recorded by the source corpus.

Composite indicators (or indexes) are very common in economic and business statistics for benchmarking the mutual and relative progress of countries in a variety of policy domains such as industrial competitiveness, sustainable development, globalization and innovation. The proliferation of the production of composite indicators by all the major international organizations is a clear symptom of their political importance and operational relevance in policy-making. As a consequence, improvements in the way these indicators are constructed and used seem to be a very important research issue from both the theoretical and operational points of view. This article aims at contributing to the improvement of the overall quality of composite indicators (or indexes) by looking at one of their technical weaknesses, that is, the aggregation convention used for their construction. For this aim, we build upon concepts coming from multi-criteria decision analysis, measurement theory and social choice. We start from the analysis of the axiomatic system underlying the mathematical modelling commonly used to construct composite indicators. Then a different methodological framework, based on noncompensatory/nonlinear aggregation rules, is developed. Main features of the proposed approach are: (i) the axiomatic system is made completely explicit and (ii) the sources of technical uncertainty and imprecise assessment are reduced to the minimum possible degree.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/3c274b1579784807a5e8f42f9953177400f37a35

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In Economics and Econometrics

In Management Science and Operations Research

Citations in the corpus

Ratings and rankings: voodoo or science? (2011, background): “c is called ‘compensatory’. Non-compensatory and non-linear aggregate ranking rules have been advocatedbythe literatureonmulticriteriadecisionmaking, seeforexampleBillaut et al. (2010), Munda (2008), Munda and Nardo (2009), Balinski and Laraki (2010). In this paper we concentrate on linear aggregati”
On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness (2018, methodology): “…(e.g. indifference, preference, and veto thresholds), the mathematical aggregation is divided into the following steps: (1) ‘pair-wise comparison of units according to the whole set of indicators’ and (2) ‘ranking of units in a partial, or complete pre-order’ (Munda and Nardo 2009, p. 1516).”
Comparing the sustainability of local and global food products in Europe (2017, unknown): “The first issue relates with aggregating indicators that are actually not comparable, because they are measured at different scales or have been generated qualitatively (Munda and Nardo, 2009).”
METHODS FOR CONSTRUCTING COMPOSITE INDICES: ONE FOR ALL OR ALL FOR ONE? (2013, methodology): “As part of partially compensatory or non-compensatory approach, different methodologies have been proposed in the literature, ranging from simple mathe- 2012), to complex procedures, such as the Multicriteria Analysis (Munda and Nardo, 2009).”
Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions (2018, background): “…the non-compensatoriness of composite indices has been a largely discussed issue (e.g., Casadio Tarabusi & Guarini, 2013; Mazziotta & Pareto, 2016; Munda & Nardo, 2009) and the most adopted aggregation function to avoid complete compensatoriness is the geometric mean that has been recently…”