Publié le 20 mai 2026 Mis à jour le 20 mai 2026
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Séminaire de recherche. The Gini and the tonic: Understanding the dynamics of inequality measurement


Sanghamitra Bandyopadhyay
Queen Mary University

Résumé

Understanding how to accurately measure the dynamics of inequality is of utmost importance to social scientists. In this paper, for the first time, we identify which inequality measures are best suited to capture the dynamics of inequality. For this purpose, we generate a dataset of twelve types of inequality measures for up to 108 years across 34 countries using mortality distributions. Upon modelling inequality as a fractionally integrated process, and using a VAR approach to measure the impact of a shock, we find that mean-independent inequality measures such as percentile shares are more suited to dynamic studies. Mean-dependent measures like the Gini, however, are revealed to be wholly unsuitable. Our findings suggest that no inequality measure should be used for dynamic purposes without rigorously testing its suitability. Tests of temporal normality and volatility serve as excellent "marker" tests as to whether a chosen inequality measure is suitable for dynamic contexts. Keywords: inequality measurement, mean-independent inequality measures, mortality distributions, percentile shares, time dependent analyses.