Understanding the Dynamics of Inequality for Growth and Development

Inequality and its evolution over time are increasingly important subjects within the social sciences, particularly in the field of political economy. This Element identifies for the first time which inequality measures are best suited to capture the dynamics of inequality. This title is also available as Open Access on Cambridge Core.

Inequality and its evolution over time are increasingly important subjects within the social sciences, particularly in the field of political economy. This Element identifies for the first time which inequality measures are best suited to capture the dynamics of inequality. The author generates a dataset of twelve types of inequality measures for 108 years across 34 countries using mortality distributions. When modelling inequality as a fractionally integrated process and using a Vector Autoregression approach, they find that mean-independent inequality measures are more suited to dynamic studies. In contrast, however, mean-dependent measures are unsuitable for dynamic studies. They 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 of whether a chosen inequality measure is suitable for dynamic contexts. This title is also available as Open Access on Cambridge Core.