SMU SOE Seminar Series (April 16, 2025): Understanding the Dynamics of Inequality for Growth and Development

TOPIC:

ABSTRACT

Understanding how to accurately measure the dynamics of inequality is of utmost importance to social scientists. In this book, for the first time, I identify which inequality measures are best suited to capture the dynamics of inequality. For this purpose, I 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, I 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. My 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, Time Dependent Analyses, Inequality and Growth Relationship, Fractional Differencing, Impulse Response Functions.

JEL: C32, C33, D31, D63.

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