Rethinking Income Inequality: A Search for the Optimal Distribution

Abstract

The United Nations’ ambitious 2030 Agenda, adopted in September 2015, outlines 17 Sustainable Development Goals (SDGs) with the overarching aim of eradicating poverty and hunger. This agenda represents an unprecedented opportunity to address global challenges. However, one crucial aspect, achieving an appropriate level of income disparity (income inequality), remains a significant hurdle for both academics and policymakers. This research gap necessitates a deeper exploration of the theoretical underpinnings of an optimal income distribution for a given population size. This study delves into this under-researched area by analysing the World Bank’s data on population size and the Gini coefficient (a metric for income inequality) for 103 countries (most recent year data available, up to 2023). The analysis employs regression techniques to unveil the relationship between the Gini coefficient and the natural logarithm of population size. The findings suggest a non-linear association, best characterized by a second-degree polynomial function. This implies that the relationship between population size and optimal income distribution is not a simple linear one. Furthermore, the estimated results indicate that the majority of countries in the sample exhibit Gini coefficients that deviate significantly from their theoretically optimal levels. This finding presents valuable insights for policymakers as they design and implement public policies aimed at achieving a more equitable income distribution. The subsequent section delves into a detailed case study of India, analysing its Gini coefficient and the extent of its deviation from the estimated optimal level.