Does club convergence matter? Empirical evidence on inequality in the human development index among Indian states

Abstract

Abstract The Human Development Index (HDI) is recognised as the most commonly used composite index to assess the socio-economic progress of a country. To preserve its pioneering role in development, there has to be a reduction in inequalities and cross-state convergence by adding a sustainable dimension. This paper investigates the convergence hypothesis for the HDI in 36 Indian states and union territories (UTs) from 1990 to 2019. For that purpose, the study used the club convergence technique of Phillips and Sul (2007) and Kernel Density estimates to assess whether states converge towards a single steady-state equilibrium or multiple groups. The paper also considers the relative performance of Indian states and UTs and the comprehension of inter-regional inequality in the HDI by employing the Gini and Theil indices. Using the Phillips and Sul technique, the results reveal that all the states converged into two final clubs (i.e., Club 1 and Club 2). The rate of convergence of HDI is approximately 0.112% for club 1 and 1.135% for club 2. The findings indicate that states with the lowest HDI converge faster than those with higher HDI. The kernel density estimates demonstrate that HDI stratifies, polarises, and becomes unimodal over time, albeit with a common steady state. Further, the Gini and Theil indices suggest a significant decline trend in HDI inequality across the Indian states and UTs from 1990 to 2019. From a policy perspective, the study recommends promoting regional development and reducing inequality, considering the unique convergence paths of the clustering states. The study’s findings could provide the government with a new perspective on attaining “horizontal equity” in HDI across Indian states and UTs.