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

The Human Development Index (HDI) is recognised as a widely used composite index to assess socio-economic progress. This study investigates the convergence hypothesis for the HDI across 36 Indian states and union territories (UTs) from 1990 to 2019 using the Phillips and Sul (2007) club convergence methodology and kernel density estimates to determine whether states converge to a single steady-state or into multiple clubs. It also examines inter-regional HDI inequality using Gini and Theil indices. Results show that states converge into two final clubs, with convergence rates of about 0.112% for Club 1 and 1.135% for Club 2, indicating faster convergence among lower-HDI states. Kernel density estimates indicate stratification in 1990, polarization in 2000 and 2010, and a shift toward a unimodal distribution by 2019. Gini and Theil indices reveal a significant decline in HDI inequality from 1990 to 2019. Policy implications include promoting regional development and reducing inequality by accounting for distinct convergence paths of clustered states, offering insights for achieving horizontal equity in HDI across Indian states and UTs.