Divergence, Not Convergence: Regional Wage Inequality and Industrial Development in India’s Formal Manufacturing sector

Despite decades of economic liberalization and industrial policy interventions, regional divergence is observed in the formal manufacturing sectors of India. Analysing Annual Survey of Industries (ASI) data from 2022-23 across 35 states and union territories, this study employs beta-convergence and sigma-convergence methodologies to examines whether the economically backward regions are able to catch up with advanced states in formal sector wage levels. Consistent positive coefficient is observed through beta analysis (β = 0.980–1.409, p < 0.001) indicating wage divergence proof rather than convergence. Sigma convergence metrics reveals extreme inequality: the Gini coefficient touches 0.693, with a P90/P10 wage ratio of 1,550.6 and a maximum to minimum ratio of 39,957.6. K-means cluster analysis distinguishes three distinct wage clubs showing convergence within but persistent divergence in-between groups. Industrial maturity works as a strongest predictor of occupational wage structures (R²= 0.961), while employment formalization in respect to benefit-to-wage ratio critically enhances aggregate wage levels (β = 23.37, p = 0.015). In contrast to human capital theory, literacy rates show a statistically non-significant negative relationship with wages, suggesting structural impediments beyond educational attainment. These results encounter the assumption of automatic wage convergence and demonstrate the needs for fiscal targeted and institutional interventions to address regional wage inequality in India’s development agenda.