This study empirically examines the long-run effect of tax structure on income inequality in India. It considers annual time-series data from 1980 to 2019. The unit root and Johansen cointegration tests substantiate a long-run relationship between tax variables and income inequality. We employ Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) techniques for the baseline analysis. For a robustness check, we utilize the Canonical Cointegration Regression (CCR) technique. The results show that the top marginal tax rate (TMTR) reduces income inequality, whereas customs duty (CD) significantly increases income inequality. Personal income tax (PIT), corporate income tax (CIT), and excise duty (ED) have no significant association with income inequality. In addition, GDP per capita significantly reduces income inequality, whereas GDP per capita squared aggravates income inequality, reflecting the absence of the Kuznets hypothesis in India. Human capital measured by mean years of schooling (MYS) also significantly worsens income inequality. Our results suggest that the Indian government should increase TMTR and reduce customs duty (CD) in order to improve income distribution.