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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.

With application of Diebold and Yilmaz’s (Int J Forecast 28(1):57–66, 2012) spillover approach, we examine shock spillover in international sovereign bond yields over short, medium, and long term maturities for major eight economies. By scrutinizing the data from 1st January 2013 to 12th November 2020, we explored that irrespective of pre-covid-19 or covid-19 period, shock spillover in bond yields across markets are much stronger over long and medium maturities relative to short-term maturity. Moreover, shock spillover of bond yields has amplified manifold during Covid-19, irrespective of their maturities compared to pre-Covid-19 period. The magnitude of shock spillovers remains low with short-term maturity. Assessing the relationship between international sovereign bond markets (SBMs) contributes to our understanding and is also crucial to the investors (both domestic and foreign) in investing in SBMs.

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Income inequality is considerably high and still growing, which may cause a significant loss of India’s human development and economic performance in the post-pandemic period. Thus, using cointegrating models viz; FMOLS, DOLS, CCR, and ARDL models, we scrutinize short-run as well as long-run impact of natural disaster, economic development, technological innovation, and human capital on income inequality in India. Results show that the natural disasters and economic development worsen income inequality in both short- and long-run. Further, India’s human capital also aggravates income inequality in the short run. In contrast, India’s technological innovation and human capital in the long run improve income distribution significantly. Finally, the policy suggestions are mentioned in the conclusion section. Our results are consistent and robust with alternative modelling.

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