Do Economic Development, Credit, Globalization and Human Capital Reduce Poverty in India? Econometric Evidence from Quantile Regression Approach

The key objective of the present study is to examine the role of macroeconomic variables on poverty in India for the period from 1980 to 2019. In the study, the total number of persons below the poverty line is the dependent variable on the other side, the economic development, credit, globalization and human capital are the regressors. The time-series data-set have been sourced from globally renowned websites such as Knoema online database, World Economic Indicators and KOF Swiss Economic Institute. The quantile regression technique has been employed, as the variables in our model have not met the conditions of linear regression such as linearity, homoscedasticity and normality. The estimated result illuminates some interesting insights that both economic growth and availability of credit have decreased the level of poverty with varying magnitudes. Shockingly, it is globalization, which increases the level of poverty in India over the study period. These results have very strong implications for policy modelling in developing countries like India.