LAUSR

ABSTRACT This study examines the impact of urban and rural development on poverty and inequality in India before economic reform. The methodology comprises two dimensions. Modern time series methods are used to uncover the dynamic patterns of urban–rural poverty and income inequality. A machine-learning algorithm is used to determine the causal structure among the development indicators. Our results show that reductions in rural poverty appear to be a more effective in reducing both urban and rural poverty, although the costs of achieving these reductions have not been considered.