The persistence of inequality across Indian states: A time series approach

There is a growing literature on the importance of persistent regional inequalities in developing countries, with evidence that the lack of convergence in incomes across regions is associated with a rise in conflict and social unrest. However, there is a relative paucity of literature on the stochastic characteristics of gross domestic product at the sub‐national level. In this paper we identify new stochastic properties of Indian states' gross domestic product between 1960 and 2019 using a fractional stochastic convergence approach. We test for fractional stochastic convergence in relative incomes in order to identify high persistence and mean reversion. Interval estimates of the largest autoregressive coefficient for the relative incomes of Indian states are wide, thus including many alternatives that are persistent. Interval estimates of the half‐life of relative income shocks suggest that in several cases shocks die out within 0–10 years. Finally, we estimate a fractionally integrated model and obtain mixed evidence of mean reversion and non‐stationarity, with six out of 16 states experiencing mean reversion. These results are highly encouraging and contradict earlier studies which show long‐term divergence and polarization of regional incomes across Indian states, and are thus of great relevance to policy‐makers.