An Era of “β-divergence”? Empirically testing the β-convergence hypothesis for the North-eastern states of India

This paper attempts to empirically test the β-convergence hypothesis for the North-Eastern states of India. In this context, β-convergence is one of the major predictions of the Solow Growth model, and emphasises on the negative relationship between the “initial or starting point of per capita Gross State Domestic Product (GSDP)” of a state and its “average growth rate” over the time period considered. This paper examines data of the eight North-eastern states of India over a time period of 14 years (2004–2017) to conduct an empirical test of the β-convergence hypothesis. Furthermore, this paper then uses the Least Squares Dummy Variables Fixed Effects Model (LSDV FEM) to test for the statistical significance of heterogeneity in the growth rates of these states with Manipur as the “reference state”. This paper finds that, rather than β-convergence, there has been a phenomenon of “β-divergence” among the North-eastern states of India. This implies that richer states in per capita terms have been achieving higher growth than poorer states – an empirical refutation of the β-convergence hypothesis. Moreover, considerable heterogeneity among the per capita GSDP growth rates is found from the LSDV FEM with the GSDP growth rates of Arunachal Pradesh, Meghalaya and Sikkim showing a statistically significant deviation from that of Manipur during the time period considered.