Conditional convergence and Spatial convergence across 103 Sub-state Indian regions

Using spatial econometrics for panel data

Authors

DOI:

https://doi.org/10.55763/ippr.2022.03.05.003

Abstract

Recent studies have devoted great emphasis to examining the phenomenon of income convergence across regions. The empirical efforts made in the context of India look at convergence among the states of India. Although there have been a few studies done on the district level, the sub-state regions that are prevalent within each state have been largely ignored in the Indian regional literature. The purpose of this research is to investigate the extent to which 103 sub-state regions within 20 Indian states converge. This research adopts a method that differs from the conventional convergence strategy by instead focusing on the spatial convergence aspect. It has been shown that not only does spatial convergence but also β-convergence: a growth process where poor regions grow faster than rich regions occur among India's 103 different regions. This study sheds insight on the two distinct forms of convergence, namely, β-convergence across all regions, and β-convergence among neighbouring regions. The finding of the existence of β-convergence and spatial convergence among neighbouring regions invites policy attention regarding the development of backward regions.

Keywords:

Spatial Convergence, Spatial fixed effects model, Panel data, Conditional Convergence

Authors Bio

Vivek Jadhav, Madras School of Economics

Vivek Jadhav is pursuing his PhD. from Madras School of Economics

Brinda Viswanathan, Madras School of Economics

Dr. Brinda Viswanathan is Professor and Dean Research at Madras School of Economics

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Published

2022-09-23