A nonparametric analysis of the growth process of Indian cities

Abstract

We examine the growth process of the largest cities in India for the post economic reform period 1991–2011 to analyze Gibrat’s and Zipf’s laws by applying nonparametric estimation. The results from stochastic kernel, contour plots, and expected growth rate and variance conditional on city size establish that Gibrat’s law holds for largest cities in India, i.e., city growth is independent of population size, and the local Zipf exponent is around one and stable. Gibrat’s law is also confirmed by the parametric regression of the aggregate relationship of the growth rate on city size.