A nonparametric analysis of the growth process of Indian cities

Jeff Luckstead, Stephen Devadoss

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish
Pages (from-to)516-519
Number of pages4
JournalEconomics Letters
Volume124
Issue number3
DOIs
StatePublished - Sep 2014

Keywords

  • Gibrat's law
  • Growth process
  • Indian cities
  • Local zipf exponent

Fingerprint Dive into the research topics of 'A nonparametric analysis of the growth process of Indian cities'. Together they form a unique fingerprint.

Cite this