Journal
PAPERS IN REGIONAL SCIENCE
Volume 93, Issue 1, Pages 159-181Publisher
WILEY
DOI: 10.1111/j.1435-5957.2012.00477.x
Keywords
state populations; dynamic panel data models; Zipf's Law; Gibrat's Law
Ask authors/readers for more resources
Abstract We investigate Zipf's Law on the size distribution and Gibrat's Law on the growth of sub-national populations in China, India and Brazil. We reject Zipf's Law for India, but not for China and Brazil; a log normal distribution also fits Brazil well, but not China and India. Gibrat's Law holds for Brazil; that is, lagged population is the best predictor of current population in Brazil. In China, market potential is an important predictor of population growth, while in India both crop area and market potential are important. Our results show that there is a diversity of experiences across countries, and we speculate that this diversity maybe caused by differences in the characteristics of the three countries.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available