Human Capital Divergence and the Size Distribution of Cities: Is Gibrat's Law Obsolete?
33 Pages Posted: 24 Aug 2019 Last revised: 31 Aug 2020
Date Written: July 29, 2020
This paper studies how the changing geographic distribution of skilled workers in the US affects theoretical models that use Gibrat's law to explain the size distribution of cities. In the empirical literature, a divergence hypothesis holds that college share increases faster in cities where college share is larger, and a growth hypothesis maintains that the rate of city population growth is also directly related to initial college share. Examining the divergence hypothesis, the classic test for Gibrat's law is shown to be a test for beta-convergence. Testing shows there has been absolute, not relative, divergence in human capital since the 1970s. However, the combination of even absolute divergence and the growth hypothesis is shown to violate the model condition that population growth is stochastic. Additional testing finds that the relation between initial college share and city growth is concave rather than monotonic.These results imply that stochastic growth models can survive the challenge posed by trends in the distribution of human capital.
Keywords: divergence, human capital, Gibrat's law, Zipf's law
JEL Classification: J24, R10, R12, R23
Suggested Citation: Suggested Citation