Patterns in US urban growth (1790–2000)

This paper reconsiders the evolution of the growth of American cities since 1790 in light of new theories of urban growth. Our null hypothesis for long-term growth is random growth. We obtain evidence supporting random growth against the alternative of mean reversion (convergence) in city sizes using panel unit root tests. We also examine mobility within the distribution to try to extract growth patterns different from the general unit root trend detected. We find evidence of high mobility when we model growth as a first-order Markov process. Finally, using a cluster procedure we find strong evidence in favor of conditional convergence in city growth rates within convergence clubs, which we interpret as “local” mean-reverting behaviors. We interpret the high mobility and the results of the clustering analysis as signs of a sequential city growth pattern.