Patterns in U.S. urban growth (1790–2000)

This paper reconsiders the evolution of the growth of American cities since 1790 in the 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 favour of conditional convergence in city growth rates within convergence clubs, which we can interpret as “local” mean-reverting behaviours. Both the high mobility and the results of the clustering analysis seem to indicate a sequential city growth pattern.