Gibrat's Law for (All) Cities
利用美国2000年人口普查数据，发现城市规模分布呈对数正态而非帕累托分布，为比例增长与对数正态分布并存提供解释，并提出基于地方外部性和随机生产率过程的均衡理论。
Two empirical regularities concerning the size distribution of cities have repeatedly been established: Zipf's law holds (the upper tail is Pareto), and city growth is proportionate. Census 2000 data are used covering the entire size distribution, not just the upper tail. The nontruncated distribution is shown to be lognormal, rather than Pareto. This provides a simple justification for the coexistence of proportionate growth and the resulting lognormal distribution. An equilibrium theory of local externalities that can explain the empirical size distribution of cities is proposed. The driving force is a random productivity process of local economies and the perfect mobility of workers.