Gibrat Revisited: An Urban Growth Model Incorporating Spatial Interaction and Innovation Cycles. 再评吉尔布瑞特：顾及空间相互作用和创新周期的城市增长模型

We designed a geographical model for simulating the distribution of urban growth in systems of cities. The model incorporates the hierarchical and spatial diffusion of innovation cycles through gravitational interactions within a set of cities. Using theoretical simulations, we demonstrate that this model is able to reproduce the observed properties of urban systems for the log‐normal distribution of city sizes as well as the observed distribution of growth rates. Our experimentation was performed on a large harmonized historical database that includes a few hundred French urban agglomerations between 1831 and 1999 (Pumain‐INED database). Both spatial interaction and innovation cycles are necessary ingredients to explain the evolution of urban hierarchies. We suggest that Gibrat's generic stochastic growth model based on independent entities should be replaced by a more relevant model of spatially and temporally interdependent geographical entities.