In much of the literature focusing on the growth and structure of the urban system, the difference between contagious and hierarchical interrelations across cities comprised in the urban system are obfuscated. In this paper, we clearly distinguish and quantify the effects of both. In other words, we focus on how the structure of the urban system influences population growth by using central place theory as a theoretical basis for addressing the research question: what natural and man-made locational characteristics influence population growth? We make three major contributions to the existing literature. First, we utilize a unique dataset of urban areas with decennial observations from 1990 to 2010 which captures the agglomerated economic activity and built extent of urban locations with at least 2,500 inhabitants, to include all but the smallest rural communities. Second, our analysis includes both the hierarchical relationship among cities of differing sizes and the continuous nature of proximity to other cities. The novel use of a spatially-lagged hierarchical linear model allows us to include both these critical aspects of the urban system in our analysis. Third, we include man-made amenities and characteristics of cities, which have been omitted from previous studies in an effort to avoid endogeneity in the analysis. By focusing on the intercept and lagged population variables in the urban area equation, we use this model to empirically explore the debate on whether there is random or deterministic growth in the distribution of cities in the United States.


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