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55th Congress of the European Regional Science Association: "World Renaissance: Changing roles for people and places", 25-28 August 2015, Lisbon, Portugal
Cities and towns are loci of population and production. In 2010, 80.7 percent of the United States population resided in urban areas, and the U.S. Bureau of Economic Analysis reported that in 2011, 90.1 percent of GDP was produced in metropolitan statistical areas (MSAs), emphasizing that urban areas and their immediate hinterlands are also centers of production. Academic interest in urban population change can be split into two literature branches. The first branch focuses on the growth and structure of individual cities. The second branch focuses on the urban system. Some of the literature in this branch implicitly assumes interconnectedness among cities, while other authors explicitly include the spatial proximity between cities or network flows among cities. However, in many studies 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. We do this 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 envisage three major contributions to the existing literature. First, we utilize a unique dataset of urban areas with decennial observations from 1990 to 2010. Most of the literature studying urban systems in the United States uses MSAs, which include rural hinterlands that are not part of the urban area, preventing a clear separation between cities and hinterlands and obscuring results. We built a new dataset at the more appropriate and precise geographic level of urban areas, which capture the agglomerated economic activity and built extent of urban locations. Second, departing from literature that includes either urban hierarchy or continuous urban proximity, 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. This econometric model captures the influence of the structure of the urban system on population change by allowing city-level explanatory variables to affect population growth differently, given the unique characteristics of each location's regional and central place market areas. Concurrently we account for contiguous effects through the inclusion of neighbors. 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. The inclusion of these characteristics allows us to include both producer-based and consumer-based characteristics in the analysis, to capture the idea that cities are markets.
hierarchical linear models
hierarchical linear models
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