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We address the fundamental question arising in geographical economics: why do economic activities agglomerate in a small number of places? The main reasons for the formation of economic clusters involving firms and/or households are analyzed: (i) externalities under perfect competition; (ii) increasing returns under monopolistic competition; and (iii)(More)
The downsizing and closing of state mental health institutions in Philadelphia in the 1990's led to the development of a continuum care network of residential-based services. Although the diversity of care settings increased, congestion in facilities caused many patients to unnecessarily spend extra days in intensive facilities. This study applies a queuing(More)
In this paper, we propose a statistical index of industrial localization based on Kullback-Leibler divergence. This index is particularly well suited to cases where industrial data is only available at the regional level. Unlike existing regional-level indices, our index can be employed to test the significance of industrial localization relative to a(More)
Using GPS devices and digital cameras, we surveyed outdoor advertisements in Austin, Los Angeles and Philadelphia. GIS and hot spot analysis revealed that unhealthy ads were clustered around child-serving institutions in Los Angeles and Philadelphia but not in Austin. Multivariate generalized least square (GLS) regression models showed that percent black(More)
There exist a variety of tests for attraction and repulsion effects between spatial point populations, most notably those involving either nearest-neighbor or cell-count statistics. Diggle and Cox (1981) showed that for the nearest-neighbor approach, a powerful test could be constructed using Kendall's rank correlation coefficient. In the present paper,(More)
In statistical models of spatial behavior, there is often a mismatch between the scale at which data is available and the scale at which key spatial dependencies are known to occur. However, in attempting to incorporate Þner grain information about spatial dependencies, certain estimation problems arise. Here it is shown that maximum likelihood procedures(More)