Abstract
Low density development distant from nodes of service provision may be more expensive to service than proximate and high density development. Limited community budgets for public services may become stressed in the face of such exurban development. In order to evaluate the fiscal efficiency of public service provision in a spatially precise manner this paper develops allocation and production function-based models of policing services for Laramie County, Wyoming. Leveraging the results of the econometric model, areas are determined that are fiscally efficient for service provision. Public service provision may be modeled with a production function where level of service outputs are related to local government inputs and neighborhood (socioeconomic and demographic) attributes (e.g. Heikkila, 2000). It is assumed that a public agency behaves similarly to a private firm where a goal is to provide a level of service in an efficient and least cost manner. Local government expenditures on public service inputs may be modeled with an allocation function of inputs based on an implicit price model. The research presented here utilizes geographic information science to derive a spatial index of development pattern suitable for inclusion in an econometric model. The index is based on a modified Moran's I statistical measure calculated on building values (measured in dollars) from a cadastral dataset. Building values are used as a proxy measure of the intensity of the built environment. Inclusion of the spatial index in the allocation function offers the opportunity to determine the spatially defined marginal costs of providing a public service and thus one impact of development. These methods, illustrated using a case example from Albany County, Wyoming, are detailed in Lieske et al. (forthcoming). Results of this research show that pattern of residential development, along with other inputs of the Laramie County Sheriff's department, are significant determinants of county law enforcement expenditures. A spatial cost function, in conjunction with a property tax revenue model, is then used to identify and map areas that are fiscally efficient for the provision of the service being analyzed. This ceteris paribus analysis captures the estimated cost of providing service from a hypothetical state of no development to existing development on a cell-by-cell basis. Following the research call of Irwin and Geoghegan (2001) these methods illustrate how individual choices can be aggregated to market outcomes. Mapped outputs of the differenced spatial cost function indicate those areas of the county that are fiscally efficient for the provision of services. Spatially precise knowledge of the cost of providing local government services could enable more informed decision making and policy.