Determining the Relationship between Urban Form and the Costs of Public Services

Abstract

Dispersed development is often associated with negative externalities and ensuing external costs. As a consequence, there is a global need for informed decision making on issues of land-use change and conversion that includes the influences of differing urban forms on the costs of public services. In this paper we quantify a relationship between cost of services and urban form through the development of an econometric model for the provision of public safety for a county in the Mountain West of the USA. The research extends previous modeling of public services to include a spatial index representing urban form, the pattern of the built environment disaggregated by land use, as an explanatory variable for input cost. The use of an index allows quantifying and tracking changes in urban form over time. The index is based on the Moran's I measure of spatial autocorrelation. It is calculated using the dollar values of buildings aggregated spatially within grid cells. By leveraging Moran's I, the index captures local and global statistics representing the intensity of the built environment by land-use category. Local Moran's I statistics quantify the contribution of individual cells to overall clustering. Global Moran's I statistics are suitable for inclusion as a spatial index in time series regression analysis. Results suggest residential development is a statistically significant driver of local government expenditures on inputs to policing services. This paper contributes to the literature on fiscal impact analysis by incorporating a measure of urban form as a determinant of local government expenditures on services and, ultimately, on the level of service provision. This provides a direct link between urban form and the cost of public services.

Equitable distribution of open space: Using spatial analysis to evaluate urban parks in Curitiba, Brazil

“…a) Global spatial autocorrelation. Among statistics of global spatial autocorrelation, Moran's I is widely used (Lieske et al, 2012;Talen and Anselin, 1998;Tsou et al, 2005). Moran's I provides a formal indication of the degree of linear association between the observed values and the spatially weighted averages of neighboring values.…”

The Fiscal Impacts of Alternative Land Uses

“…We are not the first to estimate a statistical model of the association between community characteristics and elements of community budgets. However, much of the existing literature has focused on a single-expenditure category (Craig and Heikkila 1989; Heikkila and Craig 1991; Heikkila and Kantiotou 1992; Lieske et al 2012) or used broad land-use measures to explain community revenues and expenditures (Coupal, McLeod, and Taylor 2002; Hortas-Rico 2014). To our knowledge, ours is the first study that models the relationship between revenues, expenditures, and a detailed set of land-use categories and addresses all of the outlined concerns with CCS studies raised in the literature.…”

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