Urban Sprawl Essay

To begin with, we present the results from the parameters of the urban sprawl variables. The percentage of urban area carries a positive sign in the local security and urban infrastructure and a negative sign in all other categories; it is significant only in the administration spending. Continuing, the CV does not seem to be a good measure of urban sprawl, its estimated parameters are insignificant in all the equations; in addition, its sign is negative in most estimation, the opposite of expected. On the other hand, the GI does a better job of capturing the urban sprawl effects, the estimated parameters for aggregate spending and spending on administration and environmental management are large and significant, additionally, it has a negative

The percentage of urban area carries a positive sign in the local security and urban infrastructure and a negative sign in all other categories; it is significant only in the administration spending. Continuing, the CV does not seem to be a good measure of urban sprawl, its estimated parameters are insignificant in all the equations; in addition, its sign is negative in most estimation, the opposite of expected. On the other hand, the GI does a better job of capturing the urban sprawl effects, the estimated parameters for aggregate spending and spending on administration and environmental management are large and significant, additionally, it has a negative sign in the aggregate and administration spending, and a positive sign in the environmental management; in other expenditure categories, the estimated parameters are large, but not statistically significant. The estimated parameters for the dummy for medium concentrations show that the GI is not a determinant factor of the spending on administration and environmental management for cities of medium urban concentrations, suggesting that the effects presented by the GI are related to cities of high urban concentrations; however, the estimated parameter for the aggregate spending and spending on social assistance are positive and statistically significant. Lastly, urban population density has a positive and highly significant coefficient

As indicated previously, the SEM was estimated for per capita spending on basic sanitation, housing, social assistance, sports and leisure, urban infrastructure, and aggregate spending; the SAC was estimated for per capita spending on local police. The coefficient of the spatial error term (λ) is positive and highly significant in all the disaggregated measures of spending and in the aggregate spending. This evidence suggests that some factors of a municipality i that are not specified in the models, positively affect the cost of providing public services in a municipality j. This result also indicates that the strategic interaction among the municipalities in a region is a fact that accounts for the per capita spending on local public services. With respect to the spatial variables in the spending on local police function, with the exception of the function estimated by model 1, both the λ and the We are statistically significant and have a considerable value. This implies that the per capita spending on local security in a municipality is affected by the spending on local security and other not identified characteristics of the surrounding