In the first place, suburban newcomers
benefit from the fiscal disparity between suburbia and old urban core as
well as cheaper land in the suburbs. However, in order to answer whether
the costs of sprawl will be borne by all taxpayers, it is important to
look at the fiscal impact of sprawl on taxpayers over time. Therefore,
the study will look at whether their tax rate have increased or decreased
from 1985 to 1995 and whether that is associated with the increase of low-density
developments in their localities.
(a) Methods:
A regression model will be estimated using the only
available tax burden indicator - tax rate change – as its dependent variable.
Since low-density single family land use is the major form of sprawl (MPSO
1995 and Porter 1997), independent variables will include the change in
single family land use as the indicator of the degree of sprawl. Multifamily
land use will not be considered because the debates on whether discontinuous,
patch work development leads to higher density is unclear given the imposition
of maximum density in zoning regulations in suburbs (Peiser 1990 and Breslaw
1990). Intervening variables are: (1) those related to growth such as increase
in population, households and jobs (in order to separate out the effect
of growth from sprawl (Atkinson 1996)); (2) those related to municipal
expenditure and revenue such as changes in higher density residential,
commercial, and industrial land uses (based on the assumption of fiscal
impacts of land uses and for controlling secondary effects) as well as
population level which affects the allocation of money from the state level;
(3) those that affect tax rate given the same amount of total property
tax levied such as assessment value; and (4) those related to the quality
of infrastructure of public service required such as change in income indicator
(Burchell and Newman 1996).
For most of the regression models, the units of
analysis are the MCD that have faced increases in single family land use
in Southeast Michigan. It will be assumed that local governments’ say on
zoning makes them independent from each other. The fiscal impact of sprawl
on households will be investigated on the level of municipalities, school
districts, and the aggregate of both. As a result, the dependent variables
of six estimate regression models are MCD tax rate, school tax rate, and
total tax rate. In terms of spillover effect in looking at the school and
total tax rate, land use changes in a MCD may affect the tax rate in another
MCD if they are within the same school district. One way to control for
that is to include, as independent variables in the regression models,
weighted land use changes of the school districts to which a MCD belongs.
