1. Fiscal Impact of Sprawl on Suburban Households in Southeast Michigan Hui-Chun Huang

2. Urbanization of Land in Southeast Michigan, 1890- 2010

3. What Is Sprawl? §Economists’ Definition: l An efficient distribution of economic activities in a micro sense (Muller 1981). (An aggregate result of individual households and firms’ optimum location decisions.) l A process of path dependency: a process of cumulative causation with self-reinforcing feedback loops instead of self-correcting ones in equilibrium models (Atkinson 1996).

4. Characteristics of Sprawl §Unlimited outward extension of new development. §Low-density residential and commercial settlements, especially in new growth area. §Leapfrog development jumping out beyond established settlements §Great fiscal disparities among localities

5. The Fiscal Impact of Sprawl Contradictory Statements §At the macro-level: The fiscal impact of sprawl has been found negative on municipal budgets. Based on the empirical results of the macro-scaled studies, it is speculated that the cost of sprawl will be born by all the households in an metropolitan areas in terms of increasing tax burdens. §At the micro-level: However, some micro-scaled studies argue that suburban residents benefit from sprawl in the forms of decreasing tax burdens and improved public service and infrastructure in their communities (No empirical evidence has been provided).

6. The Dynamics of Sprawl §Three Mismatches: l Temporally: Beneficial to suburban residents in the short term while costly in the long term l Socially: Beneficial to suburban residents especially newcomers while costly to some others and society l Spatially: Beneficial to some localities while costly to some others

7. Indicators §Sprawl indicators: l the change in single family residential land use §Household tax burden indicators: l The change in tax per household at three levels (Minor Civil Division Tax, School Tax, Total - Minor Civil Division Tax + School Tax) l The change in tax rate at the same three levels

8. Research Question §Do individual suburban households perceive the cost of sprawl imposed on society? §Are existing suburban residents fiscally impacted by suburban newcomers? §Is there a time lag in the fiscal impact? Does it differ between the short term and the long term? §What is the spatial pattern of the fiscal impact? Does it differ depending on the size and location of a locality? Do localities with similar or dissimilar impacts cluster? Is the observed fiscal impact a regional pattern (Do regression model makes sense?)

9. Statement of Purpose §The study attempts to look at whether suburban newcomers, who later become suburban residents, perceives the costs of sprawl they impose to society and whether the costs are born or will be born by most suburban taxpayers. The question is important in terms of forming a strong case for or against sprawl.

10. Methodology §Multiple Variable Regression Models: l Dependent Variables: Tax Burden Indicators l Independent Variables: Sprawl indicator: Change in single family land use Intervening Factors: Changed in other land use, variables affecting municipal revenues and expenditures, growth indicators. §GIS:

11. How Can GIS Help Answer These Questions? Initial insights on whether the fiscal impact of sprawl on households differ between different localities in a metropolitan area, and the short term and the long term §Thematic mapping using two variables § Spatial auto-correlation analysis §Diffusion based on two five-year data and random digital numbers

12. Thematic Mapping Based on Two Variables §Proportional Single Family Land Use Change: Areas with increase in single family land use are considered areas that have faced sprawl from 1985 to 1995. §Variables Related to Tax Burdens: These are dependent variable for regression models. If these variables present similar behaviors in the areas facing sprawl, then regression analysis is a possible methodology.

13. DATA SOURCE §STATE TAX COMMISSION: l Ad Valorem Property Tax Levy Reports (MCD, School, and Total Tax Data Based on MCDs), Assessment Values Based on School District §DEPARTMENT OF EDUCATION: l Bulletin 1014 (School Tax Data Based on School Districts) §Southeast Michigan Council of Governments: l 2020 Regional Development Forecast Technical Report (Household Numbers, Job Numbers, Number of Children, Income Indicators etc.)

14. Thematic Mapping Initial Exploration of the Spatial Pattern of the Fiscal Impact of Sprawl

15. MCD TAX PER HOUSEHOLD §Change from 1985 to 1990 §Change from 1990 to 1995 §Change from 1985 to 1995

19. Observations §MCD tax per household has increased in both five and ten-year periods. §Those MCDs in proximity to the city of Detroit of Ann Arbor have faced greater increase than other suburban MCDs in tax per household.

20. SCHOOL TAX PER HOUSEHOLD §Change from 1985 to 1990 §Change from 1990 to 1995 §Change from 1985 to 1995

21. Speculations §Rural residential developments mainly rely on unimproved roads, water wells, and septic tanks rather than more expensive facilities. §Sewer zones expansion and maintenance of infrastructure close to urban area may be reflected on the greater increase in MCD tax per household in MCDs close to urban areas..

25. TOTAL TAX PER HOUSEHOLD §Change from 1985 to 1990 §Change from 1990 to 1995 §Change from 1985 to 1995

26. Observations §School tax per household have increased in most suburban MCDs. §MCDs farther away from urban areas seem to have a greater increase in school tax per household than those close to urban areas.

27. Speculations §The impact of sprawl on school tax per household is greater in areas farther away from urban areas because new schools need to be built to accommodate new growth. §The impact of sprawl on school per household is less greater in areas whose school systems have had enough infrastructure capacity to accommodate new growth. However, operating costs of their school systems have increased.

31. Observations §The increase in aggregate tax burdens seem to be greater in areas close to urban areas from 1985 to 1990. However, those farther away from urban areas seem to have greater total tax burden increase later from 1990 to 1995.

32. MCD TAX RATE §Change from 1985 to 1990 §Change from 1990 to 1995 §Change from 1985 to 1995

36. Observations §For the MCDs adjacent to urban areas, MCD tax rate have decreased from 1985 to 1990 while those farther away from urban areas have faced an increase in their MCD tax rate §More MCDs close to urban areas started to have an increase in MCD tax rate from 1990 to 1995.

37. SCHOOL TAX RATE §Change from 1985 to 1990 §Change form 1990 to 1995 §Change from 1985 to 1995

41. Observations §School tax rate change from 1985 to 1990 is similar to that of MCD tax rate. MCDs close to urban areas have an increase in their school tax rates while those further away have a decrease in their school tax rates §In 1990 to 1995, most MCDs have an decrease in their school tax rates. Those further away from urban areas have a greater decrease.

42. TOTAL TAX RATE §Change from 1985 to 1990 §Change from 1990 to 1995 §Change from 1985 to 1995

46. At the macro level, only some growing localities have faced an increased in school tax.

47. Observation §The change of total tax rate is more dictated by the change of school tax rate. They have similar spatial patterns. §It is possible that there was a structural change in the way school tax was levied during 1990 to 1995 because some localities actually have a decrease in total school tax.

48. Spatial Autocorrelation Analysis Using MCD Tax Rate Change from 1985 to 1995

50. Among growing suburban localities, those with an increase in MCD tax rate are negatively spatially autocorrelated with those with a decrease in MCD tax rate.

51. Elimination of Growth Effect Growth Factors: §Increase in Household Numbers §Increase in Employment §Increase in Population

53. Observations §The spatial pattern of change in household numbers are similar to that of MCD and School tax per household. §The fiscal impact observed in terms of the change in tax per household may be due to growth instead of sprawl. §Therefore, it is important to use a multiple variable regression model to control growth effect to study the real impact from sprawl.

54. Spatial Intervening Factors §Sewer Zones §School Districts §Highways, County Roads, and Other Pubic Roads

58. Future Directions §The way households were spatially distributed seems to be consistent in three period. §Therefore, some other intervening spatial factors such as roads and sewer zones need to be further studied. §Diffusion can be used to project the spatial patterns of these fiscal impacts beyond these ten years.