Fiscal Impact Modeling. Onondaga County

Transcription

1 Sustainable Development Plan: Fiscal Impact Modeling for Onondaga County Final Report March 30, 2012 Prepared By: P.O. Box 3367 Saratoga Springs, NY

2 Introduction and Purpose As a precursor to the creation of its Sustainable Development Plan, Onondaga County commissioned a team of professionals to determine how various land development patterns might impact the County and to use the results of this research to inform future planning decisions. The Project Team, which included land use modeling, planning and financial consulting professionals, was asked to research the impacts that various conceptual land use development scenarios would have on the County. Camoin Associates served as the primary resource for the fiscal analysis portion of the project. The results of the modeling exercise are now being used by the County as it develops the Sustainable Development Plan and outlines goals for future growth. Land use patterns not only impact a municipality s capital improvement projects, municipal service delivery, and open space and parks preservation, but they also affect a government s revenue and expenditure streams. The fiscal portion of this impact modeling project was used to determine how future development patterns might shape municipal budgeting and resultant property tax burdens. That is, this analysis seeks to identify the costs and benefits associated with a variety of land development circumstances to determine which scenarios would result in a positive fiscal impact on the local government. These findings can then be used to enact plans that encourage and promote development that realizes the County s vision for the future while limiting strains on municipal resources. As described above, Camoin s role on the team was to model the financial impacts of different types of land development. Renaissance Planning, the land use modeling professionals on the Project Team, developed a land use model that divided the County into a grid of cells. Each cell consisted of ¼ acre of property that was categorized based on existing conditions within the cell, including existing financial conditions such as net municipal and school district costs. The model then used these inputs to project changes to the existing conditions within each cell. The resulting impacts demonstrate what the County could expect if land developed according to the scenarios outlined. The resulting impacts demonstrate in a very simplified way how future land use patterns will contribute to, or detract from, the fiscal health of the County, any related taxing jurisdictions, and, indirectly, all County residents/businesses. However, it should be noted that the model uses averages and generic assumptions regarding municipal revenues and expenditures and the results of the model are blended across the whole County. Furthermore, the model reports aggregate results, but some communities within the County may benefit while others experience losses. Moreover, a disconnect exists between the permitting jurisdiction (i.e. the town, city or village that adopts and enforces the land use ordinance for their municipality) and the taxing jurisdictions that are effected (i.e. school, fire, and other miscellaneous special districts). That is to say that land use is controlled by one set of governing bodies, but the development it allows impacts many other taxing entities without land use controls. Camoin Associates Page 1

3 Methodology To ensure consistency throughout the various components of the Project and to make certain that the results of the fiscal analysis would fit into the land use model developed, each ¼ acre cell of the grid was assigned two designations: the land use of the acreage in question and the degree of urbanization within the cell. Through the analysis described below, Camoin developed a financial figure for each cell type that represents the total (school district and municipal) net revenue/expenditures. First, Camoin identified typical land use categories, which included residential, commercial, industrial and other (e.g. recreation and entertainment, community services, and public services) with vacant properties classified based on their underlying land use designation. Undevelopable properties, such as wetlands, roads and streets, conservation lands, etc., were excluded from the model. Renaissance Planning then applied these categories to each cell. Next, using City/Town/Village and School District boundaries, and with input from Onondaga County planning staff, all cells were assigned one of the four levels of urbanization: Dense Urban, Minor Urban (Villages), Suburban, or Rural. The Legend below therefore shows the 16 possible permutations of land use/urbanization (plus a 17 th category for any excluded parcels). Next, generic community profiles, known as archetypes, were developed for each type of the four levels of urbanization. The Project Team worked closely with the County to identify one or two appropriate municipalities and school districts that would be typical of each archetype. For example, the City of Syracuse was used as the Dense Urban municipal archetype because it is the most densely developed region of the County. Similarly, the North Syracuse and West Genesee Central School Districts were used as the Suburban school district archetypes because the regions covered by these two school districts are typical of most suburban areas in the County. The municipalities and school districts chosen for each archetype are as follows: Municipalities Dense Urban City of Syracuse Minor Urban (Villages) Villages of Liverpool and Fayetteville Suburban Towns of Cicero and Camillus Rural Towns of Fabius and Elbridge School Districts Dense Urban Syracuse City School District Minor Urban (Villages) Solvay Union Free School District, East Syracuse Minoa Central School District Suburban North Syracuse & West Genesee Central School Districts Rural Fabius Pompey Central School, Marcellus Central Schools Camoin Associates Page 2

4 The map below b shows the characteerization of eaach cell within n the County by both land use type and d urbanization. See lege end on previo ous page for an a explanation of the colorr scheme. Camoin co ollected the most m recent budgets b of each of the abo ove listed mun nicipalities/scchool districtss. We analyzzed their expenditures (avveraging them m if two comm munity budgeets were used d) and assigneed expenditu ure values (ne et of non locaal revenues, such s as state aid) a to each of o the land usse categories. As Camoiin Associates P a g e 3

5 an example, we assigned school district costs to residential cells only, since only residential properties produce school aged children, which is the driver of school district costs. Secondly, we assigned average property taxes generated to each cell. We used data from the Office of Real Property Services 1 on assessments and equalization rates, filtered by land use type. Then, we took the total property tax generated by land use type and divided it among the number of cells of that land use in the geography in question. To illustrate this process, if we found out that commercial property accounted for 20% of a community s taxable assessed valuation, we assumed 20% of the property taxes collected in that community were being generated by commercial property. We multiplied 20% times the total property tax levy of the community and then divided it by the number of cells of commercial land use in that town. After assigning revenues and expenses to each cell type, Camoin calculated a net fiscal impact per ¼ acre cell. The net fiscal impact is equal to the net of revenues per cell less expenses per cell (which, again, is based on a number of metrics including the number concentration of each type of cell within a given geography). The net fiscal impact per cell for each cell type is summarized in the following table. Residential Commercial Industrial Other Dense Urban -$ $1, $ $ Minor Urban -$ $1, $ $ Suburban -$ $ $97.39 $ Rural -$44.65 $63.68 $6.69 $5.81 Source: Camoin Associates Net Fiscal Impacts per Cell As shown in the above table, Dense Urban Residential and Suburban Residential are the two most costly categories per cell (on a net basis) for municipalities and school districts in Onondaga County. This is due to the high number of students and residents receiving municipal services within these regions. However, this should not be interpreted as saying that residential development in an urban area is comparable to residential development in a suburban area. Recall that these are the net fiscal impacts per cell and that many more residential households exist on a given acreage in an urban environment than in a suburban environment. So, if you replaced 100 cells of suburban residential (net impact: negative $73,461), you might only need 25 cells of urban residential (net impact: negative $18,446). For another example using a blend of urban/village residential versus suburban/rural residential, see the next section. Dense Urban Commercial properties, on the other hand, bring in the greatest amount of net revenue per cell. This finding is entirely expected, given that commercial properties in urbanized areas are typically very dense in that improvements are typically concentrated on a limited number of acres. We note here that the preponderance of costs associated with the net fiscal impacts per cell calculation result from the costs imposed on the underlying school district by residential development. Furthermore, the burden of local property taxes is much more closely associated with school districts than with municipalities. As we see in the table on the following page, almost 60% of all property taxes levied in Onondaga County go to school districts, compared to 22% to the County and 13% to City/Village/Town governments. Not surprisingly, these are the reasons why each of the residential cells has a negative net fiscal impact and why the remaining categories have various degrees of positive net fiscal impacts. 1 NYS Office of Real Property Municipal Profile Database: Camoin Associates Page 4

6 Property Tax Levies in Onondaga County Name Type County Tax Munic. Tax Fire Tax Special Dis. School Dis. Total Syracuse City $44,647,529 $33,212,083 $64,094,544 $141,954,156 Camillus Tow n $10,494,311 $9,233,055 $1,346,961 $3,272,004 $30,947,517 $55,293,848 Camillus Village $287,785 $287,785 Cicero Tow n $15,309,359 $5,954,384 $1,941,940 $4,779,342 $41,340,325 $69,325,350 Clay Tow n $24,365,173 $7,326,206 $3,099,734 $7,616,845 $77,092,572 $119,500,530 North Syracuse Village $2,403,443 $2,403,443 DeWitt Tow n $20,704,466 $10,206,685 $5,160,705 $3,364,466 $56,773,518 $96,209,840 East Syracuse Village $2,652,066 $2,652,066 Elbridge Tow n $1,542,344 $1,277,016 $263,754 $189,833 $7,443,867 $10,716,814 Elbridge Village $108,408 $108,408 Jordan Village $228,630 $228,630 Fabius Tow n $521,002 $703,587 $247,303 $137,240 $2,732,202 $4,341,334 Fabius Village $30,051 $30,051 Geddes Tow n $9,344,395 $4,761,884 $1,166,653 $1,113,097 $21,602,325 $37,988,354 Solvay Village $2,543,209 $2,543,209 La Fayette Tow n $1,991,939 $1,231,033 $470,958 $381,971 $5,859,378 $9,935,279 Lysander Tow n $10,868,828 $1,639,508 $2,060,588 $930,562 $35,209,299 $50,708,785 Baldw insville Village $1,895,750 $1,895,750 Manlius Tow n $15,692,131 $9,381,160 $2,809,548 $1,562,474 $58,106,470 $87,551,783 Fayetteville Village $1,862,525 $1,862,525 Manlius Village $1,908,197 $1,908,197 Minoa Village $1,156,870 $1,156,870 Marcellus Tow n $2,036,336 $1,681,314 $528,854 $584,400 $8,763,367 $13,594,271 Marcellus Village $422,014 $422,014 Onondaga Tow n $8,985,586 $3,168,466 $2,649,700 $1,412,599 $31,840,050 $48,056,401 Otisco Tow n $1,048,678 $971,567 $353,063 $154,318 $3,684,226 $6,211,852 Pompey Tow n $3,431,362 $1,118,985 $1,025,549 $574,541 $14,819,361 $20,969,798 Salina Tow n $13,819,137 $6,653,951 $3,064,120 $3,295,661 $40,739,182 $67,572,051 Liverpool Village $1,184,717 $1,184,717 Skaneateles Tow n $7,125,235 $2,766,038 $767,649 $31,160 $17,315,587 $28,005,669 Skaneateles Village $1,404,164 $1,404,164 Spafford Tow n $2,090,887 $900,087 $383,660 $52,250 $5,749,296 $9,176,180 Tully Tow n $1,326,273 $885,693 $432,609 $551,569 $4,518,881 $7,715,025 Tully Village $195,088 $195,088 Van Buren Tow n $5,292,661 $2,450,236 $924,473 $534,954 $14,758,428 $23,960,752 Totals $200,637,632 $123,805,855 $28,697,821 $30,539,286 $543,390,395 $927,070,989 Percentage of Total 22% 13% 3% 3% 59% 100% Source: Office of the State Comptroller Division of Local Government and School Accountability, Camoin Associates Camoin Associates Page 5

7 Modeling Results and Interpretation These figures can be used to help the County predict what the financial implications are of growth in different parts of the region. For example, if the County is considering the development of 100 units (acres) of commercial growth, it could evaluate what the financial difference would be if the development were placed in an urban or minor urban area versus a rural or suburban town. Similarly, if the County is faced with a proposal for 100 units (households) of residential growth, it should consider the fiscal affects of the placement of these new units. These simplified examples are explained below: Commercial development: If 100 new commercial acres were placed in a City or Village, the result would be $574,281 in net fiscal benefit. If, however, these same units were placed in a Suburban or Rural town, the net fiscal benefit would be $60,922, or $513,359 less than in a City or Village. Residential: Similarly, if 100 units were placed in a City or Village, it would likely require about 110 acres and would have a net fiscal impact of $159,184. If, on the other hand, these units were placed in a Suburb or rural area converted to a suburb, then 240 acres would likely be required and the net fiscal impact would be $704,920 or $545,736 less than in a City or Village. The net financial impact figures were used as one input for the Onondaga County land use model developed by Renaissance Planning. Renaissance Planning was able to model changes to land use in each cell under two scenarios: the trend scenario and the smart growth scenario. This allowed the County to see the impact of following typical land use trends in future growth patterns versus adopting smart growth policies to encourage growth where it would be most fiscally advantageous. Cells that changed land use were assigned a value of net change that was equal to the new use impact minus the old use impact. For example, if the Renaissance Planning model projected that a Rural Other cell would become a Suburban residential cell, the impact would be the impact of the second ( $734.61) less the impact of the first ($5.81) for a total impact of $ The scenario modeling results are shown in the table below: Net Fiscal Impact Community Type Trend (2035) Smart Growth (2035) City $ 5,906,819 $ 1,425,128 Village $ 3,218,325 $ 1,514,276 Town (Suburban) $ (21,125,531) $ 4,391,085 Town (Rural) $ (2,271,191) $ (36,589) All County Sum $ (14,271,578) $ 7,293,900 At its essence, the modeling therefore shows that there is a significant difference between the Trend scenario and the Smart Growth scenario with respect to fiscal resources. Specifically, the model shows Camoin Associates Page 6

8 us that the difference amounts to about $21.4 million. The modeling relies on a series of assumptions and averages, so the actual figure may be significantly more or less than the $21.4 million. However, it is highly unlikely that the basic premise is incorrect, that Smart Growth land use patterns are more fiscally beneficial than non Smart Growth patterns. This conclusion is certainly corroborated by the research literature on the matter. We provide one special note on the interpretation of the above calculations. It appears that the Smart Growth scenario is not as beneficial to the City as the Trend scenario. We recall to the reader that the Smart Growth scenario is one where development, including residential development, is focused primarily in the urbanized areas of the County. As mentioned above, residential development poses costs on municipalities and school districts in particular. Therefore, it is only natural that, by focusing more residential development in urban areas, the costs to those urban areas go up. We again note that the aggregate cost of development is much lower in the Smart Growth scenario, since residential development in urban areas is cheaper on a per household (not per cell) basis. This is another way of saying that, as a whole, the County is better off with development focused in urban areas, even if those benefits/costs are spread out unequally. Camoin Associates Page 7

9 Policy Implications Based on the results of the modeling, the County has essentially three options for how to proceed: Option #1: Any solution to address this will be politically difficult, there are legal issues with the constitution and state statutes, so Let s just put our energy elsewhere. Option #2: We have existing regional bodies that could influence development patterns, so Let s harmonize each regional entity s policies with the Plan. In considering this second option, the County could seek to harmonize regional entities with the Sustainability Plan by: a) having the County s Sanitary District focus future development by restricting interconnects/extensions in certain areas and promoting them in others b) establishing policies at other County entities to favor smart growth (departments, agencies, IDA, LDC, authorities) Ex. Water supply, hazard mitigation c) using the power of the purse at the County government level with respect to the redistribution of County revenues. Ex. Exclude development outside of preferred areas when calculating distributions of sales tax receipts Option #3: To make a big impact, we need a big solution, so Let s undertake an effort to establish a regional planning body with commensurate authority. If the County wishes to pursue the big solution posed in option #3, there are several examples that could be followed, including the example of the Metropolitan Council of the Twin Cities, Minnesota for innovative regionally planning methods and authority (see our White Paper on the subject prepared in the context of our work on the Sustainability Plan). This option would require State legislative action but would allow for the greatest scope and depth of implementation. Moreover, the implications of smart growth could allow for regional mass transit and highway planning, land use planning, environmental conservation, economic development, parks, water/wastewater, tax base sharing, affordable housing, etc. Camoin Associates Page 8