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How Has Fiscal Impact Analysis Been Integrated Into Local Comprehensive Planning? Case Studies Of Howard County, Maryland And Loudoun County, Virginia |
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Terry Holzheimer, AICP
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Howard County, Maryland, and Loudoun County, Virginia, two of the fast growing suburbs of Washington, DC, are among the few communities to fully utilize the fiscal impact approach in integrating economic factors into their comprehensive plans. Both have won national recognition for their comprehensive plans. Howard County's The 1990 General Plan... a six point plan for the future won the American Planning Association award for planning excellence in 1990. Two years later, Loudoun County's Choices and Changes General Plan was similarly honored. The process of the development and implementation of fiscal impact analysis, as it has been incorporated into two award-winning planning efforts, is described in this study. Specifically, each case study site was investigated in the context of the following research questions:
Additionally, the case studies yield conclusions regarding the applicability of fiscal impact analysis models to other communities and provide clues as to why this approach has not been more universally utilized in comprehensive planning.
Section II provides a broad review of economic analysis techniques as they have been applied to comprehensive planning. Key elements of the fiscal impact analysis concept are then presented in Section III. The dimensions of the Howard County and Loudoun County models, and their application in comprehensive planning, are described in Section IV. Finally, Section V analyzes the perceived strengths, weaknesses, and applicability of fiscal impact analysis based on the case study descriptions and the opinions of those who have implemented the two models.
One of the earliest economic analysis techniques commonly used in local comprehensive planning was the economic base approach. First conceived in the 1920s, the economic base concept was popularized by Homer Hoyt and Richard B. Adams in the post-WWII period (Murphy 1966). Economic base analysis was introduced to a new generation of planning students in Urban Land Use Planning (Chapin 1965), one of the first general planning textbooks and in Principles and Practices of Urban Planning (ICMA 1968), another planning text also widely used by practicing planners. Planners used the economic base approach to derive employment projections, consider local economic factors, and project land use need by category - the most fundamental requirements for local comprehensive plans. This approach required only readily available secondary data which, when coupled with relatively simple analytical techniques, soon made economic base analysis a common tool in comprehensive planning.
The planning-programming-budgeting-system (PPBS) was an analytical approach of defining measurable goals, setting alternatives, evaluating each alternative for cost and effectiveness, and choosing the best means for implementation (ICMA 1979). PPBS was introduced at the local level as an outgrowth of its expanding use for complex projects at the federal level. The widespread provision of categorical federal assistance to local governments in the sixties, especially Model Cities, hastened the spread of program budgeting. While PPBS linked planning and budgeting, its complexity prevented it from being sustained once federal pressures for its use declined.
Subsequent to the brief life of PPBS, planners were offered a range of modeling techniques designed to aid in understanding local and regional economies. Input-output analysis, shift-share analysis, and fiscal impact analysis were described as planning tools in The Practice of Local Government Planning (ICMA 1979). The first two techniques found their advocates at the regional level while fiscal impact analysis was found to be most applicable at the local level, where land use and budget responsibilities are closely linked (McLean and Voytek 1992). Cost-benefit analysis techniques also found their way into the planning literature, including matrix display techniques such as the planning balance sheet (Schofield 1987). Matrix display techniques permit the inclusion of non-quantitative data within planning analyses, incorporating a wide variety of qualitative social and environmental factors with more quantitative economic measures. Cost-benefit analysis has also come to play a major role in growth management as it relates to the marginal costing of specific types of public facilities.
Growth management involved a series of discrete approaches for controlling the pattern, pace, and cost of growth (Anderson 1995). Economic elements of growth management have included impact fees, creation of markets for transferable development rights, and the outright purchase of environmental and development easements, among others. Economic analysis has been used to develop mechanisms to manage growth by allocating and shifting many of the costs of growth from the public sector to those who benefit most: new residents and businesses.
The allocation of the costs of growth, between those moving into a growing community and the community's existing population, has became a major political issue in many rapidly growing suburban areas (Snyder and Stegman 1986). Economic analysis techniques were soon applied to compute appropriate development impact fees based on the scope, location, and timing of growth (Nicholas, Nelson, and Juergensmeyer 1991). The need to fully understand the costs of growth, in order to establish impact fees or proffers in lieu of impact fees, lead to the use of fiscal impact analysis techniques in the case study communities of Howard and Loudoun Counties.
Fiscal impact analysis is a systems approach - it links economic, demographic, capital, and service factors. Development is market driven. If service levels are held constant, the demand for increased government services and facilities is largely development driven. Other market factors such as the price of housing, the value of land and commercial/industrial property, and the industrial mix all have an affect on the taxable base. The expenditures required to provide new services and facilities, and the revenues available, are directly dependent on market demand as it affects the pace, value, and location of development. Fiscal impact analysis is the one technique that links planning with the economics of the market.
Application of fiscal impact analysis occurs on two levels. At the macro level, it is used to analyze growth as it affects the entire jurisdiction. It is also used to determine the impact of specific projects on the overall community at the micro level. Both are of interest to planners, although, without development of a community-wide model, project related impact analyses are difficult and generally inaccurate. The community-wide model enables analysis of alternative development patterns, land uses and growth rates on tax rates, capital facilities expenditures and services costs. Project analysis, which is focused on product mix, pricing, and absorption rates allows local governments to consider the marginal costs of a specific development when facing requests for approval of major projects through the zoning, special exception, or use permit processes. The case studies of Howard and Loudoun Counties describe how these communities have used fiscal impact analysis at the comprehensive plan level and how project analysis in being incorporated into the incremental implementation of their plans.
Both communities were populated with sophisticated citizens and developers who were well acquainted with growth management concepts and planning law. Planners needed to ensure that the planning process was "legally defensible" and that growth management policies could withstand the close scrutiny of constitutional challenges based on tests of rational nexus and takings. Fiscal impact analysis was introduced into the planning processes not only to ensure due diligence related to the analysis of the costs of growth, but also because it "was a way of testing the implications of planning safely" (Avin).
These two case studies are intended to provide an understanding of the dimensions or characteristics of the fiscal impact analysis models and the application of fiscal impact analysis in each community. The two models are different in detail, but strikingly similar in scope and complexity. With similar tools, each community has found different uses for fiscal impact analysis in response to community needs.
Dimensions of the Model - On the revenue side, the model directly linked the zoning and land uses, as proposed in the draft plan, with the projected growth of housing units, by type and price, and commercial/industrial space, by value. More specifically, residential development was divided into several unit types, based largely on differing school-aged children generation rates. Single family detached, single family attached, apartment, condominium, and "other" unit types were allocated according to historical trends of annual market demand for such units. Thus, market factors related to product type, price, and production were integral to the fiscal impact model growth assumptions.
A fundamental element of the proposed comprehensive plan was an annual quota or cap on residential development. The level of permitted development, however, closely matched anticipated housing demand based on long term trends for housing starts. The cap was intended to dampen the "boom and bust" cycle of housing growth which made the concurrent provision of adequate government facilities difficult.
Market-related factors were also utilized in projecting non-residential growth. Development was allocated among retail, office and R&D, and industrial and warehouse uses by square footage and market value. Like the residential market, cycles were eliminated through the use of longer term trends in non-residential space absorption.
By modeling the future growth of the county at this level of detail, economic factors related to consumer demand for housing and business demand for non-residential space were integrated into the resulting plan. Revenue impacts were relatively easily derived from current tax levels, assessments, and the market value of new construction. The model directly linked unit and space demand, by type, to population and employment projections. Any land removed from the tax roles, from the acquisition of parkland, school sites, or agricultural easements, could also be accounted for easily.
Revenue projections were based on long term economic trends and ignored less predictable short term market fluctuations. The real estate bust of the early 1990s resulted in a real decline in assessed values, and a consequent reduction in the taxable base soon after the adoption of the comprehensive plan. This reduced taxable base had to be offset by a comparable increase in tax rates, in order to keep revenue relatively constant on a real per capita basis. While the model could not predict market fluctuations, it was useful in explaining the effects of the recession on county revenues.
Howard County's model used both marginal and average cost approaches in projecting expenditures (Howard County 1989). Facilities needs are incremental, with substantial new expenditures needed at the threshold of the next increment, making the marginal cost approach preferable to the average cost approach in projecting capital costs (Nicholas, Nelson, and Juergensmeyer 1991). Capital expenditures were projected based on marginal costs while operating expenditures were based on per capita costs.
Service or operating expenditures were allocated among 43 categories. The four largest categories were related to the costs of operating schools, and were based on enrollment projections derived from the anticipated housing unit growth. Highway, development agency, and miscellaneous inspection costs were also based on marginal housing unit development. The great majority of the remaining costs were based on average, per capita, measures. According to the typology presented in the Fiscal Impact Handbook (Burchell and Listokin 1978), the costing approach used by Howard County was a combination of the per capita multiplier and the service standard approaches. The Howard County fiscal impact analysis model, and the comprehensive plan, assumed that service levels and real service costs would remain level over the term of the plan, a period of twenty years. There was virtually no public debate or controversy on these assumptions.
Application of the Model - Howard County used the fiscal impact analysis model to validate the affordability of the proposed comprehensive plan. By holding service costs constant, on a per capita basis, the model outputs verified that the tax rate would require only slight increases over the 20 year study period. Outputs also demonstrated the value of accelerating the construction of some of the needed capital facilities. Howard County's use of the model increased the confidence of both elected officials and the general public in the fiscal soundness of the plan.
The model was also used to calculate the "breakeven" value of a new home - the price required to generate taxes sufficient to cover all associated service and capital costs. In 1990, that value was approximately $300,000, an amount significantly above the average value of new units being built in the County. This number was widely publicized in order to demonstrate the need for economic development. Since non-residential development was seen to "subsidize" residential growth, attaining the projected levels of commercial and industrial development was imperative. Howard County was committed to remaining a diverse community with a wide variety of housing choices. A mix of housing, with an adequate supply of affordable units, was a premise of the plan. Available affordable housing units were important to employers in attracting labor, even though affordable units required more "subsidy" than executive housing. Fiscal arguments were used to link the plan's proposed housing and employment policies.
Howard County development, business, and citizen interests have all been generally supportive of the plan. Fiscal impact analysis appears to be viewed as a positive contribution to the planning process. The County has the staff resources and skills needed to support the continued maintenance and application of the model.
The fiscal impact model is being updated and recalibrated for the next review of the comprehensive plan. Fiscal analysis will continue to be used in the planning process in ways similar to its prior use in 1989. In addition, Howard County plans to use a new project based model to evaluate future proposed mixed use projects meeting certain thresholds. It is also envisioned that this new model will be used to evaluate the fiscal impact of incentive packages proposed as part of the County's industrial recruitment effort. Howard County is continuing to integrate fiscal impact analysis into the planning process in innovative ways.
Dimensions of the Model - The Loudoun County Fiscal Impact Model (FIM) was specifically designed for application in Loudoun County. The FIM featured inter-dependent modules which incorporated demographic, revenue, capital, and service level assumptions. County staff were directly involved in developing or verifying the assumptions associated with each of these modules. Loudoun's model was significantly more complex than most other fiscal impact models in use at that time.
The demographic module contained approximately 125 growth-related variables. The assumptions associated with each variable were explicit and included such factors as pupil generation rates by housing unit type, employment per square foot by type of commercial/industrial use, real income growth, etc. The flexibility of the model enabled analysts to vary many assumptions, including unit mix, absorption rates, and prices/values of new construction. The Loudoun County FIM provided both substantial detail and flexibility. It also incorporated local economic and market factors as they related to projected development.
The tax rate was modeled as a dependent variable, with capital and services expenditures based on projected development as the independent variables. The revenue module also permitted analysis of the fiscal impacts of constant tax rates on the capital and services budgets. The FIM could be used as a budget analysis as well as development analysis tool.
Service expenditures were calculated using a method similar to that used in Howard County - average per capita costs for most factors, with school costs based on the marginal costs for students generated by the new units to be built each year. The Loudoun FIM additionally incorporated a number of embedded algorithms that accounted for economies of scale in service costs as the County urbanized, even when the growth assumptions held service levels constant (Johnson 1988). These "invisible" factors, associated with the comparable community modeling approach as described in the Fiscal Impact Handbook, would become increasingly controversial as the model's details came under public scrutiny (Burchell and Listokin). Capital costs, as included in a separate module, were initially based on average expenditures for similar sized communities across the state, but were later based on locally projected facilities needs (Johnson 1988).
Application of the Model - The first application of the fiscal impact analysis model in Loudoun County was to compare four alternative sub-area growth scenarios being considered through the comprehensive planning process (Loudoun County 1991). The model tested the fiscal impacts of providing public water and sewer, and thus permitting suburban scale development, into areas not necessarily planned for development. In summary, the provision of services and the wider distribution of development (it was assumed that opening additional areas to development would not result in greater overall growth) resulted in projections of less favorable fiscal positions for the County in three of the four areas. Ultimately, fiscal impact analysis was considered as one input into a complex decision process and did not, solely, drive the final plan recommendations. The Choices and Changes plan did, however, institutionalize fiscal impact analysis in the planning process, requiring an annual update of the model.
Development remained a highly politicized issue in Loudoun County, as local elected officials continued to approve rezonings which enabled development of tens of thousands of additional residential units (Loudoun County 1995). The real estate slump of the early 1990s lead to increasing fiscal stress as the County government experienced substantial reductions in assessments, even as new housing construction continued at relatively high levels. Although elected officials considered using the FIM for the analysis of individual projects, the development community questioned the validity of the model in light of the "invisible" embedded algorithms. Politically, the model was viewed as indefensible, and staff undertook substantial "off-line" work to supplement and document the model.
The process of documenting all assumptions and conducting sensitivity analyses of the model involved the formation of a publicly appointed group to provide oversight. The resulting Technical Review Committee (TRC) was comprised of prominent members of groups that included development, environmental, school, and taxpayer interests. Working through rules requiring consensus, the TRC validated all 125 assumptions in the demographic module, the element containing the development related assumptions. While the proprietary algorithms remained unknown, the model was generally demystified and accepted for limited application.
Subsequent to the work of the TRC, the most acceptable elements of the model were the development assumptions and these were used during the review of County agency service plans. These service plans were developed independently by individual agencies, and the aggregate capital facility timing and cost implications had not been closely scrutinized in any comprehensive manner. The Zurn Initiative, named for the Board of Supervisors member requesting the analysis, led to a review of the long term fiscal impacts of the service plans using the FIM. Ultimately, the service plans were reconsidered in total and the County developed a twenty year Capital Needs Analysis. Fiscal impact analysis had been successfully used to tie long term capital budgeting into the planning process.
The FIM was also used to analyze the fiscal impacts of two area plans, the Dulles South Plan and the Toll Road Plan. By the time these area plans were prepared, the application of fiscal impact analysis had become more accepted. It proved useful in generating public and interest group support for the area plans. The initial concerns with the black-box issue have not disappeared, however, and Loudoun's use of fiscal impact analysis has not attained the same level of public acceptability as Howard County's.
Applications of the FIM were related to broad countywide or area plan analyses. There remains a desire on the part of elected officials and planning commissioners for a project-based model applicable to individual rezoning or special exception cases. It is likely that the development of a project model will commence in the near future, further integrating fiscal analysis into the planning process. At the same time, County officials will work to modify the macro level model to remove the "unknowns" that have caused so much controversy since its inception.
A secondary benefit was a by-product of the work required to develop and implement fiscal impact analysis - the information collection and development tracking processes in both communities were greatly improved. Data collection became routine and institutionalized. More and better information about development impacts and facilities needs and costs resulted from the FIM development and documentation process.
Public expectations of fiscal analysis remain unfulfilled. The question, "if the (development) business can have a bottom line, why can't the County?" has not been adequately addressed. Additionally, Loudoun's "black box" problem, stemming from use of the comparable city method of analysis, significantly eroded the public's trust and confidence in the fiscal impact model. The model's "proprietary formula was a fatal flaw (Maio)."
Good models are complex, and consequently expensive, difficult, and time consuming to maintain. The state of the art in fiscal impact modeling (at least as it stood in 1989) is not user friendly. Users feel that models are cumbersome and data needs are "overkill," while at the same time maintaining high levels of utility requires complexity. Statistically sophisticated staff are needed to maintain and interpret fiscal impact analysis model outputs.
Planners themselves are sometimes hesitant to undertake fiscal impact analysis. The "fear of numbers" also extends to planners, who may be intimidated by the complexity of the models. Finally, planners may fear that fiscal impact analysis will drive the entire planning effort, instead of serving as one of many considerations.
In spite of its expense, complexity, and limitations, both case study communities have found significant value in fiscal impact analysis and are working to expand its applicability.
The lessons learned from Howard and Loudoun Counties' experience with fiscal impact analysis may be useful to other communities considering its application. Most of these are practical considerations that ultimately affect the acceptability and usability of the models:
Future research should focus on a broader sample of users of fiscal impact analysis models. The two communities studied here have been cited for exemplary planning efforts and they have many demographic and economic similarities; their experiences may not necessarily be appropriately generalized to other areas. New generation models may have increased the applicability of fiscal impact analysis through improved usability and reduced expense. As new technology enables ever increasing complexity, the linkage of fiscal impact analysis models with large database systems such as geographical information systems (GIS) seems inevitable. Future applications of fiscal impact analysis may substantially add to the utility of the approach.
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Pastor, Julie. 1997. Interview by author. Lessburg, VA. 24 April.
Richmond, Cynthia. 1997. Interview by author. Leesburg, VA. 4 April.
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Snyder, Thomas P. and Stegman, Michael A. (1986). Paying for Growth: Using Development Fees to Finance Infrastructure. Washington, DC: Urban Land Institute.
Wacks, Raymond S. 1997. Telephone interview by author. 23 April.
Wells, John. 1997. Interview by author. Leesburg, VA. 4 April.
Uri Avin, former Director, Howard County Department of Planning and Zoning.
Roselle George, Director of Research, Howard County Department of Planning and Zoning.
Peggy Maio, Loudoun Chapter of the Piedmont Environmental Council and member of the Fiscal Impact Analysis Technical Review Committee.
Marsha McLaughlin, Deputy Director, Howard County Department of Planning and Zoning.
Julie Pastor, Director, Loudoun County Department of Planning.
Cynthia Richmond, Assistant Director, Loudoun County Department of Economic Development.
Raymond S. Wacks, Administrator, Howard County Office of Budget.
John Wells, Deputy County Administrator, Loudoun County, Virginia.
Terry Holzheimer, AICP
Director, Office of Business Investment
Arlington County, Virginia