I DEVELOPMENT

PA C T

Robert W. Burchell David Listokin

William R. Dolphin Lawrence Q. Newton

Susan J. Foxiey

with

Robert M. Rodgers Jeffrey L. Greene Larry W. Canter David J. Minno WonsikShim Wansoolm

About ULI-: the Urban Land Institute

ULI-the Urban Land Institute is a nonprofit educa­tion and research institute that is supported and di­rected by its members. Its mission is to provide responsible leadership in the use of land in order to enhance the total environment.

ULI sponsors educational programs and forums to encourage an open international exchange of ideas and sharing of experience; initiates research that an­ticipates emerging land use trends and issues and pro­poses creative solutions based on this research; provides advisory services; and publishes a wide vari­ety of materials to disseminate information on land use and development.

Established in 1936, the Institute today has some 13,000 members and associates from 46 countries rep­resenting the entire spectrum of the land use and de­velopment disciplines. They include developers, builders, property owners, investors, architects, pub­lic officials, planners, real estate brokers, appraisers, attorneys, engineers, financiers, academics, students, and librarians. ULI members contribute to higher standards of land use by sharing their knowledge and experience. The Institute has long been recognized as one of America's most respected and widely quoted sources of objective information on urban planning, growth, and development.

Richard M. Rosan Executive Vice President

Project Staff Senior Vice President, Research, Education, alld Publieations Rachelle L. Levitt

Vice President/Publisher Frank H. Spink, Jr.

Managing Editor Nancy H. Stewart

Manuscript Editor Carol E. Soble

Electronic Publishing Solutions of Annapolis, Maryland Book Design;Layout: David M. Williams Cover Design: Melinda S. Appel

Production Manager Diann Stanley-Austin

Word Processing Joanne Nanez

About the Center for Urban Policy Research, Rutgers University

The Center for Urban Policy Research at Rutgers University is among the nation's oldest and most ac­tive research organizations dedicated to the study of urban policy. CUPR has specialized in studies of hous­ing, development impact, economic development, ur­ban and suburban land use, transportation, and the environment. Founded in 1969, the center brings to­gether a highly experienced full-time faculty of plan­ners, economists, geographers, and computer and systems experts. The center also supports an in-house publications department.

The center has carried out more than $4 million in research grants, published more than 100 books, and organized many national conferences. CUPR has con­ducted research for federal, state, and local agencies, foundations, and private sector clients. Recent studies conducted by the center include the economic assess­ment of the New Jersey State Development and Rede­velopment Plan; analysis of national housing mobility strategies; preparation of an urban transportation masterplan; development of a model subdivision and site plan ordinance; housing needs assessments for New Jersey and Westchester County, New York; and a multiyear investigation of community involvement in the siting of hazardous waste facilities.

Recommended bibliographic listing: Burchell, Robert W _/ David Listokin, et al. Development Impact Assessment Handbook. Washington, D.C.: ULI-the Urban Land Institute, 1994.

ULI Catalog Number: D86 International Standard Book Number: 0-87420-743-6 Library 01 Congress Catalog Card Number: 93-61040

Copyright © 1994 by ULI-the Urban Land Institute 625 Indiana Avenue, N.W. Washington, D.C. 20004-2930 0-'~ iod~ 0000 Printed in the United States of America. All rights reserved. No part of this book may be reproduced in any form or by any means, electronic or mechanical, including photocopy­ing, recording, or by any information storage and retrieval system, without written permission of the publisher.

ii

Chapter 8

..

Introduction Fiscal impact analysis compares the public costs

and public revenues associated with residential and!or nonresidential growth (Burchell, Listokin, and Dolphin, 1991). If costs exceed revenues, a deficit is in­curred; if revenues exceed expenditures, a surplus is generated. Fiscal impacts are projected for the public jurisdiction(s) where growth is taking place---the mu­nicipality, township, county, school district, and any special districts (Marcou and Tischler, 1978).

Fiscal impact analysis-or, as it has sometimes been called, cost-revenue analysis- has been part of the planning profession for over half a century. It started with a narrow application and over time has broadened to encompass a wide range of uses. The growing breadth of cost-revenue assessment is evi­dent from the following historical synopsis.

Planners first employed fiscal impact analysis in the 1930s to examine the effects of the nascent public housing program. Expenditures for the program were justified on the basis that public housing projects yielded a net local fiscal surplus compared to the slums they replaced. In the early 1940s, fiscal impact analysis was similarly used in the context of urban re­newal programs to demonstrate the local fiscal advan­tages of the new land uses that would replace the old.

Over time, the locus and context of fiscal impact analysis broadened (Levin, 1975). During the massive suburbanization movement of the 1950s, cost-revenue studies were effected to gauge the impact of new sin­gle-family detached homes and apartments on local school districts and municipal service providers. In the 1960s, supported by U.s. Department of Housing and Urban Development 701 planning assistance

FISCAL IMPACT ANALYSIS

funding, fiscal impact analysis was used to evaluate the economic effect of master plans. During this same period, cost-revenue projection was also applied to weigh the costs versus revenues of annexation tu both the annexing and annexed jurisdictions.

In the 19705, the techniquc emerged as an almost universal large-scale development accompaniment­either undertaken voluntarily by the deVeloper or re­quired by the municipality (Levin, 1975; Cuthbertson, 1976). Public jurisdictions such as the Association of Bay Area Governments began to incorporate cost­revenue assessment into their planning and other ac­tivities (Lewis and Hoffman, 1977). The 1970s also saw the rise of fiscal impact models. The Urban Insti­tute was a pioneer in this regard (Muller, 1975); its work eventually led to computerized cost-revenue ap­proaches such as the Municipal Impact Evaluation System (MUNlES) developed by Tischler and Associ­ates, Inc.

The 1970s also marked the publication of The Fiscal Impact Handbook by Rutgers University (Burchell and Listokin, 1978). Building on earlier work conducted at Rutgers in a publication entitled Housing Development and Municipal Costs (Sternlieb et aI., 1972), the Hand­book was developed as a baseline document for wide application by planners, developers, and others. The Handbook brought greater methodological consistency to a field that was characterized by divergent and often questionable approaches. Publication and dis­semination of the Handbook led to Widespread use and acceptance of fiscal impact analysis.

By the 198Os, cost-revenue assessment had become a common, albeit not universal, element of develop­ment impact and planning assessment (Montasser and Tischler, 1980). A cost-revenue projection was

125

typically included in the socioeconomic section of en­vironmental impact statements (see chapter 5); such a projection was required with respect to larger or in other ways atypical projects such as developments of regional impact (ORIs) in Florida. Annexation was often reviewed on its fiscal merits; rapidly growing communities ranging from Germantown, Tennessee, to Naperville, Illinois, routinely prepared technical guides to evaluate the fiscal effects of annexation on their borders (Tischler and Associates, 1988; Naperville, 1981). Planners considering changes to a community's master plan also factored in the various fi~cal consequences of land use altematives, along with other social and environmental effects. For in­stance, Newark, Delaware, developed a cost-revenue handbook to assess rezoning and other land use changes. Fiscal impact analysis was also increasingly used in a policy context ranging from decisions on the expenditure of economic development funds (i.e., whether the public subsidy would be recouped from the project-induced fiscal surplus) to the location of military facilities.

In the 1990s, fiscal impact analysis is finding appli­cation in still-emerging planning contexts. Emphasis on growth management has intensified interest in comparing the fiscal effects of development under a planned or managed land use system to the impacts of growth under sprawl or trendline conditions (American Farmland Trust, 1986). In Maryland, for in­stance, both Montgomery and Howard Counties have considered the fiscal as well as the traffic, environ­mental, and other effects of alternative future land use patterns (Montgomery County, 1989; Tischler and Associates, 1989). The state of New Jersey commis­sioned a study by Rutgers University to analyze the revenue implications of a state plan that will modify existing development patterns (Burchell, 1992). Com­munities are also recognizing that fiscal impact conse­quences should be factored into the determination of impact fees; growth resulting in a revenue surplus should receive a credit in the calibration of the impact charge. This fiscal impact-impact fee linkage has been incorporated into the formulation of impact fees for NaperVille, Illinois, and into the development of prof­fer charges in Virginia Beach, Virginia (Listokin, 1988; Burchell and Listokin, 1990).

Fiscal impact analysiS is also becoming an element in many community planning processes that tradition­ally have never incorporated cost-revenue considera­tions. An example is a capital facilities needs assessment. In Florida, for instance, state law man­dates communities to prepare a capital improvement clement (CIE) that must include a projection of both future infrastructure needs and the revenues required to finance the identified capital improvements. Flor­ida communities such as Venice have conducted fiscal impact studies of future growth to help satisfy their CIE planning requirement. Fiscal impact analysis is also being used in the context of personnel planning.

For instance, Plymouth, Minnesota, applied a commu­nitywide cost-revenue assesslnent to determine, among other things, the level of staffing various city depart­ments would need to accommodate expected growth.

In short, fiscal impact analysis has evolved from a technique narrowly applied to justify public housing and urban renewal spending to a tool that today is broadly used in a wide variety of planning contexts. Similarly, the fiscal impact assessment's analytic state of the art has evolved over the past half-century as noted in the discussion below.

Evolving State of the Art Over time, fiscal impact analysis has changed from

an ad hoc and overly simplistic projection that em­ployed the same methodology in all cases to a more standardized and comprehensive assessment that en­compasses different approaches suitable to varying applications. These changes make for a much more ac­curate analysis today than in years past.

In the mid-1970s, the authors considered the national state of the art of fiscal impact assessment (Burchell and Listokin, 1978). At that point, fiscal impact analy­sis favored direct, average-costing procedures that typically employed the per capita multiplier technique. Under this technique, service costs per unit of popula­tion (persons, pupils, and employees) would be de­rived and then applied to the devetopment-generated population (persons/pupils/ employees). These costs were then matched against growth-induced revenues to yield the net fiscal impact.

In assessing the state of the art as of the mid-1970s, the authors observed several characteristics. In most instances, the cost-revenue analysis was performed in a singular case-by-case fashion, and the per capita ap­proach was applied arbitrarily. In addition to the ab­sence of standardization, fiscal impact analysis typically focused on the end-state and was overly sim­plistic. It usually did not consider the effects of devel­opment over time as opposed to merely at final buildout. Neither did it factor in interactive effects such as the impact of local ratable additions on inter­governmental assistance.

While many of these methodolol;ical weaknesses con­tinue today, noticeable improvements have emerged. In the movement to more standardized approaches, the per capita method-still the most common technique-­is applied much more unifonnly. Other refinements are obvious as well. Even though average costing is still the most common application, it is tempered with an en­hanced sensitivity to marginal impacts. Such impacts are often determined from case study interviews of local public officials knowledgeable of service needs and ca­pacities. Another change is that the time frame of the analysis has shifted from exclusively end-state to peri­odic. As important as it is to define a development's fiscal consequences at buildout, it is likewise in­

126

I r

sightful to trace its year-by-year effects on the way to completion--often through the econometric modeling application of cost-revenue analysis.

Finally, the base data employed in fiscal impact cost projections have been refined. Ongoing efforts at­tempt to derive accurate demographic multipliers­the average number of people and school children associated with different type and size configurations of housing units. Demographic multipliers-a key in­put in the estimation of public service costs-have been updated periodically by the authors in The Practi­tioner's Guide to Fiscal Impact Analysis series (Burchell and Listokin, 1980; Burchell, Listokin, and Dolphin, 1985) and by other sources such as the Illinois School Consulting Service.

The revenue side of the fiscal impact equation has also been marked by improved accuracy. Not only is the property tax more precisely estimated by considering ac­tuallocal assessment practices, but the analysis gives greater consideration to nonproperty tax revenues such as local fees and charges and intergovernmental aid (Stein, 1976). These nonproperty tax revenues are impor­tant sources of income and may be enhanced and, at times, even reduced by proposed development. For in­stance, the introduction of a significant nonresidential ratable or certain types of residential development (such as an age-restricted housing complex) may, by increas­ing the local property valuation per pupil, reduce the state school aid received by a locality. Current applica­tion of fiscal impact analysis incorporates such changes into revenue flows.

Improvement is also evident in the analysis of non­residential facilities. In addition to developing a better sense of how such development influences public revenues and affects local nonproperty and property tax collections and intergovernmental aid, researchers are continually searching for an improved definition of the public service cost consequences of nonresiden­tialland uses. To date, refined applications of both the per capita approach and intensive case study analysiS hold the greatest promise of enhancing the analysis of the fiscal effects associated with the development of nonresidential facilities.

In sum, fiscal impact analysiS has evolved from an ad hoc assessment to a more standardized and accu­rate discipline. In addition, the number of techniques available to the analyst has expanded. In years past, only one method was available for application-a sim­ple version of the per capita multiplier approach. To­day, the per capita method has been refined and supplemented by additional methodologies, indud­lng the case study and econometric approaches.

Fiscal Impact Analysis: Methodology Fiscal impact analysis is a studied, technical under­

taking. Step-by-step procedures to carry out the per capita, case study, and other methodologies are detailed

in a number of procedural guides. The most compre­hensive guide is the Rutgers University publication entitled TIre Fiscal Impact Halldbook (Burchell and Lis­tokin, 1978). The Halldbook has been synthesized and updated in a periodic series called The Practitioner's Guide to Fiscal Impact Analysis (Burchell and Listokin, 1980; Burchdl, Listokin, and Dolphin, 1985). In addition, a useful overview of the different techniques is pro­vided in a 1988 report published by the International City Management Association and entitled"AnalYZing the Fiscal Impact of Development" (Tischler, 1988).

While it is not appropriate to duplicate the detail of the several procedural gUides, it is instructive to sum­marize the substantive content of cost-revenue assess­ment. Four basic procedures guide all fiscal impact methods as follows: • determine the population generated by growth­

people, school-age children, and employees; • translate this population into consequent public

service costs; • project the revenues induced by growth; and • compare development-induced costs to revenues:

if costs exceed revenues, a deficit is incurred; if revenues exceed expenditures, a surplUS is realized. The three fiscal impact metllods-per capita, case

study, and econometric--<liffer mainly in the "transla­tion" of population into public selvices and costs and, to a lesser extent, in terms of their revenue projections and comparison of costs to revenues. The differences will be­come evident from the following discussion of the proce­dures and methods of cost-revenue assessment.

Projecting Population It is important to identify the aspects of growth

that affect public service provision. For residential development, the population and pupil generation associated with different housing configurations is a major influence on municipal and school district oper­ating and capital obligations. The housing types that arc most population-intensive place the greatest cost burden on the public sector in terms of accommodat­ing growth.

The fiscal impact analyst uses demographiC multi­pliers to predict the poputalions that will result from new housing development. As discussed in chapter 6, multipliers calculate the number of the two principal users of local services: people, for municipal services; and school-age children, for school services. The mul­tipliers for household size represent the average num­ber of persons living in a housing unit and vary according to the type and size of housing units. Hous­ing type refers to single-family (detached) homes, townhouses, garden apartments, high-rise units, etc.; size is expressed by number of rooms or bedrooms. As might be expected, detached single-family units are~ on average, associated with larger household sizes than are attached multifamily units while larger units house more household members. The sources

127

for demographic multipliers are detailed in Appendix II of this handbook and are summarized shortly.

The multipliers for school-age children represent the average number of children of school-attending age and are generally specified according to grade category (i.e., K-<i, 7--<l, 9-12). In conducting a fiscal impact study that considers effects on public services, the analyst typically focuses on public school-age chil­dren or the share of school-age pupils attending pub­lic schools.

The discussion thus far has focused on the attribute of residential growth-population (residents and pub­lic school-age children)-that prompts a public serv­ice response. While agreement is Widespread that demographics are the appropriate "unit" to be consid­ered with respect to residential development, the de­bate over the corresponding nonresidential "unit" continues. Several studies, however, have concluded that it is the employment intensity of nonresidential development that prompts public service costs (Bea­ton, 1983). In other words, all things being equal, a nonresidential facility that introduces more jobs into a community will generate a more significant and costly public service response for both operating and infrastructure development outlays than a sister non­residential project that is less labor-intensive.

Employment intensity is typically expressed in terms of the number of employees per 1,000 square feet of nonresidential space. It is higher for certain categories of use such as office development than for warehousing, for example. Data sources for the num­

ber of employees per 1,000 square feet are discussed shortly.

The demographic multipliers for different type and size housing units and the employment-intensity lev­els for the different nonresidential land uses are ap­plied against the matrix of the project pro forma to yield the anticipated project-induced population­people, pupils, and employees. An illustrative exam­ple is shown in Exhibit 8.1. The hypothetical mixed-use development encompasses 300 residential units and 150,000 square feet of nonresidential space. The residential component includes 200 three- and four-bedroom single-family detached homes and 100 two-bedroom townhouses; the nonresidential sector, 100,000 square feet of office space and 50,000 square feet of retail space. Applying household size and school-age children multipliers for the different type and size housing units planned for the project yields a development-induced population estimate of 891 peo­ple and 192 pupilS. (For the illustrative example, the school-age children projection of 192 students is not reduced to a public school-age pupil increment. In a comprehensive study, this last step would be in­cluded.) Applying a ratio of 3.0 employees per 1,000 square feet of office space and 2.5 employees per 1,000 square feet of retail space yields a projection of 425 employees from the nonresidential component of the mixed-use development. As in the social impact assessment, these population projections serve as the starting point for the identification of attendant ef­fects.

Exhibit 8,1: EXAMPLE OF A PER CAPITA FISCAL IMPACT METHOD:

Number of Development Units (in Composition square feet}

Residential

Single-Family DC'tached

lhree-Bedroom 100

Four-Bedroom 100

Townhouse Two-Bedroom 100

Nonresidential

Office 100,000

Retail 50,DOD

Total

NUMERIC EXAMPLE

Popul<ltion (per unit or Project-Generated 1,000 square feel) Population2 Cost per Unit3 Project-Generated Cost

People1 Pupils! Employees People Pupils Employees reople Pupils Employees People Pupils Employees Total

3,09 0.67 NA 3.77 1.14 NA

2.05 !J.l1 NA

NA NA 3.0

NA NA 2.5

I

309 67 NA $581 $6,571 NA $179,529 $4~0,257 NA 377 114 NA $581 $6,571 NA $219,037 $749,094 NA

205 11 NA $581 $6,571 NA $119,105 $72,281 NA

NA NA 300 NA NA $247 NA NA $74,100

NA NA 125 NA NA $247 NA NA $30,875

891 192 425 $581 $6,571 $247 $517,671 $1,261,632 $104,975 $1,884,278

Noles

In this example, public school-age children are assumed for illustrative purposes to equal the school-age children count. In reality, the former will typically be 80 percent to 90 percenl of the latter. In a full, formal fiscal impact analysis, the public school-age children figure would be the basis for calculating public education costs. NA = Not applicable I Derived from the demographic multipliers obtained from the American Housing Survt'lJ (see Appendix II). 2 Equals number of units/square feet multiplied by the respective population/employee profiles. 3Cakulated as shown in Exhibit 8.2

.. 128

Projecting Costs Once the population introduced by growth is deter­

mined, the next step is to translate the increment of people, students, and workers into added public serv­ices and costs. The Fiscal Impact Handbook, The Practitio­ner's Guide series, and the other reference volumes cited earlier all detaU several techniques for deriving the associated services and expenditures while the ma­jor methods are summarized below.

Per Capita Method The per capita method first determines current

public service costs on a per unit basis-per pupil for the school district and per capita and per em­ployee for the municipality, township, village, county, and any special districts (i.e., fire, park, community college). The per student outlay is read­ily determined. Total school costs or the total school property tax levy is divided by the total pupil en­rollment to yield the total cost or property tax ex­pense, respectively, per student.

With noneducational services, however, it is incor­rect simply to divide incurred outlays by the local population because such services benefit both residen­tial and nonresidential land uses. Service costs must therefore be apportioned between these two types of development. The residential share of all residential and nonresidential service costs is estimated by divid­ing the residential property value and number of par­cels by the residential and nonresidential property

values and the number of parcels, respectively. The calculation produces the residential percent of the resi­dential/ nonresidential parcels and the residential per­cent of the residential/nonresidential property value. The two results are averaged, and the combined value is then applied to the total local mWlicipal costs to de­rive the estimated residential-associated share.

ThlS analysis can be illustrated by referring to the example presented in Exhibits 8.1 and 8.2. In the hypo­thetical community of 25,000 residents and 10,000 em­ployees, municipal outlays totaled S17 million. The local tax base, comprising 10,000 parcels, amounted to $800 million. Of this total, 9,600 residential parcels were valued at $600 million, and 400 nonresidential parcels were valued at $200 million. The residential share of total valuation and total parcels was there­fore 75 percent and 96 percent, respectively, for a com­bined average of 85.5 percent. The 85.5 percent figure is applied to the total municipal outlay of $17 million to yield estimated residential-associated expenditures of $14.535 million; the remaining $2.465 Il\illion is as­signed to services associated with nonrestOentialland uses. With a local population of 25,000 and workforce of 10,000 employees, the municipal costs per capita to­tal $581 ($14,515,000/25,000); the service outlay per worker amounts to $247 ($2,465,000/10,000).

Per pupil costs in the illu~trative community are calculated much more Simply. The local school dis­trict incurred outlays of $23 million to educate a stu­dent population of 3,500. The per student expense is therefore $6,571.

Exhibit 8.2: DETERMINATION OF FISCAL IMPACT COST PARAMETERS FOR THE PER CAPITA METHOD APPLICATION

1. Expenditures Total Municipal Expenditures

2. Parcels Total Parcels

Residential Parcels Residential Parcel Percentage

3. Assessed Value Total Assessed Value

Residential Parcel Assessed Value Residential Value Percentage

<1. Expenditure Parameters Estimated Share of Residential-Associated Expenditures

~stimated Municipal Residential-Associated Expenditures (lx4)

Total Local Population Municipal Expenditure per Capita Total School Expenditures Total School Population School Cost per Pupil Total Nonresidential-Associated Expenditures Total Local Employees Municipal Cost per Employee

$17,Goo,000

1O,0GO 9,600

96%

$80G,000,000 $600,000,000

75%

85.5% (96% + 75%) $14,535,000

25,000 $581 ($14.535 million + 25,000) $23 million 3,500 $6,571 $2.465 million ($17 million - $14.535 million) 10,000 $247 ($2.465 million + 10,000)

Source: Municipal and school district budgets.

129

Growth-induced public service costs are then fac­tored by multiplying the per capita cost by the total number of people, employees, and pupils introduced by development. As described earlier, the illustrative mixed-use development was projected to add 891 peo­ple, 425 workers, and 192 students. At a per unit cost of $581 per capita, $247 per employee, and $6,571 per pupil, the per capita method would project costs of about $0.6 million to serve the new residents and added workforce and about $1.3 million to provide public education.

Service costs can also be expressed on a per unit ba­sis. For instance, in the illustrative example, the single­family detached unit contains an average of about 3.43 people and 0.91 school-age children. (This discus­sion aggregates the three- and four-bedroom single­family detached units; a slightly different result is obtained when each type of single-family home is con­sidered individually.) At a per capita and per pupil cost of $581 and $6,571, respectively, the single-family detached home generates $7,973 (3.43 x $581 + 0.91 x $6,571) in public service outlays. For the townhouse unit, which has a lower household size and school­age children yield (2.05 and 0.11, respectively), public service costs amount to $1,191 (2.05 x $581) for mu­nicipal services and $723 (0.11 x $6,571) for schools for a total outlay of $1,914---less than one-quarter of the expenditure for the single-family detached home.

The per capita method is the classic average-cost­ing approach. Service costs are projected at the aver­age per unit outlay per capita, pupil, and employee. 'The technique is straightforward, relatively easily ef­fected, and, in most cases, yields a quick handhold on the impacts of development. For these and other rea­sons, it is the most common technique employed in the field. As such, step-by-step procedures for imple­menting the per capita method are incorporated into the preview model.

Case Study Method The case study approach relies on intensive site-spe­

cific interviews of public officials knowledgeable of lo­cal service conditions and capacities as the primary means of determining the effects of population growth on public services and costs. The interviews identify the anticipated marginal costs of growth given conditions of excess or deficient service capacity. In the case of ex­cess capacity (capacity beyond that needed to accommo­date the existing population at current service levels), growth will add to costs atlower-than-average per cap­ita/ student/employee levels. In the case of deficient ca­pacity (capacitY below that needed to accommodate the existing population at current service levels), growth will add to costs at higher-than-average per capita/stu­dent/employee levels.

The case study method thus departs from the per cap­ita approach in both its assumption and approach. The per capita technique projects population-induced costs at the average per unit outlay, which is detennined ar­

ithmetically by dividing local service costs by the cur­rent service population. By contrast, the case study ap­proach focuses on defining the marginal response to growth through intensive field-level investigation.

These differences are illustrated by the application of the case study approach to the hypothetical mixed­use development. According to the per capita ap­proach, the proposed development would require municipal outlays of about $0.6 million to serve new residents and employees and school outlays of about $1.3 million to accommodate new pupilS. These fig­ures were based on the existing local costs per capita, employee, and pupil. According to the case study ap­proach, expenditures would be ascertained from inter­views that would detail the specific personnel and capital equipment necessary to accommodate the pro­posed growth. For the illustrative project, the case study approach estimates school costs at about $1.1 million-$0.2 million less than the per capita ap­proach because of the system's excess capacity. The case study, however, reveals a higher municipal serv­ice outlay than that indicated by the per capita ap­proach-$0.7 million compared to $0.6 million. The added cost reflects deficient municipal service capac­ity, especially with respect to the volunteer squads, which will require municipal outlays for capital equipment. The level of detail of anticipated effects is revealed only by application of the case study method.

Econometric Method Both the per capita and case study approaches

translate population into service costs in terms of a given set of service conditions and cost parameters de­termined either arithmetically or through site study, respectively. The econometric approach goes beyond the "one-snapshot-in-time" analysis to a "moving pic­ture" of the community and its development profiles and tKe profiles' changing effects and interactions over'time. It employs a basic equation that relates a ju­risdiction's public service expenditures to its revenue parameters-tax base, tax rate, etc. The cost and reve­nue parameters embodied in the equation typically start at the existing average levels----€.g., average costs per capita, average assessed value per unit, etc. To this equation are introduced historical and current data matrices that allow past steady-state and current development conditions (both the target development under study and other simultaneous development) to affect future projections. Data matrices may include local expenditure and revenue levels per capita; the development's pro forma schedules, including build­out by type of land use; value by category of land use; estimates of annual expenditure, revenue, and real property valuation change under steady-state condi­tions; and estimates of annual expenditure, revenue, and real property valuation change under target and other development conditions.

The econometric approach yields a picture of devel­opment impact at the end of the development period as

130

well as at multiple interim stages. nus technique also compares steady-state and other-than-target develop­ment conditions to those of the development under examination. In contrast to the typically fixed view af­forded by the per capita and case srudy approaches, the econometric approach allows fiscal comparisons of growth with and without the target development and thus presents an unfolding and often-changing perspective on the fiscal consequences of growth.

The hypothetical example is useful in illustrating the differences among the three fiscal impact tech­niques. Given that the scltool district spent $23 mil­lion to educate 3,500 pupils, the per capita approach used a $6,571 average per pupil cost parameter to pro­ject growth-induced school outlays for the end-state of development. Thus, if the hypothetical project added 38 pupils a year over a five-year buildout, the development would at completion introduce 192 stu­dents and incur projected growth-induced school costs of $1.3 million (192 x $6,571). For its part, the case study identified some slack school capacity and, as such, projected total school outlays of$1.1 million at the deVelopment's completion or a $5,700 per pupil cost to educate the 192 project-induced students.

By contrast, the econometric approach starts with the eXisting average $6,571 per srudent cost factor but modi­fies the cost over time as the target development, other development, and steady-state conditions interact into the furure. By introducing a more efficient service popu­lation, the population "flows" that result from the incre­mental addition of new households might yield a $6,500 per srudent factor in the first year of the projection, a $6,400 per pupil outlay in the second year, and so on. The econometric approach, unlike the per capita and case srudy applications, would incorporate the year-by­year differences into its annual forecasts. Thus, first-year schaul expendirures would total $247,000 (38 x $6,500); second-year expendirures, $486,400 (76 x $6,400); and so on to the development's end-state. Similarly, the econometric approach would apply a year-by-year cost analysis to municipal outlays, in each case factoring how the target development affects local expendirures over and above steady-state trends and other develop­ment impacts.

Whatever tedmiquc is applied-per capita, case study, or econometric-the translation of population growth into public service costs yields one side of the fiscal impact calculation. These costs must then be matched against development-induced revenues.

Projecting Revenues Public service jurisdictions rely on revenues that in­

clude both local and extralocal sources. Local sources comprise a variety of levies, while extralocal sources pertain to intergovemmental transfers from the state and federal governments.

The local levies are usually the more significant sources of income and encompass taxes and charges

and miscellaneous revenues. The most significant tax is commonly the levy on property. Other taxes in­clude levies on personal property, utility use, con­sumer sales, and income. In addition to taxes, government jurisdictions receive income from fees and assorted revenues from interest earnings, per­mits, charges for services, fines and penalties, etc.

In considering growth-induced revenues, the full ma­trix of public revenues should be examined as follows: I Own-Source Revenues

A. Taxes 1. Real property 2. Personal property 3. Utitity 4. Income 5. Other

B. Charges and Miscellaneous Revenues 1. Interest, rents, royalties 2. Licenses and permits 3. Charges for services 4. Fines 5. Sales of fixed assets 6. Other

II Intergovernmental Revenues A. Slate Aid B. Federal Aid In projecting specifically how growth affects both

local and extralocal revenues, the fiscal impact analyst first considers the basis for each revenue source and then examines how development will affect each source. To illustrate, the property tax is a percentage levy on the value of land and improvements (real property). In some jurisdictions, a property tax is also imposed on personal property as well as on the value of automobiles. To project the property tax revenues from growth, the analyst first determines the assessed value of the development in terms of its property tax constituent components-real, personal, and automo­biles. The assessed valuation is then multiplied by the prevailing property tax rate.

Similar step-by-step calculations shown in Exhibit 8.3 project revenue collections associated with the other revenue sources. To illustrate, many govern­ments receive income from the sales tax. To calculate growth effects, the analyst estimates how develop­ment will add to local sales and then projects the con­comitant gain in sales tax revenues based on the applicable sales tax rate. Another source of local in­come is interest earnings typically derived from in­vesting major revenues before they are disbursed to pay for local expenses. The local interest earnings from growth can be determined by calculating how development adds proportionately to local revenue re­sources (i.e., property tax base) that can be invested.

In certain instances, revenue collections are related. to population size. For example, many local governments raise funds from fines/lioenses and pennits. As growth adds to the population base, the community will levy more traffic violations and overdue library charges, collect

131

Exhibit 8.3: FISCAL IMPACT ANALYSIS: MUNICIPAL REVENUE CALCULATION EXAMPLES

REVENUE SOURCE REVENUE FORMULA

I Own-Source Revenues I.A. Taxes I.A.I. Property Tax

Market value x Assessment factor Assessed val ue

Assessed value x Property tax rate Property tax revenue

I.A.2. Utility Tax Utility consumption Utility tax rate

X Utility tax revenue(Le., kWh consumption) (i.e., per kWh)

I.A.3. Sales Tax

Added local sales x Sales tax rate Sales tax revenue

I.A.4. Other Local Taxes I.A.4. a. Real Estate Transfer

Market value Transfer Annual turnover Real estate transfer of property

x tax rate

x percent sales tax revenue

I.A.4.b. Motor Vehicle Sticker Vehicle ownership by Vehicle sticker fee Motor vehicle sticker

type / size of housing unit x

per automobile tax revenue

I.A.4.c. Transient Occupancy Tax Daily Daily Nwnber Transient TransientNumber of

x occupancy x rate per x of rooms x occupancy occupancymotel rooms

rate room rented daily lax tax revenue

LB. Charges and Miscellaneous Revenue Assessed value of growth

+ x Existing interest income Interest revenue Existing community tax base

Population by type /size of x Per capita license License and housing unit and permit income permit revenue

I.B.I. Interest Earnings

I.B.2. Licenses and Pennits

I.B.3. Charges for Services

1.8.4. Fines and Forfeits (Examples)

II Intergovernmental Revenues State Assistance II.A. Income Tax Redistribution

II.B. Motor Fuels Redistribution

II.c. Other State Aid

Population by type/size of x housing unit

Vehicle ownership by type /si.ze of

housing unit

Population by type / size of

housing unit

Population by type / size of

housing unit

Population by type / size of

housing unil

Population by type / size of

housing unit

Per capita service charge income

x

Per capita automotive fine revenue

x Per capita

library fine

x

x

income

Per capita income tax

redistribution

Per capita motor fuels

redistribution

Per capita

Service charge revenue

Automotive fine

revenue

library fine

revenue

Income lax

revenue

Motor fuels

revenue

Other x "other" state aid

state aid revenue

more bicycle registration fees, etc. Therefore, local in­come from fines and licenses can be expected to in­crease as a proportionate share of population

Intergovernmental income is projected similarly. Thus, if a state granted $100 per pupil for textbooks, the development-associated income for such aid would be equal to the number of new students multiplied by $100. Where school aid fonnulas are more complex and, for example, incorporate ratios between the local versus state average equalized valuation per student, the ana­lyst would then ascertain how these relationships would change with the onset of development and thus how state support fonnulas would be altered.

By applying the formulas depicted in Exhibit 8.3, the hypothetical example generates a total $2.2 mil­lion in revenues. Of this amount, the largest share, $1.4 million or about two-thirds, is attributable to the property tax; the remaining $0.8 million reflects the ar­ray of local nonproperty and intergovernmental aid sources described above. These figures would typi­cally be disaggregated to the unit level. In the hypo­thetical example, the single-family detached homes (combining the three- and four-bedroom units) gener­ate about $7,200 in total annual revenues; the lower­priced townhouses yield $3,800 in total annual revenues.

In projecting growth-induced costs, fundamental differences may be observed among the per capita, case study, and econometric approaches. In determin­ing revenues, the differences are more a matter of nu­ance. To illustrate, in the case study approach, the analyst typically spends the most time interviewing public officials responsible for revenue-municipal and school business administrators, the tax assessor, tax collector, etc. Further, in both the per capita and case study approaches, established tax parameters (i.e., a $2.00 property tax rate) are applied to forecast the growth-induced revenues at the end-state of devel­

opment. By contrast, the analyst applying the econometric approach starts with a tax value such as the property tax rate but would modify the rate annu­ally into the forecasting period as the target develop­ment, other development, and steady-state conditions affect the jurisdiction's fiscal posture and annual prop­erty tax levy. Thus, the first-year tax rate could be $2.00 but could decline to $1.90 in the second year, to $1.85 in the third year, and 50 on as ensuing develop­ment results in a fiscal surplus. This interactive rela­tionship over time between development and the tax rate differentiates the econometric approach from the per capita and case study methods.

Comparing Costs to Revenues Once the growth-induced population is projected,

the next step is to determine the basic values for a fis­cal impact assessment by translating the forecasted population into costs and estimating the development­generated revenues. Costs are matched against reve­nues; if they exceed revenues, a deficit i~ incurred; if they fall short of revenues, a surplus is realized. When the per capita and case study approaches are applied, the cost-revenue comparison is typically expressed as an end-state value at development buildout; when the econometric technique is used, the cost-revenue com­parison is usually presented as a series of annual net results. The results are typically expressed for both the overall project and the individual development categories.

In the illustrative example, application of the per capita approach yielded total annual service costs ap­proaching $1.9 million versus annual revenues of about $2.2 million. The result is a net fiscal surplus of approximately $0.3 million. The result is a composite of the different fiscal impacts of the respective project components. Thus, as shown below, the single-family

SUMMARY OF THE FISCAL IMPACTS OF THE ILLUSTRATIVE EXAMPLE

Fiscal Impact per Unit (per residential unit! per 1,000 square feet)

Number Units/ Total Project Net Project Component 1,000 Square Feet Costs Revenues Net Impact Fiscal Impact Residential

Single-Family Detached1 200 $7,973 $7,190 ($783) ($156,600) Townhouses 100 $1,914 $3,804 $1,890 $189,000

Nonresidential Office 100 $740 $2,993 $2,253 $225,300

Retail 50 $616 $2,394 $1,778 $88900

$346,600

Rounded to $347,000

Note 1 Averages the results of three- and four-bedroom units, i.e., uses a 3.5 household size and 1.0 school-age child multiplier for "blended" 3.5 bedroom single-family detached units.

133

detached homes with high household and school-age children profiles produce a fiscal deficit, but the loss is more than offset by the surplus associated with the attached townhouse units and the project's office and retail uses.

The above discussion shows the fiscal impact re­sult derived from the per capita method. With other methods, the finding would be somewhat different. For instance, wherever the per capita approach esti­mated annual service costs at about $1.9 million, the case study estimated a lower service outlay of $1.8 million-Dr $0.1 million less-due to the method's consideration of considerable excess school capacity. The net fiscal surplus would therefore be $0.1 million more by applying the case study method or a total of $0.4 million.

Selecting an Appropriate Fiscal Impact Method

Thus far, the three fiscal impact methods have been described in terms of their application. But it is important to consider the basis for their selection. Un­der what conditions would the analyst use the per capita, case study, Or econometric technique?

One consideration relates to the appropriateness of average costing. When the service system capacity bears a close relationship to service demand and the average cost of providing services to current users is a reasonable approximation of the cost to provide serv­ices to future users, the average-cost approach is most appropriate and dictates use of the per capita ap­proach, which stresses average per unit service com­mitments. By contrast in jurisdictions with considerable slack or deficient service capacity, aver­age per unit service costs would misstate the true ef­fects of growth. The average would overestimate the needed service commitment in instances of slack ca­pacity and would understate the expensive service re­sponse necessary under conditions of deficient capacity. Accordingly, the case study, which is most sensitive to local conditions and anticipated effects, would be appropriate.

The case study is also the best method for deter­mining the impact of specialized nonresidential facili­ties, including military bases, energy plants, regional shopping centers, and other nonresidential develop­ment that does not lend itself to Simple average per unit cost projections. For similar reasons} the case study is suited to assessing the fiscal impacts of atypi­cal residential development such as group homes or other facilities for special needs populations.

When is the econometric method applied? As an average-costing approach, the econometric method should not be used in situations where considerable slack or deficient capacity has been identified. Simi­larly, it is not appropriate for the specialized condi­tions best handled by the case study. The econometric

method is instead used in "standard" development cases where average per unit costing reflects public service realities. In other words, the same general con­ditions that dictate the selection of the per capita method apply as weB to the econometric method. The analyst, however, applies the econometric approach as opposed to the per capita technique to the analyses of unusually large developments with commen­surately long build-out periods (e.g., a planned unit development comprising thousands of units that will enter the market over a decade). The very size of the developments might alter some of the basic condi­tions affecting a community's cost and revenue pa­rameters (e.g., the local school-age population and reliance on local versus intergovernmental revenue). In addition, large-scale projects often produce differ­ent impacts over the course of their buildout. Because the econometric technique's equation incorporates a jurisdiction'S interactive and evolving cost-revenue ef­fects over time, it is most suitable for ascertaining the impacts of large, multiyear projects.

A price, however, is attached to the use of the econometric method. The technique requires consider­able setup time for the basic modeling and is there­fore much more expensive than the other techniques discussed, especially the per capita method. Another consideration is that the advent of desktop computers permits the increasingly sophisticated application of the per capita method. As a result, that method can now incorporate some of the features that were once unique to the econometric technique. For instance, a per capita approach, once typically limited to show­ing only end-point results, may now incorporate inter­mediate fiscal outcomes as well.

In the field, the per capita method is by far the most commonly applied of all fiscal impact tech­niques. It therefore serves as the basis for the preview model. First, however, the discussion turns to requisi­te data sources for conducting a fiscal impact study.

Data Sources Whichever method is selected, several data ele­

ments must be collected. The most critical informa­tion sources are discussed below.

Demographic Multipliers Demographic multipliers indicate the average num­

ber of people and school-age children residing in differ­ent type and size housing units. They are available from national data sources and local surveys. The former in­clude the Public Use Microdata Sample (PUMS) of the decennial census and the American Housing Survey (AHS). Local data are available from the municipality, schools, developers, and other sources.

134

Appendix II of this handbook contains the most current demographic information available from such macrolevel sources as the rUMS and AHS. It presents the average household size and average number of school-age children, the latter differentiated by grade level. The information is organized around the most common housing types and sizes (as expressed by number of bedrooms).

Another source of multipliers, typically of the school-age children profile, is local surveys usually conducted by or in cooperation with the school board or school superintendent and based on busing or at­tendance records. In fact, the fiscal impact analyst should usc a local survey to validate the multipliers obtained from the rUMS or AI-lS, particularly when a fiscal impact assessment is applied to specialized housing types. For instance, in projecting the number of school-age children generated by a proposed town­house development in a ski resort, the analyst should consider the school yields of similar vacation-oriented housing developments in the area, not the general school-age children counts derived from the rUMS or AHS.

A local survey is conducted as follows. First, a list of housing developments similar to the project under study is compiled (i.e., recently completed ski-area va­cation homes) along with information on the number of housing units and their bedroom distribution. Sec­ond, the number of school-age children (K-12) for each of the identified housing developments is ob­tained. The pupil counts are available from busing, at­tendance, and other records maintained by the local schools The third and final step is to divide the total number of school-age children by the total number of units to derive the average number of school-age chil­dren per unit for the project under examination (i.e., ski-area vacation homes containing two and three bed­rooms).

The discussion thus far has focused on local pupil counts. [t is much more difficult to determine local household size. In some instances, demographic infor­mation on household size is locally available from renter and housing purchaser applications as well as from other marketing information maintained by de­velopers. These sources can be used as a rough gauge to determine the average household yield per unit.

The use of locally derived demographic multipliers offers several advantages. First, with respect to fiscal im­pact assessment, demographic multipliers-used to de­termine the number of people, particularly school-age children, generated by growth-are often the single greatest source of controversy and thereby frequently call into question the credibility of the results of a fiscal impact assessment. Locally derived multipliers, how­ever, can disarm much of the controversy. Second, local surveys typically provide the most current information and the most jurisdiction-specific data (e.g., for the same school district under study). By contrast, demographic multipliers from the PUMS or AHS may be dated by a

few years and/or may be available only on a larger geographic scale (e.g., a county, Metropolitan Statisti­cal Area, or census region as opposed to a local com­mtmity or school district).

In practice, obtaining local demographic data is often problematic. Inlormation on the number of school-age children generated by specific types of development may not be recorded or may be held confidential and kept from the analyst. Even if school yields from com­pleted projects can be obtained, the nwnber of units and bedroom distribution of the development in question­especially the latter--are frequently difficult to ascer­tain. These hurdles are compounded with respect to the overall project-generated population because no coun­terpart to a school district keeps records on the number of people in different types of housing. Finally, a com­mon problem with available sources of local informa­tion is insufficient sample size Of, worse, reliance on a biased sample.

In summary, despite the several advantages associ­ated with locally derived demographics, the analyst usually has to rely on national sources-the rUMS or AHS. Whenever possible, however, the analyst should seek out local information. A local survey adds to the fiscal impact assessment's credibility and is especially compelling when considering atypical housing types such as vacation homes, units clustered around a spedal use (i.e., marina or golf course), and high- and low-end developments (i.e., estate homes and very low-income housing).

Nonresidential Multipliers Nonresidential multipliers indicate the number of

employees associated with different types of nonresiden­tialland uses such as office, retail, and industrial devel­opment. The multipliers are typically expressed as the worker count per l,OOO-square-foot module and are de­rived from the sources noted in conjunction with the cal­culation of the operation-phase direct employment impacts in the economic impact analysis (chapter 7). For instance, information on the number of retail employees per 1,OOo-square-foot module can be derived from the data contained in the Census ofRetail Trade. Office em­ployment intensity is indicated in Trip Generation pub­lished by the Institute of Transportation Engineers. In addition to these published materials, the analyst may wish to contact trade and research organizations such as the Urban Land Institute and the International Council of Shopping Centers and local planning, economic de­velopment, and tax offices (e.g., certain jurisdictions im­pose a "head tax" per employee and thus keep records on employment intensity).

Population An accurate count of the public jurisdiction's cur­

rent population is necessary for determining accurate

135

per capita/per pupil costs that then become the basis for the per capita and econometric methods. Informa­tion on population is available from the local plan­ning department, the school district's vital statistics office, and/or from state, county, or regional plan­ning agencies.

In using the population statistics, the analyst must take advantage of the most current data. Typically, school districts update their census of on-roll students on a quarterly or even more frequent basis. By con­trast, figures on the total population are often out­dated, especially in intercensal periods.

It is incumbent upon the analyst to update all population counts to the most current period by ex­amining recent local housing production activity as in­dicated by the number of certificates of occupancy that have been issued and by pairing production with the household sizes indicated by the demographic multipliers (see AppendiX II). To illustrate, if a com­munity reported an estimated 1990 population of 10,000 and added 100 units of single-family detached homes over 1991 to 1992, each with an estimated household size of 3.5, then the community's 1992 population would be estimated at 10,350. The current (1992) population would then be properly paired with current (1992) cost and revenue figures (e.g., to­tal municipal expenditures and total nonproperty tax income related to population) to derive valid fiscal im­pact parameters (e.g., 1992 per capita municipal ex­penditures and per capita nonproperty tax revenues).

Costs and Revenues Cost information is obtained primarily from the

budgets of the municipality, school district, and other public jurisdictions affected by growth. TIle analyst must consider the full set of budgetary documents, in­cluding a summary volume/section as well as de­tailed backup materials on operating outlays (for staffing and support expenditures), capital costs (for major purchases), and debt service (for principal and interest repayment on preViously incurred liabilities). The analyst should also consult other documents that reveal the jurisdiction's spending proclivities and needs. Such documents range from the business ad­ministrator's annual message that usually highlights changes in the immediate past and upcoming fiscal years to the jurisdiction's official capital facilities plan.

Revenue information is similarly available from the municipal, school district, and county annual budgets as well as from the other documents mentioned above. It is important to go beyond merely identifying the ju­risdiction's sources of income to understanding how these monies are allocated. Thus, information on how locally collected but state-distributed revenues (i.e., sales taxes) are transferred often must be obtained from the state treasurer's office. Similarly, informa­tion on the status, flow, and future distribution of state and federal intergove=ental transfers, such as

aid to education, must come from the state treasurer's office and/or from federal program sources.

Property Tax Rate/Equalization Ratios The analyst must obtain the property tax rates for

the relevant public jurisdictions and, equally as impor­tant, the assessment-to-sales or equalization ratios. These ratios are important for indicating the share of true value at which a property is assessed; a ratio of 0.5 means that a property is assessed for tax purposes at one-half its true value; a ratio of 0.25, at one-quar­ter of real value; and so on. To project revenues from the real property tax, the fiscal impact analyst multi­plies the expected assessed value of the incoming de­velopment (as determined by the assessment ratios) by the property tax rate.

Information on the tax rate and equalization ratio is available from the clerk, assessor, or business ad­ministrator of the respective public jurisdictions af­fected by the development. In considering anticipated property tax income, the analyst must consider the ac­tual practice of the tax assessor's office, which may not always comport with the nominal official guide­lines. For instance, toward the end of the tax year, a "working" equalization ratio may differ from the pub­lished figure due to changing values. This working ra­tio must be incorporated into the fiscal impact calculation.

Trends/Projections in Expenditures, Revenues, and Populations

The econometric approach accounts for trends/pro­jections in expenditures, revenues, and populations. Information is available from many of the source documents cited above as well as from interviews with public officials. For instance, the school superin­tendent should be queried with respect to anticipated enrollment trends and the receipt of state aid.

Preview and Quickway Models of Fiscal Impact Analysis

The preview model of fiscal impact analysis fol­lows the per capita methodology-the most widely applied fiscal impact technique-and encompasses the basic steps of cost-revenue analysiS. First, the model projects the number of people/pupils/employ­ees generated by growth. Second, it translates the population increment into attendant public service costs by multiplying the development-generated population by the per person/pupil/employee expen­diture factors. Third, the preview model considers the revenues added by growth and, finally, compares costs to revenues to yield the net fiscal impact.

136

Quickway approaches the cost side of fiscal impact analysis by using model factors for the development­generated population and employment. Population and employment arc converted to costs of develop~

ment by applying other model factors for average costs per capila, pupil, or employee. QUickway han­dles development-generated revenues by applying av­erage equalized tax rates to the development's market value. Included. too, are average relationships be­tween property taxes generated and other sources of revenue.

Quickway's results include a comparison of costs and revenues to the host municipality, school district, and county as well as a statement on the magnitude of the annual fiscal surplus or deficit: small, rnoder~

ate, or large. The level of the annual surplus or deficit is further presented as a share of total annual reve­nues raised.

The analysis in the preview model is effected through a series of inputs and outputs (see Exhibit 8.4). The inputs include base data either built into the model (i.e., demographic multipliers) or added by the user (i.e., the project pro forma and the local property tax rate). The outputs include the interim and final cal­culations of fiscal impact analysis such as the develop­ment-induced population, service costs, revenues, and the net fiscal effect.

The inputs and outputs of the preview model are discussed in greater detail below. The 23 input factors follow:

Population Faclors. To project the development-in­duced population and workforce, the demographic and nonresidential multipliers were already applied to the project pro forma in the social impact compo­nent of the model. The inputs therefore start with the public service expenditure profile.

Cost Factors (Inputs 1-9}.lnputs 1 through 9 encom­pass the public service costs for the different public ju­risdictions affected by growth, including the municipality, county, school district, etc. To apportion municipal!county expenditures associated with resi­dential and nonresidential uses, respectively, the ana­lyst enters the valuation and number of parcels . contributed by the two respective land use categories. The data are readily available from the local business administrator, treasurer, and assessor.

Revenue Factors (Inputs 10-23). Inputs 10 through 23 include parameters for calculating the development­induced property tax, local nonproperty tax, and inter­governmental revenues. As with local costs, these factors are unique to each location; therefore, the spe­cific local values must be entered into the model.

The values are readily available. For the property tax, the analyst obtains the applicable assessment-to­sales ratio and the property tax rates from the asses­sor's office for entry into the model as inputs 10 through 15. For local nonproperty income and inter­gov€'mmental sources, revenues are expressed on either a per capita basis or a valuation-added basis

(i.e., per $1,000 of assessed value). Obtained from the existing local budget, these values are entered as in­puts 16 through 23.

The preview model contains 16 outputs that are re­lated to the input fields as follows:

Population Generation (Olltputs 1-3). For the devel­opment under exalnination, the model generates the number of people (output 1) as well as the number of children added, the latter differentiated by school grade level (K--{j, 7-8, 9-12) (output 2). In parallel, where nonresidential or mixed-use development is considered, the model yields the number of employ­ees (output 3).

Cost Generation (Outputs 4-7). The model multiplies the project-induced population by the existing cost pa­rameters contained in inputs 1 through 7 to generate the project-induced outlays required of the municipal­ity, school district, and other public jurisdictions.

Revenue Generation (Outputs 8-12). The property tax determination involves two calculations. First, the as­sessed valuation (output 8) is computed by applying the assessment ratio to the market value of the project (both previously entered as inputs 10 and 11). The model then applies the property tax rate for the appli­cable public jurisdictions (inputs 12 and 13) to the as­sessed valuation to yield the development-induced property tax revenue by jurisdiction (output 9).

The model projects local nonproperty tax income (output 10) by multiplying the project-induced popu­lation and valuation (outputs 1, 2, and 8) by the pre­viously determined nonproperty tax revenue per capita and per $1,000 valuation, respectively (inputs 16,17,20, and 21). The intergovernmental revenue generated by growth (output 11) is calculated through a similar procedure.

The sum of the development-induced property tax, nonproperty tax, and federal and state aid (outputs 9 through 11) yields the total income generated by growth (output 12).

Net Fiscal Impact/Effects (Outputs 13-16). The net fis­cal impact is determined by comparing the develop­ment-induced costs versus revenues. The resulting surplus or deficit figures are indicated individually for all the affected public service jurisdictions as well as in aggregate (outputs 13 and 14). These cost-reve­nue outcomes are then placed in perspective by relat­ing the figures to total revenues as well as to the property tax levy for each affected public jurisdiction (outputs 15 and 16).

Advantages and Limitations of the Preview Model

The fiscal impact preview model offers numerous benefits. First, it is patterned after the per capita ap­proach, which is the most applicable and widely used cost-revenue method. Its data demands are not bur­densome; the input factors are either built into the

137

Exhibit 8.4: PREVIEW AND QUICKWAY MODELS OF FISCAL IMPACT ANALYSIS

INPUT

DEVELOPMENT-INDUCED POPULATION (PREVIEW MODEL)

1. Development-generated residents 2. Development-generated school·age children

3. Development-generated employees

PUBLIC SERVICE EXPENDITURES (PREVIEW MODEL)

1. Total municipal expenditures 2. Total residential parcels

3. Total nonresidential parcels 4. Total re~identidl valuation

5. Total nonresidential valuation 6. Total municipal population

7. Total nonresidential employment 8. Total education expenditures

9. Total school enrollment

PUBLIC SERVICE REVENUES (PREVIEW MODEL) 10. Project value

11. Property·tax-assessment-to·sales rate 12. Municipal property tax levy (rate) 13. School property tax levy (rate)

14. Municipal property tax base

15. School property tax base 16. Municipal nonproperty taxes associated with

property value 17. Municipal nonproperty taxes associated with population

18. Municipal intergovernmental revenues associated with property values

19. Municipal intergovernmental revenues associated with population

20. School nonproperty taxes associated with value 21. School nonproperty taxes associated with population 22. School intergovernmental revenues associated with value 23. School intergovernmental revenues associated with

popUlation

OUTPUT

DEVELOPMENT-INDUCED POPULATION (PREVIEW MODEL)

1. Development-generated residents 2. Development-generated school-age children 3. Development-generated employees

PUBLIC SERVICE EXPENDITURES (PREVIEW MODEL)

4. Development-induced municipal expenditure 5. Development-induced municipal nonresidential

expendihlre 6. Development-induced school expenditure 7. Development-induced total expenditure

PUBLIC SERVICE REVENUES (PREVIEW MODEL)

8. Development~induced assessed valuation 9. Development-induced municipal property tax revenue

10. Development-induced municipal nonproperty taxes 11. Development-induced municipal intergovernmental

revenues 12. Total municipal development-induced public revenues 9. a. Development-induced school property tax revenues

10. a. Development-induced school nonproperty taxes

11. a. Development-induced school intergovernmental revenues

12. a. Total school development-induced public revenues

DEVELOPMENT NET FISCAL IMPACT (PREVIEW MODEL)

13. Development·mduced municipal net fiscal impact 13. a. Development-induced school net fiscal impact 14. Development~induced total net fiscal impact 15. Municipal fiscal impact perspective (total revenues)

(Quickway)

15. a. School fiscal impact perspective (total revenues) (Quickway)

16. I\.funicipal fiscal impact perspective (property taxes) 16. a. School fiscal impact perspective (property taxes)

138

model or otherwise readily obtainable. For instance, the assessment-to-sales ratio and property tax rates as well as the number and value of parcels by resi­dential/nonresidential type are either posted in offi­cial public documents such as the annual tax roll or are available from a telephone call to or interview with the tax assessor. Similarly, the other cost and revenue parameters, including municipal and school expenditures, are also readily collected from published budgetary documents and/or from con­tacting the local business administrator and school superintendent.

Despite its modest input data demands, the model produces a full array of cost-revenue outputs, includ­ing a detailed breakout of the development-induced population; costs by public service jurisdiction; costs induced by the residential versus nonresidential com­ponents of a project; revenues by jurisdiction; reve­nues differentiated into property, other local source, and intergovernrnental categories; and, finally, the net fiscal effects by individual jurisdiction and the aggre­gate public impact. Thus, the model does not give a "black box" final result but arrays and shows all the calculations and intermediate products that lead to the calculation of the final fiscal impact.

Nonetheless, the model does have some shortcom­ings. As a per capita methodology, the model is widely applicable though not always best suited to all situations. To illustrate, in cases of severe excess or slack capacity, the case study approach provides a more accurate picture of the impacts of growth. In ad­dition, the case study method offers a level of descrip­tive detail on local conditions and service responses that goes far beyond the preview model's strictly nu­meric outputs.

Another shortcoming concerns the manner in which the model calculates revenues. Revenue inputs are factored on a per capita or valuation-increment ba­sis. While such an approach is generally acceptable, it oversimplifies certain revenues--especially intergov­ernmental transfers. Intergovernmental aid is often distributed according to complicated formulas that re­late local to state parameters (local valuation per pu­pil compared to a state foundation level) whose values themselves change annually. The preview model is not structured to reflect such a high level of specificity and, as such, yields an approximation rather than the most accurate projection of develop­ment-induced revenues.

This discussion points to the appropriate use of the preview model. The model does not substitute for a comprehensive, report-length fiscal impact study that embodies case study detail, considers the nuances of each revenue source, and so on. The preview model does, however, provide a reasonably reliable depic­tion of the order-of-magnitude fiscal impact of growth. It is useful for quickly answering whether de­velopment will approximately break even or likely generate a large or small surplus or deficit.

Such order-of-magnitude information is useful in several situations. When a project is first considered, the developer often explores alternative development possibilities in terms of type, scale, and location. A quick preview analysis of the fiscal effects of the vari­ous scenarios can help the developer select the most promising options. The analysis would typically be undertaken in conjunction with parallel studies of eco­nomic feasibility and environmental and traffic im­pacts. (These other exploratory studies could be assisted through use of the preview model in the vari­ous substantive areas.)

Once a developer decides on a development option and applies to the appropriate public authorities for de­velopment approval, the fiscal impact preview model can proVide useful information. On a smaller project, say a subdivision of 20 to 30 homes, a full fiscal impact study may not be required or even appropriate. None­theless, it is often instructive to present the findings of the preview analysis-provided the limitations of the model are made clear. Even when an independently commissioned, standalone cost-revenue study is per­fanned, a developer or consultant may wish to "run" the model to get a quick, in-house sense of the final re­sults. This preview is useful because the full study may not be completed for many months.

Critiquing a Fiscal Impact Analysis A fiscal impact study is reviewed by several indi­

viduals-the client paying for the report, plan­ning/ zoning board members, the consultants retained by these boards, and the public at large. The follow­ing provides a checklist for such review:

General Considerations Inadequate Documentation

The "numbers" in a fiscal impact report-the devel­opment-induced residents and school-age children, cost figures, the new increment of property taxes, and so on-are often presented without sufficient back­ground discussion and documentation. It is impera­tive to detail the assumptions, databases, and calculations that guided the analysis so that the study can be understood, followed, and replicated.

Unbalanced Presentation The cost-revenue equation must be appropriately

balanced across several dimensions. Most fundamen­tally, both revenues and costs must be presented. In a few lingering cases, an analyst presents only one side of the equation, typically the revenue side, and indi­cates that a "shopping center will generate $1 million in property taxes upon buildout." The revenue fig­ures signify nothing in the absence of corresponding cost figures.

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Even when both costs and revenues are indicated, it is important to avoid further imbalances. For in­stance, if the analysis considers only the costs sup­ported by the property tax (i.e., the per capita expense determined by dividing the property tax levy by the local population), then it must focus exclusively on ad valorem revenue collections. If other growth-induced revenues (i.e., intergovernmental aid) are added, then the analysis is unfairly tilted to show a benefit from growth.

Large Order-of-Magnitude Impact A fiscal impact report is suspect if it shows a result

that is extremely large in terms of its order-of-magni­tude effect on the community-whether a significant surplus Dr deficit with a marked effect on the local ju­risdiction (e.g., either decreasing or increasing prop­erty taxes by 40, 50, 60 percent or more). While it is theoretically possible that a project can yield a signifi­cant result, it is more likely that a fiscal impact study is flawed by one of the above considerations (e.g., costs are not correctly paired with revenues) or by one of the technical errors outlined below.

Technical Checklist Demographic Multipliers

Are the multipliers current? Do they reflect the lat­est available information such as that contained in Ap­pendiX II? Are the multipliers correct? For instance, to calculate a development's impact on the local school district, the analyst should use the number of public school-age children and not the more encompaSSing school-age children figures; the latter includes stu­dents attending nonpublic schools. Are the multipli­ers appropriate? As discussed, general demographic sources should not be used for specialized housing types. Are the demographics locally sensitive? Has every effort been made to obtain local information and/or feedback?

Projecting Costs Is the appropriate method applied-per capita,

case study, or econometric? Are the cost factors cur­rent? Do they reflect the latest budgets and popula­tion estimates? Are costs properly stated? For instance, public jurisdictions usually pay for infra­structure over time; consequently, development-in­duced capital costs should be shown on an amortized rather than lump-sum basis.

Projecting Revenues Are the appropriate revenues counted? As stated ear­

lier, costs and revenues must be properly paired in terms of the property tax and nonproperty tax compo­nents. Are the revenue factors clIrrent? Do they reflect the latest assessed ratios, property tax rates, permit and fee schedules, and intergovernmental allocation formulas? Are the revenues locally sensilive? Do they

incorporate the field-level operating practices of the assessor and other tax officials? Are the revenues properly stated? For instance, certain revenues are generated annually, but others accrue on a periodic basis, Le., the time at which a property is sold and the recording tax paid. This difference in timing should be incorporated into the analysis. To illustrate, if prop­erties tum over an average of once in five years and the transfer tax on a sale is $2,000, then the expected transfer tax income per year is $400. Applying the $2,000 amount per unit annually would overcredit the development-induced revenues.

The reviewer should also be sensitive to possible mathematical errors in the calculation of both costs and revenues. For example, a mismatch commonly oc­curs in pairing the property assessment with the tax rate. Applying an equalized tax rate to the assessed tax base results in an undercount of income; con­versely, multiplying the market value by the nominal tax rate overcounts revenue. The correct procedure is to use the same basis for both rate and assessment.

In short, a fiscal impact analysis is a technical un­dertaking and, as such, many factors must be moni­tored in revieWing such a study.

Presentation The fiscal impact analysis report should contain

the following components:

A. Summary of Findings Brief presentation on the number of people, school­

age children, total costs/revenues, fiscal surplus or deficit, and impact on local taxes.

B. Overview of the Report Outline of what was requested, what (if anything)

was added to the report, and-as important-what was not covered in the analysis.

C. Methodology Employed Basic technique employed-per capita, case study,

or econometric; what the procedure covers; the advan­tages associated with the chosen method.

D. Data and Data Refinement Information sources: published documents, com­

puter tapes, site visits/personal interviews, and/or other local surveys.

E. Development Costs What are they? What do they include (operating

and capital)? How severe a test of the development are they? How do the estimated costs compare to the results from other studies conducted in either the same jurisdiction or elsewhere?

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F. Development Revenues What are they? What do they include (local/inter­

governmental transfers)? How conservative is the analysis of revenues? How do the report's projections compare to studies of development revenue flows conducted in the same locale or elsewhere?

G. Net Fiscal Impact Annual and!or cumulative annual difference be­

tween costs and revenues. To be conservative, if the study demonstrates a significant positive revenue flow, the analyst must understate the surplus by add­ing a cushion for additional costs. If the study demon­strates a small net impact relative to earlier expenditures or the fiscal profile data, the analyst should not specify a trivial surplus or deficit but in­stead call the net impact a "break even."

H. Impact in Context What is the impact of the development in the con­

text of total local expenditures or in the context of all revenues raised through the property tax? What will it mean to the tax rate? How does it compare to other tax increases or decreases experienced historically?

I. Rigor of the Analysis The analyst should emphasize the extreme care

taken to interpret the development and its impact and discuss how reliance on the chosen method-per cap­ita, case study, or econometric-produced the most rigorous pOSSible analysis.

The public presentation of a cost-revenue report be­fore a planning board, board of adjustment, and so on combines the technical nature of the written report with the art of oral communications. In general, the public presentation follows the report format de­scribed above. It should avoid jargon, obscure meth­odological discussion, and unnecessary numeric detail. The presentation should proceed as follows:

Introduction and Summary. Describe "fiscal im­pact analysis" in simple terms and present the find­ings for the case in question. Place the projected cost-revenue result in proper perspective by stating what it means to the local taxpayer.

Methodology. Outline the method used by relying on a general illustratiye example. Explain why the technique was chosen.

Projecting Population. Summarize the projected number of people, pupilS, and workers generated by growth. Given that projections often become a point of contention, describe in some detail how the devel­opment-induced population was determined. Indicate that the numbers were reviewed with local officials and in other ways checked against "real world" expe­rience. Discuss the development-induced population within the context of the eXisting local population base.

Projecting Costs. Describe the cost projections in simple terms and proVide an illustrative example of the calculation. Describe briefly what the imputed costs will pay for-added staffing, equipment, and!or capital improvements. Relate the develop­ment-induced expenditures to existing local service outlays.

Projecting Revenues. Indicate the revenues that were projected-local property, local nonproperty, and intergovernmental-and give an illustrative ex­ample of lhe projection, especially with respect to the property tax. Most people are familiar with this reve­nue source. Summarize the dollar amounts generated from the different revenue sources and provide the to­tat; relate the total to the existing total revenue base.

Net Fiscal Impact. Restate the population-induced service costs, development-generated revenues, and the resulting net fiscal effect and immediately discuss the net fiscal effect in terms of what it signifies to the local budget and taxpayer (e.g., added/reduced an­nual property taxes of $50 per household).

It is also important to discuss, where appropriate, the conservative nature of the fiscal impact approach. The analyst should stress that fiscal impact analysis overstates the development-induced population and costs but undercounts revenues. To illustrate; the ana­lyst might state, "While official school enrollment studies use a multiplier of 1.0 for single-family de­tached homes, the cost-revenue report factored a value of 1.1 derived from the PUMS. This means that an additional $15,000 in school outlays was attributed to the project." Similarly, the analyst should under­score the confidence level of the fiscal impact finding by stating, "Even if the development-induced costs are twice as high, a fiscal impact surplus will still re­sult."

Summary. It is opportune at the concluding point in the presentation to summarize the interim and final demographic and fiscal results of the cost-revenue analysis and to discuss their significance. It is useful to prepare a summary sheet!board that arrays the critical project-induced effects against the commu­nity's current population and financial parameters. Such a presentation places the project-induced effects in perspective.

The art of effectively presenting the results of a fis­cal impact study cannot be overstressed. A fiscal im­pact report cannot be presented in the abstract by merely stating the net result without an explanation of the intermediate calculations and base assump­tions. Such an approach compromises credibility. On the other hand, too much emphasis on numeric and methodological detail will lose the audience. An effec­tive presentation achieves a balance of appropriate technical detail and narrative that can be clearly fol­lowed by the audience.

One way of fostering effective communications is to use boards and!or handouts that illustrate some of the assessment's critical assumptions, calculations,

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and findings, These materials should include graphics (i.e., bar and pie charts) that add vitality to and en­hance the understanding of the presentation (see chapter 2 for further details).

Another suggestion is to anticipate common ques­tions and address underlying concerns in the body of the presentation. To illustrate, when a fiscal impact re­port shows that attached housing yields a surplus, at least one member of the audience is likely to ask, "How can that occur? Don't such units cost less than detached homes?" Rather than waiting for the query, the analyst should include an appropriate explana­tion when such a fiscal impact finding is first pre­sented. This explanation would point out that attached housing is often a good ratable because it in­troduces relatively small households with rew school­age children. As such, attached units generate relatively modest serVice costs. Another audience member is likely to ask, "How can an expensive de­tached unit yield a deficit?" (The explanation is the converse of the one just given for attached units.) Similarly, the basis of the demographic multipliers and the reliability of the multipliers over time (see Ap­pendiX II) are often the subject of still more questions.

In sum, thorough preparation is needed to ensure lhe effective public presentation of a cost-revenue study. The material is technical, and the public forum is often adversarial and controversial. The delivery of an accurate yet convincing presentation requires care­ful treading through a minefield of questions and challenges.

Future Directions This chapter began with a discussion of how fiscal

impact analysis has evolved over the past half-cen­tury and will continue to evolve during the 1990s. The follOWing changes are anticipated with respect to applications, data, and teChniques.

Today, fiscal impact analysis is most commonly com­missioned by a developer to study an individoal project. In the future, the focus of the analysis will expand to an areawide level that encompasses several developments and overall land uses. (Such change parallels the shift in EIS evaluations frum project-specific to regional.) In­creasingly, the public sector-agencies that prepare mas­ter plans, capital facilities projections, impact fee schedules, staffing need projections, and the like-will undertake fiscal inlpact assessments.

The mid- and late 1990s will also see improve­ments in data. Traditional fields of information such as demographic multipliers will be refined, AppendiX II of this handbook, for example, uses PUMS and AHS data. New types of multipliers will also be devel­oped. For instance, interest is growing in the infra­structure consequences of growth. Accordingly, just as demographic cuunts are now associated with differ­ent type and size housing units, "counts" of average

water use, sewage generation, road use, and park and library facility needs will, in the future, be attributed to different categories of incoming growth. These "multipliers" will provide a more precise measure of the financial impacts of growth, specifically its capital improvement needs.

The development of infrastructure profiles has also been sparked by the growing interest in impact fees, As practiced today, fiscal impact analysis and impact fee determination are distinct fields. Fiscal impact analysis compares all development-induced costs­both operahng and capital-to all development-in­duced revenues, Impact fee determination focuses only on capital costs and credits a share of revenues against the development-induced infrastructure ex­penditures. Further, fiscal impact analysis is typically used exclusively as an evaluation technique, but im­pact fees go beyond planning considerations to a charging mechanism.

Given the relationship between fiscal impact and impact fee analysis as it exists today, the question is whether such a differentiation is appropriate. If the raison d'etre of the impact fee is that"growth should pay its way," then the findings of the broader fiscal impact equation are germane to the impact fee calcula­tion. Some jurisdictions are already beginning to inte­grate the two fields of analysis, and the future will witness greater overlap (see chapter 10 for a discus­sion on strategies for integration).

The coming decade will also see changes in the tech­nique of fiscal impact analysis. The per capito approach will slill dominate but will incorporate the best features of the other methods. The per capita technique, echoing the case study approach, will increasingly build in sensi­tivity to deficient and surplus service capacity condi­tions and will adjust development-induced service costs accordingly. The per capita technique will also begin to incorporate the multiyear, interactive study of the econometric method-a proce" facilitated by the grow­ing use of the desktop computer.

A further modification in the per capita technique involves increased application of comparable city or community refinement. Heref the fiscal experience of jurisdictions as they change in size and direction of growth (e.g., gaining or losing population) is incorpo­rated into the analysis as, for instance, in the specifica­tion of per capita costs. The experience of comparable commwlities offers important inSight into future fis­cal changes and the impact of growth.

Finally, the discipline of fiscal impact analysis will have to confront the issue of reliabillty. The field to date does not test its results; the projected impacts of growth undprgo no evaluation after development to measure the actual costs incurred and revenues gener­ated. While such a study is inherently technically diffi­cult, the field of fiscal impact analysis will remain vulnerable to charges that its methods have not been empirically verified-at least until retrospective analy­sis becomes part of the process.

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