:h Division Report #6
B3^
127
H >nomic Impacts of Arts
nd Cultural Institutions:
'A Model for Assessment and
tga Case Study in Baltimore
National Endowment
for the Arts
November 1977
LIBRARY
\ NATIONAL
ENLX)WMENT
FOR THE
ARTS
A Report by David Cwi and Katherine Lyall, The Center for Metropolitan Planning and Research, The Johns Hopkins University, October 1977
Digitized by the Internet Archive
in 2012 with funding from
Boston Library Consortium Member Libraries
http://archive.org/details/economicimpactsoOOcwid
PREFACE
In February 1976, the Research Division released a program
solicitation requesting proposals for a study of the economic
impacts of arts activities and cultural institutions on their
communities. The decision to undertake this project was
based on recognition of the growing need for information that
would explain the relationship between arts and cultural
activities and the economic environment of the communities
in which these activities take place.
The research community showed keen interest in the project
by responding with 42 proposals, many of them meritorious.
Though the evaluation group recommended that five of the pro-
posals be funded, resources permitted going ahead with only one.
The proposal submitted by the Center for Metropolitan
Planning and Research, The Johns Hopkins University, has led to
the development of a general purpose model that may be used for
the analysis of the economic effects of arts and cultural in-
stitutions in many communities. The model is made up of 30
equations which may be modified as special community character-
istics require. One of the features of the model is that the
equations treat the individual effects separately, so that
modifications can be made with clear understanding of their
impacts.
This report includes both the model and a case study appli-
cation of the model to eight institutions in Baltimore. The Arts
Endowment recognizes that other methods for the evaluation of
economic effects are possible and may be valid. The experience
of selecting the proposal from The Johns Hopkins University from
many others submitted, confirms the possibility that other
satisfactory approaches may be developed for this purpose.
However, we believe that the model presented in this report can
be adapted to a variety of settings; will take account of a wide
range of local governments, as well as various social, insti-
tutional and economic conditions; and may be considered suitable
for general application.
LIBRARY , ■ ■ ■
■• •■ ■ ■ A Research Division
NATIONAL1 National Endowment for the Arts
ENDOWMENT] °Ct°ber 1977
FOR THE
ARTS
INTRODUCTION
The economic impact model uses 30 equations to determine
a variety of direct and secondary effects on business,
government, and individuals. It was developed to meet
several objectives: (1) utilize data generally available
from the internal records of arts institutions and from
local, state, or federal documents (as applied to Baltimore,
the model also required audience and employee surveys) ; (2)
be used and understood by non-economists; (3) assess economic
effects with as much accuracy as available data allows; and
(4) identify negative as well as positive effects.
Section I briefly describes the general structure of
the 30 equations comprising the model, reviews the ways in
which this report differs from other economic impact studies,
and cites important caveats regarding the use and abuse of
economic impact studies. Section II provides an overview of
the Baltimore economy and its arts community. Section III
summarizes results of the quantitative calculations for
Baltimore and discusses the role of the arts in economic
development and executive recruitment. Section IV provides
concluding policy observations. Finally, Section V presents
a detailed User Manual explaining the model and its application.
The several appendices are important to an understanding of
the assumptions and methods of the Baltimore case study and
for the application of the model in other locations.
In testing the model, we have had the indispensable
assistance of Thomas Freudenheim, Director, and Ron Goff,
Assistant Director, the Baltimore Museum of Art; Peter
Lawrence, Managing Director, the Morris A. Mechanic Theatre;
Ackneil Muldrow, Treasurer, and Camilla Sherrard, Chair of
the Board, the Arena Players Theatre; Joseph Patterson,
Business Manager, and Mark Gallagher, Center Stage Theatre;
Richard Randall, Director, Edward McCracken, Administrative
Officer, and Mary Cooney, Fiscal Secretary, the Walters Art
Gallery; Robert Collinge, Director, and Josh Miller of the
Baltimore Opera Company; Joseph Leavitt, General Manager,
and Winifred Walker, Fiscal Officer, the Baltimore Symphony
Orchestra; and Joseph Cerrone, Director, and Lynn Summerell,
Associate Director, the Maryland Ballet. These individuals
provided needed data from institutional internal records as
well as information on their institutions' internal accounting
practices which saved us from many errors. Their cooperation
was also valuable in permitting us to survey their audiences
and employees for other information vital to the computation
of the model.
Teresa Moore assisted with the programming and retrieval
of the computerized survey data. Catherine Ingraham collected
data and made many of the computations. Louie Fringer typed
the manuscript. Sally Feingold managed the audience survey
field work.
David Cwi
Katharine Lyall
ii
TABLE OF CONTENTS
Page
STRUCTURE OF THE MODEL, ITS USE AND ABUSE 1
THE BALTIMORE ECONOMY AND ITS ARTS COMMUNITY:
AN OVERVIEW 9
SUMMARY OF INSTITUTION-RELATED ECONOMIC EFFECTS
ON THE BALTIMORE METROPOLITAN AREA 13
Direct Impact of the Eight Arts Institutions
on the Business Sector of the Baltimore SMSA 13
Spending by the Eight Institutions 13
Employee Residence and Spending Patterns 13
Audience Residence and Expenditures 14
Spending by Out-of-Region Audiences 14
Spending by Guest Artists 15
Secondary and Negative Impacts on the Business
Sector 15
Negative Effects on Business Volume 17
Summary of Business Effects 17
Impacts on Local Government 17
Impacts on Individuals 21
The Arts and Economic Development 21
Industrial Location 22
Executive Recruitment 23
CONCLUDING POLICY OBSERVATIONS 24
USER MANUAL 30
Assumptions and Other Underlying
Considerations 30
Direct Impacts on the Local Economy 33
in
CONTENTS (continued)
Page
Secondary Impacts
Impacts on Government
Costs to Local Government
Impacts on Individuals
Appendices
APPENDIX A: Guide to Model and Data Sources
APPENDIX B:
APPENDIX C
APPENDIX D
APPENDIX E
APPENDIX F
Multipliers and Secondary
Spending Effects
The Employee Survey
The Audience Survey
Total Full-Time Employees and
Full-Time Equivalents
Adaptations of the Model for
Multi-Institutions and Multi-
Jurisdictions
40
49
58
65
68
79
81
84
86
88
IV
INDEX TO TABLES AND FIGURES
Page
T-l A Model to Estimate the Economic Impact of the Arts 5
T-2 List of Equations 6
F-l The Baltimore Metropolitan Area 10
T-3 Eight Baltimore Arts Institutions: Percentage
Audience from Outside the Region 16
T-4 Direct Tax Payments to Local Government by Eight
Baltimore Arts Institutions 18
T-5 Alternative Estimates of Foregone Property Taxes on
Real Estate Property Owned or Occupied by the Eight
Baltimore Arts Institutions, 1976 20
,T-6 Summary of Economic Effects, 1976 25
T-7 Summary Data for Eight Arts Organizations in
Baltimore SMSA, Fiscal Year 1976 27
T-8 Government Revenues of Eight Arts Institutions,
Baltimore SMSA, 1976 28
T-9 Multiplier Values for Baltimore Arts Study 80
v
STRUCTURE OF THE MODEL, ITS USE AND ABUSE
The primary purpose of artistic and cultural institutions
is not to create jobs, generate business for local entrepre-
neurs, or boost sales of durable goods. These functions can
be better performed by a variety of other institutions in
the public and private sectors. Nonetheless, arts institutions,
intentionally or not, generate a number of economic effects
on the local community.
The model we used to identify and estimate these effects
consists of 30 linear equations* which we categorized into
three groups: The letters B, G, and I designate these
groups of equations which identify, respectively, effects on
local business volume and expenditures, effects on government
income and expenditures, and effects on personal income,
jobs, and expenditures. Tables 1 and 2 schematically present
the relationships among these equations.
Within these groups certain equations can be solved
only by first solving a series of other equations which
provide needed values. Thus some equations are followed by
a sub-set (or even sub-sub-set) which are indicated with
decimal points. For instance, the equation Gl requires,
among others, the solution of G-l.l and this equation requires,
in turn, G-l.1.1 and G-l.l. 2. While the numeration of these
equations may cause the layman to assume that they are
difficult to solve, in fact the mathematics are quite simple.
Each set of equations is aimed at describing some
particular economic effect. For example, in the business
sector — the "B" equations — arts institutions may directly
affect local business volume by purchasing goods and services
from local sources. Those related to the institution —
employees, guest artists, and audiences — also spend locally.
Certain equations estimate the total value of these institution-
related direct expenditures during the fiscal year examined.
The firms and individuals benefitting from institution-
related direct expenditures will, in turn, spend a portion
of this income locally. For this reason, other equations
estimate the total secondary business volume that eventually
results from institution-related direct expenditures, for
example, the expansion of the local credit base eventually
resulting from institution-related direct expenditures.
The model then, also estimates economic effects involving
local government: the "G" equations. To begin with, businesses
annually pay property tax on their property, equipment, and,
in some communities, their inventory. Also, inasmuch as
*This model has been adapted from J. Caffrey and H.
Isaacs, Estimating the Impact of a College or University on the Local
Economy (Washington, D.C.: American Council on Education, 1971).
-1-
businesses have had to invest in plant, equipment, and
inventory in part because of direct expenditures related
to arts institutions, a portion of local business property
tax revenues is attributable to the institutions under study
and can be estimated by certain equations. In addition, the
institutions themselves, as well as their employees, guest
artists, and audiences, may directly pay a local sales tax
and their employees may pay local income or real estate
taxes. These direct tax payments can also be estimated by
our equations.
Local government may also receive revenues from state or
federal sources. As is typically the case when localities
receive state aid for education, these revenues may be provided
on a per capita basis so that some equations estimate state and
federal aid attributable to the examined institutions. Con-
versely, arts institutions and their employees require govern-
mental services, and public funds which must be spent to
provide these services. An estimate can be made for a given
fiscal year of the local governmental operating costs required
to service the institutions and their employees. Further,
government may forego property tax and other revenues due to
an institution's tax-exempt status. The equations in the model
estimate these foregone tax revenues.
The third category, the effect on individuals, is the "I"
series. Institution-related direct expenditures, together
with institution-related local governmental expenditures, re-
present a demand for local goods and services. To meet this
demand, local businesses not only invest in property and inven-
tory, but also add personnel or pay overtime, thereby increasing
payrolls. The model provides equations which estimate these
secondary effects on individuals.
The utility of this study and model lies less in its
precision than in its clarity and scope. We made a concerted
effort to go beyond past studies and acquire needed data
through the use of institutional internal accounts, audience
and employee surveys, and locally available data. As a general
rule, when we were required by our methods or the lack of data
to make an assumption, we opted for the most reasonable or con-
servative, that is, we adopted the assumption which attributed
the highest negative economic effect or least positive effect
to the examined arts institutions.
Consequently, this study differs from previous efforts in
several respects. Not only has no other study been as inclu-
sive, but, to the best of our knowledge, prior economic impact
studies of arts and cultural institutions have not:
* examined employee and guest artist spending as well
as audience and institutional expenditures;
-2-
* identified the toal of institution-related spending
made with local firms and not simply assumed that all
spending was local;
* identified factors affecting an institution's economic
impact on a community and established that institutions
can have different impacts;
* tried to account for the negative effects on local
government and business of a community's arts and
cultural activities to arrive at a picture of net
cost, if any;
* examined critically the common premise that the arts
are important to industrial development and executive
recruitment.
In particular, this model's strengths are as follows:
* it can be adapted to a variety of settings and take
account of local governmental, social, institutional
and economic conditions;
it utilizes data generally available from an insti-
tution's internal records or from local, state, or
federal documents;
* it focuses not only on the institution but also its
employees, guest artists and audience;
* it can be used and understood by individuals who have
no training in economics and the social sciences;
* it can be used to assess the effects of one institution
or many;
it uses as inputs a variety of policy-relevant data
respecting an institution and its community;
it identifies negative as well as positive effects:
We are aware that some readers may draw unwarranted conclusions
from this study. Therefore, we wish to caution the reader on
four points.
(1) It cannot be inferred from this or any other cur-
rently available "economic impact" study that support
for the arts, as an economic development strategy, is
to be preferred over other alternative uses of public
or private dollars;
(2) It cannot be inferred that the economic effects
identified would not have occurred had the examined
institutions not existed. For example, arts institutions
-3-
vie for leisure-time dollars that might have been spent
in the community even if they were not spent on the arts.
Conversely, much of the interest in artistic and cultural
activities is sui generis. In the case of Baltimore, some
of the audience might have travelled to Washington or other
cities to satisfy their desire for the arts. In short, if
specific institutions had not existed, we simply do not know
whether others would have, or, in any case, the extent to
which the economic effects noted would not have occurred.
(3) It cannot be inferred that the eight institutions
examined in this study exhaust the effect of the arts on
the Baltimore economy. The model utilized is intended
to assess the economic effects of institutions. However,
while the eight institutions studied include the region's
largest arts institutions, these organizations constitute
no more than 10 percent of the total arts employment in the
Baltimore metropolitan area.*
Further, it can be assumed that arts institutions and
individual artists and craftsmen residing outside the
Baltimore metropolitan area purchase arts-related goods
and services from firms in the Baltimore region. These
expenditures have not been accounted for. Finally, for
those interested in artistic and cultural activities, the
availability of the arts plays a role in determining the
attractiveness of a community as a place in which to work
and live. While it is easy to overstate the role of the
arts in decisions by individuals to remain, invest, or
relocate to a community, no attempt has been made to
assess net dollar benefits to the community due to the
preferences of individuals for the arts.
(4) It cannot be inferred that economic effects are or
ought to be important determinants of public policy toward
the arts. We conclude this report with policy observations
which include a caution against the inappropriate use of
"return on investment" criteria in the evaluation of
alternative public policies toward the arts.
*For example, census data for 1970 show a total of
5805 Writers, Artists, and Entertainers, in the Baltimore
SMSA. Total full-time equivalent employment of the eight
arts institutions was 404 in 1976, or about 7% of the reported
1970 total for the region. These represent actors, architects,
authors, dancers, designers, musicians and composers, painters
and sculptors, photographers, radio and TV announcers, and
a miscellaneous category. They exclude individuals employed
in art galleries, and other arts-related positions.
-4-
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Table 2
List of Equations
Economic Impacts on Local Business
Direct Impacts
B-l Total institution-related local expenditures (E)
B-l.l Local Institutional Expenditures for Goods and
Services (E.j )
B-l. 2 Direct Expenditures in the Local Community by
Institutional Employees (Ee)
B-l. 3 Local Expenditures by Guest Artists (E )
B-l. 4 Local Expenditures by Local Audience and Patrons (Ea)
B-l. 5 Local Ancillary Expenditures by Non-Local Audience
and Other Users (Ev)
Induced Impacts
B-2 Purchases by Local Businesses from Local Sources
in Support of Institution-Related Expenditures
in the Local Economy (B )
B-3 Local Business Volume Stimulated by Institution-
Related Income Spent by Local Business
Employees (BV)
B-4 Value of Local Business Property Committed to
Institution-Related Business (BI)
B-4.1 Value of Local Business Real Property Committed to
Support Institution-Related Business (RP)
B-4. 2 Value of Business Inventory Committed to Support
Institution-Related Direct and Secondary Business
Volume (Inv)
B-5 Expansion of the Local Credit Base Attributable to
Institution-Related Deposits (CE)
B-6 Local Business Volume Unrealized Due to Institution-
Related Enterprises (NBV)
Economic Impacts on Local Government
G-l Total Institution-Related Local Tax Revenues (GR)
G-l.l Local Real Estate Taxes Paid by the Institution,
Its Employees, and Local Businesses Serving Both
(RETX)
G-l. 1.1 Local Real Estate Taxes Paid by Institutional
Employees (RETe)
G-l. 1.2 Real Estate Taxes Paid by Local Businesses on
Real Property Committed to Support Institution-
Related Business (RETb)
G-l. 2 Local Sales Tax Revenues Resulting From Institution-
Related Direct Expenditures (ST)
G-l. 3 Local Income Tax Revenues Paid by Institutional
Employees (YT)
G-l. 4 State Per Capita Aid to Local Government Attributable
to Institutional Employees (SA)
-6-
Table 2 (Continued)
G-2 Operating Cost of Government-Provided Municipal
and Public School Services Attributable to the
Institution and its Employees (OC)
G-2.1 Local Governmental Operating Costs (Excluding
Schools)
G-2. 2 Public School Operating Costs Attributable to Insti-
tutional Employees (PSOC)
G-3 Value of Local Governmental Property Committed to
Support Services to Employees (GP)
G-4 Foregone Real Estate Taxes Due to the Institution's
Tax-Exempt Status (FTX)
G-5 Value of Local Governmental Services Self-Provided
by the Institution (SSVS)
Economic Impacts on Individuals
I-I Number of Local Jobs Resulting from Institution-
Related Direct Effects on the Local Business
Sector and Government (J)
1-2 Total Local Personal Income Due to Institution-
Related Direct Effects on the Local Business
Sector and Government (PY)
1-3 Durable Goods Purchases Attributable to Institution-
Related Increases in Total Personal Income (DG)
-7-
-8-
THE BALTIMORE ECONOMY AND ITS ARTS COMMUNITY: AN OVERVIEW
A quick overview of both the economy and the arts community
of the Baltimore metropolitan area will put into perspective the
impact of the eight arts institutions examined in this study.
As indicated by Figure 1, the Baltimore metropolitan area
consists of Baltimore City and the five surrounding counties.
While Baltimore City ranks seventh in population nationally,
with some 900,000 residents, the metropolitan area, with a
population of roughly 2.2 million persons, ranks thirteenth
among SMSA's. (As defined by governmental agencies for the
collection and aggregation of data, Baltimore City and the five
surrounding counties constitute a Standard Metropolitan Sta-
tistical Area, or SMSA. )
Major employers in the Baltimore SMSA are concentrated in
three broad sectors which together constitute a remarkably well-
balanced economic base: the Port of Baltimore and related
transportation activities; diversified manufacturing; and business,
institutional, and governmental services.
As with other major east coast cities, Baltimore traces its
economic origin to its suitability as a port. Currently, the
port is ranked fourth nationally in terms of combined import
and export tonnage and is the second leading container port on
the east coast. A recent study has estimated that 26,000 jobs
are directly related to port activities, while transportation
and transshipment expenditures associated with the port activity
pour over $400 million annually into the Maryland economy. *
As is the case nationally, manufacturing, while significant,
is of declining importance in Baltimore's total economy. By far
the single most important individual manufacturing employer in
the Baltimore SMSA is the vast Bethlehem Steel facility at
Sparrows Point, claimed to be the largest tidewater steel manu-
facturing complex in the free world. Some 25,000 to 30,000 people
work at Sparrows Point both in the steel mill and in the company's
shipbuilding operation. The size of the Bethlehem Steel work
force accounts for as much as one-sixth of the total manufacturing
employment in the Baltimore area; roughly half of these employees
live in the city proper.
Other particularly large manufacturing firms include the
General Motors' Chevrolet assembly plant (5,000 employees),
Westinghouse (13,000 employees), and Western Electric (8,000
employees) . In 1950 the garment industry employed as many as
20,000 people in the Baltimore SMSA. Today there are only about
12,000 jobs in this sector, and many of these seem threatened by
the nationwide decline of this industry.
♦University of Maryland, The Economic Impact of the Port
of Baltimore on Maryland (April, 1975).
-9-
Figure 1 The Baltimore Metropolitan Area
-10-
Maturation and expansion of the metropolitan economy
has produced a surge of jobs in the "services" sectors,
accompanied by a very substantial rise in government and
institutional employment. The latter resulted in 70,000 new
jobs between 1964 and 1970, or about one-half of the total
regional employment growth in that period. The growth of
federal and state government and medical and educational
institutions has been particularly significant. Currently,
there are some 70 firms in the Baltimore metropolitan area
with 1,000 or more employees, and there are many times that
number of smaller firms. All together these firms, large
and small, employ a total labor force of some 900,000 non-
agricultural workers, both full and part-time.
According to the Washington Post, Baltimore City has a
"growing reputation as a vital, diverse, culturally rich, and
architecturally exciting city." The city has been an innovator
and specialist in "urban homesteading" and other strategies to
encourage the re-use and rehabilitation of old buildings and
homes. Also, it has mounted one of the country's most ambitious
renewal programs. It includes: the Charles Center office-
shop-theatre-hotel complex; the transformation of Baltimore's in-
town port area into one of the nation's most spectacular urban
waterfronts; Coldspring, a new town-in-town designed by Moishe
Safdi; and recent plans for a major renewal of the downtown retail
district. In November of 1976, the Department of Housing and
Urban Development recognized Baltimore's efforts with an unpre-
cedented sixth design award in seven years.
Baltimore City is unable, under terms of the state consti-
tution, to annex its surrounding suburbs, with the result that
it has increasingly become the locus for the region's poor and
others with high service needs. The efforts highlighted above
reflect a twenty year strategy to create a culturally exciting,
physically attractive, and economically viable city in which
the SMSA's middle class will want to work, shop, and live.
The metropolitan area as a whole is rich in artistic
and cultural resources. The region's amateur and professional
arts activity is extensive. For example, in fiscal 1976,
the Maryland State Arts Council made grants to some sixty
organizations in the Baltimore SMSA. Within the SMSA are
some fifteen institutions of higher learning, including six
community colleges. There are several non-professional
theatre and choral groups and at least six dinner theatres.
Also there are a number of fully professional institutions,
which are of cultural, if not strictly speaking artistic,
importance, such as the Maryland Historical Society, the
Baltimore and Ohio Transportation Museum, the Maryland
Academy of Sciences, the Baltimore City Zoo, and numerous
historic sites. In addition, the region is fortunate to
have the Peabody Institute (a conservatory of music) and the
Maryland Institute of Art.
-11-
The eight institutions examined by this study include
the core of Baltimore's fully professional arts resources in
repertory theatre, opera, symphony, dance, and the visual
arts. They are: Baltimore Opera; Walters Arts Gallery;
Baltimore Symphony; Morris A. Mechanic Theatre; Baltimore
City Ballet; Baltimore Museum of Art; Center Stage; and
Arena Players. Together, these eight institutions received
more than $2.3 million in federal, state, and local support
in fiscal year 1976.
-12-
SUMMARY OF INSTITUTION-RELATED ECONOMIC EFFECTS ON
THE BALTIMORE METROPOLITAN AREA
Direct Impact of the Eight Arts Institutions on the
Business Sector of the Baltimore SMSA
This section summarizes and discusses the major findings
resulting from an application of the model to eight arts
institutions in the Baltimore metropolitan area. While the
identified effects are not large compared to many industries
in the metropolitan area, they indicate that significant
reductions in the budgets of these institutions would have
perceptible effects on jobs, incomes, and regional business
volume.
Throughout this report, terms such as "local," "the
Baltimore metropolitan area," and "the Baltimore region" are
used interchangeably to identify the Baltimore Standard
Metropolitan Statistical Area (SMSA) , which includes Baltimore
City and Baltimore, Anne Arundel, Carroll, Harford, and Howard
counties.
In testing the model, we treated each institution separ-
ately as well as identifying, when meaningful, each institu-
tion's differential effect among the six local governmental
units that comprise the Baltimore SMSA. Appendix F is devoted
to a review of the complications associated with multi-juris-
dictional and multi-institutional analysis. In this report,
we have aggregated the effects of the eight institutions, while
reporting them on a total SMSA basis. All figures are for
fiscal 1976 unless otherwise noted.
Spending by the 8 Institutions
In fiscal 1976, the eight institutions spent $5.3 million
for goods and services, of which 47%, $2.4 million, represents
purchases from suppliers and individuals in the Baltimore region
Another $4 million was spent for wages and salaries. Spending
by employees, audiences, and guest artists is enumerated below.
Employee Residence and Spending Patterns
One striking feature is the extent to which the employees
of the eight institutions live in the city. At least 80% of
the institutions' professional and administrative staff members
live in Baltimore City, with the remainder concentrated
primarily in Baltimore County. Slightly less than half (47%)
of all these employees are homeowners in the metropolitan area.
At the same time, a relatively small number (approximately 50)
-13-
of children of employees attend public schools in the region.
(We are unable to determine from our survey information
whether this is because employee families have fewer children
of school age than the population at large, or whether arts
employees use the private school system more extensively. )
Employees reported that of $6.7 million of disposable family
income (net income after deduction of taxes and social
security contributions), two-thirds ($4.4 million) was spent
in the metropolitan area. This figure represents one method
of handling family income in circumstances, such as the
Baltimore case, where the arts institution provides the bulk
of household income for most employee households. For a
discussion of alternative cases, see Section V.
Audience Residence and Expenditures
Total local paid attendance at all eight institutions
during the 1976 season was approximately 718,000, with about
6% of the patrons coming from outside the metropolitan
region. The percentage of out-of-region audience determined
from our audience survey varied substantially among the
eight institutions, ranging from 2% for the Walters Art
Gallery and Center Stage Theatre to 14% for the Baltimore
Museum of Art.
Local audiences spent, in addition to the ticket price,
sums ranging from $3.85 to $15.65 per party per visit for
items such as meals, transportation, parking and babysitters.
The amount varied depending on the institution and the type
of performance. As might be expected, attendance at the
museums entailed the smallest auxiliary expenditures, while
attendance at the Symphony and the Mechanic Theatre involved
the highest average supplementary expenditures. (For a dis-
cussion of the technical problems associated with determining
auxiliary spending patterns, see Section V. Because many
persons attend performances and cultural activities in
couples or groups, we formulated our survey questionnaire to
elicit average expenditures by party size.) All together,
local audiences in fiscal year 1976 spent an estimated
$2,624,601 in addition to ticket and admission fees.
Spending by Out-of-Region Audiences
In fiscal 1976, some 43,000 visitors from outside the
Baltimore region came specifically to use the eight arts
institutions. These visitors contributed roughly half as
much as resident audiences to local area spending despite
the fact that they comprise only 2% to 14% of total atten-
dance depending on the institution. Out-of-region patrons
exert a disproportionate economic influence compared to
local audiences, both because they spend more per visit and
because a larger share of these visitors (7.5% to 63% depending
on the institution) spend money at all.
-14-
Average per diem expenditures reported by out -of region
parties ranged by institution from $11.80 to $48.60, yielding
a total expenditure of $1,891,392 attributable to the drawing
power of these institutions in attracting out-of-town visitors.
It is important to remember that this calculation reflects
expenditures only for those respondents who indicated that
they came to Baltimore specifically to visit the arts institu-
tion under study. This percentage ranged from 24% of out -of -
region respondents at the Walters to 76% of out-of -region
respondents at the Opera (Table 3) . It should be noted that
these percentages reflect the presence nearby of the Washington
metropolitan area. Audience and patrons from Washington, D.C.,
were counted in our survey among the out -of -region respondents
because they are not technically in the Baltimore SMSA.
Spending By Guest Artists
Each year, arts institutions contract with designers,
directors, conductors, choreographers, featured soloists,
and others. These non-resident "guest artists" make a modest
contribution to local spending. The eight examined institu-
tions reported a total of 1,913 guest-artist days spend in
the Baltimore region at per diem rates ranging from $30 to
$40 for a total estimated fiscal 1976 local expenditure of
$68,247. Our computation of guest artist spending is un-
doubtedly conservative, since no attempt has been made to
include members of family or entourages in the total estimate.
Secondary and Negative Impacts
On the Business Sector
These direct expenditures by the institutions and their
staffs, audiences, guest artists, and out-of -region visitors
do not capture the full effect of such activities on the
economic base of the region. Such direct expenditures generate
second -order effects, as local businesses make purchases of
their own to support the institutions ' local demand for goods
and services. Eventually, Baltimore metropolitan region
businesses purchase an estimated $9.1 million in local business
volume. In addition, these local firms have invested in $5.7
million worth of inventory, equipment, and real estate in order
to service institution-related business. This represents the
fiscal 1976 value of these assets and not expenditures made in
1976, although a portion of these assets may have been acquired
in that year. Expenditures were not necessarily made with
local firms.
A portion of business and personal incomes generated by
institutional activities are deposited with local banks. This
results in an expansion of the local credit base. We estimate
that eventually the regional credit base is augmented
-15-
TABLE 3
Eight Baltimore Arts Institutions: Percentage
Audience From Outside the Region
% Audience From
Out-of -Region
% of Out-of-Region Audience
Who Came Specifically to
Attend Institution
Baltimore Opera
Walters Art Gallery
Baltimore Symphony
Morris A. Mechanic Theatre
Baltimore City Ballet
Baltimore Museum of Art
Center Stage
Arena Players
5%
2
3
6
5
14
2
NR
76
24
31
58
45
34
36
NR
NR = None reported during survey period
-16-
by some $3,106,000 as a direct consequence of fiscal 1976
institution-related deposits. The bulk of this effect
occurs through the deposits of the institutions themselves.
Negative Effects on Business Volume
To the extent that the institutions operate enterprises or
provide services in competition with local businesses, their
receipts from these activities should be recognized as a
substitution for other private business earnings in the community.
In some instances, however, it may be reasonable to think
that the subsidiary activities of arts organizations are
net additions to total business volume in the region, perhaps
competing with activities outside the area but not reducing
sales within the region. After examining the auxiliary enter-
prises operated by the eight institutions in our Baltimore sample,
we decided not to count any of the $2 80,820 in income from these
subsidiary enterprises as a net loss to other private sector
vendors. The bulk of this income was derived from gallery
and gift shop sales and from concessioned restaurant facilities;
profits from concessioned restaurant sales go to private business
anyway. In the case of gallery sales, we assumed that sales
represent items that were largely unobtainable elsewhere, and
that, in any case, museums stimulate other private sector
purchases through a heightened interest in the purchase of art.
No data is available on which to make an evaluation or assumption
of the transfers from other recreational, entertainment, or
educational areas that may be represented by all or a portion
of the ticket and related expenditures associated with attendance
at arts events.
Summary of Business Effects
On the basis of these estimates, we present a general
summary of the effects of the eight examined institutions on the
Baltimore region business sector: institution-related activi-
ties in 1976 generated about $29.6 million of direct and indirect
business volume in the region; they accounted for about $5.7 million
of business real property, equipment, and inventories; and
they generated about $3 million of additional local bank credit
in the region. While these figures are not large compared to
many firms in the private sector, they indicate that signifi-
cant reductions in the budgets of these institutions would
have perceptible effects on jobs, incomes, and business volume
in the region.
Impacts on Local Government
Tax-exempt arts institutions have an effect on the fiscal
status of local governments. We outline here fiscal 1976 tax
payments to local government attributable to the eight insti-
tutions in our sample, and we assess their cost to local govern-
ment. Costs are assessed in terms of foregone property taxes,
-17-
unreimbursed municipal services, and the operating costs of
public schools attributable to the institutions, their per-
sonnel, and their children. These items clearly do not exhaust
all effects on local government. They reflect only selected
impacts which may be traced directly to the institutions and
their employees.
Although all eight institutions operate under tax-exempt
status, they are nonetheless responsible for $151,767 in tax
payments to the six local governments in the SMSA. The sources
of these revenues were property taxes, locally retained sales
taxes, local income taxes, and population-based state aid
to localities (see Table 4). The figure of $151,767 includes
only tax payments related to direct, not secondary, expenditures.
Also, it excludes a variety of user fees paid by employees.
TABLE 4
Direct Tax Payments to Local Government by
Eight Baltimore Arts Institutions
Real estate taxes paid to jurisdictions in the
Baltimore SMSA by the arts institutions, their
employees, and business property devoted to
servicing the institutions (equation Gl.l) $99,537
Locally retained sales on institution-
related business volume* (equation G1.2) 5,062
Local income tax revenues attributable to
institutional and other business employees
(equation G1.3) 27,558
State aid to local public schools attributable
to children of institution-related families
(equation G1.4) 19,610
TOTAL $151,767
The institutions also provided municipal-type services
for themselves, including security services and trash collection,
with an annual value of about $33,172.
On the cost side of the ledger, local governments provide
services for the employees and households of the eight institu-
tions valued at more than $678,612. Of this, only $30,429
*In many areas, sales taxes are imposed by state government
but collected by local government for payment to the state. We
count here only that portion of sales tax collections actually re-
tained by the six local jurisdictions in the Baltimore metropolitan
region.
-18
represents the cost of providing public school education for
the children of arts employees.
Another cost to local government is represented by the
value of governmental property necessary to provide services
to the institutions and their employee households. The current
value of local government property so committed is estimated at
$274,138.
This may not exhaust total costs to government since insti-
tutional programs may benefit from donated government services
such as increased police protection and free facilities or
equipment.
Finally, we estimate that the value of foregone taxes on
tax-exempt property owned or occupied by the eight Baltimore
arts institutions is no more than $100,000 and is more likely
near $60,000. This range reflects the two alternative assumptions
cited in Table 5. None of the examined institutions pays
property taxes. Either they own tax exempt property or they
rent their facilities. Certain owners from whom they rent do
pay property taxes while others are tax exempt. Three of the
institutions occupy land and/or buildings owned by the City of
Baltimore. Foregone property taxes consist, then, of insti-
tution owned or rented tax exempt property together with pro-
perty owned by the City of Baltimore. For the purposes of this
case study, we will assume that city owned property and buildings
would have remained in public use in the absence of the insti-
tutions, that is, that $59,765 more nearly approximates the
real value of the subsidy provided by the city through property
tax exemptions.
It should also be noted that the alternative estimates
in Table 5 reflect only foregone tax revenues on property
used by the arts institutions themselves and do not attempt
to reflect any spillover effects that these institutions may
have on the value of surrounding (taxable) properties and
neighborhood cohesion. These spillovers may be both positive
and negative. For example, theatres stand empty much of the
time, inviting loitering and vandalism, and some institutions
create neighborhood parking problems which impose uncompensated
costs on local residents and businesses. Attempts to estimate
positive neighborhood effects must be matched by equal attempts
to measure the negative effects.
-19-
I
TABLE 5
Alternative Estimates of Foregone Property Taxes on _
Real Property Owned or Occupied by the Eight Baltimore I
Arts Insitutions, 1976 ■
j
Taxable Value* Foregone Property Te
1. All currently exempt I
property (land and j
buildings) would revert
to tax yielding uses. $ 1,562,300 $ 93,738 ,
I
2. All city-owned property ■
(land and buildings)
would remain in exempt 1
uses, but other property [
would revert to taxable
uses. $ 996,080 $ 59,754 i
I
Source: Baltimore City assessment records, 1976-77.
I
* Total taxable value, which in Baltimore equals 50% of ■
market value of land and improvements (buildings) . The
foregone tax yield on this base is the Baltimore City property j
tax rate (6%) times the total assessed value. All eight
institutions are located in Baltimore City; however, had some
been located in other local jurisdictions, the foregone tax •
yield from exempt properties would have had to have been I
calculated for each property at the tax rate levied by the
jurisdiction in which it is assessed.
-20-
Impacts on Individuals
The economic impact of arts institutions on private
individuals is largely through jobs and employment opportuni-
ties. We estimate that 1175 full-time jobs in the Baltimore
area are produced by the activities of the eight arts organ-
izations in our sample; 404 of these are directly with the
institutions, and 771 are created as a consequence of institu-
tionally related business and government expenditures. Taken
together the eight institutions are roughly equivalent in
employment effects to, say, the Coca-Cola Bottling Company,
Coppin State College, Fidelity and Deposit Company of Maryland,
or the Howard Research and Development Corporation, each of
which employs between 400 and 500 persons in the metropolitan
region. The total employment impact of the eight arts organ-
izations (1175) is approximately equal to the direct employment
totals of local firms such as Maryland Cup Corporation, Maryland
General Hospital, Reads, Eastern Stainless Steel, First National
Bank of Maryland, IBM, and the Maryland Casualty Company.
The jobs created, either directly or indirectly, by the
eight institutions and their combined business transactions
serve to generate $9.7 million of personal income in the region;
$4 00,000 of this is spent for durable goods.
The Arts and Economic Development
In recent years, advocates of the arts have stressed the
importance of spinoff economic effects that are not easily
quantified. In particular, it has been claimed that the avail-
ability of artistic and cultural activities can be a decisive
factor in both industrial relocation decisions and in the
recruitment and retention of executives.* If arts and cultural
activities have an ancillary role in economic development deci-
sions, their influence would represent an important additional
consideration in the development and evaluation of public policy
toward the arts. We sought to evaluate local and national exper-
ience with respect to the impact of artistic and cultural ameni-
ties on industrial development and executive recruitment. In
doing so, however, we do not mean to imply that public policy
toward the arts ought primarily to aim at maximum economic
returns to the community.
*E.g., The Report of the Governor's Task Force on the
Arts and Humanities, The Arts; A Priority for Investment
(Commonwealth of Massachusetts, 1973); The Greater Philadel-
phia Cultural Alliance, An Introduction to the Economics
of Philadelphia's Cultural Organizations (Philadelphia,
1975); Mayor's Committee on Cultural Policy, Report (New
York, 1974); and the Washington Center for Metropolitan
Studies, The Arts in Metropolitan Washington; Some Preliminary
Data on Economics, Financing and Organization (Washington, D.C.,
1975)
-21-
Industrial Location
No hard data is available on the impact of artistic and
cultural amenities on industrial development and executive
recruitment in the Baltimore region or nationally. For this
reason, we sought the judgments of a variety of knowledgeable
individuals through unstructured interviews. We initially
contacted local officials to assess their experience. Be-
cause of the unanimity of their views, we wondered if the
Baltimore experience as seen by these local and state officials
was typical, and so we contacted others nationally.
The twenty individuals interviewed included researchers
and consultants in plant location matters (3); State of
Maryland and local governmental officials in Baltimore City
and the five surrounding counties responsible for facilitating
industrial development in the state and region (7) ; officials
of national economic development associations (2) ; represen-
tatives of chambers of commerce outside the Baltimore region
who are active in economic development (2) ; and national
consultants in executive recruitment (6).
We were struck by the unanimity of the views of these
knowledgeable individuals. We think it fair to conclude
from these interviews that the availability of artistic and
cultural activities can in certain cases be a contributing,
although rarely a decisive, factor in plant and executive
location decisions. Those interviewed distinguished the "public
relations" use of the arts from the role that the arts may
actually play in corporate decision making.
The presence of varied and high quality artistic and
cultural amenities appears to be used by those in economic
development roles as an important indicator of the general
level of a community's civility and culture. The presence of
these amenities is used to suggest that a community is
progressive, resourceful, concerned about itself, and ener-
getic. Reference to the arts is used, then, as an important
indicator of a generally favorable quality of life.
However, there was universal agreement among respon-
dents that artistic and cultural amenities by themselves are
not a determining factor in industrial location decisions.
The majority of business location decisions involve firms
in production, assembly, manufacturing, and warehouse distribu-
tion. These firms vary in their special needs but commonly
they look to ample supplies of water and electric power,
convenient site location, availability of railroad sidings,
adequacy of rail and road networks, and the like. In making
relocation decisions, firms appear to make nested choices,
first selecting suitable regions or metropolitan areas and
then evaluating individual sites with respect to such matters
-22-
as property values, tax rates, the characteristics and avail-
ability of the local labor force, wage rates, the availability
of utilities, the size of the site, road access, transpor-
tation network, the availability of financing, proximity to
raw materials and markets, and the availability of vocational
schools. In most cases, only when "all things are equal" with
respect to the business climate will firms give weight to
quality of life considerations in their decisions.
Quality of life issues appear to be more important to
firms that employ highly trained, salaried, and mobile person-
nel, typically with advanced degrees and to firms where top
management will have to relocate. Corporate and regional
headquarters, research and development firms, and government
facilities are not as dependent on traditional site location
considerations and, since they must recruit and retain skilled
and mobile personnel, place more emphasis on quality of life
issues because of the greater need for concern over employee
satisfaction. Similar considerations also hold for single-
owner firms.
Those interviewed indicated that there are many quality
of life factors perhaps more important than quality artistic and
cultural amenities. Artistic and cultural amenities are but
one element of the total community fabric that includes factors
such as recreational opportunities, schools, neighborhoods,
the cost of living, climate, efficiency and performance of
local government, the environment both man-made and natural,
the quality of health and educational facilities, and positive
social conditions. Cultural and recreational opportunities
are generally viewed as one area of concern, with firms
interested in the total mix of educational and recreational
opportunities available to an employee and his or her family.
Those interviewed generally agreed that quality education
facilities were particularly important, with research and
development firms emphasizing proximity to institutions of
higher learning. Thus, one community's advantage with re-
spect to cultural resources might be balanced out by another's
advantage in other kinds of recreational opportunities or
generally more favorable social conditions.
However, those interviewed did point out that location
decisions can hinge on "executive preference," in which case
almost anything frojKi recreation to artistic amenities to
climate could prove decisive. At the same time, no one was
aware of any instances in which location decisions hinged
on the presence of specific cultural activities or more general
cultural considerations.
Executive Recruitment
In our interviews with executive recruitment consultants
and major firms in the Baltimore metropolitan area, respon-
ds-
dents were in agreement that an increasing number of executives
emphasize quality of life considerations as much as salary and
career advancement in deciding whether to relocate in a new
position. Salary and career opportunities still predominate,
but over the last two decades there has been a change in
executive willingness to take a position simply because it
represented a promotion and increase in salary. Apparently,
it is becoming more common for executives to ask whether
their families would also benefit from a promotion or reloca-
tion. Relocation may represent a major trauma for a spouse
or children. An increase in salary may be largely eaten up
by taxes. An executive may have to sacrifice his present
life-style, for example, the ability to get in a round of
golf before dinner.
Those interviewed went on to note that quality of life
and life-style issues are very much matters of personal pre-
ference. While few want to live in a place with no cultural
ambience, this does not mean that executives who are inter-
ested in artistic and cultural amenities require them to be
"world class" or to be located in the home community. Access
to artistic and cultural amenities may be via a more major
city, or through touring events in the home community. Gener-
ally, executives were loath to relocate to cities with reputa-
tions for decay, crime, and a high cost of living. Of special
importance were such issues as "whether it's a hassle to
commute to work," education, neighborhoods, housing, recrea-
tional opportunities, the kind of people with whom the family
would be socializing. In other words, executive status would
not automatically suggest a special interest in the arts, and
arts advocates should not equate "quality of life" with quality
of artistic and cultural resources.
CONCLUDING POLICY OBSERVATIONS
Table 6 summarizes the more prominent economic effects
of the eight arts institutions on the Baltimore metropolitan
area. (Relevant equations, calculations, and data sources
are listed in Appendix A. ) Again, note that direct effects
refer to expenditures made in fiscal 1976 by the institutions
and their audiences, employees, and guest artists, while
secondary effects may not be completely realized within one
fiscal year. Also, business investment in plant and equipment
refers only to the current (fiscal 1976) values of property that
may have been purchased in other years and from non-local
sources. Finally, we repeat our caveats from Section I. In par-
ticular, while we have noted that significant reductions in the
budgets of arts institutions may be of interest to policy
makers because of the perceptible effects on jobs, incomes,
and business volume, one cannot conclude that support for the
arts, given particular economic goals such as the creation of
jobs, is more desirable than other uses of public dollars.
-24-
TABLE 6
Summary of Economic Effects , 1976
Fiscal Year 1976
Total direct expenditures of the 8 institu-
tions for goods and services $ 5,344,754
Of which purchased locally 2,405,026
Employee household disposable income 6,701,479
Of which spent locally 4,422,976
Total audience spending (other than ticket
price) 4,515,993
Of which local audiences spent 2,624,601
Of which out-of -region audiences spent 1,891,392
Spending by guest artists 68,247
Secondary business volume generated by suppliers
and their employees 18,499,454
Current value of backup inventory, equipment,
and property 5,746,743
Institutions-related tax payments to local
government 151,767
Value of local government services to institu-
tions-related employees and their households 678,612
Foregone property taxes on tax-exempt property 59,765
Total local government contributions to the 8
arts institutions 1,578,545
Number of full-time jobs in Baltimore SMSA
attributable to institutions-related activity 1,175
Personal incomes generated by institutions-
related business /volume 9,676,284
-25 -
In evaluating and contrasting the contribution of
individual institutions to the aggregate impact noted in
Table 6, we are persuaded that institutional type, for exam-
ple theatre or museum, is less useful for identifying economic
impact than structural distinctions, such as: the proportion
of non-salary expenditures made to local suppliers (an insti-
tution's ability to spend locally is largely determined by
the size and diversity of the local economy, see Appendix B) ;
the number and composition of arts employees (guest artists,
resident troupe, permanent employees) ; the proportion of
employee expenditures remaining in the community; and local
and visiting audience expenditures attributable to institu-
tions.
The interaction of these factors is idiosyncratic. For
example, in the case of Baltimore, if an arts employee resides
in Washington, D.C., his earnings and resultant secondary
spending would primarily benefit Washington, not Baltimore.
If this were so, a visiting artist resident in Baltimore for
a part of a season might have a greater local spending impact
than the arts employee. Similarly, in the assessment of
audience expenditures attributable to the arts, it is not suffi-
cient to know total attendance, since audience spending varies
substantially according to the residence of patrons (local
versus out-of-region) and varies significantly by type of insti-
tution. Also, an institution that relies heavily on contracts
to guest artists who spend only short periods in the community
may export a significant proportion of their wage bill. An
analogous situation will arise for institutions dealing with
outside suppliers. Table 7 gives an indication of high, low
and average values of various data associated with the eight
institutions examined in this report.
It is also important to note that a significant propor-
tion of the aggregate local impact of the examined institu-
tions is due to the fact that, taken together, they received
$2,320,278, or 25% of their total fiscal 1976 budgets, from
government. As indicated by Table 8, the bulk of this
($1,578,545) came from local (city and county) governments.
The largest portion of the support from local government
consisted of $1,012,445 provided by the City of Baltimore to
the Baltimore Museum of Art. Additional sums ranging from
$12,000 to $266,000 were received from local governments by
the other institutions. It is important to note that the
city and counties contributed to other cultural activities
and organizations not included in our study sample.
-26-
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-27-
TABLE 8
Government Revenues of Eight Arts Institutions
Baltimore SMSA, 1976
Baltimore Museum
of Art
Morris A. Mechanic
Theatre
Arena Players
Center Stage
Theatre
Walters Art
Gallery
Baltimore Opera
Baltimore
Symphony
Baltimore
Ballet
Federal*
$56,401
State
Local**
7,500
75,000
76,000
150,000
3,220
$44,112 $1,012,445
2,500
72,000
10,000
31,000
197,000
17,000
12,000
66,000
157,500
44,000
266,000
24,600
TOTAL
$368,121
$373,612 $1,578,545
SOURCE: Institutional estimates, Auditors Reports, 1976.
*Excludes CETA monies.
**Local includes contributions from Baltimore City and each
of the five surrounding metropolitan counties. In 1976,
$120,000 was contributed by Baltimore County and $5,000
by Anne Arundel County to one or more of the eight arts
organizations located in Baltimore City. 1977 was the
first operating season of the Mechanic, and all figures
are Mechanic estimates.
-28-
Consideration of economic effects has a role in the
development of cultural policy. However, community planners
and arts advocates will want to consider the broader community
effects of artistic and cultural activities and not rely solely
on narrowly circumscribed "return on investment" criteria in
the development of public policy toward the arts. The following
examples illustrate the inappropriate use of economic impact
analysis: 1. Inasmuch as the economic impact of individual
arts institutions varies with the factors noted earlier, narrow
economic considerations could lead to differential funding
among individual arts insitutions, based in part on arbitrarily
applied economic goals. 2. In addition, it is clear that
strategies pursued solely to increase the long run economic
impact of particular arts programs might lead directly to a
decrease in the quality of arts activities. One way to increase
the local economic impact of arts activities would be to use
only local talent and to buy only from local suppliers. However,
even where practical, this sort of parochialism would run
counter to the important objective of enabling local residents
to experience a variety and quality of art forms generated
outside their local communities. Also, it is worth noting that
the disadvantages of such a strategy would be unevenly distri-
buted, falling more heavily on smaller, less heterogeneous
communities. 3. Similarly, maximum economic effects would
suggest emphasizing programs which attract visiting audiences,
who spend more in the community per attendance than local
patrons, and it would suggest audience-building strategies
aimed solely at people of means. Yet many communities have
thought it important to provide cultural experiences for other
segments of the population, such as the elderly and school
children, unlikely to contribute much in the way of ancillary
expenditures.
While economic considerations can be important to the develop-
ment of cultural policy, these examples highlight the potential
consequences of placing inappropriate emphasis on "return on
investment" criteria.
-29-
USER MANUAL
Earlier in this report (Tables 1 and 2), we presented
the thirty equations comprising the model used in this study.
Now we will describe each equation in some detail, indicating
necessary data sources and, where possible, alternative stra-
tegies for solving particular equations. The mathematics
are not complex. A number of equations — B-l, B-4, G-l,
G-l.l, G-l. 4, and G-2 — simply add up the estimates produced
by other equations. Certain general equations require the
solution of a sub-set of other equations. In these cases, we
first describe the general equation along with the economic
effect it yields when solved. Then we take up in order each
factor of this general equation, describing in turn the equa-
tion used to determine that factor. Thus, B-l leads us to a
series of equations on which it depends, B-l.l through B-l. 5.
We proceed in a similar manner with regard to sub-sub-sets.
In addition to our description here, the user may also wish
to look at Appendix A where we present the data sources,
equations, and calculations of the Baltimore study. As we
proceed, the reader is urged to refer to Table 1, which sum-
marizes the relationships among equations.
Assumptions and Other Underlying Considerations
Each of the thirty equations comprising the economic impact
model used in the Baltimore study generates an estimate of a
separate economic impact on businesses, government, or indivi-
duals. All of the impacts are estimated in dollar terms except
the employment component, equation 1-1, which produces an
estimate of the number of jobs generated by institution-related
activities.
In interpreting the resultant estimates, the user may
wish to add together some of the separate dollar estimates as
follows:
Total estimated audience expenditures
(other than ticket price) for local
and out-of-region audience
B-l. 4 + B-l. 5
Total estimated local expenditures
for staff and guest artists
B-l. 2 + B-l. 3
Net direct and secondary institution-
related business volume
(B-l + B-2 + B-3)
B-6
Net public sector costs to local
government (Subtract G-5 only if
it can be assumed that government
would have incurred the expense)
(G-2 + G-3 + G-4)
(G-5 + G-l)
-30-
We should also point out that the value of business in-
vestment, B-4, is a measure of asset value at a given point in
time, not a flow of expenditures over a period of time. For
this reason, it should not be added to the outputs of the other
B equations, which represent flows over the fiscal year 1976.
Similarly, in aggregating local government impacts the user
will want to consider carefully whether it is desirable to
focus narrowly on the net balance of governmental revenues to
governmental budget expenditures — which is all that is allowed
using the model — as opposed to returns to government and "the
community" more broadly conceived.
The model goes beyond previous efforts in the wealth of
data it requires, including the use of employee and audience
surveys. When our methods or the lack of data required us
to make assumptions, we opted for the most conservative, i.e.,
adopted the assumption which attributed the highest negative
economic effect or least positive effect to the examined
institution.
For example, in computing out-of -region audience expen-
ditures, we assumed that those out-of-town visitors who used
the institution, but were visiting the metropolitan area
primarily for other reasons, might have incurred some or all
of the daily expenditures they reported in any case. Therefore,
our calculations utilize only the daily expenditures of indivi-
duals who reported that the primary purpose of their visit was
to use the examined institution.
Various equations rely on estimates of household income
and other facts about employee households. Focusing on the
household rather than the individual employee is appropriate
in those circumstances when it is not unreasonable to suppose
that institutional employee households would not have been
in the community except for the presence of the institution.
Practicality suggests that in the absence of data to the
contrary, this assumption be made whenever the majority of
employee households derive the majority of their income from
the institution. When this is not the case, employee income
must be substituted for household income in equations B-1.2 and
G-1.3. However, equations B-5, G-l.1.1, G-1.4, G-l.4.1, G-2,
G-2.1, G-2. 2, and G-3 were intended to be used on a household
basis only. These equations identify economic effects that
are difficult to meaningfully attribute solely to an employee
as opposed to his total household. For example, the ability
to own a home or save may be a function of the collective
earning ability of the household. This is reflected in esti-
mated property taxes and expansion of the local credit base.
-31-
In calculating the value of foregone property taxes on
institutions-owned/occupied property, we reviewed the impact
of alternative assumptions (see Table 5) concerning the
possible uses of currently tax-exempt property, but did not
attempt to evaluate positive or negative effects, if any,
that currently exempt properties may have on surrounding
property values.
It should be noted that several equations represent con-
cessions to practicality. For example, in calculating the
values of local business property committed to support
institution-related business, we assumed that a percentage
increase in demand prompts a similar percentage increase in
investment in real property. This assumption is necessary
because there is no way to determine which firm or institu-
tion may be the marginal user that prompts the need for increased
investment in real property. Other concessions to practicality
are noted in the discussion below.
There are several points to consider with regard to the
sources of data. The user must make a determination at the very
start of the work as to the definition of the "local" area of
interest. In the Baltimore study, the local community of inter-
est was defined to be the Baltimore standard metropolitan
statistical area (SMSA) , composed of Baltimore City and the
five surrounding counties. While some of the calculations
required data that varied by jurisdiction, for example, local
property tax rates — the final estimates yielded by the
equations identify area-wide SMSA impacts. For details of
adaptations of the equations required for multi- jurisdictional
analysis, see Appendix F.
The user will note that the arts impact model in the
Baltimore study required data on audience expenditures , as
well as a wealth of data about the institution and its employee
households. Audience and confidential employee surveys were
used. In some cases, it may be possible to use information
on the community's general population where it is not possible
to conduct an adequate survey of institutional staff. Various
alternatives are explored in the description of specific equa-
tions and in appendices devoted to audience and staff surveys.
What this means is that approaches to solving certain
equations will vary depending on locally available data.
When equations utilize census or other commonly available
data, references are provided. However, the model requires
a great deal of local data, usually collected by local or
state tax divisions, planning departments, budget officers,
assessment bureaus, and the like. Because many of the
equations are interconnected, researchers should carefully
determine whether required data are available, bearing in mind
the alternatives described in the manual, before committing
themselves to assessing institutional impact through the use
of the model.
-32-
Direct Impacts on the Local Economy
We begin our description with those equations relating
to direct impact on the local economy. These include ex-
penditures made in a given fiscal year by the institution,
as well as its employees, guest artists, and audiences.
Equation B-l
E
Institution-Related Local Expenditures
E = E± + Ee + Eg + Ea + Ev
Ei = Local expenditures by institution (B-l.l)
Ee = Local expenditures by employees (B-l. 2)
Eg = Local expenditures by guest artists (B-l. 3)
Ea = Local expenditures by local audience and patrons (B-l. 4)
Ev = Local expenditures by non-local audiences and other
users (B-l. 5)
Equation B-l sums the five separate direct expenditure
effects identified by equations B-l.l through B-l. 5. This
is the total dollar value in a given fiscal year of goods and
services purchased by the institution itself, by employee
households, by guest artists, by local audiences and other
users, and by non-local visitors.
-33-
Equation B-l.l
Ei
Local Institutional Expenditures for Goods and Services
Ei = z(TE. - W - Transf. - T__)
z = Percentage of expenditures for goods and services
made to local firms
TEj_ = Total expenditures for the fiscal year under consideration
W = Gross compensation, including FICA, federal withholding,
state withholding, unemployment compensation, and
contributions to pension plans
Transf. = Transfer of funds from one internal account to another
that might appear as an expenditure and thus distort
actual total expenditure
Tx = Taxes and fees to government other than those appearing
in W above: sales taxes, real estate taxes, or other
payments and fees to government at all levels.
Institutions purchase goods and services from both local and
non-local firms. B-l.l is used to identify expenditures for goods
and services made directly by the institution with local businesses,
the first factor in determining institution-related local expen-
ditures.
Subtract from an institution's total expenditures all
payroll expenditures and payments to government, leaving only
expenditures for goods and services. Then, determine total
expenditures with local firms. This can be done in two ways.
Draw a random sample of institutional purchase orders in
each major expenditure category, noting total dollar expenditures
made in that category with local firms as compared to those
made with outside suppliers. This yields a proportion, z, spent
locally for each major expenditure category. Total dollars
spent in each category are multiplied by each z, and the
resulting local expenditures totalled to determine E^.
If the number of vendors with which the institution
deals is relatively small, there is a more direct procedure.
Simply examine the auditor's report by category of expenditure,
excluding wage-related expenditures and payments to government.
Typically, for each major category there is a handful of
vendors with whom an institution does the bulk of its business.
Simply identify the vendors that are local and add up the total
spent with these local firms. Some arts organizations have
sophisticated and computerized accounting procedures and are
able to identify each vendor, its address, and the total ex-
penditures with that vendor. These institutions will find it
quite easy to employ this more direct procedure. An extremely
high percentage of institutional expenditures are often made
with a relatively small number of firms. The fiscal officer
responsible for disbursements should then be able to get a
good estimate of total dollars spent locally.
-34-
Equation B-1.2
Ee
Direct Expenditures in the Local Community By-
Institutional Employees
Ee = (f) (Wen + -5Yns)
Ee = Direct expenditures in the local community by institutional
employee households
f = Percentage of employee household income spent locally
W = Total net institutional salaries
Y = Employee household non-salary income: income from rents,
ns
dividends, interest, and other sources
B-1.2, identifies the second factor important to determining
institution related local expenditures. It is used to identify
total expenditures in the community attributable to employees
in circumstances, unlike the Baltimore case, where institutional
salaries constitute less than one-half total employee household
income. In circumstances such as the Baltimore case, where
household income is primarily from institutional sources,
substitute total household income (Y) for (Wen + .5Yns). Note
the discussion of these questions at the beginning of this
User Manual. In particular, only use (Y) , total employee
household income, when the majority of employee households
derive the majority of their income from the institution.
To solve equation B-1.2, first identify W # total net
institutional salaries, and add 1/2 of total employee house-
hold salary income. Then multiply by f, the percentage
employees spend locally. The salary income of other family
members is not considered because there is no reason to believe
that this income is dependent on the existence of the institu-
tion. However, non-salary income is due to the enterprise of
individuals who may be in the community only because a family
member is an institutional employee. Therefore, B-1.2 arbi-
trarily attributes 1/2 of all non-salary employee household
income to the institution.
To identify the percentage spent locally, employees can
be asked, through a confidential survey (see Appendix C) , to
report this figure as well as total non-salary family income,
if needed.
In solving B-1.2, it will be important to distinguish
full-time from part-time employees. Net wages to part-time
employees will be included in total net institutional salaries,
Wen. However, it may be argued that the non-salary income
of part-time employees should not be considered inasmuch as
it is unlikely that the household whose enterprise resulted
in this income resides in the community only because of a
family member's part-time job at the institution.
-35-
Equation B-l. 3
Eg
Local Expenditures by Guest Artists
E
g = g(GD)
EQ = Local expenditures by guest artists
g = Average daily expenditures by guest artists
GD = Total guest artist days in the community
Guest artists and their entourage have hotel and restau-
rant bills and make other local expenditures. B-l. 3 is used
to identify the total amount they spend, the third factor used
in determining institution-related expenditures.
"Guest artist" refers to individuals who are not permanent
residents of the community or considered, for payroll purposes,
as employees. Typically, they are in the community for a short
period of time in order to take part in a specific program.
Guest artists can include lecturers, conductors, soloists,
and so forth. It is not necessary for the guest artist to be
paid by the institution in order for their local expenditures
to be counted.
The value g, average daily expenditures by guest artists,
is determined by dividing the total dollars guest artists re-
port that they spend in the community by total days they report
staying in the community. Presumably the guest artists avail-
able to the researcher will be those appearing at the institu-
tion during the period in which the researcher is gathering
data for the economic impact model. These guest artists com-
prise a sample of the entire year's guest artists. They can be
asked to complete a confidential survey citing the length of
their stay in the community and the amount spent. (It is conve-
nient to simply add a separate set of questions for guest art-
ists to the employee survey; see Appendix C . ) Responses col-
lected may be assumed to be typical of average daily expendi-
tures by all guest artists.
GD is determined by multiplying the total number of guest
artists by their total days in the community. (This informa-
tion is available from institutional internal records.) B-l. 3
is then solved by multiplying average daily local expenditures
by the total number of guest artist days in the community.
Some institutions may not care to ask a guest artist to
tell them how much he or she typically spends while in the
local community. In this case, some estimate should be made
based on institutional knowledge of guest artist accommodations
and so forth. When a per diem is paid, the institution may
suppose that the guest artist spends all of the per diem locally,
but not more; or the institution may have information on the
basis of which to make other assumptions.
-36-
A combined approach is probably best if an institution
plans to sample a limited number of guest artists, for example,
those appearing during the data-gathering period, or if the
institution expects only a limited number of replies by
guest artists.
Institutions preferring to rely on their own best estimate
of guest artist expenditures should take into account all
likely expenditures. This is especially true when an institution
utilizes a guest artist for a period of several weeks, for
example, if the artist is part of a resident troupe. In this
case, it is typical for the arts organization to facilitate the
rental of an apartment, or the arts organization may rent
apartments on a yearly basis which are sublet to such artists.
In any case, it is the artist who is paying the rent out of
his/her fee.
-37-
Equation B-1.4
Ea
Local Expenditures by Local Audience and Patrons
Excluding Admission
Ea = a(TA)
Ea = Local expenditures by local audience and patrons
a = Average expenditure per attendance (excluding admission)
TA = Total attendance
B-1.4 allows us to determine the fourth factor in
institution-related expenditures, the money spent locally by
local audiences aside from admissions. Multiply a, the average
expenditure per attendance (excluding admission) by the total
attendance.
Average expenditure per attendance by local audience and
patrons must be derived from an audience survey. As discussed
in Appendix D, a particularly thorny problem arises in designing
a survey instrument which can accurately elicit audience ex-
penditures on a per person basis. Individuals commonly attend
arts performances in parties of two or more and there is con-
siderable danger that researchers may misjudge total audience
expenditures if average individual responses are utilized to
make per person expenditure estimates.
An alternative is to ask respondents to report the number
of persons in their party and the total expenditures of the
entire party so that values for a can be constructed for parties
of one, two, three, and so forth, and the total attendance size
figures, TA, weighted by party size as well. The sample data
for Baltimore indicate that the distribution of audience by
party size varies significantly by type of cultural institution,
so that a stratified approach becomes more important where
a multi-institution analysis is being performed.
-38-
Equation B-1.5
Ev
Local Expenditures by Non-Local Audience and Other Users
Ev = v(TVD)
Ev = Local ancillary expenditures by non-local audience and
other users
v = Average daily per party expenditures by non-local audience
and other users (excluding admission)
TVD = Total annual visitor-days by non-local audience and other
users
This equation provides the last factor in describing di-
rect institution-related expenditures. B-1.5 is used to deter-
mine the amount spent in the community by visitors and other
non-local individuals in association with their attendance
or use of local artistic and cultural institutions.
Multiply the average per party ancillary expenditures by
total non-local audience visitor-days.
The values v and TVD can only be determined by conducting
an audience survey in which non-local individuals are asked to
report: total party expenditures in the local community; whether
they and their party are in the community specifically to use
the institution; and total days in the community (see Appendix D)
This survey will distinguish between two types of local
expenditures by non-local audiences: one, the local expendi-
tures of those who are visiting the community primarily because
of their interest in a particular institution's programs; and
the other, the expenditures of those who might have come to the
community had the institution not existed, but who happen to use
the institution while in the community. A decision to visit a
locale may include a decision to visit a particular institution;
this does not, however, tell us that a person would not have
chosen to come to a community in the absence of the institution.
So, while it may be informative to identify the percentage of
non-local users who had decided prior to visiting a community
to visit also a particular institution, this does not mean that
the money they spent during their stay or in association with
their use of the institution would not have been spent in
the community had the institution not existed.
Therefore, in the interest of being conservative, our pro-
cedure attributes to the institution only the expenditures made
by those whose principal reason for being in the community is
their use of the institution. However, information on the total
percentage of non-local users is important because it suggests
that the institution is part of what makes the community attrac-
tive as a place to visit and, further, that the institution is
helping to favorably advertise the community to others. Ulti-
mately, these factors can translate into economic terms.
-39-
Secondary Impacts
Equation B-l estimates economic effects directly related
to the institution as represented by the expenditures in a given
fiscal year made by the institution, its employees, guest
artists, and others. In turn, these direct economic effects in
local business generate second-order effects as local businesses
make purchases of their own and pay salaries in order to support
institution-related demands for goods and services. The next
seven equations identify particular secondary effects. Several
utilize economic coefficients or multipliers. These are dis-
cussed in Appendix B.
Equation B-2
BP
Purchases by Local Businesses From Local Sources in Support of
Institution-Related Expenditures in the Local Economy
BP = (mp - 1) (E)
BP = Purchases by local businesses from local sources in support
of institution-related expenditures in the local economy
mp = Repurchase coefficient for the local business sector
E = Institution-related direct expenditure in the local
community (See B-l)
E, which is determined by equation B-l, represents institu-
tion-related direct impacts on the local economy: expenditures
by employees, guest artists, out-of-town and local audiences,
and the institution itself. In order to meet the demand for
goods and services represented by E, local businesses make addi-
tional purchases of their own. The total of these secondary pur-
chases made by local businesses from local suppliers is of
interest.
You will be using a standard economic technique known as
multiplier analysis in which initial volume of spending (E) is
multiplied by a respending co-efficient (mp) , yielding BP, the
total eventually spent by local firms as a consequence
of E. Values for mp reflect one's knowledge of the size and
diversification of the local market area. The larger and more
diversified the local economic base, the less will local
businesses have to turn to outside suppliers to meet their
needs. Thus, firms in large metropolitan areas are more likely
to be able to meet their needs by turning to local suppliers,
while businesses in small towns may have to turn more frequently
to suppliers located elsewhere.
BP is an estimate of secondary purchases by local firms.
In equation B-2, 1 is subtracted from m in order not to
count direct expenditure, E, as part ofpBP. Appendix B cites
typical values for mp, and briefly explains the technique
of multiplier analysis and development.
-40-
Equation B-3
BV
Local Business Volume Stimulated by Institution-Related Income
Spent by Local Business Employees
BV = (.45) (E) (iru-1)
BV = Local business volume stimulated by institution-related
income spent by local business employees
m^ = Respending coefficient for individuals
E = Institution-related direct expenditures in the local
community (see B-l)
The previous equation, B-2, identifies total secondary
institution-related purchases made by local firms from local
sources. The employees of firms directly benefitting from
institution-related business volume receive a portion of
it as wages, and these wage earners in turn buy goods and
services from local businesses. It is estimated for all
communities that 45% of E, institution-related local expendi-
tures, is received as income by the employees of local firms.
Equation B-3 estimates the additional local business volume
attributable to these employees.
Multiply E (from equation B-l) by 45% to estimate
institution-related direct expenditures received as income
by the employees of local businesses. Multiply also by m- ,
the respending coefficient, which estimates the proportion
that is eventually respent locally for goods and services.
Values for m^ are based on national data (see Appendix B) .
As noted in the discussion of equation B-2, m^ is reduced
by 1 in order not to count direct expenditures, E, as part of
BV.
■41-
Equation B-4
BI
Value of Local Business Property Committed to
Institution-Related Business
BI = RP + Inv
BI = Value of local business property committed to institution-
related business
RP = Business real property committed to support institution-
related business (see B-4.1)
Inv = Business inventory committed to support institution-related
business (see B-4. 2)
Firms invest in real property and inventory to support the
demand for goods and services. Institution-related direct
expenditures constitute such a demand; and the equations
B-4.1 and B-4. 2 estimate, respectively, the values of local
business real property (RP) and inventory (Inv) , committed to
support institution-related business. B-4, then, sums up the
values identified by equation B-4.1 and B-4. 2.
B-4 estimates the current value of real property and
inventory and not current expenditures made in the examined
fiscal year, although a portion of these assets may have been
acquired in that year. Expenditures were not necessarily
made with local firms.
-42-
Equation B-4.1
RP
Value of Local Business Real Property Committed to Support
Institution-Related Business
RP = (E/TBV) (AV/ar)
RP = Value of local business real property committed to
support institution-related business
E = Institution-related direct expenditures in the local
economy (see B-l)
TBV = Total local business volume (total local retail sales +
total local wholesale sales + the value added to raw
materials by local manufacturers)
AV = Total assessed valuation of business real property
ar = The ratio of assessed valuation to full market value
B-4.1, which provides one of two factors needed for B-4,
assumes that the proportion of total local business real
property committed to servicing institution-related direct
expenditures is identical with E/TBV, or institution-related
expenditures as a percentage of total local business volume.
This procedures assumes that a percentage increase in
demand prompts a similar percentage increase in investment in
real property, a necessary assumption since there is no way to
determine which firm or institution may be the marginal user
that prompts the need for increased investment in real property.
Consequently, the only available procedure is to average the
value of real property over all firms in proportion to their
demand.
To determine TBV, data are available from the Census
Bureau as well as from the local planning department or
department of economic development. Consult the Bureau of the
Census publications, Retail Trade Area Statistics, Wholesale
Trade Area Statistics, and the Census of Manufacturers.
At this writing, the latest data available from these
documents are for 1967. Thus a projection must be made by the
following procedure. Due to the expansion of the economy and
inflation, TBV is much higher now than in 1967. Assume that
the increase in TBV is in direct proportion to the increase from
1967 in local sales tax receipts. If there is no local sales
tax, assume that increases in state sales tax reflect increases
in local business volume. In areas where there is only a state
sales tax, the state agency may have identified total tax reve-
nues contributed by the local community. In any case, this
percentage increase in sales tax receipts can be applied to TBV
1967 to yield an estimated current TBV. Be sure to adjust for
any increases in the sales tax rate in the years since 1967 that
might distort the calculated percentage increase.
-43-
AV is not total local assessed valuation; it refers to
business property only. Further, in many communities, the
assessed valuation (the value of property for tax purposes)
is less than full market value; and the local tax office may
only report assessed valuation. Full market value can be
determined by dividing AV by ar, the percentage of full mar-
ket value used in determining assessed valuation. When AV
is 100% of market value, ar is 1.
-44-
Equation B-4.2
Inv
Value of Business Inventory Committed to Support
Institution-Related Direct and Secondary Business Volume
Inv = ir(E + BP + BV)
Inv = Value of business inventory committed to support
institution-related direct and secondary business
volume
ir = Local inventory-to-business volume ratio
E = Institution-related direct expenditures in the local
community (see B-l)
BP = Purchases by local business from local sources in
support of institution-related expenditures in the
local economy (see B-2)
BV = Local business volume stimulated by institution-related
income spent by local business employees (see B-3)
To solve B-4.2, the second factor needed for B-4, the
local inventory-to-business volume ratio is multiplied by the
sum of E + BP + BV, the sum of direct . and indirect institution-
related expenditures in the community.
There is a direct relationship between gross sales and the
value of inventory. The value ir is the local inventory-to-
business volume ratio, calculated as the ratio of the value of
end-of-year inventory to gross sales; ir, then, is the value of
inventory as a percentage of gross business receipts. Data from
which this ratio can be calculated for a national sample are
supplied by the IRS from corporate tax returns (see Statistics
of Income, 1972, to be updated in the near future) . " If the
local planning department, assessments bureau, or economic
development agency has independent data, communities that tax
inventory will have local estimates of inventories which can be
used to calculate a local ir figure. Other communities will
have to use the national inventory- to-business volume ratio of
.112. This figure is derived from IRS, Statistics of Income,
1972, Table 5.2, p. 172. BP. and BY. were included in model
B-4.2 on the assumption that ir, the inventory-to-business
ratio, remains constant over the full adjustment period.
-45-
Equation B-5
CB
Expansion of the Local Credit Base Attributable to
Institution-Related Deposits
CB = (1-t) [TDi+(TDe) (Emps)] + (1-d) [DDi+DD^ (Emps) +cbv (E+BP+BV) ]
CB = Expansion of the local credit base attributable to
institution-related deposits
t = Local time deposit reserve requirement
TD-l = Average daily balance in institution time (savings)
accounts
TDe = Average daily balance in employee household time
(savings) accounts
Emps = Total full-time and full-time equivalent employees
d = Local demand deposit reserve requirement
DD^ = Average daily balance in institution demand (checking)
accounts
DD = Average daily balance in employee household demand
(checking) accounts
cbv = National cash-to-business volume ratio
E = Institution-related direct expenditures in the local
community (see B-l)
BP = Purchases by local business from local sources in
support of institution-related expenditures in the
local economy (see B-2)
BV = Local business volume stimulated by institution-related
income spent by local business employees (see B-3)
Equation B-5 estimates total additions to the community
credit base attributable to institution-related time (savings)
and demand (checking) accounts, that is, institutional accounts,
the accounts of employee households, and the accounts of busi-
nesses and employees affected directly or indirectly by the
institution and its employee households.
In B-5, t and d refer, respectively, to the local time and
demand deposit reserve requirements, so that 1-t or 1-d indicate
the percentage of deposits in time demand accounts that may be
used by financial institutions for loans. TDj and TDP are,
respectively, institutional and employee household time (savings)
accounts. DP-; and DDp, are, in similar fashion, average daily
balances in demand (checking) accounts by the institution and its
employee households. TD^ may be determined from institutional
accounts by averaging end and middle of the month checking account
balances as indicated by institutional checking account state-
ments, thereby taking a sample of 2 4 days. Employees can be asked
to report average daily household time and demand account
balances.
The accounts of part-time employees should be counted in
proportion to their full-time status. Therefore, Emps refers
to total full-time employees and total part-time employees
aggregated into full-time equivalents.
-46-
The value cbv is the national cash-to-business volume ra-
tio, reflecting cash held in reserve by businesses as a percent-
age of total business volume. For example, in the Baltimore
study, a value of .028 was assigned to cbv. This value was cal-
culated as an average of 1965 and 1972 ratios determined from
U.S. Statistics of Income, Internal Revenue Service, U.S. Cor-
porate Tax Returns, 1965, 1972, Table 5.2, p. 1972. We aver-
aged ratios for two years to mitigate the cyclical effects of
the most recent (1972) data which reflect the recession condi-
tions of that period.
The issues previously raised in discussion of the impact of
employee households (see B-1.2) apply, with obvious differences,
to B-5. Household savings and checking accounts may include
contributions from a working spouse or other family member.
Therefore, B-5 may overstate institutional impact in that it
combines effects that are associated with employee households
with effects more specifically attributable to individual insti-
tutional employees.
B-5 does not reflect expansion of the local credit base from
secondary employment stimulated by institution-related direct and
secondary expenditures (see 1-2) .
-47-
Equation B-6
NBV
Local Business Volume Unrealized Due to
Institution-Related Enterprises
NBV = IB
NBV = Local business volume unrealized due to institution-
related enterprises
IB = Income from institution administered businesses
The equation B-6 requires an examination of institutional
operations and auditor's reports to identify income from
enterprises administered by the institution or an affiliated
body, for example, income from sources such as gift shops,
restaurants, and sales and rental galleries. Do not include
income derived from concessions.
B-6 is an attempt to recognize institutional enterprises
that may have unforeseen negative or positive effects that
need to be taken into account in assessing the local economic
impact of the institution. Calculating the business volume
of subsidiary institutional enterprises is a first step in
identifying whether these benefit, harm, or have no impact
on other businesses or sectors of the economy, either community-
wide or in the area immediately adjacent to the institution.
The assumptions made about the impact of subsidiary enterprise
must be a matter of informed judgment on the part of the local
researcher.
-48-
Impacts on Government
All economic enterprises, including artistic and cultural
institutions, represent a cost and benefit to local government.
We note again that the equations cited in this manual provide
a narrow perspective on the costs and benefits to local govern-
ment, focusing primarily on the effects that can be most readi-
ly quantified. The next eight equations focus solely on tax
income and governmental expenditure and do not identify the
broader impact of investment in artistic and cultural institu-
tions.
Equation G-l
GR
Total Institution-Related Local Tax Revenues
GR = RETX + ST + YT + SA + OR
GR = Total institution-related local tax revenues
RETX = Real estate taxes paid by the institution, its employee
households, and local businesses serving both (see G-l.l)
ST = Local sales tax revenues resulting from institution-
related direct expenditures (see G-l. 2)
YT = Local income tax revenues paid by institutional employee
households (see G-l. 3)
SA = State aid to local government attributable to institutional
employee households (see G-l. 4)
OR = Other local revenues attributable to the institution and
its employee households (see discussion of G-l. 4)
G-l sums the institution-related local tax revenues
identified by the equations G-l.l through G-l. 4. In this
sub-set, two equations depend in turn on still others:
G-l.l requires G-l. 1.1 and G-l. 1.2 while G-l. 4 requires G-l. 4.1.
-49-
Equation G-l.l
RETX
Local Real Estate Taxes Paid by the Institution,
Its Employees , and Local Businesses
Serving Both
RETX = RETi + RETe + RETb
RETX = Local real estate taxes paid by the institution,
its employee households, and local businesses serving
both
RET-l = Local real estate taxes paid by the institution
RETe = Local real estate taxes paid by institution employee
households (see G-l.1.1)
RETk = Local real estate taxes paid by local businesses
serving the institution and its employee households
(see G-l.l. 2)
G-l.l is the first of four equations needed to describe
total institution-related local tax revenues (G-l) . It
sums the real estate taxes paid to local government by the
institution, its employees, and local businesses serving both.
RETJ represents real estate taxes paid by the institution
itself. Since most artistic and cultural institutions are
non-profit, tax-exempt institutions, they will pay no real estate
taxes, and the value of RET^ will usually be zero. Some may
own property which is not used for non-profit purposes, in which
case they will pay property tax. Total real estate taxes paid
to local government will include RET^ as well as RETe and RETj-,,
the values for which are derived by solving equations G-l.1.1
and G-l. 1.2.
-50-
Equation G-l.1.1
RETe
Local Real Estate Taxes Paid by Institutional Employees
RETe = Emps(h) (pt) (TRA/R)
RET = Local real estate taxes paid by institutional employee
households
Emps = Total number of employees
h = Percentage of employees owning homes locally
pt = Local residential property tax rate
TRA = Value of local residential housing
R = Total number of assessed residences
G-l.1.1 takes the average assessed value of a local
residence and multiplies this average by the local residential
property tax rate and the number of employee households owning
local homes in order to estimate total local property tax paid
by institutional employee households. This procedure is employed
in lieu of all employees reporting their total local property tax
payments through a confidential employee survey. All that is
required of employees is that they report whether they own a home
locally.
Dividing TRA by R yields the average value of local resi-
dential housing. TRA can be found in the local department of
assessment or taxation reports. R should be available from the
same sources. If not, consult the 1970 Census of Population
and Housing report for your local community.
It is important to note that TRA and R must be consistent.
R must include all residential units whose tax revenues are
included in TRA, for example, the revenues produced by apartment
buildings as well as private homes if individual apartments are
included in R. The value, h is the percentage of employees
owning local homes. To derive h, employees can be asked through
a confidential survey whether tney own a home (see Appendix C) .
Property tax contributions of part-time employee households
should only be counted in proportion to hours worked at the insti-
tution. This can be accomplished by differentiating full-time
from part-time employees in the employee survey and aggregating
part-time employees into full-time equivalents. Knowing the per-
centage of part-time employees who own a home and the number of
full-time equivalent personnel residing locally, G-l.1.1 can be
applied to part-time employees separately to determine their
local property tax contribution.
Equation G-l.1.1 assumes that employees who own homes
locally own only one. Employees also could be asked to report
how many homes they own, which would yield an average number of
local homes owned by employee households. This would constitute
a new term in G-l.1.1.
-51-
There are at least two issues which must be raised
in connection with G-l.1.1. First, the equation ignores
employee households that rent, and it thereby omits their
property tax contributions. The local planning agency
or bureau of taxation might have data on the average yearly
contribution to the property tax paid by renters; this can
be multiplied by 1-h to yield total property tax paid by
employee households that rent rather than own. Second, it
is not clear that the property tax revenues identified by
G-l.1.1 would not have been generated had the institution
not existed. The household might have owned the home even
if a family member had not been employed by the institution;
or, if the employee household had not bought the house,
someone else might have. All that can be claimed by any
institution is that its employees contribute to the community
through property taxes.
As noted in our discussion of B-1.2 and B-5, some
may argue that this overestimates RETe. Our remarks in these
earlier discussions apply here also. Additionally, we again
call the user's attention to the discussion of employee
households at the beginning of Section V, User Manual.
-52-
Equation 6—1.1.2
RETb
Real Estate Taxes Paid by Local Businesses on Real Property
Committed to Support Institution-Related Business
RETb = (RP) (ar) (pt)
RET^ = Real estate taxes paid by local businesses on real
property committed to support institution-related
business
RP = Value of local business real property committed to
support institution-related business
ar = The ratio of assessed valuation to full market value
pt = Business and property tax rate
Equation G-l.1.2 is a variant of equation B-4.1, which
identified RP, local business real property committed to
support institution-related direct expenditures. G-l.1.2
multiplies RP by the local assessment ratio and property
tax rate to yield real estate taxes paid by local businesses
on real property committed to institution-related businesses.
Thus, much of the discussion of B-4.1 applies to G-l.1.2.
If the local community taxes inventory apart from busi-
ness real property, G-l.1.2 can be used to identify taxes
paid on business inventory, Inv, committed to support institu-
tion-related business by substituting Inv for RP (see B-4.2)
together with the correct assessment ratio and tax rate.
6-1.1.2 does not estimate the real estate taxes paid by em-
ployees in jobs created indirectly by institution-related
direct and indirect effects on business identified by the
B-series models (see Model 1-1) .
-53-
Equation G-1.2
ST
Local Sales Tax Revenues Resulting from Institution-Related
Direct Expenditures
ST = st (STR) (E/TBV)
ST = Local sales tax revenues resulting from institution-
related direct expenditures
st = The percentage of locally generated sales tax revenues
retained locally
STR = Sales tax revenues generated locally
E = Institution-related direct expenditures in the local
community (see B-l)
TBV = Total local business volume (total local retail sales
and total local wholesale sales and the value added
to raw materials by local manufacturers)
Equation G-1.2 yields the second factor needed to estimate
total local tax revenues. In it, E/TBV identifies institution-
related direct expenditures in any one fiscal year as a percent-
age of a community's total business volume for that year (see
B-4.1). G-1.2 assumes that if institution-related direct expen-
ditures are X% of local business volume in a given year, they
can be expected to result in a similar percentage of that year's
total sales tax receipts. STR represents total sales tax reve-
nues generated locally. This information should be available
from the state or local retail sales tax division.
In some states the sales tax is a state tax with a certain
percentage returned to the local community. In this case, the
local community receives percentage st of all sales tax reve-
nues generated locally; therefore, st of (STR) (E/TBV) is locally
retained sales tax receipts. If the sales tax in a community
is strictly a local tax, st = 1 and can be dropped from the
equation.
G-1.2 underestimates total eventual sales taxes attributable
to the institution, since it does not take into account secondary
expenditure effects BP or BV (see B-2 and B-3) .
-54-
Equation G-l. 3
YT
Local Income Tax Revenues Paid by Institutional Employee Households
YT = (TYT/HH) (Emps)
YT = Local income tax revenues paid by institutional employee
households
TYT = Total income tax revenues retained by the local jurisdic-
tion
HH = Total local households
Emps = Total number of employees
Income tax revenues for local governments generally arise
in one of two ways: either they are a direct earnings or income
tax levied by local government; or they are a "piggyback" tax in
which a surcharge on the state income tax is collected by the
state and rebated to each local government. In some instances,
the calculation of local revenues from an earnings tax can be
complicated by the fact that commuters may pay the tax at a dif-
ferent rate than residents of the local jurisdiction. In this
case, G-l. 3 should be split into two parts, using different
average tax yields per household (TYT/HH) for residents and
commuters.
Income tax contributions by part-time employees should be
counted only in proportion to their full-time status. Aggregate
part-time employees into their full-time equivalents and treat
them separately. Notice that G-l. 3 assumes that each institu-
tional employee comprises a household.
In the case of a "piggyback" tax, the local fiscal officer
will have information on locally rebated revenues collected by
the state; this can be used directly in calculating the average
yield per local household.
As discussed at the beginning of this manual, it may be more
appropriate in certain cases to utilize employee rather than
household income. In this circumstance it may be possible to
utilize institutional records to total employee local income tax
withholdings. However, this introduces the possibility of error
since some individuals deliberately have their employers over-
withhold by claiming fewer deductions than they are entitled to.
When used on a household basis, G-l. 3 takes the average tax
yield per household times the number of employee households.
Alternatively, employees can be asked to report total household
income tax paid to local government on the confidential employee
survey. If per household data are not available, G-l. 3 may be
solved by identifying the total number of individuals in employee
households and multiplying this number by per capita local income
tax revenues. G-l. 3 gives the third factor in total local tax
revenues related to the institutions (G-l) .
-55-
Equation G-1.4
SA
State Per Capita Aid to Local Government Attributable to
Institutional Employees
SA = PS + OR
SA = State per capita aid to local government attributable
to institutional employee households
PS = State public school per pupil aid attributable to
institutional employee households
OR = Other state revenues attributable to the institution and
its employee households (per capita)
G-1.4, the fourth equation needed for G-l, estimates total
state aid attributable to institutional employee households as
the sum of state per pupil school aid, PS, and other per capita
state revenues. PS is estimated by equation G-l. 4.1, (see
discussion of employee households at the beginning of manual) .
G-1.4 deliberately focuses on state aid that is provided
solely on a per capita basis, as in the case of PS, which is on
a per pupil basis. Researchers will have to contact the local
community's budget officer to review state programs providing
local funds on a per capita basis, either for the total popula-
tion or by eligibility group. State aid attributable to employ-
ee households will require identifying the number of eligible
persons in employee households in each program area for which
the state provides per capita aid. Researchers will have to
judge whether the revenue source is significant enough to warrant
the additional questions on the confidential employee survey that
will be required. If aid comes on a per total population basis,
then researchers will, at a minimum, need to identify the total
number of persons in employee households. Part-time employees
should be aggregated into full-time equivalents, attributing
state per capita aid to them in proportion to their full-time
status at the institution.
-56-
Equation G-l.4.1
PS
State Public School Per Pupil Aid Attributable to
Institutional Employee Households
PS = (N) (C) (SE)
PS = State Public School Per Pupil Aid Attributable to
Institutional Employee Households
N = The number of employee households with children in
public elementary and secondary schools
C = The average number of children employee households send
to public elementary and secondary schools
SE = State per pupil educational grant to the local community
It is not uncommon for states to provide school aid to local
communities on a per pupil basis. Equation G-l.4.1 estimates PS,
total of per pupil state aid attributable to employee households.
(See employee household discussion in introduction to manual.)
To estimate N, researchers will have to identify the number
of employee households with children in public elementary and
secondary schools and the average number of children each of
these households sends to public school, thereby allowing an
estimate of the total number of employee children in public
schools. This figure, multiplied by SE, the per pupil state
grant, yields PS. To identify the number of employee households
with children in public school will require an estimate of the
percentage of all employee households with children in public
school. This means an additional question on the confidential
employee survey. Employees will also have to be asked to report
the number of children they send to public elementary and
secondary schools.
-57-
Costs to Local Government
In the preceding G equations, we have provided strategies
and structured suggestions for identifying institution-^related
contributions to local government. Our concern has been limited
to tax or other revenues attributable to the institution. From
an equally narrow perspective, researchers can examine the cost
to local government imposed by the institution and its employee
households. Selected costs are estimated by equations G-2
through G-5.
Even viewed narrowly, governmental involvement with the arts
imposes costs that are not accounted for by the equations below.
An attempt should be made to identify these costs, be they donated
services, special contributions, or whatever. Perhaps most impor-
tantly, resources devoted to the arts become unavailable to govern-
ment for use in pursuing other public goals. This is often a
primary reason for governmental concern with accountability for all
public programs, including arts programs.
It might be helpful for the user to review the discussion of
employee households at the beginning of this manual, particularly
with regard to equations G-2, G-2.1, G-2. 2, and G-3.
Model G-2
OC
Operating Cost of Government-Provided Municipal and Public
School Services Attributable to the Institution
and Its Employee Households
OC = MOC + PSOC
OC = Operating cost of government-provided municipal and
public school services attributable to the institution
and its employee households
MOC = Local governmental operating costs (excluding schools)
attributable to institutional employee households
PSOC = Public school operating costs attributable to institutional
employee households
G-2 is a summing function, adding local governmental oper-
ating costs (excluding schools) attributable to the institution
(MOC) and local public school operating costs attributable to the
institution (PSOC). Equations G-2.1 and G-2. 2 identify these two
values.
-58-
Equation G-2.1
MOC
Local Governmental Operating Costs (Excluding Schools) Attributable
to Institutional Employee Households
MOC = B(EHH/POP)
MOC = Local governmental operating costs (excluding schools)
attributable to institutional employee households
B = Local operating budget excluding public school costs
and non-locally generated revenues
EHH = Total number of persons in local residing employee
households
POP = Total local population
Local government incurs a variety of costs in providing ser-
vices to institutions and their employee households. These costs
include both capital investment in facilities required to provide
services and operating costs associated with the delivery of ser-
vices.
Equation G-2.1 apportions to the institution and its employ-
ee households their share of local governmental operating expendi-
tures in such areas as police and fire protection, library ser-
vices, sanitation, and, in general, all areas except public edu-
cation, which is handled separately by equation G-2.2. (Equation
G-3 apportions all corresponding capital costs.) G-2.1 represents
a pragmatic approach to resolving several difficulties. Neighbor-
hoods vary in their cost to local government, for example, in
areas such as police and fire protection. Employee households may
be located in a variety of neighborhoods. How should the alloca-
tion of costs to local government be weighted? Social service
costs provide a particularly striking example. These costs often
represent a major portion of a local government's operating bud-
get. If it turns out that employee households do not require
social services, then it would seem important not to attribute
social service costs to employee households.
If the factors which prompt a household to impose a dispro-
portionate cost on local government were known, appropriate ques-
tions could be included in the confidential employee survey, and
the allocation of costs per employee household could be weighted
accordingly. This procedure would present tremendous theoretical
and practical difficulties. A pragmatic approach requires the
per capita allocation of all non-school operating costs over the
entire local population, recognizing that this may overstate the
costs incurred in servicing the institution and its employee
households.
G-2.1 focuses solely on employee households. It assumes
that, if employee households make up X% of the total population,
then they impose the same percentage of total non-school govern-
mental costs. EHH/POP represents employee households as a per-
centage of the total population. EHH can be determined by
-59-
including an appropriate question on the employee survey. POP
is available from the local planning department, and B will be
provided by the local office of the budget. It is important to
make certain that the figure used for B excludes contributions
to the school budget from other than local sources, since these
have been counted in equation G-1.4, and we are only concerned
with costs to local government.
-60-
Equation G-2.2
PSOC
Public School Operating Costs Attributable to
Institutional Employee Households
PSOC = SB(C/TC)
PSOC = Public school operating costs attributable to institution-
al employee households
SB = Local public school operating budget, excluding revenues
from non-local sources
C = Number of children in employee households attending
local public primary and secondary schools
TC = Total enrollment in local public primary and secondary
schools
The preceding discussion of equation G-2.1 applies with
necessary changes, to equation G-2.2, which apportions the costs
of local public schools over employee households. Using the
employee survey, the total number of employee household children
in local primary and secondary schools can be identified. C/TC
represents employee household children in primary and secondary
schools as a percentage of the total local enrollment in public
primary and secondary schools. This percentage, when multiplied
by the public school operating budget for primary and secondary
schools, results in an estimate of total costs imposed by employee
households. SB and TC should be available from the local depart-
ment of public instruction. Aaain, be certain that the figure
used for SB excludes contributions to the school budget from other
than local sources, since these have been counted in G-1.4, and we
are only concerned with costs to local government.
-61-
Equation G-3
GP
Value of Local Governmental Property Committed to Support
Services to Employee Households
GP = (GPm) (MOC/B) + (GPS) (PSOC/SB)
GP = Value of local governmental property committed to
support services to employee households
GPm = Value to all non-school-related governmental property
GPS = Value of all school-related governmental property
MOC = Local governmental operating costs (excluding schools)
attributable to institutional employee households (see
G-2.1)
B = Local operating budget excluding public school costs
and non-locally generated revenues
PSOC = Public school operating costs attributable to institu-
tional employee households
SB = Local public school operating budget excluding revenues
from non-local sources
Equations G-2.1 and G-2.2 provide an estimate of public
school and other governmental operating costs attributable to
institutional employee households. Equation G-3 estimates
local government capital costs attributable to the institution.
PSOC/SB represents school costs attributable to employee
households as a percentage of the total school budget. G-3
attributes the same percentage of the value of school facilities,
(GPs) (PSOC/SB) , to employee households. The same procedure is
used to apportion the value of all other governmental property
(GPm) (MOC/B) . GPm and GPS should be available from the local
or state department of assessments.
Whether G-3 provides a current dollar value or provides
replacement estimate of the total land and facilities required
to serve employee households depends, in part, on how localities
determine values for GPm and GPS. If these values represent
the cost today of replacing facilities, rather than the actual
original cost of these facilities, expressed in current dollars
or otherwise, then GPm and GPS may be much larger than the orig-
inal costs of acquisition and construction. See the discussion
of G-2.1 for other issues that apply here. Also, in the discus-
sion of B-4.1 we pointed out that there was no way of determining
the marginal users, that is, the enterprise whose demand could
only be met by additional investment in business real property.
Therefore business investment in real property was apportioned
over all users. The situation in G-3 is analogous.
-62-
Equation G-4
FTX
Foregone Real Estate Taxes Due to the Institution's
Tax-Exempt Status
FTX = AV (ar) (pt)
FTX = Foregone real estate taxes due to the institution's
tax-exempt status
AV = Assessed value of institutional tax-exempt property
ar = Assessment ratio of local jurisdiction
pt = Local property tax rate
Local governments derive a significant proportion of
their income from local property taxes. When an arts organization
rents property, it may be assumed that the owner of the property
pays property tax. However, tax-exempt arts and cultural insti-
tutions that own and use property for tax-exempt purposes are not
subject to the property tax. Therefore, when a tax-exempt insti-
tution buys a piece of property, that property is, in effect,
taken off the tax rolls and represents lost or foregone local
property tax revenue .
The identification of total foregone real estate taxes pre-
sents a variety of problems. Institutions do not simply buy
property: they may build a concert hall, museum, or so forth.
This may constitute a mixed blessing when viewed from the stand-
point of foregone taxes. Even if the facility could be taxed,
the land might have generated more in property tax revenues had
it been put to some other use.
Conversely, even though non-profit arts organizations do not
pay property tax, the erection or rehabilitation of buildings for
artistic and cultural purposes can have a positive effect of sur-
rounding areas, upgrading property values and thereby increasing
total property tax revenues.
Equation G-4 identifies foregone property taxes in light of
these theoretical and technical difficulties. AV, the assessed
value of exempt property owned or occupied by the institution,
may be obtained from the local tax assessment office, as are
the assessment ratio (ar) , and the local property tax rate (pt) .
The examined institution may make voluntary contributions
in lieu of paying the property tax and/or may pay property tax
on property they own which is not devoted to non-profit purposes.
These payments are counted directly in another equation, G-l.l
(RET-i ) .
-63-
Equation G-5
SSVS
Value of Local Governmental Services Self-Provided
by the Institution
SSVS = Pi + Si + Lj_ + Ti
SSVS = Value of local governmental services self-provided
by the institution
Pi = Total annual cost of institution-provided police and
security services
Si = Total annual cost of institution-provided street
maintenance
Li = Total annual cost of institution-provided lighting
(including lighting of parking facilities)
Tj_ = Total annual cost of trash removal by private company
(does not include janitorial and building maintenance
costs)
In some cases, an examined institution may pay for services
that local government would otherwise have provided. When this
happens, the institution is saving local tax dollars by providing
for itself rather than utilizing government services at taxpayer
expense.
With respect to some specialized services, there are diffi-
culties in estimating what it would have cost government to pro-
vide them had not the institution provided for itself. The audi-
tor's report of the institution will identify what it cost the
institution to purchase these services, and the researcher will
have to make a judgment as to whether the incurred expense would
otherwise have been incurred by government. The terms in equation
G-5 refer to various typical services provided by government that
might have been self -provided by an institution.
-64-
Impacts on Individuals
Up to this point in the User Manual, we have sought to esti-
mate economic effects on ,the business sector and government. We
now estimate some economic consequences for individuals. Appendix
B discusses the multiplier values referred to in the next three
equations.
Equation 1-1
Number of Local Jobs Resulting from Institution-Related
Direct Effects on the Local Business Sector and Government
J = Emps + x(E + OC)
J = Number of local jobs resulting from institution-related
direct effects on the local business sector and
government
Emps = Total number of employees
x = Marginal employment requirement of an additional
dollar's worth of local spending
E = Institution-related direct expenditure in the local
community (see B-l)
OC = Operating cost of government-provided municipal and
public school services attributable to the institution
and its employee households (see G-2)
The equation 1-1 estimates the total number of local jobs
attributable to the institution in terms of total employment
provided by the institution itself and jobs created indirectly
due to the institution's direct local economic effects. In
order to meet demand, local business must invest in facilities,
as noted by equation B-4.1. But at some point firms must also
hire more people due to increased business volume. National
estimates have been made of the marginal employment requirements
of an additional dollar's worth of local spending, x, that is,
the number of new jobs required for each additional dollar of
demand (see Appendix B) . The terms to be multiplied by x are the
total direct local business and governmental expenditures attrib-
utable to the institutions. The resulting figure, taken together
with total jobs directly provided by the institution, yields an
estimate of total local jobs attributable to the institution.
Indirect expenditures are excluded from 1-1 because the deri-
vation of x is based on direct expenditures only. Therefore, this
formulation may significantly underestimate the eventual impact on
jobs. The inclusion of OC assumes that all local governmental
expenditures are local and that governmental expenditures have the
same local impact as private sector expenditures.
-65-
Equation 1-2
PY
Total Local Personal Income Due to Institution-Related
Direct Effects on the Local Business Sector and Government
PY = W + p(E + OC)
PY = Total local personal income due to institution-related
direct effects on the local business sector and government
W = Gross compensation, including FICA, federal withholding,
state withholding, unemployment compensation, and contribu-
tions to pension plans
P = Profit and payrolls per dollar of institution-related
expenditures
E = Institution-related direct expenditures in the local
community
OC = Operating cost of government-provided municipal and public
school services attributable to the institution and its
employee households
Total personal income of local residents attributable to
the institution can be estimated as wages to institutional employ-
ees together with wages to the additional employees identified by
equation 1-2. National estimates have been made of the addition
to payrolls and profits of each additional dollar's worth of demand,
£ (see Appendix B) . Total personal income is estimated as institu-
tional wages to local residents plus personal income as a conse-
quence of total direct demand attributable to the institution. The
coefficient p is likely to underestimate total eventual impact on
personal incomes for the reasons described in connection with the
co-efficient x of equation 1-1. The inclusion of OC in 1-2 assumes
that all local governmental expenditures are local and that govern-
mental expenditures have the same local impact as private
sector expenditures.
66-
Equation 1-3
DG
Durable Goods Purchases Attributable to Institution-Related
Increases in Total Personal Income
DG = k(PY)
DG = Durable goods purchases attributable to institution-
related increases in total personal income
k = Proportion of personal income devoted to purchases of
durable goods
PY = Total local personal income due to institution-related
direct effects on the local business sector and government
(Equation 1-2)
Equation 1-3 relies on the national estimate, k, of the pro-
portion of an individual's total income used to purchase durable
goods from local sources (see Appendix B) , PY was estimated in
1-2.
-67-
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-78-
APPENDIX B
Multiplier and Secondary Spending Effects
The "multiplier effect" describes the process by which
a dollar of primary or direct expenditure in the community
is expected successively to generate some multiple of its
original impact on the local economic base. For example, a
dollar paid to a resident employee of an arts institution
will be spent partly on local goods and services and partly
on products or services from suppliers outside the community.
The portion spent locally goes to local businesses who, in
turn, spend some share locally and the remainder with outside
suppliers, and so on until "leakage" to outside vendors
completely exhausts the initial spending effect. The final
impact of the initial expenditure will be some multiple
varying directly in size with the fraction respent locally
and varying inversely with the amount of "leakage" to outside
suppliers from the local spending cycle. A typical multiplier
value is calculated as 1 where mpc is the "marginal propensity
1-mpc
to consume (that is, the fraction of income spent) locally"
and 1-mpc is the rate of "leakage" into outside purchases.
The larger and more diversified the local economic base,
the more self-supporting the community is likely to be and
the larger will be the proportion of local direct expenditures
retained and respent locally, that is the larger will be
the anticipated multiplier effects. Because we do not have
direct survey evidence on the amount of total business
spending generated locally by local suppliers in the Baltimore
region, we have interpolated an approximate multiplier value
from data for cities of varying size in the U.S.
-79-
TABLE 9
Multiplier Values for Baltimore Arts Study
Assumed Multipliers
m
P
1.818
•
mi
2.857
P
.475
X
.000065
Model
B-2
B-3
1-2
1-1
Range of Multiplier Values
Used in Other Studies*
1.15 - 2.50
2.0 - 4.0
.25 - .66
.00007 - .00009
.031
1-3
Similarly, the larger the local market area and the more
diversified and integrated its economic base, the easier it
can absorb additional local demand from arts institutions '
expenditures with smaller additional requirements for labor
and capital. This means that nip, the marginal employment
requirements of an additional dollar's worth of local
institutions-related spending and m^ , the marginal addition
to payrolls and profits from an additional dollar's worth of
institutions-related spending, will also vary by market size
and can be interpolated from national data on other cities.
Other studies have characterized these respending
coefficients as "multipliers" and used them to estimate the
total of direct and indirect effects by multiplying total
institution expenditures by the multiplier. Equations B-2
and B-3 of this model are intended to estimate indirect effects
only. Therefore, as used in calculations the coefficients
m-[ and mp are reduced by 1.
*See Caffrey and Isaacs, Estimating the Impact of a College
or University on the Local Economy, pp. 44-45; and S.J. Weiss
Employment
to
and E.C. Gooding, Estimation of Differential
Multipliers in a Small Regional Economy
the Federal Reserve Bank of Boston, No.
(Research Report
37, Boston, 1966)
-80-
APPENDIX C
The Employee Survey
Included in this appendix is a sample confidential
survey for distribution to employees and guest artists.
The questionnaire is included for illustrative purposes only
Researchers may choose to add or omit questions depending
on the economic effects they intend to identify and the
extent to which they will utilize data on the general local
population on the assumption that institutional employees
and their households are not dissimilar. We recommend
conducting an employee survey whenever possible. There may
be important respects in which institutional employees are
likely to differ from the general population.
As in the case of survey questions 4 and 9, researchers
will have to include jurisdictional categories and names in
keeping with local and state names and types, for example,
county, parish, township. In addition, institutional
auditor's reports are for the previous fiscal year, while
the employees surveyed are those employed at the time of
the survey. Researchers must make the assumption that the
characteristics of current employees are not dissimilar to
those of the previous year. However, if the number of
employees at the time of the study is different than the
number covered by the auditor's report being used, then
researchers will have to weight results accordingly, using
the last fiscal year's number of employees.
Further, a non-professional might begin designing
the survey instrument by listing all data on employees and
their households that will be required by the equations to
be used. One might also seek the advice of experienced
researchers, perhaps taking advantage of local college
or university resources.
The questionnaire solicits personal information;
response rates may be increased by providing envelopes in
which respondents can return questionnaires.
-81-
SURVEY OF STAFF
The Johns Hopkins University Center for Metropolitan Planning
and Research is assessing the impact of arts and cultural
institutions on the economy of the Baltimore Metropolitan
Area. This study is intended to serve as a national model of
use to other metropolitan areas in evaluating the impact of
their arts and cultural institutions. PLEASE DO NOT IDENTIFY
YOURSELF ON THIS QUESTIONNAIRE. BE ASSURED THAT ALL RESPONSES
WILL BE KEPT IN STRICTEST CONFIDENCE. We appreciate your
cooperation.
PLEASE RETURN COMPLETED QUESTIONNAIRE TO THE GENERAL MANAGER'S
OFFICE IN THE ENVELOPE PROVIDED.
If you are resident full or part-time staff with this institution,
please answer questions 1 through 10.
If you are a guest artist with this institution, please begin
with question 11.
1. Are you employed at this institution full time or part time?
full time part time
2. How many persons are in your household, including
yourself?
3. How many of the children in your household attend public
elementary or secondary schools?
4. Where is your residence? (CHECK ONE)
a) City
b) County
c) Other State County
d) Out-of-State
5. In what type of housing do you now reside?
rental housing
home you own or are buying
If you own your home or are buying, approximately what
was your last annual property tax bill? $
What is the total annual salary income before taxes and
payroll deductions of ALL PERSONS (including yourself)
who live in your household? $
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8. What is the total annual non-salary income (rents,
interest, dividends, etc.) of ALL PERSONS (including
yourself) who live in your household? $
9. What percentage (0%, 10%, 20% 100%) of your
Total Household income, after taxes, do you estimate
is spent within:
a) City
b) County
c) Other State County
d) Out-of-State
10. For All Members of Your Household, please estimate the
aggregate monthly average balance in State banks, credit
unions, and savings and loans:
checking accounts $
savings accounts $
THE FOLLOWING QUESTIONS ARE FOR GUEST OR NON-RESIDENT ARTISTS ONLY
11. If you a guest artist, how many days will you stay in
the metropolitan area on this visit ?
12. Approximately how much will you, your family and those in
your entourage, spend while in the metropolitan area?
13. Approximately what proportion of this money will be spent
in the city as opposed to the suburbs?
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APPENDIX D
The Audience Survey
There are great problems associated with the use
of self-administered audience surveys in developing meaning-
ful data on audience expenditures. Distributed and collected
at the arts organizations, these survey instruments ask the
respondent to report total expenditures associated with
attendance at the arts event apart from ticket or admission
costs. A major problem is the variability of audiences with
program content and location of event. The exhibits at
museums may vary appealing to a somewhat different audience
each time. Conversely, heavily subscribed performing arts
organizations may be attended by the same audience of
subscribers regardless of the program. In all cases, a
difference in the time, day of the week, and location of the
events may effect audience composition.
Aside from the general problem of assuring "representative"
audiences when sampling only a few program events, there are
specific problems associated with the identification of ancillary
expenditures. If the respondent will incur expenses after the
performance or museum visit, he or she may not know how much
they will spend, and may not have even decided yet to incur
expenses. Respondents may be able to accurately cite only the
expenses they incurred up to the time they were asked to
complete the survey.
When individuals incur expenses, they typically are due
to costs incurred not just by themselves, but by someone
else, such as their spouse, children, relatives, or friends.
Thus, responses can only be meaningfully interpreted as
average expenditures by parties or groups of various sizes.
This would seem to require respondents to identify party size
or otherwise to indicate the number of persons covered by
the expenditures reported. If the respondent did not pay the
group expense — if, for example, a spouse or friend did —
then he or she may not know how much was spent and may not
be willing to find out. Our procedure calculated total
ancillary audience expenditures from data on total expenditures
by party, stratified by party size.
There are difficulties associated with the design and
implementation of self -administered audience surveys. This
report is not the proper vehicle by which to explore these
issues. We raise them now in the belief that our procedures
are the most sophisticated to date with respect to the use of
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self-administered audience surveys to identify audience
expenditures. Neophytes would do well to secure the
services of survey research professionals. They might
consider utilizing the talent associated with local institu-
tions of higher learning or local planning departments. We
believe that further research needs to be done on alternative
strategies for estimating audience expenditures, perhaps in-
cluding interviews and questionnaires distributed at the
surveyed events to be completed and returned by mail after
respondents return home.
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APPENDIX E
Total Full-Time Employees and Full-Time Equivalents
In several equations, we suggest that researchers
aggregate part-time employees into full-time equivalents,
and/or treat part-time employees separately from total
full-time employees. These models require data on the total
number of individual jobs, not the total number of individ-
uals who may fill those jobs, when individuals are replaced
during the year. A large turnover in various positions will
cause further complication.
You will find, especially when employing multi-
jurisdictional analysis (see Appendix F) , that employee
residence is central to the task of distinguishing governmen-
tal impacts. In the circumstances in question, you will have
to use the payroll records of those who had worked at a par-
ticular position during the year in question to determine that
X% of those employed in that position resided in one jurisdic-
tion or another. This information can then be used to apportion
high turnover payroll slots among the local units of govern-
ment. Part-time employees will have to be aggregated into
full-time equivalents and then apportioned.
Part-time employees are of two types, those who
work for the entire year or season but only part-time and
those who work full-time but only for part of the full
institutional year or season, for example, actors who may
be part of a repertory company but appear in only one play.
In the latter case, researchers should make sure that individ-
uals are employees and not guest artists on contract. Guest
artists are treated separately by equation B-1.3.
Researchers will have to use judgment in aggregating
part-time employees into full-time equivalents. Individuals
who work part-time for the entire year can be aggregated
together by the proportion of full-time hours they work dur-
ing the year. For example, 5 individuals may work 15 hours a
week and the institution may consider 4 0 hours a week to be
full time. Therefore, the number of full-time equivalents
is 5(15/40). (This example presupposes a 52-week base full-
time year. )
Individuals who work full-time but for only part of the
full institutional year can be similarly aggregated. For
example, 5 individuals may work for 4 weeks for an insti-
tution that considers 48 weeks to be full-time. Therefore, the
number of full-time equivalents is 5(4/48).
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We do not believe that volunteers and Comprehensive
Education and Training Act (CETA) personnel should be
included as employees. The model focuses on individuals
receiving compensation from the institution and on those
who are in positions that would not have existed were it
not for the examined institution. Volunteers do not meet
the former condition and CETA workers do not meet the latter
CETA positions are distributed among communities for
allocation as the community sees fit. Presumably, all
positions would have been utilized by the community even in
the absence of the examined institutions. This should not
be taken as suggesting that volunteers and CETA workers
do not have an economic impact. They do, especially in
cases where programs and services would not have been
available had there been no volunteers or CETA workers.
-87-
APPENDIX F
Adaptations of the Model for Multi-Institutions
and Multi-Jursidictions
In some instances, it may be of interest to a regional
arts organization or some other agency to analyze the economic
impact of a collection of arts and cultural organizations on
a community. In this case, the data described in the Manual
for a single-institution analysis must, of course, be gathered
for all organizations in the sample and the total impacts
calculated from the specified equations by adding up the
individual impacts of each of the component institutions.
Since accounting procedures are even less standardized
among tax-exempt organizations than among ordinary corporate
organizations, definitions of expenditures, classification of
revenues and contributions, classification of employees, and
other data items required by the equations may vary from one
arts institution to another. The researcher should inquire
about the precise definitions used by each institution at
the time the primary data are collected and treat uniformly
such items as: sales and acquisitions for museum collections;
cross-purchase of goods or services between institutions (such
as an opera company's employment of the local symphony for
its performances) ; and the capitalization of certain accounts
such as contributions to a building program. The important
principles are to avoid double-counting of expenditures in
the records of more than one institution and to standardize
as much as possible the accounting for major categories of
capital and operating expenditures.
The attached schema displays the changes in the 30
equations of the model required to account for multiple
institutions by using the subscript .i to denote a particular
n
institution and summation signs (E) to indicate where
i=l
impacts must be totalled over n institutions.
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Similar adaptations must be made in the equations
where one is concerned with identifying differential impacts
of arts institutions across multiple jurisditions . This
situation arises most frequently in metropolitan areas
where employees, audiences, and suppliers are distributed
throughout several political jurisdictions. Where multiple
jurisdictions are of interest, it is necessary to identify
the relevant items on the employee and audience surveys
by jurisdiction. For example, real estate taxes paid
by employees must be attributed to individual property
tax rates in each jurisdiction. Similarly, the allocation
of sales tax revenues, school aid, purchases from local
suppliers, and the like must be distinguished by location.
In some cases, however, there may be no reason to believe
that impacts vary by jurisdiction (as, for example, the
local respending fraction) so that a single parameter can
be used in each institutional equation.
In the attached schema, equations that may be
distinguised by jurisdiction are indicated with the sub-
script j_ and the total area impacts are indicated by sura-
m
ming over m jurisdictions (I). It should be noted
i=l
that disaggregating economic impacts among individual
jurisdictions yields information of little value in some
cases. For example, since localities within a metropolitan
area are economically integrated, though politically
distinct, attempting to trace secondary business expenditures
to particular jurisdictions does not make as much sense
as identifying an aggregate regional impact. This
occurs because, while it is possible (though unwieldy) to
identify direct expenditures by jurisdictions, one can
have relatively little confidence that the secondary im-
pacts of these expenditures will remain in the locality,
and more precise information on suppliers1 secondary
expenditure patterns is difficult to obtain.
However, disaggregation of public sector (government)
impacts is meaningful and may have utility in circumstances
where the regional distribution of support for the arts is
a policy interest. Since each disaggregation (by jurisdiction,
by institution) adds substantially to the tasks of data
collection and analysis, the researcher should consider
whether the extra detail in the resulting information will
be worth these additional costs.
-89-
Equations Adjusted for Multiple Institutions
Shown below are only those equations that must be
modified to reflect calculations over more than one institution
Equations not listed below remain the same as those described
in the text for a sinqle institution.
n
'I~
Et= E Z, (TE- - W. - Transf. - T .)
1 1 ei 1 xi
1=1
n
E = E f . (W + .5 Yric )
e i=i X eni nSi
V " <?i(GDi>
i=i
n
E = E a. (TA. )
1 = 1
n
E = E v- (TVD. )
v ■ ■ 1 i
1=1
n
CB= E { (1-t) (TD.+ (TD J (Emps. ) } +(l-d){ DDH + (DD ) (Emos.- )
i=i + cbv(E)}-} e 1 e
n
NBV=E IBi
i=i
n
RETe= E Emps^hjJ (pt) (TAR/R)
i=i
n
MOC= E (EHHi/Pop) (B)
i=i
n
PSOC= E (C./TC)SB
i=l X
n
FTX= E AV. (ar) (pt)
i=l 1
P
SSVS= E P. + S. + L. + T,
. . l l l l
1=1
n
J = E Emps- + x(E. + OC. )
i=l X
n
PY = E W. + p(E. + OC. )
,1^1 l
1=1
-90-
•* U. S. GOVERNMENT PRINTING OFFICE : 1978 O - 259-594
Equations Adjusted for Multiple Jurisdictions
Shown below are only those eauations that must be
modified to reflect calculations over more than one jurisdiction
Equations not listed below remain the same as those described
in the test for a single jurisdiction.
m
ET = E Z (TE . - W - Transf . - T )
I j=1 1 ej D Xj
m
E = E f (W + . 5Y . )
e . , en. ns]'
D=l 3
m
E = E g(GD )
g j=l ^
m
E = E a(TA.)
a • -, J
3=1
-m
E = E v(TVD.)
v j-i ]
m
RP = E (E . /TBV . ) (AV . /ar . )
j=l 3 1 3 J
m
RET = E Emps . (h. ) (pt . ) (TRA./R. )
j=l 3 3 ~ 3 J 3
m
RET, = E pt (E ./RP . ) (AV.)
b j=i J 3 3 3
m
ST = E st.(STR.)(E /TBV.)
j=l 3 3 j :
m
YT = E (TYT./HH.) (i) (Emps •)
m
SA = E PS . + OR .
j = l 3 3
m
MOC = E (EHH./Pop.) (B.)
j=l 3 3 3
m
PSOC = E (C-/TC . ) (SB. )
j=l ^ 3 3
m
GP = E (GP_ )(MOC./B ) + (GP ) (PSOC -/SB.)
j=l mj ^ j Sj 3 j
m
FXT = E AV. (ar .) (pt.)
j=l 3 : 3
m
SSVS = E P^+S.+L 4- T .
j = l D 3 j ^
-91-
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