.’h Division Report ~6 

~-~ >nomic Impacts of Arts National Endowment 

for the Arts 

and Cultural Institutions: 

November 1977 

A Model for Assessment and 

a Case Study in Baltimore 

NATIONAL
 

ENDOWMENT
 

FOR THE
 

ARTS 

A Report by David Cwi and Katherine Lyall, The Center for Metropolitan Planning and Research, The Johns Hopkins University, October 1977 
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 proposals 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 institutions in many communities. The model is made up of 30
 

equations which may be modified as special community characteristics 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 application 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 government~, as well as various social, institutional and economic conditions; and may be considered suitable
 

for general application.
 

Research Division
 

NATIONAL;	 National Endowment for the Arts 

October 1977 ENDOW?.~,i~ENT,, 

FOR THE 

ARTS 

i
 
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: (i) 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
 

iii
 
CONTENTS (continued)
 

Secondary Impacts
 

Impacts on Government
 

Costs to Local Government
 

Impacts on Individuals
 

Appendices 

APPENDIX A: Guide to Model and Data Sources 

APPENDIX B: Multipliers and Secondary 

Spending Effects 

APPENDIX C: The Employee Survey 

APPENDIX D: The Audience Survey 

APPENDIX E: Total Full-Time Employees and 

Full-Time Equivalents 

APPENDIX F: Adaptations of the Model for 

Multi-Institutions and MultiJurisdictions 

Page
 

40
 

49
 

58
 

65
 

68
 

79
 

81
 

84
 

86
 

88
 

iv
 
INDEX TO TABLES AND FIGURES
 

T-I A Model to Estimate the Economic Impact of the Arts
 

T-2 List of Equations
 

F-I The Baltimore Metropolitan Area
 

T-3 Eight Baltimore Arts Institutions: Percentage


Audience from Outside the Region
 

T-4 Direct Tax Payments to Local Government by Eight
 

Baltimore Arts Institutions
 

T-5 Alternative Estimates of Foregone Property Taxes on
 

Real Estate Property Owned or Occupied by the Eight
 

Baltimore Arts Institutions, 1976
 

Summary of Economic Effects, 1976
 

Summary Data for Eight Arts Organizations in
 

Baltimore SMSA, Fiscal Year 1976
 

T-8	 Government Revenues of Eight Arts Institutions,
 

Baltimore SMSA, 1976
 

T-9	 Multiplier Values for Baltimore Arts Study
 

5
 

6
 

i0
 

16
 

18
 

20
 

25
 

27
 

28
 

8O
 

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 entrepreneurs, 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 i~en~ify, r~spectively, 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 G1 requires,
 

among others, the solution of G-I.I and this equation requires,
 

in turn, G-I.I.I and G-I.I.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).
 

-i­
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. Conversely, arts institutions and their employees require governmental 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, represent a demand for local goods and services. To meet this
 

demand, local businesses not only invest in property and inventory, 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 conservative, 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 inclusive, 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 institution’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.
 

(I) It cannot be inferred from this or any other currently 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 institutidns 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.
 

(311 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 i0 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
 

 

TABLE 1
 

A Model to Estimate the Economic Impact of the Arts
 

Business Sector Impacts
 

B-I E =Ei + Ee + Eg + Ea + Ev
 

B-I.I Ei = z(TEi - W - Transf-Tx)
 

B-I.2 Ee = (f) (Wen + .5 Yns)
 

B-I.3 Eg = g(GD)
 

B-I.4 = a(TA)
 Ea 


B-I.5 Ev 
= v(TVD)


B-2 BP = (mp - i) (E)
 

B-3 BV = (.45) (E) (mi - i)
 

!
 

B-4 BI=RP + Inv
 

B-4.1 Rp = (E/TBV) (AV/ar)
 

B-4.2 Inv = ir (E + BP + BY)
 

B-5 CB = (l-t)[TDi + TDe (Emps)]+
 

(l-d) [DDi + DDe (Emps)+
 

cbv(E +BP +BY)]
 

B-6 NBV = IB
 

Government Sector Impacts Impacts on Individuals 

G-I GR = RETX + ST + YT + SA + OR I-I J = Emps + x(E+OC) 

G-I.I RETX = RETi + RETe + RETb I-2 PY = W + p(E+OC) 

G-I.I.I RETe = Emps(H) (pt) (TRA/R) I-3 DG = k(PY) 

G-I.I.2 RETb = (RP) (ar) (pt) 

G-I.2 ST = st(STR) (E/TBV) 

G-I.3 YT = (TYT/HH) (Emps) 

G-I.4 SA = PS + OR 

G-I.4.1 PS = N(C) (SE) 

G-2 OC = MOC + PSOC 

G-2.1 MOC = B(EHH/POP) 

G-2.2 PSOC = (SB) (C/TC) 

G-3 GP = (GPm) (MOC/B) + (GPs) (PSOC/SB) 

G-4 FTX = AV(ar) (pt) 

G-5 SSVS = Pi  ̄ + Ti + Si + Ll 

For multi-institution and multi-jurisdictional analyses, appropriate subscripts must
 

be added. See Appendix G.
 
 

Table 2
 

List of Equations
 

Economic Impacts on Local Business
 

Direct Impacts
 

Total institution-related local expenditures (E)
 

Local Institutional Expenditures for Goods and
 

Service~ (E~)
 . ~
 B-1.2 Direct Expendltures in the Local Community by
 

Institutional Employees (Ee)
 B-1.3 Local Expenditures by Guest Artists (E~)
 

B-1.4 Local Expenditures by Local Audience a~d Patrons (Ea)
 B-I.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 (BD)
 

B-3 Local Business Volume Sti~ulated biT 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)


Expansion of the Local Credit Base Attributable to
 

Institution-Related Deposits (CE)
 

Local Business Volume Unrealized Due to Institution-


Related Enterprises (NBV)
 

Economic Impacts on Local Government
 

Total Institution-Related Local Tax Revenues (GR)


Local Real Estate Taxes Paid by the Institution,
 

Its Employees, and Local Businesses Serving Both
 

(RETX)
 

Local Real Estate Taxes Paid by Institutional
 

Employees (RETe)
 Real Estate Taxes Paid by Local Businesses on
 

Real Property Committed to Support Institution-


Related Business (RETb)


G-I.2 Local Sales Tax Revenues Resulting From Institution-


Related Direct Expenditures (ST)
 

G-1.3 Local Income Tax Revenues Paid by Institutional
 

Employees (YT)
 

G-I.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 Institutional 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)
 

I-2 Total Local Personal Income Due to Institution-


Related Direct Effects on the Local Business
 

Sector and Government (PY)


I-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 I, 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 Statistical 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 manufacturing 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
 
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 nonagricultural 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 officeshop-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 unprecedented sixth design award in seven years.
 

Baltimore City is unable, under terms of the state constitution, 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.
 

-Ii­
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.
 
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 separately as well as identifying, when meaningful, each institution’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-jurisdictional 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 schoo], 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 discussion 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 attendance 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 a~ts institution under study. This percentage ranged from 24% of out-ofregion 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 institutions 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 undoubtedly 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 ­
T~BLE3
 

Eight Baltimore Arts Institutions: Percen~tage
 

Audience From Outside the Region
 

% Audience From
 

Out-of-Region
 

Baltimore Opera 5%
 

Walters Art Gallery 2
 

Baltimore Symphony 3
 

Morris A. Mechanic Theatre 6
 

Baltimore City Ballet 5
 

Baltimore Museum of Art 14
 

Center Stage 2
 

Arena Players NR
 

% of Out-of-Region Audience
 

Who Came Specifically to
 

Attend Institution
 

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 enterprises operated by the eight institutions in our Baltimore sample,
 

we decided not to count any of the $280,820 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 activities 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 significant 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 institutions in our sample, and we assess their cost to local government. 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 personnel, 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-ex@mpt
 

status, they are nonetheless responsible for $151,767 in tax
 

payments to the six local governments in the SMSA. The sources
 

ofthese 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.
 

TABLE4 

Direct Tax Payments to Local Government

Eight Baltimore ~rts 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 GI.I) $99,537 

Locally retained sales on institutionrelated business volume* (equation G1.2) 5,062 

Local income tax revenues attributable to 

institutional and other business employees 

(equation GI.3) 27,558 

State aid to local public schools attributable 

to children of institution-related families 

(equation GI.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 institutions 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 retained 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 institutional 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 $i00,000 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 institution owned or rented tax exempt property together with property 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 institutions, 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
 

 

~TABLE5
 

Alternative Estimates of Foregone Property Taxes on
 

Real Property Owned or Occupied by the Eight Baltimore
 

Arts Insitutions, 1976
 

Taxable Value* Foregone Property Tax
 

All currently exempt
 

property (land and
 

buildings) would revert
 

to tax yielding uses. $ 1,562,300 $ 93,738
 

All city-owned property
 

(land and buildings)
 

would remain in exempt
 

uses, but other property
 

would revert to taxable
 

uses.
 $ 996,080 $ 59,754
 

Source: Baltimore City assessment records, 1976-77.
 

* 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
 

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
 

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 opportunities. We estimate that 1175 full-time jobs in the Baltimore
 

area are produced by the activities of the eight arts organizations in our sample; 404 of these are directly with the
 

institutions, and 771 are created as a consequence of institutionally 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 organizations (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;
 

$400,000 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 availability 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 decisions, 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 experience with respect to the impact of artistic and cultural amenities 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 Philadelphia 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 Organi~zation (Washington, D.C.,
 

1975)
 
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. Because 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); representatives 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 energetic. Reference to the arts is used, then, as an important
 

indicator of a generally favorable quality of life.
 

However, there was universal agreement among respondents 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 distribution. 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 availability of the local labor force, wage rates, the availability
 

of utilities, the size of the site, road access, transportation 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 personnel, 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 respect 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 frown 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

-23­
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 relocation. 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 preference. While few want to live in a place with no cultural
 

ambience, this does not mean that executives who are interested 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. Generally, executives were loath to relocate to cities with reputations 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, recreational 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 particular, 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
 

Total direct expenditures of the 8 institutions for goods and services
 

Of which purchased locally
 

Employee household disposable income
 

Of which spent locally
 

Total audience spending (other than ticket
 

price)
 

Of which local audiences spent
 

Of which out-of-region audiences spent
 

Spending by guest artists
 

Secondary business volume generated by suppliers
 

and their employees
 

Current value of backup inventory, equipment,
 

and property
 

Institutions-related tax payments to local
 

government
 

Value of local government services to institutions-related employees and their households
 

Foregone property taxes on tax-exempt property
 

Total local government contributions to the 8
 

arts institutions
 

Number of full-time jobs in Baltimore SMSA
 

attributable to institutions-related activity
 

Personal incomes generated by institutions-


related business~volume
 

Fiscal Year 1976
 

$ 5,344,754
 

2,405,026
 

6,701,479
 

4,422,976
 

4,515,993
 

2,624,601
 

1,891,392
 

68,247
 

18,499,454
 

5,746,743
 

151,767
 

678,612
 

59,765
 

1,578,545
 

1,175
 

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 example 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 institution’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 institutions.
 

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 sufficient 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 institution. 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 proportion of the aggregate local impact of the examined institutions 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.
 

-2 6 ­
 

 

 

TABLE 7
 

Summary Data for Eight Arts Organizations in Baltimore SMSA, Fiscal Year 1976
 

Total Direct Expenditures
 

Labor (wages & salaries)
 

Goods & Services
 

Taxes
 

Average Percentage Non-Labor
 

Expenditures of Institutions
 

Made in SMSA
 

Total Local Paid Attendance,
 

1976 Season
 

Total Out-of-Region patrons*
 

Average Expenditures per Local
 

Party Other Than Ticket Price**
 

Average Expenditures per Out-of-


Region Party Other Than Ticket
 

Total Government Revenues Received
 

by Eight Institutions, 1976
 

Federal
 

State
 

Local (city & county)
 

Total Number of Guest
 

Artist Days
 

Total Over
 

Ei@ht Institutions
 

$	 9,418,304
 

4,041,222
 

5,344,754
 

32,328
 

47%
 

718,000 patrons
 

43,000 patrons
 

$6.60
 

$30.32
 

$ 2,320,278
 

$ 368,121
 

$ 373,612
 

$ 1,578,545
 

1,913 days
 

High & Low Values for
 

Eight Institutions
 

$80,000 - $2,710,000
 

$24,000 -- $3,117,000
 

$ 0 - $2,271,000
 

$ 8,128 - $ 24,000
 

25% - 8%
 

7,500 - 201,000 patrons
 

1,200 - 28,000 patrons
 

$ 3.85 - $15.65
 

$11.80 - $48.60 

$2,500 - $1,112,958
 

$ 0 - $ 150,000
 

$ 0 - $ 197,000
 

$ 0 - $1,012,000
 

0 - 870 days
 

*Includes only individuals indicating that they came to Baltimore specifically to use the institution.
 

**Averaged over all eight institutions and all party sizes.
 
 

TABLE8
 

Government Revenues of Eight Arts Institutions
 

Baltimore SMSA, 1976
 

Federal* State Local** 

Baltimore Museum 

of Art $56,401 $44,112 $i,012,445 

Morris A. Mechanic 

Theatre - 2,500 -

Arena Players 7,500 - 12,000 

Center Stage

Theatre 75,000 72,000 66,000 

Walters Art 

Gallery - i0,000 157,500 

Baltimore Opera 76,000 31,000 44,000 

Baltimore 

Symphony 150,000 197,000 266,000 

Baltimore 

Ballet 3,220 17,000 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: i. 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 distributed, 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 development of cultural policy, these examples highlight the potential
 

consequences of placing inappropriate emphasis on "return on
 

investment" criteria.
 

-29­
USER }£ANUAL
 

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 strategies for solving particular equations. The mathematics
 

are not complex. A number of equations -- B-l, B-4, G-l,
 

G-I.I, G-I.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 equation used to determine that factor. Thus, B-I leads us to a
 

series of equations on which it depends, B-I.I through B-I.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 i, which summarizes 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 individuals. All of the impacts are estimated in dollar terms except
 

the employment component, equation I-l, 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-I.4 + B-I.5
 

Total estimated local expenditures
 

for staff and guest artists B-I.2 + B-I.3
 

Net direct and secondary institution-


related business volume (B-I + 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-I)
 

-30 ­
We should also point out that the value of business investment, 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 expenditures, 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 individuals 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-I.2 and
 

G-I.3. However, equations B-5, G-I.I.I, G-I.4, G-I.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 estimated 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 concessions 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 institution 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 interest 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 equations 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 expenditures made in a given fiscal year by the institution,
 

as well as its employees, guest artists, and audiences.
 

Equation B-I
 

E
 

Institution-Related Local Expenditures
 

E = Ei + Ee + Eg + Ea + Ev
 

Ei = Local expenditures by institution (B-I.I)
 

Ee = Local expenditures by employees (B-I.2)
 

Eg = Local expenditures by guest artists (B-I.3)


Ea = Local expenditures by local audience and patrons (B-I.4)
 

Ev = Local expenditures by non-local audiences and other
 

users (B-I.5)
 

Equation B-I sums the five separate direct expenditure
 

effects identified by equations B-I.I through B-I.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-I.I
 

Ei
 

Local Institutional Expenditures for Goods and Services
 

Ei = z(TEi - W - Transf. - Tx)
 

z = Percentage of expenditures for goods and services
 

made to local firms
 

TEi = 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
 

T = Taxes and fees to government other than those appearing
 x
 

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-I.I 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 expenditures.
 

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 Ei.
 

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 expenditures 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-I.2
 

E
e
 

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
 

Wen = Total net institutional salaries
 

v = Employee household non-salary income: income from rents,


-ns
 dividends, interest, and other sources
 

B-I.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 Wen, total net
 institutional salaries, and add 1/2 of total employee household 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 institution. 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-I.2 arbitrarily 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-I.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-I.3
 

Eg
 

Local Expenditures by Guest Artists
 

Eg = g (GD)
 

Eg = 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 restaurant bills and make other local expenditures. B-I.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 ~, average daily expenditures by guest artists,
 

is determined by dividing the total dollars guest artists report that they spend in the community by total days they report
 

staying in the community. Presumably the guest artists available to the researcher will be those appearing at the institution during the period in which the researcher is gathering
 

data for the economic impact model. These guest artists comprise 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 convenient to simply add a separate set of questions for guest artists to the employee survey; see Appendix C.) Responses collected may be assumed to be typical of average daily expenditures by all guest artists.
 

GD is determined by multiplying the total number of guest
 

artists by their total days in the community. (This information is available from institutional internal records.) B-I.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-I.4
 

E
a
 

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-I.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) b--y 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 expenditures on a per person basis. Individuals commonly attend
 

arts performances in parties of two or more and there is considerable 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 forth7 and the total attendance size
 

figures, T__A, 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
v 

Equation B-I.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
 

= 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 direct institution-related expenditures. B-I.5 is used to determine 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 [ 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 expenditures 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 procedure 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 attractive as a place to visit and, further, that the institution is
 

helping to favorably advertise the community to others. Ultimately, these factors can translate into economic terms.
 

-39­
Secondary Impacts
 

Equation B-I 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 discussed in Appendix B.
 

Equation B-2
 

BP
 

Purchases by Local Businesses From Local Sources in Support of
 

Instit~ution-Rel~ated Expenditures in theLoc~alEconomy
 

BP = (mp - i) (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-I, represents institution-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 additional purchases of their own. The total of these secondary purchases 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 B__P, the


total eventually spent by local firms as a consequence
 

of E. Values for mD reflect one’s knowledge of the size and


diversification of %he 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 of PBP. Appendix B cites
 

typical values for mp, and briefly explains the technique


of multiplier analysls and development.
 

-40­
Equation B-3
 

BV
 

Local Business Volume Stimulated by Institution-Related Income
 

Spent by Local Business Employees
 

BV = (.45)(E)(mi-l)
 

BV = Local business volume stimulated by institution-related
 

income spent by local business employees
 

mi = 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 expenditures, 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-I) by 45% to estimate
 

institution-related direct expenditures received as income
 

by the employees of local businesses. Multiply also by mi,
 the respending coefficient, which estimates the proportion
 

that is eventually respent locally for goods and services.
 

Values for mi are based on national data (see Appendix B).


As noted in the discussion of equation B-2, mi 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 +
 

AV 

ar 

total local wholesale sales + the value added to raw 

materials by local manufacturers) 

= Total assessed valuation of business real property 

= 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 revenues 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 market value used in determining assessed valuation. When AV
 

is 100% of market value, ar is i.
 

-44­
Equation B-4.2
 

Inv
 

Value of Business Inventory Committed to Support
 

Institution-Related Direct and Secondar[ 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 + B_~V, the sum of direct and indirect institutionrelated--exp~ditures in the community.
 

There is a direct relationship between gross sales and the
 

value of inventory. The value ir is the local inventory-tobusiness volume ratio, calculated as the ratio of the value of
 

end-of-year inventory to gross sales; i__~r, 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 BV 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 = (l-t) [TDi+(TDe) (Emps)] + (l-d) [DDi+DDe(Emps)+cbv(E+BP+BV)]
 

CB = Expansion of the local credit base attributable to
 

institution-related deposits
 

t = Local time deposit reserve requirement
 

TDi = 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
 

DDi = Average daily balance in institution demand (checking)
 

accounts
 

DDe = 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 businesses 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 reser--ve requirements, so that l-t or l-d indicate
 

the percentage of deposits in time demand accounts that may be
 

used by financial institutions for loans. TDi and TD_~ are,


respectively, institutional and employee household time (savings)
 

accounts. DD_~i and ~ 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 en~ and middle of the month checking account
 

balances as indicated by institutional checking account statements, thereby taking a sample of 24 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 ratio, reflecting cash held in reserve by businesses as a percentage of total business volume. For example, in the Baltimore
 

study, a value of .028 was assigned to cbv. This value was calculated as an average of 1965 and 1972 ratios determined from
 

U.S. Statistics of Income, Internal Revenue Service, U.S. Corporate Tax Returns, 1965, 1972, Table 5.2, p. 1972. We averaged ratios for two years to mitigate the cyclical effects of
 

the most recent (1972) data which reflect the recession conditions of that period.
 

The issues previously raised in discussion of the impact of
 

employee households (see B-I.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 institutional 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 government, focusing primarily on the effects that can be most readily 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 institutions.
 

Equation G-I
 

GR
 

Total Institution-Related Local Tax Revenues
 

GR = RETX + ST + YT + SA + OR
 

GR = Total institution-relatedlocal tax revenues
 

RETX = Real estate taxes paid bythe institution, its employee
 

households, and local businesses serving both (see G-I.I)


ST = Local sales tax revenues resulting from institutionrelated direct expenditures (see G-I.2) 

YT = Local income tax revenues paid by institutional employee 

SA 

households (see G-I.3)

= State aid to local government attributable to institutional 

employee households (see G-I.4) 

OR = Other local revenues attributable to the institution and 

its employee households (see discussion of G-I.4) 

G-I sums the institution-related local tax revenues 

identified by the equations G-I.I through G-I.4. In this
 

sub-set, two equations depend in turn on still others:
 

G-I.I requires G-I.I.I and G-I.I.2 while G-I.4 requires G-I.4.1.
 

-49­
Equation G-I.I
 

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
 

botlh
 

RETi = Local real estate taxes paid by the institution
 

RETe = Local real estate taxes paid by institution employee
 

households (see G-I.I.I)
 

RETb = Local real estate taxes paid by local businesses


serving the institution and its employee households
 

(see G-I.I.2)
 

G-I.I 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.
 

RETi 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 RETi 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 RETi as well as RETe and RETb,
 the values for which are derived by solving equations G-I.I.I
 

and G-I.I.2.
 

-50­
Equation G-I.I.I
 

RETe
 

Local Real Estate Taxes Paid by Institutional Employees
 

RETe = Emps (h) (pt) (TRA/R)
 

RETe = 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.l.l 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 residential 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 they 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 institution. 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 percentage of part-time employees who own a home and the number of
 

full-time equivalent personnel residing locally, G-I.I.I can be
 

applied to part-time employees separately to determine their
 

local property tax contribution.
 

Equation G-l.l.l 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-I.I.I.
 

-51­
There are at least two issues which must be raised
 

in connection with G-I.I.I. 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 l-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-I.I.I 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-I.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 G-I.I.2
 

RETb
 

Real Estate Taxes Paid by Local Businesses on Real Property
 

Committed to Support Institution-Related Business
 

RETb = (RP) (ar) (pt)
 

RETb = 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
 

= The ratio of assessed valuation to full market value
 

= Business and property tax rate
 

Equation G-I.I.2 is a variant of equation B-4.1, which
 

identified RP, local business real property committed to
 

support institution-related direct expenditures. G-I.I.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-I.I.2.
 

If the local community taxes inventory apart from business real property, G-I.I.2 can be used to identify taxes
 

paid on business inventory, Inv, committed to support institution-related business by substituting Inv for RP (see B-4.2)
 

together with the correct assessment ratio and tax rate.
 

G-I.I.2 does not estimate the real estate taxes paid by employees in jobs created indirectly by institution-related
 

direct and indirect effects on business identified by the
 

B-series models (see Model I-l).
 

-53­
 

Equation G-I.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-I.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 percentage of a community’s total business volume for that year (see
 

B-4.1). G-I.2 assumes that if institution-related direct expenditures 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 revenues 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 revenues 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-I.2 underestimates total eventual sales taxes attributable
 

to the institution, since it does not take into account secondary
 

expenditure effects BP or BY (see B-2 and B-3).
 

-54­
Equation G-I.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 jurisdiction
 

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 different rate than residents of the local jurisdiction. In this
 

case, G-I.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-I.3 assumes that each institutional 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-I.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-I.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-I.3 gives the third factor in total local tax
 

revenues related to the institutions (G-l).
 

-55­
Equation G-I.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-I.4, the fourth equation needed for G-I, estimates total
 

state aid attributable to institutional employee households as
 

the sum of state per pupil school aid, P__S, and other per capita


state revenues. PS is estimated by equation G-I.4.1, (see
 

discussion of employee households at the beginning of manual).
 

G-I.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 population or by eligibility group. State aid attributable to employee 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-I.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-I.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 num-~er 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 importantly, resources devoted to the arts become unavailable to government 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
 

ODerating 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 operating 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 (Excludin@ 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 services 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 services.
 

Equation G-2.1 apportions to the institution and its employee households their share of local governmental operating expenditures in such areas as police and fire protection, library services, sanitation, and, in general, all areas except public education, 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. Neighborhoods 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 allocation of costs to local government be weighted? Social service
 

costs provide a particularly strikigg example. These costs often


represent a major portion of a local government’s operating budget. 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 disproportionate cost on local government were known, appropriate questions 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 governmental costs. EHH/POP represents employee households as a percentage 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-I.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-


SB 

al employee households 

= Local public school operating budget, excluding revenues 

from non-local sources 

C 

TC 

= Number of children in employee households attending 

local public primary and secondary schools 

= 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 department 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-I.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 toEmplo~yeeHouse~holds
 

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
 

S-2.1)
 

B = Local operating budget excluding public school costs
 

and non-locally generated revenues
 

PSOC = Public school operating costs attributable to institutional 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 original costs of acquisition and construction. See the discussion
 

of G-2.1 for other issues that apply here. Also, in the discussion 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 institutions that own and use property for tax-exempt purposes are not
 

subject to the property tax. Therefore, when a tax-exempt institution 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 presents 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 standpoint 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 surrounding 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. A__V, 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-I.I
 

(RETi )  ̄
 

-63­
Equation G-5
 

ssvs
 

Value of Local Gove~rnmental Services Self-Provided
 

by ~the Institution
 

SSVS = Pi + Si + Li + 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) 

Ti = 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 difficulties in estimating what it would have cost government to provide them had not the institution provided for itself. The auditor’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 estimate 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 I-i
 

J
 

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 I-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, ~, 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 attributable 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 I-i because the derivation 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 an-~ that governmental expenditures have the
 

same local impact as private sector expenditures.
 

-65­
Equation I-2
 

PY
 

Total Local P~e’r~sonal Income Due to Institution’Rel~a~ted
 

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 contributions 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 employees together with wages to the additional employees identified by
 

equation I-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 institutional wages to local residents plus personal income as a consequence 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 I-l. The inclusion of OC in I-2 assumes
 

that all local governmental expenditures are local and that governmental expenditures have the same local impact as private
 

sector expenditures.
 

-66­
Equation I-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 I-2)
 

Equation I-3 relies on the national estimate, k, of the proportion of an individual’s total income used to purc--hase durable


goods from local sources (see Appendix B). PY was estimated in
 

I-2o -­

-67­
 

 

Guide to Model and Data Sources
 

VARIABLE
 

B-I Institution-Related Local
 

Expenditures
 

E = Local expenditures by
 i
 institutions
 

Ee = Local expenditures by
 

employees
 

Eg = Local expenditures by
 

guest artists
 

Ea = Local expenditures by
 

local audience
 

E = Local expenditures by
 v
 non-local audience
 

! B-I.I Local Expenditures by


Institutions Ei
 

z = Fraction of non-labor
 

expenditures
 

TEi = Total expenditures of
 

institution
 

We 
= Gross compensation to


employees
 

Transf = Internal accounts
 

and transfers
 

Tx 
= Taxes and fees to


government
 

B-I.2	 Local Expenditures
 

by Employees (Ee)
 f = Fraction household
 

income spent locally
 

Wen = Total net institutional
 

salaries
 

Yns = Household non-salary
 

income
 

DATA SOURCE
 

B-l.l
 

B-I.2
 

B-I.3
 

B-1.4
 

B-I.5
 

Institutional
 

Records
 

Institutional
 

Records
 

Institutional
 

Records
 

Institutional
 

Records
 

Institutional
 

Records
 

Staff Survey
 

Staff Survey
 

BALTIMORE STUDY
 

RESULTS
 

E = Ei + Ee + Eg + Ea + Ev
 

E = ($2,405,026) + $4,422,976) +
 

($68,247) + ($2,624,601) +
 

($1,891,392)
 

E = $11,184,676
 

E = z(TEi - We - Transf. - Tx)


Ei = .47($9,418,304 - $4,041,222 ­

0 - $32,328)
 

Ei = $2,405,026
 

Baltimore calculations resulting
 

in Ei = $2,405,026 were diaggregated over eight institutions.
 

z = .47 is a weighted average.
 

Ee 
= f(Wen = .5Yns)


Ee 
= .66($6,701,479 + 0)


Ee = $4,422,976
 

Data for the Baltimore study were
 

calculated using family income (Y)
 

in place of Wen + .5Yns).


$6,701p479 is the equivalent value
 

of wages and non-salary income for
 

the Baltimore sample.
 

Manual Case Study
 

Page Page
 

Reference Reference
 

33
 

34 13
 

35
 13

 

 

 

 QARIABLE
 

B-I.3 Local Expenditures by
 

Guest Artists (Eg)
 

gi = Average daily expenditures
 

GDi = Total guest days in
 

region
 

B-I.4 Local Expenditures
 

by Local Audiences (Ea)
 a = Average ancillary
 

expenditures
 

TA = Total paid attendance
 

B-I.5 Local Expenditures by


Non-Local Audience (Ev)
 v = Average daily expenditures
 

! TVD = Total annual visitor
 

days
 

B-2	 Secondary Business Volume
 

Stimulated by Institution Expenditures (BP)
 

m = Repurchase coefficient
 

Ep = Institution-related local
 

expenditures
 

DATA SOURCE
 

Staff Survey &
 

Institutional
 

Records
 

Audience Survey
 

Institutional
 

Records
 

Audience Survey
 

Institutional
 

Records
 

Appendix B
 

See B-I
 

Manual Case Study
 BALTIMORE STUDY
 Page Page
 RESULTS
 Reference Reference
 

Eg = g(GD)
 

Eg = $35.68 (1,913 days)
 

Eg = $68,247
 

Ea 
= A(TA)


Ea 
= $6.60/party ($397,667)


Ea 
= $2,624,601


Ev 
= V(TVD)


Ev 
= $30.32/day (62,381 days)


Ev 
= $1,891,392


BP = mp - i) (E)
 

BP = (1.818 -1) (11,184,676)
 

BP = $9,149,065
 

36 15
 

38 14 

39 14
 

40 15
 

NOTE: Calculations in the Baltimore study covered six local jurisdictions and eight institutions. Parameters
 

(denoted by small letters in the equations - z,f,g,a,v) were computed for the purpose of this table as
 

weighted averages from separate data from each institution that was utilized for the original calculations.
 
 

 

VARIABLE
 

B-3	 Secondary Business Volu~e
 

Stimulated by Individual
 

Expenditures (BV)
 

Mi = Repurchase coefficient
 

E = Institution-related local
 

expenditures
 

B-4	 Value of Local Business
 

Property Attributable to
 

Institution Business (BI)
 

RP = Value local business
 

real property attributable
 

Inv = Value local business
 

inventory attributable
 

B-4.1 Value Local Business Real
 

Property Attributable (RP)
 

E = Institution-related local
 

expenditures
 

TBV = Total local business
 

volume
 

AV =	 Total assessed value of
 

business property
 

ar = Assessment ratio
 

DATA SOURCE
 

Appendix B
 

See B-I
 

See B-4.1
 

See B-4.2
 

See B-I
 

Census of Business
 

1967
 

Census of Manufacturing 1967
 

State Retail Sales
 

Tax Division
 

State Department
 

of Assessments and
 

Taxation 1976
 

State Department
 

of Assessments and
 

Taxation 1976
 

BALTIMORE STUDY
 

RESULTS
 

BV = (.45) ($11,184,676)
 

BV = (.45) ($11,184,676) (2.857 - i)
 

BV = $9,350,389
 

BI = RP + Inv
 

BI = $2,309,031 + $3,437,712
 

BI = $5,746,743
 

RP = (E/TBV) (AV/ar)
 

RP = ($11,184,676/$26,702,272,000)


($2,391,693,000/.434)
 

RP = $2,309,031
 

Manual Case Study
 

Page Page
 

Reference Reference
 

41 15
 

42 15
 

43
 
VARIABLE DATA SOURCE
 

B-4.2 Value of Local Business
 

Inventory Attributable (Inv)
 

ir = Inventory-business volume Statistics of
 

ratio Income 1972 IRS
 

E = Institution-related local See B-I
 

expenditures
 

BP = Secondary business volume See B-2
 

stimulated by institution
 

expenditures
 

BV = Secondary business volume See B-3
 

stimulated by individual
 

expenditures
 

!
 

BALTIMORE STUDY 

RESULTS 

Manual 

Page 

Reference 

Case Study 

Page 

Reference 

Inv = ir (E + BP + BY) 45 

Inv = .112 (11,184,676 + $9,149,065 + 

$9,350,389) 

Inv - $3,437,712 
 

 

VARIABLE
 

B-5	 Expansion of Local Credit
 

Base Attributable (CB)
 

t = Time deposit reserve re-


requirement
 

TDi = Average daily balance in
 

institution time accounts
 

TDe = Average daily balance in
 

employee time accounts
 

Emps = Total full time employees
 

d = Demand deposit reserve
 

requirement
 

DDi = Average daily balance
 

in institutional demand
 

accounts
 

DDe = Average daily balance
 

in employee demand accounts
 

cbv = Cash-to-business volume
 

ratio
 

E = Institution-related
 

local expenditures
 

BP = Secondary business volume
 

stimulated by institution expenditures
 

BV = Secondary business volume
 

stimulated by individual
 

expenditures
 

B-6 Local Business Volume
 

Unrealized (NBV)
 

IB = Income from institution
 

administered business
 

DATA SOURCE
 

Federal Reserve
 

Bulletin
 

Institutional
 

Records
 

Staff Survey
 

Institutional
 

Records
 

Federal Reserve
 

Bulletin
 

Institutional
 

Records
 

Staff Survey
 

Federal Reserve
 

Bulletin
 

See B-I
 

See B-2
 

See B-3
 

Manual Case Study
 

BALTIMORE STUDY Page Page
 

RESULTS	 Reference Reference
 

CB = (l-t) [TDi + TDe (emps)] + 46 17
 

(l-d) . [DDi + DDe (emps) +


cbv (E + BP + BY)]
 

BC = (1-.03) [$74,750 + $6,129(503)]
 

+ (1-.1625) [$43,498 + $485(503)
 

+ .028 ($11,184,676 + $9,149,065
 

+ $9,350,389)]
 

CB = $3,068,194
 

48 17
 NBV = IB
 

NBV = 0
 
 

 

VARIABLE
 

G-I Tax Revenues Attributable (GR)
 

RETXi= Institution-related real
 

revenues
 

ST = Institution-related
 

sales tax revenues
 

YT = Employee income tax
 

revenue
 

SA = State aid attributable
 

to employee households
 

OR = Other revenues attributable
 

G-l.l Institution-Related Real
 

Estate Tax Revenues (RETXi)
 RETi = Local real estate taxes
 

paid by institution
 

RETe = Local real estate taxes
 

paid by employee households
 

RETb = Local real estate taxes
 

paid by business attributable
 

G-I.I.I Local Real Estate Taxes
 

Paid By Employee House-


Holds (RETe)
 Emps = Total full time employees
 

h = Percentage of employees
 

owning homes
 

ptj = Property Tax rate
 

TRAj = Residential assessments
 

Rj = Total number of residences
 

DATA SOURCE 

BALTIMORE STUDY 

RESULTS 

Manual 

Page 

Reference 

Case Study 

Page 

Reference 

See G-I. 1 

GR = RETX + ST + YT + SA + OR 

GR = $99,537 + $5,062 + $27,558 + 

49 18 

$19,610 + 0 

See G-I. 2 GR : $151,767 

See G-I. 3 

RETX = RETi + RETe + RETb 50 18 

Institutional RETX = 0 + $60,153 + $39,384 

Records 

See G-l.l.l RETX = $99,537 

See G-l.l.2 

RETe = Emps(h) (pt) (TRA/R) 51 

Institutional RETe = 404(.51),(.38,6) . 

Records ($5,622 416 000/623,440) 

Staff Survey RETe = $60,153 

Maryland Assoc. of 

Counties Report 

1976-77 

State Department of 

Assessments & 

Taxation 1976 

1970 Census of 

Population 
 

VARIABLE
 

G-I.I.2 Local Real Estate Taxe~
 

Paid by Business Attributable (RETb)
 RP = Value of local business
 

real property
 

ar = Assessment ratio
 

ptj
 = Property tax rate


G-I.2 Institution-Related
 

Sales Tax Revenues (ST)
 

stj = Locally retained sales
 

tax rate
 

STR = Total sales tax revenues
 

! E = Institution-related
 

~ local expenditures
 ~
 TBV = Total local business
 

volume
 

G-I.3 Employee Income Tax
 

Revenues (YT)
 

TYTj= Total income tax revenues
 

retained
 

HH = Total local households
 

- Percentage of employees
 

paying income tax
 

Emps= Total full time employees
 

Manual Case Study 

Page Page 

Reference Reference 

53 

54 18
 

55 18
 

DATA SOURCE
 

See B-4.1
 

State Department
 

of Assessments &
 

Taxation 1976
 

Maryland Assoc. of
 

Counties Report
 

1976-77
 

Retail Sales Tax
 

Division
 

Maryland Counties
 

Assessors Offices
 

See B-I
 

Census of Business
 

1967
 

Census of Manufacturing 1967
 

State Retail Sales
 

Tax Office
 

BALTIMORE STUDY
 

RESULTS
 

RETb = (RP) (ar) (pt)
 

RETb = ($2,309,031)
 

RETb = $39,384
 

.434)(.0386)
 

ST = st (STR) (E/TBV
 

ST = ($38,779,000) $11,184,676 a
 

$26,702,272,000)
 

ST = $5,062
 

Baltimore calculations were disaggregated over six jurisdictions.
 

$38,779,000 [s+(STR)] is the total
 

of locally retained sales tax in
 

each of the six jurisdictions.
 

YT = (TYT/HH) (i) (Emps)
 

State Department of YT = ($178,453,000/2,138,000)


Assessments &
 (1.00) (404)
 

Taxation 1976
 

Maryland Statisti- YT = $27,558
 

cal Abstracts
 

Staff Survey
 

Institutional
 

Records
 

i 
 

 

18 

VARIABLE
 

G-1.4 State Aid Attributable to
 

Employee Households (SA)
 

PSi = State aid to public schools
 

attributable
 

OR = Other revenues attributable
 

G-1.4.1 State Aid to Public Schools
 

Attributable (PSi)
 

N = Number of employees households with children in 

public schools 

Cij = Average number of children 

per employees households 

SE = Total state aid per 

student 

G-2 Operating Cost of Municipal

and School Services Attribu­

! table (OC) 

~ MOC = Municipal operating costs 

~ attributable 

PSOC = Public school operating
 

cost attributable
 

G-2.1 Municipal Operatin@ Costs


Attributable (MOC)
 

Bj = Operating budget excluding


public schools
 

EHHij= Total number of persons
 

in employee households
 

POPj = Total local population
 

DATA SOURCE
 

See G-I.4.1
 

Staff Survey
 

Staff Survey
 

Maryland Statistical Abstracts
 

See G- 2.1
 

See G- 2.2
 

Maryland Assoc. of
 

Counties Report
 

1976-77
 

Institutional
 

Records & Staff
 

Survey
 

Maryland Assoc. of
 

Counties Report
 

1976-77
 

BALTIMORE STUDY
 

RESULTS
 

SA = PS + OR
 

SA = $19,610 + 0
 

SA = $19,610
 

PS = N(C) (SE)
 

PS = 53 (i) (370)
 

PS = $19,610
 

OC = MOC + PSOC
 

OC = $648,183 + $30,429
 

MOC = B(EHH/POP)
 

MOC = $1,050,165,000(863/2,138,000)
 

MOC - $648,183
 

Manual
 

Page
 

Reference
 

56
 

57
 

58
 

59
 

Case Study
 

Page
 

Reference
 

18
 

18
 
18 

VARIABLE
 

G-2.2 Public School Operating
 

Costs Attributable (PSOC)
 

SBj = School operating budgets
 

Cij
 = Total number of children of


employees in public school
 

TCj
 = Total number of children


in public schools
 

G-3	 Value of Government Property Committed (GP)


GPm = Value of all government
 

property except schools
 

GPs = Value of government property associated with
 

schools
 

MOC = Municipal operating cost
 

attributable
 

= Operating budget excluding
 

public schools
 

PSOC =	 Public school operating
 

costs attributable
 = School operating
 SBj budgets
 

DATA SOURCE
 

State Division of
 

Fiscal Research
 

Staff Survey
 

Maryland Statistical Abstracts
 

State Department
 

of Assessments &
 

Taxation
 

State Department
 

of Assessments &
 

Taxation
 

See G-2.1
 

Maryland Assoc.
 

of Counties Report
 

1976-77
 

See G-2.2
 

State Division of
 

Fiscal Research
 

Manual
 

BALTIMORE STUDY Page
 

RESULTS Reference
 

PSOC = (SB) (C/TC)
 61


PSOC -	 ($648,927,000) (53/452,518)
 

PSOC - $30,429
 

62
 GP = (GPm) (MOC/B) + (GPs (PSOC/SB)
 

GP = ($342,803,000) ($648,183 +


$1,050,165,000 + ($670,340,000).
 

($30,429/$648,927,000)
 

GP = $274,138
 

Case Study
 

Page
 

Reference
 

19 
VARIABLE DATA SOURCE 

BALTIMORE STUDY 

RESULTS 

Manual 

Page 

Reference 

Case Study 

Page 

Reference 

G-4 Foregone Real Estate Taxes 

Attributable (FTX) 

AVnx = Assessed value of non-exempt 

land & buildings occupied/ 

owned by insitutiton 

ar = Local assessment ratio 

City Department of 

Assessments & 

Taxation 

City Department of 

Assessments & 

FTX = AVnx(ar) (pt) 

FTX = $1,992,160 (.50) (.06) 

FTX = $59,765* 

63 19 

pt = Local property tax rate 

Taxation 

City Department of 

Assessments & 

Taxation 

! 

! 

G-5 

Pi 

Si 

Li 

Ti 

Value of Municipal Services 

Self-Provided (SSVS) 

= Total annual cost of security services self-provided 

= Total annual cost of street 

maintenance self-provided 

= Total annual cost of street 

lighting self-provided 

= Total annual cost of trash 

removal self-provided 

Institutional 

Records 

Institutional 

Records 

Institutional 

Records 

Institutional 

Records 

SSVS = Pi + Si + Li + Ti 

SSVS = $29,331 + 0 + 0 + $3,841 

SSVS = $33,172 

64 19 

I-i Number of Local Jobs 

Attributable (J) 

Emps = Total full time employees 

X = Marginal employment requirement 

Institutional 

Records 

See Appendix B 

J = Emps + x(E + OC) 

J = 404 + .000065($11,184,676 + 

$678,183) 

J = 1175 

65 21 

E = Institution-related See B-I 

OC = 

local expenditures 

Operating cost of municipal & 

school services attributable 

* Note: Assumes that all city-owned property will remain tax-exempt. See pp. 18 & 20. 
 

 

VARIABLE 

I-2 Personal Income of Employees 

We 

Attributable (PY)

= Gross compensation to 

employees 

P = Payrolls and profits per 

dollar of institutionrelated expenditures 

E = Institution-related local 

expenditures 

OC = Operating cost of municipal 

and school services attributable 

I-3 Durable Goods Purchases 

k 

Attributable (DG) 

= Proportion of personal 

income spent on durables 

PY = Personal income of 

employees attributable 

DATA SOURCE
 

Institutional
 

Records
 

See Appendix B
 

See B-I
 

See G-2
 

See Appendix B
 

See I-2
 

Manual 

BALTIMORE STUDY 

RESULTS 

Page 

Reference 

PY = We + p(E + OC) 66 

PY’=	 $4,041,222 + .475($11,184,676 +
 

$678,183)
 

PY = $9,676,284
 

DG = k(PY)	 67
 

DG = .031 ($9,676,284)
 

DG = $299,965
 

Case Study
 

Page
 

Reference
 

21
 

21
 
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 multiole


varying directly in size with the fraction respent l~cally
 

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
 

l-mpc


to consume (that is, the fraction of income spent) locally"
 

and l-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 Model 

Range of Multiplier Values

Used in Other Studies* 

mp 1.818  ̄ B-2 1.15 - 2.50 

mi 2.857 B-3 2.0 - 4.0 

p .475 I-2 .25 ­ .66 

x .000065 I-i .00007 ­ .00009 

k .031 I-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 mD, the marainal employment
 requirements of an additional dSllar’s worth of local
 

institutions-related spending and mi, 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
 

mi and mp are reduced by i.
 

*See Caffrey and Isaacs, Estimating the Impact of a College
 

or University on the Local Economy, pp. 44-45; and S.J. Weiss
 

and E.C. Gooding, Estimation of Differential Employment


Multipliers in a Small Reqional Economy (Research Report to
 

the Federal Reserve Bank of Boston, No. 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 st~ff with this institution,
 

please answer questions 1 through i0.
 

If you are a guest artist with this institution, please begin
 

with question ii.
 

i. Are you employed at this institution full time or part time?
 

full time part time
 

How many persons are in your household, including
 

yourself?
 

How many of the children in your household attend public


elementary or secondary schools?
 

4. ~ere 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? $
 

-82­
 

What is the total annual non-salary income (rents,
 

interest, dividends, etc.) of ALL PERSONS (including
 

yourself) who live in your household? $
 

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
 

i0.	 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
 

ii.	 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?
 

-83­
APPENDIX D
 

The Audience Survey
 

There are great problems associated with the use
 

of self-administered audience surveys in developing meaningful 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
 

-84­
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 institutions of higher learning or local planning departments. We
 

believe that further research needs to be done on alternative
 

strategies for estimating audience expenditures, perhaps including interviews and questionnaires distributed at the
 

surveyed events to be completed and returned by mail after
 

respondents return home.
 

-85­
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 individuals 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 governmental impacts. In the circumstances in question, you will have
 

to use the payroll records of those who had worked at a particular position during the year in question to determine that
 

X% of those employed in that position resided in one jurisdiction or another. This information can then be used to apportion
 

high turnover payroll slots among the local units of government. 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 individuals are employees and not guest artists on contract. Guest
 

artists are treated separately by equation B-I.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 during the year. For example, 5 individuals may work 15 hours a
 

week and the institution may consider 40 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 institution that considers 48 weeks to be full-time. Therefore, the
 

number of full-time equivalents is 5(4/48).
 

-86­
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 (Z) to indicate where
 

i=l
 

impacts must be totalled over n institutions.
 

-88­
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 believ~
 

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 subscript j and the total area impacts are indicated by sum-


m
 

ming over m jurisdictions (~). 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 impacts of these expenditures will remain in the locality,
 

and more precise information on suppliers’ 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 single institution.
 

n
 

EI= Z - Transf - T )


i=i
 Zi(~-~i - Wei i xi


n
 

Ee= fi (Weni + " 5 Ynsi)


l=l
 

n
 

gi (GDi)
 

n
 

a
 ai (TAi)


i=i
 

n
 

vi (TVDi )
 v
 l=l
 

n
 

CB= 7. { (l-t) {TD.+(TDe) (Emps) } i
 +(l-d) { DDi+(DDe) (Empsi)
 l=l + cbv(E) }!}
 

n
 

NBV=7. IB. 

i= 1
 i 


n
 

RETe= 7. .Empsi (hi) (pt) (TAR/R)
 

i=l
 

n
 

MOC= Z (EHHi/Pop) (B)
 

i=i
 

n
 

PSOC= 7. (Ci/ ) SB
 

i=l
 

n
 

FTX= 7. AVi (ar) (pt)
 

i=l
 

SSVS= 7. Pi + S. + L. + T.
 

i=l ~ ~ m
 n
 

J = 7. Empsi + x(E. + OCi)
 i=l 1
 

n
 

PY = E w. + p(Ei. + OCi~.
 

i=l 1
 

-90­

W U. S. GOVERNMENT PRINTIIWG 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
 

EI = 7. Z(TE. - W - Transf. - T


j=l 3 ej 3 xj m 

E = ~ e f(Wenj + .5Ynsj)
 j=l
 

m
 

E = Z g(GD. )
 g
 j=l 3


m
 

E = 7. a (TAj)


j=l
 

-m 

v
 v j=l 

m 

RP = 7. (Ej/TBVj) (iVj/arj)
 j=l 

m 

RETe ~
 Empsj (hj) (ptj) (TPAj/Rj)
 j=l 

m
 

RETb =
 ptj (Ej/RPj) (AVj)
 3=i
 

m
 

ST =
 stj (STRj) (E./TBV.)
 3=1
 

m
 

YT =
 (TYTj/HHj) (i) (Empsj)
 j=l
 

m
 

SA = PS. + OR.
 ] ]
 3=1
 

m
 

MOC =
 (EHHj/Popj) (Bj)
 j=l
 

m
 

PSOC =
 (Cj/TCj) (SBj)
 j=l
 

m (GPm ) (MOCj/B3) + (GPs ) (PSOCj/SBj)
 

GP =
 

j=l
 j


m
 

FXT =
 AVj(arj) (ptj)
 j=l
 

m
 

SSVS = Pj + S. + L + T.
 ] j 3
 3=i
 

-91­