the relationship among funding sources for art and history museums

The Relationship AmongFunding Sources for Artand History Museums

Patricia Nold Hughes,William A. Luksetich

The decline and possible elimination of federal support of thearts in the United States is likely to have a major impact onmuseum finances. Using data from the 1989 Survey of Muse-ums, we analyze the interactions among major categories ofmuseum funding. The results indicate a strong, positive stimu-lus of federal funding on private contributions, with some pos-sible displacement of state and local government contributions.The opportunity to generate funds from private sources showssome promise to offset the loss of funds from governmentsources.

THE support of the arts in the United States is reaching a criti-cal stage as a major player in the system is withdrawing itssupport. The National Endowment for the Arts (NEA), pro-

viding federal support for the arts since 1965, has been a crucial cat-alyst for outside support via its matching-grants program. Althoughthe NEA budget grew from approximately $3 million in 1966 to ahigh of $176 million in 1992, federal support of the arts has sincedeclined. The NEA suffered a budget cut of nearly 50 percentbetween fiscal years 1993 and 1998, with the budget for fiscal year1998 at $98 million. The president requested $136 million for fiscalyear 1999. Initially, the House subcommittee responsible for theNEA’s budget voted to give no money to the endowment next year,but it later reversed and voted to restore the budget at the 1998 level.

Although direct federal support accounts for less than 2 per-cent of the total operating budget of our nation’s art museums, the

NONPROFIT MANAGEMENT & LEADERSHIP, vol. 10, no. 1, Fall 1999 © Jossey-Bass Publishers 21

Note: We would like to thank Roland Kusner and the anonymous referees forvaluable comments and suggestions, many of which have been incorporatedinto this article.

withdrawal of federal funds may have a much greater impact onmuseum finances. The NEA’s block grant programs are designed tostimulate state spending by supplying additional funding resources.The competitive program grants, awarded by the NEA directly tononprofit arts organizations, also are intended to stimulate privategiving through their multidollar matching requirements and nationalprestige. If there is a stimulus effect from federal funding, a declinein this source will have a multiplier effect, escalating the problem. Ifmatching requirements are difficult to enforce, then any stimuli fromfederal funding are tempered; state and local government spendingand private contributions may increase and offset the decline in fed-eral support.

This study analyzes the interrelationship among funding sourcesof the arts in the United States. Specifically, a simultaneous equationsystem is used to analyze the relationship among federal funding,state funding, local funding, private income, and earned income forart and history museums. In a simultaneous equation system it isassumed that each funding source is influenced by other levels offunding rather than federal, state, local, and private decisions beingdetermined independently. The objective is to identify trade-offs in,and the multiplier effects of, funding sources. This information isvaluable in determining the return from developmental expendituresand projecting income changes that result from political decisionson the level of government support of the arts. Whereas other stud-ies have considered the determinants of funding sources of the artsindependently, this study incorporates the simultaneous nature ofthe various sources.

This article first describes previous models of funding sourcesfor the arts, specifically state arts appropriations, private contribu-tions, and earned income. The article then presents a simultaneousequation system for funding of the arts that explicitly captures theinterrelationship among all funding sources: federal, state, local, pri-vate, earned, and investment income. Finally, empirical results andconclusions are discussed.

Previous ModelsPrevious studies have focused on the determinants of funding sourceswithout explicitly considering the relationship among such sources.Studies that focus on the determinants of state arts appropriationsmay include a provision for a federal stimulus, although other fund-ing sources are notably absent from most of the models. Models ofprivate giving tend to emphasize the demographics, tax advantages,and crowding-out effects of giving. The tax advantages of private giv-ing relate to the “price” of giving. In states with relatively highmarginal income tax rates, a charitable contribution reduces the taxliability for those who itemize deductions and hence reducesthe price of giving. The inclusion of government funding tests the

22 HU G H E S, LU K S E T I C H

Although directfederal supportaccounts for lessthan 2 percent

of the totaloperating budget

of our nation’sart museums, the

withdrawal offederal funds

may have a muchgreater impact

on museumfinances

crowding-out question of whether individuals reduce contributionswhen government support is provided. The recognition that gov-ernment support influences private contributions is at least partialrecognition of the simultaneous nature of the various fundingsources. Models of earned income tend to focus on the demand forservices without recognizing the incentive of the arts to increaseearned income in the face of declining government revenues.

Models of state arts appropriations tend to emphasize the will-ingness and capacity of states in determining state arts appropria-tions, with limited recognition of the effect of alternative fundingsources on state contributions. Schuster (1989) focuses on variationsin state arts appropriations per capita, including three primary vari-ables: attendance rates, the number of resident artists, and the num-ber of nonprofit arts organizations. While explaining 78 percent ofthe variation in arts appropriations, there is no considerationgiven to the influence of alternative funding sources on state artsappropriations.

Netzer (1992) investigates changes in the willingness and capac-ity of states to finance public services. In this model state arts appro-priations are treated as a function of personal income, tax effort, andeducation. Tax effort proved to be consistently positive and signifi-cant; income and education yielded less consistent results.

Hofferbert and Urice (1984) use path analysis to explain differ-ences in state arts spending, including the effect of federal aid onstate contributions. Three major factors are found to influence stateart spending: social investment policy norms, legislative profession-alism, and federal aid. The authors find that NEA grants provide apositive stimulus to state arts spending.

Abrams, Bracht, and Prinz (1996) include nine major factors intheir study of state levels of support for the arts. Included in these fac-tors are federal support, city support, and private contributions. BothNEA grants transferred directly to state arts agencies and city supportprovide a stimulus to state arts appropriations. NEA grants awardeddirectly to nonprofit arts organizations and private support are foundto decrease state arts appropriations. This study attempts to capturethe interdependence of funding sources of the arts, but it considersonly one dimension of this relationship. Although federal, local, andprivate sources influence state contributions, it must also be recog-nized that each funding source influences, and is influenced by, allother funding sources. Specifically, it is very likely that state contri-butions will in turn influence federal, local, and private contributions,in which case the effects of federal, local, and private contribu-tions on state funding will be inconsistent with earlier estimates.

Turning to private contributions, the emphasis on demograph-ics and tax advantages of charitable giving is illustrated in along line of econometric research by individuals such as Taussig(1967), Schwartz (1970), Feldstein (1975), Steinberg (1990), andBarrett (1991). As an example of such research, Clotfelter and

RE L AT I O N S H I P AM O N G FU N D I N G SO U R C E S F O R ART A N D HI S T O RY MU S E U M S 23

Previous studieshave focused onthe determinantsof funding sourceswithout explicitlyconsidering the

relationshipamong such

sources

Salamon (1986) study the effects of the 1981 tax act on charitablegiving, simulating the effects of income and price changes on chari-table giving. Although they acknowledge that other factors exert asignificant influence on private giving, the authors simulate the effectof the 1981 tax act with the assumption that other patterns of inter-action remain constant.

Abrams and Schmitz (1986) consider explicitly the crowding-outeffect of government transfers on private charitable contributions. Inaddition to income and price, government transfers to charitable orga-nizations from federal sources and combined state and local sourcesare included in the model. The coefficients for the governmentaltransfer variables are consistently negative and statistically significant,indicating a significant crowding-out effect on private contributions.

Steinberg (1991) explicitly considers the simultaneous nature offunding and the effect of government spending on donations. Hedemonstrates that single-equation estimates that measure the effectof one category of funding on donations, all else equal, are biased.Single-equation estimates including only federal spending constitutea reduced form of the structural model of funding that includes allalternative funding sources. In this reduced form of the model,all adjustments in state, local, and earned income are represented bychanges in federal support only. The reduced-form estimatesthereby measure not only the direct effect of changes in federal sup-port on donations but also the indirect effect as other sources simul-taneously adjust to federal changes and influence donations. Modelsthat include the direct influence of federal, state, local, and earnedincome constitute the structural equation for donations, with theeffect of each funding source on donations explicitly considered. Anunbiased estimate of the structural equation for donations can beobtained by two-stage least squares. Estimating the structural equa-tion directly creates problems because of the feedback that changesin private donations may have on federal, state, local, and earnedincome. Regression analysis requires that causality run one directiononly, from federal, state, local, and earned income to private dona-tions. Any secondary effects that private contributions have on thelevel of alternative funding will bias the estimates of the structuralequation. In two-stage least squares, the variables representing fed-eral, state, local, and earned income are replaced with highly corre-lated variables that will not be influenced by changes in donations.In two-stage least squares the replacements for the actual fundinglevels are the estimated values of these variables based on factors thatare not influenced by private donations.

The ability of the arts to earn income is only indirectly addressedin studies that look at the demand for such services. How responsiveattendance is to admission price, measured by the price elasticity ofdemand, is a major factor in pricing decisions and revenue determi-nation. A summary of the estimates of the elasticity of demand


for attendance at the performing arts provided by Heilbrun andGray (1993, p. 90) indicates that the performing arts have the dis-cretion of increasing earned income in the face of budget cutbacks.The price elasticities of demand range from a low of 0.05 to a high of0.9. The evidence of an inelastic demand for the arts, with attendanceunresponsive to price, implies that an increase in admission price willincrease overall revenue with a relatively small effect on attendance.Luksetich and Partridge (1997) find similar results for museum atten-dance. The estimated elasticities generally range from 0.12 to 0.26,suggesting a very inelastic demand for museum attendance.

In considering the range of funding sources available to muse-ums, Luksetich, Lange, and Jacobs (1987) look at the effectivenessof museum fundraising efforts in acquiring funds from the federalgovernment, foundations, corporations, and individuals. The empha-sis of that article is on the effectiveness of development expendituresto increase funding, ignoring the possible simultaneous nature of thevarious funding sources. Two rather interesting results emerge fromtheir study. First, the marginal return on $1.00 of fundraising expen-diture is estimated at $7.44 from all sources. Second, virtually allof the population and income measures are insignificant in explain-ing the ability of museums to acquire funds from any source.

A Simultaneous Model of Funding SourcesThe objective of the simultaneous model is to identify trade-offs infunding sources and the stimulus effects of funding sources. As such,each funding source is dependent on other funding levels, in addi-tion to factors unique to that particular category. Following are adescription of the determinants of each funding category and anexplanation of the method of two-stage least squares, which are usedto estimate the system of equations.

Federal support of museums not directly owned or operated bythe national government comes mainly from three sources: the Insti-tute of Museum Services (IMS), the National Endowment for the Arts(NEA), and the National Endowment for the Humanities (NEH). Theprincipal purpose of the IMS is to provide direct operating supportto help cover general expenses. A museum may receive support ofup to 10 percent of its operating income, not to exceed $75,000.Given this cap, museums with operating incomes greater than$750,000 receive proportionally less support.

The NEA is directed to making grants for specific projects andproductions. In 1988, the year prior to this study, 20 percent of theNEA budget was required to go to the state arts agencies. These BasicState Grants require no matching funds and are allocated with a biastoward the least populous states on a per capita basis (Heilbrun andGray, 1993, p. 269). While these grants were originally intended toencourage the development of state arts agencies, they are the most


How responsiveattendance is toadmission price,measured by theprice elasticity of

demand, is amajor factor in

pricing decisionsand revenue

determination

apt to cause states to substitute federal support for state support. Infinancing particular projects, the NEA requires matching funds atleast equal to the program grant. In addition, Challenge Grantsrequire three dollars in new nonfederal contributions for every dol-lar of federal support. The matching aspect is intended to stimulatefunding from private sources. Alternatively, private dollars may beviewed as a sign of quality and the NEA seen as desiring to fund proj-ects local patrons feel are of merit.

The NEH also provides support to museums under the categoryof “Humanities Projects in Museums and Historical Organizations.”These grants are typically given in support of a special exhibition andconstitute a relatively minor source of federal support.

Given the nature of federal support, it is assumed that the levelsof public support from state and local sources and private supportare likely to influence the distribution of federal monies amongmuseums. The influence of these sources of support, however, isuncertain. Federal support may provide seed money in areas of lowstate and local public support or may reward those areas that showa commitment to the arts. In addition, public agencies may be reluc-tant to make grants to a nonprofit that did not appear to be pullingits own weight in fundraising efforts (as measured by developmentexpenditures) and private support. It is therefore expected that pri-vate support will positively influence federal grants whereas the effectof alternative public support is less certain.

In addition to alternative funding sources, the commitment of astate to social programs in general may positively influence the levelof federal support. Given the direct operating support of the IMS, fed-eral support is likely to be influenced by the collection value of themuseum. NEA grants may also be influenced by the reputation ofthe museum, as measured by age and collection value. Because therehas been concern recently that NEA program grants are concentratedin the large urban areas, population is also included as a possibledeterminant of federal funds.

The distribution of state support will be influenced by the levelof support from alternative sources and by factors influencing thestate economy and population demographics. The Basic State Grantsmay encourage the development of state arts agencies or may causestates to substitute federal support for state support. As with NEAprogram grants, most state grants to institutions require matchingfunds of at least one-to-one from other sources. We expect, therefore,that those institutions that demonstrate substantial effort to acquireprivate support receive favorable treatment from state agencies. Theeffect of local government support on state appropriations is not clearand will be determined by the empirical results.

In contrast to the NEA’s support, which is limited to grants forspecific projects and productions, 39 percent of state funding goes togeneral operating support of arts institutions (Heilbrun and Gray,1993, p. 269). This form of support tends to be biased toward large,


The objective ofthe simultaneous

model is toidentify

trade-offs infunding sourcesand the stimuluseffects of funding

sources

established institutions representing “centers of excellence.” Hence,we would expect the age and collection value of a museum topositively influence state appropriations. Although state appropria-tions do not directly cover construction and renovations, recentmajor renovations may influence state appropriations and areincluded in the model.

To capture regional differences in state appropriations, the will-ingness and ability of the state to finance the nonprofit sector is rep-resented by three variables: state educational spending, state publicsector spending, and state income. States that spend a significant por-tion of their budget on education are more likely to support activi-ties such as zoos, parks, and public sector services in general.Spending on education, including the educational services providedby museums, is the best available measure to capture the general atti-tude toward the provision of these public sector services. The size ofthe public sector and the income level demonstrate the ability of thestate to pay for the arts. All three factors are expected to exert a pos-itive influence on state arts appropriations.

Local government funding sources tend to be more diverse inpurpose and function than federal and state sources. The financialarrangements under which localities support the construction oroperation of major cultural endeavors defy easy generalization, asindicated in examples provided by Heilbrun and Gray (1993). Theemphasis of local support has been characterized as creating oppor-tunities for artistry to occur. This sentiment suggests that local sup-port will increase when other sources of support falter. Given thecommon funding source of local and private support, however, ahigh positive correlation is expected between these two fundingsources. The positive correlation observed between local public andprivate support is not assumed to represent a causal relationshipbut to be reflective of demographic factors that affect both variables.

Public support primarily concerned with creating new opportu-nities would imply a negative relationship between local support onthe one hand and collection value and age on the other. However,organizing and supporting activities to bring art to the communitymay be best undertaken by the larger, established museums, imply-ing a positive relationship. In any case, activities that are popular inthe community would be expected to receive local public support.Given the flexibility of funding, it is expected that museums withmajor renovations would be supported in part by local funding.Again, to account for regional differences in a state’s attitude towardthe provision of public sector services, state educational spending isincluded as an explanatory variable.

Private support is an aggregation of foundation, corporate, andindividual support. The diversity of purpose makes it hard to char-acterize this particular area of support. Both federal and state grantsinclude matching provisions that may stipulate new money be raised,although these requirements are difficult to enforce and may still


The commitmentof a state to

social programsin general may

positivelyinfluence the

level of federalsupport

allow some substitution of public funding for private funding. Localgovernment funding may act as a substitute for private contributions,but there is a high positive correlation between the two due toregional demographics. Whether support is concentrated on thelarger, established museums or the new upstarts is hard to determinea priori. Corporations may prefer the visibility of the larger muse-ums, whereas foundations and individuals may be following a dif-ferent agenda.

The number of foundations, corporate headquarters, and privatemembers all demonstrate the strength of the private sector. Devel-opment expenditures and expenditures on public activities areassumed to strengthen that support. Large renovations may also cre-ate a visible need for additional support from the community. Indi-viduals may support the arts directly through contributions orindirectly through admission fees. It is hypothesized that museumsthat charge admission fees will receive less support through privatecontributions. Private contributions in general are expected toincrease with income, education, and age. Given the tax advantagesof corporate and individual contributions, a higher tax rate decreasesthe cost of giving and is expected to positively influence contribu-tions. Given the general sentiment of Republicans in favor of privateversus public sector activity, the greater the demonstrated supportfor the Republican position (as measured by the percentage of thepopulation voting Republican in the previous presidential election),the greater the private contributions will be.

In the absence of public and private contributions, museumshave the discretion (given the inelastic nature of the demand formuseum services) to raise income through higher admission fees aswell as through concessions, gift shops, parking, and other endeav-ors. It is expected that earned income will replace reductions inpublic funding, particularly federal and state. Many museums mayrely heavily on local patronage, in which case earned income isdrawing from the same pool as local government, private support,and endowed income. In the case of lagging local support, thepotential for earned income is also likely to be weak. Population,income, education, age distribution, and the museum’s collectionvalue measure the strength of local support. Admission fees areincluded to determine whether museums tend to increase fees orresort to other enterprise when faced with the necessity of increas-ing earned income.

A summary of the models and a description of the variables areprovided in Table 1. Given the simultaneous nature of nonprofitfunding sources (the simultaneity confirmed by Hausman tests) (seePindyck and Rubinfield, 1998, pp. 353–354), it is necessary to esti-mate the system of equations rather than each equation indepen-dently. Two-stage least squares are applied to the system ofequations to obtain consistent estimators of the determinantsof museum funding. The first stage involves regressing each fund-ing source on all exogenous variables in the system, that is, those


Localgovernment

funding may actas a substitute

for privatecontributions,but there is ahigh positivecorrelation

between the two


Table 1. Overview of Model: Definition of Variables

Federal State Local Private Earned

Funding SourceFederal government X X X XState government X X X XLocal government X X X XPrivate support: foundation, corporate, individual X X XInvestment income: endowment and other sources X

Museum CharacteristicsCollection value X X X X XAge X X X XAttendance XMembership number XAdmission fee (yes/no) XAdmission fee $ XDevelopment and membership expenditures X X X XExpenditures on public activities XRenovation in last ten years (yes/no) X X X

State CharacteristicsSocial investment: education/government expenditures X X XPublic sector: government/total employment XPer capita income XPercentage Republican XFoundations per capita XManufacturers per capita XHighest marginal tax rate XHighest marginal corporate tax rate X

Market Area Characteristics (City, County)Population X XPer capita income X X XPercentage of population over 65 X XPercentage of population over 25 with B.A. X X

Sources: Data on funding sources and museum characteristics were obtained from the American Association of Museums1989 Survey of Museums. Data on state characteristics were obtained from the Statistical Abstract of the United States 1991,U.S. Department of Commerce, Economics and Statistics Administration, Bureau of the Census. Data on market areacharacteristics were obtained from the following U.S. Department of Commerce publications: City and County Data Book,State and Metropolitan Area Data Book, and 1990 Census of Population. Market area is defined as the entire metropolitanarea (either the metropolitan statistical area [MSA] or primary metropolitan statistical area [PMSA]), using the CensusBureau’s definition) in cases when the museum is located in a metropolitan area. If the museum is in a county that doesnot belong to a metropolitan area, the market area is defined as the county.

factors that are not affected by funding decisions. This set of equa-tions, which embody no structural relationships, are used to obtainestimates of the various funding sources. The structural equations,which explicitly model the determinants of funding, are thenestimated in the second stage. To obtain consistent estimates, theactual funding sources are replaced with the predicted values whenthese variables represent explanatory variables (appear on the right-hand side of the equation). The next section presents the estimatesof the structural equations corresponding to the second stage ofestimation.

Empirical ResultsData from the American Association of Museums’ 1989 Survey ofMuseums are coupled with socioeconomic data from the U.S. censusto estimate the determinants of funding for art museums and his-tory museums. The 1989 museum survey contains data on expendi-tures, funding sources, and museum characteristics, includingcollection value, age of museum, membership number, attendance,admission fees, and renovations. The survey is a very rich data sourcecontaining comprehensive data on museum characteristics and activ-ities. There is no recent, comparable data set that would allow theestimation of the individual funding sources as described in thisstudy. The Urban Institute is compiling the most recently availabledata. These data are from the IRS Form 990, filed by nonprofit muse-ums. The data are useful for analyzing numerous types of museumactivities. However, the data are not detailed enough to undertake astudy of the type done here. A new study of museum activities, sim-ilar to the 1989 survey, would be most useful.

The system of equations is estimated separately for art and his-tory museums, using two-stage least squares. The empirical resultsfor each type of museum are discussed in turn.

Art MuseumsThe results for art museums are shown in Table 2.

Three factors are significant in determining federal support: localgovernment support, collection value, and age of the museum. Bothcollection value and age exert a positive influence on federal fund-ing. This may be due to the direct operating expenditures of the IMSor the reputation of the museum in obtaining NEA grants. Local gov-ernment funding exerts a negative, albeit small, influence on federalfunding. This may demonstrate that there is a trade-off between localspending and federal spending.

Two factors are significant in determining state support: local gov-ernment funding and art museum development expenditures. A $1.00increase in development and membership expenditures is estimatedto increase state funding by $1.15. Development expenditures mayalso increase other areas of funding; hence, the rate of return fromfundraising activities is likely greater than 15 percent. Local govern-ment funding exerts a negative influence on state funding, demon-strating a possible trade-off between sources of public funding.

Local government support for art museums is influenced bythree significant factors: state funding, attendance, and developmentexpenditures. The more popular the museum, the greater the localsupport. Development expenditures have a positive impact onlocal support, returning $0.88 for an additional $1.00 spentfrom the general category of fundraising. State funding negativelyimpacts local support, demonstrating the substitution of state forlocal funding.


Two-stage leastsquares are

applied to thesystem of

equations toobtain consistentestimators of thedeterminants ofmuseum funding


Table 2. Art Museums: Regression Results Using Two-Stage Least Squares


Funding SourcesConstant �18753 �951350 111300 �2552400* �707230Federal government 3.7827 �3.6667 3.8646 �8.5684(Federal government) .000086016**(Federal government) �0.2045E-9**State government 0.0054 �0.15664* �0.45928** �0.0673Local government �0.0266* �0.576** 0.50874** 1.1096**Private support 0.0193 �0.0055 1.4566**Investment income 0.5126**

Museum CharacteristicsCollection value 9434.3** �61103 5338.1 �98013* 6590.2Age 382.19* 5335.2 3068.2 423.31Attendance 2.0611**Membership number 19.425Admission fee (yes/no) 45407Admission fee $ �92966Development and membershipexpenditures 0.0554 1.1487* 0.88373** �0.77513

Expenditures onpublic activities 0.44608**

Renovation in lastten years (yes/no) �232960 �98468 34417

State CharacteristicsSocial investment 7058.6 �161930 �225680Public sector 5735300Per capita income 2527800Percentage Republican 40054*Foundations per capita 11501000**Manufacturers per capita 12645Highest marginal tax rate 441700Highest marginal corporate tax rate �2927600

Market Area Characteristics (City, County)Population 3.2089 83.15Per capita income 7.2760 19.663 �49.597Percentage of population over 65 5812.2 33864Percentage of populationover 25 with B.A. �2553.7 38768

Number of observations 195 195 195 195 195R .3868 0.1057 0.6306 0.7986 0.6913

*significant at 10 percent level**significant at 5 percent level

Private support for art museums is influenced by several factors.Each $1.00 of museum expenditures on public activities is estimatedto increase private support by $0.45. This $0.45 is the aggregate ofthe effects on corporate, foundation, and individual support; it doesnot represent the marginal effect in any one category of funding.Moreover, spending on public activities may also increase other

sources of support. Our estimates indicate that museum developmentspending has no statistically significant effect on private support. Thisdoes not imply that development expenditures have no effect onprivate fundraising; it implies only that the marginal impact is notsignificant. To the extent that development activities are directed atboth public and private sources, it may not be possible to ascertainthe marginal effects of development spending on any one source offunds. Because it is not possible to determine how museums directtheir development efforts, we are unable to ascertain their impact.

The per capita number of foundations in a state bears a positiveand statistically significant relation to private giving. This may beindirect evidence that development spending is impacting founda-tion support. More prestigious museums, as measured by collectionvalue, receive more support from federal agencies and less supportfrom the private sector. As hypothesized, the greater the preferencefor private versus public activity, the greater the private support forart museums.

Alternative funding sources have a mixed effect on private sup-port. Our initial estimates indicated that each $1.00 of support fromfederal sources increased private support by over $9.33. This largeresponse to federal support may be the result of significant privatesupport from businesses and foundations to finance very popular andhighly publicized traveling exhibits, such as the King Tut exhibit. Inan effort to determine if there was a disproportionate effect of largefederal expenditures on private funding, we squared and cubedthe federal funding variable and added these terms to the privatefunding equation. The resulting estimates support the nonlinearspecification and indicate that support from federal sources stimu-lates private giving up to a point, beyond which crowding out beginsto occur. The estimates indicate that each additional $1.00 of federalsupport results in, on average, additional private support of $10.88.

Funding from state sources decreases private giving. While somestate funding has matching provisions intended to stimulate privategiving, the general operating support provided by the states appearsto be substituting for private support.

Art museums’ earned income is mainly determined by privateand local public support and by investment income. All have a pos-itive and significant effect on earned income. There is no evidencethat earned income is a direct substitute for public funding. Thisappears indicative of common sources of local funding.

To ascertain the trade-offs between sources of governmentfunding, we must look at the model as a whole. The estimates showthat local government spending has a relatively large negative effecton state support for art museums and a relatively minor negativeeffect on federal funding. There is also weak evidence that stategovernment spending has a negative effect on local support. Theseestimates indicate a tendency for state funding to substitute for local


Three factors aresignificant indetermining

federal support:local government

support,collection value,and age of the

museum

funding, but no strong evidence of any other trade-off in public sec-tor funding for art museums between different levels of government.Federal sources very strongly stimulate private contributions to artmuseums. The effects of local and state support on private supportto art museums are opposite and largely offsetting.

The results we have presented indicate, on average, trade-offsthat can be expected between sources of funding and determinantsof those sources. The results also yield information useful to artmuseum decision makers. Assuming a future decrease in federalfunding, our estimates show no compensating change in state andlocal support. They do, however, show a significant negative impacton private support. The alternative available to museums is toincrease both private support and earned income. Indeed, supportfrom individuals, businesses, and foundations tends to stimulateearned income. Perhaps individuals who support art museums (or areassociated with organizations supporting art museums) with dona-tions, grants, and so on are also more likely to visit the museums andthe associated concessions. Moreover, there is no evidence thatincreased support from private sources has any detrimental effect onsupport from any level of government. Finally, to reiterate, althoughdevelopment expenditures are not estimated to be statistically sig-nificant in affecting private support, current developmental effortsmay not be directed toward fundraising from the private sector.

History MuseumsThe results for history museums are shown in Table 3.

The results of the determinants of funding for history museumsexhibit some of the same characteristics as those of art museums,although there are some notable differences.

Federal funding for history museums is influenced by six signif-icant factors, three of those relating to alternative funding. State andlocal funding exert a negative influence on federal support. Privatesupport exerts a positive influence on federal funding; federal deci-sions are favorably influenced by museums that make an effort insecuring private support. A state’s commitment to social programsand the age (reputation) of the museum also positively influence fed-eral funding. Somewhat surprising, development expenditures exerta negative and significant influence on federal support. In the absenceof federal funding, museums may be forced to increase fundraisingefforts to secure support from other sources.

State support is influenced by four significant factors: the age ofthe museum, development spending, federal funding, and private sup-port. Age has a positive effect and development spending has a nega-tive effect on state funding. State support declines as federal supportincreases, implying a substitution of federal funding for state funding.Private support positively affects state funding. Museums that showsuccess in obtaining private support are rewarded with public money.


The alternativeavailable to

museums is toincrease both

private supportand earned

income


Table 3. History Museums: Regression Results Using Two-Stage Least Squares


Funding SourcesConstant �683980** �263050 �88925 �53065 �316470Federal government �0.48361* 0.17975 0.48479** �0.33225State government �0.4206** 0.052501 0.024384 0.58729**Local government �0.7405** �0.55372 0.39801 �0.35428Private support 1.7734** 1.0702** 1.0248**Investment income 0.3205**

Museum CharacteristicsCollection value 23879 57012 �3491.5 �5807.2 �116070**Age 3513.6** 4801.7** �25.240 �8969.8Attendance �0.34084Membership number 3.7393Admission fee (yes/no) 19315Admission fee $ 222230**Development and membershipexpenditures �4.6784** �3.0916** 1.5329** 2.1923**

Expenditures onpublic activities 0.039386

Renovation in lastten years (yes/no) 98988 16557 57933

State CharacteristicsSocial investment 1525700** 1586500 106400Public sector �1478300Per capita income �17139000Percentage Republican 190.73Foundations per capita 4635700*Manufacturers per capita 39482Highest marginal tax rate �25839Highest marginal corporate tax rate �425810

Market Area Characteristics(City, Country)

Population �7.2532 �31.883Per capita income 4.4995 3.1010 17.707Percentage of population over 65 �8969.8 23431Percentage of populationover 25 with B.A. �3166.7 �14056

Number of observations 160 160 160 160 160R 0.6740 0.1242 0.1943 0.5438 0.4327

*significant at 10 percent level**significant at 5 percent level

One significant factor determines local government support:development and membership expenditures. An additional $1.00spent for development and membership increases local governmentfunding by $1.53.

Private support is influenced by three significant factors: federalfunding, development expenditures, and the number of foundations

per capita. As is expected, the number of foundations has a positiveimpact on foundation grants and hence private support. Develop-ment expenditures increase private support by a factor of 2.86. Inaddition, the matching provision of federal funding exerts a positiveinfluence on private support.

Earned income is influenced by five significant factors, three ofthose relating to alternative funding sources. Private support andinvestment income are positively related to earnings, indicating acommon source of local funding. State support exerts a positive influ-ence on earned income. We assumed that earned income increasedas public support faltered. Apparently, it is not unusual for state artsagencies to strongly encourage recipients of their grants to increaseefforts to generate earned income and have threatened to reducegrants to larger museums if they do not do so. Collection value has anegative effect on earned income. The cause of this negative and sig-nificant relationship is not obvious. Higher admission fees have a pos-itive impact on earned income. This is consistent with resultsreported by Luksetich and Partridge (1997) that the demand formuseum services is price inelastic, indicating that increased admis-sion prices (or the institution of admission charges) will enhance his-tory museum revenues.

To determine the relationship among funding sources for historymuseums, we look at the complete model. Federal support has a pos-itive and significant effect on private support; matching provisionsare likely to be stimulating private contributions. In addition, theability of a museum to generate private support enhances its abilityto generate federal funding. Private support for history museums alsoresults in increased support from state agencies. Increases in stateand local support decrease federal support; federal funding appearsto be a substitute for local and state funding of history museums.

Our estimates show that the potential impact on history muse-ums of a decrease in federal funding is not as severe as on artmuseums. Assume a decrease in federal funding for history muse-ums. State spending will increase, but private support will fall by avirtually identical amount. Secondary effects of these changes onearned income will increase the impact of a federal cutback. Theoverall impact of the decline in federal support on history museumswill not be as great as on art museums, however.

The alternatives available to history museums are similar to thosefor art museums: to increase both private support and earned income.Support from individuals, businesses, and foundations tends to stim-ulate earned income. Once again, there is no evidence that increasedsupport from these sources has any negative effect on support fromany level of government. History museum development expenditureshave a strong, statistically significant positive effect on private andlocal government support and a strong negative impact on federal andstate support. Not much confidence should be placed in these esti-mates because the aggregation of development expenditures makes it


Federal supporthas a positiveand significant

effect on privatesupport

impossible to determine individual rates of return on developmentspending; that is, we do not know where these efforts are directed.

ConclusionA major focus of this article is to trace the impacts of changes infunding sources on each other and provide information to decisionmakers with respect to the expected impact of changes. Specifically,we look at the implications for museum finances of a reduction infederal support. The major impact of a change in federal support ison private contributions, with secondary effects on earned income.Declines in federal support have a multiplier effect on museumfinances, the effects being more severe on art museums than historymuseums. Presumably, the multiplier effects of changes in federalfunding result from the presence of grant-matching requirements,the credibility federal grants provide to recipients, or both. Policy-makers will need to replace the stimulating effects of these grants ifthey are to withstand changes in sources of funding.

Increases in private support and earned income are the bestavailable alternative revenue sources. Our results also suggest thatincreased development efforts are likely to enhance revenues(particularly for history museums), although our efforts to capturetheir effects were hampered by a lack of more detailed data. How-ever, previous research by Luksetich, Lange, and Jacobs (1987)showed that the returns on these efforts were substantial. Currentresearch is being directed toward estimating the effects of develop-ment efforts, updating our study and extending our research, anddetermining the impact of changing sources of revenue on museumbehavior.

PATRICIA NOLD HUGHES is associate professor of economics at St. CloudState University. She currently serves as director of the M.S. program inpublic and nonprofit institutions, an interdisciplinary program of the Eco-nomics and Political Science Departments at St. Cloud State University.

WILLIAM A. LUKSETICH is professor and chair of economics at St. CloudState University. He has done extensive research in the economicsof nonprofits, including the cost of producing symphony orchestraservices and the efficiency of their fundraising activities, the demandfor museum services, and the economic determinants of charitablecontributions.

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the relationship among funding sources for art and history museums

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