Journal of Cultural Economics 24: 225–241, 2000.
© 2000 Kluwer Academic Publishers. Printed in the Netherlands.
225
Research Note
Corporate Support for Artistic and Cultural
Activities: What Determines the Distribution
of Corporate Giving?
MARK S. LECLAIR and KELLY GORDON
Department of Economics, Fairfield University, N. Benson Rd., Fairfield, CT 06430, U.S.A.
Abstract. This paper examines the allocation of corporate donations among various categories of
recipients and the reasons underlying that allocation. An analytical model is utilized to determine the
importance of profitability, firm size, advertising expenditures and type of business in determining
the level of support for each activity. The results demonstrate that corporate giving to artistic/cultural
activities is correlated with advertising expenditures, while donations to educational, civic and health
causes are not. Thus, support for culture and the arts is a means of directly promoting the firm, while
giving to other causes fulfills the firm’s goals through alternative means.
Key words: business objectives of the firm, corporate arts sponsorship
1. Introduction
Corporate giving, which has increased at a rate of over eleven per cent per year
since the mid-1970s, now represents a significant source of “social spending”
within the U.S. Research on corporate giving has focused on uncovering the underlying motives behind corporate donations. In particular, is business support
primarily altruistic or self-interested in nature? Obviously, the extent to which
society benefits from these expenditures depends on what motivates corporations
to make such contributions.
Previous examinations of corporate giving have focused on total corporate
donations and their motivations. Studies presented by Johnson (1966), Schwartz
(1968), Whitehead (1976), Fry, Keim and Meiners (1982), and Arulampalam and
Stoneman (1995), as well as a number of authors in Martorella, ed. (1996) all
examined the magnitude of corporate contributions and what economic motives
might lie behind the observed level of giving. This analysis will examine the allocation of corporate donations within the U.S. to cultural/artistic activities and
what motivates businesses to allocate their contribution dollars to this category of
giving. Corporations must also decide what percentage of their donations should
be devoted to other activities, such as those that support health/human services,
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MARK S. LECLAIR AND KELLY GORDON
Table I. Total corporate donations – 1980–1994 (in
millions)
Year
Funding ($)
Real funding ($)
(1982–1984 = 100)
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
2359
2514
2906
3627
4057
4472
5179
4980
4809
4893
4752
4750
5521
6305
7103
2759
2683
2965
3584
3853
4103
4691
4315
3997
3886
3552
3447
3888
4324
4745
Source: Internal Revenue Service, Statistics of
Income-Corporate Income Tax Returns.
education, and civic and community causes. A thorough empirical analysis will be
presented to demonstrate that donations to the arts are influenced by factors that
are different from those that underlie other types of corporate giving.
2. Trends in Corporate Donations
The magnitude of corporate giving, as reported by the U.S. Internal Revenue Service has risen from approximately $2.4 billion in 1980 to just over $7 billion in
1994 (see Table I), despite a decline in contributions from 1988 through 1991. This
represents an average annual increase of 8.2 per cent over the 14-year period. In
real terms, donations rose from $2.8 billion to $4.8 billion over the same period,
an increase of nearly 72 per cent. Contributions to organizations or activities that
support education represent, by a significant margin, the greatest percentage of total
corporate giving. Key targets of this funding include project or research grants,
matching gifts, and departmental grants and capital grants at the post-secondary
level. Corporate giving to health and human services causes is the second most important category, averaging 27.8% of total donations over the 11 year period from
1984 to 1994. Civic and Community activities represent a much smaller category
of corporate giving, with just 13.5% of total contributions.
CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
227
Table II. Patterns of funding for the arts – federal (NEA),
and corporate support – 1980–1994 (in millions of current
dollars, 1982–1984 = 100)
Year
Federal
Corporate
Corporate as
% of federal
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
188.1
186.8
133.4
147.5
169.9
171.7
167.1
170.9
171.1
166.7
170.8
166.5
163.0
159.7
158.1
108.7
139.6
145.8
145.2
154.7
187.5
198.7
178.6
183.6
201.2
243.6
265.4
243.6
214.3
189.3
57.8
74.7
109.3
98.4
91.1
109.2
118.9
104.5
107.3
120.7
142.6
159.4
149.4
134.2
119.7
Source: Federal funding, U.S. National Endowment for
the Arts, Annual Report, Corporate Support, Survey of
Corporate Contributions.
Corporate support for the arts, which is the focus of this analysis, has risen
measurably since the early 1980s (see Table II). As measured by a Conference
Board survey, donations to “culture and the arts” by survey participants stood at
$108.8 million in 1980 and rose to $243.6 million by 1992, an increase of over
123%. Activities supported included museums and historical societies, public television and radio, theater, and support for local and regional symphonies. Federal
support for like activities, through the National Endowment for the Arts (NEA),
is included in Table II to demonstrate the rising importance of corporate support.
While corporate giving reported to the Conference Board stood at just over half of
NEA funding in 1980, by 1992 it exceeded federal spending by over 50 per cent.
Since that time, there has been a measurable decline in corporate donations, yet the
indicated level of business giving still exceeds federal spending by nearly 20 per
cent. Authors such as Useem (1991, p. 330) have noted that those seeking funding might begin to view corporate backing as a viable alternative to government
funding, yet the differences in motivations that underlie these two types of funding
suggest that corporate support is not a true replacement for the NEA. Corporate
managers remain answerable to their shareholders, suggesting that donations must
be targeted at improving the fortunes of the firm. Useem also noted that, unlike
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MARK S. LECLAIR AND KELLY GORDON
federal support, corporate contributions are rarely targeted at individual artists or
artwork that would be considered too avant-garde. Kenyon (1996), in his examination of business sponsorship in Canada, extended this argument further. He asserts
that corporate support for the performing and visual arts tends to strengthen existing power relationships by reinforcing corporate network structures. As a result,
Kenyon argues that such donations are unlikely to be a “force of social change”
(Kenyon, p. 45).
The analysis that follows will focus on the motives that underlie corporate
contributions. An empirical model will be developed to test various assertions
regarding the primary reasons why businesses contribute to the arts. This model
will then be reapplied to the level of corporate support for the alternative categories
noted above. This disaggregation of contributions will demonstrate that donations
by firms to specific categories of giving are driven by specific motivations. One
should then be able to conclude what is unique about corporate donations to the
arts.
3. What Determines the Level of Corporate Donations?
Previous theoretical work on the motivations behind philanthropy in general include Andreoni (1990), Sugden (1982), Bergstrom, Blume and Varian (1986), and
Smith, Kehoe and Cremer (1995). Andreoni argued that giving is driven by the
potentially conflicting motives of altruism and the desire to win public praise and
acclaim. Sugden and Bergstrom et al. examined the issue of whether charitable
contributions can be viewed as an alternative means of supplying a public good.
Smith et al. utilized a large sample of observations on household characteristics
and giving, and were able to explain a significant proportion of the variation in
donations. The authors were unable, however, to separate out the effect of altruism
upon giving.
The literature that specifically addresses corporate giving is sparse. Johnson
(1966) examined how industry structure and performance affected donations, and
concluded that pre-tax profits were the primary determinant of corporate donations.
This was also the conclusion reached by Useem (1987, 1987a), who notes that total
contributions have stabilized at around one per cent of total income. In a subsequent
article, he (Useem, 1991) notes that this makes the magnitude of corporate funding
somewhat “turbulent”, as giving tends to mirror the business cycle. Johnson, as
well as Whitehead (1976), attributed the level of support to the degree of rivalry
in specific industries. Useem (1984) and Galaskiewicz (1985) asserted that corporate giving is “enlightened self-interest”, with the latter providing some statistical
evidence to support this. Schwartz (1968) and Levy and Shatto (1979) demonstrated a link between corporate giving and advertising expenditures, suggesting
that donations may be directly tied to the firm’s attempt to promote itself. Turgeon
and Colbert (1992) established a framework under which the firm can analyze its
participation in the sponsorship of the arts. The authors argue that such sponsorship
CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
229
is increasingly used as a “marketing communications device” by businesses. Fry,
Keim and Meiners (1982) regressed the level of corporate giving against advertising expenditures and a variety of other variables that measured motivations. The
authors find that contributions are strongly tied to advertising expenditures, as well
as to the compensation of corporate officers. Fry, Keim and Meiners argue that
this invalidates the argument that such giving is altruistic in nature. Arulampalam
and Stoneman (1995) conducted a detailed empirical test of the motivations underlying corporate donations utilizing data on specific firms. The authors used a
pooled time-series/cross-sectional model for 53 firms over the 1978–1986 time
period. Significant explanatory variables included the corporate tax rate, number
of employees, profits, and four industry dummy variables. Overall, Arulampalam
and Stoneman seem to confirm previous findings regarding the determinants of
corporate giving, although their model did not include advertising expenditures.
Useem (1987) emphasized the increasing professionalization and bureaucratization
of giving, as firms seek to maximize the benefits from their contribution programs,
and how this has affected the magnitude of donations. The author also noted the
importance of peer-company comparisons that “force” corporations to raise their
level of support to match that of their competitors (see also Useem (1991, p. 333)
for further elaboration on this point). The author’s 1986 survey of corporate giving
practices in Massachusetts reinforces this conclusion (Useem, 1986, p. 107). Only
29% of companies indicated that the level of NEA support influenced their grants
programs, while 50% indicated that the policies of other corporations were a major
influence.
Non-market forces that determine the level of contributions include firm size,
community characteristics and relations with other companies (see Useem, 1988).
The author (Useem (1988, p. 81) and Useem (1989, pp. 51, 59)) notes that the
single most important determinant of giving is the size of the corporation, with
larger business able to have more organized and formal programs. Other significant
determinants include the degree of interest of top management and the firm’s position within the community. Kushner (1996) expressed this in terms of stakeholder
management, arguing that executives have multiple goals to fulfill in operating the
firm, one of which is the maximization of public welfare (Kushner, 1996, p. 240).
This stands in contrast to the more traditional view that firms must act to increase
shareholder wealth. In certain circumstances, these institutional factors can be as
important as economic factors in determining the magnitude of a firm’s contribution program. In Useem’s 1986 survey of Massachusetts firms (Useem, 1986,
p. 100), he found that nearly 70 per cent of firms report that the influence of the
Chief Executive Officer on both the size and nature of giving programs exceeded
that of all other factors. For a thorough review of the literature that addresses the
level of corporate support, see Martorella (1996). Kirchberg (1995) examined the
relationship between socioeconomic conditions in metropolitan areas and the resulting level of corporate sponsorship of the arts. Utilizing data from eleven U.S.
cities for 1977 through 1991, the author demonstrated that corporate support rises
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MARK S. LECLAIR AND KELLY GORDON
both with the educational level of the population and the importance of services
in the economic base. Significantly, the author also found that donations rise and
fall with the profitability of the corporate sector (i.e. recessions). The importance
of regional factors in determining the level of donations was also emphasized by
Useem (1988). The author asserted that the most important determinant of corporate giving was the attitude of the business community towards contributions.
Finally, Galaskiewicz and Wasserman (1989) argue that corporations temper their
support for the arts to match the interests of their clientele and employees. Thus,
service industries are more likely to contribute to the arts, since their customer base
is more likely to be composed of individuals who care about the arts (a so-called
“mimetic process”).
The arguments presented above focus on the practices of U.S. businesses.
Differences in the institutional and societal environment in other nations may
produce some decidedly different patterns of corporate giving. Goncebate and
Hajduk (1996) examined the motivations behind donations in Argentina. Although
the three most important rationales for supporting the arts were similar to those
influencing U.S. corporations, improving the firm’s image, the personal interest
of key executives, and as a marketing strategy, 38% of businesses reported that
they also gave to offset falling levels of state support (Concebate and Hajduk,
1996, p. 53). This suggests that firms in Argentina have a somewhat higher sense
of social responsibility than their counterparts in the U.S. Durand (1996) argues
that Brazilian corporations that donate to the arts are motivated both by imagemaking and by the personal interests of a company’s executives and their families,
a conclusion that is consistent with the findings on corporate behavior in the U.S.
In contrast to Durand’s findings, Kirchberg (1996) concluded that firms in East
Germany donate primarily out of a sense of social responsibility, although imagebuilding was the second most important motive given (Kirchberg, 1996, p. 125).
Finally, Hitters’ (1996) examination of corporate donations in Rotterdam indicates
that firms in the Netherlands give for much the same reason that firms donate in the
U.S., with marketing and enhanced public relations given as the primary motives.
Thus, although some variations exist in business giving practices overseas, improving the prospects of the firm appears to be a consistent motive. The key difference
appears to be an elevated sense of social responsibility in certain nations.
4. The Patterns of Corporate Giving Across Industries
The proportion of total contributions that corporations devote to educational causes
varies widely across industries, from a high of 50.79% in the Transportation Equipment sector, to a low of 16.56% in wholesale/retail trade (see Table III). In general,
the percentage is higher in manufacturing sectors and lower in the services. Donations to organizations that support health/human services activities is highest in
the service industries (42 per cent of total giving in the transportation sector, for
example) and lowest in non-durable manufacturing. In the printing and publishing
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CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
Table III. Corporate giving – Percentage donated to education, health and human
services and civic/community causes, by industry for 1984–1994
Chemicals
Electrical machinery
Food and allied
Paper and allied
Petroleum
Printing and publishing
Transportation equipment
Banking
Insurance
Transportation
Wholesale/retail trade
Education
Health and
human
services
Civic
community
causes
42.0
45.3
29.3
31.7
45.1
34.5
50.8
27.1
30.5
25.5
16.7
26.7
24.9
31.7
25.9
22.7
21.3
25.5
36.0
35.4
42.0
40.4
13.0
8.3
10.8
14.5
15.1
10.4
9.2
16.2
16.8
9.1
13.6
Source: Conference Board, Survey of Corporate Contributions.
sector, just one-fifth of total donations go to activities in this category. Corporate
funding of civic/community causes is currently the smallest category of giving,
with less than ten per cent of total giving allocated to this type of recipient in
several industries. Yet, insurance and banking firms donate one out of every six
dollars to civic/community causes. The reasons behind these wide cross-industry
variations in contributions are not directly apparent. It will be possible, however, to
draw some inferences from the empirical analysis that follows. Useem (1987) noted
these differences in donation practices across industries, particularly the tendency
of high-tech firms to donate to education causes to support the training of future
workers.
The percentage of total contributions designated for culture and arts, by industry, is presented in Table IV. These comprise only 7.44% of total donations in
the chemical industry during the ten year period from 1984–1993. Similarly, for
paper and allied products and transportation equipment, grants to the arts were
just over nine per cent of total giving. Conversely, the printing and publishing,
transportation and wholesale/retail trade sectors directed more than 15 per cent of
total donations to the arts. These differences may arise from the nature of these
businesses and the advantages gained by engaging in particular kinds of activities.
Firms seeking an innovative image, such as those in the printing/publishing and
banking sectors, might find giving to the arts a suitable means of achieving that
goal. Useem (1989) attributed variations in the level of funding for the arts to
the inter-industry differences in the degree of public contact. Donations to cultural/artistic activities may also be viewed as a means of addressing industry image
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MARK S. LECLAIR AND KELLY GORDON
Table IV. Corporate giving – percentage
donated to culture and the arts by industry
for 1984–1994
Industry
Percent
Chemicals
Electrical machinery
Food and allied
Paper and allied
Petroleum
Printing and publishing
Transportation equipment
Banking
Insurance
Transportation
Wholesale/retail trade
7.44
9.54
13.15
9.17
14.31
15.06
9.33
14.61
11.63
16.09
15.95
Source: Conference Board, Survey of Corporate Contributions.
problems. Corporations in the petroleum industry, for instance, could attempt to
reverse the public’s poor impression of the industry through enlightened donations.
Useem (1987a) also noted that regional differences exist, with corporations operating in the Mid-west more likely to donate to cultural/artistic causes than firms
operating elsewhere.
As noted above, authors of previous empirical and theoretical work have suggested a number of motivations behind corporate donations. Firms may be seeking
to improve the image of the corporation, thus increasing both sales and profitability.
Corporate donations to cultural and artistic activities are prominently displayed
in annual reports and corporate promotional literature, presenting an enlightened
image to both stockholders and consumers. Senior executives may view donations
as a means of increasing their stature in the community. Corporate giving may
also be seen as a means of increasing worker morale and satisfaction, presumably
reducing employee turnover. Finally, the magnitude of business donations may be
partially determined by the economic status of the firm. One would then expect
corporate support to rise and fall with the fortunes of the industry, as contributions
are more easily justified when the firm is profitable.
5. A Model of Corporate Giving
Previous empirical work suggests that image-building is the primary motivation
behind corporate donations. Therefore, corporate giving should increase along
with advertising expenditures (as in the empirical work by Fry, Keim and Meiners
(1982)). If corporate support is targeted at raising employee morale and retention,
CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
233
then donations should rise as the number of employees increases. Profits are included in the estimation to determine whether giving is correlated with industry
performance, an outcome which would suggest that the magnitude of donations
may be at least partly driven by opportunity.1 These three variables will be expressed as a proportion of sales to eliminate size effects. Finally, a dummy variable
representing each industry will be incorporated into the estimation (as in the empirical work by Arulampalam and Stoneman (1995)). Not only is this likely to
improve the results of the estimation, but it provides useful information on differences across industries. Although it is difficult to include all aspects of Useem’s
work, the empirical model will incorporate many of the author’s assertions regarding the determinants of corporate giving. The importance of firm size is reflected
in employment levels (see details on estimation below to see why employment
was used as a surrogate for sales), while his conclusion that corporations donate
approximately one per cent of profits is explicitly part of the estimation. Finally,
the inclusion of the binary variables is consistent with Useem’s findings on the
importance of industry sector on the degree of funding devoted to cultural and
artistic activities. The importance of key executives in determining a corporation’s
contribution policy is difficult to quantify in a model of this form, and conclusions
regarding the importance of this affect must be analyzed through surveys.
6. Aggregation Issues
Consistent with previous empirical work on corporate giving (e.g. Fry, Keim and
Meiners, 1995), industry aggregates will be utilized in the estimation. Although
this has the decided disadvantage of “washing out” variations in behavior and
performance, it eliminates the use of a severely restricted sample that may bias the
results (an issue that obviously troubled Arulampalam and Stoneman (1995)).2 The
expression of profits, employees, and advertising as a proportion of sales reduces
the concern about aggregation of data, as the variables utilized are industry return
on sales, employment per unit sales, and advertising per unit sales, commonly
utilized measures of overall industry conditions.
Alternatively, one could utilize the existing firm-by-firm data on corporate giving. Unfortunately, while the Conference Board publishes specifics on the top
75 corporate donors, the identity of the firms is protected, thus preventing the
construction of a time-series sample. Recently (1997), federal legislation was introduced in the U.S. to force businesses to divulge specifics on their contribution
programs, but this is being fought both by corporations and by business organizations. Future research in this area is likely to focus on the behavior of specific
firms, but at present, empirical work is confined to the aggregate numbers that are
available.
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MARK S. LECLAIR AND KELLY GORDON
7. Pooling
Empirical investigations into the philanthropic behavior of U.S. Corporations has
been constrained by an insufficient number of time-series observations. Consequently, authors such as Arulampalam and Stoneman have resorted to utilizing
pooled cross-sectional and time-series estimations to obtain sufficient degrees of
freedom; an approach that will be pursued here. Currently, eleven years of industryby-industry data exists on the beneficiaries of corporate giving. A total of 11
distinct industries were then identified,3 in order to provide 121 total observations.
The error terms arising from the estimation will be assumed to be both heteroskedastic and auto-correlated, requiring the use of a Generalized Least Squares (GLS)
model.
8. Empirical Model
The results reported below reflect five different estimations of the basic model:
Cit = F (Ait , Lit , Eit , Di )4
where
Cit
Ait
Lit
Eit
Di
=
=
=
=
=
Corporate contributions/sales.
Advertising by ith industry in tth year/sales.
Employment/sales.
Industry profits/sales.
Industry dummy variables, i = 1, 11.5
The first estimation will use corporate giving to culture and the arts as the dependent variable. The equation will then be re-estimated using donations to education
causes, health and human services organizations, civic/community activities, and
finally total donations. The results of the latter models will then be compared to
those for giving to culture and the arts to determine if significant differences arise.
This should provide additional insights into the motives behind corporate contributions. Although Arulampalam and Stoneman have estimated their model in log
form, this was presumably a means of reducing the degree of heteroskedasticity
affecting the estimation. Since a GLS model will be utilized here, concerns about
heteroskedasticity are eliminated, and the model will be estimated without a log
transformation. Finally, Arulampalam and Stoneman included a time trend variable
in their empirical model. Preliminary analysis of the data set utilized here showed
it to be insignificant.
CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
235
9. Data
Data on corporate donations, cross-referenced by industry and beneficiary, are
available annually from the Conference Board’s annual survey on corporate giving (Conference Board, 1984–1994). These figures represent the percentage of
total donations relegated to each of five major categories of recipients: Health
and Human Services, Education, Culture and the Arts, and Civic/Community
Causes. These percentages can then be multiplied by the corresponding figure for
“contributions or gifts” published by the Internal Revenue Service in Statistics of
Income-Corporation Income Tax Returns (IRS, various dates). This results in a
reasonable estimate of total corporate giving in each category. This document also
provided figures for both industry profits and sales. Finally, employment statistics
were drawn from Employment, Hours and Earnings (U.S. Dept of Labor, various
dates).
10. Results
The outcomes of the five estimations are presented in Tables V–IX. For the most
part, the results are consistent with previous empirical work on corporate giving.
Donations to culture and the arts as a percentage of sales rose with advertising
expenditures as a proportion of sales (Ait ), with the rate of profitability (Eit ), and
with the level of employment per unit sales (Lit ). The coefficients on these three
variables are significant at the 1% level, and the model explains just under twothirds of the variation in the donation to sales ratio. The profit-sales ratio is the
most significant of the three key variables. Although quite small in magnitude,
this coefficient expresses the direct linkage between profitability and the level of
support. This provides direct support for Useem’s (Useem, 1987, 1987a) assertions
regarding the importance of earnings as a determinant of donations. The significance of advertising expenditures is consistent with the findings of Schwartz, Levy
and Shatto, as well as those of Fry, Keim and Meiners. Unlike previous empirical
work, however, advertising expenditures are less significant than other factors in
determining corporate donations. The key role played by both industry profitability
and employment is more consistent with the empirical work of Arulampalam and
Stoneman, as well as the findings of Useem.
Three of the ten industry dummy variables were significant, representing the
petroleum industry, printing and publishing, and banking.6 All three coefficients
were positive, indicating higher donations to the arts in these three sectors. Consistent with hypotheses, the higher donations on the part of the petroleum producers
are an attempt to address the industry’s persistent image problem. Firms in the
printing/publishing and banking sectors more likely view contributions as a means
of projecting an enlightened image to the public, a result that is in full agreement
with Useem’s findings that service sector firms are more likely to donate to the
arts. Although Arulampalam and Stoneman also found inter-industry differences,
their study found an increased level of giving in the Food, Alcohol and Tobacco
236
MARK S. LECLAIR AND KELLY GORDON
Table V. Regression results – corporate donations to the arts
Variable
Estimated
coefficient
T -statistica
Advertising/sales
Profits/sales
Employees/sales
Dummy (petroleum)
Dummy (print/pub.)
Dummy (banking)
0.0013
0.0011
0.0089
0.0541
0.0981
0.0770
3.41
5.78
4.45
2.96
5.74
5.07
a N = 121; Adjusted R-squared = 64.8%; F -stat. = 34.91.
All variables significant at the 1% level.
Table VI. Regression results – corporate donations to education
Variable
Estimated
coefficient
T -statistica
Advertising/sales
Profits/sales
Employees/sales
Dummy (chemicals)
Dummy (print/pub.)
Dummy (insurance)
Dummy (transportation)
Dummy (wholesale/ret.)
–0.00003
0.0023
0.2118
0.2419
0.1196
–0.1267
–0.2196
–0.2261
–0.03b
4.40
4.01
5.78
2.69
–3.68
–4.67
–5.66
a N = 121; Adjusted R-squared = 74.89%; F -stat. = 41.75.
b Rejected.
All variables significant at the 1% level.
Table VII. Regression results – corporate donations to health and
human services activities
Variable
Estimated
coefficient
T -statistica
Advertising/sales
Profits/sales
Employees/sales
Dummy (chemicals)
Dummy (food and allied)
Dummy (print/pub.)
Dummy (banking)
–0.0039
0.0021
0.0180
0.2483
0.2547
0.1829
0.1736
–1.55b
5.36
5.14
3.73
2.91
4.90
6.61
a N = 121; Adjusted R-squared = 68.53%; F -stat. = 35.16.
b Rejected.
All variables significant at the 1% level.
CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
237
Table VIII. Regression results – corporate donations to
civic/community causes
Variable
Estimated
coefficient
Advertising/sales
Profits/sales
Employees/sales
Dummy (electr. mach.)
Dummy (banking)
0.0008
0.0020
0.0065
–0.0454
0.0623
T -statistica
1.69b
8.35
3.60
2.50c
3.32
a N = 121; Adjusted R-squared = 50.41%; F -stat. = 23.38.
b Rejected.
c Significance at the 5% level, all others at 1%.
Table IX. Regression results – total corporate donations
Variable
Estimated
coefficient
T -statistica
Advertising/sales
Profits/sales
Employees/sales
Dummy (chemicals)
Dummy (printing/pub.)
Dummy (banking)
0.0102
0.0110
0.0294
0.1682
0.5030
0.3544
5.61
11.65
4.00
2.13b
6.55
5.21
a N = 121; Adjusted R-squared = 82.3%; F -stat. = 88.46.
b Significance at the 5% level, all others at 1%.
and Leisure industries. In agreement with the findings here, Arulampalam and
Stoneman did find a higher level of donations in the Financial Services sector. The
variations between the two outcomes probably arises from differences in the data
set that was utilized. Arulampalam and Stoneman used disaggregated data from
the United Kingdom, while this study employed industry-wide observations from
the U.S. In addition, while this prior study used total donations as the dependent
variable, the first phase of this estimation used only donations to culture and the
arts.
The results from the estimations utilizing corporate donations to causes other
than culture and the arts provide some interesting contrasts (see Tables VI–VIII).
For the estimation utilizing donations to education, profitability and employment
remain significant, but donations are not positively correlated with advertising expenditures. This appears to conform to the assertion that contributions to education
may be motivated by reasons other than the promotion of the firm. In addition,
while firms in the printing/publishing industry were more likely to donate to educational causes, a result consistent with the findings for the previous estimation,
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MARK S. LECLAIR AND KELLY GORDON
the rest of the industry effects are entirely different. Donations were significantly
higher in the chemical industry, and significantly lower in the transportation, insurance and retail/wholesale trade sector. Generally, then, corporate donations to
education are higher in the manufacturing sectors than they are in the transportation
or services sectors.
The outcomes for both health and human services donations and those to
civic/community causes are similar. For the former, both profitability and employment are significant at the 1% level, while advertising expenditures are rejected
by the model. The binary variables for chemicals, food/allied, printing/publishing
and banking are all positive and strongly significant. Similarly, corporate giving
to civic/community activities also rises with profitability and employment, and
advertising expenditures are once again rejected. Only two binary variables are
accepted by the model, those representing electrical machinery, where donations
fall below those of firms in general, and banking, where giving exceeds that of
other sectors.
Are there significant differences between total corporate giving and that targeted
specifically at arts and culture? Table IX presents the results of the estimation
that utilized total corporate giving as the dependent variable. The link between
advertising expenditures and donations is now substantially stronger than in the
first estimation. Once again, both profitability and employment are important determinants of corporate contributions. Total donations are more strongly influenced
by advertising expenditures (with a t-statistic of 5.61) than are donations to the arts
where the level of employment is more important.
11. Summary and Conclusion
Table X contains a complete summary of the empirical results arising from the
five estimations. In all cases, both profitability and employment were significant
determinants of corporate contributions. Yet, only for total donations and donations
to culture and the arts were advertising expenditures significant. This suggests
that promotion of the firm is a key motivation behind giving to the arts but is
not a determinant of giving to other causes. Thus, the conclusions reached by
Schwartz (1968), Fry, Keim and Meiners (1982), and Levy and Shatto (1979) on the
importance of self-promotion in determining contribution levels is supported for
giving to the arts but not for donations targeted at other categories of giving. This
suggests that empirical work that utilized simply total contributions most likely
missed some interesting patterns in corporate support. The conclusions reached by
Johnson (1968), Useem (1987, 1987a), and Arulampalam and Stoneman (1995)
about the significance of profits holds true for all categories of giving. One can
reasonably conclude that giving is partly determined by the rising fortunes of a
particular industry and the resulting ability to increase donations without upsetting
stockholders.
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CORPORATE SUPPORT FOR ARTISTIC AND CULTURAL ACTIVITIES
Table X. Summary of results – significance of variables
Factor
Arts
Education
Health
Civic
Total
Profitability
Employees
Advertising
Binary variables
Chemicals
Electrical mach.
Food/allied
Paper/allied
Petroleum
Printing/pub.
Transportat. equip.
Banking
Insurance
Transportation
Wholesale/retail
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
No
Yes
Yes
No
Yes
Yes
Yes
No
No
No
No
Yes
Yes
No
Yes
No
No
No
Yes
No
No
No
No
Yes
No
No
Yes (<0)
Yes (<0)
Yes (<0)
Yes
No
Yes
No
No
Yes
No
Yes
No
No
No
No
Yes (<0)
No
No
No
No
No
Yes
No
No
No
Yes
No
No
No
No
Yes
No
Yes
No
No
No
Table X also provides some interesting insights into inter-industry patterns of
giving. The conclusion reached by Galaskiewicz and Wasserman (1989), that service sector firms donate more than manufacturing firms, appears to hold true only
for the banking sector. In not a single one of the four major categories of giving
did the insurance, transportation, or wholesale/retail trade sectors exhibit donations
that exceeded those of firms in general (in fact, contributions to educational causes
were significantly depressed). The pattern of giving in the petroleum industry is
also of interest, since only in this sector were donations to culture and the arts
increased while contributions to other causes were unaffected. The authors believe
this to be a reflection of the relatively negative impression that the public has of
firms in this sector of the economy. Donations to the arts provides such businesses
with a means of projecting an enlightened image to potential customers. This
provides additional evidence to support the conclusion that the support of cultural
and artistic activities is primarily a means of promoting the firm. Inter-industry
differences also lend support to Useem’s assertion that the donation practices of
peer companies are a significant determinant of business giving, as the adoption
of similar patterns of support within an industry group helps explain significant
cross-industry variations (Useem, 1988). This study does not address the situation
raised by Kirchberg (1996) in which contributions in East Germany were partly
motivated by a sense of social responsibility. To what degree this can be applied
to the U.S. economy is an area for future empirical work. Finally, the importance
of factors such as the interest of key executives or the firm’s position within the
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MARK S. LECLAIR AND KELLY GORDON
community must be examined utilizing firm-specific data, information hopefully
available to researchers in the future.
Notes
1. One could argue that the causation between profits and contributions runs in reverse, with
donations resulting in increased profitability. The two variables are measured concurrently here,
however, and one would assume that donations would affect profitability only with a lag.
2. Although the use of firm-by-firm data is undoubtedly an improvement, the authors note that
the data set is flawed in that it contains only those companies that donate large amounts to
charity. In addition, as the authors are using pooled time-series/cross-sectional data, only those
companies that were large donors over the entire sample period (1978–1986) were left in the
sample. Consequently, only 53 firms were ultimately retained in the data set.
3. The number of industries in the estimation was partly constrained by inconsistencies between
industry categories used by the International Revenue Service, and those utilized by the
Conference Board. Industries were eliminated if no correspondence could be established.
4. Previous empirical work has also included the difference between corporate tax rates and individual tax rates as a variable, with differences between the two inducing executives to donate
through the corporation rather than individually. A quick examination of corporate and individual
tax rates, however, shows them to be relatively fixed, and thus unable to explain variations in
corporate giving.
5. Inclusion of all eleven binary variables would, of course, preclude estimation of the equation.
Preliminary empirical testing was used to eliminate one binary variable from each estimation.
6. To avoid unnecessary clutter, coefficients and t-statistics are included for significant binary variables only. A summary of the significance of all dummy variables in all estimations is contained
in Table X.
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