Do Shareholders value Corporate Philanthropy?: An Event Study Test
Paul C. Godfrey
Craig B. Merrill
Marriott School of Management
Brigham Young University
Jared M. Hansen
Texas Tech University
Contact Author Information
Paul C. Godfrey
789 TNRB
Brigham Young University
Provo, UT 84602
(801) 422-4522
(801) 422-0539 FAX
Paul_Godfrey@byu.edu
This draft is intended for review and feedback. Before citing results reported in this
paper, please contact the authors for updated information.
ABSTRACT
Why should rational, profit maximizing managers invest in philanthropy? Godfrey (2005)
proposes a new mechanism for shareholder value: Cash flow preservation vs. cash flow
creation. The theory presents an intriguing rationale for philanthropy and CSR, but is as
yet untested; the major contribution of this paper is to provide a direct test of the theory’s
core propositions. Using a sample drawn from the KLD data base, we use an event study
model to examine the effect of philanthropic giving on abnormal stock returns
surrounding negative legal or regulatory events for 151 companies between 1993 and
2000. The results indicate strong support for the idea that philanthropic giving provides
insurance value for shareholders. The study also finds that higher levels of participation
in philanthropy do not provide extra insurance protection, and that more tangible forms of
giving provide better insurance protection than less tangible forms. (144 words)
Key Words: Philanthropy, Event Study, Insurance, Corporate Social Responsibility
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Do Shareholders value Corporate Philanthropy?: An Event Study Test
Why should rational, profit maximizing managers invest in philanthropy?
Adherents of strict capitalism and fiduciary duties point out that philanthropy yields no
tangible, transactional returns to the firm and is inconsistent with the managerial
obligation to return cash to shareholders (Easterbrook & Fischel, 1991; Financial
Accounting Standards Board, 1993; Friedman, 1970). The case for philanthropy comes
from two different sources; strategic philanthropists argue that, while philanthropy may
not generate direct economic returns, it will enhance the firm’s long term competitive
position through intangible gains in reputation, legitimacy, or employee loyalty
(Fombrun, Gardberg, & Barnett, 2000; Jones, 1995; Post & Waddock, 1995). Business
citizenship scholars hold that businesses, granted the right to exist by the larger society,
have an obligation to return part of their earnings to that society, philanthropy stands as
an obligation borne by business citizens of a community (Logsdon & Wood, 2002;
Waddock, 2001; Wood & Logsdon, 2002). The profitability of philanthropy is one
concrete example of the larger, longer debate on the relationship of Corporate Social
Responsibility (CSR) to Corporate Financial Performance (CFP).
This larger debate about whether or not CSR contributes to CFP has a long and
tortured history. Godfrey (2005) proposes a new mechanism for shareholder value: Cash
flow preservation vs. cash flow creation. While current models use a forward, or “front
door,” model (where CSR leads to enhanced CFP), Godfrey’s model suggests a “back
door” mechanism (where CSR protects and insures CFP); Godfrey’s model stands as a
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complement to instrumental theory1. The theory presents an intriguing rationale for
philanthropy and CSR, but is as yet untested; the major contribution of this paper
is to provide a direct test of the theory’s core propositions.
The empirical literature the CSR-CFP link is a quagmire of conflicting results.
(Margolis & Walsh, 2001), in an exhaustive study of the empirical literature in this area,
note that thirty years of work has not yielded a clear and unequivocal finding in either
direction. Within this body of general work is a set of studies dealing with the value of
behavioral signals in during crisis. This body of work is broadly consistent with the
insurance model we test here. These studies consist of two broad types, both looking at
idiosyncratic firm-specific profiles in a context of events common across the sample.
First, broad, abstract use of CSR measures linked to economy-wide events. (WTO study,
2005; 1987 stock crash study), and second, firm specific, narrow measures against
common industry events. The cotton dust study (1983); and the Chemical industry
studies (Northcutt etc.)—social reporting, not activity
Both types show limited support for the Godfrey hypothesis about CSR. Neither
study provides a direct test, however, as this work doesn’t specifically model
philanthropy, nor does it investigate the phenomena at the level of individual firms. We
employ a different level of matching: a set of firm-specific attributes (telescoping from
broad to narrow) matched with firm-specific events. Thus, we look at idiosyncratic
profiles in idiosyncratic contexts. A more stringent test of any central tendency and
1
The insurance model also complements the Business Citizenship logic. Godfrey (2005) notes that the
insurance view leads managers to make similar types of investments in social issues and activities as those
recommended by Citizenship scholars; however, the fundamental motivation differs. Under a citizenship
regime managers act without thinking of profit concerns, while under the insurance model (and the
strategic philanthropy model) managerial motivations center on the profit opportunities afforded through
CSR activities.
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a more direct test of the idea that philanthropy or other CSR’s represent
individualized insurance policies for firms.
This paper also advances and tests three theoretical extensions to Godfrey’s
(2005) core model. First, does the insurance effect generalize beyond philanthropy?
Philanthropy produces moral goodwill because it is a purely discretionary activity
(Carroll, 1979). Godfrey asserts, but does not explore, that other discretionary CSR’s
(diversity initiatives, labor practices, environmental preservation). Our data set allows us
to examine the effect of several discretionary CSR’s on shareholder wealth.
Second, is the insurance effect subject to decreasing marginal returns? The
economics of insurance stipulates a clear optimal premium level with investments beyond
the optimal level of involvement representing dead weight losses. In terms of CSR
helping insure the economic value of a firm’s intangible asset base the hard logic of
optimality may break down. Uncertainty surrounding the value of the intangible
(relational) assets, and the exact amount of goodwill generated through philanthropy
means that rational executives may insure at some level in the neighborhood of the
optimum and may err on the side of over-involvement in the hope of providing adequate
“coverage.” We hope to shed light on this issue by raising the question Does increasing
the level of commitment to philanthropy result in greater levels of shareholder wealth
protection?
Third, we extend the insurance model by asking Does the type of giving matter?
Philanthropy, in particular, is problematic because its noise/signal ratio may be rather
high; does a firm donate to the symphony to get prime seats for executives and spouses,
or to support community activities? If philanthropy provides a signal for a firm’s moral
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intentions, commitments, and coloration (Jones, 1995), then do different types of
philanthropic activities have different signal values?
We present our argument and evidence as follows. We first provide the
theoretical rationale and hypotheses we test. We then describe our methodology, data set,
and the variables used to test our hypotheses. We next present the results of our analysis
and the findings in terms of support for, or rejection of, our hypotheses. We conclude by
noting the limitations of our work and considering the implications of our findings for
both academics (theorists and empiricists) and practicing managers.
THEORY AND HYPOTHESIS DEVELOPMENT
Key Theoretical Constructs
Philanthropy and CSR Philanthropy is “an unconditional transfer of cash or other
assets to an entity or a settlement or cancellation of its liabilities in a voluntary
nonreciprocal transfer by another entity acting other than as an owner (Financial
Accounting Standards Board, 1993); emphasis original)”. Corporate social responsibility
is defined as actions that are not required by law but that appear to further some social
good, and extend beyond the explicit transactional interests of the firm (McWilliams &
Siegel, 2001). Both philanthropy and CSR constitute voluntary and discretionary actions
by firms, around which stakeholders can make moral attributions of intention.
Intangible (relational) assets. Many of a firm’s most valuable assets are resources
are intangible, idiosyncratic to the firm, and may have been developed over a number of
years (Barney, 1991; Dierickx & Cool, 1989). A number of a firm’s resources are
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relationship-based because the earning potential of these assets depends on the
relationships a firm has with its stakeholders and the related assessments these
stakeholders make regarding some (or all) elements of the firm’s activities (Wood &
Jones, 1995). Examples of these assets are reputation, loyalty, legitimacy, and trust.
These relationship-based intangible assets are termed relational wealth in the Clarkson
Principles of Stakeholder Management (Business Ethics Quarterly, 2002).
Moral capital/ insurance Jones (1995) offers an account of a firm’s moral
reputation wherein stakeholders assess interactions between the firm and its constituents
within the overall strategic context of the firm —its visions, strategies, policies, systems,
etc.— that all reflect some degree of “moral coloration” by the firm’s policy maker.
From these morally colored activities and contexts stakeholders impute moral values,
principles, intentions, and character elements. Philanthropy constitutes an action (or
interaction) between the firm and its constituents within a context rich in moral intention
and coloration; the resulting moral capital represents the outcome of the process of
assessment, evaluation, and imputation of moral values and character by stakeholders and
communities of a firm based on its philanthropic activities.
Shareholder Value Shareholder wealth is the expected discounted value of a
firm’s anticipated cash flow stream from the employment of its tangible and intangible
assets, consistent with the prescriptions of the Capital Asset Pricing Model (Brealey,
Myers, & Marcus, 1995). Insurance adds value to a firm’s equity price by protecting
shareholders against risks, such as bankruptcy, that may make it difficult to liquidate a
position profitably (Stultz, 1996).
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Negative Events organizational acts adversely affect stakeholder groups and the
communities to which they belong; organizational action or conduct that creates adverse
impact on a stakeholder group constitutes the bad act element of an offense.
Philanthropy/CSR as Insurance
The mens rea effect of CSR. Under the common law tradition, two elements must
be present for an offense to occur: a bad act and a bad mind (LaFave, 2000). A bad act
requires that some action or conduct be performed that creates harm or adverse impact on
another, be it an individual, group, or community. Bad acts must be accompanied by a
bad mind in order to constitute an offense, for “Actus not facit reum nisi mens sit rea (an
act does not make one guilty unless his mind is guilty)” (LaFave, 2000: 225). This is the
doctrine of Mens Rea. The logic of corporate Mens Rea parallels organizational
scholarship that views corporations as secondary moral agents (Wherhane, 1985) or as
moral agents but not moral actors (Werhane, 1985; Wood & Logsdon, 2002). The
doctrine of Mens Rea also underpins the U. S. sentencing guidelines, both the 1991
original and the 2004 revisions. Jurists seek for evidence of proactive ethical and
preventive behaviors, as well as considering the firm’s history of ethical and compliance
performance when considering punitive sanctions for corporate misdeeds.
When bad acts occur, Godfrey (2005) argues that stakeholders invoke the
cognitive template suggested by the Mens Rea doctrine to help determine appropriate
sanctions. As stakeholders consider possible punishments and sanctions, positive moral
capital acts as character evidence on behalf of the firm. Positive moral capital provides
counterfactual evidence to mitigate assessments of a bad mind; positive moral capital
reduces the probability that the firm possessed the evil state of mind that justifies harsh
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sanctions (Strong, 1999). Positive moral capital encourages stakeholders to give the firm
the benefit of the doubt regarding intentionality, knowledge, negligence, or recklessness.
Positive moral capital also addresses the relevant issue of a firm’s history of moral
behavior. If stakeholders follow the Mens Rea template found in the United States
Sentencing Guidelines, then the nature and severity of punishments for bad acts will be
significantly influenced by stakeholder assessments of a bad mind. Negative sanctions
may aim to remedy the causes or consequences of adverse impacts, they may seek
compensation for adverse impacts, or sanctions may aim to punish the firm and deter
future adverse impacts. Remedial sanctions may include new regulations or laws aimed
at limiting behavior or establishing future liability, or simply increased scrutiny and
monitoring by affected stakeholder groups. Compensatory sanctions may include fines,
lawsuits, or other actions aimed at financially compensating impacted groups. Punitive
sanctions may include fines, incarceration for key individuals, negative publicity
campaigns, or boycotts of the firm’s products or services. Punitive actions may also
come in the form of decreased willingness to do business with the firm, or loss of
reputation, loyalty, trust, or legitimacy.
Moral capital provides insurance-like protection to relational wealth because it
fulfills the core function of an insurance contract: it protects the underlying relational
wealth and earnings streams against loss of economic value arising from the risks of
business operations (Trieschmann & Gustavson, 1998). Positive moral capital provides a
reservoir of positive attributions that can be drawn upon to “indemnify” relational wealth
against loss of value when stakeholders are adversely affected. This logic gives rise to
H1a: In the context of a negative event, declines in shareholder value
will be smaller for philanthropic than non-philanthropic firms.
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Godfrey’s (2005) argument centers specifically on philanthropy; however, the
logic of Mens Rea and insurance value should apply for other discretionary CSR’s as
well. The discretionary aspect of other CSR activities—those exceeding legal or ethical
mandates—allows stakeholders to make attributions of moral coloration or character in
relation to these actions as well. If discretion is the driver of moral attribution then firms
having exemplary labor relationships, strong efforts to promote diversity in the
workplace, a commitment to quality products, and/or a solid record of pro-active
environmental stewardship should enjoy the same accumulation of moral capital. We
aim to test this proposition directly through
H1b: In the context of a negative event, declines in shareholder value
will be smaller for firms engaging in other discretionary CSR’s
(employee relations, diversity, product quality, and environmental
stewardship) than firms not engaging in discretionary CSR’s.
Philanthropy and Intangible (Relational) Assets
Firms have two types of value producing assets—tangible and intangible.
Tangible assets, such as property, plant, and equipment, can be insured through
traditional indemnity contracts. Intangible assets, such as brand, loyalty, trust, or
legitimacy, do not possess the criteria needed for indemnification in traditional insurance
markets. Rejda ((Rejda, 1992): 24) outlines a number of criteria for a functioning
insurance market to exist that intangible assets do not meet. First, there must be a large
number of homogeneous exposure units (objects to be insured); however, relational
wealth—like trust or brand—is not homogenous but rather idiosyncratic to a particular
relationship between a given firm and a given set of stakeholders. Second, probable
losses must be accidental and unintentional; while some events that cause loss to the
value of relationship-based intangible assets may be accidental or unintentional many of
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the events that negatively impact firm-stakeholder relationships are conscious and
deliberate decisions (e.g., closing a plant, discontinuing a product or a product line,
stretching out suppliers’ payment terms beyond reasonable limits, cutting philanthropic
activity to community groups). Third, the loss must be determinable and measurable; the
magnitude of loss to relational wealth is difficult to ascertain both ex ante—no original
invoice exists for brand or loyalty—and ex post—losses may occur over a broad
geographic region or persist through time.
If philanthropy offers insurance-like protection for a firm’s intangible asset base,
and if managers are aware of this relationship, then we would expect
H2: Philanthropic firms will have higher levels of intangible assets
than non-philanthropic firms.
The Marginal Value of Philanthropy
Godfrey (2005) adopts the underlying logic of the economics of insurance in
making his argument. One of those tenets is that there is an optimal value of insurance
protection; to under-insure is to leave assets exposed to risk of loss, to over-insure is to
pay premiums for no additional coverage (the indemnity is based on the value of the
asset, not the amount of the premium). This optimal premium proves relatively simple to
calculate, given the values of the assets at risk and the pricing and structure of traditional
indemnity contracts.
Philanthropy, and CSR in general, present two significant confounds to the
economics of insurance. First, as we noted above, intangible assets are difficult to
value—certainly to the level of precision necessary to calculate an optimal premium.
Managers or risk assessors may estimate with confidence some range of value for each
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intangible asset; however, a range is not a point estimate. Under such an estimation
regime, managers may have incentive to “over-insure” or make investments in
philanthropy. Since philanthropic investments send signals of a firm’s moral coloration
and intentions (Jones, 1995), and since the assessment of these moral attributes results in
positive moral capital, then greater levels of investment should lead to greater levels of
goodwill.
Second, managers are unsure of the exact “indemnity” offered by stakeholders.
Unlike a formal contract that specifies in clear detail the payouts for different assets at
risk, including property, plant, and protection against cash flow interruptions. The moral
capital and goodwill generated by philanthropy works on an implicit and tacit agreement.
Stakeholders form their own assessments and, when negative events occur, they create
some idiosyncratic indemnity value. Thus, managers have incentive to “over-insure” in
order to increase the probability that stakeholders have the requisite information to grant
ample amounts of goodwill based indemnity. This logic leads to:
H3a: In the context of a negative event, high participation in
philanthropy (or other CSR’s) will have a positive effect on preserving
shareholder value
An opposite case can be made as well, which focuses on the ex post invocation of
goodwill as indemnity. Take for granted that higher levels of philanthropy do in fact lead
to a greater stock of moral capital. Along with such greater goodwill, however, comes a
greater expectation on the part of stakeholders that the firm will behave in ways
consistent with its image and goodwill. Negative events may constitute a “fall from
grace,” however, as stakeholders observe that the firm and its managers behavior is not
consistent with such high expectations. Rather than granting forgiveness for human
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error, stakeholders may believe that the high levels of philanthropic activity represented
an attempt at ingratiation rather than a sincere commitment to good works. Under such a
regime, stakeholders may be more, rather than less, likely to punish the firm; first for the
negative event itself and second for the perceived ingratiating behavior (Godfrey, 2005;
(Gordon, 1996). This logic leads to
H3b: In the context of a negative event, high participation will have a
negative effect on shareholder value
Tangibility and Signal Value
Philanthropy has been impaled in the literature as both an unfair tax on
shareholders (Friedman, 1970) and as the provision of an untaxed, discretionary benefit
to management. Attending the symphony, opera, or art exhibit as the CEO of a company,
under the guise of corporate philanthropic support, represents a unique form of on-the-job
consumption (Gillmor, 1999; Minow, 1999). Certain types of philanthropic donations,
whether done directly or a corporate philanthropic foundation, will be subject to cynicism
and multiple interpretations by stakeholders. Specifically, donations that are abstract or
less tangible in nature, such as reporting that the corporation spent 1.5% of its net income
on philanthropic activities without detailing where those donations went or what process
was used to determine grantees, send signals of moral coloration and intention with a
high noise/signal ratio. These types of philanthropy provide “muddy” or “cloudy”
signals about the morality of managerial motives because the lack of information
contained in the signal cannot adequately thwart the interpretation of managerial perktaking.
Corporate giving can be structured in ways that reduce the noise/signal ratio and
provide a much clearer signal of moral coloration and intention. Clear and transparent
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donation criteria and processes reduce the ambiguity around managerial “discretion” and
perk-taking. The recipients of donations may also provide clarity as to intentions. To
contrast with our description above, we describe these types of gifts and giving as more
concrete, or more tangible. For example, a corporate philanthropic gift providing low
income housing, heating bill assistance for the elderly or indigent, or support of K-12
education in local neighborhoods provide clear signals because even the most hardened
cynics realize the CEO or members of the top management team are unlikely to live in
low income housing, need assistance with their heating bills, or send their children to the
K-12 institutions receiving corporate grants. This distinction is captured in
H4a: In the context of a negative event, more tangible forms of philanthropic giving
will have a positive effect on shareholder wealth
H4b: The effect will be stronger (more positive) than the effect of less tangible
forms of philanthropic giving.
METHODOLOGY, DATA, AND FINDINGS (12 PAGES)
Methodology
Godfrey’s (2005) theory, that philanthropy protects intangible assets when
negative events occur, suggests that an event study is not only an appropriate
methodology, but the method that will provide the most direct empirical test of the
theory’s core propositions. McWilliams and Siegel (McWilliams & Siegal, 2000)
criticize the use of event studies in management, and in the social responsibility field in
particular, on four grounds. First, they argue that the methodology has been used as a
convenient method of investigating financial effects of CSR, but the method has not been
explicitly linked with the theory. As we note, and event study provides the most direct
test of the Godfrey theory.
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Second, McWilliams and Siegel (2000) note that many event studies are not
consistent with the efficient markets hypothesis. Efficient markets hypothesis holds that
investors will rapidly incorporate new and unexpected information about a firm into its
share price. Thus, the specific “event window”—the time frame investigators use to
measure investor adjustments to the stock price—must be sufficiently short. For
example, McQueen and his colleagues show that investors incorporate new macroeconomic information into their pricing models in a matter of minutes (CITE NEEDED).
We estimated our models using a series of nested event windows, beginning with a very
narrow window (t (the event day) and t-1 (a 2-day tight window) and a broader window
(a 5-day, t-2 through t+2, window).
Third, consistency with efficient markets hypothesis further means that the event
under study should be the only relevant event that investors would incorporate into their
pricing calculations during the event window. Material events that coincide with the
event of interest, such as earnings announcements, new product announcements, major
sales, or a merger or acquisition announcement, confound the ability of the event study
methodology to assign abnormal share price movements to the focal event. In their
review of CSR related event studies, McWilliams and Siegel (2000) found that in one
extreme example, the entire data set should have been discarded because of confounding
events.
Fourth, McWilliams and Siegel (2000) note that several studies rely on extremely
small sample sizes, sometimes as small as 20. For an event study to produce meaningful
results the sample size must be large enough to have sufficient statistical power and to
warrant claims of generalizability.
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Data and Variables
Sample. The KLD Socrates data base constitutes the universe of potential
samples for our study. The Socrates data base contains 3rd party assessments (done by
KLD personnel) of a firm’s performance along several social involvement and
responsibility dimensions for each firm in the S&P 500 since 1991. We limited our
sample to the decade 1991-2000 and drew our sample from firms in data set for all years,
or 160 firms. We chose this sample because we assumed that relevant negative events
would be relatively rare (we would need a large time horizon from which to draw a
significant number of events) and that any relationship between philanthropy and share
returns would not depend on the time frame of the study. Our net sample of 160 firms
yielded 254 possible events, with 99 firms experiencing an event and 61 firms not
experiencing an event. We chose 2000 as the closing year of our study because in late
1999 and throughout 2000 the industry experienced a wave of merger activity that
created a new category—the supermajors.
Dependent Variable: The dependent variable is the abnormal return to a firm’s
share price experienced in the event window surrounding a negative event. We defined
the negative event of interest broadly, as the initial public report of a lawsuit or regulatory
action against a company in the sample. We used the Wall Street Journal as our source;
as the premier business newspaper in the United States, the Wall Street Journal produces
reports, announcement, or stories about material events affecting large publicly held and
private companies. The Journal often picks up and reports material events reported in
smaller local papers. Our initial search yielded 254 potential events, of which we settled
on a sample of 204 negative events. We eliminated events that were negative, but not
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legal or regulatory (such as an announcement of layoffs), or were legal but positive for
the company (such as winning a lawsuit or having a positive regulatory finding), or those
that dealt with individuals within a company or formerly associated with a company. We
then screened these events for confounds by searching the Wall Street Journal using a 7
day window (t-5, t+2) for other material announcements. We also eliminated events for
which we did not have corresponding KLD reports of firm CSR activities. This yielded a
final sample of 151 events. Thus, our sample size is large enough to run regressions with
enough power to warrant confidence in our results.
The abnormal return is defined as CARit 
n
 (R
it
 Eit ) for the ith firm over the
t  n
event window centered on t (t=o represents the event day) and bounded by n (the window
on either side), R represents the actual change in stock price, and E captures the expected
(equal-mean-value) return for the share price on that day. CAR captures the sum of the
day-to-day differences between the firm’s actual and expected returns. The narrowness
of our windows is consistent with efficient markets hypotheses and answers one critique
of McWilliams and Siegel (1999).
We drew stock return data from the Center for Research in Security Prices
(CRSP) data tapes and used the Wharton Research Data Service modeling software to
calculate an equal-mean-value, market adjusted expected stock return for each firm by
using the previous 180 days returns as regression inputs to calculate anticipated return.
We estimated CAR for two windows to account for different assumptions about leakage
(public knowledge of the event before its publication in the Wall Street Journal), and
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interpretation (some events may contain enough ambiguity that investors take time to
factor in the impact of the event on price).
Independent Variables. The social responsibility ratings in the KLD Socrates data
base provide the base measures for our independent variables. KLD is an appropriate data
source because 1) it is known to all market participants, and 2) the KLD data exhibits
construct validity for the underlying CSR constructs. Efficient markets theory holds that
investors will use all publicly available data at the time of the event to price the stock.
The date of the focal event was clearly demarcated; however, the actual collection and
release of the KLD rating data for any year is uncertain. Conversations with KLD
managers indicated that the data collection process for each company follows no rigid
schedule, but that the year end data for any year represents all ratings collected during the
year. To control for the possibility that a KLD rating in any year chronologically
followed a focal event, we lagged our CSR measure by one year to create a conservative
and strict test of the efficient markets assumption..
Social responsibility measures. 41 core measures of social responsibility in the
Socrates data base constitute the foundation measures for our variables. These measures
underpin KLD’s evaluations in five separate domains of CSR: Community Relations
(philanthropy)2, Employee Relations, Environmental Stewardship, Product Quality, and
the promotion of Diversity. We began by sorting the foundation measures into those that
capture endogenous choices by a firm’s management, and those capturing non-
2
The community relations dimension captured by KLD becomes our measure of philanthropy. The
Community Strengths measured by KLD that represent endogenous managerial choices all fit the FASB
definition used by Godfrey (2005) in defining philanthropy: “an unconditional transfer of cash or other
assets to an entity or a settlement or cancellation of its liabilities in a voluntary nonreciprocal transfer by
another entity acting other than as an owner (Financial Accounting Standards Board, 1993); emphasis
original)”.
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endogenous reactions by stakeholders to a firm’s choices and actions. An expert panel
verified the classification of items into these categories; rater scores were compared using
Cohen’s Kappa statistic for multiple raters; the test statistic yielded a value of 0.6148 (p <
0.0001). Raters agreed on the initial classification for 28 of the 41 items; differences
between raters were resolved by consensus among the raters. Our variables built on only
those items representing positive managerial choices in each domain of CSR. Appendix
A provides a detailed description of each the KLD foundation variables we used to
construct the CSR variables.
We captured two elements for each social responsibility domain—participation
and high participation, each based on counts of the KLD individual item scores that
reflect endogenous managerial choices in within the area. Participation is a dummy
variable, 0 if no participation (sum of area scores = 0), 1 otherwise; high participation is
also a dummy variable, 1 if sum of area scores > 1, 0 otherwise. Since the underlying
KLD measures are ordinal (1,0 variables based on participation in discrete activities
within a domain) we avoided summing scores within or across domains; we maintained
the ordinal consistency of the data.
The 4 measures of philanthropic (community) involvement consist of two “more
tangible” measures—involvement in community housing or education projects—and two
“less tangible” measures—total corporate giving at the 1.5% of net income level and
innovativeness in the giving program. Our “more tangible” measure is a discrete variable
(1 if a firm scored a 1 in the KLD ratings for either of the more tangible measures, 0
otherwise), as is our “less tangible” variable (1 if a firm scored a 1 in the KLD ratings for
either of the less tangible measures, 0 otherwise).
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Other Variables. We measured the level of relational or intangible assets through
market to book ratio, drawn from the Compustat data tapes. Efficient markets hypothesis
suggests that control variables will be superfluous as investors have already calculated
known controls, such as industry, size, management tenure, etc. into their current
calculations; it is only new information that affects the firm’s valuation during an event.
We included size, market to book, and an industry dummy to capture involvement in
manufacturing or service-based industries as control variables in the regressions,
although each proved insignificant, consistent with the efficient markets hypothesis.
Findings
Table 1: Presents the basic statistics for the variables used in the study. Pearson
product moment correlation matrix
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Insert Table 1 about here
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Table 2: Presents 4 model specifications run using OLS regression techniques.
We do not report the parameter estimates for the control variables (size, market-to-book,
manufacturing/service dummy) because these variables proved insignificant and the
efficient markets hypothesis stipulates these variables will have no explanatory power.
**********************
Insert Table 2 about here
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Figure 1: We include basic Box Plot results to buttress support for our
hypotheses. Panel A presents the box plots for the market to book variable, divided by
participation in philanthropy. Panel B presents box plots for the mean CAR-1 variables
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for each of three subgroups—those not engaged in philanthropy, firms engaged in a
single philanthropic area, and firms engaged in multiple philanthropic areas.
**********************
Insert Figure 1 about here
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Table 3 presents the results of regression models subdividing philanthropic
participation into “more tangible” and “less tangible” manifestations.
**********************
Insert Table 3 about here
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The insurance effect of philanthropy
The parameter estimate for participation in philanthropy reported in Model
1,Table 1, has a positive sign and is statistically significant at p < 0.001. This evidence
warrants rejection of the null hypothesis and provides strong support for H1A; firms
engaged in philanthropy experience smaller declines in share prices in the face of
negative events. We assert that the evidence confirms Godfrey’s core assertion—
philanthropy does appear to have an insurance effect.
Model 2 includes the variables for the other endogenous choices of involvement
in CSR by firms; none of these variables proves significant, and the overall regression
equation loses statistical significance. Model 2 does not provide statistical evidence
strong enough to reject the null hypothesis and H1B is not supported. Models 1 and 2
support a narrow reading of the philanthropy as insurance hypothesis; although
philanthropy, and community relations, appears to act as an “umbrella” insurance policy
21
against general negative events, other types of CSR do not offer shareholders such
protection.
The role of intangible assets
We tested the assertion that firms with high levels of intangible assets would be
more likely to engage in philanthropy than firms with lower levels of such assets. Figure
1, panel A, shows the box plot highlighting the mean values and variance of the
intangible asset variable for each of the two subgroups. While the box plot provides
supporting evidence, a t-test of sample means (assuming equal variances) fails to provide
the statistical evidence needed to reject the null hypothesis. H2 is not supported. The
variance around the means indicates that while the firms with high levels of intangible
assets engage in philanthropy, those with lower levels do as well.
The marginal value of philanthropy
Models 3 and 4 (Table 1) test the two “marginal value” hypotheses. These
models control for the positive effect of participation in philanthropy and test the value of
additional commitments in this arena by firms. The negative sign of the Philanthropy
High Participation variable implies a rejection of H3a and support for H3b; however, the
variable is not statistically significant from zero so we cannot warrant that assertion with
strong evidence. The lack of significance for the parameter estimate allows us to assert
with confidence that involvement in more philanthropic areas does not provide with any
additional protection—philanthropy beyond a certain amount may not exhibit negative
marginal gain, but it clearly indicates no positive marginal gain; when coupled with the
fact that increased involvement in philanthropy expends resources. Similar to overinsuring a tangible asset, the marginal return to the firm of increasing its commitment to
22
philanthropy represents a deadweight loss to shareholders in premiums paid with no
additional indemnification.
We measured the effect size of the three groups to further explore this
phenomenon. The gamma () statistic measures the effect of an entity’s placement in a
treatment, as opposed to a control, group (CITE NEEDED, Cohen, 1988). The Box plots
portrayed in Figure 1, Panel B, show what appears to be an inverted U type of
relationship between insurance value and philanthropy. The difference between being in
the moderate philanthropy (treatment) vs. no involvement (control) groups is moderate
(g= 0.54), while the difference between being in the high philanthropy vs. no
involvement group is small (g = 0.27). The box plot and gamma statistic data again
imply, but do not warrant, support for H3b, that firms involved in many areas of
philanthropy may be creating high expectations that result in perceptions of ingratiation
rather than enhanced perceptions of responsibility or virtue.
The tangibility of giving
H4a and H4b assert that more tangible forms of philanthropic giving will result in
greater levels of shareholder value protection because these types of philanthropy send a
clearer signal of moral coloration and intention than less tangible forms of giving. The
evidence presented in both Models 5 and 6 (Table 3) provides strong support for H4a and
H4b; the more tangible variable is positively signed and statistically significant (p <
0.001). More tangible forms of giving appear to provide a clearer signal of good
intentions than do merely giving, a signal investors (at least) reward with lower
reductions in shareholder value when negative events occur.
23
The evidence presented here provides strong support for the assertion that
philanthropy acts as a form of insurance against negative business events. Philanthropic
activity does not parse based on the level of a company’s intangible assets. Increased
involvement in philanthropy (measured as the number of areas a firm is involved in) does
not create additional insurance protection; in fact, the collective evidence presented here
lends support to the notion that high levels of corporate involvement in philanthropy may
erode the insurance value of philanthropy. More tangible forms of philanthropy enhance
the insurance value of philanthropy by sending clearer signals of a firm’s moral
intentions, commitments, and coloration than merely giving to philanthropic causes.
IMPLICATIONS
Limitations
As with any empirical study, ours has limitations and weaknesses. First, we only
studied one type of negative event, legal or regulatory actions against firms, and we did
not parse these events into more specific categories such as labor or diversity issues,
environmental claims, or product quality problems. Future work should look at different
types of events, labor, product recalls, environmental disasters, etc. Finer grained
analysis may find support for the insurance value of other CSR behaviors; ones that
match more closely specific types of negative events. The result surprises us because, if
the logic of philanthropy follows the logic of the insurance market, then firms should
only buy umbrella policies after purchasing specific coverage for specific business risks.
A test with specific social responsibility events (environmental crises, labor strikes or
24
issues) could determine whether or not more directed efforts in CSR provides specific
coverage.
Second, we used coarse (discrete) measures of involvement in philanthropy and
other CSRs. We feel confident about our assertions in terms of firm involvement in
philanthropic activities, but the nature of our data does not warrant assertions about
various levels of philanthropy. This moderates our findings, particularly our assertions
about the inverted U relationship between philanthropy and insurance protection. Future
research based on fine-grained, continuous measures of philanthropic activity (such as
actual philanthropic dollars, direct vs. foundation-based giving, actual projects supported,
etc.) may shed clearer and, hopefully, more light on this important and intriguing area of
philanthropy and CSR.
Third, our study, while empirically robust, provides a high-level view of
theoretical processes that beg investigation and elaboration at deeper levels through firmspecific and event-specific case studies. For example, does the insurance value of a
firm’s philanthropic activity depend on the transparency of its decision process and the
extent to which company managers make known their philanthropic endeavors? Going
beyond investors and share price, when bad things happen how do affected stakeholders
integrate philanthropic and CSR activities into their calibration of appropriate responses?
Researchers using smaller scale, finer grained investigative techniques (historical case
analysis, ethnographic studies, etc.) can help flesh out the mechanisms and implications
for managers of an insurance view of philanthropy and CSR. In terms of practical
relevance and replicability, case study research should yield greater insights into the
25
architecture (organizational and cognitive) that supports the creation and exploitation of
moral capital.
Implications for Academics
Our study provides initial and strong support for the insurance hypothesis. The
novelty of Godfrey’s (2005) approach lies in its “back door” approach to the relationship
between CSR and CFP. Support for this model argues that those studying corporate
social involvement may be well served to reverse the figure-ground relationships in
thinking about, and modeling, relationships between business (both individual businesses
and business as an institution) and society. One such figure-ground reversal would be to
question the conceptual (and empirical) sharpness of the market vs. non-market
stakeholder approach (Baron, CITE NEEDED). Our study supports the notion that how a
firm treats non-market stakeholders (community needs met through philanthropy) has
tangible economic value for its market-based stakeholders. We invite scholars to
consider what other types of figure-ground relationships should be reversed in our
understanding of business and society relationships.
The literature on Corporate Social Responsiveness argues that firms should
respond to stakeholder needs and concerns. The ingratiation literature argues that
managers must tread lightly in this area because a heavy hand may be seen as evidence of
ingratiation vs. commitment behaviors. Our tentative support for the proposition that
more philanthropic involvement leads to less insurance protection is broadly consistent
with the logic of ingratiation—lots of activity may create false impressions that appear
ingratiating in retrospect. This presents theorists and managers alike with a vexing
question: what defines the inflection point between appropriate responsiveness and
26
inappropriate ingratiation? How do managers and stakeholders manipulate not only
CSR’s but also other substantive and symbolic elements of their relationship to send
signals (make judgments) about their true intentions? Theorists and empirical researchers
need to take up these questions and consider how managers do (and should) make and
make public commitments to philanthropy and other CSRs.
The signal value of more tangible forms of philanthropy is a result not directly
predicted by Godfrey’s (2005) insurance model. This finding, coupled with the tentative
support for the declining marginal value of philanthropy, implies that shareholders and
traders (and perhaps other stakeholders as well) have quite sophisticated ways of
determining how much, and what type of, philanthropy they find valuable as insurance.
If tangibility matters in terms of insurance value, what does this imply about the signaling
values of other CSR’s? Do specific environmental practices create more goodwill than
other, more general commitments? What about labor and diversity? Does a tangible
commitment to minority participation on the board of directors represent a more (or less)
tangible commitment to diversity than a women and minority business
subcontractor/supplier contract? Both theoretical and empirical modeling needs to take
on these finer-grained, yet important, questions in order to advance our understanding of
how philanthropy and other CSRs create insurance value.
Implications for Executives
As (Saiia, Carroll, & Buchholtz, 2003) find, “Strategic Philanthropy” has become
the operating buzzword in many corporations. Our study supports strategic philanthropy
as a general principle; however, our study supports a notion of strategic philanthropy far
broader than that conceived of by most academics and executives. The logic of insurance
27
suggests that executives should consider both value adding (front door) and value
preserving (back door) drivers when defining what is strategically valuable for the
corporation and its shareholders in terms of commitments to CSR. The insurance model
argues that behaviors associated with Citizenship obligations, general community or issue
involvement in domains holding little front door strategic value to the corporation may
create substantial back door value through the generation goodwill that investors and
other stakeholders can draw down when bad things happen. As Godfrey (2005) argues,
the insurance model invites executives to reach out and serve diffuse groups and become
involved in social issue resolution with little direct bearing on the corporation’s strategy.
Philanthropy may act as an “umbrella policy” and protect value during general
negative events, but executives and decision makers should not neglect specific social
responsibilities associated with clear and specific liabilities such as environmental
degradation (remediation) or labor issues. In terms of specific events, investors and other
stakeholders may indemnify (or penalize) the firm first based on its performance in a
specific social domain, then draw down the umbrella policy.
Direct giving toward tangible causes such as support for discrete and concrete
community projects. Firms involved in housing and education saw greater insurance
value, managers should consider these areas of community involvement. Less tangible
giving can be made more tangible by providing a transparent decision process and
accounting for activities and donations. That is, executives should provide a clear
rationale for donations to the local symphony or opera, and an accounting of what
benefits accompany that donation and who the beneficiaries were. Transparency and
28
accountability strengthen the clarity of the signal regarding a firm’s moral intentions and
coloration.
CONCLUSION
Godfrey’s (2005) insurance model presents a new way to think about the business
value of Corporate Philanthropy. This paper provides strong support that philanthropy
provides an indemnity that protects shareholder wealth when negative events occur. This
study stands as one of many on the general subject of the relationship between CSR and
CFP, and as such it becomes one brick in a long wall of research on this topic. Our
findings present theorists, empirical researchers, and executives with intriguing insights
for rethinking the overall value of philanthropy.
29
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31
Appendix A: KLD Variables included in Study
Community (Philanthropy)
Generous Giving (COM-str-A). The company has consistently given over
1.5% of trailing three-year net earnings before taxes (NEBT) to charity, or
has otherwise been notably generous in its giving.
Innovative Giving (COM-str-B). The company has a notably innovative
giving program which supports nonprofit organizations particularly those
promoting self-sufficiency among the economically disadvantaged.
Companies that permit nontraditional federated charitable giving drives in the
workplace are often noted in this section as well.
Support for Housing (COM-str-C). The company is a prominent participant
in public/private partnerships that support housing initiatives for the
economically disadvantaged, e.g., the National Equity Fund or the Enterprise
Foundation.
Support for Education (COM-str-D). The company has either been notably
innovative in its support for primary or secondary school education,
particularly for those programs that benefit the economically disadvantaged,
or the company has prominently supported job-training programs for youth.
KLD began assigning this strength in 1994.
Other Strength (Com-str-X). The company has an exceptionally strong
volunteer program, in-kind giving program, or other particularly strong
community program.
Diversity
CEO (DIV-str-A). The company's chief executive officer is a woman or a
member of a minority group.
Promotion (DIV-str-B). The company has made notable progress in the
promotion of women and minorities, particularly to line positions with profitand-loss responsibilities in the corporation.
Board of Directors (DIV-str-C). Women, minorities, and/or the disabled
hold four seats or more (with no double counting) on the board of directors,
or one-third or more of the board seats if the board numbers less than 12.
Family Benefits (DIV-str-D). The company has outstanding employee
benefits or other programs addressing work/family concerns, e.g., childcare,
elder care, or flextime.
32
Women/Minority Contracting (DIV-str-E). The company does at least 5%
of its subcontracting, or otherwise has a demonstrably strong record on
purchasing or contracting, with women- and/or minority-owned businesses.
Employment of the Disabled (DIV-str-F). The company has implemented
innovative hiring programs, other innovative human resource programs for
the disabled, or otherwise has a superior reputation as an employer of the
disabled.
Progressive Gay/Lesbian Policies (DIV-str-G). The company has
implemented notably progressive policies toward its gay and lesbian
employees. In particular, it provides benefits to the domestic partners of its
employees. KLD began assigning strengths for this issue in 1995.
Other Strength (DIV-str-X). The company has made noteworthy diversity
achievements that do not fall under other KLD categories.
Employee Relations
No-Layoff Policy (EMP-str-B). The company has maintained a consistent
no-layoff policy. KLD has not assigned strengths for this issue since 1994.
Cash Profit Sharing (EMP-str-C). The company has a cash profit-sharing
program through which it has recently made distributions to a majority of its
workforce.
Employee Involvement (EMP-str-D). The company strongly encourages
worker involvement and/or ownership through stock options available to a
majority of its employees, gain sharing, stock ownership, sharing of financial
information, or participation in management decision-making.
Strong Retirement Benefits (EMP-str-F). The company has a notably strong
retirement benefits program.
Other Strength (EMP-str-X). The company has a good employee safety
record or demonstrates other noteworthy commitments to its employees’ well
being.
Environmental Stewardship
Beneficial Products and Services (ENV-str-A). The company derives
substantial revenues from innovative remediation products, environmental
services, or products that promote the efficient use of energy, or it has
developed innovative products with environmental benefits. (The term
“environmental service” does not include services with questionable
environmental effects, such as landfills, incinerators, waste-to-energy plants,
and deep injection wells.) Through 1994, “substantial revenues” was
specified as more than 4% of total revenues.
33
Pollution Prevention (ENV-str-B). The company has notably strong
pollution prevention programs including emissions reductions and toxic-use
reduction programs.
Recycling ((ENV-str-C). The company either is a substantial user of recycled
materials as raw materials in its manufacturing processes, or a major factor in
the recycling industry.
Alternative Fuels (ENV-str-D). The company derives substantial revenues
from alternative fuels. The term “alternative fuels” includes natural gas, wind
power, and solar energy. The company has demonstrated an exceptional
commitment to energy efficiency programs or the promotion of energy
efficiency.
Communications (ENV-str-E). The company is a signatory to the CERES
Principles, publishes a notably substantive environmental report, or has
notably effective internal communications systems in place for environmental
best practices. KLD began assigning strengths for this issue in 1996.
Property, Plant, and Equipment (ENV-str-F). The company maintains its
property, plant, and equipment with above average environmental
performance for its industry. KLD has not assigned strengths for this issue
since 1995.
Product Quality
Quality (PRO-str-A). The company has a long-term, well-developed,
company-wide quality program, or it has a quality program recognized as
exceptional in U.S. industry.
R&D/Innovation (PRO-str-B). The company is a leader in its industry for
research and development (R&D), particularly by bringing notably innovative
products to market.
Benefits to Economically Disadvantaged (PRO-str-C). The company has as part of
its basic mission the provision of products or services for the economically
disadvantaged.
34
Table 1a: Basic Statistics
1. MeanCAR-2
2. MeanCAR-1
3. Phil
4. Empl
5. Envr
6. Divs
7. Prod
8. Phil High
9. Empl High
10. Envr High
11. Divs High
12. Prod High
13. Phil Less Tang
14. Phil More Tang
15. Size
16. M2B
17. Service
N
151
151
151
151
151
151
151
151
151
151
151
151
151
151
150
151
147
Min
Max
μ
SD
-24
21.4 -1.02
5.26
-14
18.5 -0.74
4.11
0.0
1.0 0.42
0.49
0.0
1.0 0.34
0.48
0.0
1.0 0.36
0.48
0.0
1.0 0.46
0.50
0.0
1.0 0.22
0.41
0.0
1.0 0.14
0.35
0.0
1.0 0.08
0.27
0.0
1.0 0.11
0.32
0.0
1.0 0.21
0.41
0.0
1.0 0.01
0.08
0.0
1.0 0.27
0.45
0.0
1.0 0.25
0.44
660 180557 17001 27046
0.5
84.9 5.97
9.90
0.0
1.0 0.27
0.44
Table 1b: Kendall Tau correlation matrix
1. MeanCAR-2
2. MeanCAR-1
3. Phil
4. Empl
5. Envr
6. Divs
7. Prod
8. Phil High
9. Empl High
10. Envr High
11. Divs High
12. Prod High
13. Phil Less Tang
14. Phil More Tang
15. Size
16. M2B
17. Service
1
1
0.55***
0.13**
-0.0
0.07
0.02
-0.0
0.03
-0.0
0.05
-0.0
0.06
0.01
0.19***
0.04
0.00
0.08
2
3
0.55*** 0.13**
1
0.17***
0.17*** 1
0.01 0.17**
0.09 0.15*
0.10 0.38***
-0.0
0.04
0.00 0.47***
-0.0
-0.0
0.08 0.12
-0.0
0.25***
0.08 0.09
0.04 0.69***
0.21*** 0.65***
0.01 0.23***
0.06 0.08
-0.0
-0.0
4
5
-0.0
0.07
0.01 0.09
0.17** 0.15*
1
0.36***
0.36*** 1
0.17** 0.11
0.32*** 0.17**
0.07 0.09
0.40*** 0.24***
0.27*** 0.47***
0.16** 0.12
0.11 0.10
0.12 0.13*
0.18** 0.10
0.12* 0.22***
0.09 -0.0
-0.2*** -0.2***
6
7
8
9
0.02
-0.0
0.03
-0.0
0.10
-0.0
0.00
-0.0
0.38*** 0.04
0.47*** -0.0
0.17** 0.32*** 0.07
0.40***
0.11
0.17** 0.09
0.24***
1
0.22*** 0.32*** 0.07
0.22*** 1
0.06
0.31***
0.32*** 0.06
1
-0.0
0.07
0.31*** -0.0
1
-0.0
0.11
0.03
0.20**
0.56*** 0.23*** 0.35*** 0.20**
0.08
0.15* -0.0
-0.0
0.33*** 0.00
0.40*** -0.0
0.32*** 0.06
0.60*** -0.0
0.28*** 0.18*** 0.21*** 0.09
0.31*** 0.14** 0.01
0.12*
-0.0
-0.0
-0.0
-0.1
*** significance <= 0.001
** significance <= 0.05
* significance <= 0.1
10
0.05
0.08
0.12
0.27***
0.47***
-0.0
0.11
0.03
0.20**
1
0.02
-0.0
0.06
0.17**
0.06
0.01
-0.2**
11
-0.0
-0.0
0.25***
0.16**
0.12
0.56***
0.23***
0.35***
0.20**
0.02
1
-0.0
0.41***
0.22***
0.20***
0.10
0.02
12
0.06
0.08
0.09
0.11
0.10
0.08
0.15*
-0.0
-0.0
-0.0
-0.0
1
-0.0
0.14*
0.04
0.04
.
13
0.01
0.04
0.69***
0.12
0.13*
0.33***
0.00
0.40***
-0.0
0.06
0.41***
-0.0
1
0.16**
0.16**
0.07
0.01
14
0.19***
0.21***
0.65***
0.18**
0.10
0.32***
0.06
0.60***
-0.0
0.17**
0.22***
0.14*
0.16**
1
0.22***
-0.0
-0.1
15
0.04
0.01
0.23***
0.12*
0.22***
0.28***
0.18***
0.21***
0.09
0.06
0.20***
0.04
0.16**
0.22***
1
0.06
0.09
16
0.00
0.06
0.08
0.09
-0.0
0.31***
0.14**
0.01
0.12*
0.01
0.10
0.04
0.07
-0.0
0.06
1
-0.0
17
0.08
-0.0
-0.0
-0.2***
-0.2***
-0.0
-0.0
-0.0
-0.1
-0.2**
0.02
.
0.01
-0.1
0.09
-0.0
1
36
Table 2: OLS Regression Results: The insurance value of philanthropy
meanCAR-1
(Constant)
PHIL
DIVS
EMPL
ENVR
PROD
PHIL HIGH
DIVS HIGH
EMPL HIGH
ENVR HIGH
PROD HIGH
n
F / Sig.
R^2 / Adj R^2
Beta
Sig
-1.49 0.001
1.86 0.006
Beta
-1.74
1.48
0.89
-0.15
0.46
-0.30
Sig
0.003
0.048
0.228
0.849
0.549
0.740
Beta
Sig
-1.49 0.001
2.23 0.004
-1.17 0.295
151
7.783 0.006
0.050 0.043
151
1.455 0.188
0.066 0.021
151
4.447 0.013
0.057 0.044
Beta
-1.74
1.73
1.88
0.10
0.08
-0.15
-1.24
-1.57
-0.51
0.68
2.13
151
1.351
0.122
Sig
0.003
0.037
0.032
0.906
0.924
0.870
0.292
0.128
0.719
0.586
0.622
0.186
0.032
37
Table 3: The effect of more tangible forms of philanthropy
Model
meanCAR-1
Beta
(Constant)
-1.39
PHIL MORE TANG
2.71
PHIL LESS TANG
-0.11
n
151
F / Sig.
6.539
R^2 / Adj R^2
0.081
1
Sig
0.001
0.000
0.887
0.002
0.069
Model
Beta
-1.42
2.69
151
13.144
0.081
2
Sig
0.000
0.000
0.000
0.075
38
Figure 1: Intangible assets and philanthropy M2B
Mean +/- 2 SE MB
10.0
8.0
6.0
4.0
0
CSE
No Part
Mean 5.14
Levene's Test
F
M2B*
Sig.
2.54
0.11
1
Part
Mean 7.19
t-test for Equality of Means
t
1.25
df
149
Sig.
(2-tail)
0.21
Mean
Diff
2.05
Std.
Error
Diff
1.64
95% CI of Diff
Lower
-1.19
Upper
5.29
* Equal variances assumed
39
Figure 2: Box Plots of Philanthropy Participation levels
4.00
95% CI MeanCAR-1
2.00
0.00
-2.00
-4.00
1.00
2.00
3.00
CSE_grouping
No Part
Mean -1.5
Mod Part
Mean .7
Hi Part
Mean -.5
 (mod vs. no) = .54 (moderate effect)
 (no vs. hi) = .27 (small effect)
40
41