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MATCHING DONORS AND NONPROFITS
THE IMPORTANCE OF SIGNALING IN FUNDING AWARDS
Gina Yannitell Reinhardt
ABSTRACT
The topic of nonprofit reform has sparked a debate on the battle between effi-
ciency and effectiveness. Why do ineffective nonprofits survive? Prospective
donors favor applicants likely to fulfill donor priorities. Donors with limited
time and energy look for signals that reveal recipients true capabilities.
Knowing this, recipients attempt to send the right signals to prospective
donors. If the process of sending and reading signals is efficient, funding deci-
sions will tend toward an optimal outcome in which only effective agencies
survive. What signals do donors consider the most helpful? Are organizations
that send such signals receiving the highest payoffs? What is the financial yield
of each signal to recipients? This article uses a signaling game to sharpen our
understanding of nonprofit fundraising and derive the conditions under which
signals will be credible. Interview and survey evidence gathered in Brazil indi-
cate that signals of accessibility, reliability, and credibility attract the highest
payoffs.
KEY WORDS . foreign aid . fundraising . information asymmetry . nonprofit
.
signaling game
Introduction
Nonprofit organizations efficiency and effectiveness have gained increased
attention over the past decade. Characterized by Anheier and Salamon (1998) as
private, voluntary, self-governing entities that do not profit owners, share-
holders, or directors, nonprofit studies programs are cropping up in schools of
business and public administration around the world. Journals focusing on
Special thanks to Andrew Sobel, Gary Miller, Randall Calvert, the Center for New Institutional
Social Sciences, and the American Association of University Women, for providing intellectual and
institutional support for this research. Thank you to the organizations and respondents that took part
in this study, to the editorial staff and reviewers of the Journal of Theoretical Politics for helpful
comments and suggestions, and to Will Reinhardt.
Journal of Theoretical Politics 21(3): 283309 The Author(s), 2009.DOI: 10.1177/0951629809103965 Reprints and permissions:http://jtp.sagepub.com http://www.sagepub.co.uk/journalsPermissions.nav
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policy and management are devoting special space to studies of nonprofits (see
Journal of Policy Analysis and Management, 1998), and websites directing
would-be donors to nonprofit organizations are proliferating online (e.g. guide-
star.org, giveforchange.com, helping.org). Some of this attention is due to the
surge in participation in the sector, both in volunteers and employees, as well asthe rise in public contracts extended to nonprofit organizations (see Light,
2000). Elsewhere, attention has been driven by the concern over the abuse of
nonprofit funds, a fear released by scandals such as those generated by the resig-
nation of United Way President, William Aramony, in 1992 (see Keating and
Frumkin, 2003). These trends together have fueled the topic of nonprofit reform
the research, debate, media attention, and investigation into how to increase
nonprofit efficiency and effectiveness.
Nonprofit managers are often pulled by these two countervailing forces; as
they strive to be more efficient in operating and maintaining donor relation-
ships, they can lose effectiveness in serving their target populations. This pull
is noted by Paul C. Light (2000: 87) in his report on the tides of nonprofitmanagement reform, as he cites some concern that scarce resources are being
used more to jump through the hoops than actually serve clients. Nonprofits
thus seek the least costly methods of securing donors, so that as many
resources as possible are left to fulfill mission goals and serve clients; they
must strategically position themselves to appeal to donors (a tendency most
notably referenced in Frumkin and Kim, 2001). Conversely, donors try to
save time and effort in evaluating potential recipients, looking for clues or
indicators, hereafter termed signals, which reveal recipients true capabilities.
If the process of sending and reading signals is efficient, funding decisions
will tend toward an optimal outcome in which efficient waste is economized.
Nonprofit organizations that are experienced fundraisers may have learnedhow to send accurate signals efficiently regardless of their effectiveness, but
the less experienced may confront problems with both the cost and accuracyof their signals.
How do ineffective agencies survive? Why do they continue to get dona-
tions? I argue that the survival of ineffective agencies is perpetuated by the
nature of the fundraising interaction between donors and recipients. It is not
enough to blame a decrease in effectiveness on the quest for efficiency. Rather,
we must look more carefully at the recipientdonor interaction, which I do by
characterizing the problem as one of asymmetric information and modeling it as
a signaling game. I find that in order for a signal to be a credible indicator of
nonprofit effectiveness, the cost of sending the signal must be differential basedon whether or not the recipient is effective. The smaller the grant award, the
more likely it will be that only effective organizations will find that the benefit
outweighs the cost. Smaller grants will therefore be more likely to differentiate
those for whom the signaling cost is low from those for whom it is high. If send-
ing the signal isnt worthwhile to effective recipients, or it is so cheap that either
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type of recipient can send it, nonprofits will pool together and be indistinguish-
able to prospective donors.
Formalizing the donorrecipient interaction clarifies why ineffective agen-
cies persist, and elucidates how donors can manipulate grant sizes to ensure
the continual funding of a small group of organizations, to the detriment oforganizations attempting to break in to the funding network. I use these theore-
tical findings as a springboard for an empirical investigation, in which I pre-
sent interview and survey data collected from donors and recipients in Brazil
that point to a real-world designation of recipient attributes. Respondents indi-
cate that unalterable attributes, such as age or religious affiliation, help donors
narrow their searches. Donors then turn to alterable attributes, such as profes-
sionalism and accountability, as signals to help determine who will receive
funding. Multivariate analysis highlights which signals yield the most money,
with postestimation of how much money each signal generates. Legally regis-
tered organizations with high degrees of donor accessibility attract more
money than nonregistered, inaccessible entities. Organizations with strongreputations, and those that undergo third-party audits attract more than double
the funds of their competitors.
As I find that donor perceptions of professionalism and accountability condi-
tion funding decisions and nonprofit behavior, it becomes imperative to explore
the implications of the signaling process for nonprofit effectiveness. Unless the
signals exhibited are differentially costly and correlated with effectiveness, the
signaling process bears out a signal-reading system that is efficient according to
the constraints of the fundraising system, but possibly suboptimal in terms of
overall agency effectiveness at serving core missions. While I do not seek to test
the correlations between signals and effectiveness empirically in this piece, by
identifying and confirming the existence of signaling strategies in the nonprofitworld, this article provides an important first step to understanding how the
fundraising process can perpetuate ineffective agencies. Scholars of nonprofitmanagement and accountability can additionally benefit from the insights into
funding cycles, donor motives, and recipient strategies that formalization pro-
vides. Practically, managers of donors and nonprofit recipient organizations will
find useful information in the results regarding which signals donors target and
how much money each signal yields. Finally, this piece represents the applica-
tion of a canonical signaling model to a new situation of nonprofit funding, with
original data that expands both bodies of literature.
The Search for Credible Signals
Due to the growing competition among nonprofit and for-profit organizations,
sharpening our understanding of the nonprofit fundraising process is important
(Young and Salamon, 2003). Much of the literature on funding nonprofits
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(McIlnay, 1998; Navarro, 1988), and on the allocation of development assis-
tance (Alesina and Dollar, 2000; Alesina and Weder, 2002), focuses on donor
motivations and preferences as determinants of funding allocation. Frumkin and
Kim (2001) are an exception, viewing nonprofits as strategic in positioning
themselves to attract money. In striving to convey certain images to prospectivedonors, the organizations that compete for national and international funds are
active players in the funding arena.
Donors and recipients operate in a situation of information asymmetry.
Donors seek their ideal recipient, but only recipients know whether or not they
truly fit a donors ideal. Recipients seek to show donors, before funding occurs,
that they are of the donors ideal type, whether they are or not. Donors thus
search for credible signals as to recipients true types.
Consider the various attributes a nonprofit organization might have. Spence
(1973) divides attributes into two categories: indices and signals. Indices are
unalterable attributes. For a nonprofit, an index might be the organizations age
or the terms under which it was founded. Signals are alterable attributes theycan be manipulated by the organization. Previous literature indicates that attri-
butes nonprofits can alter might be their levels of professionalism (see Abram-
son and McCarthy, 2003) or accountability (Tuckman, 1998; Keating and
Frumkin, 2003).
It is the combination of alterable and unalterable attributes, or signals and
indices, which presents an observable picture of a nonprofit to donors. What the
donor hopes to glean from this picture is a credible indicator of the organiza-
tions true type, and whether or not that type fits the donors ideal. As indices
are unalterable, it is through the manipulation of its alterable attributes that a
nonprofit can signal its type to donors. The task then falls upon the donor to
determine which signals are credible indicators of a recipients true type, andwhich merely signify time spent on trying to achieve the look of a donors ideal.
How can one recipient be convincing?Consider the game (Figure 1) between donor (D) and recipient (R). First,
nature (N) designates the type of a potential recipient. With probability p, R is
the donors ideal (Type I). With probability (1 p), R is not ideal (Type II). The
recipient knows its true type; the donor does not. Both know the value of p.1
Assume 0 < p < 1.
The recipient moves first, deciding whether to invest in sending a signal to
the donor (S) that it is ideal, or not (S). Based on Rs action the donor can
update its beliefs about Rs type and either Fund (F) the recipient, or not ( F).
The donor distributes funding where appropriate, the game ends, and payoffsare awarded.
1. Initially, the game must be analyzed as though the two agencies have no prior funding
relationships.
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Payoffs
For each outcome in Figure 1, the payoff to the recipient is listed first, followed
by the payoff to the donor. Note that for the recipient, the payoff is determined
by the level of funding it receives, discounted by any signaling cost incurred. Iffunded, signalers receive a higher level of funding (FH) than nonsignalers (FL).
Further, Type I (effective) recipients incur a different signaling cost (cL) from
Type II (ineffective) recipients (cH). These type-differential signaling costs are
crucial to achieving separation through a credible signal.
Donor payoffs are based on recipient type. Funding an effective recipient
(H) is better than funding no one (0), but funding no one is better than fund-
ing an ineffective recipient (L). Changing the relationships among the value of
p and the payoffs for each player will determine the conditions under which var-
ious equilibria are derived.
Equilibria for the Game
Three perfect Bayesian equilibria for this game are described here:
Equilibrium 1. Organization types are distinguishable by recipients actions. The
equilibrium strategy profile is (SESE, FSFS)2 provided cH FH FL.
The Donors beliefs are 1= 0, 2= 1.
Equilibrium 2. Organization types are not distinguishable by recipients actions.
The equilibrium strategy profile is (SESE, FSFS).
The Donors beliefs are 1=p,p0 LHL ,2
0LHL.
Equilibrium 3. Organization types are not distinguishable by recipients actions.
The equilibrium strategy profile is (SESE, FSFS).
The donors beliefs are 1=p,p0LHL
, 20 LHL
.
As the game parallels the canonical signaling game, derivation of the equi-libria is omitted.3
In the first equilibrium, a credible signal achieves separation. Ideal recipients
always send the signal; non-ideal recipients never do. The donor believes the
2. Read: Recipient Sends signal if Ideal (Type I), does Not Send signal if Not Ideal (Type II).
Donor funds all senders, and does not fund non-senders.
3. Proofs available upon request. A fourth equilibrium exists where organizational types are not
distinguishable by recipients actions, and pffi. The equilibrium strategy for the recipient is
(SESE), while the Bayesian donor randomizes around its prior beliefs (1=2) and funds or
not funds by a toss of the coin.
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signal, funds all senders, and never funds non-senders. To reach this state, the
signaling cost to a Type II recipient must be higher than the highest benefit it
can attain; the non-ideal recipient will never try to send it. Ideal recipients will
send it if their cost of signaling is less than the highest benefit attainable.
If cH= cL or FH > cH, the signal is worthless, and no organization will choose
to send it; all recipients will pool by not sending a signal. Donors will retain
their prior beliefs regarding each recipients probability of being an ideal orga-nization, and will fund depending on the relationship between h and as
opposed to and L. As (h ) approaches equality with ( L), the
minimum p necessary for the donor to fund approaches 1/2. As (h )exceeds ( L), p decreases. As (h ) grows smaller than ( L),
p increases. Donors that place high priority on achieving a match with
(1-p)4
F
F
FH-cL,H
-cL,
FL,H
0,
-cH,
FL,L
0,
A
D
D
D
N
Type I:Effective
Signal
S
~S
Fund
~Fund
F
DDontSignal ~F
~F
~F
(p)
Type II:Ineffective
FH-cH,L
A
1
Let FH be the funding level to an applicant that signals.
Let FL be the funding level to an applicant that does not signal.
Let cL be the signaling cost to a Type I applicant.
Let cH be the signaling cost to a Type II applicant.
Let H be the donor payoff to funding a Type I applicant.
Let be the donor payoff when it grants no funding.
Let L be the donor payoff to funding a Type II applicant.
Assume FH > FL >0 and H > 0 >L.
2
3
Figure 1. Game between donor and recipient
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recipients (only funding Type I recipients, and never funding Type II recipients),
but do not discern between mismatching and funding no one, will fund based on
lower levels ofp (Equilibrium 2). Donors that feel that funding no one is nearly
as important as matching, but that mismatching is particularly bad, require a
higher p for funding to occur (Equilibrium 3).
Discussion
The outcomes of this model speak to the survival of ineffective organizations by
outlining the possible outcomes that may arise in the nonprofit world. Ideally,
signals credibly separate effective nonprofits from ineffective nonprofits, and
only effective nonprofits survive. The model reveals that the more expensive
and difficult it is to send signals, the more likely we are to see ideal nonprofits
differentiating from non-ideal nonprofits in the real world. Similarly, the smaller
the grant award relative to the signaling cost for nonideal nonprofits, the more
likely it will be that only Type I organizations will find that the benefit out-weighs the cost. Smaller grants will be more likely to differentiate those for
whom the signaling cost is low from those for whom it is high.
It is possible, however, that type-differential signals may credibly signal the
donors ideal, but that the donors ideal is notnonprofit effectiveness. If, instead,
the donor prioritizes characteristics such as public relations, brand naming, or
the favor of another donor, a credible signal of one of those attributes can lead
to separation based on factors beyond effectiveness. An ineffective organization
that credibly signals a good brand name will survive. The funding process, while
suboptimal according to effectiveness, will efficiently allocate resources accord-
ing to the donors ideal and the recipients signal.
Additionally, if a signal is more costly than it needs to be, those organizationsthat can afford to send it may still be incurring too much cost to do so. Both par-
ties have an interest in keeping the signal as cheap as possible, without collap-sing the separation. Any signal that costs more than separation requires is using
too many of the effective organizations extra resources, thus reducing its own
effectiveness. Even Type I organizations will have their effectiveness threatened
by having to jump through hoops to please donors.
And if the signal is too costly for anyone to send, all organizations will sim-
ply avoid sending it. Effective organizations will not be able to separate, which
will lead to regulations that require transparency and other accountability mea-
sures. Rather than insuring separation, these measures will sap further resources
from the effective organizations, while continuing to allow ineffective organiza-tions to exist, resulting in the suboptimal allocation of all funding.
As the model establishes the theoretical possibility that the fundraising pro-
cess allows ineffective agencies to perpetuate, it becomes important to investi-
gate the fundraising system empirically. The full signaling process cannot be
tested directly for, as observers, we are in the same boat as the donors: we
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cannot know at the onset which organizations are ideal, nor can we know their
true costs of signaling. What can be investigated is how donors conceptualize
alterable and unalterable attributes, and which signals are correlated with higher
levels of funding. Based on the previously discussed theoretical propositions,
then, I generate the following empirical propositions:
PROPOSITION 1: Donors recognize a distinction between recipient signals and
indices, and use information transmitted through signals and indices to make
funding decisions.
PROPOSITION 2: Recipients incur a cost when sending signals, a cost that makes
signaling too expensive for some recipients to bear.
PROPOSITION 3: Recipients that send signals receive a benefit that outweighs their
cost of signaling.
Empirically investigating these propositions is the focus of the next sections.
Qualitative Evidence of Signaling
Stone et al. (2001) discuss which nonprofit attributes attract different types of
donors. Authors contributing to Anheier and Salamon (1998) investigate these
attributes in arenas outside the US. Allowing insights from the signaling model
to drive the data analysis, I set out to investigate which signals and indices, or
alterable and unalterable attributes, donors and recipients believe correlate with
funding in the international arena.Previous scholarship suggests that some donors gear their funds toward
nations or regions of priority (Alesina and Dollar, 2000), making a cross-
national study inappropriate for this analysis. To control for cross-national
trends, which are often based on aggregate indicators and political or economic
behavior at the national level, this investigation will be limited to one develop-
ment arena. This restriction insures that preferences are common among donors,
and that the legal constraints on organizations and donors are constant. Focusingon one nation also allows investigation at the organizational and individual
level, opening an opportunity to untangle the decision-making process of orga-
nizational agents.
Brazil is an ideal choice to investigate the donornonprofit signaling interac-tion because it houses active domestic and international nonprofits that regularly
compete for funds. The economic and social needs of Brazil are not met by the
private market, and low levels of public spending have left the efforts of eco-
nomic and social development to nonprofit organizations (Anheier and Salamon,1998). The per capita amount of bilateral and multilateral funds flowing to
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Brazil is so small that nonprofits must turn to private donors (Landim, 1998),
making Brazil ideal for analyzing various types of donors (corporate/private,
nonprofit, governmental) in one study. As Brazils state and civil society are
increasingly working together to confront social and economic goals, it is a con-
structive environment for the study of nonprofit fundraising.Brazil is a generalizable test case because organizations operating there do
not stand out as recipients of particularly high or low levels of assistance (Inter-
national Development Statistics Online Database on Aid and Other Resource
Flows, 2003). Brazil fits in the 52nd percentile of developing countries, when
ranked in terms of per capita dollars flowing to nonprofits and NGOs. A few
unique attributes of Brazilian nonprofit activity will slightly constrain measure-
ment, but should not severely threaten the generalizability of the model.
Brazilian nonprofit activity has historically been structured by the ruling
regime (Bosch, 1997; Pearce, 1997). In 1993, in response to corruption scandals
unleashed by President Fernando Collor, Brazil created the National Social Wel-
fare Council (CNAS) to oversee social welfare policies (Landim, 1998). Underthe registration rules of CNAS, nonprofits must submit by-laws, founding min-
utes, and directors names. Philanthropies are a special class of organizations,
nonprofit public interest entities that provide services without discrimination,
maintain unremunerated directors, and receive breaks in water, electricity, and
trash expenses.4 Many nonprofits and philanthropies operate without registration
due to a costly and lengthy application process, and because registered non-
profits and philanthropies cannot own property (interviews with the author,
2003). Thus, nonprofits in this study will not be defined legally, but along the
lines of Anheier and Salamons (1998) categorization of a private, voluntary, self-
governing entity that does not profit owners, shareholders, or directors.
Reports of Signaling
As the model tells us there should be a distinction between alterable and unalter-
able attributes, the investigation begins with qualitative evidence of which signals
and indices donors and recipients report are factored into funding decisions. I con-
ducted 88 open-format interviews with executive and financial directors from
donor and recipient organizations that operate in Brazil (methods in Table A1). A
purposive sample was chosen to reach a broad range of donors and recipients. Of
167 organizations contacted, 61 granted at least one interview (36.5%).
Donors in the sample represented three types of agency: governmental orga-nizations (such as Interamerican Development Bank (IDB), United States
4. Donations to an unregistered nonprofit are not tax deductible. Individuals receive deductions on
up to 10 per cent of income; firms have a 5 per cent limit (Articles 79 and 246 of Brazils Federal
Income Tax Regulations, quoted in Landim, 1998).
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Agency for International Development (USAID), World Bank, European Union
(EU)); private or corporate foundations (Volkswagen, Bosch, Hewlett-Packard
Institute); and intermediary nonprofits (those that both receive and distribute
funds, such as World Wildlife Fund, Fundacao Orsa, Fundacao Abrinq). I asked
the Executive/Regional Director or Director of Projects what criteria determinewho receives money. Many governmental donors publicly solicit project propo-
sals. Other donors privately solicit applicants to enter closed competitions. Pri-
vate and corporate foundations often choose recipients without waiting for them
to approach, or accept unsolicited proposals.
Recipient respondents receive money from various combinations of govern-
mental sources (such as USAID, IDB, UNICEF, World Bank, Brazilian federal,
state, and city ministries), private/corporate foundations (Kellogg, Ford,
MacArthur, Bill and Melinda Gates, Hewlett-Packard Institute, Natura, Boti-
cario), individuals, and intermediary nonprofits (DKT International, Private
Agencies Collaborating Together, International Youth Foundation). The sample
includes organizations that have not competed successfully for internationalfunds. I asked the organizations Executive or Financial Director about fundrais-
ing strategies and operations. Some recipients have departments and staffs
devoted entirely to fundraising, while others maintain staffs that intersperse
fundraising with other duties. Respondents engage in events, direct mailing,
grant-writing, collecting dues, and providing fees-for-service.
Donors confirm that they do look to a nonprofits organizational attributes for
signals of its true type before disbursing grants. Recipients confirm that they
structure and operate their organizations according to the signals they believe
donors seek. Respondent reports of a distinction between alterable and unalter-
able attributes, coupled with insights from the literature, illustrate which attri-
butes are considered credible signals of type.
Indices
Indices indicate to donors the sort of programs an organization will be able to imple-
ment. One index donors reportedly consider is an organizations geographic range of
service. Bebbington and Riddell (1997: 11113) report that some donors choose to
fund nonprofits that are based in the region of choice, because less money is trans-
ferred to contractors along the way. Our foundation works only with communities
where a lot of our employees live, states one corporate foundation donor agent.5
Others prefer to fund intermediate or broader-range nonprofits with connections to
smaller nonprofits in diverse regions. As one recipients finance manager states, Wegot that Ministry of Education grant because our local contacts were clear. Our lower
communication costs helped us get the grant.
5. For confidentiality, no names or organizations will be associated with specific comments.
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A second unalterable attribute, or index, is the sector the organization serves.
Although previous work distinguishes sector or issue area in various ways (Reiner
and Wolpert, 1981; Wolpert and Reiner, 1984b), respondents in this sample point
the focus to the sectors of women, children, and the environment, for various
reasons. Some donors only give to childrens organizations. Womens organiza-tions tend to receive more money from international donors than from national
donors, and respondents from these organizations believe their target population
is overlooked. Authors argue that environmental organizations are staffed with
disproportionately well-educated and middle class employees (Hochstetler,
1997: 192), which might position them to petition for funds more effectively.
The third index is the type of service the potential recipient gives, either
direct or indirect. Some donors fund direct, hands-on efforts such as distributing
food, rather than the indirect pursuits of education or advocacy (more in Wolpert
and Reiner, 1984a). Gordenker and Weiss (1996: 3741) argue that indirect ser-
vice organizations find it the most difficult to raise funds. While 55 per cent of
donors agree that they prefer to fund direct service, some disavow the trend:Every child has a mother, so we try to fund organizations that work for their
rights. These conflicting views result in a relationship between type and fund-
raising that is not clear cut.
Previous literature (Reiner and Wolpert, 1981; Landim, 1998) indicates that
a nonprofits age is an unalterable attribute that can affect its ability to attract
money. Yet several Brazilian organizations were founded in response to the
political scandals and poor development reports of the early 1990s (similar to
trends in the US: Abramson and McCarthy, 2003). Many donors thus believe
that organizations founded in the 19914 scandal response range are less likely
to be corrupted, while still old enough at the time of this study (20034) to be
trusted with large amounts of money. Consequently, donors account for theunalterable attribute of the founding date with respect to this time period, rather
than the age itself, when making funding decisions.Seventy-eight per cent of donors state that whether or not a potential recipi-
ent has a religious affiliation has a profound effect on funding decisions. Pre-
vious work (Wolpert and Reiner, 1984a; Tuckman, 1998; Hodgkinson, 2003)
confirms that religious affiliation can be an important draw or deterrent of fund-
ing from different types of donor groups. Although some donors are not legally
allowed to donate to religious nonprofits, others seek them out in order to reach
certain communities. One clever recipient realizes this distinction:
we are not officially affiliated with any religion, because we have to be able toapply for federal funds. But our sister organization, which draws in millions each
year in support of its religious activities, funds us indirectly, because our work
appeals to them. That way were able to get dollars from both those that support
religious activities and those that dont. We simply cant affiliate with a religion if
we expect our work to continue.
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Indices help donors narrow their searches for the ideal recipient. Note that in
the short term of a donors funding cycle, these attributes are unalterable.6 A
recipient organization, once formed, cannot change its indices without becom-
ing a different organization.7
Signals
A signal is an alterable attribute. Although potentially difficult and time-con-
suming, recipients can change these attributes, and thus the strength of the sig-
nals they send. Interviews indicate that donors focus on two main signals of an
organizations true type: professionalism and accountability. A recipients type
influences not only the strength with which it sends various signals, but also its
ability to change that strength.
The first signal, mentioned by 100 per cent of donors, is the professional-
ism of the recipient. Abramson and McCarthy (2003: 343) define the profes-
sionalization of an organization to be a shift away from amateur orpersonalized responses and towards technical and standardized approaches to
providing services. A professionalization trend among nonprofits is noted in
Frumkin and Andre-Clark (quoted in Light, 2000) as a vehicle for improving
management, and in Gordenker and Weiss (1996) among recipients of devel-
opment assistance.
Donors interviewed believe that agencies with higher degrees of profession-
alism are more effective in their work: People who can handle things profes-
sionally are better at servicing populations and clients, states one donor
agencys managing director. Recipient financial directors confirm that they
strive to appear professional, often at great cost. When pressed for how profes-
sionalism is gauged or assessed, responses converge around three main attri-butes: accessibility, experience, and fundraising specialization.
A high degree of accessibility indicates that potential donors can gatherinformation about the organization without difficulty. An organizations accessi-
bility is the ease with which prospective donors can communicate with its staff,
6. An environmental organization cannot suddenly change itself into an AIDS clinic, just as an
organization that works exclusively in a small rural community cannot shift to the international level
overnight. It is possible that in the long run such shifts could occur (Wolpert and Reiner, 1984a;
Luong and Weinthal, 1999), but these possibilities would involve a tremendous investment of capital
and resources (see Uvin, 1996), could dilute funding, and for parsimony will not be considered here.
7. Laffont and Tiroles (1991) work on regulatory capture suggest an organizations governancestructure as another unalterable attribute. As nonprofits have no shareholder or public accountability,
some become essentially one-man operations with a captured regulatory board of directors. While
donors in the sample acknowledge that this is a plausible dimension to consider on theoretical
grounds, they report that it is too difficult to try to examine every organization closely enough to
determine whether its board is captured. Further, one donor even asserts that sometimes one person
knows whats best for an organization and its target population, so that doesnt concern me.
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and is prioritized by 79 per cent of donors. As one donors program director
states, There are people in my organization that need to see reports in Spanish
or English. If I can see right away that an organization can accommodate that,
they move to the top of my list. To attract international donors, it is often neces-
sary for a recipient to employ staff members that speak or write in more thanone language (Hulme and Edwards, 1997), even though it may have nothing to
do with the organizations core mission. States one recipients financial director,
You think its necessary to speak French to give children lunch? Its necessary
to speak French to keep our main donor from Dijon, so we pay a premium for
someone who does.
Respondents assert that to signal high levels of professionalism, an organiza-
tions employees need diverse professional experience. Donors are drawn to
recipients that operate as the donors do. It becomes important for recipients to
have experience from other economic sectors that they can use to enhance fund-
raising. As one recipient representative says, Its really expensive to hire busi-
nesspeople who . . . know how to speak the business language. And its worth itin the end because of how good they make us look.
The final component of professionalism that donors notice is a nonprofits fund-
raising specialization, whether any staff positions are devoted to attracting and
maintaining donors. Frumkin and Kim (1998, quoted in Light, 2000) note that
fundraising specialization is becoming a high priority in nonprofit hiring practices.
Ninety-one per cent of donors cite fundraising specialization as crucial to their
choice of recipients, as it offers a well-trained contact within a recipient organiza-
tion that will be available to them at all times. Schneider and Ji (1990) argue that
organizations with fewer resources cannot apply for funding because they do not
find it worth their time, based on their chances of success. A recipient agrees, Of
course wed like to hire people to devote exclusively to fundraising. Who couldntuse the extra money they might win? As it is, we cant pay the people we do have,
and they all have thousands of responsibilities.Beyond professionalism, 100 per cent of donors report seeking recipients that
are accountable. A nonprofit is here considered accountable if it can be held
responsible for its actions or inactions (OConnell, 2005; see also Tuckman,
1998; Brody, 2003). Details of how donors assess the concept are summarized
in the discussion of four alterable attributes: transparency, reliability, credibility,
and reputation.
The first component of accountability is transparency, the ability to view and
evaluate information regarding recipient accounting and operations. Previous schol-
ars (Postma, 1994; Tuckman, 1998; Keating and Frumkin, 2003; Roberts, 2004;Koppell, 2005) assert that transparency is a key means to holding organizations
accountable. Seventy-six per cent of donors agree, stating that more transparent
organizations are more accountable, and thus more likely to receive their money.
Many donors mention, however, that transparency is not always enough to
insure accountability. Transparent records must also have a high degree of
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reliability, considered present if financial records have been audited by a third
party, as suggested in Keating and Frumkin (2003; see also Kearns, 1994; Frum-
kin and Kim, 2001). Donors and recipients maintain that the audit process,
although expensive, is vital to reliably proving that an organization is operating
legitimately (see also Herman and Renz, 2004). States one recipients financialdirector, I know weve lost prospective donors because we cant assert that our
finances have been audited, but we just cant pay them, so I cant spend time
thinking about it.
Credibility, referred to by Keating and Frumkin (2003) as the ability to
believe in and trust an organization, is high on donors lists of desirable signals.
As many nonprofits in Brazil are not legally registered, donors (82%) consider
an organization more credible if it is registered as a nonprofit or philanthropy,
which Koppell (2005) argues shows that it can follow the rules. Prospective
donors know that registered organizations conform to standards of organization
and conduct, and use this registration as a signal of capabilities. For recipients,
the cost of this registration is sometimes too much to bear, as an executive direc-tor states: The red tape we have to get through would take years, and I dont
have the time. I have an organization to run.
Lastly, donors gauge an organizations accountability through its reputation,
its overall quality as judged by others. Donors are wary of relying on nonprofit
self-generated reports, which can be biased (see Frumkin and Kim, 2001), so
they often accept the endorsement of other donors (via presence of a grant from
that donor) as evidence of an effective organization. Some donors even forgo
their own searches for effective recipients to fund recipients that already have
prestigious donors. One donor reports seeking out recipients because of its repu-
tation among other donors, and eschewing recipients that approach it without
such endorsement. This practice is not lost on strategic recipients, who believedonors share opinions of recipients with one another.
Discussion
This qualitative analysis confirms the three empirical hypotheses listed earlier.
First, donor agents look to a recipients alterable and unalterable attributes
when determining funding. Second, altering these attributes is costly, too
costly for some organizations to bear. Third, the recipients that do invest in
signaling do so because they believe the cost outweighs the benefit. Addition-
ally, the quotations reflect that altering attributes can divert resources awayfrom a recipients core mission, and does not always directly reflect organiza-
tional capabilities. Hiring people who speak foreign languages, undergoing
third-party audits, and obtaining organizational certification are costs recipi-
ents incur to signal professionalism and accountability. Recipients affirm that
expending resources in these areas can divert funds away from the direct
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provision of services, although it indirectly increases the ability to provide
services by raising funds. Under what conditions will the benefit of signaling
outweigh the cost? The next section investigates this question with a larger-
sample study.
Quantitative Evidence of Signaling Benefits
I conducted a survey of 385 nonprofits in Brazil to discern which signals attract
the most funds, and how much funding they attract. Simple gross income of an
organization in the year 2003 (in US dollars), transformed logarithmically to
ensure a normal distribution, is the dependent variable in a standard OLS model.
I expect that a nonprofits signal scores will be positively correlated with its
intake, despite controlling for indices and other factors.
Data and Measurement
There is no universally known or publicly available record of nonprofits in Bra-
zil, although scholars estimate that over 200,000 exist (Anheier and Salamon,
1998). A sample of 3594 nonprofits was compiled from three clearinghouses
(ABONG, 2004; Ajuda Brasil, 2004; Seja um Voluntario, 20045),8 and invited
to participate via the internet, yielding 385 responses (10.71%).9 All communi-
ques and materials were transmitted in Portuguese.10
Signal and index measures are derived based on the qualitative reports,11 and
designed to conform to an important distinction between signals and costs: sig-
nals may not directly prove type (Spence, 1973). There is a direct link betweenan organizations type and the costit bears in signaling. Non-ideal organizations
incur high costs; ideal organizations incur low costs. Measurements must chara-
cterize signals that are expensive to send and reflect the potential to differ in cost
from one nonprofit to another.
8. Sources similar to sources found on giveforchange.com, guidestar.org, and helping.org.
9. There is a concern that poorer nonprofits will have fewer resources to fill out the survey, or that
richer nonprofits will not want to fill out a survey, resulting in self-selection and bias in the sample.
To guard against this possibility, respondent organizations were given access to a forum of partici-
pant nonprofits, and a link to their organization on the survey website, as an added enticement.Further care was taken to restrict the analysis to variables gathered from questions that yielded
approximately normal frequency distributions. As with any survey, the possibility of selection bias
cannot be completely eliminated.
10. Materials were translated into Portuguese by a native Portuguese speaker, translated back into
English by a native English speaker, then revised and translated back into Portuguese.
11. Table A2 lists definitions and sample statistics.
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An example illustrates the distinction. Consider a plausible measure of
experience the number of employees with degrees in higher education. Such a
measure indicates high levels of experience for a tuberculosis clinic because
highly educated personnel are required to operate it, but confounds proof of type
with a signal of type. Instead, consider the measure for reliability: it is expensiveto hire third parties to perform audits, and to conform to the requirements neces-
sary to undergo such an audit, yet it is unlikely to directly enhance an organiza-
tions ability to perform its core mission. This and the other measures are
designed to be true to the signaling game in that signaling costs differ, but mea-
sures are not direct proof of abilities.
A few added measures merit discussion. Reputation counts the number of
donors from which an organization received funds prior to one year before
filling out the survey. This measurement allows for the time delay between
decision and disbursal, captures the influence prominent donor relationships
can have on future funding, and accounts for repeat donor relationships
without biasing results by including a lagged dependent variable on theright-hand side.12
Several controls were inserted. Fulltime staff size13 is expected to be
positively associated with yearly intake. A few measures capturing an orga-
nizations founding scenario, the level of boost an organization received
from its founding, allows for the organizations founding to influence future
funding, and was included to guard against endogeneity.14 As Brooks
(2000) indicates, the expected effect of a founding scenario on yearly intake
is unclear, as high levels of support at founding can either boost or crowd
out other donations.
Results
Some responses were left blank or filled in with Dont know or Prefer notto respond. Rather than use listwise deletion to eliminate these responses
completely, many scholars have chosen to impute multiple datasets that
simulate missing values for these responses, then to estimate the model on
each dataset and combine the results into one output (Rubin, 1986;
12. As many assert (Shi and Svensson, 2004), an agencys budget in year t is likely to be a func-
tion of its budget in year t 1. Following Achen (2000), a lagged dependent variable is not used here
as it is likely to bias the remaining results downward.
13. Counts of volunteers were inconsistent and unreliable, and thus inappropriate to include.14. There is an infinite regress that results from the logic: If an organization makes more now, it
was more credible a year ago, but it was probably more credible then because it made more before
that. So grant success in year t 1 could increase the likelihood of grant success in year t. Ideally,
this problem would be resolved by using data spanning several years, which the current study cannot
accommodate. Instead, the reputation and founding scenario variables are used as the best available
options to combat endogeneity.
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Brownstone and Valletta, 2001). Following the lead of Escobar-Lemmon
(2003), Scheve and Slaughter (2001), and Boehmke (2002), I used the AME-
LIA (King et al., 2001) program to simulate missing values for multiple
imputations of data.15 Manipulations were run on the imputed datasets with
CLARIFY (King et al., 2000), which estimates the model on each dataset
Table 1 . Determinants of 2003 Intake (White-corrected Standard Errors in Parentheses)
Intake03 Intake03
Indices:
Geographic range: international 2.57 (1.39)* 2.69 (1.40)*Geographic range: national 1.58 (0.83)* 1.68 (0.87)*
Geographic range: state 1.02 (0.75) 1.03 (0.76)
Geographic range: municipal 1.17 (0.63)* 1.10 (0.63)*
Sector: environment 0.51 (0.67) 0.58 (0.67)
Sector: women 0.16 (0.56) 0.19 (0.56)
Sector: children 0.25 (0.72) 0.24 (0.71)
Type (direct/indirect) 0.26 (0.67) 0.22 (0.67)
Scandal range 0.85 (0.70) 0.87 (0.70)
Religious affiliation 1.69 (0.58)*** 1.75 (0.60)***
Signals:
Professionalism
Accessibility (language count) 0.46 (0.24)*
Accessibility (english dummy) 0.62 (0.60)Experience in private sector 0.00 (0.00) 0.00 (0.00)
Fundraising staff 1.77 (0.91)* 1.76 (.91)*
Accountability
Transparency (financial records) 0.09 (0.55) 0.11 (0.57)
Reliability (audit dummy) 0.87 (0.52)* 0.87 (0.52)*
Credibility (registration) 1.23 (0.57)** 1.31 (0.56)**
Reputation (prior donor) 0.79 (0.46)* 0.91 (0.46)*
Controls
Strong founding 1.05 (1.10) 1.03 (1.09)
Mid-level founding 0.10 (0.53) 0.19 (0.51)
Fulltime staff size 0.00 (0.00)* 0.00 (0.00)*
Constant 6.13(1.16)*** 6.25 (1.22)***
Observations 385 385
R2^ 0.19 0.18
^ The values for R2 are averages across all imputed datasets.
*significant at p< .10; ** significant at p< .05; *** significant at p< .01.
15. Listwise deletion is only more appropriate than multiple imputations when the data is assumed
to be Missing Completely At Random (King et al., 2001), a condition this survey data violates.
AMELIA generates educated guesses as to what the missing values would be, based on simulations
of random linear functions created from the information that is not missing. AMELIA imputed five
datasets, using Expectation-Maximization with Important Resampling.
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and applies an algorithm to yield one output.16 All descriptive statistics (see
Table A1) were based on the data before imputations. From here forward
estimates, standard errors, and predicted values reported will be based on the
imputed datasets generated by AMELIA and processed with CLARIFY.
Based on the interviews and tendency for selection, dummies for children,women, and the environment account for sector and are allowed to vary, along
with accessibility, across ten basic iterations.17 Table 1 lists estimations of
yearly intake in the log of 2003 dollars. The first column contains results for the
model including a count of foreign languages spoken, the second for the English
dummy estimation. Eight indices and signals show significance: accessibility,
reliability, credibility, fundraising specialization, reputation, religious affilia-
tion, fulltime staff, and geographic range of service.
Indices show mixed significance. Sector indicators are not significant deter-
minants of yearly intake, either inserted individually or together. This calls into
question recipient respondents beliefs that sectors beyond their own are dispro-
portionately favored in the nonprofit arena. Similarly, lack of significance on thescandal response range indicator suggests that donors do not make funding deci-
sions based on whether an organization arose as a result of the corruption
scandals.
Geographic range of service and religious affiliation indices, on the other
hand, show significance robust to all variations on the model. International,
national, and municipal range organizations all demonstrate significantly greater
intake than neighborhood organizations, although state-level organizations do
not show a significant improvement in intake over those neighborhood organiza-
tions. Religiously affiliated groups organizations take in statistically signifi-
cantly more money than their nonaffiliated counterparts.
Five of the seven signal measures show statistical significance. In thedimensions of professionalism, accessibility is significant and positive when
measured as a total language count, but not as the English dummy. As 53per cent of the organizations that speak only one foreign language list it as
English, it appears that speaking English and Portuguese alone are not
enough to attract funds. Having specialized fundraising staff, however, does
help attract funds, even controlling for fulltime staff size. Further, an inter-
national range is significant despite controlling for English and fundraising
specialization, refuting arguments that the measure simply captures the
16. With regression coefficients, means, and predicted probabilities, CLARIFY estimates the
value within each dataset and averages the values across all datasets to reach the value of output.With standard errors, CLARIFY averages the estimated variances within each dataset and adds to it
the sample variance in the point estimates across the datasets, multiplying the average across datasets
with a factor that corrects for bias (see King et al., 2001).
17. Iterations were run with each sector, no sector, and three sectors. Varying accessibility
doubled the iterations. In unreported regressions, a Spanish dummy replaced the English dummy.
Through all iterations, results were robust in magnitude, standard error, and directional effects.
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ability to hire English speakers or other specialized staff. Private sector
experience does not appear significant, which I believe is more likely a
reflection on the measurement of the concept than the theoretical validity of
the relationship.18 Together, the results on these elements of professionalism
confirm donor and recipient assertions that professionalism matters in fund-
ing allocation.
With respect to accountability, although transparency of records is not sig-
nificant, reliability of records is.19 The finding confirms donor assertions that
viewing financial records is less important than knowing they were audited by
a third party. Donors also prefer formally registered beneficent organizationsand/or public utilities to those that are not.20 The large sample confirms the
interview findings that recipient accountability is an important factor in fund-
ing decisions. Reputation, measured by how many international donors the
recipient had one year prior to the funding cycle, is also significant, demon-
strating the importance of other donors endorsements in one donors decision
calculus.
Table 2 . Effects of Varying Significant Variables while Holding Others
Constant at Their Medians
Variable Change in Value Effect on Yearly Intake
Accessibility (language count) 0 to 1 $9,7101 to 2 $15,412
Reliability (audits) 0 to 1 $16,387
Fundraising specialization 0 to 1 $21,756
Credibility (registration) 0 to 1 $18,378
Reputation 0 to 1 $32,370
(prior international donors)
Religious affiliation 0 to 1 $119,439
Geographic range (international) 0 to 1 $308,474
Geographic range (national) 0 to 1 $108,148
Geographic range (municipal) 0 to 1 $62,620
Fulltime staff size One StDev $10,959
18. While previous scholarship suggests a valid link between private sector experience and intake,
interview respondents suggested that one or two key business minds could make an important dif-ference in signaling. If so, the effort to approximate a continuous variable by counting those recipient
staff members with private sector experience could be confounding the results.
19. Results are robust to exclusion of financial records availability and the inclusion of an interac-
tion term.
20. Keep in mind that tax deductions are not applicable to donors who do not pay taxes in Brazil.
Further, most domestic donors in the sample are governmental and unconcerned with deductions.
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Analysis
How much money does each signal yield? Table 2 illustrates the effect of
changing significant variables values on yearly intake.21 Each variables
effect was measured by estimating the change in expected yearly intake as thevariable moved from one value to another, while other variables were held
constant at their medians. Dichotomous variables moved from 0 to 1, while
accessibility, reputation, and fulltime staff varied in terms of standard devia-
tions from the mean.
Varying signals shows profound effects on yearly intake. In terms of profes-
sionalism, an organization with zero accessibility, signifying that no one speaks
a foreign language, attracts an average of US$16,533 in 2003. Its competitor
that employs someone with proficiency in one foreign language brings in close
to US$10,000 more, enough to pay that person six times the minimum wage and
still increase funds by over US$5,000.22 The organization with a person that
speaks two extra languages makes an additional US$15,400, enough to pay twopeople six times the minimum wage each and still net the organization
US$15,000, double that of its counterpart. An organization with no specialized
fundraising staff averages US$4,487 in 2003, while its competitors with staff
members designated for fundraising makes US$26,243, nearly six times as
much. The increase is enough to pay a professional fundraiser ten times the
minimum wage and still increase funds by over US$13,000.
As for the elements of accessibility, an unreliable organization (no third-
party audits) brings in US$11,777. Its competitors that do undergo audits attract
over US$16,000 more. An organization that is not credible in that it is not certi-
fied or registered with the government averages US$7,865 per year. An organi-
zation that does boast legal registration brings in over US$26,000, over threetimes as much. And an organization with a low reputation among international
donors, having had no international donors in the year prior to the year of the
study, brings in an average of US$26,243, compared to US$58,613 brought in
by its counterpart that had only one international donor the year before. Index
variance illustrates important effects that unalterable attributes can have on
yearly intake as well. Organizations with community/neighborhood ranges are
eclipsed by their municipal-level, national-level, and international-level coun-terparts, which bring in an extra US$63,000, US$108,000, and US$308,000,
respectively. Increasing fulltime staff size by one standard deviation yields an
increase in 2003 intake of close to US$11,000. Religious organizations bring in,
on average, more than five times (US$119,000) as much as their non-religiouscounterparts.
21. Please contact author for original log values and confidence intervals.
22. Minimum wage in Brazil in 2003 was US$71 per month, US$852 per year (BBC, 2003).
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The analysis confirms the qualitative evidence and expands its implications.
Donors give to organizations with higher levels of professionalism and account-
ability, conceptualized through fundraising specialization, credibility, reliability,
reputation, and accessibility. Not only do these signals attract funds; they gener-
ate high returns that can more than offset the cost of the signal itself.
Conclusion
This research has explored the donorrecipient relationship in nonprofit fund-
ing and the effects of signaling on nonprofit resources. Multivariate analysis
shows that donors channel their money to organizations exhibiting higher
levels of reliability, accessibility, credibility, reputation, and fundraising spe-
cialization. Nonprofits emit these signals through obtaining certification,
employing staff members that speak various languages, acquiring the endorse-
ment of international donors, and undergoing third-party audits, and donors
are giving their money to the most skillful signalers. Larger geographic ranges
of service, more fulltime staff, and religious affiliation also increase an organi-
zations yearly intake.
Two key implications of this work are interesting to practitioners and aca-
demics. The first pertains to the potential of signaling to either co-opt or build
capacity. Hulme and Edwards (1997) and Gordenker and Weiss (1996) express
concern that concentrating on pleasing donors could, either through diverting
resources or co-opting agendas, result in a recipient losing the ability to fulfill
its core mission effectively. Strong signals would not indicate organizational
capabilities, but simply signaling capabilities, as this recipients Executive
Director implies:
Our founder was famous, Thank God. The government continues to give us money,
and people think were big and great, because we have our founders name. Were
barely holding ourselves together and our services decline every year but as long
as we keep giving the government a good name, a good place to put their money,
we should survive.
Another states, Look, we do our best, but theres no doubt that other organiza-
tions are better [at this work]. We need more money, and that means we give the
donors what they want.
Yet nonprofits benefit from the grants and relationships signaling acquires.
These relationships lead to the acquisition of resources and the possibleenhancement of capabilities as nonprofits strive to meet the procedural require-
ments associated with maintaining acquired grants. Says one program manager,
The IDB made us, forced us, to clean up. We got the IDB grant because the
World Bank had been watching us, but to keep it, IDB made us professionalize,
make our accounting more transparent, you would not believe. Another
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mentions the computer a donor demanded she acquire, after receiving funding,
to track spending. Acknowledging that it took staff away from service provision,
she is thrilled with her organizations new method for tracking of clients, and
maintains that everyone is better off.
Thinking about various donor ideals in light of the formal model can explainthe differing observed effects. Some donors fund organizations that signal a
good reputation because it helps their own image; others fund organizations that
are registered because of a concern with accountability. Such donors fund dif-
ferent types of organizations, but search for signals in the same manner. Still
others look carefully for recipients for capacity-building funds. These donors
are playing an entirely different game not one of shortcuts and signals, but one
of gathering information to discern which organizations can best utilize capa-
city-building funds, as this donor indicates: We spend years looking for organi-
zations to receive our funds. We focus on a small number and bring them in to
train in how to write project proposals and use grant money. Searching takes
time, but we believe it is crucial to building capacity. An exploration of thisspecial donorrecipient relationship is a provocative area for future research.
The second implication concerns the payoffs of the game, the fact that in
order for the signal to be credible, its cost must be higher than the highest bene-
fit possible for nonideal recipients. Donors have the incentive to make grants
small, so that the only recipients will be those for whom the cost is low. Recipi-
ents accustomed to filing applications for US$1,000 grants will continue to do
so without thinking, while those for whom the cost is high will never apply for
such small amounts. The smaller grant serves as a screening device, giving reci-
pients an in when it is time to apply for larger grants, and donors savvy to this
aspect of the game enforce the status quo by repeatedly funding the same pool
of recipients.As signaling is relevant in a variety of contexts, this empirical model is
applicable across a broad range of countries and institutional settings, particu-larly those with a competitive funding environment. The qualitative work is
specialized with respect to Brazil, but with the possible exception of the accessi-
bility measure, the quantitative variables can be measured similarly elsewhere.
Not all signals will matter to the same degree in every case, yet it will be inter-
esting to see how coefficients differ across arenas.
This study has shown that the higher signalers make the most money. It is in
the formalization of the fundraising interaction that the possible implications of
these findings are elucidated. If the signals found to yield more money are also
correlated with effectiveness, and if those signals are no more costly than theyneed to be in order to maintain separation, these donors and recipients have
reached optimal funding relationships. If, however, any of these signals is not
correlated with effectiveness, or is so costly that the organizations sending them
are wasting resources that could be used to fulfill missions, then ineffectiveness
in organizations is forced to persist.
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Appendix
Table A1. Data Collection Table Interview Methodsa
USb
Brazilc
Time frame AprilMay 2003 JulyAugust 2003
Number of peopled (organizations)
interviewed from recipient agencies
19 (15) 36 (28)
Number of people (organizations)
interviewed from donor agencies
10 (5) 23 (15)
a Interviews were open in format. The respondent was allowed to speak freely, while the interviewer
directed conversation in general terms.b Fourteen of the interviews with US agencies were conducted over the telephone (2595 minutes).
Four were conducted over email (427 days). One interview was conducted in person (160 minutes).c Thirty-seven of the Brazilian interviews were conducted in person (4775 minutes) in Sao Paulo,
SP, and Braslia, DF. One interview was conducted over the telephone (25 minutes). Four interviews
were conducted over email (315 days).d Interview respondents were solicited first from a purposive sample of lists of nonprofit contacts and
donors provided by USAID, IDB, the World Bank, the Grupo de Institucoes, Fundacoes e Empresas
and the Associacao Brasileira de Organizacoes Nao Governamentais. The sample included recipient
organizations that are successful at acquiring international funding, as well as those that are not, and
donor organizations at the national (Brazilian) and international level. Contact with this first sample
was initiated via email or over the telephone, with a 28 per cent response rate. At that point, respon-
dent contact continued from references of previous respondents, resulting in an overall sample that
originated as purposive, but ended with snowball effects.
Table A2. Variable Definitions and Descriptive Statistics
Variable Measurement Range Mean SD N
Yearly intake 2003 US$ $0$448m $4.2m $27.7m 297
Log intake Natural log of the 2003 intake 019.92 10.92 4.55 297
Experience Number of people on staff with
private sector experience
0856 17.82 65.99 319
Accessibility The total number of languages
(other than Portuguese) in which
someone from the organization
can communicate.
05 1.44 1.10 347
Fundraising
specialization
1=1 or more staff designated for
fundraising; 0=no staff
designated for fundraising.
01 0.76 0.43 301
Transparency 1=financial informationavailable; 0=financial
information unavailable.
01 0.59 0.49 317
Reliability 1= third-party audits performed;
0= no third-party audits
performed
01 0.56 0.50 315
(continued)
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Appendix. (continued)
Variable Measurement Range Mean SD N
Credibility 1= the organization possesses a
Certificado de Entidade Benefi-cente de Assistencia Social
CEBAS(Certificate of a
Beneficent Social Assistance
Entity) or Ttulo de Utilidade
Publica (Title of Public Utility)
0= no certification possessed.
01 0.65 0.48 370
Development sector * Children/Infants, Street children,
Youth/adolescents, Women,
Energy, Rights, Health,
Education, Landless Movement,
Consumer Protection,
Environment
NA NA NA 385
Children 1=
works with or for children;0= else. 01 0.68 0.47 385
Women 1=works with or for women;
0= else.
01 0.42 0.49 385
Environment 1=works with or for environment;
0= else.
01 0.22 0.42 385
Type of service 1=offers some type of indirect
services, such as research or
advocacy; 0=only direct
service offered.
01 0.74 0.44 384
International 1= international range; 0= else 01 .01 .20 381
National 1=national range; 0= else 01 .17 .38 381
State-level 1= state range; 0= else 01 .20 .40 381
Municipal 1=municipal range; 0= else 01 .35 .48 381
Community 1=neighborhood/community
range; 0= else
01 .23 .42 381
Religious affiliation 1=Religious affiliation 0=No
religious affiliation
01 0.22 0.42 383
Fulltime staff Number of fulltime staff 01400 37.11 133.73 344
Scandal range 1= founded 199194; 0= founded
prior to 1991, or after 1994
01 0.11 0.32 385
Reputation Count of international donors one
year prior to filling out survey
04 0.04 0.31 356
Strong found 1=Money from fund
appropriation, founders private
funds and contacts, or as a
spin-off with funds from another
organization; 0= else
01 .11 .31 375
Med. found 1= Individual, foundation, or
corporate funds, or combination
of money and volunteers;
0= else
01 .42 .49 375
Poor found 1=No money to found; 0= else 01 .47 .50 375
* Respondents listed a total of 10 extra sectors in the Other option.
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GINA YANNITELL REINHARDT is Assistant Professor of Public Policy, Inter-
national Affairs, and Public Service Administration at the Bush School of Govern-
ment and Public Service at Texas A&M University, where she researches
decision-making under uncertainty and its effects on the distribution of wealth in
society. ADDRESS: Bush School of Government and Public Service, Texas
A&M University, College Station, TX 77843-4220. [email: greinhardt@bush
school.tamu.edu]
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