The “Sect Effect” in Charitable Giving
Distinctive Realities of Exclusively Religious
Charitable Givers
By RUSSELL N. JAMES III and DEANNA L. SHARPE*
ABSTRACT. An examination of the charitable giving behavior of 16,442
households reveals intriguing patterns consistent with the clubtheoretic approach to religious sect affiliation. The club-theoretic
model suggests that individuals with lower socioeconomic standing
will rationally be more likely to align themselves with exclusivistic
sects. Because sect affiliation is also associated with more obligatory
religious contributions, this approach generates novel predictions
not anticipated by standard economic models of charitable behavior.
Traditional analysis of charitable giving can mask the “sect effect”
phenomenon, as low-income giving is dwarfed by the giving of the
wealthy. However, the application of a two-stage econometric
model—separating the participation decision from the subsequent
decision regarding the level of gifting—provides unique insights. Basic
socioeconomic factors have significant and opposite associations with
different categories of giving, calling into question the treatment of
charitable giving as a homogenous activity and supporting the understanding of sect affiliation, and potentially religious extremism, as
rational choice phenomena.
The study of charitable giving, and in particular the religious component of charitable giving, holds the promise of generating significant
insights when both economic and sociological perspectives are
employed. Religious charitable giving is by far the largest and most
*Russell N. James III, 203 Consumer Research Center, University of Georgia, Athens, GA
30602; e-mail Rjames@uga.edu. Dr. James’s research interests include charitable giving.
Deanna L. Sharpe, 239-C Stanley Hall, University of Missouri-Columbia, Columbia, MO
65211; e-mail SharpeD@missouri.edu. Dr. Sharpe’s research interests include consumer
expenditure patterns and later-life economic issues and policy.
American Journal of Economics and Sociology, Vol. 66, No. 4 (October, 2007).
© 2007 American Journal of Economics and Sociology, Inc.
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widespread component of the more than $183 billion in annual
donations made by individuals, exceeding all other forms of individual
charitable giving combined (Giving USA 2003; Van Slyke and Brooks
2005). Religious charitable giving has continued to grow over the last
several decades, expanding nearly 70 percent during the 1990s, with
similar periods of rapid expansion during the 1970s and early 1980s
(Giving USA 1999).
Sociologically, the importance of religion has never been more
apparent. From national security concerns and geopolitics to social
capital measurements and family structure, religion’s impact is difficult
to ignore. Because religious activity can take place in the context
of close-knit, sometimes even secretive, nonmarket environments,
empirical analysis can prove challenging. However, through the study
of religious charitable giving, we have the opportunity to use
advanced empirical tools on large data sets to help inform our
understanding of underlying religious behavior. As voluntary gifts
constitute 84 percent of all income to religious organizations in the
United States, understanding charitable giving must be core to any
serious examination of American religious organizations (Brooks
2004).
I
Background and Literature Review
STUDIES OF CHARITABLE BEHAVIOR have often treated all types of charitable
giving as homogenous or, in rare cases, have excluded religious giving
altogether (Clotfelter 1985; Reece 1979). Notwithstanding this variation, research across several decades has repeatedly confirmed some
persistent economic relationships. Charitable giving is income-elastic,
and this elasticity holds even when the price effect from the increasing
value of charitable tax deductions is held constant (Hrung 2004;
Andreoni and Scholz 1998; Clotfelter 1980, 1985; Abrams and Schitz
1978; Taussig 1967). Greater wealth and education are consistently
associated with increased giving (Schervish and Havens 2001; Brown
and Lankford 1992; Kingma 1989; Schwartz 1970).
Despite the well-established connections to income, wealth, and
education, a club-theoretic approach to sect affiliation suggests a
The “Sect Effect” in Charitable Giving
699
countervailing influence within certain groups of religious givers. A
club-theoretic approach views congregations as mutual-benefit societies where members work collectively to produce “club goods”
such as worship services, social activities, and religious instruction
(Iannaccone 1998). The value of participation, however, depends on
the positive externalities of other group members’ participation (Carr
and Landa 1983; Sullivan 1985; Wallis 1990). Group norms for
expected participation levels vary from group to group.
The participation requirements, including obligations to give, tend
to be strongest in more sect-like religious organizations. A “sect” is
defined in foundational sociological literature as exclusive, small,
ascetic, without a complex bureaucracy, rejecting or ignoring secular
society and dominant churches, with intensely devoted, close-knit
members, requiring committed, adult converts. In contrast, a “church”
is inclusive, large, impersonal, bureaucratic, adjusting to existing social
order, encompassing all who were born into it, possessing fewer
means to obligate members to give (Troeltsch 1931; Weber [1905]
1989).
Formally, we consider households maximizing an intertemporal
utility function that depends upon both secular consumption, C, and
religious activities, R:
U = U (C1, C2, . . . . , Cn, R 1, R 2, . . . . R n ).
Secular consumption utility depends upon the household inputs of
time, Tc, and purchased goods, Xc, as well as on one’s stock of
accumulated experience or “consumption capital,” Sc. Similarly, religious production depends not only on inputs of time and purchased
goods but also on one’s accumulated experience in a particular
religious tradition, itself being a function of past investments of time
and purchased goods. In addition, religious production depends upon
the positive externalities generated by the particular religious group to
which one belongs (Iannaccone 1998). These positive externalities, Q,
are a function of the m other members’ inputs of time, Tr, purchased
goods, Xr, and accumulated experience, Sr:
Ct = C( Tc, X c, Sc )
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R t = R ( Tr, X r, Sr; Q )
ΔSct = F ( Tct −1, X ct −1, Sct −1 )
ΔSrt = F ( Trt −1, X rt −1, Srt −1 )
Q = F ( Tr1, Tr 2, . . . Tr m; X r1, X r 2, . . . X r m; Sr1, Sr 2, . . . Sr m )
The effort to match desired individual religious participation levels
(Tr, Xr, Sr) with club norms, Q, generates a spectrum of religious
groups from high-cost “sects” to easygoing “churches” (Barros and
Garoupa 2002). In order to maintain equilibrium in Q, highparticipation groups typically would enforce preexisting commitment
minimums as a condition of continued membership. Maximization of
members’ utility functions necessitates that groups be able to eliminate
uncommitted “free riders” who absorb far more resources than they
contribute. This is especially critical for sect-like groups with high
average commitment levels, as member benefits can be substantial.
Sect member benefits for those in need can include food, clothing,
and shelter, as well as the status and affection that create a kind of
“alternative society” (Stark and Bainbridge 1985). Of necessity, sectlike congregations are generally smaller and more adept at monitoring
member activity to prevent free riding (Montgomery 1996; Iannaccone
1994). Thus, while sect members enjoy greater benefits, they are also
subjected to more strictly enforced obligations, including, presumably,
resource-appropriate financial contributions. Free riding also is prevented through successful enforcement of behavioral rules (perhaps
of dress, diet, holiday observance, or other conduct) at odds with
societal norms. The adoption of such behavioral rules provides an
effective, easily monitored proxy for underlying commitment. In
essence, sects present a convex production possibilities frontier
between societal norms and sect expectations where only complete
adherence or complete rejection are maximizing choices (see Iannaccone 1988 for this graphical model). Sect membership provides a high
reward option, but one that is only available at the cost of rejecting
societal norms. This “conduct and rewards” dichotomy makes a sect
The “Sect Effect” in Charitable Giving
701
more attractive to those with diminished secular opportunities, as their
opportunity costs for rejecting societal conduct norms are lower
(Iannaccone 1992).
Consistent with this optimization, we note that sects are populated
predominantly by the lower classes and churches by the upper classes
(Montgomery 1996). This finding is not new. Russell Dynes noted a
significant correlation between low socioeconomic status and sectarian orientation in his 1955 sociological study. To the extent that blacks
face fewer opportunities in mainstream society, we would rationally
expect a higher proportion to choose sect membership. And, indeed,
such racial connections have been documented (Argyle and BeitHallahmi 1975), including a particularly interesting study reviewing
West Indian immigrants to Great Britain (Hill 1971). This study found
that they commonly switched from more open church membership in
their home country to exclusivistic Pentecostal sects after emigrating,
hinting that relative secular opportunities, rather than any inherent
racial differences, drive such affiliations.
For the purposes of the present study, sect affiliation is most critical
in its impact on religious charitable giving. One large study of Northern California church members captures this distinction, finding that:
sect members are poorer and less educated; they contribute more money
and attend more services; they hold stronger and more particularistic
religious beliefs; their congregations are smaller yet are more likely to
include their closest friends. The differences are strong, striking and
statistically significant. (Iannaccone 1988: S242)
A “sect effect” suggests that lower socioeconomic standing increases
the probability of sect membership, which, in turn, generates a strong
expectation of religious giving. Any such effect would be particularly
interesting, given that the same socioeconomic factors associated with
sect membership are otherwise related to a lowered probability for
charitable giving. Naturally, this effect would be ascertained most
clearly by separately examining religious and secular charitable givers.
It is important to note that the proposed “sect effect” in religious
charitable giving has no corollaries in the standard economic models
of charitable giving. Several approaches to modeling charitable giving
have been common in the literature, including a public goods game
approach; the warm glow theory; the altruistic cooperative; and
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prestige models. A public goods game approach, if used without the
intervening construct of sect affiliation, makes no a priori predictions
that any form of charitable giving would become more likely as
socioeconomic standing decreases. Individual behavior is simply
modeled as a game wherein each participant tries to contribute
minimum resources for a maximum share of public goods. Having
fewer resources does not, by itself, rationally increase the likelihood
of contributing those scarce resources to any particular public goods
game. The “warm glow” approach assumes that donors receive utility
from the gift itself in the form of intangible benefits such as respect,
social approval, relief from guilt, or a general good feeling (Andreoni
1993, 1995). Charitable giving may also be viewed more narrowly as
a way to gain economic prestige where total utility is a function of
goods consumption and one’s income level as perceived by others
(Glazer and Konrad 1996). Yet, in either case, we would not naturally
expect lower socioeconomic standing to increase the likelihood of
purchasing either the prestige or “warm glow” effects through charitable gifts. Similarly, the altruistic cooperative proposed by Becker
(1974, 1976), in which individuals cooperate either because of their
own interdependent utility function or the interdependent utility function of another who contributes simultaneously to the individual and
a third party, does not anticipate increasing altruism (real or simulated) for those with fewer economic resources. Indeed, the “sect
effect” appears to be alone in predicting this counterintuitive behavior
for a specific segment of religious charitable giving.
II
The Two-Stage Econometric Approach
TO EXAMINE THE POSSIBILITY of a “sect effect” in religious charitable
giving, we must be careful to use an approach that will not mask
low-income charitable behavior through the dwarfing magnitude of
charitable gifts by the wealthy. A particularly appropriate approach in
the context of religious giving is to separate the decision to be a
religious-cause giver from the decision regarding the amount of gift to
be made. For example, it is unlikely that an atheist would make gifts
to organized religion regardless of the changes in his or her income or
The “Sect Effect” in Charitable Giving
703
the reduction in the (still positive) cost of the gift from tax benefits,
whereas such factors would undoubtedly affect the level of gifting for
someone with a different theological perspective. A separate analysis
of the initial binary issue of participation versus nonparticipation also
moderates the risk of large gifts from wealthy donors statistically
dominating the giving behavior of less affluent givers. (See Schervish
and Havens 1995 for an example of the importance of distinguishing
charitable giving participation rates from charitable giving levels in
statistical analysis.)
Statistical models that differentiate between the participation decision and the level of consumption decision have been commonly
employed in research of other types of consumer behavior (Garcia
and Labeaga 1996; Cragg 1971). For example, many individuals would
not purchase alcohol regardless of changes in their income or in the
price of beer. Consequently, this consumption decision frequently is
modeled using the two separate stochastic processes of the doublehurdle model (Sharpe et al. 2001). Similarly, demand models for tobacco consumption frequently employ double-hurdle models (Blaylock
and Blisard 1992). Other applications of the double-hurdle have
included consumption of cheese (Gould 1992), vegetables (Reynolds
1990), and shellfish (Lin and Milon 1993), as well as estimating
demand for mortgages (Leece 1995).
Previous statistical approaches to charitable giving necessarily had
to deal with the reality that charitable giving data typically involve
a high proportion of zero observations in the dependent variable
(i.e., many people make no charitable gifts). Thus, these analyses
commonly employed an ordinary least squares (OLS) lognormal, OLS
translog, or Tobit model (Lankford and Wyckoff 1991). However, all
of these models are restrictive in that an independent variable that
increases the probability of a nonlimit observation also increases the
mean of the dependent variable (Greene 1993). A double-hurdle
model allows these two results to be independent. The factors associated with the decision to participate may be completely different
from those that influence the level of consumption once participation
is chosen. Indeed, a factor may even have opposite effects on
the likelihood of participation and the level of participation. Such
flexibility is critical, as we hypothesize lower economic resources
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increasing the likelihood of sect participation, and hence religious
charitable giving, while recognizing that diminished resources will
ultimately have a negative impact on the potential level of giving.
We examine separately religious and charitable giving by considering three groups of givers: those who make exclusively religious gifts;
those who make exclusively secular gifts; and those who make both
religious and secular gifts. Each charitable giver category is mutually
exclusive; a decision to participate can be made in favor of only one
category. Without this division, the desire to examine differences
between those who give to religious organizations and those who give
to other charitable organizations can be frustrated by the reality that
these two groups include a large proportion of shared individuals. The
separation of exclusive-giving groups allows us to examine those
individuals not simultaneously participating in both giving categories.
This separation facilitates an examination of the differences between
those who give to religious organizations and those who give to other
charitable organizations.
As an additional benefit, the creation of a category for exclusively
religious givers should help to bring special attention to the impact of
sect members. That the exclusively religious giving category is more
likely populated by sect members corresponds with previous observations of sect characteristics. For example, more sect-like denominations define a tithe as intended for support of the church only,
whereas other denominations intend a tithe to be for both the church
and other charitable causes. Higher denominational and individual
religious strictness is commonly associated with participation in
religious giving (Olson and Perl 2005; Lunn et al. 2001). Hoge et al.
(1996) found that regular church attenders directed a lower percentage of their total giving to nonreligious charities and causes, while
infrequent attenders gave higher percentages. In addition, sect
members naturally would have the greatest impact on the “exclusively
religious giver” category due both to a higher propensity to make
religious gifts and to relatively lower financial resources for other
forms of gifting.
Our approach is identical to the Heckman complete dominance
model, but we use it to ask two separate sets of questions. First, using
probit analyses, we ask: “What factors are associated with the decision
The “Sect Effect” in Charitable Giving
705
to be a particular type of giver (exclusively religious, exclusively
secular, or mixed)?” Second, using a least squares analysis, we ask:
“Among those who have chosen to be particular types of givers, what
factors influence their nonzero level of giving?” This version of a
double-hurdle model allows us to compare the factors that influence
religious giving levels among exclusively religious givers as contrasted
with mixed givers, as well as considering these same factors’ influence
on secular giving levels among both mixed and exclusively secular
givers. Because we are postulating the exclusively religious givers
category as being more likely populated by, and representative of,
sect members, this specification becomes particularly useful in allowing us to examine the behavior of this particular category’s members.1
The models for the first-stage investigation use three separate probit
analyses with the dummy dependent variables of exclusively religious
giver, exclusively secular giver, and mixed giver. The independent
variables in each case are pretax income (natural log), number of
minor children in the household, and age of the reference2 person
(natural log), as well as the dummy variables of urban residence, level
of education of the reference person, being black (as compared with
being of another race), and being a single female or a single male (as
compared with being married). The participation equation is:
Pi = χ pi ′ βp + ε pi; ε pi ∼ n.i.d. (0, σ 2 p ) i = 1, . . . , N,
where cpi is our vector of factors explaining variation in the participation for i = 1, . . . , N; N is the number of observations; bp is a vector
of unknown parameters relating cpi to Pi,; and epi is the error term. The
error term epi is assumed to be normally and independently distributed
with a mean of zero. Because the participation equation measures the
presence of category participation, not the nonzero level of participation, Pi is a binary variable. Pi is 1 if the ith unit is participating and
0 if it is not. Holding to the previously stated assumption about the
error term, this first equation can be properly estimated using a probit
analysis.
The second stage of the analysis then focuses on the impact of these
independent variables on the (nonzero) dollar level of gifting among
individuals in each of the three different categories of givers. For
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exclusively religious givers, this dollar level is the level of religious
gifting. For exclusively secular givers, this is the level of secular
charitable gifting. For mixed givers, we consider two separate regressions. One examines the level of religious giving, and another examines the level of secular charitable giving. Thus, this second-stage
analysis involves a total of four different regressions within the three
different subgroups of charitable givers. The expenditure equation is:
Ci = χ ci ′ βc + ε ci; ε ci ∼ n.i.d. (0, σ 2c ) i = 1, . . . , N c.
In this equation, cci is a vector of factors explaining variation in the
expenditure level for i = 1, . . . , Nc; Nc is the number of observations
excluding nonparticipants; bc is a vector of unknown parameters
relating cci to Ci; and eci is the error term. The error term eci is assumed
to be normally and independently distributed with a mean of zero.
Here, Ci represents the nonzero dollar level of either religious or
nonreligious charitable expenditures, depending upon the participation category. Ci is thus a continuous, positive variable. This expenditure level is estimated using a least squares regression analysis.
In sum, we use probit analyses for participation in each of three,
mutually exclusive, giving categories followed by least squares
analysis for religious giving levels among exclusively religious givers,
nonreligious giving among exclusively secular givers, religious giving
among mixed givers, and nonreligious giving among mixed givers.
Finally, these results are compared with an alternative standard
(single-hurdle) model examining the overall impact of the independent variables on giving levels. Because 54 percent of our sample
reported no contributions, we estimate these final giving functions
with a Tobit specification censored at zero. We use three different
Tobit models to separately examine the independent variables’ impact
on total giving, religious charitable giving, and secular charitable
giving.
III
The Data
THE DATA ARE GATHERED from 16,442 separate households participating
in the Consumer Expenditure Survey from 1998 to 2001. These include
The “Sect Effect” in Charitable Giving
707
all complete income reporters who made a fifth-quarter report during
the three-year period from the second quarter of 1998 through the first
quarter of 2001. The Consumer Price Index was used to convert all
dollar variables to constant 2001 dollars. Because questions regarding
charitable expenditures were asked only in the fifth-quarter interview
and each household completes only one fifth-quarter interview, no
household is represented more than once in the sample. We label as
“religious” gifting the amounts reported in response to the question:
During the past 12 months, how much were contributions to church or
other religious organizations, excluding parochial school expenses, made
by you (or any members of your [household])?
We categorize as “secular” giving the total of those amounts given in
response to the following four questions:
1. During the past 12 months, how much were contributions to charities,
such as United Way, Red Cross, etc., made by you (or any members of your
[household])?
2. During the past 12 months, how much were contributions to educational organizations made by you (or any members of your [household])?
3. During the past 12 months, how much were political contributions
made by you (or any members of your [household])?
4. During the past 12 months, how much were other contributions made
by you (or any members of your [household])?
We exclude from this study person-to-person gifts reported in
response to the question:
During the past 12 months, how much were gifts of cash, bonds, or stocks
to persons not in the [household] made by you (or any members of your
[household])?
IV
Results
A. Summary Statistics
Broad outlines of the type of contrasts predicted by a club-theoretic
model of sect affiliation can be seen in the summary data. Income
repeatedly has been shown to be positively associated with charitable
giving. However, sect membership is negatively related to income. We
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see the initial indications of this contrast in the descriptive statistics. At
$66,292, mixed-giver households have a mean pretax income 39.5
percent above the sample average, while exclusively secular givers, at
$62,057, average 30.6 percent more income than the typical household.
In contrast, exclusively religious givers fall below the sample mean by
more than 11 percent, with only $42,224 in pretax household income
(see Table 1).
Black racial status has been linked to lower charitable giving levels
(Van Slyke and Brooks 2005). Yet to the extent that blacks face more
limited opportunities from the dominant secular culture, the rational
attractiveness of sect affiliation increases. Consistent with this predicted effect, we see a larger proportion of blacks in our exclusively
religious giver category. A much larger share of exclusively religious
givers are black (14.3 percent) than exclusively secular givers (5.4
percent). Indeed, blacks constitute a higher proportion of the exclusively religious givers category than any other category, also exceeding nongivers (12.4 percent), mixed givers (6.6 percent), and the
sample as a whole (10.6 percent).
Education has been repeatedly shown to be positively associated
with charitable giving (Brown and Lankford 1992; Kingma 1989;
Schwartz 1970). Higher education typically is associated with higher
permanent income levels and thus indicates greater access to resources.
Once again, however, sect theory predicts a counterbalancing effect, in
that lower education levels are associated with sect membership and
sect membership is linked to a higher likelihood of religious charitable
giving. Again, we can see initial indications of this counterbalancing
effect in the descriptive statistics. Having no high school diploma is less
common among mixed givers (6.9 percent) and exclusively secular
givers (8.6 percent) than among the sample as a whole (16 percent), but
is more common among exclusively religious givers (17.8 percent). We
see similar results at the higher end of the spectrum, where a greater
proportion of exclusively secular givers (23.7 percent) and mixed givers
(23.4 percent) have college degrees than the general sample (17.2
percent), while exclusively religious givers (15.6 percent) fall below the
overall average. This trend continues as we see exclusively religious
givers having less than the average proportion of graduate education
while the other giving categories have more.
-0-0-0-
Relief giving
Miscellaneous giving
2,668
$42,224
($39,943)
$1,223
($2,071)
$1,223
($2,071)
-0-
Political giving
Educational giving
Religious giving
Total giving
N
Pretax HH income
Variable
Exclusively
Religious
Givers
3,039
$66,292
($58,594)
$2,698
($8,499)
$1,891
($5,458)
$147
($2,181)
$30
($211)
$573
($4,206)
$57
($790)
Mixed
Givers
$57
($348)
$24
($178)
$334
($1,125)
$44
($582)
2,508
$62,057
($54,884)
$459
($1,380)
-0-
Exclusively
Secular Givers
Profiles of the Total Sample and the Four Subsamples
Table 1
-0-
-0-
-0-
-0-
-0-
8,227
$37,898
($38,520)
Nongivers
16,442
$47,533
($47,362)
$767
($3,920)
$548
($2,608)
$36
($949)
$9
($115)
$156
($1,875)
$17
($409)
All
The “Sect Effect” in Charitable Giving
709
Family size
HH making education gifts
HH making political gifts
HH making relief gifts
HH making miscellany gifts
% of after-tax income given
Tithers (giving 10%+ of after-tax
income to any charity)
Religion tithers (giving 10%+ of
after-tax income to religion)
Married HH
Single female HH
Single male HH
Age of reference person
Variable
21.3%
12.7%
88.6%
8.6%
4.5%
14.1%
10.4%
68.3%
22.0%
9.7%
53.2
(16.5)
2.6 (1.5)
11.7%
58.8%
29.8%
11.4%
49.9
(18.4)
2.7 (1.6)
Mixed
Givers
-0-0-0-03.1%
11.7%
Exclusively
Religious
Givers
Table 1 Continued
55.0%
25.9%
19.1%
48.2
(16.1)
2.4 (1.3)
-0-
15.7%
10.6%
84.8%
10.2%
0.8%
1.6%
Exclusively
Secular Givers
46.0%
31.7%
22.2%
45.7
(17.9)
2.5 (1.5)
-0-
-0-0-0-0-0-0-
Nongivers
53.5%
28.7%
17.7%
48.2
(17.7)
2.5 (1.5)
3.8%
6.3%
4.0%
29.4%
3.1%
1.7%
4.7%
All
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The American Journal of Economics and Sociology
HH with persons over 64
HH with persons under 18
Number under 18 in HH
Education level
Less than high school
High school graduate
Some college
Bachelor’s degree
Graduate education
Black HH
Urban HH
31.2%
34.8%
0.66 (1.07)
6.9%
23.6%
29.8%
23.4%
16.3%
6.6%
91.9%
28.3%
38.7%
0.77 (1.18)
17.8%
28.9%
31.5%
15.6%
6.1%
14.3%
88.9%
8.6%
25.3%
27.8%
23.7%
14.6%
5.4%
92.1%
20.3%
30.2%
0.53 (0.95)
21.1%
30.8%
28.7%
13.4%
6.0%
12.4%
90.8%
20.8%
37.0%
0.71 (1.12)
16.0%
28.3%
29.2%
17.2%
9.2%
10.6%
90.9%
23.9%
35.9%
0.69 (1.10)
The “Sect Effect” in Charitable Giving
711
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The American Journal of Economics and Sociology
Overall, the demographic characteristics of our exclusively religious
giving group mirror those of sect members. As discussed previously:
“Theologically conservative denominations (typically labeled ‘fundamentalist,’ ‘Pentecostal,’ or ‘sectarian’) draw a disproportionate share
of their members from among the poorer, less educated, and minority
members of society” (Iannaccone 1998: n.6).
Exclusively religious donors constitute about 15 percent of our data
set. It is difficult to ascertain a comparable national number of those
in more sect-like denominations. This exercise is challenging in part
because there is no universally accepted taxonomy of “conservative,”
“fundamentalist,” or “sect-like” denominations. The problem is
compounded by broad denominational categories that include radical
splinter groups and the presence of some 500 to 1,000 cults or
alternative religions in the United States (Barker 1986). However, we
can consider a rough comparison with the American Religious Identification Survey (Kosmin, Mayer, and Keysar 2001), which indicates
that about 8 percent of Americans belong to Pentecostal, Charismatic,
Assemblies of God, Churches of God, Churches of Christ, Jehovah’s
Witnesses, Christian Scientist, Apostolic, Foursquare Gospel, or LatterDay Saints (Mormon) denominations, with another 16 percent belonging to some form of Baptist church. Similarly, General Social Survey
data from 1989–1996 showed that about a quarter of individuals
affiliate with “Baptist or conservative Protestant bodies (e.g., Assembly
of God, Churches of Christ, Church of God in Christ, Nazarene,
Pentecostal)” (Sherkat and Ellison 1999: 366)
Such statistical comparisons are problematic for the current analysis,
as we do not anticipate that all sect members will be exclusively
religious givers or that all exclusively religious givers will be sect
members. Rather, the expectation, based upon previous studies, is that
sect members are more likely to engage in exclusively religious giving
than others and hence will be heavily represented in this category.
B. First-Stage Probit Analysis
The first stage of the double-hurdle model investigates the impact of
the independent variables on the likelihood of participation in a particular category of giving, without considering the level of participation.
The “Sect Effect” in Charitable Giving
713
In particular, the first set of results explores the relationship of various
independent variables to the likelihood of being an exclusively religious giver, an exclusively secular giver, or a mixed giver.
The results shown in Table 2 display an immediate, substantial
difference in the impact of certain variables on the likelihood of
participating in the three different forms of charitable giving.
In examining the impact of income, we see a direct contrast
between exclusively religious givers and other types of givers. Greater
income significantly increases the likelihood of exclusively secular
giving and mixed giving but significantly decreases the likelihood of
exclusively religious giving. In the area of race, we again see a direct
contrast between exclusively religious and exclusively secular giving.
For exclusively secular giving, black racial status is significant at the
0.001 level and decreases the likelihood of giving as compared with
nonblack racial status. However, for exclusively religious giving, black
racial status is also significant at the 0.001 level and increases the
likelihood of giving.
The contrast continues when we examine education. Having less
than a high school education significantly reduces the likelihood of
being an exclusively secular giver or a mixed giver but has no such
impact on the likelihood of being an exclusively religious giver.
Conversely, graduate education significantly reduces the likelihood of
being an exclusively religious giver while significantly increasing the
likelihood of being a mixed or exclusively secular giver. Once again,
the results are consistent with the posited influence of sect membership within the exclusively religious charitable giving.
C. Second-Stage Truncated Regression Analysis
As we might expect, the level of giving among those who have made
the decision to be givers is more similarly affected by economic factors.
All of the significant variables are of the same sign, and we see little of
the contrast revealed in the first-stage probit analysis.3 (See Table 3.)
D. Tobit Analysis
It is instructive to note that many of the most interesting “sect-effect”
phenomena are masked when using a standard Tobit analysis. If we
Bachelor’s degree
Some college
Education level of reference person
Less than high school grad
Single female reference person
Single male reference person
Black
Ln (Income)
-0.211***
(0.043)
0.023
(0.033)
0.179***
(0.037)
0.178***
(0.014)
-0.323***
(0.048)
0.106
(0.036)
0.096
(0.032)
-0.046***
(0.012)
0.248***
(0.037)
-0.331***
(0.038)
-0.105***
(0.03)
0.008
(0.826)
0.081
(0.031)
-0.008
(0.825)
(Probit) Probability
of Being an Exclusively
Secular Giver
(Probit) Probability
of Being an
Exclusively Religious
Giver
Results of Probit Analysis for Charitable Giving Types
Table 2
-0.397***
(0.044)
0.210***
(0.032)
0.328***
(0.036)
0.191***
(0.015)
-0.122
(0.044)
-0.351***
(0.039)
-0.155***
(0.031)
(Probit) Probability
of Being a
Mixed Giver
714
The American Journal of Economics and Sociology
0.241***
(0.044)
0.029
(0.044)
-0.089***
(0.013)
0.044
(0.036)
-3.079***
(0.211)
2,508
-6,739.12
-0.220***
(0.05)
-0.127
(0.04)
0.041***
(0.012)
0.173***
(0.034)
-1.042***
(0.19)
2,668
-7,164.68
0.426***
(0.043)
0.043
(0.043)
0.017
(0.013)
0.817***
(0.039)
-6.119
(0.233)
3,039
-7,104.40
(Probit) Probability
of Being a
Mixed Giver
N = 16,442.
***Estimate is significant at the 0.1% level (p < 0.001). Given the large N, we note only those having this very high significance level.
Group members
Log likelihood
Constant
Ln (age of reference person)
Number of minor children in household
Urban residence
Graduate education
(Probit) Probability
of Being an Exclusively
Secular Giver
(Probit) Probability
of Being an
Exclusively Religious
Giver
Table 2 Continued
The “Sect Effect” in Charitable Giving
715
Bachelor’s degree
Some college
Education level of reference person
Less than high school graduate
Single female reference person
Single male reference person
Black
Ln (Income)
Truncated Regressions (OLS)
-234.26*
(118.56)
367.04***
(102.32)
254.16*
(125.89)
314.28***
(47.50)
190.84
(114.13)
-502.39***
(134.86)
-387.30***
(102.11)
Religious Giving
of Exclusively
Religious Givers
-50.47
(108.21)
121.75
(74.64)
261.09***
(78.94)
149.13***
(28.30)
-40.88
(120.61)
-74.64
(76.71)
-82.69
(69.51)
Secular Giving
of Exclusively
Secular Givers
-44.50
(393.13)
295.66
(249.50)
673.14*
(270.29)
313.04**
(103.50)
-343.16
(365.84)
344.04
(321.97)
10.06
(242.43)
Secular Giving
of Mixed Givers
Results of Truncated Regression Analysis for Charitable Giving Levels
Table 3
-199.99
(425.64)
406.46
(270.14)
778.72**
(292.64)
719.54***
(112.06)
480.91
(396.10)
256.87
(348.60)
-258.04
(262.49)
Religious Giving
of Mixed Givers
716
The American Journal of Economics and Sociology
***p < 0.001; **p < 0.01; *p < 0.05.
N
R2
Constant
Ln (age of reference person)
Number of minor children in household
Urban residence
Graduate education
856.03***
(174.73)
-4.87
(124.80)
-1.97
(37.14)
335.75**
(112.78)
-3,308.07***
(672.27)
2,668
0.07
498.37***
(90.74)
183.58
(101.14)
-39.57
(31.24)
326.35***
(83.81)
-(2,652.24)***
(463.77)
2,508
0.05
1,609.01***
(298.00)
-310.27
(333.10)
-33.96
(97.43)
1,071.10***
(317.32)
-6,969.92***
(1,798.51)
3,039
0.02
1871.76***
(322.65)
-102.48
(360.65)
101.45
(105.49)
1,622.47***
(343.57)
-12,776***
(1,947.25)
3,039
0.04
The “Sect Effect” in Charitable Giving
717
718
The American Journal of Economics and Sociology
simply estimate the effect of a variable on the overall population’s
level of giving without any separate examination of participation
effects, the impact of large gifts by the wealthy can cover significant
behavioral trends among poorer donors.
The Tobit coefficients (see Table 4) simply provide the standard
results, seen in numerous other studies, that overall charitable giving
is positively related to income, education, age, and marriage. Separating religious giving from nonreligious giving in the Tobit analysis is
a positive step. This separation reveals the significant and opposite
impact of black racial status on religious and nonreligious giving. But
the sect effect impacts seen in income and education remain hidden.
Just as the impact of sect affiliation is highlighted by examining
exclusively religious givers as a separate group, it is masked when we
pool them with other, generally more affluent, donors in the traditional Tobit analysis.
V
Conclusions
A. It May Be Inappropriate to Analyze Charitable Giving
as a Homogenous Activity
It is not uncommon for studies of charitable giving to treat all types of
charitable gifts as essentially fungible, in other words, as a homogeneous type of consumer transaction. The dangers of such an approach
are demonstrated in the significant and opposite relationships of basic
socioeconomic variables such as income, education, and race to
different categories of charitable giving. If two-thirds of a group is
traveling north and one-third is traveling south, it is not necessarily
appropriate to describe the group as moving north, slowly. And yet a
statement that decreased income and education is associated with a
decreased likelihood of charitable gifting creates a similarly deceptive
impression. We know, for our sample at least, that specific kinds
of charitable activity, such as the exclusive support of religious
organizations, relate to fundamental socioeconomic variables in
ways directly contrary to other forms of charitable giving, such as the
exclusive support of secular charitable organizations. However, if we
Graduate education
Bachelor’s degree
Some college
Education level of reference person
Less than high school
Single female reference person
Single male reference person
Black
Ln (Income)
-839.77***
(157.35)
910.99***
(125.06)
1,132.38***
(144.84)
1,736.60***
(173.30)
569.13***
(54.50)
570.86***
(156.81)
-1,757.67***
(150.38)
-799.151***
(121.13)
(Tobit) Religious
Contributions
-1,181.13***
(144.66)
568.72***
(106.70)
1,215.55***
(119.75)
1,986.87***
(140.48)
779.30***
(46.21)
-929.02***
(150.10)
-412.50***
(121.06)
-169.56
(102.97)
(Tobit) Secular
Contributions
Results of Tobit Analysis for Charitable Giving for Entire for Entire Sample
Table 4
-1,146.18***
(173.62)
975.30***
(137.03)
1,617.89***
(157.47)
2,733.60***
(189.06)
915.08***
(58.30)
-44.48
(176.66)
-1,340.74***
(158.17)
-589.19***
(132.19)
(Tobit) All
Contributions
The “Sect Effect” in Charitable Giving
719
***Estimate is significant at the 0.1% level.
Noncensored observations
Censored observations
Log likelihood
Constant
Ln (age of reference person)
Number of minor children in household
Urban residence
(Tobit) Secular
Contributions
114.60
(142.56)
-152.85***
(42.25)
1,936.96***
(122.49)
-18,566.9
(727.50)
5,547
10,895
-57,883.56
(Tobit) Religious
Contributions
-203.76
(162.35)
171.34***
(47.21)
2,669.49***
(143.09)
-18,940.8
(836.52)
5,707
10,735
-61,131.68
Table 4 Continued
-139.36
(179.84)
-2.54
(52.60)
2,824.65***
(153.80)
-22,442.8***
(894.45)
8,215
8,227
-86,809.37
(Tobit) All
Contributions
720
The American Journal of Economics and Sociology
The “Sect Effect” in Charitable Giving
721
were to examine only the Tobit analysis on overall charitable giving
levels, we would see little to indicate the presence of this sect effect
among exclusively religious donors. No doubt these distinctions can
make descriptions more cumbersome, but the presence of multiple,
highly significant relationships of opposite sign provide strong evidence that generalizations of charitable giving as a whole run the risk
of ignoring important realities within specific classes of donors. It is
also worth mentioning that we can’t simply say that religious givers
are poorer and less educated, because mixed givers—also a class of
religious givers—are, in our sample, demonstrably wealthier and more
educated than both exclusively secular givers and the sample as a
whole.
B. The “Sect Effect” Provides a Potential Theoretical Basis
for These Notable Results
The curious result that participation in a certain class of charitable
giving is made more likely by the presence of reduced income,
lowered education, and black racial status is not predicted by the
standard economic theories on charitable giving. In the absence of the
club-theoretic model of sect affiliation, we might have some difficulty
putting together a coherent theoretical underpinning for this unusual
consumer behavior. Yet, these results are clearly consistent with the
posited club-theoretic sect affiliation model.
Sects provide a high reward option, but one that is only available at
the cost of rejecting societal norms. Those with relatively lower secular
opportunity costs should rationally be drawn to the sect value proposition. Lower income, less education, and black racial status all point
to the likelihood of fewer societal opportunities. As predicted, these
same factors are all associated with an increased likelihood of exclusively religious charitable giving, our posited proxy for sect-consistent
behavior.4
C. A Rational Choice Model of Religion May Be Appropriate
for Future Policy Considerations
Recently, religious extremism has been associated with a variety of
violent and offensive behaviors of geopolitical significance. Nobel
722
The American Journal of Economics and Sociology
Laureate Gary Becker modeled the typical responses to offensive
behavior as increasing the probability or magnitude of punishment
(Becker 1968). These responses fall short, however, when religious
extremists engage in intentional martyrdom, harming others in the
process. In these situations, despite absence of government or other
public policy intervention, the probability and magnitude of the
punishment for the extremist (death) are high.
Results of this study suggest that other responses to offensive
religious behavior may warrant consideration. Specifically, if religious
behavior is viewed as an irrational, exogenous, unmanageable constant, then we are unlikely to recognize the power of underlying
economic factors in encouraging such extremism. A rational choice
model of sect affiliation suggests that the future martyr’s initial decision
to affiliate with the extremist group may have resulted from rational
choice. As such, it may be worthwhile to consider the circumstances
that made the initial affiliation appear to be utility-maximizing. For
example, Iannaccone (2000), following an argument earlier presented
by Adam Smith in the Wealth of Nations, discusses how an open
religious market structure allowing the free formation of religious
groups may reduce extremism by providing a wider array of strictness
choices, instead of only extremes. Evidence that religious affiliation
flows from rational choices—rather than being an irrational, exogenous
factor—strengthens the value of such policy considerations.
Notes
1. Other double-hurdle specifications examine the impact of an independent variable on the overall level of consumption in the population as a
whole. Here our model’s use is dictated by the particular question being
asked, that is: Given that an individual is in a particular participation category,
how do various factors influence the level of participation? We specify this
second question to explore differences among different category members in
what influences nonzero levels of giving. For questions examining the impact
of an independent variable on the overall level of consumption in the
population as a whole, the standard complete dominance model is appropriate where the participation and consumption equations are independent
(Heckman 1979; Blaylock and Blisard 1993).
2. The reference person is the first member mentioned by the respondent
when asked to “[s]tart with the name of the person or one of the persons who
owns or rents the home” (U.S. Dept. of Labor 2003: 250).
The “Sect Effect” in Charitable Giving
723
3. The R 2 values are quite low in this analysis. As our goal in this second
stage is to examine the impact of the independent variables at issue, rather
than using the model to successfully predict the ultimate level of giving, we
can perhaps be slightly less concerned with this issue. Nevertheless, these
standard socioeconomic variables appear to be doing a poor job of explaining
the variation in the ultimate giving levels among those who have chosen to be
certain types of givers.
4. We see similar results even among those who are mixed givers. An
ordinary least squares regression on the proportion of giving dedicated to
religion within this mixed group, using the same dependent variables as our
probit model, finds negative association of income [-0.01048 (0.00532)],
bachelor’s-level education [-0.02771 (0.01389)], and graduate-level education
[-0.08661 (0.01531)] while finding positive association of black racial status
[0.12632 (0.018800)].
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