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Sarah L. Pettijohn1/ Elizabeth T. Boris2
Testing Nonprofit State Culture: Its Impact on the
Health of the Nonprofit Sector
Abstract:
Government monitors, regulates, and funds nonprot organizations, making it is a key player in the health of
the nonprot sector in the United States. However, not all states treat nonprots similarly. Prior work identi-
ed three types of state nonprot culture (Pettijohn, S. L., and E. T. Boris. 2017. State Nonprot Culture: Assessing
the Impact of State Regulation on the Government-Nonprot Relationship. Grand Rapids, MI: ARNOVA Presenta-
tion.), or a unique set of attitudes and beliefs that shape the operating norms between state government and
nonprots. This article analyzes whether dierences among state nonprot culture are measureable in the
government-nonprot relationship. Using data from the Urban Institute’s 2013 Nonprot-Government Con-
tracting and Grants survey, we nd there are signicant dierences in the government-nonprot funding rela-
tionships, which means nonprots operating in certain state nonprot cultures face dierent types and degrees
of risk to their organization’s overall health.
Keywords: nonprot government relations, state government, nonprot regulation
DOI: 10.1515/npf-2018-0012
Government is a key player in the health of the nonprot sector in the United States. Not only do local, state,
and federal governments account for more than one-third of the sector’s total revenue (McKeever, Dietz, and
Fye 2016), they also regulate and monitor nonprot activity, all of which profoundly impacts the health of
the nonprot sector. The relationship between nonprots and state government has become more important as
resource constraints at the Internal Revenue Service (IRS) have weakened federal oversight of charitable orga-
nizations (Mayer 2016), further strengthening the state’s role in regulating nonprots. Lott and Fremont-Smith
nd, “State governments have a direct impact on nonprot charities in several ways: they regulate them, they
exempt them from major taxes, and they use them as vehicles to deliver publicly funded services”(2017, 163).
However, each state determines how it regulates, exempts, and partners with nonprots operating within its
boundaries. This means a nonprot operating in one state may have more complex requirements, enjoy greater
support or face more opposition from its state government compared to a nonprot operating in another state.
Recent work identied three types of state nonprot cultures that describe the relationship between govern-
ment and nonprots at the state level. In this paper, we explore whether there are signicant dierences for
nonprots that operate in these three dierent state nonprot cultures. Specically, the paper examines dif-
ferences between state nonprot culture and the level of nancial risk (assumed in dierent types of contracts
with government agencies) or dierences in problems nonprots report on securing, managing, and reporting
on government funds. We begin by discussing the three types of state nonprot cultures and the government-
nonprot funding relationship. Then, we outline data sources, variables considered, and methods used. The
nal two sections present the results and ndings.
1 State Nonprofit Culture
Political scientists have long discussed the importance of how U.S. states were settled and the role ethnic and
religious values played in a state’s political culture, or its “system of shared values that legitimate a preferred
set of social relationships”(Lieske 2012, 110–111). A state’s political culture shapes social and political prefer-
ences by helping individuals understand who they are, how they should behave, and whether an institution
is legitimate (Lieske 2012; Wildavsky 1987). Recent research expands upon state political culture by integrat-
ing a state’s political and philanthropic culture with the state’s nonprot regulatory regime to help explain
the state’s nonprot culture, or the behaviors, values, and norms that dene how government and nonprots
interact (Pettijohn and Boris (2017).
Sarah L. Pettijohn
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To determine a state’s nonprot culture, Pettijohn and Boris (2017) use Lieske’s (2010) model of social and
political culture within states, which considers race and ethnic ancestry, religious preferences, and social struc-
tures,1and include variables to measure the political ideology of the state,2state-level regulation of its nonprot
sector,3the state government’s scal environment,4and the size of the nonprot sector.5The analysis identi-
ed three distinct state nonprot cultures in the U.S, which can be discussed by adapting Young’s (2000) work
on understanding the government-nonprot relationship. Pettijohn and Boris (2017) found that within a state,
nonprots operate in ways that complement, supplement, or behave independently from state government.
Nonprots operating in a complementary state nonprot culture appear to work with government to provide
services. While this is the culture of the fewest number of states, these states have a signicant nonprot pres-
ence in terms of revenues and assets. State governments in this group, spend signicantly more on education,
welfare, and public safety compared to states in the other two culture groups, rely on the federal government
for smaller portions of their state budgets, and require individuals to pay a higher percentage of their income
in state taxes. These states also tend to elect more Democrats and are more regulated than states in the other
two culture groups.
The second state nonprot culture is one where government and nonprots appear to supplement each other,
or as Young articulates, “nonprots are seen as fullling a demand for public goods left unsatised by govern-
ment”(1999, 33). Here, Pettijohn and Boris (2017) nd the supplemental state nonprot culture consists of
states that are relatively healthy, scally speaking, with government spending on education, welfare, and pub-
lic safety no dierent from the other two state nonprot culture groups. However, states with the supplemental
state nonprot culture have signicantly more nonprots per capita than states with an individual state non-
prot culture. Since the number of nonprots per resident is larger than in other states, individuals have more
options to exercise choices for association and services that reect their individual values.
In the nal state nonprot culture, nonprots appear to operate independent of government. It is on the
opposite end of the spectrum from the complementary state nonprot culture. These states have the fewest
nonprots and nonprot dollars per resident even though nonprots operate with fewer regulations compared
to those in both the complementary and supplementary culture states. Independent nonprot culture states
tend to receive a larger percentage of their state budgets from the federal government, but they spend less on
education and welfare, while having the healthiest scal conditions. These states have individuals contributing
larger amounts of funding to nonprots (based on average itemized contributions), which may indicate the
relationship is between individuals and nonprots with minimum government involvement. Finally, the model
reveals a higher percentage of individuals voted for Trump and more Republicans holding statewide elected
oices. Table 1 lists the three state nonprot cultures and the states that belong to each.
Table 1: State nonprot culture.
Complementary Supplementary Independent
Connecticut Alaska Alabama
Illinois California Arizona
Maryland Colorado Arkansas
Massachusetts Delaware Florida
Michigan Georgia Idaho
Minnesota Hawaii Kansas
Nebraska Indiana Kentucky
New Hampshire Iowa Louisiana
New York Maine Mississippi
North Dakota Missouri Nevada
Pennsylvania Montana New Mexico
Rhode Island New Jersey Oklahoma
Washington North Carolina Oregon
Ohio South Carolina
South Dakota Tennessee
Vermont Texas
Virginia Utah
Wisconsin West Virginia
Wyoming
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2 Government Funding of Nonprofit Organizations
Government funding accounts for nearly one-third of the total nonprot sector’s revenue (McKeever, Dietz,
and Fye 2016), but it often comes with requirements that force or strongly encourage nonprots to alter their
behavior and operations. These demands may aect the health of nonprot organizations receiving govern-
ment funding. Prior research has extensively studied the impact government funding has on nonprots in the
following areas: governance (Guo 2007; Peterson 1970; Piven and Cloward 1971; Smith and Lipsky 1993), volun-
teers (Nowland-Foreman 2002; Ebaugh, Chaftez, and Pipes 2005; Smith and Lipsky 1993; Van Til 1988), mission
(Rangan 2004; Pettijohn and Boris 2013), political activity (e. g. Chaves, Stephens, and Galaskiewicz 2004), ad-
vocacy (e. g. Mosley 2012; Neumayr, Schneider, and Meyer 2015; Salamon 1987), loss of autonomy (Grojnberg
1993), administrative eiciency (Frumkin and Kim 2002; Grojnberg 1993), and strategic decision-making (Ver-
schuere and De Corte 2014). This paper, however, approaches the government-nonprot relationship from a
dierent perspective. Instead of focusing on the impact government funding has on nonprots, it focuses on
whether there are measurable dierences in the government-nonprot relationship among the three types of
state nonprot culture. Specically, the paper examines the relationship related to the level of nancial risk (as-
sumed in dierent types of contracts with government agencies) or dierences in problems nonprots report
on securing, managing, and reporting on government funds, which may impact the health of the nonprot
sector.
2.1 Implementation of Formal Government-Nonprofit Funding Relationships
First, we examine the formal government-nonprot funding relationship by assessing the types of contracts
used to execute the terms and conditions of government funding for nonprots in dierent state-nonprot
cultures. Contract type determines who accepts the nancial risk should actual costs of the goods/services
procured exceed the expected costs. The Federal Acquisition Regulation Systems (FAR) discusses two broad
contract types: rm-xed price and cost-reimbursement and notes that rm-xed price contracts are govern-
ments preferred contract type (48 C. F. R.). FAR requires federal agencies to use rm-xed-price contracts “in
which the contractor [nonprot] has full responsibility for the performance costs and resulting prot (or loss)”
(48 C. F. R. § 16.101b). Firm-xed price contracts require the least amount of interaction between the govern-
ment and its contractor because the terms and conditions of the contract are set in advance, require signicantly
less oversight than other contract types, and protect the government from paying additional costs (48 C. F. R.
§ 16; U.S. Government Accountability Oice (GAO) 2009). This allows government to shift the nancial risk of
the contracted work to the nonprot, which then bears the nancial burden should unexpected or higher than
expected costs arise. While a longer-term relationship may mitigate some of the risk of a rm-xed price con-
tract, broader issues regarding supply and demand and ination in the general economy still pose a nancial
risk to nonprot organizations operating under rm-xed price contracts. Since nonprots operating in the
supplemental state nonprot culture are providing services when government is unwilling or unable to do so,
we hypothesize:
H1: Nonprots operating in supplementary culture state are more likely to report rm-xed price con-
tracts, with government shifting the nancial risk to the nonprot.
Cost-reimbursement contracts are in direct contrast to rm-xed price contracts. FAR only permits the use of
this type of contract when the agency has determined a rm-xed price contract is inadequate for the goods or
services in question (48 C. F. R. § 16.3). Agencies are advised that cost-reimbursement contracts are “considered
high risk for the government because of the potential for cost escalation and because the government pays a
contractor’s costs of performance regardless of whether the work is completed”(U.S. Government Account-
ability Oice (GAO) 2009, p. 1). It also costs the government more to use cost reimbursement contracts because
these contracts require more monitoring and oversight (U.S. Government Accountability Oice (GAO) 2009)
because government assumes the nancial risk should the cost of services exceed the contracted amount. When
government and nonprots operate independently of each other, we expect nonprots may not be willing to
accept the nancial risk of providing government services, and thus, we hypothesize:
H2: Nonprots operating in independent culture states are more likely to report cost reimbursement
contracts, which means government retains the nancial risk.
The government can also use various incentive contracts with both rm-xed price and cost reimbursable con-
tracts to motivate the contractor to perform tasks that are hard to dene and specify, and/or when government
wants to discourage contractor ineiciency or waste (48 C. F. R. § 16.4). These performance-based contracts
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spilt the risk more evenly between the government and nonprot and often require more interaction between
government and nonprot oicials to negotiate and agree on performance targets. Thus, nonprots partnering
with government to provide services in these types of contracts may be more likely to share the nancial risk
more equally, so we hypothesize:
H3: Nonprots operating in complementary culture states are more likely to report performance-based
price contracts.
Finally, some contracts require nonprots to cost share or match a portion of the costs incurred by the govern-
ment for the services. Cost sharing or matching requirements impose nancial burdens on nonprots as they
“potentially limit the sector’s ability to eectively partner with the federal government, can lead to nonprots
providing fewer or lower-quality federal services, and, over the long term, could risk the viability of the sector”
(U.S. Government Accountability Oice (GAO) 2010, p. 22). Nonprots with these requirements must dedicate
existing resources or incur fundraising costs to match government support, but, in a complementary culture,
there is likely to be an alignment of goals between the nonprots and government partners leading to a will-
ingness of the nonprot to raise the additional resources that enable it to provide the services. As a result, we
hypothesize:
H4: Nonprots operating in complementary culture states are more likely to report sharing or matching
requirements.
2.2 Problems and Feedback: the Nonprofit Perspective
While government funding of nonprots continues to increase, the relationship is not without problems, and
the problems nonprots report threaten the health of the nonprot sector. Nonprots often face obstacles at
many points in securing, managing, and reporting on government funds. Following the great recession of 2008,
a national random survey of human service nonprot organizations revealed the scope of problems that non-
prots endured (Boris et al. 2010). Many nonprot leaders reported that government failed to reimburse their
organizations within the allotted time frame outlined in the contract, made changes to the contract or grant
after it was executed, and failed to cover the full cost of services provided (Boris et al. 2010; Pettijohn and Boris
2013). These problems forced nonprots to take out loans, use existing credit to ensure payrolls were met, and
cut employee benets and hours, in their eorts to provide services and retain employees (Boris et al. 2010).
The problems nonprots report in their work with government agencies begins before funding is awarded
and continue after the contract is completed. Nonprots report they are burdened by overly complicated ap-
plication and reporting requirements (Boris et al. 2010; 2013). Inconsistencies in denitions related to allowable
and unallowable and direct and indirect costs among local, state, and federal governments further exacerbate
the problems nonprots face and add more layers of complexity and costs of application and compliance in the
government funding processes (U.S. Government Accountability Oice (GAO) 2010).
Ideally, when such problems arise, government and nonprots would have open feedback loops that allow
both parties to communicate eectively and work together to resolve problems. Nonprots, however, may be
hesitant to notify government oicials of their problems and frustrations out of fear of losing their government
funding. To speak up, nonprots may have to feel as though they are equal partners and have a trusting rela-
tionship with their government funders. Firm-xed price contracts provide clearer terms and conditions which
leavelittle room for misinterpretation. Cost reimbursement and performance-based contracts are, by denition,
more ambiguous and only used when the requirements are uncertain, which could create more problems and
therefore, more opportunity for feedback. Since the relationship between problems in the contracting processes
and state nonprot culture are not evident, we hypothesize:
H5: Nonprots working in dierent nonprot culture states will experience problems with government
funders dierently.
H6: Nonprots operating in dierent nonprot culture states will not provide feedback at the same rates.
3 Data, Variables, and Methods
This analysis uses data from the Urban Institute’s 2013 Nonprot-Government Contracting and Grants survey,
which asks nonprot leaders about their relationships with government in 2012. The national, randomlydrawn
sample of 20,000 nonprots organization consisted of 80,098 501(c)(3) nonprot organizations in the Urban
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Institute’s National Center for Charitable Statistics (NCCS) database. The sample was limited to those nonprots
required to le an annual nancial statement (Form 990) with the U.S. Internal Review Service and reported
more than $100,000 in expenditures. The study does not include hospitals or higher education institutions as
well as nonprots not likely to have government contracts and grants. To ensure a representative sample, prior
to selection, organizations were stratied by state, type of nonprot, and size of nonprot. Smaller states were
oversampled to ensure adequate sample sizes for state-level analysis.
The nal response rate was 33 % with 4,024 organizations responding (see Pettijohn and Boris 2013 for more
information). This analysis focuses on the responses from 2,611 nonprots reporting government funding.6
These survey data are merged with core data from NCCS for 2012, which provided nancial information about
the organizations, and with Pettijohn and Boris (2017) classication of states according to their state nonprot
culture.
Table 2 outlines the dependent and independent variables used in the analysis. To isolate the impact of
state culture on government-nonprot relations, a number of variables are included in the analysis. Here, we
control for funder characteristics (level of government the nonprot receives funding from, number of agencies
the nonprot receives funding from, and number of contracts or grants) and organizational characteristics (size
based on organization’s expenses and type of nonprot based on National Taxonomy of Exempt Entities (NTEE)
code).
Table 2: Key variable description.
Category Variable Description
Dependent
variables
Contract type
Firm-xed Binomial indicator; a nonprot received a rm-xed price contract (1=
yes; 0=no)
Cost reimbursement Binomial indicator; a nonprot received a cost-reimbursement
contract (1= yes; 0=no)
Performance Binomial indicator; a nonprot received a performance-based contract
(1= yes; 0=no)
Cost sharing Binomial indicator; a nonprot is required to share cost or match
government funding (1= yes; 0=no)
Nonprot experience with
government
Late payment Ordinal variable; nonprot’s experience with late payments (beyond
contract specications) was 0=not a problem, 1= small problem, 2=big
problem
Insuicient payments Ordinal variable; nonprot’s experience with payments not covering
full cost of contracted services was 0=not a problem, 1= small
problem, 2=big problem
Application process Ordinal variable; nonprot’s experience with complexity of/time
required by application process was 0=not a problem, 1= small
problem, 2=big problem
Contract changes Ordinal variable; nonprot’s experience with government changes to
contract or grant midstream was 0=not a problem, 1= small problem,
2=big problem
Reporting process Ordinal variable; nonprot’s experience with complexity of/time
required for reporting was 0=not a problem, 1= small problem, 2=big
problem
Provided feedback Binomial indicator; a nonprot provided feedback to government (1=
yes; 0=no)
Independent
variables
State nonprot culture
Complementary Binomial indicator; a nonprot is located in complementary culture
state (1= yes; 0=no)
Supplementary Binomial indicator; a nonprot is located in supplementary culture
state (1= yes; 0=no)
Independent Binomial indicator; a nonprot is located in independent culture state
(1= yes; 0=no)
The non-linear, binary nature of the rst four dependent variables indicates a logit model is the most appro-
priate approach to test the rst four hypotheses (Gujarati and Porter 2009). For the remaining two hypotheses,
where the dependent variable is non-continuous but ordered, ordered logit is the most appropriate statisti-
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cal test (Gujarati and Porter 2009). The results report odds ratios and robust standard errors. All analyses are
weighted to represent the nonprot sector with government funding within each state (except as noted).
4 Descriptive Statistics
We begin by examining the size and scope of the funding relationships between nonprots and governments.
We nd, on average, nonprots in a complementary culture state received more government funding, both in
terms of the average number of agreements and dollars, than those in an independent culture state (Table 3). As
Salamon (1995) notes, the complementary view often involves government nancing services that are delivered
by nonprots. These nonprots also received grants from more government agencies than other states.
Table 3: Size and scope of government-nonprot relationship by state nonprot culture.
Complementary Supplementary Independent
Average number of nonprots 37,064 34,496 24,491
Average nonprot assets (million) $185,354 $103,453 $59,004
Average number of contracts and grants 1,591 1,168 698
Average dollar value of contracts and grants (million) $4,471 $2,929 $1,304
We nd that while the scal condition of the states with independent cultures are healthier than states with
complementary state cultures, the nonprot sectors in the independent state culture group tend to be weaker.
That is, states in the independent state culture group not only had signicantly smaller nonprot sectors per
capita, but also nonprots with government funding were more likely to report a decit at the end of 2012.
Nonprots operating in independent culture states were also signicantly more likely to cut health insurance,
retirement, and other sta benets for their employees, and they were more likely to take out loans or lines
of credit than nonprots in states that complemented or supplemented government services. This suggests
an inverse relationship between the scal conditions of state government and nonprots in the state. It also
suggests the importance of government funding for the health of nonprots since higher average contributions
did not compensate for lower levels of government funding. Table 4 includes descriptive statistics for the percent
of respondents receiving government funding from each level of government by state nonprot culture.
Table 4: Percent of nonprots reporting level of government funding by state nonprot culture.
Complementary Supplementary Independent Total
Local only 2.9 3.9 2.9 9.7
State only 6.2 6.4 6.2 18.8
Federal only 3.1 3.6 4.8 11.5
Local and state (no federal) 5.5 5.9 4.9 16.3
Local and federal (no state) 1.5 2.1 1.7 5.3
State and federal (no local) 4.3 6.3 6.7 17.3
Local, state, and federal (all levels) 7.4 7.6 6.1 21.1
Total 30.8 35.8 33.3 100.0
1Notes: Subtotals may not sum to totals because of rounding.
The results for the size and scope of the government-nonprot relationship are as one might expect. That is,
when we consider the driving factors that determine which state culture a state falls into, we see an overlap of
characteristics in state nonprot culture categories and the size and scope of the government-nonprot funding
relationship. For example, we expect nonprots in complementary culture states to partner with government to
provide services. We also expect nonprots in supplementary culture states to have less funding, since govern-
ment is providing services at a level the average citizen desires, which may not fully satisfy some citizens who
turn to nonprots to ll their needs. Finally, nonprots in independent culture states receive less government
funding, which reinforces the nding that in these states nonprots and government are more independent of
each other.
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5 Analytic Results and Discussion
While the results for the six hypotheses are mixed, there are measureable dierences in the government-
nonprot funding relationship among state nonprot cultures (Table 5). Nonprots operating in the inde-
pendent culture states were signicantly more likely to report a cost reimbursement contract, but they were
also more likely to report a cost sharing or matching requirement. As for experiencing problems with govern-
ment agencies, nonprots in independent culture states were signicantly less likely to report problems secur-
ing, managing, and reporting on government funding than their counterparts. These ndings are discussed in
greater detail below.
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Table 5: Logistic regression implementation of formal government nonprot relationships.
Model 1: Model 2: Model 3: Model 4:
Firm-xed Cost reimbursement Performance Cost Sharing
Odds Ratio Robust
Standard Error
Odds Ratio Robust
Standard Error
Odds Ratio Robust
Standard Error
Odds Ratio Robust
Standard Error
State Nonprot Culture
Complimentary 1.142 0.148 0.770+ 0.105 1.165 0.202 0.766* 0.104
Supplementary 1.181 0.153 0.775+ 0.109 0.971 0.175 0.959 0.131
Level of Government Funding
Local only 0.769 0.169 0.306*** 0.077 0.524* 0.147 0.145*** 0.040
State only 0.453*** 0.085 0.490** 0.106 0.475** 0.117 0.265*** 0.056
Federal only 0.436*** 0.093 0.454** 0.110 0.309*** 0.100 0.295*** 0.070
Local and state (no federal) 0.785 0.151 0.673* 0.134 0.799 0.175 0.428*** 0.023
Local and federal (no state) 0.761 0.194 1.485 0.426 0.480* 0.152 0.456*** 0.116
State and federal (no local) 0.494*** 0.089 1.409 0.299 0.733 0.160 0.625*** 0.119
Number of Government
Funding Agencies
1.031 0.025 1.086+ 0.048 1.045+ 0.024 1.046 0.032
Number of Government
Contracts/Grants
1.007 0.007 1.038+ 0.021 1.005 0.006 1.020 0.021
Expense Size
$250,000 to $999,999 1.133 0.018 1.284 0.213 1.484+ 0.335 1.104 0.177
$1 million or more 1.080 0.176 1.268 0.219 1.196 0.275 1.290 0.217
Organizational Type (NTEE
Category)
Arts, culture, and humanities 1.425*** 0.770 0.444** 0.109 0.857** 0.254 1.937** 0.430
Education 1.914 0.434 0.879+ 0.299 1.034 0.464 0.779 0.256
Environment and animals 1.702* 0.619 0.878** 0.291 1.032 0.437 1.405 0.465
Health 1.544* 0.404 0.663 0.175 0.924 0.293 0.516* 0.135
Human Services 1.398+ 0.252 0.898+ 0.190 1.014 0.241 0.791 0.149
Observations 2,190 2,190 2,190 2,168
Prob > chi2 0.000 0.000 0.000 0.000
Pseudo R20.093 0.112 0.158 0.110
+p<.10 *p<.05 **p<.01 ***p<.001
Notes: Excluded categories include independent culture; funding from all levels of government; small organizations with a $100,000 to $249,000
expense size; and ”Other” types of nonprots.
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5.1 Implementation of Formal Government-Nonprofit Funding Relationships
When examining the types of contracts government uses to award nonprots funds, only cost reimbursement
contracts gained signicance in the analysis. Table 5 shows that while the dierences among culture moved in
the direction expected, the other relationships were not signicant, so there is no support for hypotheses one
(xed contracts) and three (performance contracts).
We expected complementary culture states to report more cost sharing or matching requirements, which
was partially supported by the analysis. That is, nonprots in complementary culture states are signicantly
more likely to report a cost-sharing requirement than their counterparts in independent culture states, but there
is no dierence in the likelihood of nonprots in complimentary culture states reporting more cost sharing re-
quirements than nonprots in supplementary culture states. Yet, overall, the relationships we nd between
nonprots and government via contract type align with what we expected for each group. That is, we see in
complementary culture states, nonprots work with government to share the nancial risk of the relationship
as well as the cost of providing services to clients, and in the independent culture group, contract types re-
quire the government to assume the risks for services it seeks nonprots to deliver. However, nonprots in
supplementary culture states are no more likely to use a rm-xed price contract.
5.2 Reported Problems by Nonprofits
All types and sizes of nonprots reported some level of diiculty with the ve problem areas explored in the
survey. However, nonprots in the supplementary culture states were more likely to report signicant problems
in three of the ve areas (Table 6) compared to respondents in independent culture states. These nonprots
reported late payments for services rendered, awards not covering the full cost of services, and time-consuming
application requirements were more problematic than nonprots operating in the independent culture states.
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Table 6: Ordered logistic regression problems and feedback.
Model 5: Model 6: Model 7: Model 8: Model 9: Model 10:
Late payment Insuicient payments Application process Contract changes Reporting process Feedback
OddsRatio Robust
Standard
Error
OddsRatio Robust
Standard
Error
OddsRatio Robust
Standard
Error
OddsRatio Robust
Standard
Error
OddsRatio Robust
Standard
Error
OddsRatio Robust
Standard
Error
State Nonprot Culture
Complimentary 1.861*** 0.254 1.268 0.184 1.138 0.145 1.259 0.196 1.286* 0.161 1.084 0.121
Supplementary 1.512** 0.210 1.267+ 0.180 1.253+ 0.163 1.173 0.185 1.242 0.165 1.135 0.127
Level of Government
Funding
Local only 0.535** 0.127 0.822 0.185 0.432*** 0.094 0.746 0.204 0.458*** 0.099 0.558** 0.095
State only 0.634* 0.121 0.716+ 0.134 0.430*** 0.075 0.813 0.167 0.490*** 0.089 0.557*** 0.094
Federal only 0.222** 0.060 0.236*** 0.062 0.375*** 0.080 0.490** 0.124 0.392*** 0.084 0.344*** 0.059
Local and state (no
federal)
0.892 0.159 1.053 0.206 0.941 0.163 1.415+ 0.276 0.897 0.144 0.761+ 0.111
Local and federal (no
state)
0.862 0.215 0.806 0.192 0.938 0.232 1.047 0.324 0.864 0.215 0.900 0.190
State and federal (no
local)
0.759 0.134 0.581** 0.102 0.572*** 0.090 0.809 0.147 0.590** 0.097 0.633** 0.102
Number of Government
Funding Partners
1.008 0.014 1.006 0.023 1.000 0.015 0.989 0.013 1.021 0.025 1.006 0.016
Number of Government
Contracts/Grants
1.011* 0.006 1.020* 0.009 1.012+ 0.007 1.019* 0.008 1.018+ 0.011 1.014** 0.007
Expense Size
$250,000 to $999,999 1.102 0.221 1.115 0.238 1.184 0.186 1.250 0.261 1.068 0.171 0.958 0.122
$1 million or more 0.965 0.187 1.195 0.248 1.108 0.177 1.327 0.274 1.382* 0.225 1.461** 0.201
Organizational Type
(NTEE Category)
Arts, culture, and
humanities
0.506* 0.141 0.377** 0.107 0.901 0.184 0.436** 0.118 0.628* 0.132 0.527** 0.102
Education 0.630 0.258 0.676 0.217 1.165 0.334 0.612 0.251 1.135 0.355 0.861 0.281
Environment and animals 0.515 0.229 0.249*** 0.097 0.577 0.195 0.142** 0.083 0.322*** 0.104 0.506** 0.130
Health 1.334 0.368 1.628+ 0.421 1.501 0.355 1.302 0.354 1.220 0.285 1.174 0.252
Human Services 1.028 0.239 0.799 0.173 1.038 0.178 0.963 0.207 0.909 0.169 1.170 0.205
Observations 1,678 1,565 1,862 1,482 1,885 2,149
Prob > chi2 0.000 0.000 0.000 0.000 0.016 0.000
Pseudo R20.123 0.120 0.071 0.126 0.079 0.138
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+p<.10 *p<.05 **p<.01 ***p<.001
Notes: Excluded categories include independent culture; funding from all levels of government; small organizations with a $100,000 to $249,000
expense size; and ”Other” types of nonprots.
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Nonprots in complementary states reported signicant problems related to late payments and complex
reporting requirements. Additionally, complementary states were more likely to report the government still
owed them money. These organizations reported that state government was the biggest oender for outstanding
payments. This nding should be interpreted with caution, however. Recall that the scal conditions of state
governments in the complementary group are the weakest of the three groups, so more research is necessary
to explore the relationship between late payments and poor scal health at the state level.
As previously mentioned, nonprots in complementary states were more likely to say that reporting re-
quirements were time-consuming. This is, in large part, due to more frequent and more demanding reporting
requirements. Nonprots in the complementary states were more likely to be required to submit a narrative
report of program accomplishments and surveys of clients on satisfaction with services received. These reports
are more complex and time-consuming than data on individuals served or units of services provided, which
were more likely required of nonprots in the supplemental culture states.
Finally, many nonprots note challenges when government agencies have dierent reporting requirements
from nonprots. Once again, we see nonprots in complementary state cultures were more likely to report their
denitions did not align with government agencies in terms of services, budget categories, reporting formats,
allowances for administrative or overhead expenses, and outcome reporting requirements compared to their
counterparts operating in the supplemental culture group. More research should examine why nonprots in
the independent culture states are more likely to have similar reporting requirements compared to those in
complementary culture states, which may be a function of the contract types used in these state cultures.
The last area analyzed in the government-nonprot relationship centered on feedback nonprots provided
to government about funding issues and/or procedures. Here, we nd no signicant dierences in feedback
provided by nonprots in dierent state nonprot cultures. Nonprots in the complementary environment
provided feedback through indirect advocacy (e. g. ailiated organizations or coalitions). Additionally, these
nonprots were also more likely to contact contracts or grants ombudsmen. Further research should explore
whether these organizations provided feedback and contacted ombudsmen because these organizations had
more problems, and thus, saw feedback as avenue for resolving the issue or if it indicates the organizations felt
they could provide feedback without endangering their government funding.
6 Conclusion
This paper expands research on the government-nonprot relationship by testing three distinct nonprot cul-
tures among the 50 states. There are signicant dierences in government-nonprot funding relationships in
the complementary, supplementary and independent state cultures, which means nonprots operating in cer-
tain state nonprot cultures face dierent types and degrees of risk to their organization’s overall health. The
strength of the nonprot infrastructure also varies somewhat among the dierent state cultures. Future research
will allow us to probe the implications of these and other aspects of diverse state cultures and will enrich our
understanding of the interactions of nonprots and state governments.
Notes
1 Indicators for social structures measure the dierence in “socioeconomic development, population size, urbanization, education, occu-
pational status, family structure, social mobility, age distribution, racial diversity, and income inequality”(Lieske 2010, 541).
2 To control for political ideology, Pettijohn and Boris (2017) considered the percent of individuals in the state who voted for President
Trump and the number of statewide elected oicials that are members of the Republican Party.
3 This variable includes data registration, notice, and ling requirements for charities and fundraisers, location of state regulatory and
enforcement powers, and deductibility of charitable contributions on state income taxes (see Lott et al. 2016 for more information).
4 This includes scal solvency, revenue sources, and welfare and social service spending.
5 This includes number of nonprots, revenue, and assets per capita and individual giving to nonprots.
6 The types and sizes of organizations that participated in the study were similar to the organizations that did not participate. Hence, the
potential of nonresponse bias for this study is rather small.
References
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