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Government monitors, regulates, and funds nonprofit organizations, making it is a key player in the health of the nonprofit sector in the United States. However, not all states treat nonprofits similarly. Prior work identified three types of state nonprofit culture (Pettijohn, S. L., and E. T. Boris. 2017. State Nonprofit Culture: Assessing the Impact of State Regulation on the Government-Nonprofit Relationship . Grand Rapids, MI: ARNOVA Presentation.), or a unique set of attitudes and beliefs that shape the operating norms between state government and nonprofits. This article analyzes whether differences among state nonprofit culture are measureable in the government-nonprofit relationship. Using data from the Urban Institute’s 2013 Nonprofit-Government Contracting and Grants survey, we find there are significant differences in the government-nonprofit funding relationships, which means nonprofits operating in certain state nonprofit cultures face different types and degrees of risk to their organization’s overall health.
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          
DE GRUYTER     
Sarah L. Pettijohn1/ Elizabeth T. Boris2
Testing Nonprofit State Culture: Its Impact on the
Health of the Nonprofit Sector
                
  
                
Government monitors, regulates, and funds nonprot organizations, making it is a key player in the health of
the nonprot sector in the United States. However, not all states treat nonprots similarly. Prior work identi-
ed three types of state nonprot culture (Pettijohn, S. L., and E. T. Boris. 2017. State Nonprot Culture: Assessing
the Impact of State Regulation on the Government-Nonprot Relationship. Grand Rapids, MI: ARNOVA Presenta-
tion.), or a unique set of attitudes and beliefs that shape the operating norms between state government and
nonprots. This article analyzes whether dierences among state nonprot culture are measureable in the
government-nonprot relationship. Using data from the Urban Institutes 2013 Nonprot-Government Con-
tracting and Grants survey, we nd there are signicant dierences in the government-nonprot funding rela-
tionships, which means nonprots operating in certain state nonprot cultures face dierent types and degrees
of risk to their organizations overall health.
Keywords: nonprot government relations, state government, nonprot regulation
DOI: 10.1515/npf-2018-0012
Government is a key player in the health of the nonprot sector in the United States. Not only do local, state,
and federal governments account for more than one-third of the sectors total revenue (McKeever, Dietz, and
Fye 2016), they also regulate and monitor nonprot activity, all of which profoundly impacts the health of
the nonprot sector. The relationship between nonprots 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 states role in regulating nonprots. Lott and Fremont-Smith
nd, State governments have a direct impact on nonprot 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 nonprots operating within its
boundaries. This means a nonprot operating in one state may have more complex requirements, enjoy greater
support or face more opposition from its state government compared to a nonprot operating in another state.
Recent work identied three types of state nonprot cultures that describe the relationship between govern-
ment and nonprots at the state level. In this paper, we explore whether there are signicant dierences for
nonprots that operate in these three dierent state nonprot cultures. Specically, the paper examines dif-
ferences between state nonprot culture and the level of nancial risk (assumed in dierent types of contracts
with government agencies) or dierences in problems nonprots report on securing, managing, and reporting
on government funds. We begin by discussing the three types of state nonprot cultures and the government-
nonprot 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 states political culture, or its system of shared values that legitimate a preferred
set of social relationships(Lieske 2012, 110111). A states 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 states political and philanthropic culture with the states nonprot regulatory regime to help explain
the states nonprot culture, or the behaviors, values, and norms that dene how government and nonprots
interact (Pettijohn and Boris (2017).
Sarah L. Pettijohn    
     
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   DE GRUYTER
To determine a states nonprot culture, Pettijohn and Boris (2017) use Lieskes (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 nonprot
sector,3the state governments scal environment,4and the size of the nonprot sector.5The analysis identi-
ed three distinct state nonprot cultures in the U.S, which can be discussed by adapting Youngs (2000) work
on understanding the government-nonprot relationship. Pettijohn and Boris (2017) found that within a state,
nonprots operate in ways that complement, supplement, or behave independently from state government.
Nonprots operating in a complementary state nonprot culture appear to work with government to provide
services. While this is the culture of the fewest number of states, these states have a signicant nonprot pres-
ence in terms of revenues and assets. State governments in this group, spend signicantly 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 nonprot culture is one where government and nonprots appear to supplement each other,
or as Young articulates, nonprots are seen as fullling a demand for public goods left unsatised by govern-
ment(1999, 33). Here, Pettijohn and Boris (2017) nd the supplemental state nonprot culture consists of
states that are relatively healthy, scally speaking, with government spending on education, welfare, and pub-
lic safety no dierent from the other two state nonprot culture groups. However, states with the supplemental
state nonprot culture have signicantly more nonprots per capita than states with an individual state non-
prot culture. Since the number of nonprots per resident is larger than in other states, individuals have more
options to exercise choices for association and services that reect their individual values.
In the nal state nonprot culture, nonprots appear to operate independent of government. It is on the
opposite end of the spectrum from the complementary state nonprot culture. These states have the fewest
nonprots and nonprot dollars per resident even though nonprots operate with fewer regulations compared
to those in both the complementary and supplementary culture states. Independent nonprot 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 nonprots (based on average itemized contributions), which may indicate the
relationship is between individuals and nonprots with minimum government involvement. Finally, the model
reveals a higher percentage of individuals voted for Trump and more Republicans holding statewide elected
oices. Table 1 lists the three state nonprot cultures and the states that belong to each.
Table 1: State nonprot 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
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          
DE GRUYTER   
2 Government Funding of Nonprofit Organizations
Government funding accounts for nearly one-third of the total nonprot sectors revenue (McKeever, Dietz,
and Fye 2016), but it often comes with requirements that force or strongly encourage nonprots to alter their
behavior and operations. These demands may aect the health of nonprot organizations receiving govern-
ment funding. Prior research has extensively studied the impact government funding has on nonprots 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 eiciency (Frumkin and Kim 2002; Grojnberg 1993), and strategic decision-making (Ver-
schuere and De Corte 2014). This paper, however, approaches the government-nonprot relationship from a
dierent perspective. Instead of focusing on the impact government funding has on nonprots, it focuses on
whether there are measurable dierences in the government-nonprot relationship among the three types of
state nonprot culture. Specically, the paper examines the relationship related to the level of nancial risk (as-
sumed in dierent types of contracts with government agencies) or dierences in problems nonprots report
on securing, managing, and reporting on government funds, which may impact the health of the nonprot
2.1 Implementation of Formal Government-Nonprofit Funding Relationships
First, we examine the formal government-nonprot funding relationship by assessing the types of contracts
used to execute the terms and conditions of government funding for nonprots in dierent state-nonprot
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 [nonprot] has full responsibility for the performance costs and resulting prot (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 signicantly
less oversight than other contract types, and protect the government from paying additional costs (48 C. F. R.
§16; U.S. Government Accountability Oice (GAO) 2009). This allows government to shift the nancial risk of
the contracted work to the nonprot, 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 ination in the general economy still pose a nancial
risk to nonprot organizations operating under rm-xed price contracts. Since nonprots operating in the
supplemental state nonprot culture are providing services when government is unwilling or unable to do so,
we hypothesize:
H1: Nonprots operating in supplementary culture state are more likely to report rm-xed price con-
tracts, with government shifting the nancial risk to the nonprot.
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
contractors costs of performance regardless of whether the work is completed(U.S. Government Account-
ability Oice (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 Oice (GAO) 2009)
because government assumes the nancial risk should the cost of services exceed the contracted amount. When
government and nonprots operate independently of each other, we expect nonprots may not be willing to
accept the nancial risk of providing government services, and thus, we hypothesize:
H2: Nonprots 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 dene and specify, and/or when government
wants to discourage contractor ineiciency or waste (48 C. F. R. §16.4). These performance-based contracts
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   DE GRUYTER
spilt the risk more evenly between the government and nonprot and often require more interaction between
government and nonprot oicials to negotiate and agree on performance targets. Thus, nonprots 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: Nonprots operating in complementary culture states are more likely to report performance-based
price contracts.
Finally, some contracts require nonprots 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 nonprots as they
potentially limit the sectors ability to eectively partner with the federal government, can lead to nonprots
providing fewer or lower-quality federal services, and, over the long term, could risk the viability of the sector
(U.S. Government Accountability Oice (GAO) 2010, p. 22). Nonprots 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 nonprots and government partners leading to a will-
ingness of the nonprot to raise the additional resources that enable it to provide the services. As a result, we
H4: Nonprots operating in complementary culture states are more likely to report sharing or matching
2.2 Problems and Feedback: the Nonprofit Perspective
While government funding of nonprots continues to increase, the relationship is not without problems, and
the problems nonprots report threaten the health of the nonprot sector. Nonprots 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 nonprot organizations revealed the scope of problems that non-
prots endured (Boris etal. 2010). Many nonprot 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 etal. 2010; Pettijohn and Boris
2013). These problems forced nonprots to take out loans, use existing credit to ensure payrolls were met, and
cut employee benets and hours, in their eorts to provide services and retain employees (Boris etal. 2010).
The problems nonprots report in their work with government agencies begins before funding is awarded
and continue after the contract is completed. Nonprots report they are burdened by overly complicated ap-
plication and reporting requirements (Boris etal. 2010; 2013). Inconsistencies in denitions related to allowable
and unallowable and direct and indirect costs among local, state, and federal governments further exacerbate
the problems nonprots face and add more layers of complexity and costs of application and compliance in the
government funding processes (U.S. Government Accountability Oice (GAO) 2010).
Ideally, when such problems arise, government and nonprots would have open feedback loops that allow
both parties to communicate eectively and work together to resolve problems. Nonprots, however, may be
hesitant to notify government oicials of their problems and frustrations out of fear of losing their government
funding. To speak up, nonprots 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 denition,
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 nonprot culture are not evident, we hypothesize:
H5: Nonprots working in dierent nonprot culture states will experience problems with government
funders dierently.
H6: Nonprots operating in dierent nonprot culture states will not provide feedback at the same rates.
3 Data, Variables, and Methods
This analysis uses data from the Urban Institutes 2013 Nonprot-Government Contracting and Grants survey,
which asks nonprot leaders about their relationships with government in 2012. The national, randomlydrawn
sample of 20,000 nonprots organization consisted of 80,098 501(c)(3) nonprot organizations in the Urban
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          
DE GRUYTER   
Institutes National Center for Charitable Statistics (NCCS) database. The sample was limited to those nonprots
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 nonprots not likely to have government contracts and grants. To ensure a representative sample, prior
to selection, organizations were stratied by state, type of nonprot, and size of nonprot. 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 nonprots 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) classication of states according to their state nonprot
Table 2 outlines the dependent and independent variables used in the analysis. To isolate the impact of
state culture on government-nonprot relations, a number of variables are included in the analysis. Here, we
control for funder characteristics (level of government the nonprot receives funding from, number of agencies
the nonprot receives funding from, and number of contracts or grants) and organizational characteristics (size
based on organizations expenses and type of nonprot based on National Taxonomy of Exempt Entities (NTEE)
Table 2: Key variable description.
Category Variable Description
Contract type
Firm-xed Binomial indicator; a nonprot received a rm-xed price contract (1=
yes; 0=no)
Cost reimbursement Binomial indicator; a nonprot received a cost-reimbursement
contract (1= yes; 0=no)
Performance Binomial indicator; a nonprot received a performance-based contract
(1= yes; 0=no)
Cost sharing Binomial indicator; a nonprot is required to share cost or match
government funding (1= yes; 0=no)
Nonprot experience with
Late payment Ordinal variable; nonprots experience with late payments (beyond
contract specications) was 0=not a problem, 1= small problem, 2=big
Insuicient payments Ordinal variable; nonprots 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; nonprots experience with complexity of/time
required by application process was 0=not a problem, 1= small
problem, 2=big problem
Contract changes Ordinal variable; nonprots experience with government changes to
contract or grant midstream was 0=not a problem, 1= small problem,
2=big problem
Reporting process Ordinal variable; nonprots experience with complexity of/time
required for reporting was 0=not a problem, 1= small problem, 2=big
Provided feedback Binomial indicator; a nonprot provided feedback to government (1=
yes; 0=no)
State nonprot culture
Complementary Binomial indicator; a nonprot is located in complementary culture
state (1= yes; 0=no)
Supplementary Binomial indicator; a nonprot is located in supplementary culture
state (1= yes; 0=no)
Independent Binomial indicator; a nonprot 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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          
   DE GRUYTER
cal test (Gujarati and Porter 2009). The results report odds ratios and robust standard errors. All analyses are
weighted to represent the nonprot 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 nonprots and governments.
We nd, on average, nonprots 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 nonprots. These nonprots also received grants from more government agencies than other states.
Table 3: Size and scope of government-nonprot relationship by state nonprot culture.
Complementary Supplementary Independent
Average number of nonprots 37,064 34,496 24,491
Average nonprot 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 nonprot sectors in the independent state culture group tend to be weaker.
That is, states in the independent state culture group not only had signicantly smaller nonprot sectors per
capita, but also nonprots with government funding were more likely to report a decit at the end of 2012.
Nonprots operating in independent culture states were also signicantly more likely to cut health insurance,
retirement, and other sta benets for their employees, and they were more likely to take out loans or lines
of credit than nonprots in states that complemented or supplemented government services. This suggests
an inverse relationship between the scal conditions of state government and nonprots in the state. It also
suggests the importance of government funding for the health of nonprots 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 nonprot culture.
Table 4: Percent of nonprots reporting level of government funding by state nonprot 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-nonprot 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 nonprot culture categories and the size and scope of the government-nonprot funding
relationship. For example, we expect nonprots in complementary culture states to partner with government to
provide services. We also expect nonprots 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 nonprots to ll their needs. Finally, nonprots in independent culture states receive less government
funding, which reinforces the nding that in these states nonprots and government are more independent of
each other.
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          
DE GRUYTER   
5 Analytic Results and Discussion
While the results for the six hypotheses are mixed, there are measureable dierences in the government-
nonprot funding relationship among state nonprot cultures (Table 5). Nonprots operating in the inde-
pendent culture states were signicantly 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, nonprots in independent culture states were signicantly 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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          
   DE GRUYTER
Table 5: Logistic regression implementation of formal government nonprot 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 Nonprot 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
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
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 nonprots.
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          
DE GRUYTER   
5.1 Implementation of Formal Government-Nonprofit Funding Relationships
When examining the types of contracts government uses to award nonprots funds, only cost reimbursement
contracts gained signicance in the analysis. Table 5 shows that while the dierences among culture moved in
the direction expected, the other relationships were not signicant, 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, nonprots in complementary culture states are signicantly
more likely to report a cost-sharing requirement than their counterparts in independent culture states, but there
is no dierence in the likelihood of nonprots in complimentary culture states reporting more cost sharing re-
quirements than nonprots in supplementary culture states. Yet, overall, the relationships we nd between
nonprots and government via contract type align with what we expected for each group. That is, we see in
complementary culture states, nonprots 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 nonprots to deliver. However, nonprots 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 nonprots reported some level of diiculty with the ve problem areas explored in the
survey. However, nonprots in the supplementary culture states were more likely to report signicant problems
in three of the ve areas (Table 6) compared to respondents in independent culture states. These nonprots
reported late payments for services rendered, awards not covering the full cost of services, and time-consuming
application requirements were more problematic than nonprots operating in the independent culture states.
Download Date | 11/4/18 1:36 AM
          
   DE GRUYTER
Table 6: Ordered logistic regression problems and feedback.
Model 5: Model 6: Model 7: Model 8: Model 9: Model 10:
Late payment Insuicient payments Application process Contract changes Reporting process Feedback
OddsRatio Robust
OddsRatio Robust
OddsRatio Robust
OddsRatio Robust
OddsRatio Robust
OddsRatio Robust
State Nonprot 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
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
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
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
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
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
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
10 Unauthenticated
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          
DE GRUYTER   
+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 nonprots.
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          
   DE GRUYTER
Nonprots in complementary states reported signicant 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 oender 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, nonprots 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. Nonprots 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 nonprots in the supplemental culture states.
Finally, many nonprots note challenges when government agencies have dierent reporting requirements
from nonprots. Once again, we see nonprots in complementary state cultures were more likely to report their
denitions 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 nonprots 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-nonprot relationship centered on feedback nonprots provided
to government about funding issues and/or procedures. Here, we nd no signicant dierences in feedback
provided by nonprots in dierent state nonprot cultures. Nonprots in the complementary environment
provided feedback through indirect advocacy (e.g. ailiated organizations or coalitions). Additionally, these
nonprots 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-nonprot relationship by testing three distinct nonprot cul-
tures among the 50 states. There are signicant dierences in government-nonprot funding relationships in
the complementary, supplementary and independent state cultures, which means nonprots operating in cer-
tain state nonprot cultures face dierent types and degrees of risk to their organizations overall health. The
strength of the nonprot infrastructure also varies somewhat among the dierent 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 nonprots and state governments.
1 Indicators for social structures measure the dierence 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 oicials 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 etal. 2016 for more information).
4 This includes scal solvency, revenue sources, and welfare and social service spending.
5 This includes number of nonprots, revenue, and assets per capita and individual giving to nonprots.
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.
                   
               
12 Unauthenticated
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          
DE GRUYTER   
              
   
                     
     
                
   
               
   
               
                 
     
                   
    
                 
                 
               
                         
     
                     
       
                     
    
                   
        
                  
    
             
                  
  
                   
             
                   
    
                  
           
                    
            
            
                      
                
      
                
            
                  
                      
         
            
              
                     
    
             
       
Download Date | 11/4/18 1:36 AM
... Yet, there is little debate and even less agreement on the definition of "a healthy nonprofit sector" or an index to measure how the nonprofit sector is faring. In this special issue alone, a variety of topics are suggested as important for nonprofit sector health, including: equity (Benenson 2018), culture (Pettijohn and Boris 2018), competencies (Castillo 2018), and capacity (Kushner 2018). Although many challenges exist to represent the entire nonprofit sector and track changes over time, doing so would enable policy-makers and the general public to engage on issues affecting nonprofit operations (Abramson, Grayson, and Moore 2018). ...
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Nonprofit social capital refers to the trust, norms, and networks that can improve organizational performance to fulfill a mission. Research on social capital within organizations, and specifically with nonprofits, is relatively widespread; however, the notion that we can quantify, measure, and incentivize its growth across a sector is novel. Nonprofits actively work to solve some of society’s most complex challenges in diverse areas, such as public health, education, social inequality, and environment. Few would argue against the need for a robust and healthy nonprofit sector. Yet, there is little debate and even less agreement on the definition of “a healthy nonprofit sector” or how to measure it. We offer a policy brief on this topic in the form of an exploratory think piece, rather than a definitive empirical methodology or research paper, that connects nonprofit social capital to a framework of sector health. Solving many of the challenges facing society today will require trust, working together, and networks of resources and reciprocity. Because of this, nonprofit social capital – both cognitive and structural – is an important benchmark of nonprofit sector health and could supplement other metrics of an index offering a signal as to changes occurring in the sector.
Standard economic theories of nonprofits argue that donors largely cannot observe nonprofit performance. Using market data from the US nonprofit housing sector, federal financial data, and rare internal production reports, this study examines the effects of nonprofit performance on donations with a dynamic panel model. Donors in our sample are only weakly sensitive to indicators of nonprofit productivity. Our results imply that nonprofit performance theory might be distinct from other sectors in that nonprofits cannot expect increased performance to be meaningfully rewarded with funding.
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Recent events have highlighted the difficulties the Internal Revenue Service faces when attempting to ensure that purportedly tax-exempt organizations in fact qualify for that status. The problems in this area go much deeper than a group of IRS employees subjecting certain organizations to greater scrutiny based on their political leanings, however. For decades members of the public, the media, the academy, and Congress have criticized the limited ability of the IRS to ensure that organizations claiming exemption from federal income tax in fact deserve that categorization. Yet examples of IRS failings in this area continue to arise with depressing frequency. This is not surprising given that oversight of exempt organizations is but one of many areas that suffers from major difficulties faced by the IRS as a whole, including shrinking resources, growing responsibilities, and increasing responsibility for determinations that go beyond those necessary for revenue collection. As detailed in Part I of this Article, these difficulties have rendered the IRS unable to keep pace with the growth of the exempt organizations sector over the past 40 years. One of the latest such initiatives suggests a new approach, however. In 2014 the IRS introduced the much shorter and simpler Form 1023-EZ application for nonprofit organizations that claim exempt charitable status and expect to have only modest financial resources, accompanied by faster procedures for handling all applications for recognition of exemption. These innovations represent the first significant permanent reduction in the level of oversight the IRS provides in this area since the introduction of a shorter version of the annual information return required for most exempt organizations. The questions they raise are whether such a reduction of oversight is in fact prudent, and whether other reductions might also be advisable. Part II of this Article draws on tax compliance literature to explore how the current level and methods of oversight for exempt organizations could be modified to improve compliance even given the existing resource constraints. It concludes that while marginal improvements in oversight are possible, there is no silver bullet to counter the IRS’s growing inability to oversee this area. Part III of this Article therefore turns to more radical proposals that would move the locus of oversight for exempt and particularly charitable organizations out of the IRS. The proposal that shows the most promise, but also is the most risky, would shift much of this role to a private, self-regulatory body overseen by the IRS. The current crisis highlights the need to pursue this proposal now.
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This article aims to contribute to the long-standing discussion about nonprofit organizations’ (NPOs) dependence on public funding and its consequences on their advocacy role in modern societies. Drawing on resource dependence theory and data from a quantitative survey, the study investigates the impact of public funding and its extent on nonprofit engagement in advocacy. Traditionally, scholars have cautioned that NPOs reliant on public sources will hesitate to pursue political objectives and to engage in advocacy work. Yet, empirical findings are strikingly inconsistent. One of the reasons for these ambiguous findings may be the way advocacy is measured. To address this issue, we apply two different approaches to evaluate NPO engagement. Both sets of findings from our multivariate analyses of Austrian NPOs suggest that public funding does not have a negative impact on advocacy.
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Nonprofit-Government Contracting and Grants, a study of human service organizations designed to document the extent of nonprofit-government contracting, processes and problems. It also examines the impact of the recession on these organizations and the cutbacks they have made to keep their programs operating. While contracting problems are not new, many are exacerbated by the deep recession that has reduced government budgets and private contributions. Nearly 33,000 human service nonprofits have government contracts and grants, and 9,000 organizations with expenditures over 100,000 were surveyed for this study.
Private nonprofit organizations (NPO) involved in publically funded welfare programs face the challenge of maintaining autonomy in their strategic decision-making processes. In this article we study the extent to which NPO managers perceive this autonomy vis-à-vis government in defining the NPO's mission, their working procedures, the target groups to be served and the results to be achieved. Empirical evidence is taken from a large-N sample of 255 NPOs engaged in social welfare provision in Belgium. Our findings suggest that public resource dependence does have a negative impact on the perception of NPOs about the level of organizational autonomy. Still, we will argue that, when looking at the relative share of public income in the NPO's total budget, the nature and intensity of the consultation process between government and NPO and some measures of organizational capacity, this picture is less black and white than presumed.
Debate over representation has been a continuing part of the Western political tradition at least since the writings of Hobbes. Recently, Hanna Pitkin, using the tools of linguistic analysis, has clarified, if not resolved, the debate by examining the disparate uses of the term in both political and non-political discourse. In order to elucidate the issues, she discussed such different forms of representation as formal representation, descriptive representation, substantive representation and interest representation. In this paper I will utilize the distinctions she has developed as a framework for analyzing the process of representation within the community action program of the Office of Economic Opportunity (OEO) during its initial formative period (1964-1966) in the cities of Chicago, Philadelphia and New York City. I will argue that 1) the manner of selecting representatives of the poor (formal representation) was a function of the political resources of competing interests in the city; 2) the orientations (interest representativeness) of the formal representatives affected their influence (actual representation); 3) the influence (actual representation) of the formal representatives affected the level of intra-neighborhood conflict, which in turn affected the representatives' orientations (interest representation); 4) the character of the actual and interest representation was affected by the type of formal representation; and 5) the social characteristics of the representatives (descriptive representation) influenced the character of actual and interest representation.
Lester Salamon pioneered the study of nonprofit organizations and of their cooperation with government in the development and delivery of important social and economic services. His unique research in the early and mid-1980s was the first to document the pervasive interrelationships between government and the nonprofit sector in the United States, identifying some of crucial characteristics of nonprofit human service agencies and examining the impact of the budget and tax policies of tire Reagan and Bush administrations. Partners in Public Service brings together some of Lester Salamon's most important work on the changing relationship between government and the voluntary sector in the American version of the modern welfare state. Approaching issues from a variety of perspectives -- theoretical, empirical, retrospective, prospective, and comparative -- Salamon illuminates the theoretical basis of government-nonprofit cooperation, shows why government came to rely on nonprofit groups to administer public programs, documents the scope of the resulting partnership, reviews the consequences for this partnership of recent attempts to cut federal spending, and explores the expanding scope of government-nonprofit collaboration at the international level.
Human service nonprofits have historically played an important role in advocating on behalf of the vulnerable populations that they serve. Growth in privatization has led many scholars and practitioners to wonder if increased dependence on government funds would compromise this role. The objective of this study is to explore the relationship between government funding and advocacy participation, goals, and tactics through a qualitative investigation of advocacy involvement in the field of homeless services. Results demonstrate that having government funding is associated with managers being highly motivated to participate in advocacy in the hopes of solidifying funding relationships. As a result, advocacy goals are focused primarily on brokering resources and promoting the organization rather than substantive policy change or client representation. Furthermore, in order to be perceived as a legitimate partner to government, organizations reject confrontational methods and advocate as insiders. Overall, these findings indicate perceptions about advocacy may need to shift as increased reliance on government funding has made advocacy participation and participation in collaborative governance virtually indistinguishable.