Poster prepared for the Association for Public Policy Analysis and Management 2011 Conference in Washington, DC.

1. Does Mandated Collaboration Work? An Analysis of Homelessness Planning Networks
Stephanie O. Macgill, MPA, Derek Kauneckis, PhD | University of Nevada, Reno
Abstract Results Discussion
The U.S. Department of Housing and Urban Development (HUD) requires There were 2,323 organizations included in the analysis. Housing providers constituted 23% The analyses reveal the importance of assessing the degree to which mandated
(543) of the sample. collaboration results in a network comprised of key stakeholders. 36% of housing
communities to form collaborative networks (CoCs) in order to annually compete for a
Continuum of Care Homeless Assistance Program grant. The CoC networks are 64% of the 543 housing providers analyzed were members of their local CoC network. providers were not members of their local CoC networks. As a result, these housing
charged with planning and managing the delivery of homelessness services, and providers were not participating in a community dialogue about homelessness or being
demonstrating progress toward reducing homelessness in their community. Although Housing providers in areas with mixed population density were the least integrated into CoC considered for funding opportunities.
housing is often not the only service individuals and families need in order to exit networks. Housing providers were also the least integrated into Southern CoC networks.
On the community level, the homelessness rate was more important than the size of
homelessness, organizations that operate emergency shelters, transitional housing the population in terms of bringing housing providers to the planning table. As the
and permanent supportive housing (housing providers) are critical partners for CoC Membership by Population Density and Region need for homelessness services and housing increased, housing providers were more
ensuring CoC network effectiveness. This paper utilizes administrative data from 30 likely to be found at the planning table.
60%
CoC grant applications to examine the extent to which housing providers are
members of their local CoC network, and to explore community, network and 50% Governance structures of CoC networks were also important. CoC networks with
organizational level factors that may affect membership. 40% frequent governing board meetings (monthly versus quarterly), and who have in place
a formalized structure to determine governing board membership and leadership
30%
(election versus voluntary) had higher degrees of housing provider integration.
Continuum of Care Homeless Assistance Program 20%
10%
When all organizations were included in the analysis (Models 1 and 2), simply being a
• Competitive grant program created in 1995 to streamline HUD’s funding structure housing provider was a significant predictor of non CoC network membership. This
0%
for homelessness services, and to incentivize the coordination of homelessness Rural Mixed Urban New England South Midwest West could be a reflection of the fact that housing providers comprise less than 25% of the
Rural/Suburban
service delivery. total sample. Along these lines, CoC networks appear to be successfully including a
CoC Members Non-CoC Members wide range of stakeholders.
• Communities must form planning networks that are responsible for identifying local
funding priorities for homelessness programs and services. When the analysis only included housing providers (Models 3 and 4), receiving HUD
Factors Predicting CoC Membership funding, operating emergency shelters and operating permanent supportive housing
• The CoC grant program requires a single application from each community that were predictors of CoC membership. Given HUD’s emphasis on permanent supportive
Rare events logistic regression analyses were conducted to explore what factors may affect
demonstrates network-level collaboration, strategic planning and progress toward housing as a critical component to ending chronic homelessness, this finding is
housing provider CoC membership. Model 1 analyzes community, network and organizational
reducing homelessness. promising, and answered the second hypothesis in the affirmative.
level factors for all organizations in the dataset. Model 2 adds regional interaction variables.
• Although the CoC grant pays only for housing services, CoC networks are Models 3 and 4 test the same variables but control for organizational type by only including As hypothesized, larger housing providers were more likely to be CoC network
expected to serve as coordinated service delivery models that integrate community housing providers in the analyses. members. However, the size of the organization lost importance when the analysis
stakeholders into community-wide efforts to address homelessness. only included housing providers, indicating that smaller housing providers may not be
Rare Events Logistic Regression of CoC Network Membership as constrained by size and organizational capacity as expected, an encouraging
Model 1 Model 2 Model 3 Model 4 finding for the likelihood of CoC network inclusiveness.
Previous Research Population (logged) -0.20 -0.12 -0.17 -0.04
The third hypothesis was not substantiated in the findings. The size of the CoC
CoC size -0.004 -0.001 -0.004 -0.002
Researchers found that HUD’s CoC mandate increased communication and Homelessness rate .05*** 0.06* 0.05*** 0.05* network approached significance in Models 1 and 3 (p = .10), but lost all effect on
knowledge sharing among network members. Factors important for network success Governing board meeting network membership when regional interaction terms were included in the analysis.
0.72*** 0.83** 0.71*** 0.66*
frequency However, the negative direction of the coefficients were as expected.
included strong CoC network leadership and integration of mainstream service CoC is legal entity (i.e., 501c3) -0.30 -0.44 -0.21 -0.26
providers (such as public housing agencies) into CoC networks. (Burt et al., 2002). Voluntary governing board CoC networks located in the South and in areas with a mixed rural/suburban
-0.54 -1.22* -0.50 -0.84
leadership
Participation in CoC networks resulted in increased service capacity, heightened population density had the least integrated networks. However, all “mixed” CoC
Voluntary governing board
-0.96** -0.68 -1.10** -0.68 networks in the sample were located in the South, so these results could be a result of
public profiles, and beneficial new relationships with other service providers. Although membership
Receiving other HUD funding 1.55*** 1.54*** 1.46*** 1.42*** sample bias and must be viewed with caution.
CoC applications described broad planning processes, in reality, CoC planning was
Housing provider size 0.44** 0.48** 0.08 0.10
driven by a small group of organizations (Ivery, 2008). Operating beds before 2007 -3.90*** -3.79*** 0.91 0.80
New beds available by 1/31/08 -1.11 -0.98 -0.11 0.01
Limitations
This paper builds on previous research by examining the efficacy of a federal
Beds available after 1/31/08 -0.27 -0.30 0.42 0.50
mandate for collaboration in the delivery of social services. Housing providers play an Permanent supportive housing 0.18 0.21 0.63* 0.65*
• Administrative data do not allow for an analysis of the degree to which communities
important role in ending homelessness and if they are not participating in CoC Transitional Housing -0.02 -0.21 0.55 0.39 have achieved meaningful collaboratives. Nominal inclusion in the network does not
network planning and service delivery, communities may not be responding to Emergency shelter 0.63* 0.65* 1.05*** 1.05*** necessarily result in substantive collaboration.
homelessness as effectively as they could. Target population -1.39** -1.48** 0.01 -0.06
• The pace of network development and achievement of network outcomes, such as
Target sub-population -0.49 -0.49 -0.12 -0.12
Urban New England - -0.60 - -0.80
changes in network membership or governance structure, and reductions in
Rural South - -0.70 - -0.75
homelessness, cannot be determined through one year of administrative data. This
• How integrated are housing providers into CoC networks?
Research Questions and Hypotheses analysis can only offer a “snapshot” of a dynamic process.
Urban South - -1.43 - -1.54
Mixed rural/suburban South - -1.79* - -1.61
• How do different CoC network governance structures affect housing provider Urban Midwest - -0.19 - -0.32 Implications
membership? Urban West - -1.17 - -0.76
Rural West - -3.03 - -2.12 Communities across the country have responded to HUD’s mandate for collaboration
• Larger housing providers are expected to have more organizational capacity to Constant 5.32** 5.34** -1.91 -2.16 in the planning and delivery of homelessness services positively. In many ways, the
participate in networks and are therefore more likely to be CoC network members. All Organizations (N=2,323) Housing Providers Only (N=543) mandate has been successful as communities have begun to use the CoC networks
*** p = .001, two tailed chi2 (17df) = 616.59*** chi2 (24df) = 638.43*** chi2 (17df) = 161.64*** chi2 (24df) = 174.19*** as comprehensive planning structures. A wide range of stakeholders are involved in
• HUD emphasizes the importance of permanent supportive housing; operating ** p = .01, two tailed Log likelihood = -366.19 Log likelihood = -355.26 Log likelihood = -274.85 Log likelihood = -268.57 the planning processes, and CoC networks manage a range of critical services and
* p = .05, two tailed Pseudo R2 = 0.46 Pseudo R2 = 0.47 Pseudo R2 = 0.23 Pseudo R2 = 0.24
permanent supportive housing is expected to positively affect CoC membership. housing options, many of which are not funded by HUD’s financial incentives for
collaboration.
• Because the coordination costs of managing a large network can become a Model 1
disincentive to recruit all housing providers, large networks are expected to have a • The rate of homelessness, frequent CoC governing board meetings, receiving HUD funding, However, CoC networks should continue to consider how integrated housing providers
negative impact on housing provider CoC membership. operating a larger number of facilities, and operating emergency shelters positively affect are in the planning processes. Housing providers are critical to ending homelessness
the likelihood of housing provider membership in the CoC network. and communities should ensure all housing providers are offered a meaningful
• Voluntary governing board membership, currently operating beds and identifying a target opportunity to participate and be represented in the planning process.
Data population negatively affect the likelihood of CoC membership. Networks that appear to be informally managed may deter potential members who
• Operating permanent supportive housing has no effect on CoC membership. would like to participate but see little benefit. As CoC networks age, the governance
• CoC networks were selected based on a population density stratification. 6 rural, 5 structures should be assessed to ensure that formal and facilitative structures are in
Model 2
mixed rural/suburban, and 19 urban CoC networks were randomly selected for
• The inclusion of regional and population density interaction variables causes voluntary place. Formal structures are critical for recruiting stakeholders and instilling a sense of
analysis. The sample stratification reflects the population distribution of rural, mixed governing board membership to lose significance, and voluntary governing board leadership purpose and investment to the mission of the CoC network.
and urban CoC networks. to become negatively significant.
Future research could explore whether community level differences in outcomes exist
• Data were compiled from FY2008 CoC grant applications, the most recent year • Of the interaction variables, only “mixed south” is significant.
between CoC networks with high and low degrees of housing provider integration.
available at time of data collection. Model 3 Also, utilizing multiple years of administrative data would shed light on the ways in
• The rate of homelessness, governing board meeting frequency, receiving HUD funding and which community, network and organizational level factors affect CoC membership
• Data were obtained from the National Alliance to End Homelessness in August,
operating emergency shelters remain positively significant. and CoC network effectiveness over time.
2010. • When housing providers only are included in the analysis, operating permanent supportive
• The applications listed CoC network members and included details on the CoC housing becomes a significant predictor of CoC membership. References
network governance structure. The applications also included a housing inventory • Voluntary governing board membership decreases the likelihood of CoC membership. Burt, M. R., Pollack D., Sosland A., Mikelson, K.S., Drapa, E., Greenwalt, K., Sharley, P., Graham, A., Abravanel, M., Smith, R. (2002).
Evaluation of Continuums of Care for Homeless People. Washington, DC: The Urban Institute.
attachment, which listed all housing providers in the community, the types of Model 4 Ivery, J. (2008). Policy Mandated Collaboration. Journal of Sociology and Social Welfare, 25, 52-70.
housing operated and the populations served. • None of the regional interaction terms are significant. Lewis, B., Boulahanis, J., Matheny, E. (2009). Joined-up governance: mandated collaboration in US homeless services. International
Journal of Public Sector Management, 22, 392-399.
• Once again, the inclusion of the regional interactions cause voluntary governing board
• The housing inventory and the network membership data were merged for leadership to lose significance. Acknowledgements
analysis. This research would not have been possible without the assistance of Dr. William Lee Eubank (Department of Political Science, UNR);
Dr. Markus Kemmelmeier (Department of Social Psychology, UNR); and Dr. M. William Sermons (former Director of Research at the
National Alliance to End Homelessness).