Abstract: Advancing New Markets: Examining Network Structure in the New Markets Tax Credits Program (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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Advancing New Markets: Examining Network Structure in the New Markets Tax Credits Program

Thursday, January 21, 2021
* noted as presenting author
Andrew Foell, MSW, MPP, Doctoral Student, Washington University in Saint Louis, St. Louis, MO
Kyle A. Pitzer, MSSW, Doctoral Student, Washington University in Saint Louis, St. Louis, MO
Background & Purpose: The New Markets Tax Credits (NMTC) program allocates billions of dollars to qualified low-income communities to sustain local economies by stimulating private investment. Partnerships are integral to implementation of the NMTC program. However, no studies have examined the extent to which NMTC partners collaborate to finance and implement the program. Additionally, few studies have examined how federal community development programs create networks of partners that share information and innovations across communities. The objectives of this study are to address these knowledge gaps by examining the structure and stability of collaboration in the NMTC program.

Methods: This study used the NMTC Public Data Release 2019 from the Community Development Financial Institutions (CDFI) Fund which consisted of NMTC projects (n=5,799) and community development entities (CDEs) that financed each project (n=321) from 2001 to 2017. The dataset included project-level data including project allocation amount, project location, investment purpose, whether the investment was a project between multiple CDEs, and whether the project served multiple census tracts. Additional CDE data was retrieved from the CDFI Fund’s Searchable Awards Database. Network visualization and descriptive statistics were examined for bipartite and one-mode networks to identify trends over time. Exponential Random Graph Models (ERGM) were developed to examine predictors of collaboration. Data visualization and analysis occurred in R version 3.5.3.

Results: From 2001 to 2017, 321 CDEs invested over $48 billion in NMTC projects. Financed NMTC projects increased from 1 to 443 between 2001 and 2017 (M=325, SD=182.47). CDEs receiving NMTC allocations also increased from 1 to 157 (M=130.60, SD=75.47). CDE network density increased from 0 in 2001 to 0.08 by 2017 (M=0.03, SD=0.03), while network isolates decreased from 33 to 5. Project network density remained stable over time (M=0.02, SD=0.01). Projects in the same state were significantly more likely to be connected (b=2.04, p<0.001), and projects in urban areas were more likely to be connected to other urban projects (b=0.10 , p<0.001). Multi-tract project connections were also more likely than single-tract ties (b=0.09, p<0.001). CDEs that remained in the network longer formed more ties (b=1.02, p<0.001). National CDEs were more likely to partner with other national CDEs to finance projects (b=0.30, p<0.001) compared to partnerships with regional, state, or local CDEs.

Conclusions & Implications: A national network of CDEs partner to finance economic development projects in low-income communities through the NMTC program. NMTC funding connects geographically distant neighborhoods through project investments, suggesting that CDEs may facilitate the diffusion of innovations across community contexts. A core group of highly connected national-level CDEs emerged and became central to the network over time. Thus, the program is indicative of a success-to-successful program archetype, where demonstrated NMTC funding success leads to continued success. Network analysis offers important insights to neighborhood and community research and the science of social change by mapping channels of communication, information flow, and collaboration in community development policy networks. Further research is needed to examine how collaborative network structures influence project and community-level outcomes.