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The Low Income Housing Tax Credit and Neighborhood Quality

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Presentation on theme: "The Low Income Housing Tax Credit and Neighborhood Quality"— Presentation transcript:

1 The Low Income Housing Tax Credit and Neighborhood Quality
A Proposal for Measuring Siting Factors, Outputs, and Outcomes Margaret B. Doyle

2 Outline Introduction to LIHTC Literature Review
Scan of Selected Qualified Allocation Plans Proposed Performance Measures Implementation Ideas Conclusion

3 Introduction to LIHTC This project:
Scanned selected states’ QAPs to identify overarching program design/siting factors Proposes performance measures for new properties’ inputs, outputs, and outcomes

4 Introduction to LIHTC State Qualified Allocation Plans (QAPS)
U.S. Treasury and HUD roles Recent developments The Low Income Housing Tax Credit (LIHTC) Program is the largest federal program supporting the production of affordable housing. The LIHTC program is a supply-side approach to affordable housing production, and is widely heralded as a strong example of coordination between public and private investment in affordable housing. While the production and preservation of affordable housing are the primary goals of the program, states have leeway in how and to whom they award these competitive tax credits. Thus, each state has a system to determine the winners of the tax credits, and accordingly, the developers’ (for-profit and not-for-profit, and sometimes both) siting of properties and subsequent effects on neighborhood quality are of interest. Very recently, some states have come under fire for not working to deconcentrate poverty or site LIHTC units in high-opportunity neighborhoods, directly evidenced by the 2015 Supreme Court case Texas Department of Housing and Community Affairs et al. vs. Inclusive Communities Project, Inc., et al. The case was brought by Inclusive Communities, a Dallas nonprofit organization that works to place Section 8 voucher-holding families in high-opportunity communities; the LIHTC program requires developments to accept vouchers. Inclusive Communities found, however, that all the LIHTC properties in Dallas were clustered in segregated areas. This appeared to be evidence of racial segregation, violating the Fair Housing Act’s disparate impact doctrine

5 Literature Review Three pronged:
Studies evaluating effect on neighborhood Studies evaluating QAPs and siting Work on performance measures

6 Scan of QAPs Why were these states chosen? Information from the literature review/states that were highlighted (the Kresge Foundation in particular identified several helpful examples from state QAPs that pay attention to neighborhood quality); Suggestions from my supervisor; Geographic diversity; Fast-growing states with high affordable housing need/competitive LIHTC programs; Personal knowledge (Maryland).

7 Scan of QAPs: Conclusions
Fundamental divide: poverty deconcentration vs. investment in neighborhoods with high need Green building and sustainability, mixed-use or revitalization projects, access to amenities all common

8 Proposed Performance Measures
Social Economic Environmental Avg. Walkscore Median rent % units LEED certified % units within ½ mile of public transportation % units included in reinvestment plan % units using energy efficiency strategies Avg. commute length % units in mixed-use plan % units using renewable energy Avg. school attendance Avg. poverty rate % units within ½ mile of public park Avg. H.S. grad rate Median income Crime rates % vacant units in tract Avg. % affordable units in development

9 Proposed Performance Measures
Flexibility of measures Contextual factors on their face or serving as baseline Can be used together, e.g. LEED certified units in mixed-use project Availability of data Census tract data LIHTC unit addresses

10 Implementation and Conclusion
Broad federal oversight or implementation at the state level Value of measuring these factors: Provides information for potential summative evaluation Illustration of how program design is implemented re: neighborhoods

11 Questions Thank you! Margaret B. Doyle, University of Maryland School of Public Policy With the support of Dr. Regina C. Gray, Office of Policy Development and Research U.S. Department of Housing and Urban Development


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