The Spatial Concentration of Subsidized Housing - Poverty & Race ...

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updated LIHTC data. Although HUD had updated the database since 2000 with morerecent LIHTC data, in some cases the LIHTC database was more up to date,particularly early 1990 projects which were sometimes reported in the 1990’s but notcompleted during the 1990’s. This resulted in the removal of 3,894 projects with179,824 units.Subsidized Housing Unit CharacteristicsThe study calculates a total number of subsidized housing units as well as therelative ratio of units of subsidized housing by type at the census tract level. Thereforeit is appropriate to ask if these types of units are comparable.All subsidized housing programs in this study serve very low and extremelylow income households. However, LIHTC units serve relatively higher incomehouseholds ($13,300 compared to about $9,500 for other types). Other site-basedunits on average house smaller households (1.9 persons per household compared toabout 2.5 for other types). Public housing projects are significantly larger in size thanother site-based housing types (40 percent of public housing units were in projectswith over 200 units compared to about 15 percent of units in projects of other types).The use of number of units (rather than number of projects) in this study should reducethis bias. Data is not available at the census tract level for all subsidized housingtypes. See Appendix A-6 for subsidized housing tenant characteristics.50
Unduplication of Subsidized UnitsDue to the fact that subsidized housing projects often contain multiple sourcesof financing it was necessary to unduplicate the data order to determine the totalnumber of subsidized units in a given geographic area. Since each program is reportedseparately there is a possibility that duplicates were still in the database. The actualnumber of these units was small due to prior effort by HUD to remove duplicateunits. 99The HUD website documentation for A Picture of Subsidized Housing, 2000 retrievedfrom www.hud.gov on 9/10/09 and dated 9/15/08 notes that HUD categorized subprogramsand decreased the number of units when they overlapped. “This table[Housing Sub-programs] shows how we have categorized the subsidy records at HUD,matching on FHA and Section 8 project numbers to avoid double-counting. There isstill a limited amount of double-counting in the figures, since Vouchers may be used inSection 236 projects, and Section 8 may be used in Tax Credit projects, and we do notyet subtract out the overlap.” (n.p.)51
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THE SPATIAL CONCENTRATION OF SUBSID
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I certify that I have read this dis
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TABLE OF CONTENTSLIST OF TABLES ...
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6.4 Summary of Cluster Analysis Res
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Table 5.2 Range of MSA Segregation
Page 11 and 12: ABSTRACTSubsidized housing has been
Page 13 and 14: Chapter 1INTRODUCTIONPublic housing
Page 15 and 16: Data on subsidized housing prior to
Page 17 and 18: subsidy programs in that rents are
Page 19 and 20: Chapter 2LITERATURE REVIEWA compreh
Page 21 and 22: from the nine matched neighborhood
Page 23 and 24: Overall, it is clear that there are
Page 25 and 26: limited the study to city vs. subur
Page 27 and 28: to the public housing, location adj
Page 29 and 30: hardship; and 2) public housing wea
Page 31 and 32: deconcentrated over time is whether
Page 33 and 34: deconcentration. In fact, a higher
Page 35 and 36: in the same neighborhood). On avera
Page 37 and 38: Concentration of Tenant-Based Subsi
Page 39 and 40: Wang, Varady and Wang (2008) studie
Page 41 and 42: from the vouchers. However, there w
Page 43 and 44: consisting of single family zones,
Page 45 and 46: early-mid 1990’s consisting of pu
Page 47 and 48: Recent studies of individual housin
Page 49 and 50: One of the criticisms of the HOPE V
Page 51 and 52: that they are smaller scale, better
Page 53 and 54: Chapter 3METHODOLOGYWhile the conce
Page 55 and 56: Data AvailabilityA limitation in th
Page 57 and 58: just coming on line in the 1990’s
Page 59 and 60: with 1,500 to 12,000 the minimum an
Page 61: exclusion of these units is not pro
Page 65: projects between 35.2 and 46.6 perc
Page 68 and 69: Resulting Data for AnalysisAs a res
Page 70 and 71: Lack of household level data will l
Page 72 and 73: TABLE 4.2Mean Subsidized Housing Un
Page 74 and 75: Measures of ConcentrationThree meas
Page 76 and 77: TABLE 4.6Subsidized Units as a Perc
Page 78 and 79: would have to be to be considered t
Page 80 and 81: mean of 82 subsidized units per tra
Page 82 and 83: Subsidized Housing by Type and Pove
Page 84 and 85: TABLE 4.9Subsidized Units by Subsid
Page 86 and 87: unemployment rate (.427), less than
Page 88 and 89: TABLE 4.12Correlation Matrix (page
Page 90 and 91: TABLE 4.12Correlation Matrix (page
Page 92 and 93: spatial sensitivity because many di
Page 94 and 95: It is possible that these census tr
Page 96 and 97: only 8 MSA’s). The segregation in
Page 98 and 99: The correlation between the subsidi
Page 100 and 101: developing strategies to deconcentr
Page 102 and 103: y subsidy type. The correlation bet
Page 104 and 105: with a poverty rate of 9.2 percent.
Page 106 and 107: The cluster is relatively small con
Page 108 and 109: Cluster 7: Other Site-Based Units -
Page 110 and 111: the only cluster that had a signifi
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alter the perception of public hous
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VouchersVoucher type tracts are dom
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TABLE 6.1Subsidized Units by Cluste
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FIGURE 6.1Percent Census Tracts by
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FIGURE 6.5Census Tract Percent Rent
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Cluster - Concentration -PovertyCen
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strategies. The cluster map shows t
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FIGURE 6.9Map of Public Housing Uni
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Cluster 1: Voucher/No Subsidized Un
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considered moderately concentrated
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Cluster Analysis ResultsThe cluster
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tracts than other subsidy types it
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ecommend efforts to reduce the leve
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scale at which the impacts occur; 2
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units. Given the high cost of these
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REFERENCESAbt Associates, I. (2006)
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Briggs, X. d. S. (Ed.). (2005). The
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Deng, L. (2007). Comparing the effe
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Ellen, I. G., & Voicu, I. (2005). N
Page 150 and 151:
Galster, G. C. (2005). Consequences
Page 152 and 153:
Harris, L. E. (1999). A home is mor
Page 154 and 155:
Johnson, M. P. (2006). Single-perio
Page 156 and 157:
Lee, B. A., Reardon, S. F., Firebau
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Nguyen, M. T. (2005). Does Affordab
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implementing eight consent decrees.
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Schwartz, A. (1999). New York City
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Varady, D. P., & Walker, C. C. (200
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APPENDIX A.1Downloadable Databases
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APPENDIX A.4Missing DataPublicHousi
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APPENDIX A.6Subsidized Housing Unit
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APPENDIX A.8Subsidized Housing Unit
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APPENDIX A.9Demographics by Cluster
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MSAFIPS MSA Name Population Voucher
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MSA /PMSA Code MSA / PMSA Name Popu
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Author Date Data GeographyGalster a
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Author Date Data GeographyHolloway,
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Author Date Data GeographyType ofPr
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Author Date Data GeographyMurray 19
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Author Date Data GeographyLee 20081
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Author Date Data GeographyOakley 20
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Devine, Gray,Rubin andTaghavi (HUD)
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Carlson,Haveman,Kaplan andWolfe 200
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Newman andSchnare 1997Rohe andFreem
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Galster andZobel 1998Freeman andBot
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