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

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Khadduri, Buron and Climaco (Abt Associates) (2006) studied 182 MSA’s withpopulations over 250,000 between 1995 and 2003 and found the percentage of unitsconstructed in low poverty areas has increased over time. The study also founddifferences between states in the location of LIHTC units.Oakley (2008) studied the geographic location of LIHTC units in four MSA’susing multivariate analysis and found that poverty and unemployment were notsignificant indicators. Except for Los Angeles, race/ethnicity was not a significantpredictor. The strongest predictor was the presence of the project in a qualified censustract (QCT), which indicates that this incentive was effective at bringing LIHTC’s toareas that needed redevelopment, but this may also have limited the decentralization ofunits. Units were also more likely to be sited in tracts that also had other LIHTCprojects nearby (p. 26). The author concludes that the spatial distribution of LIHTC isgeographically more dispersed than previous site-based housing projects but the trendis toward clustering of the LIHTC units over time.Deng (2007) compared the impacts of vouchers and LIHTC units in Miami-Dade County. The study found a strong similarity between the voucher and LIHTCneighborhoods. Most LIHTC units were located in very low and low incomeneighborhoods, with only a small proportion in middle-income neighborhoods (p. 32).Most voucher and LIHTC units were located in areas with schools that perform understate averages, regardless of subsidy type. As for the tightness of the housing market,the author did not find evidence that a balanced market led to greater income or racial20
deconcentration. In fact, a higher percentage of voucher holders lived in middleincomeneighborhoods in tight markets than in balanced ones (p. 33).Van Zandt and Mhatre (2009) found a significant spatial clustering of LIHTCunits in the Dallas metropolitan region. Increased spatial clustering was associatedwith higher minority populations (r =.483), higher poverty levels (r=.359), lowerhousehold incomes (r =.202), lower safety levels (r =.350) and lower educationalquality (r =.263). Overall about half the units were highly clustered, mostly in urbanareas. The other half are not clustered and located in areas with social and economicvariables comparable to regional averages. This study is limited to only one MSA andis therefore not generalizable.O’Neill (2008) studied the LIHTC in 25 of the largest central cities and foundextensive clustering. The clustering varied by city and was associated with highpoverty in some but not all cities.Two studies compared the location of LIHTC units and vouchers. McClure(2006) compared the location of LIHTC units and vouchers in a nationwide study. Alarger proportion of LIHTC units were located in low poverty suburban neighborhoodsthan the vouchers. The impact of the LIHTC on suburban tract poverty was minimal.Deng (2007) looked at income, racial segregation and school quality in six MSA’s andfound that most vouchers and LIHTC units are located in areas with schools thatperform under state averages, regardless of subsidy type.21
Page 1 and 2: THE SPATIAL CONCENTRATION OF SUBSID
Page 3 and 4: I certify that I have read this dis
Page 5 and 6: TABLE OF CONTENTSLIST OF TABLES ...
Page 7 and 8: 6.4 Summary of Cluster Analysis Res
Page 9 and 10: 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: deconcentrated over time is whether
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 and 62: exclusion of these units is not pro
Page 63 and 64: Unduplication of Subsidized UnitsDu
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
Page 116 and 117:
TABLE 6.1Subsidized Units by Cluste
Page 118 and 119:
FIGURE 6.1Percent Census Tracts by
Page 120 and 121:
FIGURE 6.5Census Tract Percent Rent
Page 122 and 123:
Cluster - Concentration -PovertyCen
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strategies. The cluster map shows t
Page 126 and 127:
FIGURE 6.9Map of Public Housing Uni
Page 128 and 129:
Cluster 1: Voucher/No Subsidized Un
Page 130 and 131:
considered moderately concentrated
Page 132 and 133:
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
Page 140 and 141:
units. Given the high cost of these
Page 142 and 143:
REFERENCESAbt Associates, I. (2006)
Page 144 and 145:
Briggs, X. d. S. (Ed.). (2005). The
Page 146 and 147:
Deng, L. (2007). Comparing the effe
Page 148 and 149:
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
Page 158 and 159:
Nguyen, M. T. (2005). Does Affordab
Page 160 and 161:
implementing eight consent decrees.
Page 162 and 163:
Schwartz, A. (1999). New York City
Page 164 and 165:
Varady, D. P., & Walker, C. C. (200
Page 166 and 167:
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
Page 178 and 179:
Page 180 and 181:
Page 182 and 183:
Page 184 and 185:
Page 186 and 187:
MSA /PMSA Code MSA / PMSA Name Popu
Page 188 and 189:
Page 190 and 191:
Page 192 and 193:
Page 194 and 195:
Page 196 and 197:
Author Date Data GeographyGalster a
Page 198 and 199:
Author Date Data GeographyHolloway,
Page 200 and 201:
Author Date Data GeographyType ofPr
Page 202 and 203:
Author Date Data GeographyMurray 19
Page 204 and 205:
Author Date Data GeographyLee 20081
Page 206 and 207:
Author Date Data GeographyOakley 20
Page 208 and 209:
Devine, Gray,Rubin andTaghavi (HUD)
Page 210 and 211:
Carlson,Haveman,Kaplan andWolfe 200
Page 212 and 213:
Newman andSchnare 1997Rohe andFreem
Page 214:
Galster andZobel 1998Freeman andBot
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