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

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FIGURE 6.5Census Tract Percent Rental by Cluster 2000FIGURE 6.6Census Tract Density by Cluster 2000108
TABLE 6.5Policy Recommendations by ClusterCluster – Concentration -PovertyCensusTractsSubsidizedUnits perTractPovertyRateCluster 1: Voucher/NoSubsidized Units - VeryLow Concentration –Very Low Poverty 30,792 7 9.2Cluster 2: Voucher – LowConcentration – LowPoverty 8,490 61 15.9Cluster 3: Voucher –Moderate Concentration –Moderate Poverty 1,366 135 22.2Cluster 4: Public Housing– Moderate Concentration– Moderate Poverty 1,158 144 19.1Cluster 5: Other SiteBased – ModerateConcentration – ModeratePoverty 2,051 144 15.8Cluster 6: LIHTC –Moderate Concentration –Moderate Poverty 997 148 14.6Policy RecommendationsThese neighborhoods present an opportunityfor siting new subsidized housing andtargeting vouchers.Because these neighborhoods contain somesite-based subsidized units it would beinteresting to study these neighborhoodfurther as potential low-concentration, lowpovertydevelopment models. However, theexisting neighborhoods should be monitoredso they do not attract too many additionalunits of subsidized housing.These neighborhoods are at risk of beingover-concentrated and should be avoidedwhen building new subsidized housing orwhen using vouchers. They should be furtherstudied to identify why there is a largerconcentration of vouchers and how to addressthis problem.These neighborhoods are at risk of beingover-concentrated and should be avoidedwhen building new subsidized housing orwhen using vouchers. Small scaledeconcentration and relocation efforts couldbe helpful as well to reduce the existingconcentration.These neighborhoods are at risk of beingover-concentrated and should be avoidedwhen building new subsidized housing orwhen using vouchers. Small scaledeconcentration and relocation efforts couldbe helpful as well to reduce the existingconcentration.These neighborhoods are at risk of beingover-concentrated and should be avoidedwhen building new subsidized housing orwhen using vouchers. However, theseneighborhoods represent a lowerconcentration model for siting of LIHTCprojects and should be further studied forpossible replication.109
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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
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ABSTRACTSubsidized housing has been
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Chapter 1INTRODUCTIONPublic housing
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Data on subsidized housing prior to
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subsidy programs in that rents are
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Chapter 2LITERATURE REVIEWA compreh
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from the nine matched neighborhood
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Overall, it is clear that there are
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limited the study to city vs. subur
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to the public housing, location adj
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hardship; and 2) public housing wea
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deconcentrated over time is whether
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deconcentration. In fact, a higher
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in the same neighborhood). On avera
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Concentration of Tenant-Based Subsi
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Wang, Varady and Wang (2008) studie
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from the vouchers. However, there w
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consisting of single family zones,
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early-mid 1990’s consisting of pu
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Recent studies of individual housin
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One of the criticisms of the HOPE V
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that they are smaller scale, better
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Chapter 3METHODOLOGYWhile the conce
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Data AvailabilityA limitation in th
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just coming on line in the 1990’s
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with 1,500 to 12,000 the minimum an
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exclusion of these units is not pro
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Unduplication of Subsidized UnitsDu
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projects between 35.2 and 46.6 perc
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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
Page 112 and 113: alter the perception of public hous
Page 114 and 115: 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 122 and 123: Cluster - Concentration -PovertyCen
Page 124 and 125: 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
Page 134 and 135: tracts than other subsidy types it
Page 136 and 137: ecommend efforts to reduce the leve
Page 138 and 139: 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
Page 168 and 169: 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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