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

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Galster, G. C. (2005). Consequences from the redistribution of urban poverty duringthe 1990s: A cautionary tale. Economic Development Quarterly, 19(2), 119-125.Galster, G. C., Tatian, P., & Smith, R. (1999). The impact of neighbors who usesection 8 certificates on property values. Housing Policy Debate, 10(4), 879-917.GAO. (1997). Tax Credits: Opportunities to Improve Oversight of the Low-IncomeHousing Program. Washington, DC: U.S. Government Accounting Office.GAO. (2003). Public Housing: HOPE VI Resident Issues and Changes inNeighborhoods Surrounding Grant Sites. Washington, DC: GAO.Gillen, K. C. (2005). Three essays in urban economics. Unpublished Ph.D., Universityof Pennsylvania, United States -- Pennsylvania.Goering, J., & Feins, J. (2008). Social Science, Housing Policy, and the HarmfulEffects of Poverty. Journal of Urban Affairs, 30(2), 139-148.Goering, J., Kamely, A., & Richardson, T. (1997). Recent Research on RacialSegregation and Poverty Concentration in Public Housing in the United States.Urban Affairs Review, 32(5), 723-745.Goetz, E. G. (2003). Clearing the Way: Deconcentrating the Poor in Urban America.Washington, DC: The Urban Institute Press.138
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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
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Lack of household level data will l
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TABLE 4.2Mean Subsidized Housing Un
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Measures of ConcentrationThree meas
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TABLE 4.6Subsidized Units as a Perc
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would have to be to be considered t
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mean of 82 subsidized units per tra
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Subsidized Housing by Type and Pove
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TABLE 4.9Subsidized Units by Subsid
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unemployment rate (.427), less than
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TABLE 4.12Correlation Matrix (page
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TABLE 4.12Correlation Matrix (page
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spatial sensitivity because many di
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It is possible that these census tr
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only 8 MSA’s). The segregation in
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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 120 and 121: FIGURE 6.5Census Tract Percent Rent
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 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
Page 170 and 171: APPENDIX A.6Subsidized Housing Unit
Page 172 and 173: APPENDIX A.8Subsidized Housing Unit
Page 174 and 175: APPENDIX A.9Demographics by Cluster
Page 176 and 177: MSAFIPS MSA Name Population Voucher
Page 186 and 187: MSA /PMSA Code MSA / PMSA Name Popu
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
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Author Date Data GeographyMurray 19
Page 204 and 205:
Author Date Data GeographyLee 20081
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Author Date Data GeographyOakley 20
Page 208 and 209:
Devine, Gray,Rubin andTaghavi (HUD)
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Carlson,Haveman,Kaplan andWolfe 200
Page 212 and 213:
Newman andSchnare 1997Rohe andFreem
Page 214:
Galster andZobel 1998Freeman andBot
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