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

More documents

Recommendations

Info

elicited personal opinions about the neighborhood. Properties in close proximity tothe subsidized units saw values rise. This effect was most likely due to the fact thatmany of the properties acquired were vacant and underwent considerablerehabilitation. This small scale impact was insufficient to change neighborhooddynamics at a larger scale. Focus groups were aware of and concerned about othersubsidized housing in their neighborhoods besides the scattered sites and in generalwere concerned with the quality of rental maintenance, both subsidized andunsubsidized, in their neighborhoods. The authors conclude that post-occupancyproperty management is crucial and that a negative effect of more units in vulnerableneighborhoods suggests there may be a maximum threshold which triggersneighborhood decline regardless of distance.Lee (2008) studied the change in property values surrounding multiple sitebased housing including public housing, other HUD site-based housing and the LIHTCin five MSA’s and found that results varied by type of housing, proximity, andconcentration. Public housing reduced home values while LIHTC results were mixed.Positive effects depended on the number of units.Lyons and Loveridge (1993) studied the impact on property values of varioustypes of subsidized housing in Ramsey County, MN and found that the number ofunits had a small but statistically significant negative effect which diminished withdistance from the subsidized housing. Larger projects had more of an impact thanindividual units being added to neighborhoods.24
Concentration of Tenant-Based Subsidized Housing (Vouchers)Housing vouchers have increasingly become a significant percentage of allfederally subsidized housing units increasing from 1.35 million units to 1.50 millionunits (11 percent increase) from 1993 to 2000 at a time when public housing unitsdeclined by 22 percent. Housing vouchers were also used during this period forvarious mobility programs and HOPE VI relocations. A number of studies ofvouchers were conducted to determine if vouchers were indeed effective atdeconcentrating housing and poverty. Since these studies typically track recipients ofsubsidized housing they are also useful in geographic concentration studies becausethey capture the geographic clustering of units. These studies have used the mostrecent data available to study patterns of dispersion and concentration of subsidizedhousing. Results indicate greater movement to lower poverty neighborhoods but themovement was minimal given the size of the subsidized housing stock and there wasvirtually no lessening of racial and ethnic segregation.Kingsley, Johnson and Pettit (2003) studied relocation in the HOPE VIprogram in 31 MSA’s. They found that the number of HOPE VI relocation voucherswas small enough not to impact the location pattern of the overall voucher program (p.441). Clustering was found in some cases but was not the predominant pattern.Clusters were more likely in tracts with middle to high poverty rates and high minorityconcentration (p.443). The authors conclude that “the numbers alone cannot tell uswhether the degree of clustering we have observed in a particular city is problematic or25
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 and 32: deconcentrated over time is whether
Page 33 and 34: deconcentration. In fact, a higher
Page 35: in the same neighborhood). On avera
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
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 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
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 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
show all

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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?