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

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The correlation between the subsidized housing index score for the MSA andother demographic and housing variables at the census tract level did not identify anysignificant census tract level relationships. See Table 5.5 for correlations betweensubsidized housing segregation and selected census tract level variables.These results indicate that the MSA distribution of subsidized housing appearsto be independent of metropolitan scale, neighborhood concentration, or other censustract level indicators.TABLE 5.5Correlations for Selected Variables with MSA Subsidized Housing SegregationIndex (D) 2000Correlation with Subsidized Housing Segregation Index (D)Correlation(Pearson)Black-Non-Black Segregation Index (D) .495Hispanic-Non-Hispanic Segregation Index (D) .253Poor-Non-Poor Segregation Index (D) .332Subsidized As Percent of Total Housing Units -.137Poverty Rate -.100Percent Less Than HS -.008Civilian Unemployment Rate -.081Percent Households With Public Assistance -.119Percent Black .162Percent Hispanic -.018Percent Foreign Born .094Percent Elderly .044Percent Rent Occupied Units -.084Percent Vacant Units .066Percent Units Built Before 1939 -.043Median Rent .141Density of Total Housing Units Per Square Mile .159State .014Region -.24386
Segregation Index and PovertySubsidized housing concentration at the MSA level is found to be higher thanracial segregation while poverty concentration on average is lower than subsidizedhousing segregation. It could be that individual MSA’s do not follow the averagerelationship masking differences that could be important in directing appropriatestrategies.To test this the MSA’s were split into three equal groups based on subsidizedhousing segregation scores and labeled high, medium and low. Racial and incomesegregation scores were also distributed in the same manner. As expected, mostMSA’s fit the general average and direction of the relationship between thesegregation indices. However, in a significant minority of 67 MSA’s (20.2 percent)the pattern is reversed.There are 16 MSA’s (4.8 percent) with relatively low subsidized housingsegregation and high poverty concentration. An additional 22 MSA’s (6.6 percent)have relatively high subsidized housing segregation but low poverty concentration.There are 12 MSA’s (3.6%) with relatively low subsidized housing and highracial concentration scores. In addition, there are 17 MSA’s (5.1 percent) where thesubsidized housing segregation is in the top third of the distribution while the racialsegregation is in the bottom third. While the total number of these MSA’s is relativelysmall, further study about what makes these MSA’s different could be useful in87
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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
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 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
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Ellen, I. G., & Voicu, I. (2005). N
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Galster, G. C. (2005). Consequences
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Harris, L. E. (1999). A home is mor
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Johnson, M. P. (2006). Single-perio
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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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