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

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MSAFIPS MSA Name Population Vouchers Public HousingOther Site Based(MF/S236/S8) LIHTC Total8780 Visalia-Tulare-Porterville, CA MSA 367,137 1,510 704 588 1,361 4,1638800 Waco, TX MSA 213,517 1,660 1,066 1,171 560 4,4578840 Washington, DC-MD-VA-WV PMSA 4,922,060 19,366 14,782 32,020 27,782 93,9508880 Waterbury, CT PMSA 229,064 934 820 4,257 414 6,4258920 Waterloo-Cedar Falls, IA MSA 128,012 1,137 91 1,132 217 2,5778940 Wausau, WI MSA 125,834 273 189 488 368 1,3188960 West Palm Beach-Boca Raton, FL MSA 1,128,748 4,303 2,326 1,967 4,334 12,9309000 Wheeling, WV-OH MSA 153,172 596 2,018 1,235 290 4,1399040 Wichita, KS MSA 545,220 2,024 912 2,361 2,705 8,0029080 Wichita Falls, TX MSA 140,518 739 774 912 322 2,7479140 Williamsport, PA MSA 120,044 457 672 469 286 1,8849160 Wilmington-Newark, DE-MD PMSA 586,216 2,568 1,899 3,697 1,985 10,1499200 Wilmington, NC MSA 233,450 1,662 1,416 711 897 4,6869240 Worcester, MA-CT PMSA 508,982 3,000 2,502 6,176 1,960 13,6389260 Yakima, WA MSA 222,581 425 290 796 832 2,3439270 Yolo, CA PMSA 168,660 1,237 421 1,104 969 3,7319280 York, PA MSA 381,751 1,128 1,060 893 799 3,8809320 Youngstown-Warren, OH MSA 594,746 2,425 3,513 3,608 1,619 11,1659340 Yuba City, CA MSA 139,149 666 213 733 192 1,8049360 Yuma, AZ MSA 160,026 1,049 394 248 581 2,272Total 225,666,050 1,182,557 772,810 1,254,601 716,915 4,026,883172
APPENDIX A.11Segregation Index (D) by MSA 2000MSA /PMSA Code MSA / PMSA Name PopulationBlack-Non-BlackHispanic-Non-HispanicPoor-Non-PoorSubsidized-Non-Subsidized40 Abilene, TX MSA 125,062 0.3505 0.3778 0.3261 0.606880 Akron, OH PMSA 694,960 0.6429 0.3422 0.4221 0.6031120 Albany, GA MSA 120,822 0.5960 0.3479 0.3971 0.5292160 Albany-Schenectady-Troy, NY MSA 874,183 0.5979 0.3885 0.3914 0.5691200 Albuquerque, NM MSA 712,738 0.2843 0.3859 0.3284 0.5054220 Alexandria, LA MSA 126,337 0.5962 0.3890 0.3120 0.5074240 Allentown-Bethlehem-Easton, PA MSA 637,958 0.4967 0.6047 0.3945 0.5803280 Altoona, PA MSA 129,144 0.4567 0.4704 0.2698 0.5725320 Amarillo, TX MSA 217,858 0.5687 0.4236 0.3286 0.4570380 Anchorage, AK MSA 260,283 0.3203 0.2041 0.2943 0.4861440 Ann Arbor, MI PMSA 578,736 0.6052 0.3756 0.5029 0.6910450 Anniston, AL MSA 112,249 0.4987 0.3171 0.2755 0.6293460 Appleton-Oshkosh-Neenah, WI MSA 358,365 0.4883 0.3214 0.2887 0.5273480 Asheville, NC MSA 225,965 0.5650 0.3378 0.2278 0.6205500 Athens, GA MSA 153,444 0.4437 0.4293 0.3933 0.6338520 Atlanta, GA MSA 4,112,198 0.6129 0.4618 0.3614 0.6678560 Atlantic-Cape May, NJ PMSA 354,878 0.5880 0.4423 0.3145 0.6898580 Auburn-Opelika, AL MSA 115,092 0.3756 0.2447 0.4407 0.5413600 Augusta-Aiken, GA-SC MSA 477,441 0.4428 0.2613 0.3016 0.5312640 Austin-San Marcos, TX MSA 1,247,329 0.4146 0.4068 0.4158 0.6783680 Bakersfield, CA MSA 651,083 0.4165 0.4886 0.3160 0.5335720 Baltimore, MD PMSA 2,543,268 0.6637 0.3459 0.4380 0.6212730 Bangor, ME MSA 83,033 0.3985 0.3858 0.3175 0.4529740 Barnstable-Yarmouth, MA MSA 162,571 0.3852 0.3624 0.2498 0.5100760 Baton Rouge, LA MSA 602,894 0.6430 0.3162 0.3926 0.6377840 Beaumont-Port Arthur, TX MSA 380,080 0.6493 0.3856 0.3315 0.5801860 Bellingham, WA MSA 166,814 0.2952 0.2149 0.2939 0.4214870 Benton Harbor, MI MSA 162,453 0.7250 0.4102 0.3729 0.6347875 Bergen-Passaic, NJ PMSA 1,372,791 0.6253 0.5049 0.3916 0.5429880 Billings, MT MSA 129,352 0.3126 0.2650 0.2720 0.4282173
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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
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developing strategies to deconcentr
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y subsidy type. The correlation bet
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with a poverty rate of 9.2 percent.
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The cluster is relatively small con
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Cluster 7: Other Site-Based Units -
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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
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TABLE 6.1Subsidized Units by Cluste
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FIGURE 6.1Percent Census Tracts by
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FIGURE 6.5Census Tract Percent Rent
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Cluster - Concentration -PovertyCen
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strategies. The cluster map shows t
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FIGURE 6.9Map of Public Housing Uni
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Cluster 1: Voucher/No Subsidized Un
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considered moderately concentrated
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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 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
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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