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

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Author Date Data GeographyLee 20081996-2002 Five MSA'sType ofProgramPublic housing,other HUDsite-based, andLIHTCOutcomeMeasures Method FindingsHedonic regression usingdifference-in-differencespecification on propertieswithin 2,500 feet of subsidizedhousing that were either addedor removed during the studyperiod.Property valuessurrounding thesubsidizedhousingResults varied by type of housing, proximityand concentration. Public housing additionsreduced home values while LIHTC resultsare mixed. The number of units added orremoved was very important with positiveeffects depending on the number of units.Buron, Nolden,Heintz andStewart (AbtAssociates) 20001992-199439 Projectsin 5 MSA'S:Boston,Kansas City,MiamiMilwaukeeand OaklandLIHTCFreeman 2004 2000 All MSA's LIHTCLIHTCExtent ofconcentration ofsubsidizedhousingExtent ofconcentration ofsubsidizedhousingDescriptive statistics ongeographic location of LIHTCunits.Descriptive statistics ongeographic location of LIHTCunits.LIHTC projects are serving low incomehouseholds (74%) but have a significantlevel of section 8 assistance (37%) most inthe form of site-based subsidies. Projectsvaried as to economic diversity with halfhaving more than 50% under 30% MFI.Neighborhoods were income diverse buthad high minority rates. Half ofdevelopments were located in QualifiedCensus Tracts (QCT's). Recommendationsfor further study include comparison ofwhere LIHTC and Section 8 residents liveand more in depth study of the impact ofLIHTC properties on their neighborhoods.Slightly less than half of LIHTC units arelocated in the suburbs which is higher thanother federally funded site-based projects(24%). LIHTC neighborhoods are raciallyconcentrated but experienced larger declinesin poverty during the 1990's than otherneighborhoods. Policy recommendation tosite more family units outside high povertyand high minority city neighborhoods.192
Author Date Data GeographyKhadduri, Buronand Climaco(Abt Associates) 2006Eriksen andRosenthal 20071995-2003O'Neill 2008 2000Type ofProgram182 MSA'swithpopulationsover250,000 LIHTC1987-2000 National LIHTC25 mostpopulouscitiesLIHTCOutcomeMeasures Method FindingsPoverty and raceat the census tractlevelChanges inhousing marketproduction (newunits over time)Extent ofconcentration ofsubsidizedhousingDescriptive statistics of familyunits in low-poverty censustracts.OLS and GMM regressionanalysis controlling for MSAlevel factors calculated atvarious distance neighborhoodscales. LIHTC units increases orreduces the overall number ofaffordable units in the housingmarket ("crowding out" effect)and whether it shifts demandwithin the neighborhood.Regression controls for housingdemand. Measuresneighborhood at various distancerings from census tract centroid.Dataset includes public housingdemolitions and date ofintroduction of LIHTC unitswhich is not included in manyother studies."Hot Spot" cluster analysis ofthe spatial distribution of LIHTCunits. An index was developedon the extent of clustering at thecity level and cities were rankedby their index score in order tocompare levels of concentrationbetween cities.The percentage of units constructed in lowpoverty areas has increased over time.There are differences in the location ofLIHTC units between the states.Results vary considerable by neighborhoodincome. In higher income neighborhoodsthe addition of 100 LIHTC units isassociated with 80 fewer unsubsidizedrental construction units and a 6% decreasein owner-occupied units. In the lowestincome neighborhoods the same 100 LIHTCunits is associated with an increase of 17rental construction units and a 1 percentincrease in property values.There was extensive clustering of LIHTCunits in the study cities with the clusteringconsidered extreme in some cases. Theclustering varied by city and was associatedwith poverty in some but not all cities.193
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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
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tracts than other subsidy types it
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ecommend efforts to reduce the leve
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scale at which the impacts occur; 2
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units. Given the high cost of these
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REFERENCESAbt Associates, I. (2006)
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Briggs, X. d. S. (Ed.). (2005). The
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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
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 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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