40 50 60 70 80 90 100 110 120 Washington, DC W. Shaw E. Shaw 1999 1998 1997 1996 1995 1994 1993 1992 0,000 0,000 0,000 0,000 0,000 Judkins City-Wide 1Q99 1Q 98 3Q 97 3Q 96 3Q 95 0 50 100 150 200 250 300 350 400 450 Houston 77020 77026 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 0 50 100 150 200 250 300 350 400 450 Houston 77020 77026 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 Lindley R. Higgins A Collaboration between The Local Initiatives Support Corporation’s Center for Home Ownership and George Mason University’s School of Public Policy April 2001 FIRST IN A SERIES OF WORKING PAPERS ON HOMEOWNERSHIP ISSUES Measuring the Economic Impact of Community-Based Homeownership Programs on Neighborhood Revitalization
The Local Initiatives Support Corporation’sCenter for Home Ownership
and
George Mason University’s School of Public Policy
April 2001
F I R S T I N A S E R I E S O F W O R K I N G PA P E R S O N H O M E O W N E R S H I P I S S U E S
Measuringthe
Economic Impactof
Community-BasedHomeownership Programs
on
NeighborhoodRevitalization
Question:Is it possible to quantify theimpact of community develop-ment organizations’ low-incomehomeownership programs onneighborhood revitalization
Foreword
Community development cor-porations (CDCs) have beenimproving neighborhoods for
years. Comeback Cities, a recentstudy of the increasing vitality ofAmerican cities by Paul Grogan andTony Proscio, observes that “CDCsare actually a way for ordinary peo-ple to change, create, and make useof market forces to alter the funda-mental economics of their neighbor-hoods… They are among the mosteffective vehicles for public invest-ment in the inner city.”
True. But while there is abundantanecdotal evidence of CDCs’ effec-tiveness, the development of meth-ods to systematically measure theireconomic impact has not kept pace.This analysis takes an important firststep toward establishing a generallyacceptable methodology to quantifytheir value as engines of economicrevitalization.
The case studies presented hereare of neighborhoods that haveexperienced positive change as aresult, in large part, of CDC inter-ventions. They were among a num-
ber of communities identified byLocal Initiatives SupportCorporation (LISC) program offi-cers as having notably effective CDCaffordable housing programs.
Anyone involved in creatinghousing and homeownership pro-grams, in neighborhoods strugglingto maintain or restore their viability,knows that the ripple effects extendfar beyond the initial construction orrehabilitation of shelter. Affordablehousing and homeownership initia-tives can stabilize a neighborhood,increase real estate values, stimulatelocal business development, andreduce crime.
All this we know from experi-ence, but experience alone does notgive us all the tools we need to sys-tematically promote the most effec-tive use of CDC resources, identifybest practices, and attract greaterpublic and private support for CDCinitiatives. This report is a good startat giving us the additional tool ofmeasurement. Further research willbe needed to refine and augmentthe approach outlined here.
This is the first in a series ofworking papers sponsored by LISC’sCenter for Home Ownership. LISCis pleased to be collaborating withGeorge Mason University’s Schoolof Public Policy, which is committedto supporting research that makessubstantive contributions to thedevelopment and implementation ofpublic policy, both at the nationallevel and in the Washington, D.C.,region. The author, Lindley R.Higgins, is a doctoral candidate atthe School of Public Policy and anindependent consultant specializingin studies of low-income housingand urban economic development.Our thanks to him for carrying out adifficult assignment and producingan exemplary report.
Harold O. WilsonDirectorLISC Center for Home
Ownership
Stephen S. FullerSchool of Public PolicyGeorge Mason University
Community-based efforts torevitalize neighborhoods havehad a significant impact on
many the of nation’s inner cities.However, the community develop-ment corporations (CDCs) leadingthese efforts are increasingly calledupon to demonstrate their impacts inquantitative, economic terms. Thisresearch focuses on two questions:
■ Can the impact of community-based homeownership efforts bequantified in terms of economic indicators?
■ Are there identifiable thresholdsof development at which changes inthese indicators accelerate?
The first question is raised by theneed for community-based organiza-tions to move beyond anecdotal infor-mation in demonstrating that theirefforts have an impact. The ultimateaim of this line of inquiry is to developa method that community groups canuse to demonstrate their impact inquantitative terms. The second ques-tion addresses the dynamics of revital-ization: Is there an identifiable point atwhich community developmentefforts, by changing the perceptionsabout a neighborhood, begin to attractmore private, profit-seeking investmentthat triggers a synergistic accelerationof recovery and development?
Five case studies of urban neigh-borhoods – in Kalamazoo, Houston,Seattle and Washington, D.C. – areanalyzed. In each of these cases, com-munity-based organizations, primarilyCDCs, created a significant amountof affordable for-sale housing. Datawere gathered on the timing andlocation of this housing developmentand the effect of this development onthree indicators:
■ residential real estate markets; ■ commercial activity; and ■ crime rates. Interviews were conducted with
individuals who were closely involvedwith economic change in the neigh-borhood, including bankers, localgovernment officials and communityrepresentatives, to help understandthe impact of the housing develop-ment on these three indicators.Preliminary research findings werepresented and critiqued at a round-table of community development academics and practitioners.
The evidence suggests that in fourof the five case studies, community-based for-sale housing developmenthad a demonstrable impact on theneighborhood economy and that thisdevelopment was the primary driverof revitalization. While residential realestate values were significantlychanged in only three of these cases,other indicators of positive impacts onthe real estate market were noted inall four. (Single-family or single-unittownhouses were used to estimate thechange in real estate prices in twocase studies; mortgage amounts wereused in the other three.) Retail saleswere positively affected in the twocases where such data were available.Crime incidences showed sharpdeclines in three cases.
Residential real estate priceschanged significantly in the Seattlecase, with the average price for a sin-gle-family home doubling in a three-and-a-half year period, compared to anincrease of about 30 percent in the cityas a whole. This increase is evidenteven when accounting for the size ofthe house and inflation, with medianprice per square foot in the neighbor-
hood increasing by more than 50 per-cent between 1996 and 1999 in con-stant dollars. However, the portion ofhome sales under $100,000, whichhad averaged more than 25 percent inthe neighborhood from 1991 to 1996,declined to less than 10 percent by1999 (constant dollars). In addition,between 1995 and 1999 the price ofrental units increased at twice the rateof the city as a whole.
In the Washington, D.C., case,real estate prices in one part of theneighborhood examined did increasesignificantly, but the intervieweesattributed much of that change tofactors other than CDC homeowner-ship programs. Residential real estateprices did not show any increase inthe other part of the neighborhood,particularly after accounting for infla-tion and home size. For two of theother three case studies—one of thetwo in Kalamazoo and one inHouston—mortgage amounts didshow significant increases even whencompared to increases for their coun-ties. The other Kalamazoo case studyshowed sharp increases in number ofmortgages originated and buyerincome between 1998 and 1999.
In regard to commercial activity,the Seattle case study also showed alarge increase in both retail sales andcommercial real estate sales. Retailsales in the neighborhood more thandoubled between 1996 and 1999compared to 32 percent in the city asa whole. The value of commercial realestate sales also doubled in value toan average of $8 million per yearbetween 1996 and 1999 after havingaveraged less than $4 million per yearfor the previous 10 years.
In the Houston case, indicators of
Executive Summary
certain types of retail sales improvedsteadily, starting a few years after thefor-sale housing development began.Sales of building materials and furni-ture increased at a much greater ratein the neighborhood than in the cityas a whole. Sales of building materialsincreased four-fold for one neighbor-hood zip code between 1992 and1999, while increasing 75 percentcitywide (in constant terms). Sales offurniture in another neighborhoodzip code increased over 150 percentbetween 1996 and 1999 whileincreasing only 9 percent citywide.
Retail sales data were not availablefor Washington, D.C., or Kalamazoo,and the data on commercial realestate sales did not lend itself to anymeaningful analysis.
Crime rates declined in the neigh-borhoods at greater rates than theircities for three of the five cases. InSeattle, total incidences of crimedeclined precipitously between 1997and 1998, dropping 53 percent in theneighborhood compared to 6 percentin the city as a whole. In Houston,incidences of violent crime decreased34 percent in the neighborhood com-pared to 4 percent citywide between1996 and 1999. In one Kalamazooneighborhood, total crime incidencesdeclined 25 percent compared to 14percent citywide between 1996 and1999, while in the other neighbor-hood the change in the number ofincidences was close to the citywiderate of change. Crime rates inWashington, D.C.’s Shaw did notdecrease at the rate they did for thecity as a whole.
A development threshold wasclearly reached only in the Seattle casestudy, although the Houston case andone Kalamazoo case did show somesigns that a threshold may have beenreached. The research yielded someinsights regarding factors that mayplay an important role in reaching athreshold. These include the concen-tration in space and time of housingdevelopment, whether the housing
developed is new construction orrehabilitated, proximity to the centralbusiness district (particularly wherecommuter traffic is a problem), andthe baseline economic conditions ofthe neighborhood when housingdevelopment began.
The case studies also showed thatrevitalization efforts, particularlywhere a development threshold isreached, can create an impetus forgentrification to occur in the neigh-borhood, with attendant problems. InSeattle, the strengthening of the realestate market also caused a reductionin the amount of affordable housingavailable for sale or rent, which couldcause the displacement of residents.In Washington, D.C., community-based housing development may havecontributed to significant increases inprices in the neighborhood, though itis likely that other factors were moreimportant. The problems caused bygentrification raise concerns aboutreaching a development threshold,and the research highlights some fac-tors that may help to predict wheregentrification is a threat.
The research also examined howthe fiscal impacts of for-sale housingdevelopment can be estimated. Thedevelopment and sale of housing pro-vides government revenues throughsales taxes on building materials andfurniture, transfer taxes on homesales, and property taxes, whichincrease as property appreciates. Forexample, furniture sales in theHouston neighborhood, which dou-bled between 1998 and 1999, provid-ed an estimated $180,000 inadditional sales taxes. In the Seattlecase, housing price increases may haveprovided an average of an additional$1,000 per house in property taxesbecause of the steep increase in hous-ing values.
The roundtable discussion of thepreliminary findings highlighted boththe strengths and weaknesses of thistype of research and suggested areasneeding further analysis. The primary
weaknesses identified were the lack ofa counterfactual (comparing a similarneighborhood without CDC for-salehousing development); the difficultyin establishing a causal link betweenthe housing development and retailsales; the limited availability of broad-ly useful baseline data against whichto track change; and the lack of analy-sis of what it was about increasedhomeownership that created change.Further research areas identifiedinclude: how more sophisticatedmethods, particularly econometricmethods, might be applied to neigh-borhood revitalization; how HomeMortgage Disclosure Act data mightbe used by community groups;whether change in the retail mix or inbank deposits might be good indica-tors; and how the negative effects ofgentrification can be mitigated.
One conclusion that can bereached from this project is that effortsto quantify the impacts of communitydevelopment, while clearly necessaryand valuable, require further refine-ment before they can supercede theanecdotal evidence upon which com-munity development organizationshave long relied. This suggests, inturn, the need to improve both kindsof evidence, for example by more sys-tematically establishing baseline dataagainst which to track both quantita-tive and anecdotal change. The forcesacting to change the economic viabili-ty of a neighborhood for better or forworse are complex. They can be cap-tured to some degree by quantitativeanalysis, but they are also the sum ofthe perceptions of those who live,work, and otherwise have a stake inthe neighborhood. In short, an accu-rate portrait of change requires bothobjective and subjective inputs, andthe goal of community developers, fin-anciers, and researchers alike should beto develop policies and programsbased on continually improving—andmaking balanced assessments of—bothkinds of information about whatworks, and where, and why.
1Community-based efforts to
revitalize neighborhoods havehad a demonstrable effect in
cities across the country. Communitydevelopment corporations (CDCs)are growing in number and capacity,as are the organizations that supporttheir work, including such nationalintermediaries as the Local InitiativesSupport Corporation (LISC). Asthese organizations gain in capacityand experience, they are able to havea greater and more visible impact oninner-city neighborhoods, but at thesame time there is also a growingneed to try to capture that impact inquantitative, economic terms. Thisresearch attempts to help fill the gapsin understanding how CDCs’ impactcan be measured and to move thequantification process forward.
Community development involvesa comprehensive approach to revital-izing distressed areas and mayinclude such diverse activities asoperating crime prevention pro-grams, providing job training andemployment services, and attractingcommercial investors. However, themost common work of CDCs is theproduction of affordable housing,often with the aim of increasinghomeownership among residents.Increasing homeownership rates isseen as an effective means forimproving neighborhoods because itaddresses several inter-related prob-lems. For example, homeownershipnot only gives residents a greaterstake in working to improve theirneighborhoods, but also increasestheir equity by increasing propertyvalues (Rohe and Stewart 1996).
Higher rates of homeownership havebeen linked to greater neighborhoodstability, increased political activityand even improved social behaviorwithin the neighborhood (Ahlbrandtand Cunningham 1979, Henig1982, Lyons and Lowery 1989,Green and White 1994, Rohe andStegman 1994, Saunders 1990).
This research examines the impacton neighborhood revitalization ofcommunity-based homeownershipprograms aimed at low-incomehouseholds. It addresses two primaryquestions:
■ Can the impact of community-based homeownership efforts bequantified in terms of economicindicators?
■ Are there identifiable thresholds ofdevelopment at which changes inthese indicators accelerate?
The first question is raised by theneed for community-based organiza-tions to demonstrate that theirefforts have an impact beyond thelargely anecdotal information uponwhich they have relied in the past.The ultimate aim of this line ofinquiry is to develop a method thatcommunity groups can use todemonstrate in quantitative termsthe economic impact of their hous-ing development efforts. The secondquestion addresses the dynamics ofrevitalization: Is there an identifiablepoint at which community develop-ment efforts, by changing the per-ceptions about a neighborhood,begin to attract more private, profit-seeking investment that causes the
neighborhood to “take off?” Theidea of thresholds related to changein distressed communities has beendefined as “…a dynamic process inwhich the magnitude of the responsechanges significantly as the triggeringstimulus exceeds some critical value”(Quercia and Galster 1999). In thiscontext, the triggering stimulus isincreased homeownership and theresponses are measured in terms ofhousing prices, commercial develop-ment and crime rates.
The findings are drawn from fivecase studies of neighborhoods where
Introduction
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ContentsIntroduction . . . . . . . . . .1
Development Thresholdsand Perceptions . . . . . . .2
community-based organizations, pri-marily CDCs, created a significantamount of homeownership opportu-nities for low-income residents. Theneighborhoods are in Kalamazoo(two neighborhoods), Houston,Seattle, and Washington, D.C. Ineach case, defining (even naming)the neighborhood was a somewhatsubjective process that was deter-mined, in part, by how the availabledata conformed to the geographicarea where for-sale housing wasdeveloped by the CDCs. Data weregathered on the timing and locationof housing developed for sale andcompared to data relating to the res-idential real estate market, commer-cial development and crime. Inaddition, interviews were conductedwith individuals who were involvedin and witnessed economic change inthe neighborhood, includingbankers, local government officials
and community representatives. Theprimary purpose of the interviewswas to determine the nature of cau-sation between the housing devel-oped for sale and the data onneighborhood conditions. The eval-uation of community-based revital-ization efforts may be best achievedusing a mix of quantitative and qual-itative analysis (Briggs and Mueller1997). A more detailed descriptionof the methodology, particularly thegeographic fit of data to neighbor-hoods, is provided in the Appendix.
The next section defines develop-ment thresholds and examines theimportance of perceptions aboutneighborhoods. A brief descriptionof each of the case studies follows,with a focus on the nature of causali-ty between the housing developmentand the indicators examined for eachcase. The following three sectionsdescribe changes in the indicators:
1) the residential real estate market,measured by changes in single-familyhome prices or mortgage values, andsupplemented where necessary byother mortgage-related data; 2)commercial development, measuredby retail sales and commercial realestate sales; and 3) crime rates, meas-ured by the total number of inci-dences of crime and the incidencesof violent crime. Then the cases areexamined regarding whether there isevidence to support the thresholdhypothesis. There follows a demon-stration of how the effects of non-profit housing development ongovernment revenues can be estimat-ed. The final sections describe theimplications of the research’s find-ings on community developmentpractices and identify opportunitiesfor future research.
The economic viability of aneighborhood is a matter thatcan not be determined solely
through quantitative analysis. It isalso the sum of the perceptions ofthose who live, work and otherwisehave a stake there. Whether theneighborhood is in a state of decline,stability or revitalization is, at least inpart, a matter of opinion. How aneighborhood is trending can bedefined as a function of the percep-tion of residents, investors, financial
institutions and local governmentconcerning the future viability of theneighborhood (Ahlbrandt andBrophy 1975, p. 6). Their percep-tions are affected by observablephysical and social characteristics,such as the age and condition of thehousing stock, the state of the streetsand sidewalks, and the appearanceand attitudes of people seen on thestreet, as well as how these character-istics have changed over time. Theseperceptions may be the most impor-
tant factor affecting investment inthe neighborhood.
Investors’ perceptions of a neigh-borhood’s viability are based in parton what they see first-hand in aneighborhood and in part on theinformation they receive from others.Thus their actions will be based to acertain extent on how others behave.If enough attitudes toward a neigh-borhood change, this will have aneffect on the attitudes of others. Forcertain activities, there is a common
dynamic described by ThomasSchelling (1978):
“…[P]eople’s behavior dependson how many are behaving a particu-lar way, or how much they arebehaving that way… how many leavethe dying neighborhood and howmany leave the school.” (p. 94; italics in original)
The phenomenon of enough peo-ple behaving in a particular way isknown as attaining a “critical mass,”a term adopted from nuclear engi-neering. Critical mass models, what-ever the discipline, involve someactivity that is self-sustaining oncethe measure of that activity passes acertain level. In some cases, criticalmass may be reached by absolutenumbers (“I’ll attend those commu-nity meetings if there are at least tenother people there”) or by a ratio,such as racial “tipping points.” Themodels can involve a process of “tip-ping-out,” such as white householdsleaving a neighborhood as blacksmove in, or “tipping-in,” such as anincreasing number of people decid-ing a neighborhood is newly viable.In both cases, the process mayinvolve expectations—not waitinguntil actual numbers measurablyincrease, but being confident of anobserved trend (Schelling 1978,p.101).
If such a dynamic were to influ-ence the decision of investors regard-ing the viability of a neighborhood,there would be an observable pointat which investment in that neigh-borhood would begin to increase ata greater rate. That point may bedescribed as the “developmentthreshold” at which attitudes aboutthe neighborhood’s viability, based
on expectations of future growth,have changed enough that investorssee the potential for an attractivereturn. As investment comes into theneighborhood and improvementsoccur, there may be something of aself-fulfilling prophecy: critical massis attained and the reaction becomesself-sustaining.
One question addressed in thisresearch is what constitutes a criticalmass of homeownership by residents.Past research has concluded that twoof the most important factors affect-ing neighborhood trends are the rateof homeownership and the strengthof neighborhood institutions, such ascommunity organizations andchurches (Downs 1981, p. 66;Ahlbrandt and Brophy 1975, p. 25,32). Homeownership can be seen ashaving a number of stabilizingeffects on a neighborhood, includinglength of resident tenure, propertyvalues, physical conditions and socialconditions (Rohe and Stewart1996). The relationship betweenincreased homeownership and hous-ing values is examined here throughthe former’s effect on perceptions ofneighborhood viability. Crime rates
are likely to affect both perceptionsand housing prices and are thereforeincluded in the analysis. Since CDCsalso see developing housing andrestoring the housing market as thefoundation for establishing businessenterprise and other economic devel-opment activities (Stoutland 1999,p. 202), the health of the businessenvironment is also examinedthrough retail sales and commercialreal estate activity. Thus it is hypoth-esized that increased homeownershipcreated by CDCs affects perceptionsof the neighborhood and, along withcomplementary programs, helpsreduce crime rates, which furtherimproves perceptions of neighbor-hood viability. This in turn has aneffect on housing prices and subse-quently on the business environment(Figure 1). In addition, changes in aneighborhood’s economy are affect-ed by factors relating to growth anddecline of the economy, and crimerates, across the entire city (exoge-nous factors) and these are thereforealso taken into account in the casestudies.
Figure 1: Theorized Effect of Increased Homeownership on a Neighborhood
CDC Home-OwnershipPrograms
Perceptions ofNeighborhood
ConditionsHousing
CommercialCrime
PreventionCrimeRates Exogenous
Effects
3Overview of the Case StudiesSeattle’s Judkins Park
Digging a tunnel for Interstate90 through the Central Areaof Seattle had a particularly
devastating effect on Judkins Park, aneighborhood cut in half by thehighway. By the time the tunnel wascompleted in 1991, the sections ofJudkins Park near the constructionhad seen a significant decline in thequality of the housing stock, but the
vacant land and abandoned housingalso offered an opportunity torebuild. Although attempts weremade to find private companies will-ing to take on development, no suc-cessful development projects cameabout until a community develop-ment corporation, HomeSight, wasformed by local leaders. These lead-ers saw an opportunity, in an areariddled with crime and scarred by
the after-effects of highway construc-tion, that private developers did not.HomeSight then negotiated success-fully with the city for the right-of-first-refusal for the development ofmuch of the vacant land around theI-90 corridor.
Judkins Park is located nearSeattle’s central business district.HomeSight’s housing developmentis in a concentrated area comprising
seven census block groups, aboutone square mile in area.
These block groups are spreadacross four larger census tracts, andit is these four tracts that define theboundaries of the Judkins Parkneighborhood for this study.According to the 1990 Census, theseven block groups had a populationof about 3,500 and contained 1,400housing units. The four census tractshad a population of 16,400 and con-tained a little more than 7,000 hous-ing units. These tracts had a higherpoverty rate and lower averagehousehold income than the cityoverall, and these values were moreextreme in the block groups (Table1, next page). However, homeown-ership rates were close to the cityaverage. Housing values were muchlower, with all but one of the seven
block groups having median housingvalues under $87,000 compared to acitywide median value of $136,500.
Map 1: The Judkins Park Neighborhood and Census Tracts
Map 2: HomeSight’s Housing Development inJudkins Park by Census Block Group
LakeWashington
Source: Environmental Systems Research Institute (ESRI)
Source: ESRI
The prices for the census tracts aresomewhat skewed by those homesthat are lakefront properties on thevery eastern edge of Judkins Park.
HomeSight’s housing develop-ment moved quickly, thanks to a$2.5 million Nehemiah grant fromthe U.S. Department of Housingand Urban Development and LISCloan guarantees. The first single-family houses were completed in1993, and by 1999 more than 150units had been completed. In 1997,at the height of production, theCDC completed 71 units (Table 2).
The housing developed byHomeSight appears to have been theprimary cause for much of theincrease in residential real estateprices in the area. According tothose interviewed for the study, pri-vate developers had been eitherunwilling or unable to build homesin the neighborhood. Thus it isunlikely that much new developmentwould have occurred withoutHomeSight’s intervention. WhileJudkins Park did have the advantageof proximity to downtown, it wasalso known for drive-by shootings,open-air drug markets and prostitu-tion, and the neighborhood hadbeen made more physically unattrac-tive by the residual effects of the I-90 construction work.
HomeSight’s development of for-sale housing also played an impor-tant role in reducing crime in the
area. Increased homeownership anda close relationship betweenHomeSight and other community-based organizations and the SeattlePolice Department eventually pro-duced significant decreases in bothviolent and property crimes. Part ofHomeSight’s role in crime reductionwas providing moral and politicalsupport to early homebuyers whowere threatened by local drug dealers.
Interviewees stated that housingdevelopment by HomeSight was asignificant factor in attracting andkeeping businesses in the area. Thelocal commercial strip mall had haddifficulty in filling vacancies. Effortsby the city and the local develop-ment authority also helped improvethe business climate. The establish-ment of a Walgreens drug store anda Starbucks coffee shop were impor-tant milestones in commercial devel-opment. While many factors mayhave motivated business owners toinvest in Judkins Park, intervieweesstated that they believed increasedhomeownership played a major role.
Houston’s Fifth WardHighway improvements also
played a large part in the decline ofHouston’s Fifth Ward, once a thriv-ing neighborhood and the birthplaceof many of Houston’s most accom-plished citizens. Barbara Jordan, thefirst black Congresswoman from theSouth, Congressman and humanrights activist Mickey Leland, civilrights pioneer Dr. Lonnie Smith,jazz great Joe Sample, and GeorgeForeman, heavyweight boxing cham-pion, all hailed from the Fifth Ward.The development of Route 59 cutoff the center of Fifth Ward’s com-mercial district from the rest of theneighborhood, and both subse-quently collapsed. Neighborhooddecline and increases in crime andpoverty followed.
In 1979, Texas Monthly describedthe Fifth Ward as “Texas’ baddestghetto,” and it has long been knownas “the Bloody Fifth” because of itshigh rates of violent crime. By 1990,the nine census tracts that make upthe heart of the Fifth Ward had apoverty rate of over 60 percent(Table 3, next page).
Bounded by Route 59, Interstate610, the Buffalo Bayou andLockwood Avenue, the Fifth Ward isa few miles from Houston’s down-town (Map 3). Aside from its highpoverty rate, the neighborhood alsosuffered from very low homeowner-ship rates and housing values. Itsmain commercial corridor, LyonsAvenue, had few healthy businesses.
Table 1: Selected Characteristics for Judkins Park and Seattle, 1990
Poverty Ave House- HO* MedianRate hold Income Rate Housing Value**
7 Block Groups 22.0% $24,243 42.6% $83,293
4 Census Tracts 17.4% $35,108 44.3% $114,815
City of Seattle 12.4% $38,895 46.5% $136,500
*Home Ownership**Weighted average of median home prices in block groups and tractsSource: Census Bureau
Table 2: Annual Number of Single-Family Homes Developed byHomeSight
Habitat for Humanity came intothe Fifth Ward in 1989, bringing
volunteers to work alongside resi-dents building homes. One of those
volunteers was an experienced devel-oper who, with the encouragementand support of local clergy, set upthe Fifth Ward CommunityRedevelopment Corporation (CRC).Fifth Ward CRC began housing pro-duction in 1992 and by 2000 hadproduced 101 units of affordablesingle-family housing (Table 4). Thisdevelopment was supplemented byHabitat development, involving 54units built there and in an adjacentcensus tract during a Jimmy CarterProject in the summer of 1998.Between Habitat for Humanity,Houston and Fifth Ward CRC, atotal of 190 units of affordable hous-ing have been developed in the areasince 1990. In addition to the hous-ing development, Fifth Ward CRCand a sister CDC, Pleasant Hill, havebuilt a 182-unit senior citizen home,two commercial malls, and rentalhousing (which is doubling as ahomeownership incubator), alongwith a sense of community thatbrings residents out to neighbor-hood clean-up projects.
Those interviewed about develop-ment in the Fifth Ward generallyattributed positive change in theneighborhood to the homes builtthere by Fifth Ward CRC andHabitat. One described the neigh-borhood as a “self-contained eco-nomic unit” because of its physical
Table 3: Selected Characteristics for Fifth Ward and Houston, 1990
Poverty Ave House- HO MedianRate hold Income Rate Housing Value*
Fifth Ward 60.2% $15,561 28.6% $25,716
City of Houston 20.7% $37,296 37.9% $57,100
Harris County 15.7% $41,391 45.5% $62,600
*Weighted average of median home prices in nine tractsSource: Census Bureau
Map 3: Houston’s Fifth Ward: For-Sale Housing Development by Fifth Ward Community Redevelopment Corporation andHabitat for Humanity
Table 4: Single-Family Housing Developed by Fifth Ward CRC and Habitat for Humanity, Houston
Comulative Total 10 30 38 44 57 68 95 106 170 182 19035 developed in tract adjacent to Fifth Ward.Source: Fifth Ward CRC and Habitat for Humanity, Houston
Source: ESRI
DenverHarbor
isolation from the rest of thecity. No private developershad been interested in build-ing in the area, in partbecause of the high crimerate. While the neighborhoodshould have benefitted frombeing reasonably close todowntown, no other develop-ment projects had come toFifth Ward prior to the workof Fifth Ward CRC. Althoughthe Fifth Ward was seen bymost of the interviewees as aneighborhood still in transi-tion, recent newspaper arti-cles have begun to makepeople more aware of itspotential.
Kalamazoo’sNorthside andEdisonNeighborhoods
Two neighborhoods wereexamined in the southwest Michigancity of Kalamazoo: Northside andEdison (Map 4). These neighbor-hoods, like the city in which they arelocated, are much smaller than thoseexamined in the other case studies.Each consists of two census tracts.Northside had a population of justover 6,200 in 1990, and is the pre-dominantly African-American sectionof Kalamazoo, with 85 percent of itspopulation African-American com-pared to 18.8 percent citywide.More than one-third of all African-Americans in the city lived in thosetwo census tracts in 1990. Edison,with a population of about 8,500 in1990, was more diverse than the restof the city in its racial distributionand had a large portion of the city’sHispanic population.
In 1990, the two neighborhoods,particularly Northside, had lowerincome levels than the city overall(Table 5). Northside also had a
much higher poverty rate than thecity as a whole, and its median hous-ing value was less than half that ofthe overall city. However, homeown-ership rates were higher in Northsidethan in either Edison or the cityoverall. Edison had a lower housingvalue than the city as a whole, butwas similar in homeownership andpoverty rates.
The primary nonprofitprovider of low-income hous-ing for sale is KalamazooNeighborhood HousingServices (KNHS), althoughthe Kalamazoo NorthsideNonprofit HousingCorporation (KNNHC) andKalamazoo Valley Habitat forHumanity have also beenvery active. KNHS beganoperations in 1980 by provid-ing small home improvementloans. During the 1980s, theorganization began to focuson rehabilitating housing tosell to low-income residents.Since 1989, KNHS, KNNHCand Habitat have rehabbedover 375 homes for sale tolow-income residents ofEdison and Northside (Table6). These sales were aug-mented by a significantamount of housing rehabi-litation by the City of
Kalamazoo, which has completedover 150 units in the two neighborhoods.
Interviewees stated that increasedhomeownership and housing devel-opment have made a difference inthe two neighborhoods, particularlyNorthside. Strong neighborhoodorganizations have also helpedimprove public perceptions of both
Map 4: Kalamazoo’s Northside and EdisonNeighborhoods: Community-Based HomeOwnership Development
Source: ESRI
Table 5: Selected Characteristics for the Northside and EdisonNeighborhoods and the City of Kalamazoo, 1990
Poverty Ave House- HO MedianRate hold Income Rate Housing Value*
Northside 52.1% $15,834 49.9% $21,800
Edison 26.9% $22,018 41.3% $30,761
Kalamazoo City 26.2% $31,276 44.2% $47,600
Kalamazoo County 13.5% $38,109 60.6% $62,500
*Weighted for neighborhoods by number of unitsSource: Census Bureau
neighborhoods, as have other typesof development. In Northside,brownfields rehabilitation hascleaned up large properties that hadformerly been industrial sites. Animportant sign of revitalization hasbeen the market-rate housing devel-oped there by KNNHC. Northsidehas also experienced recent commer-cial development activity, and a largepart of that is attributed to the hous-ing development.
In Edison, the construction ofBronson Hospital on the easternedge of the neighborhood hashelped to spur some developmentaround it. However, Edison is seenas a neighborhood that still needsmuch improvement and is hamperedby public image problems. The pres-ence of “adult” businesses alongPortage Road, Edison’s main com-mercial corridor, has had a chillingeffect on further commercial devel-opment there. The neighborhood’srelatively high crime rate alsoremains a barrier to commercialdevelopment.
Washington, D.C.’sShaw Neighborhood
Once the center of African-American culture in Washington,Shaw’s decline accelerated when itbecame the flashpoint for the riotsfollowing the assassination of MartinLuther King in 1968. Much of thedestruction left by the riots went
untouched for over a decade; mid-dle-class households moved away;and little development of any kindtook place in the neighborhood.However, the completion of theReeves Municipal Center in 1986,which provided jobs and stimulatedlocal business development, markedthe beginning of Shaw’s economicturnaround. Five years later theopening of a Metro subway stationon U Street spurred the revitaliza-tion of Shaw’s primary commercialcorridor as well as stimulating hous-ing in a neighborhood newly linkedby the subway to employmentopportunities throughout the metro-
politan area. The reopening of theWhitelaw Hotel and the LincolnTheatre, important landmarks of theAfrican-American cultural heritage inWashington, have also been indica-tors of neighborhood recovery.
Shaw is located in the heart ofWashington, just north of the centralbusiness district. Adjoining Shaw tothe west is the Dupont Circle area, asignificantly higher-income neigh-borhood with a healthier residentialreal estate market and much greatercommercial activity. Shaw compriseseight census tracts with a populationof 21,685 in 10,500 housing units in1990. Poverty rates are higher thanin the city overall, and householdincome and homeownership rates arelower (Table 7). However, theseindicators vary widely across theneighborhood. For example, povertyrates ranged from a high of 27.7 per-cent to a low of 9.0 percent acrosstracts, and homeownership ratesranged from 6.8 percent to 42.2 per-cent. Thus it is risky to make gener-alizations about Shaw as a singleneighborhood. Because of this diffi-culty, and the changes observed since
Map 5: Washington, D.C.’s Shaw Neighborhood: Community-BasedHousing Development
Table 6: Single-Family Housing Developed in the Edison and North-side Neighborhoods, With Cumulative Totals, 1989-99
Cum. 7 16 25 34 53 62 77 88 106 130Source: W.E. Upjohn Institute for Employment Research
Source: ESRI
1990, the most western two tracts—with 38 percent of the 1990 popula-tion—will be referred to here asWest Shaw, with the remainder iden-tified as East Shaw.
The two local CDCs have focusedmost of their single-family for-salehousing on the east side of theneighborhood and their multi-familyhousing more on the west side. Since1983, the two CDCs—Manna andNorth Capital NeighborhoodDevelopment Corporation(NCDC)—have developed 74 unitsof single-family housing and 154units of multi-family condominiumsand cooperatives (Table 8). In addi-tion, there has been significant pri-vate-sector investment in Shaw inrecent years, including the buildingof a convention center and develop-ment of many high-priced condo-miniums. West Shaw, in particular, isnow getting much of the same kinds
of higher-priced housing that theDupont Circle neighborhood isknown for.
Interviews suggest that Shaw’srevitalization is attributable to severalfactors, with the housing developedby nonprofits overshadowed byother developments, in particular theopening of the Reeves MunicipalCenter, which provided a directsource of employment and boostedretail trade through the service facili-ties around it. The opening of theMetro station was also cited as par-ticularly important in making theneighborhood more attractive forcommuters. Declining crime ratesand high housing costs in DupontCircle helped attract more middle-income households to Shaw. Someinterviewees argued that the multi-family units developed in West Shawalso helped provide the stimulus to
make the area more attractive tomiddle-income buyers.
It is difficult to estimate the effectof nonprofit housing on retail trade,since the city does not collect busi-ness data in a manner that can beanalyzed at the neighborhood level.(And the city government is onlybeginning to automate many of itsdata processing systems.)
Case StudyComparisons
The CDCs in these case studiesare engaged in more than housingdevelopment alone. For example,homeowner education programs andvarious forms of financial assistanceare considered crucial to their devel-opment efforts. Homeowner educa-tion programs are seen as an effectivemeans to create pools of potentialbuyers and reduce mortgagedefaults. Financial assistance pro-grams primarily help bridge the gapsbetween the limited funds that low-income households can provide for adown payment and the minimumneeded to secure a mortgage. Whilethe importance of these programsshould not be underestimated, adetailed description of how eachCDC helped residents realize thegoal of owning their own home isbeyond the scope of this report.
Similarly, the CDCs in these casestudies were involved in a variety of
Table 7: Selected Characteristics for Shaw Neighborhood andWashington, D.C., 1990
Poverty Ave House- HO MedianRate hold Income Rate Housing Value*
Shaw (8 tracts) 21.4% $30,015 20.0% $168,054
East Shaw (6) 20.0% $28,685 22.9% $120,209
West Shaw (2) 23.7% $31,919 16.2% $232,788
Washington, DC 16.9% $44,413 34.9% $121,700
*Weighted average of median values for tractsSource: Census Bureau
Table 8: Single-Family Houses and Multi-Family Units Developed by Manna and NCDC, 1983-2000
Total units developed: 74 Single-family, 154 Multi-family
Source: Manna and North Capital Neighborhood Development Corporation
4
community revitalization efforts.Many are involved either directly orindirectly in stimulating commercialdevelopment, and all work to lever-age their effectiveness by partneringwith other community-based organi-zations. Indeed, an important char-acteristic of all the housing programswas that they involved multiple part-nerships with public and privateorganizations. The most importantpartner in most cases was the localgovernment, with much financialassistance coming from city housingand community development pro-grams. However, local governmentwas also often cited as an impedi-ment to development, primarilybecause of bureaucratic delays thatincreased costs and at times jeopard-ized the success of some projects.
Banks also played an important rolein most cases, working closely withthe CDCs to make sure loans werebankable and to provide financialand technical support. Every CDCalso cited the importance of LISC’sfinancing and technical assistance.
The most significant differencebetween the CDC developmentefforts was the type of housingdevelopment undertaken. Seattle’sHomeSight, working with largevacant lots, built new homes, oftenin large clusters, creating cohesivesmall housing developments on thelots south of I-90. In contrast,Houston’s Fifth Ward CRC andHabitat built primarily new homesand rehabilitated older homes indevelopments intermingled with theolder housing stock. This led to
some sharp contrasts on a singlestreet, with three brand new housessitting next to three weather-beatenolder houses. Washington’s Mannaand NCND used the available hous-ing stock, doing significant rehabili-tation for the most part and somecompletely new construction. Thehomeownership opportunities theycreated were scattered in some casesand concentrated in others.Kalamazoo’s KNHS primarily pro-vided financing for housing rehabili-tation, with KNNHC and Habitatresponsible for the few new homesbuilt in the neighborhoods. Thesedifferences in how houses weredeveloped and grouped are likely tohave affected the economic impacton each neighborhood.
Community-based for-salehousing development can beshown to have had some posi-
tive impact on the local economies infour of the five case studies. (Only inWashington, D.C., were changes inthe indicators attributed to other factors.)
The impact of CDC housing wasmost readily quantifiable in Seattle’sJudkins Park, where it appears tohave stimulated a large amount ofprivate investment in the area andthe neighborhood indicatorschanged significantly.
Houston’s Fifth Ward, wherehousing development and comple-mentary programs by nonprofitswere seen as the primary driver ofchange, experienced increases inboth mortgage amounts and the
incomes of homebuyers after 1996,and the number of mortgages steadi-ly increased until 1999. In addition,certain retail sales sectors and crimerates, particularly violent crime,changed dramatically in Fifth Ward.
Kalamazoo’s Edison experiencedsteady increases in mortgageamounts after 1995, while Northsidehad large increases in 1999 in home-buyers’ incomes and the number ofmortgages originated.
For Washington, D.C., for-salehousing development was not seenas the most important contributor tooverall change in Shaw. Availableindicators did not show any mean-ingful change in one part of theneighborhood, and changes in theother were more likely due to otherdevelopment projects, the neighbor-
hood’s location, and changes in thecity as a whole.
In regard to thresholds, in twocase studies there was some indica-tion of a threshold being reachedthat was likely due to the develop-ment of for-sale housing by commu-nity groups. The clearest example ofa threshold is in Judkins Park, wheredata on single-family housing prices,commercial development and crimerates, as well as the interviews, allshow that a significant change tookplace in the neighborhood duringthe 1996-97 period. For the FifthWard case study, the presence of adevelopment threshold is less clear,but a number of indicators began tochange noticeably in 1997.
Primary Findings
Residential real estate prices maybe the best indicator of neigh-borhood revitalization, since
they show the increased desire ofpeople to invest and live there. Fortwo of the case studies—Seattle andWashington, D.C.—the impact onthe real estate markets was deter-mined by the average or median saleprice of single-family homes in thecensus tracts that defined eachneighborhood. These two cases alsoallowed for an analysis of change inthe price per square foot, in order toprovide some control for housingquality. For the Kalamazoo andHouston case studies, real estateprices were estimated using mort-gage data. (Details of the methodol-ogy are in the Appendix.)
Seattle’s Judkins ParkSeattle’s Judkins Park neighbor-
hood went through its most signifi-cant changes in the 1996-97 period.Single-family homes increased at asignificantly greater rate than theyhad in the past (Figure 2) and theincreases were greater than for thecity overall (Figure 3: the quartersused in this chart were determinedby the data available from the City ofSeattle’s Department of Housing).This was also the period ofHomeSight’s greatest activity, with22 homes completed in 1996 and 71in 1997. HomeSight’s productionwas an important stimulant to thelocal real estate market, with thenumber of home sales in JudkinsPark more than doubling between
1993 and 1997.The data appear to support the
interviewees’ statements that the
new single-family homes built byHomeSight had an effect on housingprices in the neighborhood. The
$150,000
$190,000
$230,000
$270,000
$310,000Judkins
City-Wide
1Q991Q 983Q 973Q 963Q 95
Figure 3:Average Single-Family Home Prices, Judkins Park and City ofSeattle (Selected Periods: 3rd Quarter 1995 - 1st Quarter 1999)
Source: City of Seattle, Department of Housing; First American Real Estate Solutions
5Assessing Impacts on Residential Real Estate Markets
$100,000
$125,000
$150,000
$175,000
$200,000
$225,000
$250,000
$275,000
2000199919981997199619951994199319921991
Figure 2:Median Single-Family Home Prices, Judkins Park, 1991-1st Quarter 2000 (1998 Dollars)
Source: First American Real Estate Solutions
median home price in the four tractsnearly doubled between 1995 and2000 (1st Quarter) from $131,000to $259,000 (Figure 2). When aver-age single-family home prices arecompared to the overall city forselected quarters, single-family homeprices increased in Judkins Park by95 percent between 3rd quarter
1995 and 1st quarter 1999, whileincreasing only 28 percent in the cityas a whole (Figure 3).
The increase in housing values inJudkins Park during the 1996-97period holds even after accountingfor the square footage of the house.Between 1991 and 1995, price persquare foot stayed between $60 and
$70. In 1996, the price began to risesignificantly, rising to $124 persquare foot in 1999 (Figure 4).
The downside to the revitaliza-tion of housing prices in JudkinsPark was a decline in the number ofaffordable housing units available. In1991 nearly 40 percent of all single-family housing sales were for lessthan $100,000; by 1999 this figurehad declined to about 8 percent(Table 9). Even HomeSight was hav-ing difficulty keeping the homes itsold at affordable rates. Such increas-es in housing prices were not unex-pected in a neighborhood withJudkins Park’s potential and proximi-ty to the central business district, andwere also undoubtedly influenced bySeattle’s booming economy. Still,when neighborhood revitalizationdirectly or indirectly shrinks the sup-ply of affordable housing, it raisesconcerns about contributing to gentrification, clearly not the inten-tion of community developmentorganizations.
Rental prices in Seattle’s CentralArea, of which Judkins Park is a largeportion, increased 99 percent
0
15
30
45
60
75
90
105
120
$135
199919981997199619951994199319921991
Figure 4: Median Price per Square Foot of Single-Family Homes inJudkins Park, 1991-99 (1998 Dollars)
Source: First American Real Estate Solutions
Table 9: Number and Percentage of Single-Family Houses Sold each Year for Under $100,000 in Judkins Park
between 1990 and 1999. As shownin Table 10, during the past fiveyears rental prices have continued toincrease at a much higher rate forthe Central Area than for the overallcity (54 percent versus 24 percent).While rising home prices createwealth for those who have purchasedhomes, higher prices may be drivingothers out of the neighborhood.
Houston’s Fifth WardIn Houston, changes in housing
prices were extrapolated from HomeMortgage Disclosure Act (HMDA)data. This exercise was necessarybecause Texas is one of the few stateswith a “no-disclosure” law that barspublic disclosure of the sale price ofhomes. To test for the accuracy ofthis methodology, HMDA data onthe average mortgage value per yearfor each tract in Seattle’s JudkinsPark was correlated with similar dataon home sales. The correlation wasfound to be close. It thus appearsthat HMDA average mortgageamounts could be used as an accept-able surrogate for average home salesprice. Since HMDA data are relative-ly inexpensive and simple to analyze,this finding may provide a significantbenefit to community groups search-ing for ways to quantify change intheir neighborhoods.
HMDA mortgage data are avail-able from the Federal FinancialInstitutions Examination Council(FFIEC). This data set of all mort-gage applications includes: 1) thepurpose of the loan, whether it is forhome purchase, improvement orrefinancing; 2) whether the unit isfor owner-occupancy or not; 3) theaction taken on the loan, whether itwas denied, originated, withdrawn orother action; 4) the amount of themortgage applied for; 5) the incomelevel of the applicant; 6) whether theloan uses conventional or subsidized
(e.g., FHA) financing; and 7) thecensus tract in which the property islocated. From this information it ispossible to get records of theamount of originated mortgages forowner-occupied purchases for agiven neighborhood. In addition,the total number of mortgages origi-nated for owner-occupied homes,the number that were conventionalmortgages (as opposed to subsi-dized), and the average income ofthe applicants of originated mort-gages can be determined. Becausethe data are available for the years1992 through 1999, it is possible toexamine some trends in the amountof the mortgages originated and inthese other indicators of the housingmarket. However, the data forHouston may not be as reliable asthe Seattle data because there wererelatively few loans originated in theFifth Ward. Where the SeattleHMDA/sales price correlation wasbased on an average of 36 sales pertract per year and about as manymortgages, each tract in the FifthWard averaged little more than fourmortgages per year.
For the Fifth Ward, HMDA datawere analyzed from the eleven cen-sus tracts where Fifth Ward CRCand Habitat for Humanity builthomes for sale. These tracts includethe nine that comprise the FifthWard plus two adjacent tracts whereboth organizations have been active.The data for these eleven tracts werecompared to data for Harris County,which includes the City of Houston.While Harris County as a whole ismore affluent and has higher hous-ing prices than the City of Houston(Table 3), HMDA data are definedby county and not by city. Houstonmade up 58 percent of the popula-tion of Harris County in 1990 andaccounted for 62 percent of housingunits.
The HMDA data show thatmortgage amounts sharply increasedin the Fifth Ward after a steadydecline between 1993 and 1996(Figure 5). This pattern reflects, andwas likely influenced by, changes incounty-wide mortgage amounts. Thedecline was greater in the FifthWard, 34 percent over three years,than in the overall county, where
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
$100,000
$110,000
Fifth Ward
Harris Co.
19991998199719961995199419931992
Figure 5: Average Originated Mortgage Values for Owner-Occupied Home Purchase in Fifth Ward and HarrisCounty, 1992-99 (1998 Dollars)
Source: Federal Financial Institutions Examination Council
prices dropped 10 percent; but therecovery was also greater, with pricesincreasing at a much higher rate inthe neighborhood than the county(74 percent versus 18 percent).
The average income of homebuy-ers in the Ward also increased signifi-cantly during the same period thatmortgage amounts increased,approaching the average for thecounty (Figure 6). This may be anindicator of more middle-incomehouseholds seeing the Ward as agood place to invest in a home.Another sign of the health of the res-idential real estate market is theincrease in the number of loans orig-inated, which went from just 16 in1992 to 76 in 1998 before decliningto 50 in 1999 (Figure 7). This indi-cates that the work of Fifth WardRDC and Habitat for Humanitymade lending more viable over time.
Kalamazoo’s Edisonand NorthsideNeighborhoods
Real estate price changes for theKalamazoo neighborhoods were alsoestimated using HMDA data andwere compared to KalamazooCounty, which contains the City ofKalamazoo. Kalamazoo County iswealthier and has higher housing val-ues and homeownership rates thanthe city (Table 5). Kalamazoo Citymade up 36 percent of the county’spopulation and accounted for 35percent of housing units. The twoneighborhoods had very differentlevels of mortgage activity, at leastfor originated, owner-occupied homepurchases, with Edison averaging 88such mortgages per year comparedto 22 for Northside (Table 11).
On a percentage basis, mortgagevalues increased more in Edison (37percent) than in the county as awhole (27 percent) between 1992and 1999, even with an 8 percent
decline between 1992 and 1994(Figure 8). Northside mortgage val-ues increased 8 percent between1992 and 1999, but trends weremore erratic because so few loanswere originated there. However, itshould be kept in mind that evenmaintaining a similar price increase
to that of a wealthier and more eco-nomically stable suburban countywould be an accomplishment for aninner-city neighborhood.
While mortgage amounts inNorthside did not increase much,both the number of loans originatedand the average income of home-
0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
Fifth Ward
Harris Co.
19991998199719961995199419931992
Figure 6: Average Homebuyer Income for Owner-Occupied HomePurchase in Fifth Ward and Harris County, 1992-99
Source: Federal Financial Institutions Examination Council
0
10
20
30
40
50
60
70
80
19991998199719961995199419931992
Figure 7: Number of Mortgages for Owner-Occupied HomePurchases Originated for Fifth Ward Properties, 1992-99
Source: Federal Financial Institutions Examination Council
buyers increased significantly in1999 (Table 11 and Figure 9). Inaddition, the percentage of mort-gages in Northside that were con-ventional, not requiring subsidies,went from an average of 30 percentin the 1992-1993 period to an aver-age of 75 percent in the 1998-1999period. While home prices, reflectedby mortgage amounts, may not haveincreased substantially in Northside,these other indicators of the residen-tial real estate market do show astrengthening of that market.
Washington, D.C.’sShaw
The Shaw neighborhoods weredifficult to analyze because of thewide variety of housing stock locatedthere. While homes in Judkins Park,Fifth Ward, Edison and Northsideare primarily single-family houses,Shaw has units listed as multi-family,townhouse/rowhouse, condomini-um, or cooperative, as well as homeslisted as single-family but that alsowere described as having more thanone unit. Thus the data used are forsingle-family housing listed as singleunit and townhouse/rowhouse listedas single unit.
Shaw is divided by East and Westbecause of the significant changes inhousing prices that occurred in WestShaw due in part to the neighbor-hood on Shaw’s western boundary(Map 5). The Dupont Circle neigh-borhood has been a relatively high-
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
$80,000
$90,000
$100,000
$110,000
Edison
Northside
Kalamazoo County
19991998199719961995199419931992
Figure 8: Average Mortgage Value for Owner-Occupied HomePurchase in Edison, Northside and the KalamazooCounty, 1992-99
Source: Federal Financial Institutions Examination Council
Table 11: Number of Mortgages for Owner-Occupied Home Purchases for Edison, Northside andKalamazoo County, 1992-1999
Edison 41 54 99 93 107 92 98 118 88Source: Federal Financial Institutions Examination Council
0
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
$70,000
Edison
Northside
Kalamazoo County
19991998199719961995199419931992
Figure 9: Average Homebuyer Income for Owner-Occupied HomePurchase in Edison, Northside and Kalamazoo County,1992-99
Source: Federal Financial Institutions Examination Council
priced area for quite some time, andboth the interviews and the dataindicate that it is having an influenceon housing prices in West Shaw.West Shaw is considered to be thetwo most western census tracts ofShaw, numbers 44 and 50, between11th and 13th Streets, from FloridaAvenue to Massachusetts Avenue.West Shaw has about 38 percent ofthe total Shaw population and 43percent of the housing units. EastShaw consists of the remaining sixtracts, east of 11th Street to NorthCapitol.
The median price per square footof single units in East Shaw has notchanged much during the pastdecade and a half, while prices inWest Shaw have shown a markedincrease since 1996 (Figure 10).Prices per square foot in West Shawalso rose between 1987 and 1988,which may have been in response tothe completion of the Reeves Centerin 1986—identified in interviews asthe most important factor in Shaw’seconomic turnaround. The Center islocated on the western edge of Shawat 14th and U Streets. The construc-tion of the Center and its positiveimpact on the commercial develop-
ment along U Street, which was fur-thered by the opening of a Metrostation, helped bring higher housingprices east.
The Housing Price Index forWashington, D.C. was used to com-pare changes in housing prices inShaw with the rest of the city. TheHPI is an index of single-familyhousing prices from the Office ofFederal Housing EnterpriseOversight that uses data provided bythe Federal National MortgageAssociation (Fannie Mae) and theFederal Home Loan MortgageCorporation (Freddie Mac) to cap-ture changes in the value of single-family homes in the individual statesand the District of Columbia.* TheHPI provides quarterly estimates, sovalues for the city of Washington are
the average of the index for the fourquarters. While the HPI is not a per-fect indicator of housing values, itmay be the only source that providessome comparison without includingthe entire metropolitan area. Indexesof median single-family and singletownhouse/rowhouse unit prices forEast and West Shaw from 1986 to1999 were used in the comparison.(Indexes use a starting period with avalue of 100, and that value changesaccording to percentage changes inthe observed data.)
Housing prices in East Shawbegan a steady decline in 1990 thatlasted until 1996, when they beganto recover, exceeding the 1990 peakin 1998 before declining again in1999 (Figure 11). East Shaw pricesincreased 68 percent between 1996and 1999, compared to only 16 per-cent for the city as a whole.However, this strong recoveryappears weaker when square footageis taken into account. Price persquare foot has still not reached its1990 peak. Nevertheless, this doesrepresent something of a recoveryfor East Shaw and, despite thedecrease in price per unit and persquare foot in 1999, may mark thestart of East Shaw’s revitalization.
Prices in West Shaw haveincreased more dramatically. Since1996, unit prices have increased 137percent, while the price per squarefoot has increased 121 percent.While the 1999 price per unit is only16 percent higher than the peak yearof 1992, the sales price derived fromthe sales data for 1992 may be ananomaly. The cost per unit in 1999was twice as high in West Shaw asEast Shaw, and the analysis for WestShaw did not include a large numberof high-priced condominiums builtthere recently.
The HMDA data also show theincreased health of West Shaw’s resi-dential real estate market and what
Figure 10: Median Price per Square Foot, Single Unit Homes inEast and West Shaw, 1986-99 (1998 Dollars)
Source: First American Real Estate Solutions
* The HPI is a weighted repeat sales index,meaning that it measures average pricechanges in repeat sales or refinancings onthe same properties. Mortgages on prop-erties financed by government-insuredloans, such as FHA or VA mortgages, areexcluded from the HPI, as are propertieswith mortgages whose principal amountexceeds the conforming loan limit.
may be the beginning of revitaliza-tion in East Shaw. Data on mortgageamounts and homebuyer incomegenerally followed the same patternas housing price changes. However,the number of loans originated have
steadily increased in East Shaw andshow particular growth after 1996(Figure 12). The strong growth inmortgage lending, up more than150 percent in three years, is an indi-cator that the residential real estate
market there has become moreattractive to homebuyers.
SummaryThe residential real estate markets
appear to have gained strength overthe past few years in all of the neigh-borhoods examined here, thoughthis is not necessarily reflected in realestate prices or mortgage amounts.However, gentrification is a compli-cating factor in at least one of thoseplaces, and perhaps in a second. InJudkins Park, the impact of CDChomeownership programs on hous-ing prices has been strong, causingmedian prices to nearly double. Thehousing built by HomeSight seemsto have stimulated significant privateinvestment in housing in a shortperiod, but has also reduced theavailability of affordable housing forsale and rent. The cause of priceincreases in West Shaw has more todo with the influence of high-pricedhomes in the adjacent Dupont Circleneighborhood. It is not possible toestimate how much of a role the 50units of housing Manna has devel-oped there since 1997 played instimulating the price increases orwhether these increases threatenWest Shaw with gentrification.
Mortgage values increased inFifth Ward and Edison at higherrates than their counties, andNorthside and East Shaw have seen significant increases in the num-ber of mortgages originated, indicat-ing a healthier market and perhapsmarking the beginning of revitaliza-tion. The average income of home-buyers has also increased in FifthWard and Northside, demonstratingthose neighborhoods’ increasingability to attract middle-incomehomebuyers, an important aspect ofneighborhood revitalization.
50
70
90
110
130
150
170
190
E. Shaw
W. Shaw
WDC
1999199819971996199519941993199219911990
Figure 11: Index of Housing Price Changes, East and West Shawand Washington, D.C., 1990-99 (1990 = 100; 1998 Dollars)
Source: First American Real Estate Solutions
0
50
100
150
200
250
W. Shaw
E. Shaw
19991998199719961995199419931992
Figure 12: Number of Loans Originated for Owner-OccupiedHousing, East and West Shaw, 1992-99
Source: Federal Financial Institutions Examination Council
The level of commercial activityin a neighborhood is anothermeasure of private investment.
Increased retail sales and commercialreal estate activity indicate a changein the perception of neighborhoodviability by businesspeople. Whilereal estate is an important type ofinvestment in a neighborhood, it isimpossible to reach a critical mass ofdevelopment without an influx ofprivate commercial investment.However, annual data on commer-cial activity at the neighborhoodlevel are more difficult to obtain andwere available for only three of thecase studies.
Seattle’s Judkins ParkRetail sales in Judkins Park
showed a rapid increase over the pastfour years, mirroring the increaseseen for single-family housing prices(Figure 13). Retail sales in the fourcensus tracts increased by more than50 percent between 1996 and 1997compared to 10 percent for the Cityof Seattle. The increase was also sig-nificant for the two tracts (89 and90) that include South JacksonStreet, the primary commercial corri-dor for the area developed byHomeSight. Between 1996 and1997 the increase in retail sales forthese two tracts was 63 percent com-pared to an increase of only 10 per-cent for the City of Seattle. By 1999,retail sales for Judkins Park’s fourtracts had more than doubled from
their 1996 level, as had sales in justthe two tracts that included SouthJackson Street. Thus the accelerationin retail sales above the overall cityrate has continued over a four-yearperiod.
Judkins Park also saw an increasein commercial real estate activityafter HomeSight’s housing develop-ment there. Between 1986 and1995, commercial real estate sales inthe four census tracts averaged justunder $4 million per year (rangingfrom $985,000 in 1992 to $9.3 mil-lion in 1989). Since 1996, however,Judkins Park averaged over $8 mil-lion a year in commercial real estatesales and had over $3 million in salesduring the first quarter of 2000.
While figures for commercial saleswere not available for the entire Cityof Seattle, this large an increase rep-resents a significant change for theneighborhood.
Houston’s Fifth WardRetail sales data at the zip code
level are used to measure change inFifth Ward. Two zip codes cover theWard: 77020 in the south and77026 in the north. One of theproblems with zip code level data isthat it does not fit the boundaries ofthe neighborhood as well as othergeographic definitions. The southernzip code, 77020, also includes thecontiguous neighborhood of Denver
6Assessing Impacts onCommercial Activity
0
50
100
150
200
250
300
350
400
Seattle
Judkins Park
Tracts 89 & 90
1999199819971996199519941993199219911990
Figure 13: Index of Retail Sales for Judkins Park, Two Tracts (89 &90) and the City of Seattle (1990 = 100; 1998 Dollars)
Source: Research Division, Washington State Department of Revenue
Harbor to its east, and 77026includes Route 59, which has com-mercial establishments along itsaccess roads that would not beaffected by development in theneighborhood, and some areas northand west of Fifth Ward. However,this is the only form in which thesedata were available.
Retail sales within the two zipcodes were first examined in aggre-gate and compared to data for theCity of Houston. Between 1986 and1998, retail sales grew at similar ratesin the Ward as in the city overall:39.4 percent versus 37.6 percent (in1998 dollars). However, since 1995,total retail sales for the two zip codesdeclined by 7 percent while increas-ing 19 percent in the city overall.Given the inclusion of anotherneighborhood and the businessesalong and across the highway, it wasdifficult to determine the effect thathousing development has had onoverall retail sales.
In order to isolate the effect ofhousing on retail sales in the Ward,sales data were broken down to thenext level of detail. Data for the twozip codes in the retail areas ofBuilding Materials and GardenSupplies (Standard IndustrialClassification [SIC]-52) andFurniture and Home Furnishings(SIC-57) were examined, since theyappeared to be the two types of retailsales most likely to be affected by for-sale housing development by non-profits. As common sense tellsus—and studies confirm—new home-buyers spend more on household fur-nishings, home fix-up, landscapingand remodeling than other home-owners (Apgar et al 1987, Emrath1994, Price Waterhouse 1992).
Retail sales for Building Materialsand Furniture were also broken
down to examine differencesbetween zip codes. The southern zipcode, 77020, has much more retailactivity in Building Materials andFurniture than does 77026. Zipcode 77020 averaged over $20 mil-lion per year in sales in the past fiveyears, compared to less than $7.5million for 77026. The change inretail sales for each of the zip codesis also very different for each of thetwo retail categories.
In regard to Building Materials,the growth of sales in 77026 wasmuch greater than in 77020 (Figure14). The growth of BuildingMaterials sales for 77026 began in1993, which may indicate that hous-ing production by Fifth Ward CRCand Habitat for Humanity was astimulant, and was much strongerthan growth in the overall city.Another strong increase occurred in1996, the year of Fifth Ward’s high-est level of production (Table 4).The southern zip code, 77020, didnot grow in sales after 1994 otherthan the bump in 1998 caused byHabitat’s Jimmy Carter Project that
summer in Fifth Ward and westernDenver Harbor. Though its growthfrom 1986 to 1999 was higher thanthe city, that growth occurred priorto 1994. While growth was less in77020, total retail sales for BuildingMaterials were still higher there in1999 than in 77026 ($14 millionversus $8 million, both figures in1998 dollars).
The story is somewhat differentfor Furniture. Retail sales growth inthe southern zip code, 77020, wasstronger than in 77026 starting in1992, and began to grow even morequickly after 1996 (Figure 15).Furniture sales in 77020 went fromjust over $500,000 in 1991 to over$8 million in 1999. Even accountingfor inflation, this is an increase ofabout 13-fold over a seven-year peri-od. Furniture sales in 77026 weremuch weaker throughout the entireperiod examined. While they recov-ered in 1997 and 1998, theseincreases closely match those for thecity as a whole, and the decline in1999 was much greater than thecity’s decline that year. Total
Figure 14: Index of Retail Sales of Building Materials in Fifth WardZip Codes and City of Houston, 1986-99 (1986 = 100;1998 Dollars)
Source: State of Texas, Comptroller of Public Accounts
Furniture sales for 77026 were alsomuch lower in 1999 ($750,000using 1998 dollars) than for 77020.
Kalamazoo andWashington, D.C.
Retail sales data were not avail-able for either of the two neighbor-hoods in Kalamazoo nor for Shaw inWashington, D.C., so any analysis ofcommercial activity there would haveto rest on commercial real estatesales alone. However, commercialsales data for Kalamazoo were notavailable, and those for Shaw were of
questionable value because ofnumerous duplications in the recordsthat made it difficult to determinethe number of sales that had takenplace. From the records available, itwas not possible to know whether aparcel had been split up and soldseparately or whether the sales pricerepresented one price for all of thevarious pieces. Furthermore, whenthe commercial real estate price salesfor each year were estimated (to theextent the data would allow), no discernable trends were noted, withtotal commercial real estate sale values going up and down in signifi-
cant amounts each year. Thus thedata on commercial real estate activi-ty in Shaw did not lend themselvesto any meaningful analysis. Zip codelevel analysis, which could have pro-vided some indication of trends incommercial activity, was not usefulfor Shaw because the zip codeboundaries do not conform toShaw’s boundaries.
SummaryThere were marked changes in
commercial activity in Judkins Park,with both retail sales and commercialreal estate sales increasing dramati-cally. The retail sales increase evenholds for just the two tracts whereJudkins Park’s primary commercialcorridor lies. These changes in trendsalso occurred at about the same timeas changes in real estate prices, rein-forcing the development thresholdobserved in the data. Changes inretail sales for Fifth Ward were alsosubstantial, and it is likely that theincreases in sales of BuildingMaterials in one zip code andFurniture in the other has beeninfluenced by for-sale housing devel-opment by community groups. It isunfortunate that similar analysescould not be done for Kalamazooand Washington, D.C., but the lackof information points to the need toimprove collection of small-area data.
Figure 15: Index of Retail Sales of Furniture in Fifth Ward Zip Codesand City of Houston, 1986-99 (1986 = 100; 1998 Dollars)
Source: State of Texas, Comptroller of Public Accounts
The prevalence of crime in aneighborhood can have a sig-nificant effect on perceptions
and investment. Violent crime, inparticular, makes a neighborhoodless attractive for home purchase andbusiness start-up.
High crime rates can keep a neigh-borhood from attracting the invest-ment needed to reach a developmentthreshold and to revitalize. Increasedhomeownership can help reduce crimerates by providing a greater incentivefor residents to become involved incrime prevention programs and towork cooperatively with police. Thisrelationship between homeownership,crime, and perceptions makes anexamination of changes in crime ratesa necessary part of this study.
Seattle’s Judkins ParkCrime rates in Seattle seemed to
have a similar threshold dynamic asseen for single-family home pricesand commercial activity, but changecame in 1998, later than these otherchanges. This is at odds with themodel of neighborhood changedescribed above, in which reducedcrime rates impact housing pricesand commercial real estate (Figure1). In Judkins Park, there were actu-ally two periods in which overallcrime rates decreased significantly(Figure 16). The first decline inoverall ‘Part 1’ crime rates — includ-ing both violent crimes (murder,rape, robbery and aggravated assault)
and property crimes (burglary, theft,auto theft and arson) — occurredbetween 1992 and 1996 and closelymatched the decrease seen in crimerates citywide. In both cases, crimerates declined about 16 percent. Thesecond significant drop in total crimerates occurred between 1997 and1998. It was more dramatic inJudkins Park (down 53 percent) thancitywide (down 6 percent), and thedecline continued into 1999.
Violent crime declined substan-tially citywide (39 percent) between1993 and 1996 (Figure 17). ForJudkins Park, the decrease duringthis period was even greater (51 per-cent), and it occurred at the sametime that HomeSight began to buildhomes in the neighborhood.However, the neighborhood saw asubstantial increase in 1997, larger
than that for the city. Violent crimein Judkins Park and the city thendeclined again, at a greater rate inthe neighborhood (31 percent) thancitywide (16 percent).
Houston’s Fifth WardCrime in the Fifth Ward was
measured by a police beat within theWard and compared to overall citycrime rates. The Ward is actuallycovered by two Police Beats, 7C10and 7C20, south and north of therailroad tracks that split the neigh-borhood (Map 3). Neither preciselyoverlaps the Ward as defined in thisstudy. However, while Beat 7C10has some streets that are beyond itsboundaries, much of Beat 7C20 liesoutside the area. Since the largemajority of 7C10 is within Fifth
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Seattle
Judkins Park
19991998199719961995199419931992199119901989
Figure 16: Index of Crime Rates for Judkins Park and the City ofSeattle, 1989-99 (1989 = 100)
Source: City of Seattle Police Department
7Assessing Impacts on Crime Rates
Ward proper, this beat is used toindicate trends in the neighborhood.
Changes in overall crime rates,property and violent, in 7C10 closelyfollowed rates in the city until 1997,when rates declined more quickly inthis beat (Figure 18). Actually, totalcrimes in the City of Houstonincreased slightly between 1997 and1999, while they decreased by 27percent in 7C10. Some of thedecrease in overall crime in 7C10 isdue to the significant decrease in vio-lent crime there (Figure 19). Violentcrime accounts for a much higherpercentage of total crime for 7C10than for the overall city. Over thepast five years, violent crime citywideaccounted for 16 percent of allcrimes, while it accounted for over30 percent of all crimes in 7C10.Thus the recent decline in total crimein 7C10 was significantly affected bythe decline in violent crime. Until1996, changes in violent crime ratesfor 7C10 roughly mirrored changesfor the city. However, between 1996and 1999, violent crimes in 7C10decreased 34 percent compared toonly 4 percent citywide.
Kalamazoo’s Edisonand NorthsideNeighborhoods
Crime data for Kalamazoo neigh-borhoods were available only for1996 to 1999, so it is not possible toassess a longer-term trend (Figure20). What can be seen is that crimedecreased more in Northside (25 per-cent) during this four-year periodthan it did citywide (14 percent), butthere was less of a decline in Edison(12 percent). After accounting for theincrease in the neighborhoods in1997, the decline in crime rates wasgreater for the two neighborhoods in
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Houston
Fifth Ward
19991998199719961995199419931992199119901989
Figure 18: Index of Total Crime for Police Beat 7C10 (Fifth Ward)and the City of Houston, 1989-99 (1989 = 100)
Source: Houston Police Department
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Houston
Fifth Ward
19991998199719961995199419931992199119901989
Figure 19: Index of Violent Crime for Police Beat 7C10 (Fifth Ward)and the City of Houston, 1989-99 (1989 = 100)
Source: Houston Police Department
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SeattleJudkins Park
19991998199719961995199419931992199119901989
Figure 17: Index of Violent Crime Rates, Judkins Park and City ofSeattle, 1989-99 (1989 = 100)
Source: City of Seattle Police Department
the past three years, particularly inNorthside, than for the city as awhole. While crime citywide declined6 percent in the three-year period, itdropped 15 percent in Edison andnearly 30 percent in Northside.
Washington, D.C.’sShaw
Time periods for the availablecrime data were not precisely thesame for Shaw (1992-1998) as theywere for the city of Washington(1993-1999), but they were similarenough to allow comparison. Totalcrime in East Shaw dropped 35 per-cent between 1996 and 1998, mirror-ing the decline citywide (Figure 21).However, while total crime declinedin West Shaw between 1996 and1998, this came after a large increasefrom 1994 to 1996 and only broughtthe number of incidents back to the1992 level. Violent crime alsodeclined sharply after 1996 in bothparts of Shaw, but again only EastShaw kept up with the citywide rateof decline (Figure 22).
It is difficult to reconcile the stub-bornly high rates of crime in WestShaw with its increasing housingprices, particularly while citywidecrime rates were declining at such asignificant pace. A more thoroughexamination of crime in that area isnecessary to understanding why ahigh crime rate persists in an areathat appears to be revitalizing.
SummaryCrime rates in the neighborhoods
examined have been affected by thedeclining crime rates in their cities.However, in three of the five cases,changes in the neighborhoods weregreater than those in the city as awhole. In Judkins Park, total crime
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Northside
EdisonKalamazoo
1999199819971996
Figure 20: Index of Crime for Edison, Northside and Kalamazoo,1996-99 (1989 = 100)
Source: City of Kalamazoo Police Department
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Washington, DC
W. Shaw
E. Shaw
19991998199719961995199419931992
Figure 21: Index of Total Crime for East and West Shaw (1992 =100) and Washington, DC (1993 = 100), 1992-99
Source: Crime Analysis Unit, Metropolitan Police Department
rates dropped significantly in 1998,close on the heels of HomeSight’shighest production period. In thiscase, it can be inferred thatincreased vigilance and civicactivism on the part of new home-owners had an impact. In the vio-lence-plagued Fifth Ward, violentcrime decline precipitously at atime when violent crime rates city-wide were decreasing much moreslowly, driving the decline in totalcrime for the neighborhood. Whilethe data did not permit analysis oflong-term trends, the decline ofcrime rates in Northside and EastShaw may show some indicationthat perceptions of those neighbor-hoods are improving.
8Assessing Evidence of Development Thresholds
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Washington, DC
W. Shaw
E. Shaw
19991998199719961995199419931992
Figure 22: Index of Violent Crime for East and West Shaw(1992=100) and Washington, DC (1993=100), 1992-99
Source: Crime Analysis Unit, Metropolitan Police Department
Public perceptions of a neigh-borhood have a substantialinfluence on the willingness of
people to invest there, whether as ahomebuyer or a businessperson. Asperceptions are changed by revital-ization efforts, a critical mass ofopinion may be reached that causespeople to begin “tipping in” ratherthan vice versa. A developmentthreshold is reached when the “tip-ping in” becomes self-sustaining.
The Seattle case study reveals aneighborhood reaching a develop-ment threshold, as confirmed bothquantitatively, through the data onhousing prices and commercial activ-ity, and qualitatively, via the inter-views. Single-family housing prices,retail sales and commercial real estate
sales all exhibited significant changesin trends beginning in either 1996or 1997, the same time when, in theopinion of numerous interviewees,Judkins Park had turned around.Houston’s Fifth Ward also exhibitedwhat seems to be a threshold in 1997,with increases in mortgage values,homebuyer income and certain retailsales, and declines in crime rates.Kalamazoo’s Northside may have justreached a development threshold in1999, with sharp increases in home-buyer income and the number ofmortgages originated and a decline incrime rates, but it is too early to besure. There was no evidence of thresh-olds in Kalamazoo’s Edison nor inWashington, D.C.’s Shaw that can beattributed to housing development.
Why did some neighborhoodsreach a threshold and others not?
To begin with, each of the neigh-borhoods examined started from dif-ferent places, as the data from the1990 Census illustrate. Judkins Park,Edison and Shaw did not have thehigh poverty rates of the Fifth Wardor Northside, though they were stillhigher than citywide rates and higherthan the national rate (13 percent).Also, housing values were much lessthan the city median for Fifth Ward,Edison and Northside and the seven-block group area of Judkins Park. InShaw, housing values were higherthan the city median, but the neigh-borhood had the lowest homeowner-ship rate (20 percent) of any of thecase studies. In the other neighbor-
hoods, homeownership rates werenot much lower (i.e., more than 10percentage points) than the city ratefor all neighborhoods. The neighbor-hoods also varied significantly in size,measured by both population andnumber of housing units (Table 12).
Whether development has a highprofile—that is, whether public per-ceptions of change are heightened byseeing a large number of new for-salehouses relative to the size of theneighborhood, or being aware ofdevelopment taking place within aconcentrated period of time—maybe part of the threshold equation.For example, in Judkins Park, 154housing units were developed forsale in a span of six years, with morethan 100 sales recorded in just twoyears. Within the smaller seven cen-sus block groups, this representsmore than 10 percent of the housingstock that existed in 1990, though itis just 2.2 percent of stock in thelarger four census tracts. This highconcentration of housing develop-ment, both spatially and temporally,may have been an important factorin Judkins Park reaching its develop-ment threshold. In contrast, devel-opment in Shaw took place over amuch longer period, with 74 single-family and 154 multi-family unitsdeveloped over an 18-year periodand spread out over an area with 50percent more housing units.
For Fifth Ward, 190 single-familyunits were developed in a little overten years, with 64 of these unitscompleted in 1998. Additional fac-tors included the completion of a165-unit senior citizens home in1998 and the fact that Fifth WardCRC supplements its for-sale hous-ing programs with commercial devel-opment projects and rental housingdevelopment. This further compli-cates the equation, as does the factthat the effects of the surge of devel-opment in 1998 may just be begin-
ning and thus are not yet fullyreflected in the data on mortgagesand retail sales.
Another spatial factor, aside fromthe concentration of housing devel-opment, that may have helpedJudkins Park reach a developmentthreshold is its proximity to the city’scentral business district (CBD),which is just a mile away. Urban-sub-urban traffic congestion may be act-ing as a push, and reduced crimerates as a pull, to attract more peopleto live in central cities. These factorsmay have played a role in decisions tobuy homes in Judkins Park, sincecommuter traffic is a major problemin the greater Seattle metropolitanarea and overall crime rates in the cityhave declined 42 percent since 1991.
The same dynamic is present inWashington, D.C., working to theadvantage of West Shaw, which bor-ders both the CBD and a gentrifiedarea overflowing its supply of attrac-tive housing. However, this proximi-ty to the CBD did not notably helpEast Shaw, although prices therehave been increasing modestly in thelast two years and the number ofmortgages originated is also increas-ing. (This increase is somewhatgreater in the three westernmostcensus tracts of East Shaw, whichmay be an indication that higherhome prices are moving east throughShaw.) The revitalization of the CBDhas also been moving east, from
15th Street to 7th Street, which maybe one reason why the effect hasbeen greater on West Shaw.
Houston’s Fifth Ward is also veryclose to the CBD, but is more isolat-ed both by the highways and by itsrelatively high rates of poverty andviolent crime. The relatively smallsize of Kalamazoo makes the neigh-borhoods of Edison and Northsidepotentially more attractive to thosewho want to be close to the CBD,but commuter traffic is not a signifi-cant problem in Kalamazoo and thusnot much of an impetus for inner-city neighborhood revitalization.
Generally speaking, as inner-cityneighborhoods improve they arelikely to attract more people whowant to live closer to where theywork. Attracting private investmentto a neighborhood, including thepurchase of market-rate homes andretail establishment start-ups, may bethe primary determinant of whethera development threshold occurs. Theability to attract investment rests to acertain extent on the ability of theneighborhood to attract new resi-dents and, particularly for distressedneighborhoods, middle-income resi-dents. The outmigration of middle-income households from cities andthe subsequent concentration ofpoverty there is, of course, a primarycause of inner-city problems. Theattraction of middle-income house-holds provides both fiscal benefits to
Table 12: Populations and Housing Units for Neighborhoods, 1990Population Housing Units
Judkins Park (4 tracts) 16,398 7,0247 Block Groups 3,535 1,401
Edison 8,547 3,374Northside 6,254 2,401Source: Census Bureau
the city and social benefits at theneighborhood level (Quercia andGalster 1997). In addition toincreasing housing prices, attractingmiddle-income households shouldalso help increase commercial activityand may keep down crime rates.
It is also likely that the type ofhousing developed is a factor inreaching a development threshold.For example, the impact of multi-family housing may not be as greatper unit as single-family housing. InJudkins Park, not only was nearly allthe housing single-family, but it wasalmost entirely new construction andwas accompanied by improvementsin streets, curbs and sidewalks, radi-cally changing the appearance of the
neighborhood. In Fifth Ward, theconstruction was also new and sin-gle-family, and numerous infrastruc-ture improvements were made, butmuch of the neighborhood remainswithout sidewalks and some streetsare still unpaved. The housing devel-oped in Shaw included some newconstruction, but also much rehabili-tation of existing stock. This was alsothe pattern in Kalamazoo.
Five case studies cannot producea definitive answer on what causes aneighborhood to reach a develop-ment threshold. While the JudkinsPark case points to the importanceof concentrated housing, other fac-tors also have an effect, including thepresence of programs to address
neighborhood needs other thanhousing, proximity to the CBD, andthe characteristics of the neighbor-hood prior to development.Determining the characteristics, pro-grams and development that willbest improve the odds of attaining adevelopment threshold will requiremore in-depth analyses. Comparisonsto neighborhood revitalizationefforts that do not use increasedhomeownership as the central strate-gy would be useful, but such com-parisons were beyond the scope ofthis research. The aspects of commu-nity development that should beaddressed in future research are dis-cussed in the concluding section ofthis report.
9Estimating the Fiscal Impacts
The production or rehabilita-tion of housing by communi-ty groups can increase fiscal-
revenues for state and local govern-ments in several ways. First, housingdevelopment requires large quanti-ties of building materials from whichrevenue is received through salestaxes. Transfer taxes are applied tothe finished home when sold andsales taxes to the acquisition of fur-nishings for the home. New andimproved homes also tend toincrease home values, which has apositive effect on property taxes, theprimary source of income for manylocal governments. If neighborhoodrevitalization has some success, per-haps reaching a development thresh-old, then revenues from propertytaxes may increase in a broader area.
Estimating the increased revenuefrom housing development and
neighborhood revitalization is animprecise art, since it is difficult tosort out what portion of housingprice increases or increases in retailsales are attributable to CDC activityversus other factors impacting eitherthe neighborhood or the city as awhole. However, the importance ofdemonstrating how neighborhoodrevitalization affects government rev-enue makes it worthwhile to formu-late a means of estimation. JudkinsPark’s HomeSight has developed amethod for estimating the return oninvestment that the city realizedfrom its assistance to HomeSight’sdevelopment work, an exercise thathelps make the case for governmentinvolvement and helps insulate thegovernment from criticism after thefact. Demonstrating the value ofcommunity development efforts helpsboth government and community
groups to build and sustain supportfor ongoing programs that put moneyback into distressed communities.
Estimates of the fiscal benefits ofhome ownership have included bothone-time benefits, from transfer andtitle fees and taxes and fees fromconstruction, and ongoing benefitsfrom increased tax receipts from newhouseholds (NRC 1998). For exam-ple, local governments receiveapproximately 1.25 percent of thesale price of a home in fees and taxes(Census of Governments 1996).HomeSight has estimated that insales, property and excise taxes, it hasgenerated over $3.3 million in gov-ernment revenues. Based on what itsexecutive director believes are con-servative estimates, HomeSight alsoprojects that by 2006 it will havepaid back the government subsidiesit has received.
Direct benefits are easier to esti-mate and justify than are the indirect“spin-off” benefits from the eco-nomic stimulation induced by hous-ing development and neighborhoodrevitalization. For example, if muchof the increase in sales of furniture inHouston’s Fifth Ward can be attrib-uted to the housing development byFifth Ward RDC and Habitat forHumanity, then a portion of theincrease in sales tax receipts is anindirect fiscal benefit of that develop-ment. The volume of furniture salessubject to state sales tax in 1998 forthe two zip codes covering FifthWard was at their highest level since1986 (the earliest date for which
data were available), and this amountmore than doubled in 1999. The$2.9 million in furniture sales subjectto state sales tax (6.25 percent) in1999 provided more than $180,000to the state treasury. Similarly, theretail sales increases in Judkins Parkalso provided significant increases insales tax receipts for their state andlocal governments.
Since some of the increases inhousing prices can be attributed tononprofit housing development, socan increases in property tax rev-enue. For example, in Judkins Parkhousing prices increased 95 percentduring the three and a half yearsbetween 3rd Quarter 1995 and 1st
Quarter 1999, compared to 28 per-cent for the city as a whole. If oneassumes that without HomeSight’sfor-sale housing development, hous-ing prices in Judkins Park wouldincrease at the same rate as the city,then the average price in the neigh-borhood for a single-family homewould be $197,715 dollars insteadof about $300,000. Thus it can beargued that HomeSight’s effortsprovided more than $1,000 per sin-gle-family house in additional prop-erty tax revenue, assuming a localproperty tax of 1 percent. Impactson the city’s treasury range into themillions of dollars per year.
10Conclusion
The case studies show that theeconomic impacts of commu-nity-based homeownership
programs can be estimated with afair degree of confidence. In certaincases, such as Seattle’s Judkins Park,the impacts are clearly demonstratedby significant changes in the indica-tors, even compared to the positivechanges in the city as a whole. Inother cases, there appears to be littleor no impact (East Shaw) or theimpact is overshadowed by otherfactors (West Shaw). In the FifthWard, the impacts on the real estatemarket may just be beginning andfurther evidence of change can befound when looking closely at cer-tain retail sales data and crime statis-tics. Kalamazoo’s Northside may bejust beginning a revitalization that isnot reflected in mortgage values.However, putting a “bottom-line”
figure on the economic impact, oron the fiscal revenue generated, maynot be possible.
The Judkins Park and Fifth Wardcase studies also demonstrate thatdevelopment thresholds exist: thereis a point at which a critical mass ofperceptions change and investmentcauses a marked change in economicindicators. While reaching a thresh-old may have some negative conse-quences (such as triggeringmiddle-class gentrification and itsconcurrent housing price increases,to the detriment of lower-incomehouseholds), it is important tounderstand how and why develop-ment thresholds occur. Communitygroups have limited resources andattracting private investment andmiddle-income households is oftenused as a means to further neighbor-hood revitalization. This research has
not determined how the thresholdswere reached, only that there weresignificant changes in neighborhoodsdemonstrated by changes in percep-tions and quantitative indicators. Theresearch has suggested what factorsplay a role in reaching thresholds:spatial and temporal concentration ofhousing development; types of hous-ing, both new construction versusrehabilitated housing and single-family versus multi-family; proximityto the central business district; thehealth of the local economy; and thebaseline social and economic condi-tions that were present when develop-ment began.
The uneven availability of datalimits the extent to which the neces-sary analyses can be performed. Thedata for Seattle were comprehensiveand thus allowed for a thoroughanalysis. For the other case studies,
however, much of the data was notavailable, or a surrogate—HMDAmortgage data—had to be used.HMDA data are valuable tools foranalyzing neighborhood developmentand may prove to be a useful andaccessible tool for this type ofresearch, but their accuracy in predict-ing changes in home prices needsmore study. While the correlationbetween average sales prices and aver-age mortgage amounts was strong forSeattle, this association may not holdup in other markets.
The limits of examining onlyquantitative data, even when available,are brought out by the Shaw casestudy. Without knowing that otherfactors played an important part intriggering West Shaw’s rapidly risingreal estate prices, one might haveattributed them entirely to localhomeownership programs. This caseillustrates the importance of usingboth quantitative and qualitativeinformation to put together a moreaccurate portrait of change. Absent adiscussion of Shaw’s economy withthose most familiar with it, aresearcher (or prospective fundingsource) might have exaggerated therole of CDC-sponsored housingdevelopment in the revitalization ofWest Shaw. In fact, it is likely that thehousing developed in West Shaw,along with demand pressure from thewest and other development in theneighborhood, did help to stimulatehousing price increases. However, thisdoes not mean that nonprofit home-ownership program development wasthe primary cause of real estate priceincreases as appears to have been truein other case studies.
The possible movement of gentri-fication into West Shaw and the suc-cess of HomeSight in developingJudkins Park—to the point where itattracted many middle-class house-holds—creates challenges for commu-nity developers. As the data indicate,
the availability of affordable homesfor sale and apartments for rentdeclined in Judkins Park as the neigh-borhood took off. The revitalizationof the neighborhood changed it froma place of open-air drug markets anddrive-by shootings to a desirable placefor middle-income households.Certainly no one could argue that thisis a bad thing, but the increase in realestate prices may force those unableto purchase homes or who are facingincreased property taxes on a fixedincome to relocate. Interviewees inShaw stated that some long-time resi-dents there were beginning to bedriven out—to less desirable and thuslower-priced neighborhoods—becauseof increased rents. This raises con-cerns about the problems that maycome with reaching a developmentthreshold and demonstrates the needfor community development effortsto be comprehensive, addressing notjust issues of place but also of people.
The analyses performed in thisstudy were based on descriptive statis-tics and qualitative analysis. Noeconometric methods were applied.In other studies of neighborhoodchange, a number of statistical andeconometric tools have been appliedto testing thresholds, such as splineregression analysis (Galster et al 1999,Quercia and Galster 1999), and theeffects of development across an area,such as the methods used in spatialeconometrics (Can 1998, Anselin1998). These methods have not beenapplied to studies of development atthe neighborhood level. However,this research, in helping to under-stand the dynamics of neighborhoodchange, may allow for a more accu-rate estimation of the value of econo-metric models.
The roundtable discussion of thepreliminary findings highlighted someof the shortcomings of this type ofresearch and identified priorities forfurther study. The primary weaknesses
identified were the lack of a counter-factual (comparing trends in a similarneighborhood lacking CDC for-salehousing development); the limitedavailability of broadly useful neighbor-hood-level baseline data against whichto measure change; the limited causallink between housing developmentand retail sales; and the lack of analysisof what about increased homeowner-ship created change. Further researchareas identified include: how moresophisticated methods, particularlyeconometric methods, might beapplied to neighborhood revitaliza-tion; how Home Mortgage DisclosureAct data might be used by communitygroups; whether change in the retailmix or in bank deposits might begood indicators; and how the negativeeffects of gentrification in revitalizedneighborhoods can be mitigated.
Community-based homeowner-ship programs are turning distressedneighborhoods around and makingthem desirable places to live and toinvest in business. The evidence ofthis change is clearly visible in manyplaces, and stories of changed livesand new beginnings can be heardnationwide. However, there is still ascarcity of quantitative evidence thathomeownership programs are havinga significant economic impact—inshort, that they “pay off”—and thetools to measure that impact are stillinsufficiently refined. This study indi-cates both the limitations and thepotential of this kind of analysis.Further research should be of value tothose who are understandably con-cerned with the bottom line. Whilethe value of anecdotal evidenceshould not be underestimated, theneed to describe neighborhood revi-talization in quantitative, economicterms can only increase in the yearsahead, and adequate resources shouldbe devoted to meeting that need.
Overview Case studies of neighborhoods in the cities of Washington,
Seattle, Houston, and Kalamazoo were used to assess theimpact of for-sale housing development by nonprofit commu-nity groups, generally community development corporations(CDCs), on economic indicators for those neighborhoods. Theneighborhoods were selected primarily because each had seen asignificant amount of this kind of development over a reason-ably long span of time (7-18 years). For each case study, localrepresentatives of the Local Initiatives Support Corporationwere consulted to gather information on neighborhoods in thecities they served. Each case study involved: 1) gathering dataon nonprofit housing development, including when and wherehouses were built or rehabilitated for sale; 2) interviewingselected experts on the neighborhood economy; 3) gatheringdata on local indicators of economic development, includinghousing prices, commercial activity and crime rates; and 4) ana-lyzing the indicators for trends over time and the relationship ofthe trends to the nonprofit housing development.
Neighborhood Boundaries and theData’s Geographic Definitions
The neighborhood boundaries were defined by asking rep-resentatives of the CDCs what they felt was their area of respon-sibility and where they developed housing. However, the datagathered for the indicators did not necessarily conform perfect-ly to the area described by the CDC representative. Most of thedata were available at the census tract level, which generallyconformed well to the defined boundaries. However, some datawere collected at the zip code and at the police beat levels.Exceptions to the geographic fit of the data and how theyaffected the analysis are described below.
Seattle’s Judkins Park was defined as comprising four Censustracts: 89, 90, 94 and 95, the boundaries of which are shownon Map 1. The northern edge of the Tracts 89 and 90 was thesame as described by the CDC representative: Yesler Avenue.The western edge of tracts 89 and 94 run along 12th and 13thStreets, while HomeSight saw its western edge as runningnorthwest/ southeast along Rainier Avenue, leaving a largeportion of tract 94 that was not in HomeSight’s defined neigh-borhood. In addition, Tract 95 runs farther south than thesouthern edge of the neighborhood which runs along BayviewAvenue, leaving another half-square-mile outside the JudkinsPark neighborhood. The eastern edge of tracts 89 and 95extended approximately one-quarter mile more than thedefined area, to the lakefront, an area with generally higher-
priced homes, but not as densely populated. Thus, the censustracts are not a perfect fit for Judkins Park. However, the datawere only available at tract level and HomeSight developedhomes in all four tracts.
Various analyses were run to determine how the differencesin boundaries might affect the conclusions drawn from the data.For example, the change in median price per square foot wasexamined for each tract individually. Prices increased most intracts 89 and 95, the two tracts where HomeSight did most ofits development. Changes in the number of incidences of crime,both total and violent, followed very similar patterns for all fourtracts. Retail sales were also examined by individual tract andwhile the greatest increase was in tract 94, which also most ofthe volume for the four tracts, the other tracts also had signifi-cant increases. Because of the boundary problems, the reportdescribes retail sales changes for just tracts 89 and 90 as well asfor the four tract area.
Houston’s Fifth Ward was defined for the study as compris-ing nine census tracts: 201.01, 201.02, 204, 205.03, 205.98,206.01, 206.98, 207.03, and 208.02 (Map 3). While theboundaries described by the executive director of Fifth WardCRC did not include tracts 206.01, 207.03 and most of208.03, the organization developed 45 units in those threetracts. Tracts 203.01 and 208.03 were included in the analysisof the number of houses developed as they are contiguous tothe Fifth Ward tracts and had 38 units developed by Fifth WardCRC and Habitat for Humanity, Houston.
The zip codes used for retail sales included large areas not partof Fifth Ward proper. For example, zip code 22026 in the northincluded six census tracts outside Fifth Ward that had a 1990population of 9,500. Zip code 22020 included six census tractsoutside Fifth Ward, though two of those tracts are those includ-ed in the analysis of housing developed, 203.01 and 208.03.Police Beat 7C10 used for crime data included a few blocks eastof Fifth Ward’s eastern boundary, though these were in tract203.01 where 36 for-sale homes were developed. The beat alsoincluded parts of tracts 502 and 205.01, west of Route 59.
Washington, D.C.’s Shaw was defined as comprising eightCensus tracts which conformed to the definition provided bythe executive director of the CDC that developed most of thehousing used in this study.
For the Kalamazoo neighborhoods, the census tracts con-formed closely to both neighborhoods, with small exceptions.Of the two census tracts that comprise Edison, 9 and 10, a fewblocks of the northern tract, 9, are out of the Edison neighbor-hood. However, this is a sparsely populated, industrial area.Likewise, the northern edges of the two tracts comprisingNorthside, 2.02 and 3, are not considered part of that neigh-
Appendix:Methodology
borhood, but are primarily also industrial areas. The crime datafor Kalamazoo were based on the city’s geographic definition ofthe neighborhoods which are those also used by the communi-ty groups.
Data Sources and AnalysesReal estate data for Washington, D.C. and Seattle were pur-
chased from First American Real Estate Solutions, which col-lected data on mortgages for the last two sales of a property andwere enhanced by data from the recorded deeds. Annual homesale prices for Seattle’s Judkins Park were determined by takingthe median (Figure 2) prices for all sales of single-family homesfor that year in the four census tracts that defined the neigh-borhood. Single-family homes accounted for over 90 percent ofall residential real estate sales in the Judkins Park census tracts.Average single-family home price for the selected quarters wereused in order to compare changes in Judkins Park with those inthe city overall (Figure 3). Data on city prices were provided asaverages for the selected quarters. Median price per square foot(Figure 4) divided the median prices by the square footagereported in the real estate data.
Average annual mortgage amounts for Houston andKalamazoo, as well as the number of mortgages originated,were determined from an analysis of Home MortgageDisclosure Act (HMDA) data provided by the Federal FinancialInstitutions Examination Council (FFEIC). This data set of allmortgage applications includes: 1) the purpose of the loan,whether it is for home purchase, improvement or refinancing;2) whether the unit is for owner-occupancy or not; 3) theaction taken on the loan, whether it was denied, originated,withdrawn or other action; 4) the amount of the mortgageapplied for; and 5) the income level of the applicant; 6) whetherthe loan uses conventional or subsidized (e.g., Federal HousingAdministration) financing; and 7) the census tract in which theproperty is located. The data are available for the years 1992through 1999. Figures were determined by using only origi-nated mortgages that were for home purchase by the owner-occupant. The data were extracted at the county level and thencensus tract level data were parsed out of the county data andaggregated for the neighborhood.
Average sales prices for the four Seattle tracts, plus threeadditional contiguous tracts, were correlated with averagemortgage amounts for home purchases by owner-occupants.The results were based on over 1,500 sales and approximatelythe same number of mortgages, that were aggregated into 56observations, seven tracts times eight years. The resultingPearson’s r was 0.94.
Median annual home sale prices per square foot for Shaw(Figure 10) were determined in a similar manner to those forJudkins Park, however, only sales where single-family homeswere listed as one unit (some were designated as two or threeunits) were used. In addition to those data, sales designated astownhouse/rowhouse and as one unit were also used due tonature of the housing stock in Washington, D.C., which is adensely populated city with fewer single-family homes than
most cities. The index comparing changes in single-familyhome values in East and West Shaw to the overall city usedchanges in median prices for single unit sales in Shaw with theannual average of the Housing Price Index from the Office ofFederal Housing Enterprise Oversight, as described in thereport.
Retail sales data were obtained from the state ofWashington for Seattle and the State of Texas for Houston.Sales figures were adjusted for inflation using the consumerprice index. Both sets of sales figures are based geographicallyon addresses for tax returns and there is no way of knowingwhether the transactions that the tax records represent tookplace in that geographic area (zip codes for Houston, censustracts for Seattle). However, while absolute values of retail salesmay not be accurate, the data does capture trends of retail activ-ity. The Houston data were also broken down into the types ofretail sales most likely affected by housing development.Indicators of commercial activity for Washington, D.C. wereestimated from commercial real estate activity, but no trendswere noted. Crime data were provided by the police depart-ments of each jurisdiction.
Data were also gathered for each of the indicators on a city-wide or county-wide basis for comparison purposes. This wasdone in order to estimate the affect of exogenous factors onneighborhood-level data. Changes residential real estate prices,commercial activity and crime rates at the city or county levelrepresent the effect of exogenous factors. City-wide or county-wide data that were comparable to neighborhood level data wereused where available to examine differences between the twogeographic levels. In some cases, such as price per square foot forresidential real estate, comparable data were not available.
Finally, data on CDC housing development for sale wereprovided by the CDCs themselves, or by Habitat for Humanity,which builds low-income housing in many neighborhoods.These data were gathered by year and by location (census tract,or neighborhood for Kalamazoo) of the housing developed.
The InterviewsIn order to determine how important the housing developed
by local CDCs was to changes in the indicators, interviews withthose knowledgeable of the neighborhood and its developmentaugmented the quantitative analysis. Interviewees includedbankers, local government officials and community representa-tives. A standardized questionnaire was used to determine: 1)how important respondents felt the CDC’s housing develop-ment had been to changes in the neighborhood; 2) what otherfactors may have caused changes in real estate prices, commer-cial development or crime rates; and 3) whether perceptionsabout the neighborhood had changed and, if so, when theychanged. Thirty-four interviews were conducted across the fourcase studies, with at least eight persons interviewed for each city.The duration of each interview was approximately one hour.
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References
For additional copies of this reportor for more information, please contact:
Harold O. Wilson, DirectorCenter for Home Ownership
Local Initiatives Support Corporation (LISC)1825 K Street NW, Suite 1100
This publication is also available online at the LISC Online Resource Library
www.liscnet.org/resources
The work that provided the basis for this publication was supported by funding from the U.S. Department of Housing and Urban Development andthe National Community Development Initiative. The substance and findings of the work are dedicated to the public. The author and publisherare solely responsible for the accuracy of the statements and interpretations contained in this publication. Such interpretations do not necessarily reflect the views of the Government or the NCDI funders.
