Refining Indicators Finding the Best Measures for Improvements in Urban Housing Michael Barndt Neighborhood Data Center Program Nonprofit Center of Milwaukee Community Indicators Conference Reno, Nevada March 2004

Where I’m Coming From  Nonprofit Center of Milwaukee – Capacity building for nonprofits  Neighborhood Data Center – a clearinghouse defined by a Data/GIS Services mission  Focus on neighborhood program decision-support – work is demand driven – “retail” services  Rich data environment in Milwaukee – especially in housing  Rich technology environment – program staff of 9  6 are “apprentices” from local universities  Member – National Neighborhood Indicators Partnership and Making Connections Initiative

There are two kinds of people in the world  Those who think that we can all come together and find through consensus that we are all alike – that there is one common view  Those who see differences – that perhaps …. there are three kinds of people …  Academic syndrome - Closure problems  Confirmed by market driven service  Continually new, diverse requests  Well beyond a set of indicators and reports

Talking Points  Multiple contexts for viewing a subject  Indicators should not be oversimplified – their contents change as they are unbundled  Place/time/sub-communities matter  Use of data is more than creating indicators  We still are not able to measure much of what we would really like to know

Varying Perspectives  Housing Markets  Housing Preservation  Resident Benefits  Equity and Justice  Quality of Life

Varying Perspectives Housing Markets  Values increase, investment attracted, quality maintained  Home ownership, equity through appreciation  Development rewards  Strong, safe, organized neighborhoods  Attractiveness, demand, value

Varying Perspectives Housing Preservation  Loss of housing stock may trump housing production  Housing condition enforcement  Resources to maintain and restore  Predatory behavior  Landlord behavior  Program mix appropriate to needs

Varying Perspectives Resident Benefit  Affordability – supporting access, reasonable costs for housing  Ownership as asset – wealth building  Choices for renters – ability to be effective consumers  Place/ People – Gentrification  Homeless

Varying Perspectives Equity and Justice  Segregation  Market perception  Institutional behaviors  Access to resources  Political will to respond  Spatial isolation within region  Race, income, political jurisdiction

Varying Perspectives Quality of Life  Much more than housing  Mobility  Unstable Transitions  “Urban Village”  Safety  “Community”  Collective local action  Economically viable  Services  Role in region

Parsing Indicators  Ownership  Value  Equity – (ownership/value)  Housing Supply  Condition  Investment  Equality

Ownership Definition and measurement  Census /city approach  Data accuracy  Homestead effects  Land contract sub-market  Rate of ownership  Capacity factor

Ownership Who owns?  Life Cycle patterns – the Elderly  Transition of property  Late interventions  Owner – renter fault lines  Bi-modal characteristics – income, race, mobility, children, participation, multiple problems  Persistence of renters  Policy biases toward ownership  Investor owners// slum lords  Patterns/ Practice

“Ownership” Getting at the large term  Responsibilities of ownership  Investment  Order  Neighborhood upkeep  Organizations – Block clubs

Value Tracking Sales data  Sales  Limited numbers of transactions  Affected by type  Affected by circumstance – arms length  Sales perspectives  Volume  Value/ changing value  Within a market

Value Tracking Assessment  Model  Quality  “Comparable” Zones  Amenity effects  Implementation  Effect of volume of information  Data limitations – quality/ condition  Pace – sensitivity choices  Administrative effects

Value Unbundling the Indicator  Differential markets – duplexes  Shifting housing stock base  Consider a resident owner perspective  Flipping – distortions in market information

Value Effects of perception  Changing expectations  Speculation effects  Investment/ commodity  Effects on investment/ maintenance decisions by owners  Effects on lending decisions

Equity Ownership as Wealth Building  Common assumption  Equity deteriation  Use of equity loans  Effects of predatory lending  Value of “bootstrap” programs  Difficulties measuring resident experience  Wealth other than income  Debt and factors affecting debt  Credit worthiness – Access to primary financial systems

Housing Supply Vacancy  Hard to measure vacant units  Especially those ready for occupancy  Some units taken off market – duplexes  Vacant land  Understated  Government ownership

Housing supply Interpretation  “Abandonment” as a stage  Threshold for investment decisions  Triage has come to mean public abandonment of certain neighborhoods  Relationship to population change  Did public leave first?  Or did housing condition/options drive them out  Regional growth often reinvents neighborhoods beyond basic needs for supply

Housing supply Use  Residents like vacant lots  Are lots effective open space?  Are lots used for other purposes?  Gardens  Tot lots  Are lots appropriate for redevelopment?  Assembly issues  Land-banking as a policy  Holding action  Obsolete footprints  Bias against “infill”

Investment HMDA  Investment patterns  Lending packages for slumlords  Sub-prime lending  Predatory lending

Investment Foreclosure  Tax foreclosure  Mortgage foreclosure  Patterns of concentration  A subset - elderly  Resident owner/ Investor owner  Recent policy effects  Patterns of return of property to the market

Investment Maintenance/ Improvements  Costs to maintain  The back side to “bootstrap” options  Lending limits when costs exceed value  Costs do not vary by geography  Incentives  Disincentives  Effects of lax enforcement

Investment Programs  Mix of options and resources  Running out of funds  How well are options marketed  Is there capacity to implement  Especially local  Who does not fit the options?

Investment Access to capital  Affordability  Work-income comes first  Costs of new investments  Public Policy  Public policy stresses increasing middle income participation/ or removing lower income concentrations  Failure of “trickle-down”  Tax structure – subsidizing wealth  Costs  Increasing burden - % of income spent on housing  Risks associated with bootstrap approaches

Equality Discrimination by race  HMDA lending / refusal patterns  Importance of testing  Debate over measures of segregation  Extent of transitory “integrated” neighborhoods  Extent of “unstable” “integrated” neighborhoods

Equality Discrimination against persons  Who cares about low income housing supply  Renter programs  Homeless programs  Employment – wages/ stability  Low income solutions in the past  Public housing ghettos  Weeding out  Felons  Transitional services  Homeless – linking to the full cycle

Equality Lending practices  From “trust”  Racial effects  Community connections – local lending  To formulas  What is the bias in these?

Equality Discrimination against place  Redlining  Regional equity  Taxing resources  Schools  Public policy  Local capacity  For self help  For locally driven development  Public/ nonprofit partnerships

Equality Redefining place  Destroy a village to save it  Eliminate old housing stock  Recreate a community, but for different people  Gentrification