NEW O.R. MODEL TACKLES CONFLICTING DEMANDS OF SECTION 8 HOUSING, COMMUNITIES (January 26, 2001)

While policymakers have no direct control over where families relocate with housing vouchers, the new study allows planners to evaluate potential policies statistically, diagrammatically, and spatially. The most desirable of these policies could be used to generate incentives to encourage certain stakeholders, such as landlords, to participate in the housing mobility program.

"We see it in many cities – Competing interests that present urban public housing authorities with great challenges," says Michael P. Johnson of Carnegie Mellon University’s Heinz School of Public Policy and Management.

"Since new federal housing legislation was passed in 1996, there’s been less emphasis on the existing stock of public housing and more on helping families find new apartments with Section 8 subsidies. But the rental housing market is often tight, and middle-class communities often resist the arrival of Section 8 tenants. We set out to provide a scientific model for balancing the different interests."

The study, "Decision Support for a Housing Mobility Program Using a Multiobjective Optimization Model," is by Dr. Johnson and Prof. Arthur P. Hurter of the Department of Industrial Engineering and Management Sciences, Robert R. McCormick School of Engineering and Applied Science, Northwestern University. It appears in the current issue of Management Science, an INFORMS publication.

Four Core Interests
The model provides planners at public housing authorities and regional planning agencies with a decision support methodology to assess the effects on four groups: 1. families that occupy subsidized housing; 2. host communities, to which the families may move; 3. the origin community, which the families leave; and 4. society as a whole.

The authors use economic models to estimate the impact of tenant relocation in dollar values. These models examine such factors as the benefits a family enjoys by moving to a new area and the impact on property values associated with subsidized housing families moving into middle class neighborhoods. They also use non-dollar-valued "equity" measures that represent the perceived fairness of potential allocations with respect to destination communities and potential employers.

They employ optimization – a basic modeling tool used by operations researchers – to give planners a "multiobjective optimization model" that generates alternative relocation schemes based on tradeoffs between competing groups’ objectives.

Revisiting the Chicago Area
The authors tested their model using housing, labor market and demographic data for the city of Chicago and nearby Lake County, Illinois. In particular, the authors used observations of actual families in public housing in Chicago and in Section 8 housing in Lake County to estimate the benefits and costs of hypothetical relocation strategies between Chicago and Lake County. They found that these family allocations generate significantly differing impacts associated with the various objective functions.

One possible plan, for example, concentrates 300 Section 8 families in Lake County municipalities that have higher than average minority populations. This solution has the most favorable net benefit value of all the possible plans.

A second plan spreads families evenly across census tracts in Lake County. It has the greatest community equity measure. But this second solution represents a decrease of about $1.5 million over the economic benefits associated with the other solution.

"An appropriate policy question would then be whether this increased yearly cost of about $5,064 per family is justified by potentially decreased political opposition among all host communities," write the authors.

The authors examined several additional alternatives to the status quo. In one, they hypothesize a 16% increase in affordable rental housing across Lake County. Here, the model’s outputs again outperform the existing distribution of Section 8 housing, with estimated potential yearly savings in what are termed "net social costs" of $155,179, or 11% of net social costs compared to the status quo. Because this permutation distributes available housing more evenly, low-income families gain greater access to areas with a wider range of shopping, employment, and transportation, again improving net social benefits and equity.

The authors caution that given the political sensitivity of housing mobility programs, no planning model can be implemented unless there is prior consensus among stakeholders that a variety of alternative solutions will be considered.

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