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«A Journal of Policy Development and Research HoPe VI Volume 12, Number 1 • 2010 U.S. Department of Housing and Urban Development Office of Policy ...»

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This study has two important limitations. First, by looking at only the neighborhoods that experienced heavy population decline, the results can be generalized only to other such neighborhoods. Second, by looking at only a single city and only three neighborhoods in it, my ability to understand what other new uses replaced the decreased number of previously occupied housing units in general is limited. The assumption that much of what replaced occupied housing units was unoccupied housing units or vacant lots, an assumption that was supported by the case study, was hardly proven. Future research could address these weaknesses and also explore how neighborhoods with higher or lower density housing might change differently. Does occupied-housing-unit density work as an effective measure in depopulating suburban areas? How does this measurement work in regions outside the industrial Rustbelt of the United States?

Community development and planning practice has traditionally been geared toward issues of growth and development. Community development strategies that assume decline are only beginning to emerge as alternatives. Communities currently lack the skills and resources to respond to decline in an effective and positive way. Community development plans and design strategies for shrinkage need to be built on sound empirical evidence about the ways cities decline. This article introduces a potentially valuable metric for studying the land use effects of population decline and lays a potential foundation for developing planning and urban design tools that respond to the unique needs and characteristics of shrinking cities. Leadership at the federal level through the new Sustainable Communities Initiative at the U.S. Department of Housing and Urban Development could be valuable here to provide incentives and support to communities that plan for their anticipated smaller populations. With or without federal or state support, cities and towns that are losing population should use the occupied-housing-unit density measure in their own planning to monitor land use changes in a systematic way. Flint recently hosted a series of open meetings to debate the future of the city; shrinking was part of the discussion. The findings here demonstrate that occupied-housing-unit density is a valuable metric for approaching shrinkage and aiding Flint’s leaders and residents in devising strategies and approaches. For example, blotting and sideyard acquisitions could be encouraged explicitly by local planning and zoning ordinance in support of changing densities in depopulating neighborhoods.

Acknowledgments The author acknowledges the invaluable research assistance provided by Erin Heacock, Elizabeth Antin, and Courtney Knapp. In addition, the author acknowledges advice and feedback offered by Durwood Marshall, Terry Schwarz, Christina Kelly, Michael Greenberg, and Frank Popper in conducting this investigation. This research was partially supported through funding from the Genesee Institute and through a research associate appointment at Vassar College. Special thanks go to Leonard Nevarez, Pinar Bitur, and Meg Ronsheim at Vassar. This paper benefited from feedback received at a public lecture sponsored by the Taubman Center for Local and State Government, Kennedy School of Government, Harvard University—thanks go to attendees and to Dr. Edward Glaeser for sponsoring the lecture.

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Author Justin B. Hollander is assistant professor of urban and environmental policy and planning at Tufts University.

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Combining Data on Residential Vacancy Rates and Mortgage Foreclosures Provides a Picture of Neighborhood Change Robert N. Renner U.S. Department of Housing and Urban Development Jamie W. Wolf KBM Group, Inc.

The U.S. Department of Housing and Urban Development’s (HUD’s) Office of Policy Development and Research recently acquired a product from Lender Processing Services Applied Analytics1, which contains proprietary individual-loan–level data covering approximately 75 percent of the entire mortgage loan market. This product is a robust data source of 40 million mortgage loans2 with ZIP Code geographic detail. It includes more than 70 loan attributes, credit scores, and foreclosure status. The ability to identify and track loans in foreclosure and calculate foreclosure rates at various geographic levels can lead to powerful knowledge for all parties involved in community development and housing policy. To illustrate the geographic concentration and extent of social and economic distress resulting from the current housing crisis in the map of the Las Vegas, Nevada metropolitan area in exhibit 1, we connect this mortgage data with U.S. Postal Service (USPS)3 data on vacant addresses.

The ZIP Codes on the map are shaded from light to dark based on the foreclosure rate as of August

2009. One-half of the ZIP Codes in the area have a foreclosure rate of 10 percent or higher, with Formerly McDash Analytics.

Includes first and second mortgages.

USPS vacancy data are available through HUD USER (http://www.huduser.org/datasets/usps.html).

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ZIP Code 89109, located in the center of the map, approaching 20 percent. The hatched areas on the map are ZIP Codes that have had increases in residential vacancy above the mean change for all ZIP Codes in Las Vegas and its surrounding communities from September 2008 to September

2009. The mean change in ZIP Code residential vacancy rate during this period is 1.25 percent.

The average increase in residential vacancy rate in the hatched ZIP Codes is 2.66 percent, which is more than twice the mean. The average residential vacancy rate for these ZIP Codes has increased from 3.8 to 6.5 percent during this period.

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