Combining Data on Residential Vacancy Rates and Mortgage Foreclosures Provides a Picture of Neighborhood Change

Robert N. Renner
Jamie W. Wolf

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Geographic Information Systems organize and clarify the patterns of human activities on the earth's surface and their interaction with each other. GIS data, in the form of maps, can quickly and powerfully convey relationships to policymakers and the public. This department of Cityscape includes maps that convey important housing or community development policy issues or solutions. If you have made such a map and are willing to share it in a future issue of Cityscape, please contact david.e.chase@hud.gov.

As with the articles in this issue, this introduction reflects the views of the authors and does not necessarily reflect the views of the U.S. Department of Housing and Urban Development.

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 Analytics, 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 loans 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) data on vacant addresses.