Go Public!

Problem: While mortgage foreclosures are devastating communities across the United States, few planners know how to access the data necessary to document the number of foreclosures, where they are located, how the problem has changed over time, or how many households are affected, in order to assess how foreclosures affect borrowers, renters, and communities. There is no national dataset with foreclosure information, and in many communities, this information is buried in county property records, state legal files, and property auction lists. Purpose: This article explains foreclosure as a process and describes how to use publicly available data to study foreclosure and inform outreach efforts. It shows how a collaborative effort among researchers and practitioners can produce useful data and analysis to reduce incidences of foreclosure. It concludes with suggestions for improving data access and quality. Methods: The main foreclosure data used in the illustrative examples in this article were gathered from foreclosure court records and enhanced with data from property sales and tax records, Home Mortgage Disclosure Act data, and foreclosure sale records. Results and conclusions: Although records on property foreclosures, real estate owned properties, and loan servicers are publicly available, accessing them, combining information from different records, and correcting mistakes to make them useful for analysis is time consuming and costly. Teams of researchers, public officials, and non-profits in a number of places, including one involving the author, have collaborated to build local foreclosure datasets using public data, producing accurate, property-level data that planners can use to guide policy, target direct outreach to at-risk borrowers and renters, and purchase distressed properties. Takeaway for practice: Public entities hold some of the best data available on the foreclosure crisis but, in most places, accessing it involves considerable time, effort, and money. When researchers and practitioners work collaboratively to access and analyze these data their joint efforts can transform data-sharing practices and institutions, facilitating wider access and use in the future. Research support: This research was supported by the Fund for New Jersey, NeighborWorks America, Local Initiatives Support Corporation (LISC), the Michael J. and Susan Angelides Public Policy Research Fund, the Edward J. Bloustein School of Planning and Public Policy at Rutgers University, Essex County, Hudson County/Jersey City, and Union County.