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Abstract
Housing conditions can vary greatly from one property to the next, but housing characteristics often are measured at different geographic units because of data limitations. This article discusses the process of connecting address-level datasets to create meaningful analyses at the property level in the absence of a comprehensive address-to-parcel crosswalk. To demonstrate this process, the authors describe linking child lead screening, lead property compliance, foreclosure, and tax assessors' property records for a U.S. Department of Housing and Urban Development-funded Lead Technical Study in four Rhode Island core cities. Using the linked data analysis, robust property-level findings can lead to an effective evaluation of policies that affect properties, particularly for urban communities with high proportions of multifamily housing.
Introduction
Connecting existing datasets to conduct policy evaluation is a smart way to make the best use of available resources. Administrative datasets across multiple domains contain addresses and can be linked to gain insight regarding housing conditions and policy. In some situations, however, researchers prefer data about entire properties to address-level data when describing housing issues. Many multiunit residential properties have more than one address and, when researchers try to collect information about all residential units within properties, address listings are often insufficient. This concern is particularly evident for analysis in urban communities, where a high proportion of the housing stock contains more than one unit.
Robust statewide data systems ideally would exist and would enable researchers and city administrators to easily link address-specific data to property-level data. In Rhode Island, as we suspect in many other states, that ideal is not yet the reality. Therefore, extensive preparatory work was completed to conduct a property-level analysis of childhood lead exposure, lead compliance certificates, and foreclosures in four Rhode Island cities. In this article, we discuss the process of connecting a variety of separate address-level datasets with unique variables and coding systems. We provide background information that defines the study's purpose and describe how we created a master lookup table, matched our datasets to it, and analyzed the data. We also share the lessons we learned from this effort.
Context
The 2005 Rhode Island Lead Hazard Mitigation Act requires owners of nonowner-occupied properties built before 1978 (when residential lead-based paint was banned in the country) to...