In 2012, the U.S. Department of Housing and Urban Development (HUD) released the Location Affordability Index (LAI) as an online portal and downloadable data set. The LAI has elevated the U.S. conversation on affordability to include transportation and access to opportunities, and has been used in state and federal programming, by researchers, and by private households. However, although some researchers have noted concerns with and potential limitations of the data, none has provided practitioners and researchers with an under-the-hood view of the data, analysis of its reliability or validity, or its conceptual limitations. This article recommends methodological improvements dealing with issues of variable construction, aggregation, and modeling. A recreation of the LAI at the census-tract level suggests the LAI overestimates both costs and cost burden, but especially among renters, and especially in metropolitan areas. On the transportation side, model recreation requires partnership and resourcing to both gain access to restricted data and to develop a reliable database on transit supply and use.In 2012, the U.S. Department of Housing and Urban Development (HUD) released the Location Affordability Index (LAI) as an online portal and downloadable data set. HUD adopted and revised the LAI from its origin as the Center for Neighborhood Technology's Housing and Transportation (H+T) Affordability Index. This database seeks to inform households and public agencies of the costs of living in various places, changing the discussion about affordability from one focused solely on housing to one inclusive of transportation costs. Numerous scholars have analyzed the LAI estimates, resulting in a special issue of Housing Policy Debate as well as other publications. These publications have addressed housing subsidies, mortgage risk, and racial disparities in costs, among other things. However, these publications have not provided practitioners and researchers with an under-the-hood view of the data, analysis of its reliability or validity, or its conceptual limitations. As this article shows, some elements of the LAI introduce either considerable error or the potential for considerable error. Many of those issues, based in variable construction, aggregation, and modeling decisions, can be fixed. Others-notably, data on transit use-are more problematic. If left unchecked, such error could misinform decisions regarding household location or public policy issues in housing or transportation-potentially costing private households or public agencies considerably. This article uses data from across the state of Ohio, intending it as an illustrative case study of the national implications of the conceptual and technical bounds of the LAI.
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