Exploring the Spatial Distribution of Low Income Housing Tax Credit Properties
U.S. housing policies promulgated by the U.S. Department of Housing and Urban Development (HUD) have placed increasing emphasis on dispersing housing assistance in order to deconcentrate poverty. The Low Income Housing Tax Credit (LIHTC) program, the nation’s largest affordable housing subsidy program, is not administered by HUD and therefore not closely monitored for compliance with poverty de-concentration objectives. In fact, several provisions of the LIHTC enabling statute provide incentives to concentrate LIHTC properties within high-poverty census tracts.
This study examines the spatial distribution of LIHTC properties to determine if the units are being placed in a way that is in conflict with the goal of de-concentrating the spatial pattern of housing assistance. This is the first study to rely on the actual locations of individual properties to assess the extent of LIHTC clustering. The analytical approach employed is a variation of the Ripley’s K function, a common technique used to characterize spatial point patterns. This study relies on a unique modification of the Ripley’s K function which allows for comparisons between an observed point pattern and a simulated pattern generated from the underlying distribution of housing units. Using this comparison, it is possible to determine if LIHTC properties are more clustered than the average housing unit. Several analyses are performed, including a global clustering analysis, a local clustering analysis, a descriptive examination of the characteristics of clustered properties, and an analysis of space-time clustering, or “diffusion.”
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