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Neighborhood Sorting Dynamics in Real Estate: Evidence from the Virginia Sex Offender Registry

Given the potential risk of recidivism, recent real estate research has found that registered sex offenders impose external costs, which are capitalized into the value and liquidity of nearby residential real estate. Several studies have shown that registered sex offenders lower nearby residential home prices significantly, in addition to lengthening time on market. These negative externalities might have lower overall costs to society if they were concentrated, or clustered, in particular areas. We demonstrate that, in theory, individuals operating within the market will sort according to their preferences and incentives, resulting in segmentation of these two groups (i.e. sex offenders vs. general populace). We predict that over time, neighborhoods will “tip” one way or another as part of the market process, resulting in clustering of registered sex offenders and segregation of these two groups. Further, we test this prediction empirically and its implications for the real estate market using GIS and other statistical/econometric techniques, exploiting a data set from Virginia that includes more than a decade of real estate transactions and a unique data set of registered sex offenders provided by the Virginia State Police. This research may help real estate academics and practitioners understand residential sorting dynamics with respect to registered sex offenders as well as the implications for the real estate market more generally.