This study examines the relationship between crime trajectories and housing prices at the micro-geographic level, focusing on street segments in Tel-Aviv-Yafo. It combines two analytic strategies: a quasi-experimental comparison of matched segments using group-based trajectory modeling, and multivariate ordinary least squares regressions predicting logged housing prices. In the quasi-experimental analysis, matched pairs of street segments from a typology of nine crime trajectory groups began with similar crime levels but diverged over time. Segments that experienced steeper increases in crime tended to show slower housing price appreciation. In the multivariate models, a 10-crime increase between 2005 and 2014 was associated with approximately 3–4% decline in price per square meter (2013–2016). These effects remained robust after adjusting for demographic, land-use, and built environment characteristics, and controlling for spatial dependence. The findings advance the criminology of place by showing that crime is a dynamic and spatially concentrated force with measurable economic consequences. From a policy perspective, targeted crime prevention in high-trajectory areas may enhance both public safety and property values.
Hagit et al. (Fri,) studied this question.