What do “balance-of-trade” models tell us about variation in supply and demand for stolen cars across city neighborhoods?

• In Event: WG-PLACE 3: Understanding and Preventing Auto Thefts

Abstract

In a typical year, around 20,000 cars are reported stolen in the City of Los Angeles. Around 60% of these stolen vehicles are eventually recovered, though often from locations far from the initial point of theft. This paper examines the spatial patterning in theft-recovery data for different make-models of cars using a “balance-of-trade” approach. In a closed world, each theft of a car from one neighborhood would be balanced by the recovery of that car from the same or some other neighborhood. The theft-recovery pattern thus should reflect the supply-and-demand relationships within and between neighborhoods. Specifically, some neighborhoods may be net “exporters” of stolen vehicles and other neighborhoods net “importers” of stolen vehicles. We explore whether neighborhoods spatially cluster into functional “exporting” or “importing” blocks. We also address whether theft-recovery patterns within and between neighborhoods vary across car make-models. Some car types may be almost always recovered when stolen, and others almost never recovered. The implications for countering both opportunistic and organized car theft are discussed.

Authors

• P. Jeffrey Brantingham, University of California Los Angeles

• Craig D. Uchida, Justice & Security Strategies, Inc.