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Deterrence and Displacement in Auto Theft

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Author Info
Marco Gonzalez-Navarro (Princeton University)
Abstract

Lojack is a stolen vehicle tracking technology that achieves extremely high recovery rates. Ayres and Levitt (1998) show that introduction of the system produced large reductions in vehicle thefts in areas where it was implemented in the United States. The reduced theft risk was shared by all vehicle owners, not only those who bought Lojack. This paper, in contrast, uses the introduction of Lojack to a publicly known set of Ford car models in some Mexican states to show that Lojack generates negative externalities if thieves can distinguish between Lojack and non-Lojack-equipped cars. The empirical analysis suggests that, although Lojack-equipped vehicles experienced a reduction in theft risk of 55%, most of the averted thefts were replaced by thefts of non-Lojack-equipped automobiles in neighboring states. The increase in thefts in non Lojack-serviced states was especially strong for the same car models that in Lojack-serviced states were sold equipped with Lojack.

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Paper provided by Princeton University, Department of Economics, Center for Economic Policy Studies. in its series Working Papers with number 1098.

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Date of creation: Oct 2008
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Handle: RePEc:pri:cepsud:1098

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Find related papers by JEL classification:
K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies

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  1. Gary S. Becker, 1968. "Crime and Punishment: An Economic Approach," Journal of Political Economy, University of Chicago Press, vol. 76, pages 169. [Downloadable!] (restricted)
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  2. Camerer, Colin, et al, 1997. "Labor Supply of New York City Cabdrivers: One Day at a Time," The Quarterly Journal of Economics, MIT Press, vol. 112(2), pages 407-41, May.
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  3. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2006. "Robust Inference with Multi-way Clustering," NBER Technical Working Papers 0327, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  4. Edward Miguel & Michael Kremer, 2004. "Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities," Econometrica, Econometric Society, vol. 72(1), pages 159-217, 01. [Downloadable!] (restricted)
  5. Ian Ayres & Steven D. Levitt, 1998. "Measuring Positive Externalities From Unobservable Victim Precaution: An Empirical Analysis Of Lojack," The Quarterly Journal of Economics, MIT Press, vol. 113(1), pages 43-77, February. [Downloadable!] (restricted)
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