Using monthly panel data we solve and estimate, using maximum likelihood techniques, an explicitly dynamic model of criminal behavior where current criminal activity adversely affects future employment outcomes. This acts as 'dynamic deterrence' to crime: the threat of future adverse effects on employment payoffs when caught committing crimes reduces the incentive to commit them. We show that this dynamic deterrence effect is strong in the data. Hence, policies which weaken dynamic deterrence will be less effective in fighting crime. This suggests that prevention is more powerful than redemption since the latter weakens dynamic deterrence as anticipated future redemption allows criminals to look forward to negating the consequences of their crimes. Static models of criminal behavior neglect this and hence sole reliance on them can result in misleading policy analysis.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
8281.
Length: Date of creation: May 2001 Date of revision: Handle: RePEc:nbr:nberwo:8281
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Edward L. Glaeser & Bruce Sacerdote & Jose A. Scheinkman, 1995.
"Crime and Social Interactions,"
NBER Working Papers
5026, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
Ayse Imrohoroglu & Antonio Merlo & Peter Rupert, 2004.
"What Accounts For The Decline In Crime?,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(3), pages 707-729, 08.
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