The dynamics of deterrence The University of （大学的威慑的动力）.pdf

The dynamics of deterrence Mark Kleimana,1 and Beau Kilmerb aDepartment of Public Policy, University of California, 3250 Public Affairs Building, Los Angeles, CA 90095-1656; and bDrug Policy Research Center, RAND, 1776 Main Street, Santa Monica, CA 90407-2138 Communicated by Thomas C. Schelling, University of Maryland, College Park, College Park, MD, June 15, 2009 (received for review September 7, 2007) Because punishment is scarce, costly, and painful, optimal enforce- absolute number (not just the rate) of detected violations de- ment strategies will minimize the amount of actual punishment creased; the majority of those who received warnings never needed required to effectuate deterrence. If potential offenders are suffi- to be sanctioned at all (9).† ciently deterrable, increasing the conditional probability of punish- These observations help illustrate the potential interactions ment (given violation) can reduce the amount of punishment actually among 3 variables: The rate at which a rule is broken, the probability inflicted, by ‘‘tipping’’ a situation from its high-violation equilibrium that any given incident of rule-breaking leads to punishment, and to its low-violation equilibrium. Compared to random or ‘‘equal the total quantity of punishment actually administered. They can be opportunity’’ enforcement, dynamically concentrated sanctions can explained by a common-sense observation known to everyone who reduce the punishment level necessary to tip the system, especially if has successfully raised a child or trained a pet; holding sanction preceded by warnings. Game theory and some simple and robust intensity constant, the more credible the commitment to punish Monte Carlo simula