Munich Personal RePEc Archive

Dynamic law enforcement with learning

Jellal, Mohamed and Garoupa, Nuno (2004): Dynamic law enforcement with learning. Published in: Journal of Law Economics and Organization , Vol. Vol 20, No. Issue 1: 192-206


Download (301kB) | Preview


This paper modifies a standard model of law enforcement to allow for learning by doing. We incorporate the process of enforcement learning by assuming that the agency’s current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime) enhancing the ability of future apprehension at a lower marginal cost. We focus on the impact of enforcement learning on optimal compliance rules. In particular, we show that the optimal fine could be less than maximal and the optimal probability of detection could be higher than otherwise. It is also suggested that the optimal imprisonment sentence could be higher than otherwise.

Logo of the University Library LMU Munich
MPRA is a RePEc service hosted by
the University Library LMU Munich in Germany.