Search Profiling with Partial Knowledge of Deterrence

Consider the choice of a profiling policy where decisions to search for evidence of crime may vary with observable covariates of the persons at risk of search. I pose a planning problem whose objective is to minimise the social cost of crime and search. The consequences of a search rule depend on the extent to which search deters crime. I study the planning problem when the planner has partial knowledge of deterrence. I show how the planner can eliminate dominated search rules and how he can use the minimax or minimax-regret criterion to choose an undominated rule.