ABOUT BOOK

We model criminal investigation as a principal-agent-monitor problem in which the agent can bribe the monitor to destroy evidence. Building on insights from Laffont and Martimort (1997) we study whether the principal can profitably introduce asymmetric information between agent and monitor by randomizing the monitor’s incentives. We show it can be the case, but the optimality of random incentives depends on unobserved pre-existing patterns of private information. We provide a data-driven framework for policy evaluation requiring only unverified reports. A potential local policy change is an improvement if, everything else equal, it is associated with greater reports of crime