DP19695 "If You Only Have a Hammer": Optimal Dynamic Prevention Policy
We study the gains of improving forecasting for a policymaker who faces a recurring risk and has the choice between preventive early actions and de-escalating late actions. We build a Markov model where early and late interventions are the solution to an optimal stopping problems and the timing of intervention depends on the ability to forecast future states. We then study the role of forecasting for optimal armed conflict prevention in a model which is estimated using a large cross-country panel. Prevention benefits are substantial but critically depend on the systematic use of forecasting. The information rent of using a forecast is larger than 60\% of GDP. In line with the theory we find that de-escalation policies reduce the incentives for prevention, whereas prevention increases incentives for de-escalation.
