Methods for Robust Control

Robust control allows policymakers to formulate policies that guard against model misspecification. The principal tools used to solve robust control problems are state-space methods (see Hansen and Sargent 2008, and Giordani and Soderlind 2004). In this paper we show that the structural-form methods developed by Dennis (2007) to solve control problems with rational expectations can also be applied to robust control problems, with the advantage that they bypass the task, often onerous, of having to express the reference model in state-space form. In addition, we show how to implement two different timing assumptions with distinct implications for the robust policy and the economy. We apply our methods to a New Keynesian dynamic stochastic general equilibrium model and find that robustness has important effects on policy and the economy.