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, 2006, and Giordani and
Soderlind, 2004). In this paper we show that the structural-form methods
developed by Dennis (2006) 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
statespace form. Interestingly, because state-space forms and structural forms
are not unique the two approaches do not necessarily return the same equilibria
for robust control problems. We apply both state-space and structural solution
methods to an empirical New Keynesian business cycle model and find that the
differences between the methods are both qualitatively and quantitatively important.
In particular, with the structural-form solution methods the specification errors generally
involve changes to the conditional variances in addition to theconditional means of the
shock processes.