Robust Stability of Monetary Policy Rules under Adaptive Learning

Recent research has explored how minor changes in expectation formation can change the stability properties of a model (Duffy and Xiao 2007, Evans and Honkapoja 2009). This paper builds on this research by examining an economy subject to a variety of monetary policy rules under an endogenous learning algorithm proposed by Marcet and Nicolini (2003). The results indicate that operational versions of optimal discretionary rules are not "robustly stable" as in Evans and Honkapoja (2009). In addition commitment rules are not robust to minor changes in expectational structure and parameter values.