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 ( 2007 ; 2009 ). This article builds on this research by examining an economy subject to a variety of monetary policy rules under an endogenous learning algorithm proposed by 2003 . The results indicate that operational versions of optimal discretionary rules are not robustly stable, as in 2009 . In addition, commitment rules are not robust to minor changes in expectational structure and parameter values.