ABSTRACT Average inflation targeting (AIT) aims to stabilize inflation expectations by offsetting past deviations from target. However, ambiguity about the averaging window can complicate expectations formation and reduce policy effectiveness. This paper integrates AIT into a benchmark DSGE model, incorporating adaptive learning and a signal extraction problem to examine the trade‐offs between policy clarity and ambiguity. Results indicate that inflation is most stable and central bank losses are minimized when the averaging window is 5 years. However, the policy's success depends on transparency about the averaging window, as imperfect information about the averaging window leads to consistently worse outcomes. These findings provide insights into the design of monetary policy frameworks, particularly as central banks revisit their strategies.
James W. Dean (Wed,) studied this question.