Adaptive learning and inflation persistence

What generates persistence in ination? Is ination persistence structural? This paper investigates learning as a potential source of persistence in ination. The paper focuses on the price-setting problem of \u85rms and presents a model that nests structural sources of persistence (indexation) and learning. Indexation is typically necessary under rational expectations to match the inertia in the data and to improve the \u85t of estimated New Keynesian Phillips curves. The empirical results show that when learning replaces the assumption of fully rational expectations, structural sources of persistence in ination, such as indexation, become unsupported by the data. The results suggest learning behavior as the main source of persistence in ination. This \u85nding has implications for the optimal monetary policy. The paper also shows how ones results can heavily depend on the assumed learning speed. The estimated persistence and the model \u85t, in fact, vary across the whole range of constant gain values. The paper derives the best-\u85tting constant gains in the sample and shows that the learning speed has substantially changed over time