Evaluating the New Keynesian Phillips Curve under VAR-based learning

This paper proposes the evaluation of the New Keynesian Phillips Curve (NKPC) under a new learning mechanism where VAR learning dynamics is combined with the idea of testing the validity of the forward-looking model of inflation dynamics. The key assumption is that agents’ perceived law of motion is a VAR whose parameters are updated by recursive least squares. Differently from standard adaptive learning methods, agents test sequentially the cross-equation restrictions that the NKPC imposes on the VAR as the information set increases. When the restrictions are not rejected agents learn under the restricted system and exploit the cross-equation restrictions to forecast inflation. It is thus possible to check how much and in which periods agents’ beliefs are consistent with the restrictions of the theory. The empirical analysis on quarterly data on the euro area shows that the NKPC with negligible backward-looking parameter is not rejected when the model is evaluated over the period 1984-2005 under the proposed learning mechanism. The result, however, is not fully robust to specifications based on non stationary variables and points out that learning may represent a remarkable source of euro area inflation persistence but not its only determinant.