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A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous?

Milani, Fabio (2006): A Bayesian DSGE Model with Infinite-Horizon Learning: Do "Mechanical" Sources of Persistence Become Superfluous? Published in: International Journal of Central Banking , Vol. Volume, No. Number 3 (14. September 2006): pp. 87-106.

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Abstract

This paper estimates a monetary DSGE model with learning introduced from the primitive assumptions. The model nests infinite-horizon learning and features, such as habit formation in consumption and inflation indexation, that are essential for the model fit under rational expectations. I estimate the DSGE model by Bayesian methods, obtaining estimates of the main learning parameter, the constant gain, jointly with the deep parameters of the economy. The results show that relaxing the assumption of rational expectations in favor of learning may render mechanical sources of persistence superfluous. In particular, learning appears to be a crucial determinant of inflation inertia.

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