Misspecification and Expectations Correction in New Keynesian DSGE Models

Giovanni Angelini and Luca Fanelli ()

No 1, Quaderni di Dipartimento from Department of Statistics, University of Bologna

Abstract: This paper focuses on the dynamic misspecification that characterizes the class of small-scale New-Keynesian models and provides a `natural' remedy for the typical difficulties these models have in accounting for the rich contemporaneous and dynamic correlation structure of the data, generally faced with ad hoc shock specifications. We suggest using the `best fitting' statistical model for the data as a device through which it is possible to adapt the econometric specification of the New-Keynesian model. The statistical model may feature an autocorrelation structure that is more involved than the autocorrelation structure implied by the structural model's reduced form solution under rational expectations, and it is treated as the actual agents' expectations generating mechanism. A pseudo-structural form is built from the baseline system of Euler equations by forcing the state vector of the system to have the same dimension as the state vector characterizing the statistical model. We provide an empirical illustration based on U.S. quarterly data and a small-scale monetary New Keynesian model.

Keywords: Dynamic stochastic general equilibrium model; Expectations; Kalman filter; New Keynesian models; State space model. (search for similar items in EconPapers)
Pages: 34
Date: 2015
New Economics Papers: this item is included in nep-dge and nep-ecm
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Misspecification and Expectations Correction in New Keynesian DSGE Models (2016)
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