Identification of DSGE models—The effect of higher-order approximation and pruning

Willi Mutschler

Journal of Economic Dynamics and Control, 2015, vol. 56, issue C, 34-54

Abstract: This paper shows how to check rank criteria for a local identification of nonlinear DSGE models, given higher-order approximations and pruning. This approach imposes additional restrictions on (higher-order) moments and polyspectra, which can be used to identify parameters that are unidentified in a first-order approximation. The identification procedures are demonstrated by means of the Kim (2003) and the An and Schorfheide (2007) models. Both models are identifiable with a second-order approximation. Furthermore, analytical derivatives of unconditional moments, cumulants and corresponding polyspectra up to fourth order are derived for the pruned state-space.

Keywords: Identification; Pruning; Higher-order moments; Cumulants; Polyspectra; Analytical derivatives (search for similar items in EconPapers)
JEL-codes: C10 C51 C52 E1 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Related works:
Working Paper: Identification of DSGE Models - the Effect of Higher-Order Approximation and Pruning (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:56:y:2015:i:c:p:34-54

DOI: 10.1016/j.jedc.2015.04.007

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