Tractable Likelihood-Based Estimation of Non-Linear DSGE Models

Robert Kollmann ()

No 12262, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: This paper presents a simple and fast maximum likelihood estimation method for non-linear DSGE models that are solved using a second- (or higher-) order accurate approximation. The method requires that the number of observables equals the number of exogenous shocks. Exogenous innovations are extracted recursively by inverting the observation equation, which allows easy computation of the likelihood function.

Keywords: Estimation of non-linear dsge models; Observation equation inversion (search for similar items in EconPapers)
JEL-codes: C51 C63 C68 E37 (search for similar items in EconPapers)
Date: 2017-08
New Economics Papers: this item is included in nep-ecm and nep-mac
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Tractable likelihood-based estimation of non-linear DSGE models (2017)
Working Paper: Tractable likelihood-based estimation of non- linear DSGE models (2017)
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