Estimation of DSGE Models With the Effective Lower Bound

Felix Strobel

CRC TR 224 Discussion Paper Series from University of Bonn and University of Mannheim, Germany

Abstract: We propose a set of tools for the efficient and robust Bayesian estimation of medium- and large-scale DSGE models while accounting for the effective lower bound on nominal interest rates. We combine a novel nonlinear recursive filter with a computationally efficient piece-wise linear solution method and a state-of-the-art MCMC sampler. The filter allows for fast likelihood approximations, in particular of models with large state spaces. Using artificial data, we demonstrate that our methods accurately capture the true model parameters even with very long lower bound episodes. We apply our approach to analyze post-2008 US business cycle properties.

Keywords: Effective Lower Bound; Bayesian Estimation; Great Recession; Business Cycles (search for similar items in EconPapers)
JEL-codes: C11 C63 E31 E32 E44 (search for similar items in EconPapers)
Pages: 54
Date: 2022-06
New Economics Papers: this item is included in nep-dge, nep-ecm and nep-ets
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.crctr224.de/research/discussion-papers/archive/dp356 (application/pdf)

Related works:
Journal Article: Estimation of DSGE models with the effective lower bound (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bon:boncrc:crctr224_2022_356

Access Statistics for this paper

More papers in CRC TR 224 Discussion Paper Series from University of Bonn and University of Mannheim, Germany Kaiserstr. 1, 53113 Bonn , Germany.
Bibliographic data for series maintained by CRC Office ().