Estimation of DSGE Models with the Effective Lower Bound

54 Pages Posted: 27 Jun 2022

See all articles by Gregor Boehl

Gregor Boehl

University of Bonn

Felix Strobel

Deutsche Bundesbank

Date Written: June 16, 2022

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

JEL Classification: C11, C63, E31, E32, E44

Suggested Citation

Boehl, Gregor and Strobel, Felix, Estimation of DSGE Models with the Effective Lower Bound (June 16, 2022). Available at SSRN: https://ssrn.com/abstract=4138532 or http://dx.doi.org/10.2139/ssrn.4138532

Gregor Boehl (Contact Author)

University of Bonn ( email )

Adenauerallee 24-42
Bonn, D-53113
Germany

Felix Strobel

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

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