Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/223402 
Year of Publication: 
2020
Series/Report no.: 
IMFS Working Paper Series No. 144
Publisher: 
Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), Frankfurt a. M.
Abstract: 
In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and sampling diagnostics con firm the parameter estimates available in existing literature. In addition we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm which permits the estimation of DSGE models with ill-behaved posterior densities.
Subjects: 
DSGE Estimation
Bayesian Analysis
Hamiltonian Monte Carlo
JEL: 
C11
C15
E10
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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