TY  - UNPD
A1  - Farkas, Mátyás
A1  - Tatar, Balint
T1  - Bayesian estimation of DSGE models with Hamiltonian Monte Carlo
T2  - Working paper series / Institute for Monetary and Financial Stability ; 144 [August 31, 2020]
N2  - 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 confirm 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.
T3  - Working paper series / Institute for Monetary and Financial Stability - 144 [v. 31.08.2020] 
KW  - DSGE Estimation
KW  - Bayesian Analysis
KW  - Hamiltonian Monte Carlo
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/55470
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-554705
UR  - https://www.imfs-frankfurt.de/fileadmin/user_upload/IMFS_WP/IMFS_WP_144.pdf
N1  - Aktuellere Version: http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hebis:30:3-554818
PB  - Johann Wolfgang Goethe-Univ., Inst. for Monetary and Financial Stability
CY  - Frankfurt am Main
ER  -