Arbeitspapier

Adaptive hybrid Metropolis-Hastings samplers for DSGE models

Bayesian inference for DSGE models is typically carried out by single block random walk Metropolis, involving very high computing costs. This paper combines two features, adaptive independent Metropolis-Hastings and parallelisation, to achieve large computational gains in DSGE model estimation. The history of the draws is used to continuously improve a t-copula proposal distribution, and an adaptive random walk step is inserted at predetermined intervals to escape difficult points. In linear estimation applications to a medium scale (23 parameters) and a large scale (51 parameters) DSGE model, the computing time per independent draw is reduced by 85% and 65-75% respectively. In a stylised nonlinear estimation example (13 parameters) the reduction is 80%. The sampler is also better suited to parallelisation than random walk Metropolis or blocking strategies, so that the effective computational gains, i.e. the reduction in wall-clock time per independent equivalent draw, can potentially be much larger.

Sprache
Englisch

Erschienen in
Series: SSE/EFI Working Paper Series in Economics and Finance ; No. 724

Klassifikation
Wirtschaft
Bayesian Analysis: General
Computational Techniques; Simulation Modeling
Thema
Markov Chain Monte Carlo (MCMC)
Adaptive Metropolis-Hastings
Parallel algorithm
DSGE model
Copula
Dynamisches Gleichgewicht
Markovscher Prozess
Monte-Carlo-Methode
Algorithmus
Kopula (Mathematik)
Theorie

Ereignis
Geistige Schöpfung
(wer)
Strid, Ingvar
Giordani, Paolo
Kohn, Robert
Ereignis
Veröffentlichung
(wer)
Stockholm School of Economics, The Economic Research Institute (EFI)
(wo)
Stockholm
(wann)
2010

Handle
Letzte Aktualisierung
10.03.2025, 11:46 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Strid, Ingvar
  • Giordani, Paolo
  • Kohn, Robert
  • Stockholm School of Economics, The Economic Research Institute (EFI)

Entstanden

  • 2010

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