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2008-04-25Buch DOI: 10.18452/4126
JBendge
dc.contributor.authorWinschel, Viktor
dc.contributor.authorKrätzig, Markus
dc.date.accessioned2017-06-15T23:42:24Z
dc.date.available2017-06-15T23:42:24Z
dc.date.created2008-05-22
dc.date.issued2008-04-25
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4778
dc.description.abstractWe present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The imple- mented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a function iterator using a multivariate global Chebyshev polynomial approximation with the Smolyak op- erator to overcome the course of dimensionality. The operator is also useful for numerical integration and we use it for the integrals arising in rational expecta- tions and in nonlinear state space filters. The estimation step is done by a parallel Metropolis-Hastings (MH) algorithm, using a linear or nonlinear filter. Implemented are the Kalman, Extended Kalman, Particle, Smolyak Kalman, Smolyak Sum, and Smolyak Kalman Particle filters. The MH sampling step can be interactively moni- tored and controlled by sequence and statistics plots. The number of parallel threads can be adjusted to benefit from multiprocessor environments. JBendge is based on the framework JStatCom, which provides a standardized ap- plication interface. All tasks are supported by an elaborate multi-threaded graphical user interface (GUI) with project management and data handling facilities.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectDynamic Stochastic General Equilibrium (DSGE) Modelseng
dc.subjectBayesian Time Series Econometricseng
dc.subjectJavaeng
dc.subjectSoftware Developmenteng
dc.subject.ddc330 Wirtschaft
dc.titleJBendge
dc.typebook
dc.subtitleAn Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models
dc.identifier.urnurn:nbn:de:kobv:11-10088581
dc.identifier.doihttp://dx.doi.org/10.18452/4126
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages38
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2008
local.edoc.container-issue34
local.edoc.container-year2008
local.edoc.container-erstkatid2195055-6

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