A comparison and evaluation of some alternative solution methods to dynamics stochastic models

We compare and evaluate the performance of four widely used numerical solution methods to dynamic rational expectations stochastic models, in the context of optimal and nonoptimal Pareto settings using a wide variety of statistical measures and two sample sizes. We find that: (i.) differences betwee...

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Detalles Bibliográficos
Autor: Pérez García, Javier-José
Tipo de recurso: informe técnico
Fecha de publicación:1998
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/64210
Acceso en línea:https://hdl.handle.net/20.500.14352/64210
Access Level:acceso abierto
Palabra clave:Approximation
Simulation
Numerical methods.
Procesos estocásticos
1208.08 Procesos Estocásticos
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spelling A comparison and evaluation of some alternative solution methods to dynamics stochastic modelsPérez García, Javier-JoséApproximationSimulationNumerical methods.Procesos estocásticos1208.08 Procesos EstocásticosWe compare and evaluate the performance of four widely used numerical solution methods to dynamic rational expectations stochastic models, in the context of optimal and nonoptimal Pareto settings using a wide variety of statistical measures and two sample sizes. We find that: (i.) differences between methods do not necessarily increase with the complexity of the solved model (ii.) For all the example model economies we considered, a log-linear approximation behaves as well as a more complex to implernent finite element method. (iii.) Rejection of a particular solution method attending to the fulfilment of the rational expectation hypothesis is compatible with almost no differences between methods attending to other comparison criteria. (iv.) It is proper to consider 'large' sample sizes to check the properties of a particular solution.Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)Universidad Complutense de Madrid19981998-01-0119981998-01-01technical reporthttp://purl.org/coar/resource_type/c_18ghinfo:eu-repo/semantics/reportapplication/pdfhttps://hdl.handle.net/20.500.14352/64210reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución-NoComercial-CompartirIgual 3.0 Españahttps://creativecommons.org/licenses/by-nc-sa/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/642102026-06-02T12:44:21Z
dc.title.none.fl_str_mv A comparison and evaluation of some alternative solution methods to dynamics stochastic models
title A comparison and evaluation of some alternative solution methods to dynamics stochastic models
spellingShingle A comparison and evaluation of some alternative solution methods to dynamics stochastic models
Pérez García, Javier-José
Approximation
Simulation
Numerical methods.
Procesos estocásticos
1208.08 Procesos Estocásticos
title_short A comparison and evaluation of some alternative solution methods to dynamics stochastic models
title_full A comparison and evaluation of some alternative solution methods to dynamics stochastic models
title_fullStr A comparison and evaluation of some alternative solution methods to dynamics stochastic models
title_full_unstemmed A comparison and evaluation of some alternative solution methods to dynamics stochastic models
title_sort A comparison and evaluation of some alternative solution methods to dynamics stochastic models
dc.creator.none.fl_str_mv Pérez García, Javier-José
author Pérez García, Javier-José
author_facet Pérez García, Javier-José
author_role author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv Approximation
Simulation
Numerical methods.
Procesos estocásticos
1208.08 Procesos Estocásticos
topic Approximation
Simulation
Numerical methods.
Procesos estocásticos
1208.08 Procesos Estocásticos
description We compare and evaluate the performance of four widely used numerical solution methods to dynamic rational expectations stochastic models, in the context of optimal and nonoptimal Pareto settings using a wide variety of statistical measures and two sample sizes. We find that: (i.) differences between methods do not necessarily increase with the complexity of the solved model (ii.) For all the example model economies we considered, a log-linear approximation behaves as well as a more complex to implernent finite element method. (iii.) Rejection of a particular solution method attending to the fulfilment of the rational expectation hypothesis is compatible with almost no differences between methods attending to other comparison criteria. (iv.) It is proper to consider 'large' sample sizes to check the properties of a particular solution.
publishDate 1998
dc.date.none.fl_str_mv 1998
1998-01-01
1998
1998-01-01
dc.type.none.fl_str_mv technical report
http://purl.org/coar/resource_type/c_18gh
dc.type.openaire.fl_str_mv info:eu-repo/semantics/report
format report
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/64210
url https://hdl.handle.net/20.500.14352/64210
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-CompartirIgual 3.0 España
https://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución-NoComercial-CompartirIgual 3.0 España
https://creativecommons.org/licenses/by-nc-sa/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
publisher.none.fl_str_mv Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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