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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Bibliographic Details
Author: Pérez García, Javier-José
Format: report
Publication Date:1998
Country:España
Institution:Universidad Complutense de Madrid (UCM)
Repository:Docta Complutense
Language:English
OAI Identifier:oai:docta.ucm.es:20.500.14352/64210
Online Access:https://hdl.handle.net/20.500.14352/64210
Access Level:Open access
Keyword:Approximation
Simulation
Numerical methods.
Procesos estocásticos
1208.08 Procesos Estocásticos
Description
Summary: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.