Computing second-order-accurate solutions for rational expectation models using linear solution methods

Giovanni Lombardo; Alan  Sutherland

doi:10.1016/j.jedc.2005.10.004

Computing second-order-accurate solutions for rational expectation models using linear solution methods

Giovanni Lombardo
, Alan Sutherland

Research output: Contribution to journal › Article › peer-review

Abstract

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts. (C) 2006 Elsevier B.V. All rights reserved.

Original language	English
Pages (from-to)	515-530
Number of pages	16
Journal	Journal of Economic Dynamics and Control
Volume	31
Issue number	2
DOIs	https://doi.org/10.1016/j.jedc.2005.10.004
Publication status	Published - Feb 2007

Keywords

second-order approximation
solution methods for rational expectation models
POLICY

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title = "Computing second-order-accurate solutions for rational expectation models using linear solution methods",

abstract = "This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts. (C) 2006 Elsevier B.V. All rights reserved.",

keywords = "second-order approximation, solution methods for rational expectation models, POLICY",

author = "Giovanni Lombardo and Alan Sutherland",

year = "2007",

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AU - Lombardo, Giovanni

AU - Sutherland, Alan

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AB - This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts. (C) 2006 Elsevier B.V. All rights reserved.

KW - second-order approximation

KW - solution methods for rational expectation models

KW - POLICY

UR - https://www.scopus.com/pages/publications/33846303585

UR - http://www.sciencedirect.com/science/article/B6V85-4JFGF55-3/2/c342f0ce59a828bcb48e90ae36208b01

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DO - 10.1016/j.jedc.2005.10.004

M3 - Article

SN - 0165-1889

VL - 31

SP - 515

EP - 530

JO - Journal of Economic Dynamics and Control

JF - Journal of Economic Dynamics and Control

IS - 2

ER -

Computing second-order-accurate solutions for rational expectation models using linear solution methods

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Keywords

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