Resource Center

Advanced Search
Technical Papers
Working Papers
Research Memoranda
GTAP-L Mailing List
GTAP FAQs
Educational Materials
CGE Books/Articles
Important References
Submit New Resource

GTAP Resources: Resource Display

GTAP Resource #1251

"Rational Expectations for Large Models : a Practical Algorithm and a Policy Application"
by Dixon, Peter, Ken Pearson, Mark Picton and Maureen Rimmer


Abstract
This paper describes a practical and conceptually simple iterative method for solving large dynamic CGE models under rational expectations. Details are given for the MONASH model of Australia but the general approach could be applied to a wide range of dynamic models. The method has been automated in the RunMONASH Windows software. This software provided a natural starting point for developing an automated procedure for conducting policy analysis under rational expectations because it already performed this function for static expectations. RunMONASH was also convenient because it incorporates comprehensive user-friendly data- and solution-interrogation facilities. We provide an illustrative application in which MONASH results obtained under rational expectations for the effects of motor vehicle tariff cuts are compared with results obtained under static expectations.


Resource Details (Export Citation) GTAP Keywords
Category: 2003 Conference Paper
Status: Published
By/In: Presented at the 6th Annual Conference on Global Economic Analysis, The Hague, The Netherlands
Date: 2003
Version:
Created: Pearson, K. (4/29/2003)
Updated: Bacou, M. (4/30/2003)
Visits: 2,466
- Calibration and parameter estimation


Attachments
If you have trouble accessing any of the attachments below due to disability, please contact the authors listed above.


Public Access
  File format PDF Version   (137.7 KB)   Replicated: 0 time(s)


Restricted Access
No documents have been attached.


Special Instructions
No instructions have been specified.


Comments (0 posted)
You must log in before entering comments.

No comments have been posted.