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Rational Expectations for Large Models: A Practical Algorithm and a Policy Application

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  • Peter B. Dixon
  • K.R. Pearson
  • Mark R. Picton
  • Maureen T. 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.

Suggested Citation

  • Peter B. Dixon & K.R. Pearson & Mark R. Picton & Maureen T. Rimmer, 2002. "Rational Expectations for Large Models: A Practical Algorithm and a Policy Application," Centre of Policy Studies/IMPACT Centre Working Papers ip-81, Victoria University, Centre of Policy Studies/IMPACT Centre.
    • Handle: RePEc:cop:wpaper:ip-81
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    References listed on IDEAS

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    1. David Lipton & James M. Poterba & Jeffrey Sachs & Lawrence H. Summers, 1983. "Multiple Shooting in Rational Expectations Models," NBER Technical Working Papers 0003, National Bureau of Economic Research, Inc.
    2. Bovenberg, A.L., 1985. "A dynamic general equilibrium model with adjustment cost," Other publications TiSEM e4c132f1-4c01-42df-890b-6, Tilburg University, School of Economics and Management.
    3. repec:bla:ecorec:v:74:y:1998:i:225:p:121-38 is not listed on IDEAS
    4. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-1185, July.
    5. Fair, Ray C, 1979. "An Analysis of a Macro-Econometric Model with Rational Expectations in the Bond and Stock Markets," American Economic Review, American Economic Association, vol. 69(4), pages 539-552, September.
    6. Michael Malakellis, 1998. "Should Tariff Reductions be Announced? An Intertemporal Computable General Equilibrium Analysis," The Economic Record, The Economic Society of Australia, vol. 74(225), pages 121-138, June.
    7. Arvind Panagariya, 1994. "East Asia and the New Regionalism in World Trade," The World Economy, Wiley Blackwell, vol. 17(6), pages 817-839, November.
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    Cited by:

    1. Jill Harrison & Glyn Wittwer, 2003. "RunMONASH: Automating A Dynamic, Recursive CGE Model," Centre of Policy Studies/IMPACT Centre Working Papers c14, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Dixon, Peter B. & Pearson, K.R. & Picton, Mark R. & Rimmer, Maureen T., 2005. "Rational expectations for large CGE models: A practical algorithm and a policy application," Economic Modelling, Elsevier, vol. 22(6), pages 1001-1019, December.
    3. Emini, Christian Arnault & Cockburn, John & Decaluwe, Bernard, 2005. "The poverty impacts of the Doha Round in Cameroon : the role of tax policy," Policy Research Working Paper Series 3746, The World Bank.

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    Keywords

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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