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State-level Dynamic CGE Modeling for Forecasting and Policy Analysis

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  • Peter B. Dixon
  • Maureen T. Rimmer

Abstract

In computable general equilibrium (CGE) modeling there are two broad approaches to generating regional results: bottoms-up and tops-down. We describe both, providing illustrative examples from our experience in Australia. We then describe USAGE, a 500-order dynamic CGE model of the US that we are developing in collaboration with the US International Trade Commission. Tops-down State results from USAGE will be available in a relatively short time. With a longer time horizon, it will be possible to create a bottoms-up version of USAGE. Tops-down applications will be adequate for analysis of economy-wide shocks such as changes in Federal policies. Bottoms-up modeling will be required for analysis of shocks in which the essence is a change in relative costs across regions.

Suggested Citation

  • Peter B. Dixon & Maureen T. Rimmer, 2003. "State-level Dynamic CGE Modeling for Forecasting and Policy Analysis," Centre of Policy Studies/IMPACT Centre Working Papers ip-82, Victoria University, Centre of Policy Studies/IMPACT Centre.
    • Handle: RePEc:cop:wpaper:ip-82
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    References listed on IDEAS

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    1. Dixon, P.B. & Parmenter, B.R. & Sutton, J., 1978. "Spatial Disaggregation of Orani Results: A Preliminary Analysis of the Impact of Protection at the State Level," Economic Analysis and Policy, Elsevier, vol. 8(1), pages 35-86.
    2. Liew, L. H., 1984. ""Tops-down" versus "bottoms-up" approaches to regional modeling," Journal of Policy Modeling, Elsevier, vol. 6(3), pages 351-367, August.
    3. Naqvi, Farzana & Peter, Matthew W, 1996. "A Multiregional, Multisectoral Model of the Australian Economy with an Illustrative Application," Australian Economic Papers, Wiley Blackwell, vol. 35(66), pages 94-113, June.
    4. Dixon, Peter B & Madden, John R & Peter, Matthew W, 1993. "The Effects of Reallocating General Revenue Assistance among the Australian States," The Economic Record, The Economic Society of Australia, vol. 69(207), pages 367-381, December.
    5. Glyn Wittwer & Peter Dixon, 2004. "Forecasting the Economic impact of an industrial stoppage using a dynamic, computable general equilibrium model," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 7(1), pages 39-51, March.
    6. Peter B. Dixon & John R. Madden & Matthew W. Peter, 1993. "The Effects of Reallocating General Revenue Assistance among the Australian States," The Economic Record, The Economic Society of Australia, vol. 69(4), pages 367-381, December.
    7. Hertel, Thomas, 1997. "Global Trade Analysis: Modeling and applications," GTAP Books, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, number 7685, December.
    8. Robert E. Litan & Alice M. Rivlin, 2001. "Projecting the Economic Impact of the Internet," American Economic Review, American Economic Association, vol. 91(2), pages 313-317, May.
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    Cited by:

    1. Rodriguez, U-Primo E., 2007. "State-of-the-Art in Regional Computable General Equilibrium Modelling with a Case Study of the Philippines," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 20(1).
    2. Glyn Wittwer & Simon McKirdy & Ryan Wilson, 2003. "Analysing the Economic Impacts of a Plant Disease Incursion Using a General Equilibrium Approach," Centre of Policy Studies/IMPACT Centre Working Papers op-97, Victoria University, Centre of Policy Studies/IMPACT Centre.

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    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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