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Reaching the planners: Generating detailed commodity Forecasts from a computable general equilibrium model


  • Philip D. Adams
  • Peter B.Dixon


The largest computable general equilibrium (CGE) models currently in operation produce forecasts for about 100 commodities (goods and services). This level of detail may seem overwhelming to macroeconomists, but is often inadequate for micro planning. For example, a forecast for business services (a typical commodity at the 100-level) is of marginal interest in planning educational programs for sub-categories of business services such as accountancy, advertising and architecture. As a step towards generating information for micro planning, this paper describes a top-down method for disaggregating CGE forecasts. The method relies on detailed sales data often collected by input-output sections of statistical agencies. An application is reported in which forecasts from a 114-commodity CGE model are disaggregated into forecasts for 780 commodities. Within each of the 114 core commodities, differences in prospects are forecast for sub-commodities reflecting differences in their sales patterns and in the degree to which they face import competition.

Suggested Citation

  • Philip D. Adams & Peter B.Dixon, 1996. "Reaching the planners: Generating detailed commodity Forecasts from a computable general equilibrium model," Centre of Policy Studies/IMPACT Centre Working Papers op-83, Victoria University, Centre of Policy Studies/IMPACT Centre.
  • Handle: RePEc:cop:wpaper:op-83

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    References listed on IDEAS

    1. Adams, Philip D. & Dixon, Peter B. & McDonald, Daina & Meagher, G. A. & Parmenter, Brian R., 1994. "Forecasts for the Australian economy using the MONASH model," International Journal of Forecasting, Elsevier, vol. 10(4), pages 557-571, December.
    2. Powell, Alan A. & Snape, Richard H., 1993. "The contribution of applied general equilibrium analysis to policy reform in Australia," Journal of Policy Modeling, Elsevier, vol. 15(4), pages 393-414, August.
    3. Robinson, Sherman, 1991. "Macroeconomics, financial variables, and computable general equilibrium models," World Development, Elsevier, vol. 19(11), pages 1509-1525, November.
    4. Robinson, Sherman, 1989. "Multisectoral models," Handbook of Development Economics,in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 2, chapter 18, pages 885-947 Elsevier.
    5. Bandara, Jayatilleke S, 1991. " Computable General Equilibrium Models for Development Policy Analysis in LDCs," Journal of Economic Surveys, Wiley Blackwell, vol. 5(1), pages 3-69.
    6. Shoven, John B & Whalley, John, 1984. "Applied General-Equilibrium Models of Taxation and International Trade: An Introduction and Survey," Journal of Economic Literature, American Economic Association, vol. 22(3), pages 1007-1051, September.
    7. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
    8. Pereira, Alfredo M. & Shoven, John B., 1988. "Survey of dynamic computational general equilibrium models for tax policy evaluation," Journal of Policy Modeling, Elsevier, vol. 10(3), pages 401-436.
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    More about this item

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods


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