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Forecasting and Policy Analysis with a Dynamic CGE Model of Australia


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  • Peter B. Dixon
  • Maureen T. Rimmer


The main ideas in this paper are: (a) that CGE models can be used in forecasting; and (b) that forecasts matter for policy analysis. We demonstrate these ideas by describing an application of MONASH, a dynamic CGE model of Australia, to the Australian motor vehicle industry over the period 1987 to 2016. The key to generating believable forecasts is to use detailed information available from expert groups specializing in the analysis of different aspects of the economy. In MONASH we incorporate forecasts by specialists: on the domestic macro economy; on Australian economic policy; on world commodity markets; on international tourism; on production technologies; and on consumer preferences. We have found that CGE forecasts incorporating such specialist information are readily saleable to public and private organizations concerned with investment, employment, training and education issues. This is partly because the economy-wide consistency guaranteed by the CGE approach enables users of economic intelligence to see the disparate forecasts dealing with different parts and aspects of the economy within an integrated perspective. Over the last thirty five years, CGE models have been used almost exclusively as aids to "what if" (usually policy) analysis. In almost all cases it has been assumed that the effects of the shock under consideration are independent of the future path of the economy. Thus, for "what if" analysis, a common implicit view is that realistic basecase forecasts are unnecessary. Contrary to this view, we find that "what if" answers depend significantly on the basecase forecasts. This is not surprising when we are concerned with unemployment and other adjustment costs. However, we find that basecase forecasts are critical even when our concern is the long-run welfare implications of a policy change. For example, we find that the simulated long-run effects of a tariff cut on imported cars are strongly influenced by the basecase forecast of the rate of technical progress in the car industry relative to that in other industries.

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Bibliographic Info

Paper provided by Victoria University, Centre of Policy Studies/IMPACT Centre in its series Centre of Policy Studies/IMPACT Centre Working Papers with number op-90.

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Date of creation: Jun 1998
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Handle: RePEc:cop:wpaper:op-90

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Keywords: CGE model; forecasting; policy analysis; MONASH model; automobile industry; adjustment costs;

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  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.
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Cited by:
  1. W. Jill Harrison & J. Mark Horridge & K.R. Pearson, 1999. "Decomposing Simulation Results with Respect to Exogenous Shocks," Centre of Policy Studies/IMPACT Centre Working Papers ip-73, Victoria University, Centre of Policy Studies/IMPACT Centre.
  2. Graafland, Johan J. & de Mooij, Ruud A., 1999. "Fiscal policy and the labour market: An AGE analysis," Economic Modelling, Elsevier, vol. 16(2), pages 189-219, April.
  3. Wittwer, Glyn, 2000. "The Sensitivity Of Wine Industry Outcomes To Model Assumptions In Gst Scenarios," 2000 Conference (44th), January 23-25, 2000, Sydney, Australia 123742, Australian Agricultural and Resource Economics Society.
  4. Eduardo Haddad & Geoffrey Hewings, 2004. "Transportation Costs, Increasing Returns and Regional Growth: An Interregional CGE Analysis," ERSA conference papers ersa04p461, European Regional Science Association.
  5. Edson Paulo Domingues & Kênia Barreiro de Souza, 2012. "The Welfare Impacts of Changes in the Brazilian Domestic Work Market," One Pager 180, International Policy Centre for Inclusive Growth.


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