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Using a highly disaggregated multi-regional single-country model to analyse the impacts of the 2002-03 drought on Australia


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  • Mark Horridge
  • John Madden
  • Glyn Wittwer


TERM (The Enormous Regional Model) is a "bottom-up" CGE model of Australia which treats each region as a separate economy. TERM was created specifically to deal with highly disag-gregated regional data while providing a quick solution to simulations. This makes it a useful tool for examining the regional impacts of shocks that may be region-specific. We include some details of how we prepared the TERM database, using a national input-output table, together with regional data showing output (for agriculture) and employment (in other sectors) for each of 144 sectors and 57 regions [the Australian statistical divisions]. Using a 38-sector, 45-region aggregation of the model, we simulate the short-run effects of the Australian drought of 2002-03, which was the most widespread for 20 years. The effects on some statistical divisions are extreme, with income losses of up to 20 per cent. Despite the relatively small share of agriculture in Australian GDP, the drought reduces GDP by 1.6 per cent, and contributes to a decline in unemployment and to a worsening of the balance of trade.

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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 g-141.

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Date of creation: Oct 2003
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Publication status: Published in Journal of Policy Modeling, Vol 27/3 2005, pp. 285-308.
Handle: RePEc:cop:wpaper:g-141

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  1. Pearson, K. R., 1988. "Automating the computation of solutions of large economic models," Economic Modelling, Elsevier, Elsevier, vol. 5(4), pages 385-395, October.
  2. Naqvi, Farzana & Peter, Matthew W, 1996. "A Multiregional, Multisectoral Model of the Australian Economy with an Illustrative Application," Australian Economic Papers, Wiley Blackwell, Wiley Blackwell, vol. 35(66), pages 94-113, June.
  3. Philip D. Adams & Mark Horridge & Glyn Wittwer, 2003. "MMRF-GREEN: A Dynamic Multi-Regional Applied General Equilibrium Model of the Australian Economy, Based on the MMR and MONASH Models," Centre of Policy Studies/IMPACT Centre Working Papers, Victoria University, Centre of Policy Studies/IMPACT Centre g-140, Victoria University, Centre of Policy Studies/IMPACT Centre.
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Cited by:
  1. Productivity Commission, 2008. "Modelling Economy-wide Effects of Future Automotive Assistance," Research Reports, Productivity Commission, Government of Australia, Productivity Commission, Government of Australia, number 30.
  2. Wittwer, Glyn & Griffith, Marnie, 2010. "Closing the factory doors until better times: CGE modelling of drought using a theory of excess capacity," 2010 Conference (54th), February 10-12, 2010, Adelaide, Australia, Australian Agricultural and Resource Economics Society 59263, Australian Agricultural and Resource Economics Society.
  3. Horridge, Mark & Wittwer, Glyn, 2008. "SinoTERM, a multi-regional CGE model of China," China Economic Review, Elsevier, Elsevier, vol. 19(4), pages 628-634, December.
  4. Marcos Minoru Hasegawa, 2010. "The Tax Policy in the Chilean Economy: a Regional Applied General Equilibrium Analysis," Documentos de Trabajo en Economia y Ciencia Regional, Universidad Catolica del Norte, Chile, Department of Economics 05, Universidad Catolica del Norte, Chile, Department of Economics, revised Dec 2010.
  5. Andrew Leigh, 2009. "Precipitation, Profits, and Pile-Ups," CEPR Discussion Papers, Centre for Economic Policy Research, Research School of Economics, Australian National University 629, Centre for Economic Policy Research, Research School of Economics, Australian National University.
  6. Wittwer, Glyn & McKirdy, Simon & Wilson, Ryan, 2005. "Regional economic impacts of a plant disease incursion using a general equilibrium approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, Australian Agricultural and Resource Economics Society, vol. 49(1), March.


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